GROWING OLD IN JAMAICA

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GROWING OLD IN JAMAICA:   Population
Ageing and Senior Citizens’ Wellbeing




       Paul Andrew Bourne
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  GROWING OLD IN JAMAICA:   Population
  Ageing and Senior Citizens’ Wellbeing




                                     By




                Paul Andrew Bourne
Health Research Scientist, the University of the West Indies,
                     Mona Campus




Department of Community Health and Psychiatry
Faculty of Medical Sciences
The University of the West Indies, Mona Campus, Kingston, Jamaica.
                                                                                3


© Paul Andrew Bourne 2009




Growing Old in Jamaica: Population Ageing and Senior Citizens’ Wellbeing




While the copyright of this text is vested in Paul Andrew Bourne, the Department
of Community Health and Psychiatry is the publisher and no parts of the chapters
may be reproduced wholly or in part without the express permission in writing of
both author and publisher.



All rights reserved. Published April, 2009


Department of Community Health and Psychiatry
Faculty of Medical Sciences
The University of the West Indies, Mona Campus, Kingston, Jamaica.



National Library of Jamaica Cataloguing in Publication data

A catalogue record for this book is available from the National Library of Jamaica

ISBN 978 976 41 0232 8 (pbk)




Covers were designed by Paul Andrew Bourne and Evadney Delores Bourne
                          4




         This book


            Is


       Dedicated
           To


 All Elderly Jamaicans

          And

The Prospective Elderly
                                                                                 5


     Acknowledgement

This book was born out of (1) my Master of Science thesis in Demography, which

examined ‘Determinants of Wellbeing of the Jamaican Elderly’; (2) an interest in

the health status of older people within the context of the current economic

downturn in the global economy; and (3) a desire to apply econometric analysis to

the study of the health status of the elderly.

        I have started on many occasions to fulfil this task, but I was overwhelmed

by the daunting challenge of investigating matters of the elderly – and though I

am not one to complain of the difficulty presented by a task or to be fearful of a

voluminous workload, I found it problematic to rework material that has already

been in existence for some time.

        Upon pursuing the Doctor of Philosophy (PhD.) in Public Health, where

my dissertation speaks to the: Quality of Life over the Life Course, I was once

again challenged to embark on the project. Ergo, I felt that I would have betrayed

the academy if this project was not made available to the world. The project is

now finalized and there are several people who started the journey with me from

the Master of Science degree to the final completed manuscript.

        I wish to take this opportunity to thank a number of persons who have

made this task a reality. Firstly, my past Supervisor for the Master of Science

Degree, Ms. Sharon Priestley, and co-Supervisors Mr. Julian Devonish,

Professors C. Uche, Patricia Anderson and Professor Anthony Harriott, from the

University of the West Indies, Mona for their advice, support and reading of the

Master of Science manuscript.
                                                                               6


        In extending gratitude to Ms. Norma Davis, Assistant Librarian at the Sir

Arthur Lewis Institute, UWI, Mona, Jamaica, who dedicated quality time to

correcting and proofreading my reference, I wish to postulate that although words

are powerful, yet they are not enough to express my heart-felt appreciation for a

task so well done without requesting any form of remuneration.    I wish to also

express appreciation to other persons who were instrumental in adding some other

form of assistance; namely: Mr. Maxwell “Bunny” Williams, Ms. Thorna Smith,

Mrs. Janet Higgins, and Mrs. Audrey Chambers (recently deceased). I miss you

Mrs. Chambers – you have left me disliking the socio-physiological reality of

death; but our meeting has transformed a normal life into a meaningful one.

        In terms of proofreading, critique, moral support, insightfulness, and

commitment, I hereby extend sincere appreciation to Drs. Samuel ‘Sam’

McDaniel and I. Solan of the Department of Mathematics, the University of the

West Indies, Mona, Kingston; and Orville Beckford, lecturer in the Department of

Sociology, Psychology and Social Work, at the University of the West Indies,

Mona.
                                                                           7


                           TABLE OF CONTENTS


                                                                Page
Dedication                                                        i

Acknowledgements                                                     ii

List of Tables                                                       vii

List of Figures                                                      x

Chapter One                                                           1

       Introduction

       Survey

Chapter Two                                                     14

       Ageing Transition

Chapter Three                                                        28

       Population Ageing: Historical and Global


Chapter Four                                                         42

       Population Ageing: Caribbean Demographic Trends
       With Emphasis on Jamaica

Chapter Five                                                         60

       An Overview of the Conceptual Perspective on Wellbeing
       of the Elderly: Part One

Chapter Six                                                          67

       An Overview of the Conceptual Perspective on Wellbeing
       of the Elderly: Part Two

Chapter Seven                                                        88
      An Overview of the Conceptual Perspective on Wellbeing
       of the Elderly: Part Three
                                                            8


Chapter Eight                                         136
      Modelling Wellbeing

Chapter Nine                                          146

      Findings: Sociodemographic Characteristics of
      Sampled Population

Chapter Ten                                           166

      Findings: Multivariate Analysis

Chapter Eleven                                        179

      Epilogue

Glossary                                              214

Analytic Model of Wellbeing                           217

Reference                                             222
                                                                                 9


Appendices                                                         144

Appendix I. Table 2.1.1: Average Growth Rate of Selected Age Group and Total
Population of Jamaica, using Census data: 1844-2050 (in %)

Appendix II. Table 2.1.2a: Percentage of Estimated or Projected Populations by
Selected Age Groups of different Caribbean Nations: 1950, 1975, 2007 and 2050

Appendix III. Table 3.1.5: Growth Rate (in %) for Selected Regions, and
Countries based on certain Time Periods: 1950 to 2050

Appendix IV. Table 4.1.2: Life Expectancy at Birth of Jamaicans by Sex: 1880-
2004


Appendix V: Table 4.1.2: Life Expectancy at Birth of Jamaicans by Sex: 1880-
2004
                                                                               10




                                LIST OF TABLES


                                                                        Page

Table 1.1.1: Selected Age Groups of Jamaican Population,
       using Census data: 1881-2001 (in %)                              2


Table 1.1.2: Selected Age Groups of Jamaican Population:
       1950, 1975, 2007, 2025 and 2050 (in %)                           3

Table 1.1.3: World Percentage of Population at Older Ages, 1950—2050 3

Table 2.1.3: Characteristic of the Three Categories of Elderly,
       and the Ageing Transition                                        23

Table 3.1.1: Life Expectancy at Birth for Selected Regions
       by Both Sexes: 1950-2050 (in years)                              31

Table3.1.2: World Life Expectancy by Specific Aged Cohorts
       and by Gender, 1950—2050                                         32

Table 3.1.4: World Growth Rate (in %) by Aged Cohorts, 1950—2050        33

Table 4.1.1: Net External Migration of the Population
       by Selected Age Groups, Jamaica: 1988-2006                       45

Table 4.1.2: Estimated or Projected Populations
       by Selected Age Groups of different Caribbean Nations:
       1950, 1975, 2007 and 2050 (in %)                                 48

Table 4.1.3: Rate of Growth for Selected Regions, and Countries
        based on certain Time Periods: 1950 to 2050 (in %)              49

Table 4.1.4: Cuba: Selected Statistics of the Aged Population, 1899-2025 50

Table 4.1.5: Cuba: Life Expectancy by Gender. 1950-1986                 50

Table 4.1.6: Rate of Growth of Selected Age Groups and of
       Total Population of Jamaica, using Census data: 1844-2050 (in %) 51

Table 4.1.7: Life Expectancy at Birth of Jamaicans by Sex:
       1880-2004 (in yrs)                                               55
                                                                              11


Table 9.1.1: Univariate Analyses of Variables used in Wellbeing Model   147

Table 9.1.2: Percentage of Sex of Respondents by Elderly Cohort         148

Table 9.1.3: Percentage of Marital Status of Respondents
       by Elderly Cohort                                                150

Table 9.1.4: Percentage of Educational Level by Elderly Cohort          152

Table 9.1.5.i: Percentage of Area of Residence by Elderly Cohort        153

Table 9.1.5.ii: Percentage of Area of Residence by Elderly Cohort       154

Table 9.1.6: Percentage of Elderly Receiving
       National Insurance Scheme (NIS)                                  155

Table 9.1.7.i: Percentage of Elderly Receiving Government
or Private Pension by Elderly Cohort                                    155

Table 9.1.7.ii: Percentage of Sampled Population who Receive
       NIS by PENSION (Government or Private)                           156

Table 9.1.7.iii: Percentage of Sampled Population who Receive
       NIS by Area of Residence                                         157

Table 9.1.7.iv: Percentage of Sampled Population who
        Receive Pension by Area of Residence                            157

Table 9.1.7.v: Percentage of Sampled Population who Receive NIS by Sex 158

Table 9.1.7.vi: Percentage of Sampled Population who
       Receive Pension by Sex                                           158

Table 9.1.8: Physical Health Status by Elderly Cohort                   159

Table 9.1.9.i: Descriptive Statistics for Health Care Expenditure
       of the Elderly Cohort                                            161

Table 9.1.9.ii: Descriptive Statistics for Health Care Expenditure
       based on Area of Residence                                       162

Table 9.1.9.iii: Descriptive Statistics for Health Care Expenditure
       based on Sex                                                     163

Table 10.1.1: A Multivariate Model of Wellbeing of
       the Jamaican Elderly, N=629                                      167
                                                                              12



Table 10.1.3: Difference in Wellbeing of Jamaican Elderly based on Area of
Residence (assume that only Area of Residence changes in equation 3)    173

Table 10.1.4: Wellbeing of Different Elderly based on Years Lived
       174

Table 10.1.5: Decomposing General Wellbeing Model:
       Physical Functioning Model, N= 629                              175


Table 10.1.6: Decomposing General Wellbeing Model:
       Economic Model, N=629                                           177
                                                                               13


                               LIST OF FIGURES

Figure 1.1.1: Explanatory Model for Wellbeing of Elderly Jamaicans       31

Figure 3.1.1: Selected Regions and their Percentage of Pop. 65+ years
       35

Figure 3.1.2: Ranked Order of Five Leading Causes of Mortality in the
            Population 65 yrs and older, 1990                            37


Figure 3.1.3: Leading Causes of Self-Reported Morbidity in the
              Population of Seniors, by gender in Barbados and Jamaica 38

Figure 4.1.1: Percentage Change in the Size of Elderly Age-subgroups,
               1991-2001                                                 54

Figure 4.1.2: Population Pyramid of Jamaica by Age and Gender, 2000      56

Figure 4.1.3: Population Pyramid of Jamaica by Age and Gender, 2025      56

Figure 4.1.4: Population Pyramid of Jamaica by Age and Gender, 2050      57
Figure 4.1.5: Percentage Change in Age Sub-groups as a Proportion

       of Total Population between 1991 and 2001                         58

Figure 7.1.1: Respiratory System of a Human                              128

Figure 9.1.1: Area of Residence by Sex of Respondents                   149

Figure 9.1.2: Percentage of Health Conditions Reported by Sex           160

Figure 9.1.3: Per-capita Population Quintile,
           by Age Group of respondents                                  164


Figure 9.1.4: Per-capita Population Quintile,
       by Age Group Controlled for Sex                                  165


Figure 11.1.1: Percentage of Elderly (ages 60+ years) in Jamaica,
                1850-2050                                               205
                                                                                 14




                                      PROLOGUE


       Reports from the PIOJ, STATIN, and the United Nations have shown that

life expectancy at birth for both genders (male and female) in Jamaica has more

than doubled over the last 100 years. This has increased by up to 20 years from

the 1950s to 2004. However, the new focus is not on life expectancy, but on

healthy life expectancy and disability free life expectancy. It is undoubtedly clear

from statistics that we have managed to add years to life, hence we need to

examine the quality of life for those years and in particular that of the elderly.

Looking at the life expectancy data for Jamaica (2002-2004), it is 74.1 years for

both genders (Demographic Statistics 2006) but according to the WHO (2003)

healthy life expectancy of Jamaicans is 65.1 years. This reality reiterates the

point that despite the gains in life expectancy, the elderly are living longer but

with disability, which is undoubtedly reducing their wellbeing (or quality of life).

Thus, by examining factors that influence their wellbeing, we will be unearthing

issues that have an impact on their quality of life.



       Over the years, in operationalizing wellbeing or health, scholars have used

(1) physical functioning (Hambleton et al. 2005; Smith and Kington 1997;

Grossman, 1972), (2) self reported happiness (Kashdan 2004; Stutzer and Frey.

2003; Diener 2000; Lyubonirsky 2001) or (3) income (Sen 1998). Based on my

review of the works, there is no single study that has used a combination of two or
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more of those conditions identified earlier in operationalizing wellbeing, and this

is so in Jamaica as well. After much investigation, it appears that this is the first of

its kind in Jamaica in a number of different ways. Firstly, the study has expanded

on the operational definition of wellbeing from either functional limitations or

income to a composite index that includes health conditions, income,

consumption and ownership of material resources (excluding ownership of house

or dwelling). Secondly, the research has used the biopsychosocial model in

evaluating factors that are likely to influence wellbeing.         Finally, the model

developed by this work will be able to examine the quality of life of elderly

Jamaicans.

        Historically,   in    Jamaica,    wellbeing     has    been     predominantly

conceptualized, diagnosed and treated primarily from a biomedical perspective.

To this end, socioeconomic, environmental and psychological issues have not

been emphasized. This is evident from the data collected and published by the

Jamaica Survey of Living Conditions (JSLC) reports that guide policy

formulation in the country. The collected data on health status focus on self-

reported illness or injury, severity of illness, utilization of health services and cost

of health care. In order to develop a definition that is more reflective of people’s

quality of life, we must assess ‘non-biomedical’ factors as a part of the construct

of subjective well-being which is multifaceted.

        Since humans are unique and complex social agents, health and well-being

cannot be built around a one-dimensional construct. In this paper a model is

framed that will estimate the wellbeing of the elderly (persons 60 years and
                                                                                    16


beyond). It is developed using socio-economic, environmental and psychological

conditions as self-reported by Jamaicans, from a nationally representative data.




Theoretical Model - framework




There are a number of reasons for this project, and among the purposes for the

writing of this book is the development of a model that can be used to examine

and evaluate the wellbeing of aged Jamaica. The theoretical model that was used

to drive this book is a mathematical function that was earlier developed by

Grossman, which I modify to include other variables that were identified from the

literature. Hence, the theoretical model that is used herein subsumes all the

research findings that indicate the wellbeing (quality of life) of aged people in

Jamaica.

         Theoretical framework guides all research. It is this framework which

guides the research materials used, the methodologies, the methods of data

collection, the analysis of data, along with the research objectives and the survey

questions. Hence, the theoretical framework plays a fundamental role in the

research process. With this being the case, Waller’s monograph summarized this

perfectly, that:

         [It] is a self-conscious set of (a) fundamental principles or axioms (ethical,

         political, philosophical) and (b) a set of rules for combining and applying

         them (e.g. induction, deduction, contradictions, and extrapolation). … and

         so determines the kinds of knowledge about the objects that can be
                                                                                  17


       produced legitimately within the framework (Waller 2006, 25).



       Waller’s construct highlights the importance of assumptions, procedures

and principles in the execution of social research. Social research is hinged on

particular sets of worlds, and the apparatus which is present for the interpretation

of that cosmology. Based on Waller’s proposition, for this project the researcher

will employ Ecological, and Selective Optimization with Compensation Model of

Ageing, the biopsychosocial model, in an attempt to understand the state of the

aged in Jamaica

       The utilization of this model rests squarely in the thrust for the 21st

Century in that we now recognize the complexity of different sociocultural,

psychological and economic conditions, playing on the health status and by

extension the wellbeing of people. Quality of life is not adequately addressed in

the old biomedical model - because they (medical doctors, biologists to name a

few scientists) believe that socioeconomic, psychological and environmental

factors contribute to the health status of people (see for example Barrett et al.

1998). It is argued that the environment and phenomena such as El Niňo have

aided the increase of illnesses such as malaria, dengue fever, asthma and other

respiratory diseases, and cholera. (See Barrett et al. 1998, 258-259).

       The biopyschosocial model is captured in a mathematical model devised

by a group of scholars. It is a function that researchers call wellbeing, which is an

additive approach of various explanatory variables (wellbeing = f (socioeconomic

conditions, psychological variables, biomedical conditions)).            While many
                                                                                  18


scholars such as Erber (2005), Brannon, and Feist (2004) had put forward the idea

that this is timely in the measurement of quality of life, neither of them proposed a

mathematical model to the worded construct.



W ii =ƒ (P mc , ED, E t , A i, En , G, MS, AR, P, N, O, H, T, V)           [1]



        Individual wellbeing, Wi , is a function of cost of medical care P mc ,

educational level of the individual, ED, elderly cohort A i, where i is 65 years and

over), the environment En, gender of the respondents G, marital status MS, area

of residents AR, positive affective conditions P, negative affective conditions N,

occupancy per room O, home tenure H, property ownership, T, and crime and

victimization, V.



        The model is primarily shaped by regression analysis. Embedded with

this model was the correlation between sociodemographic, institutional,

environmental and economic conditions on the wellbeing of each individual with

different time intervals. Engel’s biopsychosocial model was not really a model.

Instead it was a construct which sought to encapsulate body, mind and social

conditions in the treating of health.        He argued for the expansion of the

biomedical model but during the process did not formulate a theory or a model.

Thus, Dr. Engel’s work on the biopyschosocial model did not define a set of

variables; neither did he use any advancing statistical technique to illustrate what

he referred to as a model. Two economists, Smith and Kington, on the other
                                                                                  19


hand, have sought to provide a platform upon which more studies should be

positioned in understanding the health status of a population, when they used

theorizing developed by Grossman, which was the actual model building of the

construct outlined by Engel, biopyschosocial construct. It is an econometric

model, which uses the principles of a production function. This is a broader

construct of health that incorporates biological, psychological and sociological

conditions in assessing health status.




Finding of the Model

We found that there is a moderately strongly positive relationship (r= 64.5%, ρ

value< 0.05) between the determinants used in this paper and general wellbeing,

with a coefficient of variation (r2) of 40.1%. This denotes that the model explains

40.1% of the variation in wellbeing. In this research five additional factors were

introduced. These include crime, area of residence, psychological conditions,

environmental factors and age of respondents.        In addition, we decomposed

general wellbeing into both functional ability and material resources, in order to

comprehend how the predisposed variables impact on each component of

wellbeing. From the selected variables of this study, we have found that there are

10 factors of general wellbeing. General wellbeing of the Jamaican elderly is

affected by (i) psychological conditions - positive and negative affective

conditions; (ii) area of residence; (ii) crime; (iv) marital status; (v) physical

milieu; (vi) property ownership; (vii) educational level; (viii) cost of health care,

(ix) average occupancy per room and (x) age of the respondents. The five most
                                                                                 20


important impacting factors of wellbeing of the Jamaican elderly in descending

order are as follows: Average occupancy per room (β = -0.229), Physical

environment (β = -0.190), Education (β = 0.173), Area of residence (β = 0.164);

and Cost of health care (β = 0.148). Thus, the significance of this paper is that we

now have a quantitative model that can be used to evaluate the wellbeing of

elderly Jamaicans.

LAYOUT OF THE BOOK




In this study, the researcher (Paul Andrew Bourne) will provide a conceptual

framework along with a theoretical framework for understanding the individual

factors that influence wellbeing, as well as the construction of the theories on the

topic. This text, ergo, is subdivided into five chapters. Chapters 1 and 2

summarize the context of the study, providing contextual and theoretical

underpinning of the discourse on wellbeing, and a number of the explanatory

variables. The first chapter (Chapter 1) provides studies and materials on the

general discourse from an international, regional and national perspective, while

the next chapter (Chapter 2) gives the framework upon which analyses will be

done, and how these will aid the study.          The third chapter presents the

conceptualization, operationalization, and data transformation of the key variables

along with the particular method of data analysis.       This begins with a brief

overview of the choice of paradigm, and the survey design, followed by the

method of analysis and explanatory model. Chapter four provides the findings

and the analyses of the data against the background of the method. The focus of
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this section is the provision of information in hypothesis testing. Chapter 5, on the

other hand, concludes with the summary, conclusion and recommendation of text

- determinants of the wellbeing of the Jamaican elderly.



Paul Andrew Bourne, Dip Edu, BSc, MSc, PhD
Political Sociologist, Biostatistician and Public Health Specialist
                                                                                  22


                                 Chapter One

                                 Introduction

       Ageing is not a recent phenomenon. It goes back centuries, from time

immemorial. The total human population, within any geographical area, is made

up of children, youth, people of working age and the elderly. This latter grouping

is a phenomenon not only in developed nations but also in many developing

societies. For many Caribbean countries, this is also their reality. The factors that

explain the “greying” of the world’s population are fertility decline, reduced

mortality at ‘older ages’ and the external migration of the young, as well as the

return of retirees. Those conditions, coupled with increases in life expectancies

due to public health improvement and better water qualities, have significant

consequences for population size and structure. Where the elderly population

outgrows the younger, the population structure at younger ages is constricted and

at older ages it expands (Rowland 2003, 98). This is an aspect of demographic

transition which will change significantly in the 21st century.

       Demographic ageing at the micro and macro levels implies a demand for

certain services such as geriatric care. In addition to preventative care, there will

be a need for particular equipment and products (i.e. wheelchairs, walkers). Then

there are future preparations for pension and labour force changes, along with the

social and economic costs that are associated with ageing, as well as the policy

base research to better plan for the reality of these age groups. The World Health

Organization (WHO), in explaining the ‘problems’ that are likely to occur

because of population ageing, argues that the 21st century will not be easy for
                                                                                  23


policy makers, who are pivotal in the preparation process to postpone ailments

and disability and in the challenge of providing a particular standard of health for

the populace within the context of an ageing population (WHO 1998, 5). What

constitutes population ageing?        Some demographers have put forward the

benchmark of 8-10% as an indicator of population ageing (Gavrilov and

Heuveline 2003). Within the construct of Gavrilov and Heuveline’s perspective,

the Jamaican population began experiencing this significant population ageing as

of 1975 (using 60+ years for ageing) or of 2001 (if ageing is 65+ years) (See

Tables 1.1.1 and 1.12), and the world since the 1950s (Table 1.1.3). The numbers

comprising the ageing population will double come 2050 irrespective of the

chronological definition of ageing (see Table 1.1.2 and Table 1.1.3), but what

about the      quality of life of the elderly? This book is concerned not about

population ageing in the world, the Caribbean or for that matter Jamaica, but we

will examine the wellbeing of aged Jamaicans within the reality of population

ageing.

Table 1.1.1: Selected Age Groups of Jamaican Population, using Census data:
1881-2001 (in %)

Age groups       1881   1891   1911    1921   1943   1960    1970   1991       2001



0 – 14 yrs.      38.8   38.7   39.8    39.4   36.6   41.1    45.9     35.2     32.2


15 – 64 yrs.     56.5   57.5   56.7    56.9   59.2   54.5 48.5       57.5      57.6

65+ yrs.         4.7    3.8     3.5    3.7    4.2    4.4     5.6     7.3       10.2

Source: Computed by Author from Statistical Yearbook of Jamaica: 1973-1989 &
Demographic Statistics: 1973-2006.
                                                                                          24


Table 1.1.2: Selected Age Groups of Jamaican Population: 1950, 1975, 2007,
2025 and 2050 (in %)

Age groups      1950             1975             2007            2025             2050

0 – 14 yrs.     36.0             45.2             28.6*           24.4             18.5

15 – 59 yrs.    58.2             46.3             60.7*           60.6             57.9

60+ yrs.        5.8              8.5              10.7*           15.0             23.6

65+ yrs.        3.9              5.8              8.0*            10.3             17.7

80+ yrs.        0.2              0.8              2.0**           2.3              5.6

Source: United Nations, 2007, pp308-309
* Using figures taken from Demographic Statistics 2006 for the same year
** Estimate for 2005 from United Nations, 2007


Table 1.1.3: World Percentage of Population at Older Ages, 1950—2050
Details      Age       1950        1975        2000        2025    2050

Total          60+         8.2          8.6           10.0         15.0         21.1
               65+         5.2          5.7           6.9          10.4         15.6
               80+         0.5          0.8           1.1          1.9          4.1
Female         60+         9.0          9.7           11.1         16.3         22.7
               65+         5.9          6.6           7.9          11.6         17.3
               80+         0.7          1.0           1.5          2.5          5.0
Male           60+         7.3          7.5           8.9          13.6         19.4
               65+         4.5          4.8           5.9          9.2          14.0
               80+         0.4          0.6           0.8          1.4          3.1
Source: Population Division, DESA, United Nations, in United Nations. 2004. World Population
Ageing 1950-2050. New York: United Nations, pp. 46




         Caribbean demographers, like other demographers, have been using life

expectancy for years as the measure for wellbeing.             Over the years, we have

accepted the perspective of those scholars who used life expectancy as an

indicator of health status and by extension quality of life, but this approach

accepted that a quantitative assessment of years allows us to understand the
                                                                                 25


quality of those years lived by someone. Life expectancy (or population ageing)

speaks to number of years, but this focus fails to address the other tenets of this

subject. We will present an example that illustrates the disparity between long life

and quality of years lived. Ali, Christian and Chung, who are medical doctors,

cite the case of a 74 year-old man who had epilepsy, and presented their findings

in the West Indian Medical Journal.

       They write that:

       Elderly patients are frequently afflicted with paroxysmal impairments of
       consciousness usually because they often have chronic medical disorders
       such as diabetes mellitus and hypertension and can also be on many
       medications. The differential diagnosis of transient impairment of
       sensorium in the elderly is wide and includes metabolic encephalopathies
       e.g. medication side effects, syncope, including cardiogenic syncope,
       transient ischaemic attacks and strokes, the syndrome of transient global
       amnesia, psychogenic fugue states and epileptic seizures. Many elderly
       patients may have more than one cause for this symptom. (Ali, Christian
       and Chung 2007, 376)


       The case presented by the medical doctors emphasizes the point we have

been arguing, that long life does not imply quality of life years. Although the case

study cited here does not constitute a general perspective on all the elderly, other

quantitative studies have concurred with Ali, Christian and Chung’s general

findings. Scientists agree that biological ageing means degeneration of the human

body (also see: Hooyman and Kiyak 2005; The Merck Manual of Aging 2004;

Eldemire-Shearer 2003; Kalache 2003; Ling and Bathon 1998), and such a reality

means that longer life will not mean quality years. Thus population ageing, like

life expectancy, does mean more than increased number of people for the human

population. Population ageing is going to be a socioeconomic, psychological and
                                                                               26


political challenge today, tomorrow and in the future for developing countries and

nations like Jamaica. However, this paper is concerned with the wellbeing of the

aged from the perspective of the biopsychosocial model and its determinants, and

the state of the elderly in Jamaica.    The biospsychosocial model posits that

biological, sociological, and psychological conditions play a significant role in

determining the wellbeing of an individual. How was this study conducted? And

what is the prescribed model that is being put forward here that will drive the

study?

         Research Design

         The research design for this study is an explanatory one. This study

utilizes cross-sectional data from a reputable data collections agency in order to

identify and explain the determinants of wellbeing among the Jamaican elderly.

The use of multivariate analysis to generate a model for the phenomenon clearly

indicates a mathematical demographic approach.

         Many scholars, (for example Crotty 2005; Neuman 2006; Boxill,

Chambers and Wint 1997; Babbie 2000; Heiman 1995; Shaughnessy and

Zechmeister 1990; Bryman and Cramer 2005) have written on social research

methods, but the researcher has found Michael Crotty’s monograph aptly fitting

for this paper, as it summarized the research process in a diagrammatic and

systematic manner while providing elaborate details of each component. In the

text titled ‘The foundations of social research: Meaning and perspective in the

research process’, Crotty (2005) aggregated the research process in four schema

(i.e. four questions which must be answered in examining social phenomena),
                                                                                 27


namely (1) methods, (2) methodology, (3) theoretical perspective, and (4)

epistemology.

       The four schema of the research process according to Crotty (2005, 2-4)

are encapsulated into a flow chart (See Figure 4.1). Michael Crotty, a lecturer in

education and research study at the Flinders University of South Australia,

believed that the purpose of research guides the choice of methodology and

method. In this way, the chosen methodology and method clearly depict the set

of assumptions the researcher has about reality (Crotty 2005, 2) (i.e. what [he/she]

brings to the work).

       The schema of the research process is not simply a unidirectional model

(Crotty 2005, 2-4). Crotty (2005) pointed out that this process may begin with

epistemology, theoretical perspective, methodology and method, but noted that it

may flow from method, methodology, theoretical perspective and lastly

epistemology. Embedded in this schema is not the preciseness of the direction but

that those areas are a must within a research process.

       Survey Design

       This book for its research design used secondary data taken from a

reputable statistical agency      to   examine socio-political, ecological and

psychological factors and how they influence the wellbeing of elderly Jamaicans.

The institution began collecting data to aid planning in the late 1980s when the

institution collaborated with another, and adopted, with some modifications, the

World Bank's Living Standards Measurement Study (LSMS) household surveys.

The PLC has its focus of policy implications of government programmes, and so
                                                                                  28


each year a different module is included with the aim of evaluating a particular

programme. The PLC is a self-administered instrument (questionnaire) where

respondents are asked to recall details of information on particular activities. The

questionnaire covers demographic variables, health, immunization of children 0 to

59 months, education, daily expenses, non-food consumption expenditure,

housing conditions, inventory of durable goods and social assistance. Interviewers

are trained to collect the data, which is prepared by the household members. The

survey is usually conducted between April and July annually.

       The current study extracted data on public-private health care utilization,

mean cost for visits to public-private health care facilities in the last 4 weeks of

the survey period, and health insurance coverage from the PLC. Information was

extracted on the annual inflation rate from 1988 to 2007. Scatter diagrams

(graphical plots) were on variations of public-private health care utilization by

inflation, mean cost of care for visits, as well as other graphic presentations used

to assess whether any statistical association exists between the dependent variable

and the independent variable; and some of the graphs were only interpreted. In the

current study, sub-samples of 3,009 elderly Jamaicans (60 years and older) were

extracted from the PLC’s survey that had 25,018 respondents. The rationale for

the use of PLC 2002 was based on two critical issues: 1) it was the largest dataset

ever collected by the two Institutions, and 2) it was the first time in the annals of

the PLC that crime and victimization, demographic characteristics, household

consumption, education, health, social welfare and related programmes, and

housing were collected together. Hence, within the context of a large dataset and
                                                                                    29


the number of conditions that are related to the cohort in investigation, I believe

that it was fitting to use this period as against other occasions with less than 3,000

respondents and not having data on crime and victimization, which is a major

problem faced by countless Jamaicans.


General Hypothesis: The mathematical model which drives this paper.



W iki =ƒ (P mc , ED, A i , En , G, MS, AR, P, N, O, H, T, V)

        W i is the wellbeing of the Jamaican elderly, i, is a function of the cost of

medical (health) care, (P mc ), the educational level of the elderly individual, (A i ,

where i is an elderly individual ), the environment (En), gender of the respondents

(G), marital status (MS), area of residents (AR), positive affective conditions (P),

negative affective conditions (N), average occupancy per room (O), home tenure

(H), property ownership (T), and crime and victimization (V).

        The sample survey research methodology requires objectification in the

investigation of phenomena. The primary purpose in using this methodology is

objectivism, as some scientists argue that things exist out there independently of

our consciousness and experiences. As such, the positivists’ paradigm is the most

suitable and preferred theoretical framework to execute the specified

methodology. Positivism is fundamentally based on (1) science (i.e. free from

value judgment – science is guided by observation and not opinion or beliefs), and

(2) measurement - that if a phenomenon cannot be measured, it should not be

studied – which explains why positivists embody theories in hypotheses that are

testable.
                                                                               30


       The positivists’ philosophy is carried out by hypothesis testing through

conducting experiments (i.e. observation) and the manipulation of variables. This

is referred to as the scientific method – that is, logical reasoning, with an

emphasis on experience (i.e. observation) and measurement.

       A renowned methodologist, Neuman (2003), penned the following

perspective that aptly summarized positivism, when he said that:

       Positivism sees social sciences as an organized method for combining
       deductive logic with precise empirical observation … in order to discover
       and confirm a set of probabilistic causal laws that can be used to predict
       general patterns in human activity (Neuman 2000, 66).

       Embedded in positivist research are the techniques used in obtrusive and

controlled measurement. This guides the data-gathering process (also see Waller

2006) – by way of survey, experiments, case-control studies, statistical records,

structured observation, content analysis, and other quantitative techniques. The

very nature of this research on wellbeing, was not the collection of data through

observation, but that a primary institution gathered pertinent data from Jamaicans

based on the people’s belief (i.e. self-reported), which makes for value

judgements (see for example, Trochim 2006). Hence, in its truism form, the

researcher did not use positivism. Instead, a hybrid methodology was used.

       Based on the fact that the researcher used a survey (Jamaica Survey of

Living Conditions) which collected data from people within Jamaica, and that the

data given are individuals’ perspective on how they conceptualize what they see,

the researcher used mixed positivism, which captures what the post-positivist (see

Trochim    2006)   called   constructivism    while   applying     causation   and

objectification. Constructivism speaks to the position of each person, and from an
                                                                                   31


objective reality (i.e. through precise measurement – that is using the scientific

method).

       From the post-positivism stance, the researcher in an attempt to reach “the

goal of getting it right about reality” (Trochim 2006) put forward the idea that this

can only be attained through triangulation, and so did not use this in its entirety.

       Nevertheless, based on the type of data gathered by the Statistical Institute

of Jamaica (i.e. self-reported information from each respondent on how he/she

conceptualizes his/her surrounding); the researcher will use this self-reported data

to guide the analysis of a wellbeing function. The function will apply regression

analysis to construct a model for wellbeing for the Jamaican elderly, using

hypothesis testing, precise measurement of concepts and some econometric

modelling techniques (see Explanatory Model, p.124; also see Methodology and

Method (Chapter 3) – i.e. hypotheses).

       The use of multivariate analysis to generate a model for the phenomenon

clearly dictates that a mathematical–demographic approach had to be taken;

hence, positivism was the preferred and appropriate choice of methodology.

       Furthermore, the study will test a number of hypotheses by first carefully

analyzing the data through cross tabulation – to establish relationship, and then,

secondly, by removing all confounding variables. After this, the researcher will

use model building in order to finalize a causal model. Hence, the positivist

paradigm is the appropriate choice.           The positivists’ paradigm assumes

objectivity, impersonality, causal laws, and           rationality.   This   construct

encapsulates scientific method, precise measurement, and deductive and
                                                                                         32


analytical division of social realities. From this standpoint, the objective of the

researcher is to provide internal validity for the study, which will rely totally on

scientific methods, precise measurement, value free sociology and impersonality.

        The study will design its approach in a similar way to that of natural

science by using logical empiricism. This will be done by precise measurement

through statistics (chi-square and modelling – logistic regression). By using

hypotheses testing, value free sociology, logical empiricism, cause-and-effect

relationships, precise measurement through the use of statistics and survey and

deductive logic with precise observation, this study could not have used the

interpretivist paradigm, as the latter seeks to understand how people within their

social setting construct meaning in their natural setting, which is subjective rather

than the position taken in this research – an objective stance. Conversely, this

study does not intend to transform peoples’ social reality by way of

empowerment, but is primarily concerned with unearthing a truth that is out there,

and as such, that was the reason for the non-selection of the Critical Social

Scientist paradigm.

Limitation to the Study Model

This model W=ƒ (P mc , ED , Ai, E n, G, M, A R , P, N, O, H t , T,   V, S ,   H S) + ei is a

linear function

W= 1.922+ 0.197P mc + 1.091A R 2 + 1.698 A R 3 – 0.633 En + 0.341 M1 + 0.560
M2 + 0.240 E D 2 + 1.700 ED 3 + 0.210S – 0.691O + 0.606 T + 0.105P -0052N-
0.022 A i + ei

Therefore we are unable to distinguish between the wellbeing of two individuals

who have the same typology, and the wellbeing of an individual that may change
                                                                                  33


over short time intervals that do not affect the age parameter.         As such in

attempting to add further tenets to this model in order to be able to fashion a close

approximation of reality, the following modifications are being recommended.

         Each individual’s wellbeing will be different even if that person’s

valuation for quality of life is the same as someone else who shares similar

characteristics. Hence, a variable P representing the individual should be

introduced to this model in a parameter α (p). Secondly, the wellbeing of the

elderly is different throughout the course of the year, and so time is an important

factor. Thus, we are proposing the inclusion of a time-dependent parameter in the

model.     Therefore, the general proposition for further studies is that the linear

function should incorporate α (p, t) a parameter depending on the individual

and time.
                                                                                                    34


EXPLA
 Home Tenure
   Property
  ownership


Sex




Environment




Marital Status




Area of residence



Cost of Health                                                                                Wellbeing
care




Level of
Education



Average
occupancy per
household


Psychological:
Positive
Affective, and
Negative
Affective


Elderly




          Figure 1.1.1: Bourne’s Linear Conceptual Model of Wellbeing for Elderly Jamaicans
                                                                                 35


                                    Chapter Two

                                    Ageing Transition




       The issue of ageing and its conceptualization date back to earlier centuries.

The scientific study of this phenomenon in addition to that of older adulthood is a

more recent debate – nineteenth century – and it began as early as in 1835. This

fascination that people have for ageing, older adulthood and the ageing process is

a longstanding debate, and it emerged because of man’s eagerness to reduce the

ageing process. History has recounted that a Spanish explorer – during 1460 to

1521- in his quest to reclaim youth by rescinding the ageing process, discovered

Florida as a result. This explains the pilgrimage and people’s fascination with

bath fountains, health spas, dietary requirements, gyms, physical exercise and

their willingness to extend themselves in healthy lifestyle practices. Although we

have spent millions of dollars on DALY (i.e. Disability Adjusted Life Years)

lifestyle issues, we still cannot stop the ageing process. On a point of emphasis,

the developing world’s populations are even ageing at a faster rate than in the

developed world (Bourne and Eldemire-Shearer 2008b; Bourne 2007; United

Nations 2004, 2005; Eldemire-Shearer 2003; Kalache 2003). Thus, what is

ageing? And, what is the ageing process?

       There are many indicators of ageing (i.e. median age, the proportion of the

population older than 60 years, mean age of the population, and the dependency

ratio), but how do we know when it begins? In this chapter, the author will

examine different conceptualizations of ageing, in order to evaluate the process of
                                                                               36


ageing and when ageing commences.

        Chronological ageing

        However the author, using the available data for Jamaica from the

Statistical Institute of Jamaica, was able to compute the average growth rate for

children (i.e. ages less than 15 years), work age population (ages 15 through 64

years) and the elderly (ages 65+) from as far back as 1844. The author has

concluded that while he was unable to definitely say that population ageing

began in the mid 1960s, the average growth rates show that the ageing of the

nation’s population occurred between 1960 and 1970. Between 1950 and 1960,

the average growth rate was 1.74%, and it rose to 3.36% between 1960 and 1970,

with no other period before 1950 and post 1970 showing an average growth rate

close to 3.4%. (See Appendix I - Tables 2.1.1). The average growth rate for 1991

to 2001 stood at 1.43%. Professor Denise Eldemire-Shearer, a Jamaican public

health and ageing expert, on the other hand, did not substantiate her claim as to

why she argued that population ageing in Jamaica began in the ‘mid 1960s’. The

author, using a percentage of the elderly population (i.e. ages 60+ years) cannot

substantiate Eldemire-Shearer’s claim, but what can be said with authority is that

it occurred between 1960 and 1970 (also see Appendix II – Table 2.2.2a and

Table 2.2.2b), and for the world (see Table 1.1.3), Barbados and Suriname (Table

2.2.2a) it started in the 1950s.

        With regard to global population, 10.4% of individuals are 60 years or

older (United Nations 2005c). Jamaica’s elderly population in 2005 rose

marginally by 0.3% to 10.7% in 2006 (PIOJ 2007). The United Nations data show
                                                                                37


that 8% of people in developing nations are 60 years or over (United Nations

2005c), which is approximately 2% less than the number of aged people in

Jamaica. According to the Demographic Statistics (2006), 10.9% of Jamaicans

females are 60 years and older compared to 10.3% of males.

       Despite the indecisiveness in reaching consensus on a definition of ageing

from the United Nations’ perspective on the elderly, ‘old age’ begins at 60 years

while other scholars conceptualize ageing to commence at age 65 years or older

(See for example Lauderdale 2001; Elo 2001; Manton and Land 2000; Preston et

al. 1996; Smith and Kington 1997a; Rosenberg, M.W., and E.G. Moore. 1997;

Smith and Waitzman 1994; Rudkin 1993). The WHO says that we can either use

the chronological age of 60 or 65 years or over to indicate the beginning of ageing

(WHO 2002, 125). So why is there no standardized definition for the elderly or

where ageing begins? Thane (2000) noted that ‘old age’ for all people was

defined as 60 years in medieval times. She justified this by putting forward an

argument for the established age. In medieval England, men and women ceased at

60 years to be liable for compulsory service under labour laws or to participate in

military duties. In Ancient Rome, on the other hand, ‘old age’ began from early

40 to 70 years, with 60 years being ‘some sort of annus climactorius’. Some

Demographers see seniors - the elderly or the aged (old people) - as beginning at

the chronological age of 65 years and older, and not an individual who is 60 years

of age. Up to 1992, the Statistical Institute of Jamaica defined old-age as those

people 65 years and older (Demographic Statistics 1992).         At that time the

Professor of Demography at the University of the West Indies at Mona was
                                                                                 38


primarily responsible for much of the output from that Institution, and for the

training of staff. This may explain why the Statistical Institute of Jamaica used 65

years in its conceptualization of old-age. Furthermore, Western societies use 65

years and older to represent the elderly (seniors) as this is the period when people

become fully eligible for Social Security benefits.

       One Caribbean scholar emphasized that there is no absoluteness in the

operational definition of the “elderly” (Eldemire 1995, 1). She commented that

from the World Assembly of Ageing (which was held in Vienna in 1982), the

term “elderly” uses the chronological age of 60 years and older ‘as the beginning

of the ageing process’. Jamaica having signed the Vienna Declaration of Ageing,

which defines ageing to begin at 60 years, Eldemire questioned academics and

other scholars over their rationale in using 65 years. Many demographers use 65

years and older to represent the commencement of the ageing process, but that is

due primarily to the nature of the study. Demographers use 65 years and beyond

when they examine the elderly and this is used more in the context of retirement

matters. However, these scholars frequently use 60 years and older in situations

when health is being examined, which is in keeping with the medical perspective

that the chronological age of 60 years is the beginning of the ageing process.

       Within the study of demography, elderly begins at the chronological age

of 65 years – using the unit of analysis of time, based on the number of years and

months that have elapsed since birth (See for example Erber 2005; Iwashyna et al.

1998; Preston, Elo, Rosenwaike, and Hill 1996; Smith and Waitzman 1994).

However, based on the monographs from other scholars (such as - Marcoux 2001;
                                                                                 39


Eldemire 1999; Ministry of Labour, Social Security and Sports 1997; Eldemire

1997; PAHO and WHO 1997; Eldemire 1995a; Eldemire 1994; Barrett 1987), the

issue of the aged begins at 60 years. Hence, the operational definition of the

‘elderly’ continues unabated in non-standardization. Those who use 60 years

adopt this value because of the World Assembly on Ageing (in Vienna, Austria:

July-August 1982), which puts forward the idea that ageing begins

chronologically at 60 years.

       In a discussion with Professor Eldemire (on 7th April, 2008), she opined

that among the reasons for the non-standardization of the term ‘elderly’ was the

disparity in the actual commencement of the ageing process. Eldemire pointed

out that, although the World Health Organization (WHO) recommended that we

use 60 years to indicate the beginning of ‘old age’, some people start ageing at the

chronological age of 60 years, and there are others who begin this stage at a later

age – 65 years. Eldemire’s position is in keeping with the arguments put forward

by the WHO on the rationale for the non-standardization of the operational

definition of when “older age” begins.

       The Canadian statistical agency used age 65 years as the dividing line

between “young” and “old” (Moore et al. 1997, 2; also see Smith and Waitzman

1994; Preston, Elo, Rosenwaike and Hill 1996).           The issue of using the

chronological age of 65 years to measure older adulthood, according to one

academic, comes from the minimum age at which the Social Security System

begins disbursing payment for pensions to people living in the United States

(Erber 2005, 12). It is argued that in 1935, the U.S. government modelled this on
                                                                                 40


the German retirement system. This explains the use of 65 years of age by many

scholars, practitioners and non-professionals ever since.      This approach sub-

divides ageing into three categories. These are (i) young-old (ages 65 through 74

years), (ii) old-old (ages 75-84 years) and oldest-old (ages 85 years and beyond).

However, is there a difference between biological and chronological ageing?

       The WHO (2002) offered us a rationale for ‘old age’ in one of its

publications entitled ‘World Report on Violence and Health’, that it is based on

‘physical decline’ (or functional limitation) of people in regard to them “no longer

[being able to] carry out their family or work roles. Embedded in the rationale for

the operational definition offered by the WHO is the recognition that ‘old age’ is

both a chronological as well as a biological phenomenon. Hence, what is the

discussion on biological ageing?

       Biological ageing

       As cells age, they function less well. Eventually, they must die, as a
       normal part of the body’s functioning (The Merck Manual of Health and
       Aging, 2004, 5)


       As the years pass, most people experience changes in the way their body
       functions. Some changes are obvious. For example, before age 50, most
       people begin to have trouble seeing objects that are up close. Other
       changes are hardly noticeable. For example, few people are aware that the
       kidneys may become less able to filter waste products out of the blood,
       because the kidneys usually continue to filter the blood well enough to
       avoid problems. Most people learn that their kidneys have aged only if a
       disorder develops (The Merck Manual of Health and Aging 2004, 5)



       Organisms age naturally, which explains biological ageing, including

kidney issues, vision, hearing, reduced mobility and even natural death owing to
                                                                                  41


ageing organisms. Here ageing implies growth, development and maturity (Ross

and Mirowsky 2008). This approach emphasizes the longevity of the cells, in

relation to the number of years the organism can live. Thus, in this construction,

the human body (an organism) is valued based on physical appearance and/or the

state of the cells. Embedded in this apparatus is the genetic composition of the

survivor.   This occurs when the body’s longevity is explained by genetic

components (See for example Yashin and Iachine 1997, 32). Gompertz’s law in

Gavriolov and Gavrilova (2001) shows that there is a fundamental quantitative

theory of ageing and mortality in certain species (the examples here are as follows

– humans, human lice, rats, mice, fruit flies, and flour beetles (also see, Gavriolov

and Gavrilova 1991).     Gompertz’s law went further to establish that human

mortality increases twofold with every 8 years of an adult life, which means that

ageing increases in geometric progression. This phenomenon means that human

mortality increases with the age of the human adult, but that this becomes less

progressive in advanced ageing. Thus, biological ageing is a process where the

human cells degenerate with years (i.e. the cells die with increasing age), which is

explored in evolutionary biology (see Medawar 1946; Carnes and Olshansky

1993; Carnes et al. 1999; Charlesworth 1994). But studies have shown that using

evolutionary theory for “late-life mortality plateaus” fails, because of the arguably

unrealistic set of assumptions that the theory uses to establish itself (Mueller and

Rose 1996; Charlesworth and Partridge 1997; Pletcher and Curtsinger 1998;

Wachter 1999).

       Reliability theory, on the other hand, is a better fitted explanation for the
                                                                                     42


ageing of humans than that argued by Gompertz’s law, as the ‘failing law’ speaks

to the deterioration of human organisms with age (Gavrilov and Gavrilova 2001)

as well as the non-ageing term. The latter, based on Gavrilov and Gavrilova

(2001), can occur because of accidents and acute infection, which are called

“extrinsic causes of death.” While Gompertz’s law speaks to mortality in ageing

organisms due to age-related degenerative illnesses such as heart diseases and

cancers, a part of the reliability function is Gompertz’s function, as well as the

non-ageing component.

        When the biological approach is used to measure ageing, this may be

problematic, as two different individuals with the same organs and physical

appearance may not be able to perform at the same rates, which speaks to the

difficulty in using this construct in measuring ageing.

        Nevertheless, this construct is able to compare and contrast organisms in

relation to the number of years that a cell may be likely to exist. Erber (2005)

argues that this is undoubtedly subjective, as we are unable with any definiteness

to predict the life span of a living cell (Erber 2005, 9). Interestingly, the biological

approach highlights that the ageing process comes with changes in physical

functioning.   The oldest-old categorization is said to be the least physically

functioning compared to the other classifications in chronological ageing. The

young-old, on the other hand, are more likely to be the most functioning, as the

organism is just beginning the transition into the aged arena (see for example

Erber 2005; Brannon and Fiest 2004).

        It is important to avoid such pitfalls in constructions as may arise with the
                                                                                 43


use of the biological approach, ergo, for all intents and purposes, given the nature

of policy implications in effective planning, the researcher is putting forward the

perspective that seniority in age commences at age 65 years – using the

chronological ageing approach.

        In the ageing transition, both chronological and biological ageing have a

similar tenet. It should be noted that as an individual shifts from young-old to

oldest-old, the body deteriorates and what was of low severity in the earlier part

of the ageing process becomes of critical mass in the latter stage. Hence, at the

introductory stage of the ageing transition, the individual may feel the same as

when he/she was in the working-age population, but the reality is that the body is

in a declining mode. Because humans are continuously operating with negatives

and positives, as he/she becomes older – using the ageing transition (i.e. 65 years

and older) – the losses (or negatives) outweigh the positives. This simply means

that the functionality limitation of the body falls, and so opens the person to a

higher probability of becoming susceptible to morbidity and mortality. Secondly,

the environment, which may not have been problematic in the past, now becomes

a health hazard. One University of Chicago scholars summarizes this quite well

in Table 2.1.3:

       This study seeks to evaluate the wellbeing of the aged and not those who

are eligible for Social Security Benefits. Hence, for this study ‘old age’ or the

elderly (seniors) will begin from the chronological age of 60 years and older.
                                                                                                44


Table 2.1.3: Characteristics of the Three Categories of Elderly, and the Ageing
Transition
Characteristic


                                           The Ageing Transition

                                   Young-old           Aged 1      Oldest-Old

Health problems                   Low              Moderate      High

Physical disability               Low              Moderate      High

Demand for medical care           Low              Moderate      High

Demand for public service Low                      Moderate      High

Demands on children               Low              Moderate      High

Dependency on others              Low              Moderate      High

Social isolation                  Low              Moderate      High

Source: This is taken from Essays in Human Ecology 4. Bogue 1999, 3.

         Eldemire’s classifications differ somewhat from the perspective put

forward by Donald Bogue (1993). Old age (i.e. elderly) according to Bogue

begins at 65 years, whereas Eldemire believes that this should be 60 years and

older, which is in keeping with the conceptual definition of elderly based on the

United Nations’ charter. This discourse of the operational definition of ageing and

the values for the categories of age cohorts also differ marginally between the two

scholars. Like Bogue, Denise Eldemire has three age groups into which she

classifies the elderly. These are (1) young-old (ages 60 to 74 years); old-old (ages

75 to 84 years) and (3) oldest-old (i.e. 85 + years). Both researchers used the

1
  Donald Bogue (1999) used aged (age 75 – 84 years) to refer to what this paper calls old-old; 65
to 74 years to denote young-old and from 85 years and older to indicate oldest-old.
                                                                                  45


three groups because they represent the ‘stages of ageing’. The three ‘stages of

ageing’ are widely accepted in gerontology as indicators of the biological

transition which the elderly pass through, accompanied by progressive

physiological deterioration of the human body.

        Elderly patients are frequently afflicted with paroxysmal impairments of
       consciousness usually because they often have chronic medical disorders
       such as diabetes mellitus and hypertension and can also be on many
       medications (Ali, Christian and Chung, 2007, 376)


       Despite the claims made by a few medical doctors (Ali, Christian and

Chung), another medical practitioner wrote that “The majority of Jamaican older

persons are physically and mentally well and living in family units” (Eldemire

1995a, i). Professor Eldemire has extensively researched issues relating to the

Jamaican elderly for some time now, and as such she formulated a perspective of

this group that encompasses more than biology in examining elderly people’s

quality of life.   Therefore this speaks to the need for us to understand the

difference between biomedical and biopsychosocial models of wellbeing. The

implied issue within Eldemire’s monograph is the inadequacy of measuring

quality of life using only physiological status. Clearly, with elderly Jamaicans

physically and mentally well, it is safe to argue that their wellbeing is high, given

the old model of measuring quality of life (i.e. biomedical – using physical illness

or lack thereof). However, this measure is simplistic. Can we say in Jamaica that

the high crime rate, the death of loved ones, widowhood, unemployment,

retirement (separation from employment), insufficient financial resources and cost

of living, loneliness, lifestyle changes, dependence on family members or friends,
                                                                                 46


childless old people, and other psychosocial conditions will not affect the health

and wellbeing of the aged? This is answered in later Chapters. Before we begin

the discussion on wellbeing, or wellbeing of the aged, we need to address the

issue of population ageing.

       Functional Ageing

       Functional ageing is having to deal with one’s ability and capability to

carry out a physiological functioning – competence in executing a physical task.

One of the differences with this phenomenon is that each individual’s competence

is not determined at the same chronological ageing – and equally the biological

process of each individual is not necessarily the same, as people’s genes

predominantly explain what is likely to affect them and at what age. Hence, an

individual may not be to perform a particular task at a certain chronological age,

but his/her colleague at the same age may be able to execute the same function.

Within the same breath, the functional limitation of the same individual can

change based on a particular event, time, situation or mass.     For instance, a 90

year old man may be able to drive himself to the supermarket and purchase his

groceries - but he is not able to open his zipper to urinate.

       Using physical functioning for definition ageing (or ageing transition), an

individual who is 60 years old who is able to perform all physiological activities

without assistance as well as being able to run a mile, do miniature things like

threading a needle, combing his/her hair, clipping his/her finger and toe nails,

lifting his luggage or carrying a container of a particular weight, could be defined
                                                                                   47


as functionally young, whereas by using chronological ageing he/she would have

already shifted from young to old age.

       In a monologue with my PhD. Supervisor – Professor Denise Eldermire-

Shearer – she noted that although the World Assembly on Ageing uses the

chronological age of 60 years to mark the commencement of the ageing process –

which earmarks the transition from young to middle age to old age – this is not

necessarily the experience of each individual. Embedded in Eldemire-Shearer’s

perspective is the acceptance that the ageing transition is not a static chronological

valuation that we have formulated as the benchmark for ageing, as this is not

necessarily the same across ethnicity, genetic composition and traits, or gender of

individuals.

       In summary, ageing is accompanied by normal declines in function as body

cells undergo senescence. Age-associated disease is also increasingly evident. Non-

communicable diseases and pathological impairment manifest as morbidity, disability,

and loss of function among older persons. These factors combine to diminish the

capacity to continue to carry out Activities of Daily Living (e.g. eating, bathing,

dressing, toileting, transferring (walking) and continence) and Instrumental Activities

of Daily Living (e.g. using the telephone, shopping, managing medication and handling

finances). As the capacity to fulfil these functions declines, so does the ability to

maintain independence and to ‘age in place’. As early as 1987, Jette and Bottomley

provided substantial evidence of the magnitude of the increase of disability with age;

disability defined as needing help in accomplishing or inability to perform one or more

of the Activities of Daily Living or Instrumental Activities of Daily Living. Among
                                                                               48


persons 65-74 years, 5% had some level of disability with respect to the Activities of

Daily Living (ADL). The prevalence was slightly more than twice that proportion in the

75- to 84-year-old group (11.4%), and among those 85+ years, 35 % had disability with

regard to the ADL. The pattern was similar with regard to the Instrumental Activities of

Daily Living (IADL) where 40% of elders of 85 years of age or more required help

compared with 5.7% of those 65 to 74 years old (Jette and Bottomley 1987). As

functional loss or decline increases, the need for support services (intra-familial and

extra-familial) to age in place also tends to increase.
                                                                               49


                                  Chapter Three

                  Population Ageing: Historical and Global

       In the late 1800s (1884) an Englishman named Francis Galton, who was

both a mathematician and medical doctor, set out collecting data on ‘physical and

mental functioning’ of some 9,000 people between the ages of 5 and 80 years

(Erber 2005, 4), because of his interest in life expectancy and the state of older

people. This was not the first time that such an examination had been done as in

1835 Adolphe Quetelet published a text in which he discussed the physical and

behavioural features of people at different ages. Like his predecessor, Galton

wanted to understand the human life span, but this time from an empirical

perspective. The epistemology at the time was based on authority, tradition,

speculation and mere non-scientific observation. Thus in keeping with his interest

and training as a mathematician, Galton wanted some empirical basis on which to

formulate a position on the matter. Thus, he sponsored an exhibition that would

allow for the gathering of pertinent data that would aid empiricism. The data were

later analyzed by several scientists. The process culminated with a published text

in 1922 by G.S. Hall titled ‘Senescence: The Second Half of Life’. The findings

not only concurred with the existing literature in physiology, medicine, anatomy

and philosophy but provided empiricism to the knowledge that existed at that

time. This begs the question – what explains that fascination of man in seeking to

understand ageing, and in particular, his/her intrigue with the aged and their

wellbeing?

       Globally, changes in Public Health – namely sanitation and nutrition, have
                                                                                 50


added a substantial number of years to people’s life expectancies. This is evident

in the life expectancy for the world as it increased from 46.5 years in 1950-1955

to 66.0 years in 2000-2005 (i.e. a 29.5% increase in approximately 50 years) and

come the next 50 years it will increase by 13.1%, suggesting that the changes in

public health measures and standard of living have improved life expectancy

more in the early 5-decades than the next half a century. In addition, it is equally

attributed to the introduction of antibiotics in the treatment of patient care. This

goes further to explain the reason for the demographic transition toward an aged

population. Prior to its development and implementation, pestilence and pandemic

would have limited life expectancy to below 50 years, in many instances. During

the pre-20th centuries, death statistics were used to measure health status and

mortality along with quality of life, which explains why physicians would be

preoccupied with illnesses and diseases as a measure of how to effectively address

the wellbeing of people. This is captured in a study done by Mckeown (1965)

which found a correlation between mortality and diseases from data for 1851 to

1900. He found that reduced mortality for the period was primarily due to

infectious diseases such as tuberculosis, typhus, typhoid, cholera and smallpox

(Mckeown, 1965, p. 57).

       The 20th century has brought with it massive changes in typologies of

diseases, where deaths have shifted from infectious diseases such as tuberculosis,

pneumonia, yellow fever, Black Death (i.e. Bubonic Plague), smallpox and

‘diphtheria’ to diseases such as cancer, heart illnesses, and diabetes. Although

diseases have shifted from infectious to degenerate, chronic non-communicable
                                                                                   51


illnesses have arisen and are still lingering in spite of all the advances in science,

medicine and technology. Non-communicable diseases such as heart disease,

hypertension, and diabetes mellitus are among the leading causes of mortality in

the Caribbean region (McKenzie and Bell 2004). Although a shifting away from

communicable and infectious diseases has occurred in the region, there is a

remarkable increase in some communicable and infectious ones such as HIV,

sexually transmitted infections (STIs), and in one particular country in the region,

Jamaica, since 2004 there have been reports of an outbreak of malaria and cholera

in particular geographical areas. In spite of morbidities and mortality causing

pathogens (Mckeown 1965), non-communicable diseases are responsible for more

deaths in the region than communicable diseases.

       This situation also exists among the Jamaican population where Morrison

(2000) in an article entitled ‘Diabetes and Hypertension: Twin Trouble’

establishes that diabetes mellitus and hypertension have now become two

problems for Jamaicans and in the wider Caribbean. This situation was supported

by Callender (2000) and Steingo (2000), at the 6th International Diabetes and

Hypertension Conference, which was held in Jamaica in March 2000, each

identifying a positive association between diabetic and hypertensive patients -

50% of individuals with diabetes who had a history of hypertension evident in old

age had their origin in childhood and early adulthood. Eldemire (1995a) argues

that hypertension and arthritis are two diseases that plague the Jamaican elderly,

but that they would have begun in early adulthood. In 2006, 34.8% of new cases

of diabetes and 39.6% of hypertension were associated with senior citizens, i.e.
                                                                          52


ages 60 and over (PIOJ, 2007).    Accompanying this period of the ‘age of

degenerative and man-made illnesses’ are life expectancies that now exceed 50

years. (Table 3.1.1)
                                                                            53


Table 3.1.1: Life Expectancy at Birth for Selected Regions by Both Sexes: 1950-
2050 (in years)

                                         Period
Regions:

              1950-1955   1975-1980   2005-2010    2025-2030   2045--2050

World         46.6        59.9        66.5         71.1        75.1
More
developed     66.1        72.3        76.2         79.5        82.1
regions
Less
developed     41.1        56.9        64.6         69.6        74.0
regions
 Least
developed     36.1        45.9        52.5         59.9        66.5
regions

Africa        38.4        48.7        49.9         58.0        65.4

Asia          41.4        58.6        68.8         73.5        77.2

Europe        65.6        71.5        74.3         77.8        80.6
Latin
America and
Caribbean
              51.4        63.0        72.9         76.8        79.5

Caribbean     52.2        64.5        68.7         73.2        76.9

Central       49.1        63.5        74.8         78.3        80.3
America

South         52.0        62.6        72.7         76.6        79.4
America
Northern
America       68.8        73.3        78.2         80.5        82.7

Oceania       60.4        67.4        75.1         78.6        81.2
Source: World Population Ageing, 2007
                                                                                   54


          Generally when one speaks about population ageing, people begin to think

of reduced fertility and mortality and an increase in the population older than 60

or 65 years, and this is rightly so, but having given information on life

expectancy, the author will examine the feminization associated with population

ageing. While life expectancy for the globe has moved from 46.5 years from birth

during 1950-1955 to 66.0 years in 2000-2005, women continue to outlive men.

During 1950-1955, global life expectancy for women was 47.9 years, which was

2.7 years more than that of men in the same period, and during 2000-2005, the

difference increased by 4.2 years (which is a 55.6% increase). While the gap will

narrow come 2025 to 2030 and for 2045 to 2050, life expectancy will still have a

feminization to it as women will be still outliving men in the future (Figure 3.1.2).

Table3.1.2: World Life Expectancy by Specific Aged Cohorts and by Gender, 1950—
2050
Details         Age        1950-       1975-       2000-       2025-       2045-
                           1955        1980        2005        2030        2050
Life
Expectancy:
Total        Birth      46.5       59.8       66.0        72.4       76.0
             60         ..         ..         18.8        21.0       22.2
             65         ..         ..         15.3        17.2       18.2
             80         ..         ..         7.2         8.2        8.8
Female       Birth      47.9       61.5       68.1        74.7       78.5
             60         ..         ..         20.4        22.8       24.1
             65         ..         ..         16.7        18.7       19.9
             80         ..         ..         7.9         9.0        9.7
Male         Birth      45.2       58.0       63.9        70.1       73.7
             60         ..         ..         17.0        19.1       20.2
             65         ..         ..         13.8        15.5       16.4
             80         ..         ..         6.3         7.1        7.6
Source: Population Division, DESA, United Nations, in United Nations. 2004.
World Population Ageing 1950-2050. New York: United Nations, pp. 47
                                                                                   55



          Globally, apart from the feminization of life expectancy, what else is there

on population ageing? During 1950 to 1955, the rate of growth of the world’s

population was 1.8 percent and it was the same for the elderly population, and it

was 3.1 percent (72% more than the general growth rate for the world’s

population) for elderly 80 years and beyond (Table 3.1.4). The rate of growth of

different regions of the world can be analyzed in Table 3.1.5. On further

examination of the total growth rates (Table 3.1.4) and that of the aged

population, the population 80+ was increasing faster than the other elderly age

cohorts (Table 3.1.4).      Come 2045-2050, the rate of growth for the globe’s

population will be 0.5% while it would be 6 times more for elderly 80+ years.



Table 3.1.4: World Growth Rate (in %) by Aged Cohorts, 1950—2050

Details        Age        1950-        1975-       2000-       2025-       2045-
                          1955         1980        2005        2030        2050

Total                 1.8        1.7        1.2          0.8        0.5
           60+        1.8        1.8        1.9          2.8        1.6
           65+        2.1        2.6        2.3          3.1        1.6
           80+        3.1        2.7        3.8          3.9        3.0
Source: Population Division, DESA, United Nations, in United Nations. 2004.
World Population Ageing 1950-2050. New York: United Nations, pp. 49




          While people are living to age 70 years and beyond in many developed

and in some developing states (see Table 3.1.1), the question is - are they living a

healthier life – how is their wellbeing within the increases in life expectancy?

Alternatively, is it that we are just stuck on life expectancies and diseases as

primary predictors of wellbeing – or health status?
                                                                                 56


          Before the establishment of the American Gerontology Association in the

1930s and their many scientific studies on the ageing process (Erber 2005), many

studies were done based on the biomedical model, that is, physical functioning or

illness and/or disease-causing organism (Brannon and Feist 2004, 9). Many

official publications use either (i) reported illnesses and/or ailments, or (ii)

prevalence of seeking medical care for sicknesses, to speak of health status.

Some scholars have still not moved to the biopsychosocial predictors of health

status.    The biopsychosocial model incorporates the mind (i.e. psychological

conditions), along with biology and social conditions (i.e. culture, belief systems,

demographic characteristics). The dominance of the biomedical approach is so

strong and present within the twenty-first century, that many doctors are still

treating illnesses and sicknesses without an understanding of the psychosocial and

economic conditions of their patients. To illustrate this more vividly, a public

health nutritionist, Dr. Kornelia Buzina, says that “when used appropriately, drugs

may be the single most important intervention in the care of an older patient …

and may even endanger the health of an older patient …” (Caribbean Food and

Nutrition Institute, 1999:180)

          Global Issues on Ageing

          Even though the ageing process is lifelong, and although it may be

constructed within each society differently, many decades have elapsed since

Galton’s study on the health status of people. Despite changes in human

development and the shift in world population toward demographic ageing –

people living beyond 65 years (see ILO 2000; Wise 1997), the issues of the aged
                                                                                                                     57


and their health status have not taken front stage on the radar of demographers

unlike many other demographic issues. This is equally true for many Caribbean

nations. (See Figure 3.1.1 below).


                                                                         U.S.A
                                                                      Sw eden

               Major Area, region and country
                                                                      Germany
                                                                           Italy

                                                                        Europe
                                                                         Japan

                                                                          India

                                                                         China
                                                Latin America and the Caribbean

                                                                         Africa
                                                                         World

                                                                                   0   10     20     30      40
                                                                             Percentage of the Elderly (65+ years)

                                                                                       1950   2000   2050




       Figure 3.1.1: Selected regions and their percent of pop. 65+ years
       Source: United Nations 2005: World Population Prospects: The 2004 revision (page 20)




Again, as we mentioned earlier, global changes in Public Health have added
substantially more years to life expectancies, which is captured in the proportion
of elderly population come 2050 (Figure 3.1.1). Remarkably, the majority of the
world’s population come 2050 will be experiencing population ageing because
they would have had more people 65 years and older. Thus, there is a
demographic transition toward an aged population. In addition, this is attributed to
the introduction of vaccination, in particular to the discovery of penicillin.



       The issue of non-communicable diseases is not only a phenomenon

specific to Jamaica, but is equally a Caribbean challenge for policy makers. (See

Figure 3.1.2 below)
                                                                                                    58



              Trinidad &
               Tobago


               St. Lucia
                                                                             Acute respiratory
                                                                             infections
              Montserrat                                                     Hypertension


               Jamaica                                                       Diabetes
    Country




                                                                             Neoplasms
                Guyana

                                                                             Cardiovascular
              Dominica                                                       disease

                                                                             Cerebrovascular
                                                                             disease
              Barbados


              Bahamas


                           0        1       2        3       4        5
                           Ranked Order of 5 leading causes of mortality




Figure 3.1.2: Ranked order of five leading causes of mortality in the population 65 yrs and older, 1990
Source: Adopted from Caribbean Food and Nutrition Institute1999, 222
                                                                                                                      59




                      Stroke




                Heart disease
                                                                        Jamaica
                                                                        Female
     Diseases

                                                                        Jamaica Male
                     Arthritis

                                                                        Barbados
                                                                        Female
                    Diabetes                                            Barbados
                                                                        Female
                                                                        Barbados
                                                                        Male
                Hyp ertension



                                 0   20        40         60
                                     Percentage



Source: Figure taken from Caribbean Food and Nutrition Institute1999, 225.
Figure 3.1.3: Leading causes of self-reported morbidity in the population of seniors, by gender in Barbados and Jamaica.




                The data in Figure 3.1.3 shows that hypertension and arthritis are

morbidities that significantly plague both men and women in both Caribbean

countries. These chronic non-communicable diseases continue to interface within

the functional lives of the elderly, which mean that they are indeed living longer

but are faced with lowered wellbeing. In a study, generalizable to the Jamaican

population, Sargeant et al. (2004) reported that among persons aged 45-74 years,

the overall prevalence of diabetes was 22.4%, and much existing diabetes was

undetected.                Furthermore, among persons aged 45-74 years, the overall

prevalence of diabetes was 22.4%. Another study, based on the Jamaica Lifestyle

Survey 2001, documents the gender-specific prevalence of 66% (males) and 71 %
                                                                                 60


(females) among persons 65+years old (Wilks, 2007). These observations provide

further evidence of the eminence of non-communicable disease among older

persons in Jamaica. Ageing, though not a disease itself, may be accompanied by

increased frequency of disease.

       Secondly, if they are poor with proper and adequate health care coverage –

which could be private or public - the implications of the cost of care along with

daily living could add further stresses to the status of life experienced by the

elderly. Hence, living longer, although it is directly related to reduced mortality,

does not speak to the lifestyle changes and their positive influences on the

wellbeing of seniors. A study conducted by Costa, using secondary data drawn

from the records of the Union Army (UA) pension programme that covered some

85% of all UA, shows that there is an association between chronic conditions and

functional limitation – which include difficulty walking and bending, blindness in

at least one eye and deafness (Costa 2002). Among the significant findings is the

predictability between congestive heart failure in men and functional limitation

(i.e. walking and bending). Although Costa’s study was on men, this equally

applies to women as biological ageing reduces physical functioning, and so any

chronic ailment will only add further to the difficulties of movement of the aged,

be it man or woman.

       Some scholars have still not moved to the post-biomedical predictors of

health status. The dominance of this approach is so strong and present within the

twenty-first century, that many doctors are still treating illnesses and sicknesses

without an understanding of the psychosocial and economic conditions of their
                                                                                   61


patients.   Among those who have studied health are demographers. Is there a

difference between the approach of the other scholars (or scientists) and

demographers?

        Demographers have spent years studying mortality, and this has been used

as an indicator of life expectancy, such as the Coale and Demeny Model life

tables, and by extension health status. Life expectancy, on the other hand, has

always been viewed as the avenue through which demographers evaluate the

health status of people; as lived years is an indicator of living beyond certain

health conditions. Thus, health and wellbeing are tied to mortality patterns, which

is rightfully so, but this approach puts little emphasis on conditions that are likely

to decrease morbidity and thereby reduce mortality. With this being the case,

demographers have consumed more time assessing mortality, life expectancy and

morbidity because of their close approximation of wellbeing (or health status),

and this is similarly the case for Caribbean demographers.
                                                                                62


                               Chapter Four

  Population Ageing: Caribbean Demographic Trends, with Emphasis on

                                    Jamaica

       The Caribbean has been identified as the most rapidly ageing region of the

world. During the 1960 -1995 period, there was a 76.8% increase in the elderly

population (UN.org). The mean growth rate in the elderly population was 5.3%,

which was recorded for the period 1995-2000. The elderly as a percentage of total

population has been projected to reach about 15% by 2020, an almost four-fold

increase over the 1950 figure of 4.3% (PAHO, 1997).

       Demographic development in the Caribbean has taken a path similar to the

rest of the world (Population Reference Bureau 2007; STATIN 2006; United

Nations 2005c). Over the years, the movement has been such that mortality and

fertility have been declining, and the population 60 years and older has been

increasing proportionately more than the percentage increase in children (aged

less than 15 years) and/or the working age (15 through 59 years) population.

Jamaica as well as the rest of the Caribbean and Latin America is said to be at the

second stage of the demographic transition model (STATIN 2007). Cajanus

(1999) argues that what has changed since the 1960s in the Caribbean is the pace

of population ageing. He commented that “…demographic changes … began in

earnest in the 1960s” (p. 217) to describe what is known as demographic ageing

(or population ageing), which is a feature in many developed nations and some

developing societies. This is now a characteristic of some states in the Caribbean

like Jamaica, Cuba, Barbados, and Trinidad and Tobago.
                                                                                 63


       Several Caribbean countries, such as the aforementioned ones, could be

said to be approaching the third stage of the transition. The demographic

transition refers to the changes in population growth that are attributable to

transition from high to lower levels of fertility and mortality. So for countries to

be at the third stage of the transition, they would be experiencing population

ageing due to persistently low fertility, and even lower mortality. Like the rest of

the world, these changes also brought improvements in living conditions,

advancement in medicine, improvements in health care and discovery and use of

family planning measures.

       Statistics revealed that the total fertility from 1970 to 1975 for the world

was 4.49 and from 2000 to 2005, it fell to 2.65; whereas in Latin America and the

Caribbean between 1970 and 1975, it was 5.05 and this was further reduced to

2.55 from 2000 to 2005 (United Nations 2005c, xxi). As early as 2005, some

countries in the Caribbean had reached replacement level fertility. Total fertility

per woman reached in the Bahamas is 2.2, Barbados 1.5, Jamaica 1.93

(Demographic Statistics, 2006) and Trinidad and Tobago, 1.6 (United Nations

2006, 87-89). Barbados, Jamaica and the twin islands of Trinidad and Tobago are

currently experiencing below replacement level fertility (Total Fertility Rate –

TFR of 2.1 – United Nations 2000, 4). Since 2005, this has become a

demographic reality for many developed nations. The examples here are some

countries in Eastern Europe (TFR, 1.3) Southern Europe (TFR, 1.4) Northern

Europe (TFR, 1.7) and the United States, 2.0 (United Nations 2007; 2005c, xxi).

In addition, mortality in the Caribbean has been falling, coupled with increased
                                                                               64


life expectancies comparable with those in developed nations, beyond 71 years.

(United Nations 2005c, xxii), which according to Rowland (2003, 18) are

components within the demographic transition model.

       Return migration also plays a significant role in the ageing of the

Caribbean’s population. Jamaica, like Trinidad and Tobago and Barbados, is

experiencing the return of some of those who migrated in the 1950s-1960s, and

who are now elderly. In addition to return migration of aged Jamaicans, the

continuously high emigration of young people (Caribbean Food and Nutrition

Institute 1999) has further exacerbated population ageing in the country. From

the data reported in Table 4.1.1, at least 65 percent of the net migration is

accounted for by ages less than 30 years. Even though the negative net migration

of Jamaicans has been reduced by more than half over the last twenty years

(1988-2006), the pattern of those who emigrate has remained the same. However,

in ages 60 years and above, based on the available data in Table 4.1.1, there is

predominantly a net inflow of migration to Jamaica. This explains the return

migration of elderly Jamaicans within the context of net outflow at the younger

ages, which depletes the human resources of the country. Although the net

migration outflow of migrants from Jamaica, for each year, has never surpassed 1

percent of the total population for the year in question, the cumulative effect of

this over a long period is equally significant in the explanation of the nation’s

ageing population.
                                                                                 65


Table 4.1.1: Net External Migration of the Population by Selected Age Groups,
Jamaica: 1988-2006

                              Net Migration

Year                                  Age Groups
                     0 – 14          15 – 29     30 – 59           60+        Total

     1988            -7,857         -17,411        -12837          -802     -38,935
    1989           -8,508          -10,435          5,638        2,859      -10,446
    1990           -9,184          -15,021        -2,192           305      -26,092
    1991           -7,914          -12,296        -7,227         1,525      -25,912
    1992                *                *          *               *       -20,462
    1993           -8,068           -16,731        2,637           973      -21,319
    1994               *                *            *               *      -18,984
    1995           -1,822          -5065          -7,771         -3011       -17669
    1996                *             *              *              *       -18,096
    1997                *              *             *              *       -19,773
    1998                *              *            *               *       -20,133
    1999               *               *            *              *        -20,959
    2000                *              *            *               *       -21,834
    2001               *               *             *            *         -21,742
    2002               *              *              *             *        -23,160
    2003                *             *              *             *        -17,679
    2004            -4,209         -10,239        -5,786          2,365     -17,798
    2005               *             *              *              *        -17,169
    2006               *              *              *             *        -17,087
Source: Computation was done by Author from Demographic Statistics, various years.
* Missing data

       Therefore, many Caribbean countries began experiencing population

ageing since as early as in the 1950s and/or the 1960s. In 1950, 8.5 percent of

Barbados’ population was 60 years and older; Cuba, 7.3%; Suriname, 8.4%,

which was higher than 6.9 percent for the Caribbean and 8.2 percent for the

world. (Table 4.1.2 to Table 4.1.5). Jamaica’s population ageing, on the other

hand, did not begin until the 1960s (see Table 4.1.6), which coincides with

Eldemire 1997). Using the growth rate of the population for different age groups

as an indictor of ageing population, Jamaica’s population 65 years and over
                                                                                  66


doubled from 1960-1970 and 1943-1960, which only occurred in this age group.

Although Professor Denise Eldemire believes and uses the chronological age of

60 years and older to operationalize the elderly and the data below utilizes 65+

years, it should be noted that the general conclusion of population ageing between

both scholars is the same. It should be noted here that even though the author

believes, like Eldemire, that old age commences at 60 years, which is in keeping

which the United Nations’ operational definition of elderly (i.e. old age), the

Statistical Institute of Jamaica, like demographers, uses 65+ years. Based on the

records of statistical publications by the Statistical Institute of Jamaica, prior to

1991 the agency used 65 years as the benchmark of old age. This approach, I

believe, is due substantially to the fact that Professor Roberts, who was a

demographer, was the chief advisor to the organization. However, post-1991, the

Statistical Institute of Jamaica has incorporated 60 to 64 years as a part of its

publication on the elderly.

       However, in the Caribbean, the matter has recently begun to be of concern

(Caribbean Food and Nutrition Institute 1999, 192, 217). The reason for this

thrust is because of the rate of increase of this age cohort compared to the other

age cohort. By 2050, the population of people 60 years and older in some

Caribbean nations will more than double, while the young population (ages 0 to

14 years) would have been reduced by half.

       Some developing states such as Barbados, Trinidad and Tobago and

Jamaica are currently experiencing a shift toward an ageing population (see

Appendix IV). In 2007, all three Caribbean nations had in excess of 10 percent
                                                                              67


of their population ages 60 years and older. Barbados, on the other hand, has the

largest percentage of persons ≥ 60 years (13.2%).
                                                                                                                                        68


Table 4.1.2: Estimated or projected populations by Selected Age Groups of different Caribbean Nations: 1950, 1975, 2007 and 2050
(in %)
                  1950               1975             2007             2025                2050


               0-14yrs    60+ yrs    0-14 yrs   60+ yrs   0-14 yrs   60+ yrs   0-14 yrs   60+ yrs   0-14 yrs   60+ yrs
Country:

Barbados       33.2       8.5        31.5       13.6      18.4       13.6      15.4       25.3      14.7       35.9

Guyana         41.1       6.7        44.1       5.5       28.7       7.7       19.9       15.0      13.3       35.2

Jamaica        36.0       5.8        45.2       8.5       30.2       10.3      24.4       15.0      18.5       23.6

Suriname       40.0       8.4        47.6       5.8       29.5       9.2       23.3       15.4      16.7       27.6

Trinidad       40.4       6.1        38.0       7.6       20.7       11.4      19.2       20.2      16.6       32.5

Caribbean 38.6            6.9        39.9       8.1       27.1       11.1      23.0       16.4      18.6       24.8

Source: United Nations. 2007: World Population Ageing, 2007, and United Nations. 2005c: World Population Prospects: The 2004 Revision
                                                                                                                     69




Table 4.1.3: Rate of Growth for Selected Regions and Countries, Based on Certain Time Periods: 1950 to 2050 (in %)

Regions and/or
Countries                      1950-1955      1975-1980       2005-2010      2025-2030       2045-2050


World                          1.8            1.7             1.1            0.7             0.4
More developed regions         1.2            0.7             0.2            0.0             -0.1
Less developed regions         2.1            2.1             1.3            0.9             0.5
Least developed countries      2.0            2.5             2.3            1.9             1.3

Africa                         2.2            2.8             2.1            1.7             1.2
Asia                           2.0            1.9             1.1            0.6             0.2
Europe                         1.0            0.5             -0.1           -0.3            -0.4
Latin America &
Caribbean                      2.7            2.3             1.3            0.7             0.2

Caribbean                      1.8            1.5             0.8            0.4             -0.1
Central America                2.7            2.7             1.4            0.8             0.2
South America                  2.8            2.3             1.3            0.7             0.3
Northern America               1.7            1.0             0.9            0.6             0.4
Oceania                        2.1            1.5             1.2            0.8             0.4

Source: World Population Ageing, 2007
                                                                                                               70


 Table 4.1.4: Cuba: Selected Statistics of the Aged Population, 1899-2025

Detail                1899               1919         1950                  1980         2000         2025

 60+ (population,           4.6             4.8              7.3              10.8         13.4            22.1

          %)

   Median age          20.7yrs            18.7yrs          23.3yrs           24.4yrs      32.4yrs         38.6yrs

  Ages-Percent              100            100              100               100          100             100

      60-64             47.7               41.8             33.5              29.9         30.1            32.7

      65-69             19.4               20.9             26.7              25.2         22.5            20.0

      70-74             16.4               15.8             19.7              20.1         19.0            18.2

      75-79                 6.0             8.4             12.4              14.9         13.0            14.3

         80+            10.5               13.1              7.7               9.9         15.5            14.8

 Source: 1899 and 1919: Cuban Population Censuses; 1950-2025: United Nations, 1991, pages
 144-145 in R H. Castellón. 1994. Population Ageing in Cuba. Malta: International Institute of
 Ageing (United Nations – Malta), p. 25.



 Table 4.1.5: Cuba: Life Expectancy by Gender. 1950-1986

 Detail              1900     1950         1955     1960           1965       1970       1975       1980     1986



 Male – at birth     31.2         53.6     58.4      62.0            65.4       68.6      71.1      72.3     72.7

 Female – at birth   35.1         57.9     62.9      66.1            68.9       71.8      74.6      75.8     76.3

 Male – at 60                     15.1     15.1      16.0            16.9       17.7      18.8      19.4     19.5

 Female – at 60                   16.7     17.0      17.7            18.5       19.6      20.7      21.6     21.6

 Male – at 80                     4.8       4.9      5.0             5.2           5.7    6.3       7.5       7.2

 Female – at 80                   5.1       5.5      5.6             5.8           6.7    6.9       8.2       8.0

 Source: Quoted in R H. Castellón. 1994. Population Ageing in Cuba. Malta: International
 Institute of Ageing (United Nations – Malta) p. 32
                                                                                    71


Table 4.1.6: Rate of Growth of Selected Age Groups and of Total Population of
Jamaica, using Census Data: 1844-2050 (in %)

Year                     0-14            15-64            65+3             Total


1844-1861                *               *                *               0.87
1861-1871                 *               *                *              1.25
1871-1881                  *             *                *               1.25
1881-1891               0.94             1.07             -0.4            0.86
1891-1911               1.39             1.19             0.90             1.25
1911-1921               0.18             0.33             0.85             0.29
1921-1943               1.27             1.77             2.08             1.59
1943-19501              1.39             1.76             0.55             1.57
1950-19602              2.25             1.06             1.74             1.55
1943-1960               2.12             1.00             1.65             1.46
1960-1970               2.07             0.03             3.36             1.08
1982-1991               -0.32            1.04             1.18             0.55
1991-2001               0.33             1.46             1.43             1.08
2001-2006               -1.61            1.33             1.10             0.42
2005-2010               *                *                1.0**            0.4**
2025-2030               *                *                3.3**            0.0**
2045-2050               *                *                2.0**            -0.6**
Source: Computed by Author from Statistical Yearbooks and Demographic Statistics
            * Missing data
            ** Taken from the World Population Ageing 2007:309
1
 The figures for 1943 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
2
 The figures for 1960 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
3
 The rationale that explains the use of 65+ to represent the elderly is solely due to
the statistical data that are available prior to 1991. Before 1991, the Statistical
Institute of Jamaica’s operational definition for the elderly was 65 years and
older. Hence, their publication between 1844 and 1991 did not produce years for
60+. However, post 1992, the organization began providing data for both ages.
As such, the researcher used 65+ because he wanted to examine figures from
1844 to 2006.
                                                                                 72


       The issue of the ageing of a population cannot be simply overlooked, and

has far-reaching implications for labour supply, pension systems, health care

facilities, product demand, mortality, morbidity and public expenditure, among

other events. Ageing is not simply about mortality, fertility and/or morbidity.

The phenomenon is about people, their environment and how they must coexist in

order to survive. Ageing, therefore, is here to stay.       In order to grasp the

complexities of this phenomenon, Lawson’s monograph adequately provides a

summative position on the matter. She noted that:

       Actually, it is predicted (U.N.) that developing countries are likely to have
       an older generation crisis about the year 2030, that is, about the same time
       as most developed countries (Lawson 1996, 1)

       This demographic transition is not only promulgated by Lawson, but was

argued by Cowgill (1983) who believed that during the next half-century (2050),

there is a strong possibility that this transition will be an issue for some

developing nations. This implies that population ageing, which has been the

experience of many developed nations (Gavrilov and Heuveline 2003; Marcoux

2001; Lawson 1996), will be a reality for some lesser developed countries and

more developing regions in the future.

       Seniors cannot be neglected, as they will constitute an increasingly larger

percentage of total population and sub-populations in different regions than in

previous centuries (UN 2005; WHO 2005; Chou 2005; STATIN 2004; Apt 1999;

Caribbean Food and Nutrition Institute 1999a; Randal and German 1999; US

Census Bureau 1998; Eldemire 1995, 1994; European Foundation for the

Improvement of Living and Working Conditions 1993; Mesfin et al. 1987; Grell,
                                                                                  73


1987; National Health and Welfare 1982). According to Randal and German

(1999), the number of aged persons living in developing countries will more than

double come 2025, ‘reaching 850 million’. The Caribbean is not different, as

according to Grell (1987) the English-speaking Caribbean from the 1970 census

revealed that between 8.8 and 9.8 percent of the populace were 60 years and

older, a matter which Lawson noted had begun in Jamaica since the 1900s

(Lawson 1996, 1-37). From the figures presented in Appendix XIV (i.e. growth

rates in percentage of selected age groups), the author disagrees with Lawson that

population ageing began in the 1900s in Jamaica, but more specifically it started

in the 1960s.

       Demographic Trends: Jamaica

        The annual growth rate for the Jamaican population since 1996 has

always been less than 1.0%, and the figure for 2006 is estimated to be 0.5%

(Demographic Statistics 2006) which is lower than the global average of 1.2

percent (CIA 2007). In order to provide readers with a better understanding of

population ageing in Jamaica, we need to present statistics that can be used to

establish any trends, as well as to be able to provide a more detailed analysis of

this phenomenon. Jamaica’s elderly population (i.e. ages 60+ years) has increased

significantly since the mid 1960s (see Eldemire, 1997, 77), but based on the

statistical publications for the nation the author is unable to concur with Eldemire.

       Jamaica’s life expectancy at birth for males between 1879 and 1882 was

37.02 years and for females it was 39.80 years. Between 2002 and 2004 males

are expected to live for 71.26 years and females 77.07 years, which is a clear
                                                                                              74


indictor of demographic ageing (See Table 4.1.7, below). In order to grasp the

complexity of life expectancy, I will disaggregate the elderly population of the

society, using data from 1991 to 2001. An examination of 5-year age cohorts of

the elderly population in Jamaica revealed that 85+ years is the fastest growing

from the general elderly population (see Figure 4.1.1). Society is experiencing an

oldest-old population explosion never before seen in its history, and this points to

the gains made in public health measures, and improvements in the standard of

living of the general populace since the 20th century.


         50%


         40%


         30%


         20%


         10%


          0%
                    60 - 64       65 - 69        70 - 74       75 - 79        80 - 84   85+
                                               Age Group (yrs.)


       Compiled by author using data from the Statistical Institute of Jamaica (2003)

       Figure 4.1.1: Percentage change in the size of elderly age sub-groups, 1991-2001.

       Does this mean better quality of life or subjective wellbeing? Answers

will be given throughout this book, but an insight will be provided here, as a study

by Powell, Bourne and Waller (2007) found that the psychosocial wellbeing of

Jamaicans was moderately high (mean score = 6.8 out of 10). On examining this,

they found that the subjective wellbeing of those in the lower subjective social
                                                                                75


class had a minimal score (mean score = 5.8 out of 10) compared with those in the

upper class (mean score = 6.5 out of 10) and those in the middle class (mean score

= 6.8 out of 10) (Powell, Bourne and Waller 2007). Furthermore, of the sampled

population, 1,338 randomly stratified Jamaicans (69%), indicated that their

current economic situation was at most average, with 19% reporting that it was

bad. Can we say that a two-fold increase in life expectancy means better quality

of life?




Table 4.1.7: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004 (in yrs)
                            Average Expected Years of Life at Birth
Period:                     Male                         Female

1880-1882                   37.02                        39.80

1890-1892                   36.74                        38.30

1910-1912                   39.04                        41.41

1920-1922                   35.89                        38.20

1945-1947                   51.25                        54.58

1950-1952                   55.73                        58.89

1959-1961                   62.65                        66.63

1969-1970                   66.70                        70.20

1979-1981                   69.03                        72.37

1989-1991                   69.97                        72.64

1999-2001                   70.94                        75.58

2002-2004                   71.26                        77.07
Sources: Demographic Statistics (1972-2006) in Bourne (2007)
                                                                                76


Using the population pyramid for Jamaica, population ageing come 2050 will be

even worse than in 2007 (See Figure 4.1.2-4.1.4).


Pictorial of the population ageing in Jamaica, 2000 – 2050




Figure 4.1.2: Population pyramid of Jamaica by age and gender, 2000


From the U.S. Census Bureau, International Data Base, Jamaica’s population in
2000 showed a relatively young population, which is because of the broad base.
This triangular age profile is an indication of the high proportion of children,
which means that Jamaica in 2000 had high fertility and high mortality rates.




Figure 4.1.3: Population pyramid of Jamaica by age and gender, 2025
However, the young population that was observed in 2000, from all indications, is
                                                                                 77


shifting as the base of the age profile narrows and the middle expands. Within the
demographic transition, this is a representation where the young population is
falling and shifting toward the middle ages, and old type of profile.




Figure 4.1.4: Population pyramid of Jamaica by age and gender, 2050



        While the demographic transition is not necessarily as obvious in 2025 as

in 2050, Jamaica’s population profile will definitely be contracting at the base and

expanding at the middle and old ages. Such a profile is an indication of low

fertility and death rates. A careful look at the diagram reveals that come 2050 and

beyond, Jamaica’s oldest elderly will consist of substantially more females.

Using statistics for 1-decade (data on Jamaica – 1991-2001), I will provide a

synopsis of the ageing phenomenon at a glance in Figure 4.1.5.
                                                                                                                                                                                   78




50%


40%


30%


20%


10%


 0%
         0-4

               5-9

                     10 - 14

                               15 - 19

                                         20 - 24

                                                   25 - 29

                                                             30 - 34

                                                                        35 - 39

                                                                                  40 - 44

                                                                                            45 - 49

                                                                                                      50 - 54

                                                                                                                55 - 59

                                                                                                                          60 - 64

                                                                                                                                    65 - 69

                                                                                                                                               70 - 74

                                                                                                                                                         75 - 79

                                                                                                                                                                   80 - 84

                                                                                                                                                                             85+
-10%


-20%
                                                                                                                                              ©K. James 2008
                                                                       Age group (yrs.)


       Figure 4.1.5: Percentage change in age sub-groups as a proportion of total population
       between 1991 and 2001
       Compiled using data from the Statistical Institute of Jamaica (2003)




                 The “greying” of the Jamaican population is coming, and has already

       made its way within the society. From records of the Population Division of the

       United Nations, Jamaica’s population 60 years and older in 2050, using the

       medium variant, is likely to be 24% of the entire population, with 17.7% being 65

       years and older, compared to approximately 5.6% being 80 years or over (United

       Nations 2007a; 2005c).                                          These shifts indicate the presence of degenerative

       conditions at older ages, increased disability and diminished quality of life. The

       disparity in gender composition at older ages speaks to the higher morbidity in
                                                                              79


women and higher mortality for men (see Newman 2001, 8). With this inevitable

pending socio-economic and political challenge ahead, should demographers be

bothered with studying ageing and the wellbeing of the aged?

         Having established the issue of population ageing and the demographic

transition throughout the world, with particular emphasis on the Caribbean and

especially Jamaica, we will now venture to evaluate the crux of this paper,

wellbeing, and the wellbeing of aged Jamaicans. From the PLC reports published

by the PIOJ and STATIN, which         are primarily focused on the traditional

construct of health using the biomedical model, the researcher is putting forward

a position that if we wish to more effectively capture the wellbeing status of

Jamaicans, we must operationally expand the definition of health in such a

manner that it encompasses biopsychosocial factors such as – (i) biological; (ii)

psychological; (iii) social; (iv) economic, and (v) environmental conditions, as

this vulnerable group may even be worse off than reported, given the definition

chosen to measure health status. There are no published works on the general

wellbeing of the Jamaican elderly in which the researchers have sought to capture

a quality of life index which encompasses biological, sociological, psychological

and environmental conditions. It is within this general framework that this study

of the elderly is timely, as it seeks to expand an assessment of the subjective

wellbeing of aged Jamaicans from the perspective of a more comprehensive

model.
                                                                                80


                                Chapter Five

      AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                      WELLBEING OF THE ELDERLY

                                   PART ONE

        This present study examines the determinants of wellbeing of the

Jamaican aged. The research focuses on the determinants of wellbeing,

specifically on the aged, from the use of the biopsychosocial model. The rationale

behind this approach is embodied in the fact that physical functioning and frailty,

symptoms and diseases for medical attention do not constitute the only

components within the discourse of health and wellbeing. Grossman’s model

highlights socioeconomic conditions such as cost of health care, the educational

level of family members, household income, and biological conditions in the form

of stock of health (i.e. previous health status) and lifestyle practices (such as

exercise, non-smoking and low consumption of alcoholic beverages).

        Although Grossman’s model of measuring wellbeing stops short of

including psychological and ecological conditions, their inclusion in this study is

based on the Ecological Model and the Selective Optimization Model which

undoubtedly argue that the environment influences the wellbeing of aged people.

Furthermore, the Models show that the psychological state of aged persons

changes with years because of frailty and other physiological changes. Stress can

be used as a deciding psychological condition that drives other biomedical

illnesses.   This was put forward by a neuropsychologist from North Ridge

Medical Centre, U.S.A., speaking at the 6th International Conference on Diabetes

and Hypertension in Jamaica. Additionally, seeking to diagnose depression in a
                                                                                81


patient with hypertension and diabetes is problematic, as many of the conditions

overlap (see McCarthy 2000). Therefore, the Selective Optimization and the

Ecological Model have helped the researcher to identify other factors, such as the

environment, and positive and negative affective conditions that are likely to

affect the wellbeing of aged people, as well as variables which were already

identified by Grossman, and later modified by Smith and Kington. Thus, this

study will evaluate different factors aimed at influencing the wellbeing of elderly

Jamaicans, which are in keeping with the model as outlined in the theoretical

framework.

       In putting together these discourses, the writer sought to undertake a

mapping of the scholarly and policy landscape with the aim of developing

taxonomy in this regard. As this paper seeks to examine the wellbeing of the

Jamaican elderly, it will be done in the wider context of the demographic

transition that is ‘sweeping’ our world. One of the primary reasons for this paper

is that “Population ageing is changing the numbers of older persons in relation to

that of other age groups in the population in all regions of the world, with the

changes occurring more rapidly in the more developed regions...” (UNFPA 2002,

8). But there is still insufficient study on the elderly among us.

       In any wellbeing assessment of the elderly, we cannot only focus on

decomposing increased life expectancy or the causes of mortality, in an attempt at

understanding quality of life, as wellbeing goes far beyond those parameters

(Bourne, 2007, 2008a, 2008b, 2008c, 2008d, 2008e, 2009a, 2009b; Longest 2002;

Abel-Smith, 1994). Here the paradigm that is needed in practice, as against a
                                                                                 82


conceptual perspective, must be in keeping with the definition offered by the

WHO in the Preamble to its Constitution in 1948 that it must extend to the social,

psychological, economic and environmental conditions, and not merely biological

conditions.

       Rowland (2003), Preston et al. (2001), Newell (1988), and Shryock et al.

(1976) provided an extensive and elaborate model of life tables (Elo 2001) on

particular patterns from which they compute life expectancy.          Demographic

studies on life expectancy imply that mortality patterns explain people’s health

status (See Crimmins, Hayward and Saito 1994; Vaupel 1986; Pollard 1982), but

despite the procedures and the high applicability of those deterministic models in

projecting life span, the calculations lack socioeconomic and psychological

insight. Studies on mortality have shown that there is a high correlation between

patterns of death and health and/or life expectancy (See for example Vaupel and

Romo 2003; Horiuchi and Wilmoth 1998; Gage 1994). Furthermore, an article in

honour of Nathan Keyfitz’s 90th birthday, using calculus – mathematical formulae

by integration - shows that decomposing change in life expectancy finds that the

‘time derivative of life expectancy’ is a function of (1) the average rate of

improvements in mortality by the number of life-years lost and (2) that a

covariation exists between improvement in death and remaining life expectancies

(See Vaupel and Romo 2003, 201). Even though life expectancy is a good

explanation of people’s wellbeing, it does not speak to the quality of those years

lived by the individual. Hence, ‘hale life expectancy’ is an alternative technique

that bridges the gap between years lived (or to be lived), and years lived (or to be
                           83


lived) in ‘good’ health.
                                                                                84


       Healthy Life Expectancy

       One of the drawbacks to the use of life expectancy is its failure to capture

‘hale’ years of life. Traditionally when life expectancy is measured, it uses

mortality data to predetermine the number of years of life yet to be lived by an

individual, assuming that he/she subscribes to the same mortality patterns of the

group. The emphasis of this approach is on length of life and not on the quality of

those years lived. Hence changes in life expectancy are primarily due to mortality

movements, and imply changes to external conditions in the socio-biological

environment. These changes include public health, water and food quality, the

physical milieu, and technological/medical advancement. With all the

aforementioned conditions that have improved over the last century, increased life

expectancy in the world is not surprising to scholars. One way of evaluating

population ageing in the world or in any geopolitical space is ‘life expectancy’.

Today it should come as no surprise to people that many developing nations have

been experiencing increased gains in additional years of life for members of its

population in comparison to the 20th century.

       Associated with ageing are the high probability of increased dysfunctions

and the unavoidable degeneration of the body. This explains why it is germane to

analyze healthy life expectancy and not merely life expectancy. Healthy life

expectancy is defined as the number of years that an individual is expected to live

in ‘good’ health. Technological advancement is able to prolong life, but it is not

able to remove morbidity, or deterioration in the quality of lived years of the

individual. Thus, while life expectancy in the Caribbean is increasing and though
                                                                                    85


it is in keeping with the rest of the world, there is a simultaneous increase in

chronic diseases. This reality highlights the disparity between the quantity of

years lived and the quality of those lived years, due to sociopsychological

conditions- such as loneliness, bereavement, social support (or the lack of), low

self-esteem, low self-actualization and so on.

        In evaluating health or wellbeing, we must seek to examine more than just

the number of years that an individual is likely to survive, as we should be

concerned about the quality of those years. Even though life expectancy is an

indicator of health, the new focus is on healthy life expectancy. Based on the

Healthy People 2010, the new thrust is on increasing the quality of years of life.

In attempting to capture ‘quality of years lived’, in 1999 the WHO introduced an

approach that allows us to evaluate this, the ‘disability adjusted life expectancy’

(DALE). DALE does not only use length of years to indicate the status of health

and wellbeing of an individual or a nation, but it incorporates the number of years

lived without disabilities.

        DALE is a modification of the traditional ‘life expectancy’ approach in

assessing health. It uses the number of years lived as its principal component.

This is referred to as ‘full health’. In addition, the number of years of ill-health is

weighed, based on severity, as another component in the equation. This is then

subtracted from the expected overall life expectancy to give what is referred to as

years of hale life. Embedded in this approach is the adjustment of years lived in

‘ill-health’.
                                                                                86


       Having arrived at ‘healthy life expectancy’, the WHO has found that

poorer countries lost more from their ‘traditional life expectancy’ than developed

nations. The reasons put forward by the WHO are the plethora of dysfunctions

and the devastating effects of some tropical diseases like malaria that tend to

strike children and young adults. The institution found that these account for a 14

percent reduction in life expectancy from poorer countries and 9 percent from

more developed nations (WHO 2000b). This system is in keeping with a more

holistic approach to the measuring of health and wellbeing which this study seeks

to capture. By using the biopsychosocial model in the evaluation of the wellbeing

of aged Jamaicans, we will begin to understand factors that are likely to influence

the quality of lived years of the elderly, and not be satisfied with the increased

length of life of the populace. Looking at the life expectancy data for Jamaica,

the figure is 74.1 years for both sexes (Demographic Statistics 2006) but using

healthy life expectancy it is 65.1 years (WHO 2003).         This means that life

expectancy has been increasing at a faster rate than ‘healthy life expectancy’.

Therefore, Jamaicans are expected to spend some 9 years of their life in ‘poor

health’.

           Before any further meaningful discourse can take place herein, it is

imperative that we put forward some discussion on wellbeing, as this will allow

us to understand what we are examining, and the likely factors that may account

for the aforementioned changes.
                                                                                 87


                                 Chapter Six

      AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                      WELLBEING OF THE ELDERLY

                                   PART TWO
Wellbeing

Wellbeing is used interchangeably with quality of life in different scholarships,

and some intelligentsias have gone on to distinguish between the two constructs.

We believe, however, that there is a clear distinction between the aforementioned

phenomena, and that the ‘quality’ of one’s life affects his/her experienced

wellbeing. Embedded in our argument here is that one’s quality of life is more

narrow that the construct of one’s wellbeing. To illustrate this point we will put

forward a conceptualization offered by Ries and Murphy, “a quality of life is a

state of living in which you are in balance or alignment” (1999, 5). Embodied in

Ries and Murphy’s perspective is the operational functionality of quality of life,

which means an alignment with all the elements of this life which will afford one

the option of having a particular state of life – ‘quality of life’. Thus, we concur

with other scholars that there is a distinction between quality of life and

wellbeing, but in this book we will not make these dissimilarities.      However,

what is wellbeing? And how has wellbeing been operationally defined since

before the 1950s?

       The discussion did not begin with what constituted wellbeing, or how it

should be measured. Instead, the discourse before the 1950s was on health, which

was later expanded to become wellbeing. Men have always been concerned about

the status of their health, and living longer has equally been a fascination for
                                                                                  88


people everywhere.      With this in mind, they have sought healers, ‘obeah

medicine’, ‘miracle spa and water’, and have spent millions of dollars on healthy

life style practices.

        At one point in the annals of human beings, people sought to be cured

from spirits, as they believed that many of the physiological ailments of the day

were due to spirits entering the human body.         With this perspective, man’s

position on health was from a perspective of spirit – manifested in physical

dispositions. But, during 1,800 to 700 BCE – the time of the Babylonians and

Assyrians - they started placing emphasis on diseases, as these were interpreted as

proxy for punishment by the gods. This general perspective was the same for the

Ancient Hebrews between 1,000 and 3000BCE. Thus, the cosmology of health

across different cultures was that of physical dysfunctions, this being the hallmark

of God’s disapproval of humans’ behaviour. It was not until the late 1940s that

there was a thrust afoot to widen this longstanding tradition.

        After WWII ended in September 1945, a number of institutions were

formed to address particular concerns regarding life. These include the IMF, the

World Bank, the United Nations, and the WHO. Each of these entities had a

distinct function and their portfolio was to effectively police certain issues within

the world. In this book, we will not seek to provide a discussion on the World

Bank, the IMF nor the United Nations. It is not our intent to provide information

on the functioning of the WHO or any of its related institutions, but the use of its

name is within the context of its contribution to the current space of health, health

research and health operations, in particular wellbeing.
                                                                                89


       It was during the writing of the WHO charter, at its first convention (1946)

that a caucus at the event was formed, which later developed the current

conceptualization of health (or wellbeing). This was ratified two years later.

What constitutes health from that institution’s perspective? The concept of health

according to the WHO is multifaceted. “Health is a state of complete physical,

mental and social wellbeing and not merely the absence of disease or infirmity”

(WHO 1947, 1948; Wang 2005, 153; Brannon and Feist 2007, 10). From the

WHO’s perspective, health status is an indicator of wellbeing (also see, Crisp

2005). Crisp, however, believes and puts forward the position that such a

conceptualization was elusive, and could not be measured with any level of

accuracy as it was ‘too’ wide. This position brings into the discourse not only a

doubt about the definition of the WHO, but introduces ‘subjective’ in an

operational definition of health (or wellbeing for that matter).

       Some scholars like Crisp predominantly believe that wellbeing should be

objectively measured, which premise is laid out by the positivists in the social

sciences, in an attempt to model the soft science (social science) like the natural

sciences – economic determinism.        With this said, health or wellbeing was

operationalized using disease, a tradition which began in Ancient Hebrew times.

Using diseases to evaluate health or wellbeing, which is referred to as the use of

the biomedical model – using physical dysfunction – was aimed at establishing a

correlation between health and longevity, and health and development. Thus,

scientists became involved in this cosmology and extensive research and finances

were placed in this field. This means that for a number of centuries, scientists
                                                                                 90


believed and explored biomedical cosmology.

       It was at the start of the 20th century that the biomedical model was being

rivalled by an alternative paradigm, the biopsychosocial model. This was during

an era when infectious diseases were replacing non-communicable diseases.

Thus, diseases that once ravished humanity, like the black plague, smallpox,

tuberculosis, polio, cholera, measles and dengue were replaced by hypertension,

heart disease, diabetes and cancer, to name of few which are now prevalent in

humanity.

       Life expectancy has substantially increased since the 1900s, and people

are living longer with some of the aforementioned ailments. Thus, the focus of

health cannot be centred on the mechanistic results of the exposure to specific

pathogens that are disease-causing organisms, since this limits the discourse to

physical conditions, which explains our focus on the panacea to health research.

The antithesis of disease, that is, functionality and a balanced state or quality of

life, are what many people commonly use in the imagining of health (or

wellbeing). Humans are multidimensional, and so using a biomedical model for

the study of health is unidirectional, since it explains disease, pathology and

dysfunctions, but does not deal with health or wellbeing. Nineteen years after the

first expanded definition of health offered by the WHO, Dubos speaks of “the

states of health and disease [as] the expressions of the success or failure

experienced by the organism in its efforts to respond adaptively to environmental

changes” (1965, xvii). This emphasizes the dominance of the antithesis of

diseases in the measurement of health.      In addition, it speaks to the world’s
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obsession with diseases, disability and mortality in the study of wellbeing, which

is a clear indication that health must be expanded beyond dysfunction and

functionality, and must reflect a balanced state. Currently, the discourse on

wellbeing (or health) has shifted from dysfunction, physiological growth and

functionality, to wellbeing.

       Before we begin with a comprehensive discourse of the expanded

definition of wellbeing, we will re-examine the definition put forward by the

WHO - “Health is a state of complete physical, mental and social wellbeing, and

not merely the absence of disease or infirmity”, because it is an embodiment of

physical, social and mental wellbeing, in particular ”completeness”. Some

intelligentsia have explained the fundamentals of the WHO definition, when they

opine that “anything less than complete wellbeing is not health” (Buetow and

Kerse 2001, 74). It follows that any study of wellbeing must be all-inclusive (also

see Pacione 2003, 19), as this will be more in keeping with a multidimensional

human. There are scholars who have argued that, although not stated in the

WHO’s definition of wellbeing, embedded in this construct is the psychological

state, since any ‘complete’ health includes the environment, with people

influencing the milieu and vice versa (also see Dunn 1961, 4-5).     This explains

why, when people are asked ‘what constitutes their health’ they are able to give a

‘good’ sense of their health, which is more comprehensive than the objective

definition. No objectification of wellbeing is able to combine people’s emotions,

beliefs, temperaments, behaviours, situations, experiences and biases, with the

subjective evaluation of events impacting on the individual’s existence (Kashdan
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2004; Wheeler 1991). Furthermore, what objective valuation can serve as the

input for humour, happiness, joy, and contentment? There is no denial that the

aforementioned issues are directly related to wellbeing, and that they are primary

to an expression of wellbeing or health. Traditionally wellbeing was

conceptualized and operationalized primarily from an objective viewpoint, which

gave rise to the dominance of economic wellbeing. But any measurement of

wellbeing must embrace economic and non-economic conditions, as they both

impact on human existence (also see Sumner 2004). As intelligentsia we are

bastions of more than cosmology, since empiricism must override populist

positions, because science holds no bias. Within this context, we will examine the

various discourses on wellbeing, as this will provide a better understanding of this

book’s rationale for a composite approach to the measurement of wellbeing.

       Wellbeing for some scholars is a state of happiness – the status of life

satisfaction and positive feelings (see for example, Rojas 2005; Easterlin 2003;

Diener, Larson, Levine, and Emmons 1985; Diener 1984), satisfaction of

preferences, desires, health or prosperity of an individual (Diener and Suh 1997;

Jones 2001; Crips 2005; Whang 2005), or what psychologists refer to as positive

effects (Headey and Wooden 2004). Simply put, wellbeing is subjectively what is

‘good’ for each person (See for example, Crisp 2005). It is sometimes connected

with good health. Crisp offered an explanation for this, when he said that “When

discussing the notion of what makes life good for the individual living that life, it

is preferable to use the term ‘wellbeing’ instead of ‘happiness” (Crisp 2005),

which explains the rationale for this project utilizing the term wellbeing and not
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good health.

       In order to put forward an understanding of what constitutes wellbeing or

illbeing, a system must be instituted that will allow us to coalesce a measurement

that will unearth peoples’ sense of overall quality of life from either economic-

welfarism (see Becker et al. 2004) or psychological theories (Diener, Suh, and

Oishi, 1997; Headey and Wooden 2004; Kashdan 2004; Diener 2000). This must

be done with the general construct of a complex man. Economists like Smith and

Kington, and Stutzer and Frey, as well as Engel, believe that man’s wellbeing is

not only influenced by his biological state but that it is always dependent on his

environment, economic and sociologic conditions. Some studies and academics

have sought to analyze this phenomenon in a subjective manner by way of general

personal happiness, self-rated wellbeing, positive moods and emotions, agony,

hopelessness, depression, and other psychosocial indicators (Arthaud-day et al.

2005; Diener et al. 1999; Skevington et al.1997; Diener 1984).

       An economist (Easterlin) studying happiness and income found an

association between the two phenomena (Easterlin 2001a, 2001b), (also see

Stutzer and Frey 2003; Di Telli, MacCulloch, and Oswald 2001). He began with

the statement that “the relationship between happiness and income is puzzling”

(Easterlin 2001a, 465), and found that people with higher incomes were happier

than those with lower incomes – he referred to it as a correlation between

subjective wellbeing and income (also see, Stutzer and Frey 2003, 8; Rojas 2005).

He did not cease at this juncture, but sought to justify this realty, when he said

that “those with higher incomes will be better able to fulfil their aspirations and,
                                                                                94


other things being equal, on an average, feel better off” (Easterlin 2001a, 472).

Another scholar admits that a statistical relationship exists between income and

happiness (subjective wellbeing), but he went on to refine this, explaining that

the association is dependent on an individual’s conceptual referent for happiness

(Rojas 2005) – “…and as income increases so do total desires; therefore,

happiness does not necessarily increase with income” (Rojas 2005, 2). Using

regression analysis (ordered-probit technique), he had some weak R-Squared

coefficients.   However, what emerged from the finding was that R-Squared

coefficients increased based on the conceptual referent a person held. Rojas found

that people with an outer orientation compared to those with an inner orientation

in their conceptual referent had a high propensity to be happier with income.

Thus, the effect of income on happiness is greater for people who want to seize

the moment from life’s offerings, compared to those who accept their current state

(happiness is based on internal conditions – e.g. virtues, tranquil life, utopia,

stoicism), and by extension are satisfied therein. Wellbeing, therefore, can be

explained outside of the welfare theory and/or purely on objectification- objective

utility (See for example, Kimball and Willis 2005; Stutzer and Frey 2003).

       Whereas Easterlin found a bivariate relationship between subjective

wellbeing and income (also see Rojas 2005), Stutzer and Frey revealed that the

association is a non-linear one. They concretized the position by offering an

explanation that “In the data set for Germany, for example, the simple correlation

is 0.11 based on 12, 979 observations” (Stutzer and Frey 2003, 9). Nevertheless,

from Stutzer and Frey’s findings, a position association does exist between
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subjective wellbeing and income, despite differences of linearity or non-linearity.

       The issue of wellbeing is embodied in three theories – (1) Hedonism, (2)

Desire, and (3) Objective List.         Using ‘evaluative hedonism’, wellbeing

constitutes the greatest balance of pleasure over pain (See for example, Crisp

2005; Whang 2005, 154). With this theorizing, wellbeing is simply personal

pleasantness, which indicates that the more pleasantries an individual receives, the

better off he or she will be. The very construct of this methodology is the primary

reason for a criticism of its approach (i.e. ‘experience machine’), which gave rise

to other theories. Crisp (2005), using the work of Thomas Carlyle described the

hedonistic structure of utilitarianism as the ‘philosophy of swine’, because this

concept assumes that all pleasure is on par. He summarized this adequately by

saying “… whether they [are] the lowest animal pleasures of sex or the highest of

aesthetic appreciation” (Crisp 2005).

       The desire approach, on the other hand, is on a continuum of experienced

desires. This is popularized by welfare economics, as economists see wellbeing

as constituting the satisfaction of preference or desires (Crisp 2005, 7; Whang

2005, 154), which makes for the ranking of preferences, and assessment by way

of money. People are made better off if their current desires are fulfilled. Despite

this theory’s strengths, it has a fundamental shortcoming, the issue of addiction.

This is borne out by the possible addictive nature of consuming ‘hard drugs’

because of the summative pleasure it gives to the recipient.

       Objective list theory: This approach in measuring wellbeing lists items

not merely because of pleasurable experiences or ‘desire-satisfaction,’ but that
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every good thing should be included, such as knowledge and/or friendship. It is a

concept influenced by Aristotle, and “developed by Thomas Hurka (1993) as

perfectionism” (Crisp 2005).     According to this approach, the constituent of

wellbeing is an environment of perfecting human nature.        What goes on an

‘objective list’ is based on a person’s reflective judgement or intuition.      A

criticism of this technique is elitism (Crisp 2005), since an assumption of this

approach is that certain things are good for people. Crisp (2005) provided an

excellent rationale for this limitation, when he said that “…even if those people

will not enjoy them, and do not even want them”.

       In the work of Arthaud-day et al., applying structural modelling,

subjective wellbeing was found to constitute “(1) cognitive evaluations of one's

life (i.e. life satisfaction or happiness); (2) positive affect; and (3) negative

affect.” Subjective wellbeing, therefore, is the individual’s own viewpoint. If an

individual feels his/her life is going well, then we need to accept this as the

person’s reality. One of the drawbacks to this measurement is that it is not

summative, and it lacks generalizability.

       Studies have shown that subjective wellbeing can be measured on a

community level (Bobbit et al.2005; Lau 2005; Boelhouwer and Stoop 1999) or

on a household level (Lau 2005; Diener 1984), whereas other experts have sought

to use empiricism (biomedical indicators - absence of disease symptoms, life

expectancy; and an economic component - Gross Domestic Product per capita;

welfarism - utility function).

       Powell (1997) in a paper entitled ‘Measures of quality of life and
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subjective wellbeing’ argued that psychological wellbeing is a component of

quality of life. He believed that this measurement, in particular for the older,

must include the Life Satisfaction Index, as this approach constitutes a number of

items based on “cognitively based attitudes toward life in general and more

emotion-based     judgment”(Powell     1997).     Powell    addressed   this   two-

dimensionally, where those means are relatively constant over time, while in

seeking to unearth changes in the short run, ‘for example an intervention’,

procedures that mirror changed states may be preferable. This can be assessed by

way of a twenty-item Positive and Negative Affect Schedule or a ten-item

Philadelphia Geriatric Centre Positive Affect and Negative Affect Scale (Powell

1997).

         In a reading entitled ‘Objective measures of wellbeing and the cooperation

production problem’, Gaspart (1998) provided arguments that support the

rationale behind the objectification of wellbeing. His premise for the objective

quality of life is embedded within the difficulty as it relates to consistency of

measurement, when subjectivity is the construct of operationalization.         This

approach takes precedence because an objective measurement of concept is of

exactness as non-objectification; therefore, the former receives priority over any

subjective preferences. He claimed that for wellbeing to be comparable across

individuals, population and communities, there is a need for empiricism.

         Gaspart discussed a number of economic theories (Equal Income

Walrasian equilibria, objective egalitarianism, Pareto efficiency, Welfarism),

which saw the paper expounding on a number of mathematical theorems in order
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to quantify quality of life. Such a stance assumes that humans are predictable and

rational which means that we are objectively able to plan our future actions. The

very axioms cited by Gaspart emphasized a particular set of assumptions that he

used for finalizing a measurement for the wellbeing of man, who is a complex

social animal. The researcher points to a sentence that was written by Gaspart

that speaks to the difficulty of objective quality of life; he wrote, “So its

objectivism is already contaminated by post-welfarism, opening the door to a

mixed approach, in which preferences matter as well as objective wellbeing”

(Gaspart 1998).    Another group of scholars emphasized the importance of

measuring wellbeing outside of welfarism and/or pure objectification, when they

said that “Although GDP per capita is usually used as a proxy for the quality of

life in different countries, material gain is obviously only one of many aspects of

life that enhance economic wellbeing” (Becker et al. 2004, 1), and that wellbeing

depends on both the quality and the quantity of life lived by the individual (also

see Easterlin 2001). This is affirmed in a study carried out by Lima and Nova

(2006), which found that happiness, general life satisfaction, social acceptance

and actualizations are all directly related to GDP per capita for a geographic

location (see Lima and Nova 2006, 9). Even though in Europe these were found

not to be causal, income provides some predictability of subjective wellbeing,

more so in poor countries than in wealthy nations. (See Lima and Nova 2006, 11)

       It should be understood that GDP per capita speaks of the market

economic resources which are produced domestically within a particular

geographic space. So increased production in goods and/or services may generate
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an excess which can then be exported, and vital products (such as vaccinations,

sanitary products, vitamins, iron and other commodities) can be purchased, which

can improve the standard of living and quality of life of the same people over the

previous period. One scholar (Caldwell 1999) has shown that life expectancies are

usually higher in countries with high GDP per capita, which means that income is

able to purchase better quality products, which indirectly affect the number of

years lived by people. This realty could explain why in economic recession, war

and violence, when economic growth is lower (or even non-existent) there is a

lower life expectancy.      Some of the reasons for these justifications are

government’s inability to provide for an extensive population in the form of

nutritional care, public health and health-care services. Good health is, therefore,

linked to economic growth, which further justifies why economists use GDP per

capita as an objective valuation of standard of living, and why income should

definitely be a component in the analysis of health status. There is another twist to

this discourse, as a country’s GDP per capita may be low, but life expectancy high

because health care is free for the population. Despite this fact, material living

standards undoubtedly affect the health status and wellbeing of a people, as well

as the level of females’ educational attainment.

       Ringen (1995) in a paper entitled ‘Wellbeing, measurement, and

Preferences’ argued that non-welfarist approaches to measuring wellbeing are

possible despite their subjectivity. The direct approach for wellbeing computation

through the utility function, according to Ringen, is not a better quantification as

against the indirect method (i.e. using social indicators). The stance taken was
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purely from the vantage point that utility is a function ‘not of goods and

preferences’ but of products and ‘taste’. The constitution of wellbeing is based on

choices.   Choices are a function of individual assets and options. With this

premise, Ringen put forward arguments which show that people’s choices are

sometimes ‘irrational’, which is the make for the departure from empiricism.

       Wellbeing can be computed from either the direct (i.e. consumption

expenditure) or the indirect (i.e. disposable income) approach (Ringen 1995, 8).

The former is calculated using consumption expenditure, whereas the latter uses

disposable income.    Ringen noted that in order to use income as a proxy for

wellbeing, we must assume that (1) income is the only resource, and (2) all

persons operate in identical market places. On the other hand, the direct approach

has two key assumptions. These are (1) what we can buy is what we can consume

and (2) what we can consume is an expression of wellbeing. From Ringen’s

monograph, the assumptions are limitations.

       In presenting potent arguments in favour of non-empiricism in the

computation of wellbeing, Ringen highlighted a number of drawbacks to

welfarism. According to Ringen:

       Utility is not a particularly good criterion for wellbeing since it is a
       function not only of circumstances and preferences, but also of
       expectation. In the measurement of wellbeing, respect for personal
       preferences is best sought in non-welfarist approaches that have the
       quality of preference neutrality; …As soon as preferences are brought into
       it, the concept of wellbeing cannot but be subjective. (Ringen 1995, 11)


              The difficulties in using empiricism to quantify wellbeing have not

only been put forward by Ringen, as O’Donnell and Tait (2003) were equally
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forthright in arguing that there were challenges in measuring the quality of life

quantitatively. O’Donnell and Tait believed that health is a primary indicator of

wellbeing. Hence, self-rated health status is a highly reliable proxy of health

which “successfully crosses cultural lines” (O’Donnell and Tait 2003, 20). They

argued that self-reported health status can be used, as they found that all the

respondents of chronic diseases indicated that their health was very poor. To

capture the state of the quality of life of humans, we are continuously and

increasingly seeking to ascertain more advanced methods that will allow us to

encapsulate a quantification of wellbeing that is multidimensional and

multifaceted (Pacione, 2003). Therefore, an operational definition of wellbeing

that sees the phenomenon in a single dimension such as physical health (Steward

and King 1994), medical perspective (Farquhar 1995), or material (Lipsey 1999),

would have omitted indicators such as crime, education, leisure facilities, housing,

social exclusion and the environment (Pacione 2003; Campbell et al 1976) as well

as subjective indicators which cannot be an acceptable holistic measurement of

this construct. This suggests that wellbeing is not simply a single space; and so,

the traditional biomedical conceptual definitions of wellbeing exclude many

individual satisfactions, and in the process reduce the tenets of a superior

coverage of quality of life.

       One writer noted that the environment positively influenced the quality of

people’s lives (Pacione 2003, 20; Bourne, 2007; Bourne 2008a, 2008c); in order

to establish the validity and reliability of wellbeing, empirical data must include

issues relating to the environment. The quality of the environment is a condition
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utilized in explaining elements of people’s quality of life. Air and water quality,

through industrial fumes, toxic waste, gases and other pollutants, affect

environmental quality. This is directly related to the maintenance, or lack thereof,

of societal and personal wellbeing (Pacione 2003).

       Studies have conclusively shown that environmental issues such as

industrial fumes and gases, poor solid waste management, mosquito infestation

and poor housing are likely to result in physiological conditions like respiratory

tract infections (for example lung infection), and asthma.

       According to Langlois and Anderson (2002), approximately 30 years ago,

a seminal study conducted by Smith (1973, 2) “proposed that wellbeing be used to

refer to conditions that apply to a population generally, while quality of life

should be limited to individuals’ subjective assessments of their lives …” They

argued that the distinction between the two variables has been lost with time.

From Langlois and Anderson’s monograph, during the 1960s and 1970s,

wellbeing was approached from a quantitative assessment by the use of GDP or

GNP (also See, Becker, Philipson and Soares 2004), and unemployment rates; this

they refer to as a “rigid approach to the [enquiry of the subject matter] subject.”

According to Langlois and Anderson (2002), the positivism approach to the

methodology of wellbeing was objectification, an assessment that was highly

favoured by Andrews and Withley 1976, and Campbell et al., 1976.

       In measuring quality of life, some writers have thought it fitting to use

Gross Domestic Product per capita (i.e. GDP per capita) to which they refer as

standard of living (Lipsey 1999; Summers and Heston 1995; Hanson 1986).
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According to Summers and Heston (1995), “The index most commonly used until

now to compare countries' material wellbeing is their GDP      POP' .”   The United

Nations Development Programme has expanded on the material wellbeing

definition put forward primarily by economists, and has included life expectancy,

educational attainment (Human Development Reports, 2005, p. 341) and other

social indicators (Diener 1984; Diener and Suh 1997). This operational definition

of wellbeing has become increasingly popular in the last twenty-five years, but

given the expanded definition of health as cited by the WHO, wellbeing must be

measured in a more comprehensive manner than using material wellbeing as seen

by economists.

       Despite the fact that quality of life extends beyond the number of years of

schooling and material wellbeing, in general terms wellbeing is substantially

construed as an economic phenomenon. Embedded within this construct of a

measurement is the emphasis on economic resources, and we have already

established that man’s wellbeing is multifaceted. Hence, any definition of the

quality of life of people cannot simply analyze spending, the creation of goods

and/or services that are economically exchangeable, or the number of years of

schooling and life expectancy, but must include the psychosocial conditions of the

people within their natural environment.

       GDP is the coalesced sum of all the economic resources of people in a

certain topographical area, so this does not capture the psychosocial state of the

individual in attaining the valued GDP. By this approach, we may arrive at a

value that is higher than in previous periods, making it seem as though people are
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doing very well. However, with this increase in GDP, the single component is

insufficient to determine wellbeing, as the increase in GDP may be by (1) more

working hours, (2) higher rates of pollution and environmental conditions, (3)

psychological fatigue, (4) social exclusion, (5) human ‘burn out’, (6) reduction in

freedom, (7) unhappiness, (8) chronic and acute diseases, and so forth. Summers

and Heston (1995) note that “However, GDP POP is an inadequate measure of

countries' immediate material wellbeing, even apart from the general practical and

conceptual problems of measuring countries' national outputs.” Generally, from

that perspective the measurement of quality of life is therefore highly economic,

and excludes the psychosocial factors, and whether the quality of life extends

beyond monetary objectification.

       In developing countries, Camfield (2003), in looking at wellbeing from a

subjective vantage point, notes that Diener (1984) argues that subjective

wellbeing constitutes the existence of positive emotions and the absence of

negative ones, within a space of general satisfaction with life. According to

Camfield, Cummins’ (1997) perspective subsumed ‘subjective and objective

measures of material wellbeing’ along with the absence of illnesses, efficiency,

social closeness, security, place in community and emotional wellbeing, which

implies that “life’s satisfaction” comprehensively envelopes subjective wellbeing.

       Diener (2000) in an article entitled ‘Subjective Wellbeing: The Science of

Happiness and a Proposal for a National Index’ theorizes that the objectification

of wellbeing is embodied within satisfaction of life. His points to a construct of

wellbeing called happiness.
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       He cited that:

       People's moods and emotions reflect on-line reactions to events happening
       to them. Each individual also makes broader judgments about his or her
       life as a whole, as well as about domains such as marriage and work.
       Thus, there are a number of separable components of SWB [subjective
       wellbeing]: life satisfaction (global judgments of one's life), satisfaction
       with important domains (e.g., work satisfaction), positive affect
       (experiencing many pleasant emotions and moods), and low levels of
       negative affect (experiencing few unpleasant emotions and moods). In the
       early research on SWB, researchers studying the facets of happiness
       usually relied on only a single self-report item to measure each construct
       (Diener, 2000, 34).


       Diener’s theorizing on wellbeing encapsulates more than the marginalized

stance of other academics and researchers, who enlightened the discourse with

economic, psychosocial, or subjective indicators. He shows that quality of life is

multifaceted, and coalescing economic, social, psychological and subjective

indicators is more far-reaching in ultimately measuring wellbeing. This work

shows a construct that can be used to operationalize a more multidimensional

variable, wellbeing, which widens the tenet of previous operational definition on

the subject. From the theorizing of various writers, it is clear that wellbeing is

multidimensional, multidisciplinary and multispatial. Some writers emphasize the

environmental components of subject matter (Lui 1976; Pacione 1984; Smith

1973), from the psychosocial aspect (Clarke and Ryff 2000) and from a social

capital vantage point (Glaeser 2001; Putnam 1995; Woolcock 2001).

        Smith and Kington (1997), using H t = f (H t-1 , P m G o , Bt , MC t ED, Ā t , ) to

conceptualize a theoretical framework for “stock of health,” noted that health in

period t, Ht, is the result of health preceding this period (H t-1) , medical care

(MC t) , good personal health (G o) , the price of medical care (P m ), and bad choices
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(Bt) , a vector of family education (ED) and all sources of household income (Ā t ).

Embedded in this function is the wellbeing that the individual enjoys (or does not

enjoy) (see Smith and Kington 1997, 159-160).

       In seeking to operationalize wellbeing, the United Nations Development

Programme (UNDP) in the Human Development Reports (1997, 2000)

conceptualized human development as a “process of widening people’s choice as

well as the level of achieved wellbeing”. Embedded within this definition is the

emphasis on materialism in interpreting quality of life. From the UNDP’s Human

Development (1993), the human development index (HDI) “…is a normative

measure of a desirable standard of living or a measure of the level of living”,

which speaks to the subjectivity of this valuation, irrespective of the inclusion of

welfarism (i.e. gross domestic product (GDP) per capita). The HDI constitutes

adjusted educational achievement (E= a 1 * literacy + a 2 * years of schooling,

where a1, = 2/3 and a2 = 1/3), life expectancy (demographic modelling) and
                                     1-e
income (W (9y) = 1/ (1 - e) * y        ). The function W(y) denotes “utility or

wellbeing derived from income”.       This income component of the HDI is a

national average (i.e. GDP per capita, which is then adjusted for income

distribution (W*(y) = W(y) {1 - G}), where G = Gini coefficient). In wanting to

disaggregate the HDI within a country, the UNDP (1993) noted that data are not

available for many countries, which limits the possibility.

       An economist writing on ‘objective wellbeing’ summarized the matter

simply by stating that “…one can adopt a mixed approach, in which the

satisfaction of subjective preferences is taken as valuable too” (Gaspart 1998,
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111) (also see Cummin1997a, 2001, 2005), which is the premise to which this

paper will adhere in keeping with this multidimensional construct, wellbeing.

Wellbeing, therefore, for this paper, will be the overall health status of people,

which includes access to and control over material resources, environmental and

psychosocial conditions, and per capita consumption.

       Both demographers and medical scientists primarily rely on advanced

multivariate statistical techniques to establish the causality of particular variables

on health; and before predictability of the event is forecasted, variations in

wellbeing (or health) must be explained by each variable.
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                               Chapter Seven

     AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                       WELLBEING OF THE ELDERLY

                                 PART THREE

         Education, Income, Occupation and Employment

         Studies have analyzed and established a statistical relationship between

socioeconomic status (SES) and health conditions. Those inquires have found that

a strong association exists between SES, income (UNDP 2006; Roos et al. 2004;

Case 2001: Kawachi et at 1997; Smith and Kington 1997a, 1997b), occupation

(Hemingway, Nicholson, and Marriott 1997; McQueen and Seigrist 1982), and

education (Koo, Rie and Park 2004; Ross and Mirowsky 1999; Preston and Elo

1995).

         A group of demographers (Ross and Mirowsky 1999) sought to refine the

association between health status and education, by using ‘The Quantity Model’.

It was established that the number of years of schooling (i.e. The Quantity

Theory) was a crucial predictor of the health status of an individual (Ross and

Mirowsky 1999, 449 and 452).        This, they argued, is attained by access to

information, improved work and economic conditions, and an understanding of

the requirements for better health care and wellbeing (Ross and Mirowsky 1999,

446). Freedman and Martin (1999), using data from the 1984 and 1993 panels on

Survey of Income and Program Participation, narrowed their study more so than

Ross and Mirowsky by looking at the relationship between educational attainment

and the physical function of aged people. They found that there was an

association between the educational level and the physical functioning of people
                                                                                  109


65 years and over.

       Koo, Rie and Park (2004), using multivariate regression, went further than

Ross and Mirowsky’s work of mere association to that of causation. They

concluded that education was a predictor of increased subjective wellbeing (t

[2523] = 7.83, ρ value ≤ 0.001]. The sample size was 2529 randomly selected

adults residing in Seoul and Chunchum, with 956 males and 1573 females. The

ages of those who responded to the survey instrument (questionnaire) were from

43 to 102 years old. Thus, the findings are generalizable because of the sample

design. Roos et al.’s study (Roos et al. 2004) contradicts the significant

relationship between education and health status. They drew their sample from

two Canadian Provinces. The findings revealed that a marginal association exists

between education and mortality. Another survey using data from the Survey of

Income and Program Participation – data collected by the U.S. Census Bureau

1991, finds that trends in educational attainment are associated with particular

functioning such as seeing, lifting and carrying, climbing stairs and walking ¼

mile (Freeman and Martin 1999).

       Freeman and Martin’s work did not merely reflect an associative

relationship between educational attainment and health – defined as physical

functioning – but showed that it was a predictive one (see also Bourne 2008a).

Using logistic regression, the coefficient revealed that having more schooling is

predictive of functioning. The researchers found that “this consistently suggests

that having less than a high school education is associated with approximately

twice the odds [e.g. exp. (0.695) = 2.0] of having functional limitation in late life”
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which was compared to someone who has attained more than secondary level

education (Freeman and Martin 1999, 466); Ross and Mirowsky, on the other

hand, further refined education and its association with health status.

       As if education’s influence on health status was insufficient, Ross and

Mirowsky (1999) refined the discourse when they put forward a theorizing that

years of schooling influence health through choices, knowledge, and capacity of

the recipients. The researchers - using data from a 1995 survey on Aging, Status,

and the Sense of Control, representative of U.S households (some 2,593

respondents ages ranging from 18 to 95 years), found that it is the years of

schooling that expand human capital – skills, abilities and resources.

       According to Ross and Mirowsky (1999), education in and of itself opens

and develops particular skills and the knowledge base of individuals, which is the

catalyst for inquiry, reasoning and lifestyle changes. It is this empowerment

which shapes the health and wellbeing of the educated populace. From Ross and

Mirowsky’s work, it is not merely education that improves DALE lifestyle but

rather the number of years of schooling.

       They (Ross and Mirowsky) found that years of schooling are a predictor of

better health status (also see Headey and Wooden 2003, 16). From their literature

review, using quantity modelling, they argued that a clear predictive association

exists between years of schooling and health (Ross and Mirowsky 1999, 445),

which was corroborated by Lauderdale (2001).           This was supported by the

argument put forward by Ross and Morowsky that in comparison with those with

little schooling, the well educated are more likely to exercise and drink in
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moderation, as opposed to abstaining or drinking healthily (Ross and Mirowsky

1999, 446).

       Within our society, on an average, people 65 years and over tend to have

less education compared to those who are between 25 and 60 years (Palmore

1981, 150).    Palmore noted this in a study that was done by Harris (1975) in

which “63 percent of those 65 and over never graduated from high school,

compared with only 26 percent of those 18 to 64. As a matter of fact, some aged

acquire more education as they grow older; 5 percent of those aged 55-64 and 2

percent of those 65 and over were enrolled in courses in 1974” (Palmore 1981,

15). He compared the number of years of schooling of young people and aged

persons, and found that younger cohorts were more educated than their older adult

counterparts. But as these educated people move into the senior category, the

mean educational attainment of the aged populace will substantially improve over

previous years.

       Other scholars (Moore et al. 1997) agree that educational attainment

influences people’s health status. The rationale given for this position is that

education directly improves knowledge and access to information. Studies have

shown that people with low incomes or who have significantly shorter life

expectancies are less educated. According to Moore et al. (1997), Crimmins et al.

(1990) showed that life expectancy at age 65 for white women with more than 13

years of schooling is 19.8 years, compared with 18.4 for those with less than 9

years of schooling (p.134). A study by Prause et al. (2005) revealed a contrasting

finding to other studies presented earlier; they found that education does not affect
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SWB. This was refuted by a majority of the literature presented by the experts

themselves (Prause et al. 2005, 364). One of the advantages of more schooling is

its linkage to better jobs, which is a factor in providing higher income and the

tendency for one to improve his/her standard of living.

       In a series of papers presented to the Child Conference in Jamaica in 2008,

scholars found that educational attainments of youth (ages 15 to 25 years) did not

determine self-reported wellbeing, but the educational level of parents strongly

correlated with their children’s quality of life (Bourne and Cornwall, 2008;

Bourne, 2008; Bourne and Beckford 2008). An interesting finding which emerged

from the paper highlighted the fact that youth whose parents had tertiary level

education had greater subjective wellbeing, and that when the female

(parent/guardian) had university education the youth had greater wellbeing.

Embedded in this is that the number of years of schooling does make a difference,

but also that the level which the person reaches will not only expand his/her

personal horizon, but that of his/her child or household, suggesting that education

plays both a social and an economic role in the community. This is in keeping

with   the   aforementioned    scholarships   on   education   and    health,   and

multidimensional tenets on personal, community and society development.

        Based on the caption another germane factor is income and its association

with quality of life. Eldemire in an article captioned The Elderly- A Jamaican

Perspective noted that income and employment, among others issues, were

‘common problems’ affecting the quality of life of the elderly (Eldemire 1987a).

These are simply determinants of wellbeing of the Jamaican elderly.
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        In a survey conducted by Diener, Sandvik, Seidlitz and Diener (1993),

Diener et al. state that the correlation between income and subjective wellbeing

was small in most countries. Benzeval, Judge and Shouls’s (2001) study concurs

with Diener et al.’s work, in that income is associated with health status.

Benzeval et al. went further, as their research revealed that a strong negative

correlation exists between increasing income and poor health. Furthermore, it

was found that people from the bottom 25 percent of the income distribution self-

reported poorer subjective health by 2.4 times more than people in the fifth

quintile (Benzal and Judge 2001). One renowned scholar, Amartya Sen, argues

against the use of income and durable goods as a measure of wellbeing (Sen

1998). His rationale is tied to the difficulty of evaluating people’s intrinsic values

with the use of money and commodities. People’s value systems play a pivotal

role in how they perceive life, and by extension how they view their wellbeing.

Wellbeing is not simply a function of income, although income is able to afford

someone a ‘good life’. The UNDP’s (UNDP 2006) human development index

(HDI) is an indicator of wellbeing, and it is used for comparisons across

countries. The HDI uses national income (GDP per capita), health status and

education as causal predictors of wellbeing.

       The HDI assumes that increases in economic growth will directly result in

an improvement in health status (Easterlin 2004) and by extension the wellbeing

of peoples within a particular geographic space. If the construct between income

and health status holds true, then should poor countries not have a life expectancy

which is equally comparable with the developed countries? But this is not
                                                                               114


affirmative, as countries like Jamaica and Barbados have life expectancies that are

in excess of 70 years for both sexes, which is keeping with the values for many

societies in first world countries. Even though this income theory of explaining

health may seem applicable, health is not necessarily a function of income, but

rather a set of mechanisms that money can purchase, that can afford a certain

health – and not one single factor (see for example Case 2001), which includes

education, material possessions, durable goods, technology and so on. A group of

scholars, instead of using income, have used the possession of durable goods as

an indicator of wealth and income, and this has proved to be significantly

associated with health (Filmer and Pritchett 2001).

       In another study of 1440 elderly (72 and 77 year olds) from a Danish

survey in 1997, the findings revealed that seniors who were in the low-income

categorization had lesser physiological functioning and poorer psychological

wellbeing (Arendt 2005). Arendt, using ordered logistic models, finds that the

income effects are predictive.

       Marriott, Professor and Head of the Department of Epidemiology and

Public Health, and Director of the International Centre for Health and Society at

the University College of London, asked the question “Does money matter for

health?” He seeks to establish his theorizing through a conceptual framework of

using life expectancy and gross national product per capita of a country, by

examining the 1993 World Bank report based on data available from more than

100 countries. In support of his theorizing, he uses Angus Deaton’s theoretical

framework, which established that there is a nonlinear increase in the probability
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of dying with declining income. Marriott, in putting forward a conclusion on the

relationship between income and health, finds that when education is included in

the model with income, mortality is remarkably reduced (Marriott 2002, 40).


       From research findings, unhealthy living and poor working conditions of

people can be explained through levels of income and typology of occupation

(Lynch 2003). Lynch’s work uses data collected by the National Health Interview

Survey (NHIS) and National Health and Nutrition Examination Survey (NHNES).

The NHIS and NHNES were cross-sectional studies; NHIS sample size was

45,000 households (i.e. 878,317 persons between 1972 and 1993) compared to

6,373 used by NHNES. His findings reveal that there is a strong negative effect

in the probability of individuals who reported fair or poor health and their

educational level.    Lynch (2003, 309) argues that the relationship between

education and health is the most powerful association in social science studies,

and that it is still the most complex to clarify. Educational achievement is an

indicator of occupation types, and so in an investigation of the former on health

status, the latter must be taken into consideration.

       Occupation is a source of social status for many people, and this is typical

for aged people. In Jamaica, occupations such as Medicine, Academics, Law,

Managerial positions and Engineering are all professions of high calibre which

are associated with social clout. Owing to the fact that retirement diminishes this

status, the accompanying psychological losses will influence the wellbeing of

aged people, as they are no longer seen as productive beings because of old

adulthood (Palmore 1981, 16). A group of researchers, in analyzing occupation,
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reported that this variable is intricate, and its valuation is dependent on one’s

theoretical viewpoint on the importance of different aspects of one’s employment

existence (Adler and Newman 2002, 64). The researchers [Adler and Newman]

theorized that employed people are of a higher health status than their

unemployed counterparts. They added that aspects of this relationship are a

function of the ‘health worker’ effect, which suggests that there is evidence that

unemployment and the length of unemployment affect health status. In putting

forward their perspective in a vivid manner, Adler and Newman used scholarly

work to emphasize how the threat of unemployment and job insecurity can

influence the health status of people. They wrote “Ralph Catalano and Seth

Serxner found elevated rates of low birth weight in geographic locales threatened

with high rates of unemployment”.

       It is simplistic to determine from a single study that a sole variable is

responsible for a change in an event without a controlled experiment.          The

lowered birth weight of infants born to persons who were threatened with

unemployment or job insecurity may be incidental to inadequate pre-maternal

care, frustration with present management practices, insufficient nutrition,

environmental factors and current poverty, and while those stressors may result in

changes in blood pressure, they may also have a direct causal effect on the infant.

Thus, retirement is construed by some people as that avenue of refuge from some

of the psychosocial dynamics at work with which they were uncomfortable, but

which they had to tolerate while within the job space.

       Marcia Angel in Adler and Newman (2002) posited that income,
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education and occupation are complex determinants concerning their influences

on health. They offered the perspective that they are indirect determinants which

are proxies for other predictors. A study known as the SABE project (i.e. Health,

Wellbeing, and Ageing in Latin America and the Caribbean), which was

conducted in Barbados between December 1999 and June 2000, reveals that the

higher one’s level of education, the more likely it is for that individual to self-

report better heath status (Hambleton et al. 2005). This had a minimum sample

size of 1,500 respondents from seven cities in Latin America and the Caribbean,

including Bridgetown, Barbados. The respondents chosen are people who in

1999 were 60 years or older.           In respect of occupation typologies, the

professionals showed a higher degree of self-reported better health status than the

non-professionals and the semi-professionals (the odds ratios are 1.00 for non-

professionals, 1.08 for semi-professionals and 1.55 for professionals). Embedded

within this finding is the fact that professionals are 55 percent more likely to self-

report better health status than non-professionals, and 47 percent better health

status than semi-professionals.

         When socioeconomic status is assessed by income, education, or

occupation concerning health status, education is the most “basic socioeconomic

component since it shapes future occupation opportunities and earning potential”

(Adler and Newman 2002, 60). Winkleby and colleagues in Adler and Newman’s

study (2002) revealed that education was the only socioeconomic variable to

remain statistically significant out of education, income and occupation in relation

to their influence on cardiovascular disease (Adler and Newman 2002, 60).
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        Poverty and Financial Status

        There is an argument that poverty is higher among the aged populace than

young adults simply because elderly people are substantially outside of the labour

force, as the aged are likely to be the ones who are placed on retirement, which is

the reason for them receiving less income (Palmore 1981, 16). This was recorded

in a Cornel Study of Retirement that showed that retirees’ income declined to

56% of their pre-retirement income, which is a significant reduction in their

purchasing power, and by extension, their standard of living (Palmore 1981, 16).

He argued that tax advantages, housing subsidies, Medicare and income tax

exemptions offset this. This enables the aged to afford to maintain a particular

accustomed standard of living; but the social setting of the aged poor was not

accounted for in Palmore’s theorizing, and the widespread human suffering that

this has on the less educated aged poor. Eldemire (1994) alluded to this finding,

when she suggested that loss of financial resources may result in a change in

people’s lifestyle practices From Eldemire’s monograph, it can be construed that

senior citizens (i.e. elderly) are highly likely to see a change in their lifestyle as a

result of changes in their financial base. Warnes (1982, 4) encapsulated the

importance of resources to the quality of life of the elderly in the statement that

“…much if not more related to their social isolation or integration and to their

physical capacities as to their command of material resources”.

        In a paper entitled Poverty and Health, Murray (2006) argued that there is

a clear interrelation between poverty and health.           She noted that financial

inadequacy prevents an individual from accessing:           food and good nutrition,
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potable water, proper sanitation, medical care, preventative care, adequate

housing, knowledge of health practices and attendance at particular educational

institutions, among other things. The issue of resource insufficiency affects the

ability and capacity of the poor to access the quality of goods and services

comparable to the rich, who are better able to add value to wellbeing. This is

succinctly put forward by Murray in her monograph:

       Poverty also leads to increased dangers to health: working environments
       of poorer people often hold more environmental risks for illness and
       disability (Murray 2006, 923)

       The issue of poverty and health, according to Murray, is interlinked with

money. It is because of financial inadequacies that some people will not be able

to transform a risky physical environment into a safe place for people, in

particular the elderly. Studies exist that clearly show a relationship between

persistent, extended poverty and health, and even mortality (Lynch et al. 1997;

Menchik 1993; Zick and Ken 1991). If poverty is indisputably a primary cause of

malnutrition (Muller and Krawinkel 2005), then access to money plays a pivotal

role in the wellbeing of individuals. In order to grasp the severity of the issue of

money, we need to be brought into the recognition of poverty and health status.

According to Bloom and Canning (2003), ‘ill-health’ significantly affects poor

people. This further goes to explain the higher probability (5 times) of mortality

of the poor than the rich (World Health Organization 1999).

       Actuarial studies carried out in Canada have revealed that effective

planning is needed concerning social programmes for the elderly, otherwise

pension plans will not be able to meet their intended objective (Moore, et al.
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1997, 1). This discourse has taken on a new dimension, which is ‘who should

endow the cost of health care for the elderly, private or public institutions’?

Moore et al. (1997) added that the Canadian population has not only changed in

demographic composition concerning the elderly, but there are increasingly a

greater percentage of people 80 years of age and over (p.3).

       Psychological – Positive and Negative conditions

       In the pursuit of a precise operational definition of subjective wellbeing,

some scholars (see for example, Kashdan 2004; Diener 2000; Lyubomirsky 2001)

categorized the phenomenon into positive and negative psychological conditions.

They believed that happiness is as a result of a number of positive psychological

factors (also see Kim-Prieto, Diener, Tamir, Scollon, and Diener 2005; Easterlin

2003). A few scholars (see for example Liang 1984, 1985; Diener and Emmons

1984) have sought to make a distinction between the positive and negative

psychological conditions.

       In seeking to unearth ‘why some people are happier’, Lyubomirsky (2001)

approached the study from the perspective of positive psychology. She noted

that, to comprehend the disparity in self-reported happiness between individuals,

“one must understand the cognitive and motivational process that serves to

maintain, and even enhance happiness and transient mood’ (Lyubomirsky 2001,

239). Using positive psychology, Lyubomirsky identified comfortable income,

robust health, supportive marriage, and lack of tragedy or trauma in the lives of

people, as factors that distinguish happy from unhappy people, which was

discovered in an earlier study by Diener, Suh, Lucas and Smith (1999). In an
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even earlier study by Diener, Horwitz and Emmon (1985), they were able to add

value to the discourse of income and subjective wellbeing. They found that the

wealthy-affluent (those earning in excess of US 10-million annually) who self-

reported wellbeing (personal happiness of the wealthy affluent) were marginally

more than that of the lower wealthy.

       People’s cognitive responses to ordinary and extraordinary situational

events in life are associated with a different typology of wellbeing (Lyubomirsky,

King, and Diener 2005; Lyubomirsky 2001). It is found that happier people are

more optimistic and as such conceptualize life’s experiences in a positive manner.

Self-fulfilment and self-esteem will transform the individual into a happier person

who, in the long run, views life’s challenges and situations as experiences, and

thereby makes decisions a completely different way from someone who is

negative or pessimistic. Thus, goal achievement and self-actualization are critical

components in positivistic affective conditions, and they do directly influence

people’s wellbeing (Ross and Mirowsky 2008; Richman 2005; Fredrickson 2003;

Gross 1997).

       Studies revealed that positive moods and emotions are associated with

wellbeing (Ross and Mirowsky 2008; Leung et al. 2005), as the individual is able

to think, feel and act in ways that foster resource building and involvement with

particular goal materialization (Lyubomirsky, King, and Diener 2005).         This

situation is later internalized, causing the individual to be self-confident, from

which follow a series of positive attitudes that guide further actions (Sheldon and

Lyubomirsky 2006). Positive mood is not limited to active responses by the
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individual, but a study showed that “counting one’s blessings”, “committing acts

of kindness”, recognizing and using signature strengths, “remembering oneself at

one’s best,” and “working on personal goals” all positively influence wellbeing

(Sheldon and Lyubomirsky 2006; Abbe et al. 2003). Happiness is not a mood that

does not change with time or situation; hence, happy people can experience

negative moods (Diener and Seligman, 2002).

       Human emotions are the combination of not only positive conditions but

also negative factors (Watson et al. 1999). Hence, depression, anxiety,

neuroticism and pessimism are seen as a measure of the negative psychological

conditions that affect subjective wellbeing (Evans et al. 2005; Harris et al. 2005;

Kashdan 2004).      From Evans and colleague, Harris et al. and Kashdon’s

monographs, negative psychological conditions affect subjective wellbeing in a

negative manner (i.e. guilt, fear, anger, disgust); and positive factors influence

self-reported wellbeing in a direct way – this was        corroborated by a study

conducted by Fromson (2006); and by other scholars (McCullough et al. 2001;

Watson et al 1988a, 1988b). Acton and Zodda (2005) aptly summarized the

negative affective of subjective wellbeing in the sentence that says “expressed

emotion is detrimental to the patient's recovery; it has a high correlation with

relapse to many psychiatric disorders.”

       Marital status

       In wanting to analyze possible determinants of wellbeing of the elderly,

any assessment without marital status in respect to the elderly is missing a critical

aspect of the living arrangements of people. According to Moore et al. (1997,
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29), they concluded that people who reside with a spouse have a different base of

support in the event of poor health, as against those with other social

arrangements (Also see Smith and Waitzman 1994; Lillard and Panis 1996).

Cohen and Wills (1985) found that perceived support from one’s spouse increased

wellbeing (also see Smith and Waitzman 1994), while Ganster et al. (1986)

reported that support from supervisors, family members and friends was related to

low health complaints. The findings of Koo, Rie and Park (2004) revealed that

being married was a ‘good’ cause for an increase in psychological and subjective

wellbeing in old age. Smith and Waitzman (1994) offered the explanation that

wives were found to dissuade their husbands from particular risky behaviours

such as the use of alcohol and drugs, and would ensure that they maintained a

strict medical regimen coupled with proper eating habits (also see Ross et al.

1990; Gore 1973). In an effort to contextualize the psychosocial and biomedical

health status of a particular marital status, one demographer cited that the death of

a spouse signified closure of daily communication and shared activities, which

sometimes translated into depression that affected the wellbeing of the elderly

more than if they had invested in a partner (Delbés and Gaymu 2002, 905). They

pointed to a paradox that this was not necessarily the case among males. In

addition, it was found that the widowed have a less optimistic attitude towards life

than married people, which is not an unexpected result (Delbés and Gaymu 2002,

905) as the widowed person will no longer have the company of another partner

who is able to share and be a part of lived experiences.

       In Smith and Waitzman’s (1994, 488) literature review, they added that
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men’s gains from marriage were greater than those of women (also see Lillard

and Panis 1996, 313). This, then, explains why some scholars made the statement

that “many observers have theorized that married individuals have access to more

informal social support than do non-married individuals” (Smith and Waitzman

1994, 488), which explains the social reality of a higher quality of life in married

couples than ‘non-married’ individuals (also see Lillard and Panis 1996). Some

studies have shown that married people have a lower mortality risk in the hale

category than the ‘non-married’ (see for example Goldman 1993), and this

justifies why they take less life-threatening risks (Smith and Waitzman 1994;

Umberson 1987).

       Using a sample of 1,049 Austrians aged 14 years and over, Prause et al.

(2005) found that married individuals reported better subjective health-related

quality of life index (8.3 ) than divorced persons (7.6) or singles (7.7). Smock,

Manning and Gupta (1999) concurred with Prause et al. and other studies on the

fact that there is a direct relationship between being married (for females) and

economic wellbeing. Drawing longitudinal data from the National Survey of

Families and Households for 1987-1988 (NSHH1) and a follow-up survey

(NSFH2) of some 13, 008, a sample size of 2,665 females of 60 years and older

was used. Each study had a response rate of approximately 74 percent for NSFH1

and 82 percent for NSFH2. The research revealed that married women had

greater economic wellbeing than divorced females. It was found that females

who were remarried experienced the same degree of wellbeing as their married

counterparts, which was greater than that experienced by single females.
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       In Widowhood and Race, a study conducted by Elwert and Christakis

(2006), the findings revealed increased mortality upon bereavement for both

genders. Among the findings is that “For men, the hazard ratio is 1.17, indicating

a 17 percent increase in … death due to widowhood” (Elwert and Christakis 2006,

28). The study used a longitudinal and nationally representative dataset of elderly

married couples in the United States (N=410,272).            One potent tenet of

widowhood is the sociological fact that marital unions (including married and

common-law unions) that experience mortality of one of the two partners have a

decided influence on wellbeing through either psychological depression (i.e.

bereavement) or death of the surviving partner.         Baro (1985) in a PAHO

document titled Toward the Wellbeing of the Elderly declared that loneliness and

bereavement are determinants of the health status of the elderly.

       With the disparity in life expectancies of the sexes, oftentimes the woman

lives alone after the death of her spouse and may have difficulties accessing

friends and/or family for support, which in turn affects her quality of life (Havens

1995). The widow is likely to suffer from chronic and acute conditions, coupled

with the social isolation that results from the death of the partner, which usually

causes irreversible pathology. It should be reiterated that chronic illness can be

burdensome. The aged person is left with pain, frequent physician visits, and the

death of a beloved partner, all of which diminish the quality of life (Kart 1990).

       In studies conducted by Mastekaasa (1992) and Scott (1991) in Diener,

people who were married were found to be happier, so the “causal influence

between subjective wellbeing and marriage may work in both directions” (Diener
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1984). Lee, Seccombe and Shehan (1991) in Diener, noted that married couples

of either gender were found to be more contented than those who were not

married or even divorced or separated.

       Physical Exercise

       In an effort to present a cogent perspective on the value of physical

exercise and its influence on wellbeing, the researcher will use the American

Heart Association’s perspective that “Physical inactivity is a major risk factor for

developing coronary artery disease. It also increases the risk of stroke and such

other major cardiovascular risk factors as obesity, high blood pressure, low HDL

(’good’) cholesterol and diabetes” (American Heart Association, 2006). From the

diseases presented in the American Heart Association’s monograph, senior

citizens are likely to be affected by those conditions. The wellness community, in

wanting people to grasp the critical necessity of physical exercise, noted that

conditions such as stiff joints, breathing problems, skin sores, poor appetite and

mental changes can result from a lack of physical exercise. This is equally

endorsed by a longitudinal study conducted in England, which revealed that

“limitations in physical activities reduced quality of life (mobility -0.434, 95%CI

to -0.545)” (Netuveli et al. 2006, 360).

       In the SABE project, the report shows that people who exercise are 41

percent more likely to report a better health status than those who do not

participate in physical exercise. Of equal importance is the issue of body mass

and reported health status. The findings reveal that the respondents who had a

normal body index reported a 19 percent and 49 percent point better health status
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than the overweight and obese persons respectively.

       A study of 50 U.S states including the District of Columbia and Puerto

Rico in 2001, in which 120 non-institutionalized civilians aged 18 years and older

were contacted by way of telephoning using cross-sectional data, Rie (2004)

revealed that physical activities have been reduced in the case of senior citizens,

and this speaks to the difficulties of health conditions of this group of people.

Studies conducted by a group of researchers concur with the findings of other

studies, in that an association exists between physical exercise and quality of life.

A study by Paw et al. (2002) involving 217 seniors (i.e. 70 years and older), and

conducted between January and July 1997, revealed that a moderate association

existed between physical fitness (r=0.20) and general wellbeing.


       Fertility of the woman (Number of children had), and household size


       Some people argue from a purely economic perspective that the larger the

number of children a female has, the less likely it is that she will be healthy, and

this is from the premise of the socio-demographic conditions of child- rearing and

the socio-economic cost of the process. It may appear simplistic for one to

believe that associated with childbearing is the reality of the psychosocial

condition of the child and the family, and accompanying this are the biomedical

conditions which are usually accepted as given. On the contrary, some people

conceptualize childbearing as a vehicle of social mobility, and some consider their

offspring as material resources for their old age. Within the psyche of the poor,

poverty alleviation is seen through the investment in a child or children, similar
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to what some people see as investing in stocks, bonds, shares or other physical

assets.

          Studies from the RAND Center for the Study of Aging (1998) confirm

some of the epistemological beliefs of people in our society. The institute has

carried out research showing that “Childbearing has often been thought to have a

beneficial effect on a woman's health, primarily because it reduces the risk of

breast, endometrial, and ovarian cancer”, which concretize some of the common

sense thoughts of people on wellbeing and childbearing.        A crucial issue that

needs mentioning is how the RAND’s study highlights the non-socio-

demographic benefits of childbearing. Coupled with this is the frequency of

medical care which the new mother is likely to see, thereby ensuring that she

seeks health care.

          The study appears to be emphasizing the wholesale advantages of

childbearing, but researchers at RAND discovered that with ageing, many of

those advantages become detriments.          RAND’s findings reveal that “in

childbearing histories of women aged 50 and older, the research shows that

women who bore six or more children were likely to suffer poorer health in later

years than those women who had fewer children or no children at all” (RAND,

1998).     This study encapsulates the inverse relationship between number of

children and wellbeing in later years of life. The issue of poor health could also

be tied to certain fertility conditions (i.e. childbirth). An important finding that

arises from RAND’s study is how “women who lost a child during the first year

of its life and women who delivered their first child before they reached 18 years
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of age both had an increased likelihood of poor health at age 50 and beyond.”

Which gives rise to the next issue, how does the environment affect a pregnant

woman, the birth of a foetus, and also the health, and by extension the wellbeing,

of senior citizens?

       Although children are seen in some societies as a pension, which justifies

the poor having many of them, the household directly affects the wellbeing status

of a family, in that the more children a family has, the less that family will have

available to spend on each child (see Zimmer and Kwong 2003). Education,

which for many families means social mobility out of poverty, will be less likely

with larger families, as the income of the family will be spread thinner, and so

fewer resources will be expended on each child for social and economic

development. So even though the family may perceive children as an escape from

poverty (or an old age pension), this possibility will become increasingly less if

the children are not able to develop their capacity to attract high-end employment

when their parents reach retirement.       Keister’s (2003) study finds a strong

association between family size and wellbeing in adult years, which means that

for each additional child in a family, the share of resources available for that child

becomes significantly smaller.

       Gender

       The World Health Organization (2005) put forward a position that there is

a disparity between contracting many diseases and the gender constitution of an

individual.   One health psychologist, Phillip Rice, in concurring with WHO,

argued that differences in death and illnesses are the result of differential risks
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acquired from functions, stress, life styles and ‘preventative health practices’

(Rice 1998).

        Biomedical studies showed that there are gender specific diseases. The

examples here are prostate cancer (affecting only men) and uterine cancer (which

plagues only women). Rice believed that this health difference between the sexes

is due to social support.   According to Rice (1998), Rodin and Ickovics (1990)

this can be explained by epidemiological trends. Lifestyle practices may justify

the advantages that women enjoy compared to men concerning health status.

However, a survey done by Rudkin found that women have lower levels of

wellbeing (i.e. economic) than men (Rudkin 1993 222). This finding is further

sanctioned by Haveman et al. (2003) whose study reveals that retired men’s

wellbeing was higher than that of their female counterparts, because men usually

received more material resources, and more retirement benefits compared to

women of ages 65 years and older. Thus, with men receiving more than women,

and having more durable possessions than women, their material wellbeing is

higher in later life.

        The issue extends beyond those two types of chronic illnesses, as

Courtenay (2003) noted from research conducted by the Department of Health

and Human Services (2000) and Centers for Disease Control (1997) that from the

15 leading causes of death except Alzheimer’s disease, the death rates are higher

for men and boys in all age cohorts compared to women and girls. Embedded

within this theorizing are the differences in fatal diseases that are explained by

gender constitution (Seltzer and Hendricks 1989, 7), which Courtenay (2003)
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explained are due to behavioural practices of the sexes, and which explains the

fact that men are dying 6 years earlier than females (U.S. Preventive Services

Task Force, 1996).

       Other studies show agreement with Schoen et al. that men in general tend

to be more stressed and be less hale than females, and further argued that men can

use denial, distraction, alcoholism and other social strategies to conceal their

illness or disabilities (Friedman, 1991; Kopp, Shrabski, and Szedmak, 1998;

Weidner and Collins, 1993; Sutkin and Good, 1987). On the other hand, Herzog

(1989) in Physical and Mental Health in Older Women, using studies from a

number of experts, wrote that females had higher rates of depression than their

male counterparts. Could suicide be used as a proxy for depression? Numbers of

suicides are taken from death registers, and are likely to be under-reported for the

aged, since other illnesses are present, and may be substituted as the cause of

mortality (Herzog 1989).     Herzog noted that data on suicide and depression

yielded different results, and based on this fact, suicide cannot be used as an

indicator for depression.

       Males, nevertheless, are more likely to have heart diseases, gout and high

blood pressure than women. The WHO attributes this biomedical condition to

differences between the genders based on hormonal differentiations, social

networks and support, and cultural and lifestyle practices of the sexes, with which

Courtenay et al. (2002) concurred.

       Based on demographic models from abridged Life Tables, mortality is

different between the genders (Elo 2001). Generally, from the United Nations
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statistical databases, life expectancy for males is lower than for females. This is

particularly true for females in the old aged cohorts (United Nations 2004; Moore

et al. 1997). Moore et al. (1997) added, “Females’ life expectancies are likely to

remain above those of males [Elo 2001] for the foreseeable future, among both

the population as a whole and the elderly” (Moore et al. 1997, 12). Among the

justifications for the differential between life expectancy of the sexes is the link

between the health consciousness of women and their approach to preventative

care. Unlike women, men worldwide have a reluctance to ‘seek health care’

compared to their female counterparts. It follows in truth that women have

bought themselves additional time in their younger years, and it is a practice that

they continue throughout their lifetime, which makes the gap in age differential

what it is – approximately a 4-year difference in Jamaica.

       Elo (2001,106) in his discussion of the findings from the use of the vital

registration and the census dataset, postulating a reduction in infant and sex-

specific mortality, favoured women, and this will account for the disparity in life

expectancy between the sexes. Within the workings of this space, demographers

assume that we are in the third stage of the epidemiological transition (Omran

1971) in which health conditions associated with chronic conditions have replaced

infectious and parasitic illness as the dominant cause of death.

       Studies have revealed that the classification of many diseases affects a

particular gender. For particular chronic ailments, the primary contributor to death

is ischemic heart disease, which is substantially a man’s rather than a woman’s

disease. In a research project conducted jointly by the University of Michigan in
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the United States and the Bureau of Health Promotion in Taiwan on elderly

Taiwanese, between 1989 and 1993, of 4,049 people aged 60 years and beyond, a

number of socio-economic determinants were studied concerning mortality. From

the findings, femininity is negatively related to health conditions as opposed to

age, which is positively related to health conditions. (Zimmer and Martin 2003,

p.17).

         Embedded within Zimmer, Martin and Lin’s findings are the direct

relationship between ageing and health conditions, compared to an inverse

relationship existing between health conditions and females. It is clear from the

socio-economic factors mentioned previously that males who are older than sixty

have a higher propensity to be ill than females.

         It should be noted here that a study conducted by Franzini et al. (2004) on

native Mexicans in Texas found that females had worse mental and self-reported

health than their male counterparts, but not physical health. Franzini et al.’s work

contravenes many findings on gender and health status. Another study on the

socioeconomic determinants of mortality in two Canadian provinces found that

household income and education were significant in predicting mortality. When

gender was introduced within the model, the association dissipated (Roos et al.

2004).

         A study conducted by McDonough and Walters (2001) revealed that

women had a 23 percent higher distress score than men, and were more likely to

report chronic diseases than males (30%). It was found that men believed their

health was better (2% higher) than that self-reported by females. McDonough
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and Walters used data from a longitudinal study named the Canadian National

Population Health Survey (NPHS). The study was initiated in 1994, and data

were collected every second year for a duration of six years. The information was

taken from 20,000 household members who were 12 years of age and older.

        Research carried out by a group of economists (Headey and Wooden)

revealed that “…women are slightly more likely to report higher levels of life

satisfaction than men (mean=78.3, compared with 77.1 for men…” (Headey and

Wooden 2003, 14). Based on the nature of the study, ‘…subjective wellbeing and

ill-being’, the reported wellbeing (measured by life satisfaction) of women is

higher than that of men, but males have greater financial wellbeing than females

(Headey and Wooden 2003, 16).

       HIV/AIDS and the Elderly


       The issue of HIV/AIDS is not solely limited to infected individuals, whose

numbers are substantial between 15 and 24 years (UNAIDS 2004), but the elderly

who will be increasingly asked to support their infected children and other

members of the family. Instead of being the socio-financial support for their

children and other household members, the aged populace will be needed to

absorb the stress of loved ones in addition to their psychosocial and demographic

challenges. According to Knodel et al.’s (Knodel et al. 2001, 1320) study carried

out in Thailand, “59 percent of those who died of an AIDS-related disease co-

resided with a parent at the terminal stage.”    This implies that the aged are

expected to perform caretaking duties. With this social reality, the aged person’s

wellbeing will be affected in a two-fold manner. Firstly, the aged parents are
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expected to care for a dying loved one; and secondly, they are forced to absorb the

stress of this arrangement with the biological and psychosocial conditions of their

ageing organism. In order to understand the stresses of this situation on the aged,

we need to analyze it within the context of the cost and duration of care for the

elderly and the AIDS patients. This can be supported by a study that revealed that

longstanding ailments do diminish quality of life (Neteveli et al. 2006).

       Globally, regionally and nationally, the core for HIV/AIDS infected

candidates is between 15 and 55 years, and these are likely to be the children of

many aged people. Therefore, the social support system that the elderly would

expect is highly likely to be reverted to the children. Day and Livingstone (2003)

found that social support is an effective coping mechanism to deal with stress.

From this established theory, the potential stressors that will be levelled against

the elderly will automatically expand.

       A longitudinal research project which was conducted between 1991 and

1994 on households drawn from North-western Tanzania compared and

contrasted the body weights of some elderly individuals prior to and post the

deaths of a “prime-age adult” in the household.         According to Dayton and

Ainsworth (2004), the findings indicated that the seniors with the lowest physical

wellbeing (measured using body mass index, BMI) were those in poor families

that had not experienced a household adult death in the survey period. The BMI

for the elderly was less after the death of a loved one than before the death of the

household member. Another revelation from the study was the increased time

spent by the elderly in household chores preceding the adult’s death, and
                                                                              136


reduction in waged employment.

       In the event that the HIV/AIDS virus does not infect the children of the

elderly, or other household members, UNADS (2004) reported that less than five

percent of them are infected by the epidemic. This social reality within the

financial constraint of the family typology will become a psychosocial stress for

the elderly. The issue of stress is a determinant of wellbeing as regards the

HIV/AIDS virus.      Lazarus and Folkman (1984) conceptualized stress as a

“relationship between the person and the environment that is appraised by the

person as taxing or exceeding his or her resources and endangering his or her

wellbeing” (p.19).

       With the prevalence and incidence rates of HIV/AIDS, there is a demand

on the aged populace to cope with such a social setting. Coping is embedded in

an individual's cognitive, affective, and behavioural efforts to manage specific

external and/or internal demands (Crocker, Kowalski, & Graham 1998; Lazarus

1999). Studies have shown the positive association between coping and

wellbeing; see for example, Paragment 1997). Epping-Jordan, et al. (1994) did a

study on coping and health (also see Paragment 1997), using a sample of 66

cancer patients diagnosed with a variety of different types of cancer including

breast cancer, gynaecologic cancers, haematological malignancies, brain tumours

and malignant melanoma. The findings revealed that the relationship between

coping and disease progression demonstrates how the relationship between coping

and health is ultimately quite complicated.

       The elderly need to cope with the discrimination, the social exclusion, and
                                                                              137


the psychosocial and financial responsibility of the infected close family member,

in addition to dealing with personal infection within an aged body and the

corresponding demands.

       Rogers (1995) in a study entitled “Sociodemographic Characteristics of

Long-lived and Healthy Individuals” cited that many factors account for long

lives. Rogers’ study was based on secondary data collected by the US Department

of Health and Human Services in 1988, and called The 1984 National Health

Interview Survey. The sample size was 15,938 individuals aged 5 and older. The

findings revealed that females who walk are expected to live 7.5 years more than

males, while females who are physically incapacitated are expected to live 5.5

years more when compared to males. There was association between age, sex,

income, education, physical health, social network participation and emotional

wellbeing and perceived health (Rogers 1995, 41). He wrote “. . . death is more

likely to occur among those who are older, male, less educated, and with

disabilities, chronic conditions, and perceived poor health” (Rogers 1995, 46).

One of the reasons for elderly people attending church is because of the social

networking that this institution provides them.

       Religiosity

       A number of scholars have said that religion is associated with wellbeing

(Krause 2006; Jurkovic and Walker 2006; Wiegand, and Weiss 2006; Ardelt

2003; Willits and Crider 1988; Witter, Stock, Okun and Haring 1985; Graham et

al. 1978) as well as low mortality (House, Robbin and Metzner 1982). Religion is

seen as the opiate of the people from Karl Marx’s perspective, but theologians, on
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the other hand, hypothesize that religion is a coping mechanism against

unhappiness and stress (also see Wiegand, and Weiss 2006). According to Kart

(1990), religious guidelines aid wellbeing in that they restrict behavioural habits

which are health risks, such as smoking, drinking alcohol, and even diet.

       The discourse of religiosity and spirituality influencing wellbeing is well-

documented (Frazier et al. 2005; Edmondson et al. 2005; Moberg 1984; Graham

et al. 1978). Researchers have sought to concretize this issue by studying the

influence of religiosity on quality and life, and they have found that a positive

association exists between the two phenomena (Maskelko and Kubzansky 2006;

Franzini et al. 2004). They found that the relationship was even stronger for men

than for women, and that this association was influenced by denominational

affiliation. Graham et al.’s (Graham, et al. 1978) study found that blood pressure

for highly religious male heads of households in Evan County was low. The

findings of this research were not changed when controlled for age, obesity,

cigarette smoking, and socioeconomic status. A study on the Mormons in Utah

revealed that cancer rates were lower (by 80%) for those who adhere to Church

doctrine (Gardner and Lyon 1982a, 1982b) as opposed to those with weaker

adherence.

       In their study of 147 volunteer Australian males between 18 and 83 years

of age, Jurkovic and Walker (2006) found a high stress level in non-religious as

compared to religious men.       The researchers, in constructing a contextual

literature, quoted many studies that have made a link between non-spirituality and

“dryness”, which results in suicide. Even though, Jurkovic and Walker’s research
                                                                                139


was primarily on spiritual wellbeing, it provides a platform that can be used in

understanding the linkages between the psychological status of people and their

general wellbeing.     In a study which looked at young adult women, the

researchers found that spirituality affects the physical wellbeing of its populace

(Edmondson et al. 2005). Embedded within that study is the positive influence of

spirituality and religion on the health status of women. Edmondson et al.’s work

consisted of 42 female college students of which 78.8 percent were Caucasian,

13.5 percent African-American, 5.8 percent Asian and 92 percent were non-

smokers.

       Cox and Hammonds (1988) found that there is a positive relationship

between religiosity and wellbeing in the elderly; this was also corroborated by

Edward and Klemmack (1973), Hummer et al. (1999) and Spreitzer and Synder

(1974) in separate studies on the same space. Cox and Hammonds, in their

abstract, put forward the perspective that all past studies that have analyzed

religiosity and life satisfaction came to the same conclusion – which is that

individuals   who    attend   church   experience a greater      life satisfaction.

       According to Cox and Hammonds (1988), Guy, in a study on the discourse

of religiosity and life satisfaction, found that the group with the highest score on

the measure of life satisfaction was that which reported the most frequent church

attendance. Other research on the same space agreed with Guy, and Cox and

Hammonds (1988) that religiosity was a determinant of life satisfaction

experienced by the elderly (Markides1983). Cox and Hammonds stated that this

space in the discipline of gerontology has a high degree of scientific bias, as
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scientists are less likely to reflect the secular attitudes of the public. In addition to

the few longitudinal studies on the matter, Cox and Hammonds (1988, 47) argued

that all interpretations of the results and conclusions must be used cautiously.

        In a study conducted by Frazier et al. (2005) exclusively on African

American older people, they found that several multidimensional measures of

religiosity were associated with psychological wellbeing. Kail and Cavanaugh

(2004, 584) captured the experiences of seniors and how religion enhances their

survivability, when they said that "...older adults who are more involved and

committed to their faith have better physical and mental health ..." When asked

'how you deal with the living', respondents listed among coping strategies

spirituality (Kail and Cavanaugh 2004). From studies analyzed earlier, spiritual

support is a mechanism used in coping with life's challenges, as the church offers

a social support system and this is a mantle of hope. Religiosity is a determinant

of the health status of people, and more so for seniors as they continue to grapple

with loss of spouse, work and other psychosocial and biological conditions.

        Violence and fear of criminal victimization

        The statistical association between age and fear of crime is well studied.

“Fear of criminal victimization” (Franzini et al. 2004; Harriott 2003) in our social

space is also another factor which influences the psychosocial state of people.

According to Harriott (2003, 36) “the effects of the fear of criminal victimization

usually extend beyond altering the psychological states of individuals to

influencing their behavioural patterns.”       He added, “It is simply intended to

indicate the wide scope of the impact of the fear of crime, its effect on the quality
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of life. . .” Franzini et al. concurred with Harriott that fear of victimization is

negatively associated with physical and mental health. Harriott mentioned an

issue that has implications for quality in life of Jamaica, in particular the

vulnerable elderly, when he said that “Given the high density and long duration of

this violence … the Jamaican population has been gripped by a high level of

anxiety and fear of criminal victimization” (Harriott 2003, 35). This justifies the

strong association between physical vulnerability and fear of victimization.

Physical vulnerability was categorized based on sex and age.

       Harriott’s sample was 1,340 Jamaicans. He used a probability-sampling

technique, with a sampling error of 3% and a response rate of 96%. Harriott

(2003, 42) found that 40% of the sample regarded themselves as being highly at

risk, and exhibited high levels of ‘worry’ about criminal victimization; those who

were least at risk indicated that they were most fearful; 31% of the victims

expressed serious worry in regard to being murdered whilst 24% of the non-

victims had the same ‘worry’, and a strong direct relationship existed between

physical vulnerability and the fear of victimization.


       Despite the Caribbean, in particular Jamaica, not presently experiencing

the level of conflicts found in Cambodia, Sierra Leone and other countries in

Africa, the degree of conflicts that do arise in certain inner cities in the island may

result in psychological trauma for the aged. The periodic violence in August

Town, Denham Town, Grants Pen, Warehouse et cetera does affect the aged as

regards their visiting health professionals for care. Embedded within the conflicts

are the psychosocial conditions (anxiety, loss of loved ones, depression et cetera)
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that are experienced by the aged. If the aged ARE vulnerable, then conflicts

inversely impact on their quality of life, as this disruption affects people’s lives in

every way (WHO 2002, 226).

       Chadee (2003) conducted a study in Trinidad and Tobago. His research

found that concerning mixed ethnicity, there existed an inverse relationship

between the fear of victimization and age, and non-victims were more fearful than

victims, while persons residing in low crime areas were more fearful compared

with people who were in high crime zones (Chadee 2003, 84). A number of

studies found that the aged who were less likely to be victimized were more likely

to be fearful (Harriott 2003; Chadee 2003; Baldassare 1986; Brillon 1987; Clarke

1984; Cook and Cook 1976). This undoubtedly influences their psychological

state and by extension their wellbeing.

       The World Health Organization aided the discourse on crime,

victimization and health by relating those issues to psychological stress (WHO

2002). According to Quirk and Casco (1994), psychological stresses which relate

to conflict are associated with depression and anxiety, loss of life and status,

psychosomatic ailments, displacement and grief.         The WHO noted that, “the

impact of conflict on health can be very great in terms of mortality, morbidity and

disabilities” (WHO 2002, 222). In the World Report on Violence and Health, the

WHO cited that in Zimbabwe, 13 percent of all physiological dismemberments

and disabilities were due to ‘armed conflict’ This is also common to other

topographies, as in Ethiopia, ‘armed conflict’ resulted in 1 million deaths (Kloos

1992); in Cambodia 36,000 people have lost at least one limb because of
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accidents due to landmines, and a similar situation occurred in Sierra Leone

(Human Rights Watch 1999). There is an inverse relationship between crime,

violence and victimization, based on the studies and expert’s work presented here.

       Home ownership

       In a study analyzing data germane to people and their environment, the

findings indicate that ‘perceived health’ and housing satisfaction contribute the

most to wellbeing among the elderly (Barresi, Ferraro, Hobey 1983, 84).

According to Breeze et al.’s (Breeze et al. 2004) study, using data from the

Medical Research Council in Britain, the aged who were owners of their homes

were less likely to report poor quality of life. A finding of importance was that

dependent seniors in their own housing were no more likely to have poor quality

of life, compared to those who lived in rented dwellings.

       In respect to gender, men’s and women’s home ownership was not found

to influence wellbeing positively. Nevertheless, for men who owned their own

homes, lower scores on wellbeing were found. The results also indicate that while

the quantity of neighbour interaction benefits the wellbeing of men, women

benefit more from the positive sentiments of sociability in the neighbourhood.

This study emphasizes the importance of environmental satisfaction and

neighbourhood sociability as key determinants of wellbeing in later life (Barresi,

Ferraro, Hobey 1983, 84)

       Household Size, Social Support (i.e. Family)

       In a 1992 survey of the Support for the Elderly in Rural and Urban China

(20,000 cases), Zimmer and Kwong (2003) used that data to analyze family size
                                                                                144


and support of older adults in urban and rural China. They found that an increase

of more than one child increases the probability for old-age support.

       In urban China, those having more than three children are less likely to

receive support than those with one child. The data revealed that each additional

child that is born to the elderly increases the likelihood of the elderly receiving

financial support without any diminishing return. The findings showed that

increasing gains from having an additional child are more apparent in rural than in

urban zones (Zimmer and Kwong 2003, 32). With a strong positive association

between the number of children and the likelihood of elderly support, a reduction

in family size will see changes in support for the aged populace. In McNally and

Williams (undated), Martin (1990) put forward the position that in developing

countries, family support plays a significant role in representing the best form of

care for the elderly; a point on which Anthony (1999) and Stecklov (1999)

concur. Anthony commented that the aged are sometimes left alone because of

the death of the other partner, which may result in depression or even low self-

esteem. It is important, then, to comprehend how social isolation impacts on the

wellbeing of the elderly. Steckklov, on the other hand, in his thesis ‘Evaluating

the economic returns to childbearing in Cote d’Ivoire’ sought to prove (or

disprove) the claim that children are economic assets to their parents, and affirms

with the other studies that this is so. He finds that, on an average, the additional

child increases the elderly parent’s material possessions with time. This fact is a

rationale for poor families to increase their family size in an attempt to relieve

them of poverty over time. Despite the difficulties of sharing the ‘little’ that the
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parents have, they perceive that the opportunity cost of high fertility in the future

outweighs the present cost of economic misfortune. This is even more pervasive

in poor households, in rural zones, with low educational attainment.

       The children are not only economic assets, but they stand as social support

in old age. Parents are equally concerned about their old age, and so in planning

for this reality many poor parents believe that one of the roles of their children is

to ‘look after them in old age’. Thus, this becomes a critical aspect of the

socialization of children by their parents, that they (i.e. parents) are expecting to

invest in education and other social products while sacrificing consumption for

them, so as not to be forgotten in their time of need, in old age.



       Environment

       Any study on the quality of life of humans cannot conclude without

examining whether or not the environment has an impact on the health status of

the individual (See Pacione 2003; Pebley 1998). This is because human activities

– in the form of deforestation, urbanization, industrialization, development,

growth and production, interface with the finite physical environment; issues such

as pesticides, radioactive waste, climate change, air and water pollution, emission

of greenhouse gases, asbestos and household waste, must be explored in relation

to their association with health status (Pebley 1998, 384). Pebley (1998) argued

that human activities have transformed the earth’s topography. He believed that

population growth accounted for many of the environmental problems and

hazards that we experience today. This, then, begs the question, does the
                                                                                          146


environment impact on human wellbeing?

          Pebley stated that “environmental factors are likely to play a small but

significant role in mortality and morbidity…” (Pebley 1998, 384); he admits that

an associative role does exist between the environment and the status of human

health (also see Khaleque and Elias 1995). From Pebley’s, and Khaleque and

Elias’ works, environmental factors must be included in any analysis of health

status.




          Figure 7.1.1: Respiratory system of a human.

          Source: Health Canada




          Sastry (2002), believed that the long-term effects on health from exposure

to air pollutants are known to be difficult to detect, but argued that there is a

short-term impact on the respiratory system, and that mortality from airborne

pollutants has been well established.                    A group of practitioners and scholars
                                                                                   147


(O’Neill et al. 2007) disagree somewhat with the position of Sastry in a study of

some 92 diabetes patients in Boston. They have shown a direct association

between air pollution and inflammation and endothelial dysfunction among

people with diabetes. The argument constructed by scholars is that because of the

very susceptible nature of type 2 diabetics, they are more prone to death if

exposed to airborne pollutants than other people, and the researcher believes that

this does not exclude those with asthma or other respiratory ailments, nor does it

exclude young children.

           It was not the mere exposure to airborne particles [i.e. PM 2.5 , “particles

<2.5 µm in aerodynamic diameter, known as fine particles” (O’Neill et al. 2007)]

that led to the possible death of the patients with type 2 diabetes, but it was the

degree of contact with the particles, the present health status and the genetics of

the individuals. Within the context of diabetes being one of the five leading

causes of death of the aged, then undoubtedly the presence of air pollutants is

highly likely to affect the wellbeing of senior citizens, which makes the

environment a component of any study of the wellbeing of this group. Airborne

particles not only affect the aged in regard to mortality, but their physical

functionality is also influenced by these pollutants, thereby affecting their quality

of life.     These are manifested in the form of chronic respiratory ailments or

cardiovascular conditions, anxiety, depression, pain and a sense of diminished

quality of life among the aged. While the sample size of O’Neill et al. (2007) was

92 and bearing in mind that it was not chosen using a probability sampling

technique, this lacks generalizability. Nevertheless, a study carried out by the
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American Thoracic Society (2002) unequivocally shows that airborne pollutants

do affect the quality of life of people.

        Eldemire identifies ageing as a ‘biological process’ which is impacted

upon by the environment (See Eldemire 1994, 33). This argument recognizes the

interplay between the environment and the human body, as regards growing old

and survivability. The human body depends on the environment for oxygen. This

is not the only dependency that exists between the two physical entities; but the

body is able through the process of homeostasis to survive in different ecologic

conditions as dictated by the environment.            Because there is this natural

connection between them, any mishap within the environment is highly likely to

cause a shift in the health status of people, in particular the aged.

        As such, it should come as no surprise that pollutants in the atmosphere

cause illnesses (or ailments) like tuberculosis, viral influenza, cholera, and so

forth. Another matter which is of importance here is how ‘deforestation’ on the

hills (or mountains) results in flooding - which results in either (i) increased

ailments or mortality, or (ii) destroyed water quality and food supply – which

again affects the wellbeing of people. The human body, therefore, depends on the

environment for nutrients, and vital oxygen for survival. Because the body

survives within the environment and relies on it for sustenance, changes in this

physical space directly alter the functioning of people. Such a premise emphasizes

that the human body and the environment are one; as such the lungs depend on

the outside environment (see Appendix 4), the air, to carry oxygen into the body,

and so do the blood cells. Oxygen to the human body is comparable to gasoline
                                                                                     149


in a vehicle, which carries that vital source of life to the engine. Without it the

body is like any other inanimate, lifeless object, and is referred to as a corpse.

       In a study conducted on Malaysians in which the information on causes of

mortality was gathered between 1994 and 1997 from vital statistical records,

Sastry (2002) reported that a strong association exists between deaths and air

pollution. The study indicated that the youngest aged people (less than one year)

and the oldest aged populace (65 to 74 years) who were exposed to air pollution

had a higher probability of mortality. According to Sastry (2002, 15), “deaths

from non-traumatic causes are 19% higher after air-pollution days.” With this

finding, high air pollution implies an increased mortality which is modest for

those aged 75 years and over. This was also the case for infants after a day of high

air pollution. From this research, increased mortality does not occur as a result of

a single day of high air pollution, but it is more related to a five-day duration.

Bascom et al. (1996) and Dockery and Pope (1994) as well as Sastry (2002)

theorized that a direct association existed between air pollution and daily deaths.

Those deaths resulted from cardiovascular and respiratory diseases. Sastry (2002)

warned against a perspective of causality between air-pollution and mortality. He

used the Samet et al. (2000) study to emphasize the disparity.

       In an article entitled ‘Urban environmental quality and human wellbeing -

a social geographical perspective’,     Pacione (2003) argues that environmental

quality within a particular topography influences people’s quality of life, and that

people in developed nations now realize that wellbeing is not necessarily a simple

function of material wealth (Pacione 2003, 19). This theorizing was the bedrock
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upon which Pacione put forward his claim that the quality of the environment

directly affects one’s wellbeing or ‘illbeing.’ Despite the article being on ‘Urban

environmental quality and human wellbeing’, some issues such as deforestation,

climatic change, human encroachment on the natural environment, changes in

farming densities and practices, air pollution, human and animal demography, and

inappropriate sewage disposal are just a few elements, present in both rural and

urban zones in developing countries, which affect the quality of life everywhere

(Planning Institute of Jamaica 1995, 28). Liberato et al (2006) carried out a study

in Bolivia using secondary data and found that the rural/urban locality influence

was the largest on wellbeing, which reiterates that Pacione’s article is applicable

across urban or rural zones.

       A study of some 1,212 Taiwanese elderly (65 years and beyond) selected,

using cluster sampling, from a listing of households in northern Taiwan, revealed

that the elimination of environmental vulnerability is important to the wellbeing

of the elderly (Tzu-Ting 2005).      The research indicated that for seniors the

bathroom was a prime location for environmental hazards in the home. Among

the predictors of ecological perils were (1) living in urban zones, (2) poor

awareness of one’s health status, and (3) seniors (ages 74 years and beyond).

       Pacione (2003, 20) used an illustration of inner city communities in the

UK where the quality of life of the residents is low, and this was attributable to

overcrowding, “amenity deficient housing”, low skills levels, and migration.

Kart (1990) in the text ‘The realities of aging’ attributed particular typologies of

environment to the degree of wellbeing experienced by the elderly. He argued
                                                                                    151


that quiet neighbourhoods with adequately maintained topographies were suitable

for the ‘frail elderly’. According to Kart, using a study by Chapman and Beaudet

(1983), an association exists between the physical qualities of the environs.

        Summary

        This literature review has provided a conceptual framework of the possible

factors which can either be included, or those that are likely to be used, in

building a model on the wellbeing of the aged. Wellbeing is undoubtedly a multi-

dimensional phenomenon. It is not based on a single element, such as biological

condition (i.e. illnesses and injuries). Despite the fact that this plays a critical role

in curative care (SABRE’s project – biological factors account for 33% of a

38.2% model), the literature has shown that psychosocial, environmental and

cultural factors are equally important in influencing wellbeing. In particular, the

quality of life of the aged is associated with biopsychosocial conditions – social

support, home ownership, psychological affective conditions, household density,

ecological factors, ageing, level of education, cost of health care and marital

status; and it does differ based on gender.

        Past works have shown that positive psychological conditions directly

correlate with quality of life, and negative affective conditions inversely relate to

wellbeing, but none of the work that has been reviewed has made a distinction

with regard to degree of influence. The current study will address this gap, as the

researcher is concerned about which of the two psychological conditions has more

influence on the wellbeing of senior citizens.

        On the matter of the environment, which can play a critical role in its
                                                                                   152


effect on the human body and its psychological state, all the previous studies

converge in that it is a significant determinant of quality of life. This study will

isolate the psychological conditions from the environment, and in the process will

evaluate whether or not airborne pollutants and other ecological factors can be

used to predict the quality of life or human wellbeing.

         This takes me into the next variable, crime. One of the issues which this

research seeks to address is whether or not crime does inversely affect the quality

of life of humans. Although fear of anything in life is correlated with a negative

psychological state, by separating the psychological conditions from crime, this

study will distinguish between the two phenomena.            The current work will

differentiate between the fear of crime, which is constituted in the psychological

conditions, and the crime itself, and by so doing this study will be able to address

the matter of who are more likely to have crimes perpetrated against them, and

the correlation with the wellbeing of aged Jamaicans.

         On another factor, the issues of home ownership, property ownership and

areas of residence were not distinguished in other studies. The current work will

single out each condition in an effort to generalize the influence of typologies of

home ownership, property ownership and area of residence on the quality of life

of aged people within the Jamaican context. Past works did not differentiate

between house ownership and property ownership within the construct of where

one lives, to see which, if any, of the three conditions influences the quality of

life, and if so, the degree to which it is affected. This gap will be rectified in this

paper.
                                                                                     153


       There is another gap with which this study will concern itself, and it is of

gender. There are many contradictions in past literature on the quality of life of

males and females. Some studies have shown that the health status of males is

greater than that of females, while other works have disproved this claim. From

the literature, the economic wellbeing of males is higher than that of their female

counterparts, but no single work has twinned both health status and income in

measuring the wellbeing of the aged, while noting any gender differences. Thus,

this present study seeks to address this gap by evaluating wellbeing from the two-

dimensional delimitation of previous works, and in the process see whether or not

a difference exists between the sexes’ subjective wellbeing. This leads me to the

next matter, the influence of education on the quality of life of senior citizens.

       The literature has generalized that years of schooling (i.e. educational

attainment) play a multi-dimensional role in the quality of life of people. It is

argued that education does not only directly influence the wellbeing of people, but

that it inversely does so through occupations, lifestyle practices and typology of

education. Owing to the fact that this study will not be using occupation and

typology of employment status of the delimitation of the dataset (i.e.

approximately 75% of the data are missing), this model will be able to isolate the

single effect of education on the general wellbeing of aged Jamaicans.

       Furthermore, this literature review has even provided information on

religion and/or religiosity that is a critical condition as an indicator of wellbeing,

but because of the limitation of the dataset this has not been evaluated as a part of

this paper, along with lifestyle risk factors and some historical socioeconomic
                                                                                154


indicators (such as childhood diseases, nutrition, health and economic situation in

childhood).    Nevertheless, the generalized finding is that socioeconomic,

ecological and psychological conditions are indeed factors in measuring the

wellbeing of aged people. Given that we have established a plethora of factors

that singly affect wellbeing; this leads us to the next issue, which is the approach

to combining those variables in a single model. The next CHAPTER will address

the aforementioned issues raised.
                                                                                  155


                                   Chapter Eight

                               Modelling Wellbeing

       The researcher has employed the Ecological, Selective Optimization with

Compensation Model of Ageing and the economic model of health put forward by

Smith and Kington (1997), in an attempt to understand the state of elderly

Jamaicans. Those models are discussed below.

       While many scholars such as Erber (2005), Brannon, and Feist (2004) had

put forward the idea that this is timely in the measurement of quality of life,

neither of them proposed a mathematical model for the worded construct. Even

though a single ideational purpose drove this paper, the final, biopsychosocial

model was developed through a hybrid approach. The researcher drew variables

and used advanced quantitative statistical analysis from various theories, models

and functions. The building of this model drew its premise from the mathematical

framework outlined by Stutzer and Frey (2003) referred to as the micro-

econometric happiness function – this is written as

       Wit = α + β X it + ε it .      …………………………….. ….. (1)

       Where W it represents subjective wellbeing, X it denotes x 1 , x2 , x 3 , and so

on, in which x 1 to x n are variables – ‘sociodemographic’, ‘environmental’, and

‘social’, ‘institutional’ and ‘economic conditions’ (Stutzer and Frey 2003, 7).

Furthermore, according to Stutzer and Frey (2003, 8), classical economists,

positivists, were not concerned with the valuation of happiness. It was thought to

be highly subjective, in that each person had a different perspective on what

constitutes, for him or her, a ‘good life’.   The indicators of individual wellbeing
                                                                               156


become highly problematic, and should be left to the psychologists. Despite

being economists, Stutzer and Frey ventured into this discourse. They theorized

that subjective wellbeing is a proxy for utility, a construct that economists know

very well.

       The model is primarily shaped by regression analysis. Embedded with

this model was the correlation between sociodemographic, institutional,

environmental and economic conditions, and the wellbeing of each individual

with different time intervals. Engel’s biopsychosocial model was not really a

model. Instead it was a construct which sought to encapsulate body, mind and

social conditions in treating health, as a model represents a theoretical network

through the use of symbols. What he provided was a set of abstractions that are

designed to explain a special theoretical underpinning of health care. Engle

argued for the expansion of the biomedical model but during the process did not

formulate a theory or a model. Thus, Dr. Engel’s work on the biopyschosocial

model did not have a definite set of variables; neither did he advance any

statistical technique to illustrate what he referred to as a model. Two economists,

Smith and Kington, on the other hand, have sought to provide a platform upon

which more studies should be positioned in understanding the health status of a

population, when they used an economic model developed by Grossman.

Grossman’s work was the embodiment of the actual construct outlined by Engel,

the biopyschosocial construct, following which the biopsychosocial construct was

now formulated into a model. It is an econometric model, which uses the

principles of a production function. This is a broader construct of health that
                                                                                    157


incorporates biological, psychological, and sociological conditions in assessing

health status:

       W=ƒ ( P mc , ED, Et , A i , En , G, MS, AR, P, N, O, H, T, R t, V).

       The researcher will explain how he arrived at the aforementioned model.

       The overarching theoretical framework that will be adopted in this study is

an econometric model which was developed by Grossman (1972), quoted in

Smith and Kington 1997a, which reads:

       H t = ƒ (H t-1 , G o , B t , MC t , ED) ……………………………………… (2)

       In which the H t – current health in time period t , stock of health (H t-1 ) in

previous period , Bt – smoking and excessive drinking, and good personal health

behaviours (including exercise – G o ), MC t ,- use of medical care, education of

each family member (ED), and all sources of household income (including current

income) - (see Smith and Kington 1997a, 159-160). Grossman’s model was

further expanded upon by Smith and Kington to include socioeconomic variables

(see Equation 3).

       H t = H* (H t-1 , P mc , P o , ED, Et , R t , A t , G o ) …. ……………………… (3)

       Eq. (2) expresses current health status H t as a function of stock of health

(H t-1 ), price of medical care P mc , the price of other inputs Po , education of each

family member (ED), all sources of household income (Et ), family background or

genetic endowments (G o ), retirement related income (R t ), asset income (A t ,)

       Among the limitations in the use of the biopsychologic model that was

used by Smith and Kington are psychological conditions and ecological variables.

Many of the variables used in Eq. (2), because data from this study based on the
                                                                                 158


Jamaica Survey of Living Conditions (PLC) and Labour Force Survey (LFS) were

not primarily intended for this purpose, equally limit this study. The PLC is a

national cross-sectional study that collects data for general policy formulation,

and so we will not be able to track the individuals over time in order to establish a

former health status. The updated PLC and LFS do not have information – such

as preventative lifestyle behaviour, exercise, family background, and smoking

habits. From a model by Smith and Kington in Equation 3, and based on the

limitation of the dataset, we were able to extract some variables that were

compatible across the two studies. These are as follows:

       W=ƒ ( P mc , ED) ……………………………………………………… (4)

       Wellbeing of the Jamaican elderly W is the result of the cost of medical

care (P mc ), the educational level of the individual and not each family member

(ED). Thus, the researcher, having obtained some germane variables from Smith

and Kington, reviewed other theoretical perspectives in an attempt to validate his

position, to expand the definition of wellbeing from that of Smith and Kington,

physical functioning, to a composite index of physical functioning and income, as

well as examining the Ecological, Selective Optimization with Compensation

Model of Ageing to finally arrive at a single model that would reflect a closer

measure of subjective wellbeing of the elderly. With this objective, the researcher

viewed the perspective of using income and self-reported health conditions in an

attempt to assess the possibility of a composite index of wellbeing. After this, he

ventured   into   evaluating   the   Ecological,   Selective    Optimization    with
                                                                                159


Compensation Model of Ageing, which provide the final set of selected variables

for the model.

       The Selective Optimization with Compensation Model of Ageing is

guided by two principal assumptions. These are – (1) man is adaptable to

situations throughout his life and is always redefining himself in an attempt to fit

within the changes and (2) man is continuously interfacing with positives and

negatives during his life but as he becomes older, the losses (i.e. negatives)

outstrip the gains (or positives). With the ageing process, increasingly man’s

physical functioning deteriorates along with his ‘reserve capacity’. Hence, frailty

sets in and ageing of the body makes it fairly unlikely that he will be able to

perform to the highest level. (See Erber 2005, 32).

       Of importance to this theory is how the aged must now select strategies

within a particular domain in an effort to acquire a better life with an increased

lifespan. With the physical changes occurring within the body, the individual

must now replace losses with positives, even though many of the losses can

become psychological conditions during this period. Hence, the developmental

changes that occur will result in the adaptability of the elderly. He/she must now

use perceptual, cognitive, personal and social domains in an attempt to address the

frailty and unstoppable physiological conditions that are changing.             The

optimization that is likely from this model is totally based on the choices and how

they are able to attain that maximum (or optimization), which is a mark for “a

good chance of achieving successful ageing” (Erber 2005, 32).
                                                                                 160


       The Ecological model of ageing, on the other hand, that Erber credits to

Lawton and Nahemow, is based on the collaboration between the individual and

his/her milieu. This model still relies on adaptability, but its formulation is based

on affective (i.e. emotional) wellbeing and behaviour. Wellbeing is measured by

using competence, which is valued based on physiologic conditions,

psychological state and social capabilities. The environment, on the other hand, is

operationalized as to how the individual is able to perform within the demands

placed on him/her.      These may be physical, sensory, cognitive, or social.

Therefore, the individual’s level of capability is dominated using his/her

adaptability from the pressures placed on him/her by the environment.

       The model emphasizes how as an individual is placed under more stresses

by the environment, for his/her level of competence to rise, he/she requires a

greater degree of environmental pressure. According to Erber, “…the higher

level of environmental press is needed for positive adaptation” (Erber 2005, 33),

and the opposite holds true.    Implicit in this theorizing is how the aged person

continuously has to adapt to the stressor levied on him/her by the environment.

From this model, it is clear that the aged person is interfacing with his/her

environment, and that he/she is not passively absorbing all the forces distributed

by the environment. The elderly person is an active participant with his physical,

social, economic and psychological surroundings. Thus, this paper uses the

principles of the biopsychosocial model started by Grossman and then later

modified by Smith and Kington. From the recognition in Smith and Kington’s

model that psychological conditions were not inputted,            having used the
                                                                                     161


Ecological, and Selective Optimization with Compensation Model of Ageing,

other conditions in addition to psychological variables, such as environment, age

of respondents, area of residence, occupancy per room and home ownership, were

added to the model. Furthermore, because of the limitations of the dataset, a

number of variables were excluded from the model such as stock of health,

lifestyle practices, price of other inputs and family background, religion, and

depression.


        The PLC, on the other hand, collects data on crime and victimization,

environmental conditions and household size, room occupancy, gender and age of

respondents, which were all important for this model, modified from that used by

Smith and Kington in Equation 4.             Along with the Ecological, Selective

Optimization with Compensation Model of Ageing, the final model for this paper

is:

        W=ƒ (P mc , ED, A i , En , G, MS, AR, P, N, O, H, T, V) ………… (5)

        Wellbeing of the Jamaican elderly W, is the result of the cost of medical

care (P mc ), the educational level of the individual, elderly cohort (A i , where i is 65

years and over), the environment (En), gender of the respondents (G), marital

status (MS), area of residents (AR), positive affective conditions (P), negative

affective conditions (N), occupancy per room (O), ownership of home (H), paying

property taxes, (T), and crime and victimization, (V).

                                      Limitations


One of the fundamental challenges for (or drawbacks to) this study is the use of
                                                                                  162


secondary data. The Planning Institute of Jamaica and the Statistical Institute of

Jamaica collect survey data on the health status of Jamaica by way of the

biomedical model.     This model according to Dr. George Engel is simplistic,

which is the reason behind him developing the biopsychosocial model in the

1960s.     Data from the Jamaican policy institutions conceptualize and

operationalize illness, injuries, and degree of sickness as primary to the measure

of health status, which is used as the indicator for quality of life. Hence, based on

how those institutions collect data, in attempting to measure wellbeing using the

biopsychological model, difficulties were encountered. It should be noted here

that fundamentally critical aspects of the lifestyle of the elderly were omitted from

the Jamaica Survey of Living Conditions. From the literature, religion plays an

important role in determining the wellbeing of the elderly, and this was notably

absent from the dataset. Another important factor is loneliness. The literature

shows that many seniors retire from work, and for some their jobs are not merely

financial support, but they form a whole structure of socio-psychological security.

Therefore, when this is coupled with the death of a spouse, and friends and

children moving to reside on their own, it creates a particular loneliness as a result

of the lowered social support.

         More missing links within the dataset were substantial issues relating to

lifestyle and preventative practices. Important questions that were not asked are

as follows: Exercise - can you bathe or dress yourself; can you climb several

flights of stairs; can you bend, kneel, stoop, lift or carry groceries, or heavy

objects? Do you experience depression, loneliness, tiredness or fatigue? Have you
                                                                                 163


felt downhearted and blue, or so down in the dumps that nothing could cheer you

up?

        These factors, that are not included within the dataset, further justify

going to the low explanatory model.          Any model of wellbeing of the aged which

has not included established factors of influence will not only reduce the power of

the explanatory model, but will be a good explanation of the phenomenon that is

being investigated. This is because those variables which are in the model will

explain an aspect of the quality of life of the aged, while the germane variables

which are excluded will significantly alter the degree of explanation that the

model will have.      In summary, because biological ageing is correlated with

functional disabilities and ailments, the exclusion of lifestyle behaviours,

psychological conditions (such as depression, despondence, and fatigue) and past

stock of health as well as religion, must substantially reduce the predictability of

the current model.

        A group of scholars (Hutchinson et al. 2004, 43) - although they did not

provide a mathematical model like the other aforementioned researchers – using a

sample of 2,580 Jamaicans (1,601 females and 979 males, with an average age of

29.7 ± 9.2 yrs; Range: 15 – 50 years) found that a number of socio-demographic

elements do influence psychological wellbeing. Gender, educational attainment,

employment status, union status, religiosity and self-esteem were factors of

psychological wellbeing (p value < 0.05), with age and church attendance not

being statistically significant variables.

        Using multiple regression analyses to establish the aforementioned
                                                                                   164


predictors of psychological wellbeing and satisfaction with life, Hutchinson et al.

(2004) did not provide or use the explanatory power of the model.                  This

delimitation hampers the variance that can be explained by the predictive

variables. In addition to what was put forward earlier, the table that the researcher

cited from did not provide us with any beta (β) coefficients – for the linear

multiple regression – or Wald statistics for the logistic regression. It is difficult to

state the effect of each predictive factor of the dependent variable – in one case

this was psychological wellbeing and in another it was life satisfaction. The

application of multivariate analyses to observation survey data is of itself an

embodiment of the econometric model. And with this reality, Hutchinson et al’s

work is subjected to the same set of limitations that befall this current piece of

work. Despite the delimitations of all the models presented in this text, this piece

of work provides some premises which we are able to understand in attempting to

better the wellbeing of Jamaicans, in particular aged people. This now sets the

stage for an examination of the wellbeing of aged Jamaicans from the perspective

of econometric modelling.
                                                                               165


                                   Chapter Nine



        FINDINGS: SOCIO-DEMOGRAPHIC CHARACTERISTICS

                      OF SAMPLED POPULATION



The sample population consisted of 3,009 elderly Jamaicans (ages 60 years and

older). The mean age of the sample is 71 years 10 months ± 8 years 6 months

(Range= 39 yrs, with the maximum age being 99 years) (See Table 9.1.1). Males

constituted 47.3% of the sample compared to 52.7% of females. Disaggregating

the data revealed that 64.5% of the sampled population were young old, 26.4%

were old-old and 9.2% belonged in the oldest-old age cohort (See Table 9.1.1).

With regard to the sex composition of the surveyed population, the sex

distribution was relatively even. However, there was a substantial disparity in the

oldest-old age group where approximately two-thirds (65%) of the cohort were

females. (See Table 9.1.2)

        On an overall average the wellbeing of elderly Jamaicans is low, 3.8 out

of 14, with a mode of 3.5. The wellbeing index ranges from a low of -1 to a high

of 14 (Table 9.1.1). A score from -1 to 3 denotes very low, 4 to 6 indicate low; 7

to 10 is moderate and 11 to 14 denotes high wellbeing.

       Another point of emphasis is that the majority of the sampled population

dwells in rural areas (approximately two-thirds or 66.8%), and approximately

86% of the elderly population own their own home. In addition, less than 4% of

the surveyed population has attained post-secondary level education, with a high

of 63% having had primary level education (See Table 9.1.1).
                                                                                                 166


Table 9.1.1: Univariate Analyses of Variables used in Wellbeing Model


                                                                                   Percent (n)
Area of residence
       Rural Areas                                                        66.8 (2010)
       Other Towns                                                               21.1 (634)
       Kingston Metropolitan Area                                                12.1 (365)
Gender
       Males                                                                      47.3 (1423)
       Females                                                                    52.7 (1586)
Home Tenure
       Own                                                                         85.9 (2580)
       Rent                                                                         4.9 (147)
       Other (include squat, rent-free, and other)                                  9.3 (278)
Marital Status
       Married                                                                    40.4 (1192)
       Never Married                                                              29.3 (864)
       Divorced                                                                     1.8 (54)
       Separated                                                                    2.1 (63)
       Widowed                                                                    26.4 (778)
Environment
       Affected by landslide etc.                                                38.4 (1848)
       Not Affected by                                                           61.6 (1848)
Level of Education
       Primary/Prep. and below                                                   63.2 (1793)
       Secondary/high                                                            33.4 (949)
       Post-secondary (i.e. tertiary)                                             3.4 (97)
Elderly cohort
       Young-old (60 – 74 yrs.)                                                 64.5 (1940)
       Old-old (75 – 84 yrs.)                                                    26.4 (793)
       Oldest-old (85+ yrs.)                                                     9.2 (276)

Age (mean ± SD) 71yrs.10 mths. ± 8 yrs. 6 mths.

Crime Index (means ± SD) 1.2 (± 5.88), median = 0

Cost of Health Care (mean ± SD) $1,636.24 (± $3,224.99), median is $650.00

General Wellbeing 2 (mean ± SD) 3.9 ± 2.3; mode 3.5
Positive Affective conditions (mean ± SD) 2.9 ± 2.5; mode = 4
Negative Affective conditions (mean ± SD) 3.8 ± 3.2; mode = 0
Occupancy per room        (mean ± SD) 1 ± 1; mode = 1, range 11

2
  The index ranges from a low of -1 to a high of 14. A score from -1 to 3 denotes very low, 4 to 6
indicates low; 7 to 10 is moderate and 11 to 14 denotes high wellbeing.
                                                                                  167


 Table 9.1.2: Percentage of Sex of Respondents by Elderly Cohort

                                                             Elderly Cohort

                                                 Young-old     Old-old     Oldest-old
                                                 (60 - 74)     (75 – 84)   (85+)




                                                 50.0          44.9        35.1
                Male

Sex:

                Female                           50.0          55.1        64.9




Total                                            1940          793         276
                                                                            168




       Figure 9.1.1: Area of Residence by Sex of Respondents


       The majority of the sampled population lived in rural Jamaica (66.8%),

with 21.1% residing in other towns, compared with 12.1% who lived in the

Kingston Metropolitan Area (KMA) (Table 9.1.1).             When the data were

deconstructed by sex, marginally more females resided in rural areas compared to

their male counterparts. Marginally more females dwelled in rural areas and KMA

than in other towns (a 9.8% sex disparity) (See Figure 9.1.1).
                                                                                        169


Table 9.1.3: Percentage of Marital Status of Respondents by Elderly Cohort
                                                   Elderly cohort
              Details                Young old      Old-Old        Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)

                 Never married                   31.9            24.1                   25.7

                 Widowed                         17.6            38.4                   54.3

Marital status   Divorced and/or                  4.0                 4.4                2.3
                 separated

                 Married                         46.5            33.1                   17.7

                 Total                         1910               776                   265



A further decomposition of marital status revealed some interesting results. When

a cross tabulation was done for marital status and elderly cohort, the response rate

was 98.1%.       Of the young-elderly, 31.9% were never married, 17.6% were

widowed, and 4.0% were either divorced or separated, compared to 46.5% who

were married. Concerning the old-old, most of them were widowed (38.4%)

compared to 33.1% who were married elderly, and 24.1% were never married. In

the oldest-old group, on the other hand, more than half of them were widowed

(54%), 17.7% were married, with 2.3% being divorced and/or separated,

compared to 25.7% who were never married (Table 9.1.3).

         The majority of the surveyed respondents were living alone (i.e. one-

person households) 97.6%, while 1.7%            were in two-person households,

compared to 0.7% who indicated that they were in three-person households.
                                                                                170


         The composite Crime Index showed that on an average the number of

crimes witnessed or experienced by the household of the elderly in survey was

approximately one (± approximately six crimes), with a mode being 0 crimes.

         The psychological state of the elderly was subdivided into two categories,

(1) positive affective and (2) negative affective conditions.       Concerning the

positive affective conditions, the average score is approximately 3-point (± 2.5),

(moderate) with a maximum score of 6. The index ranges from 0 to 6, where 0 to

2 is low, 3 is moderate and 4 through 6 are high. In relation to the negative

affective conditions of the sampled population, the average score is approximately

4-point (± 3.1) (very low), with the least score being 0 and the most being 14,

while the total for the index is 19-point. Thus, the interpretation of this index is:

from 0 to 4 is very low, 5-8 is low, moderate is 9 through 12 and high is from 13

to 19.
                                                                                     171


Table 9.1.4: Percentage of Educational Level by Elderly Cohort

                                                        Elderly Cohort


               Details                 Young Old        Old-Old             Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)
                                                 61.3             65.2               70.7
               Primary and below
                                                 34.7             32.0               28.1
Educational    Secondary
Level                                             4.0                 2.8                1.2
               Tertiary

               Total                           1844               753                242



        Of the 3,009 elderly people in the survey, 2,839 of them were used for this

cross tabulation. Approximately 63% had attained at most primary level education

– the oldest-old (70.7%); the old-old (65.2%) and the young-old (61.3%). Only

3.4% had obtained post-secondary level education – with 1.2% of the oldest-old,

4.0% compared to 2.8% of the old-old (Table 9.1.4)
                                                                                  172


Table 9.1.5.i: Percentage of Area of Residence by Elderly Cohort

                 Details                                Elderly cohort


                                        Young Old       Old-Old          Oldest-Old
                                        (60 – 74 yrs)   (75-84 yrs)      (85+ yrs)
                                        65.9            67.3             71.4
                  Rural area
Area of
                                        21.2            21.4             18.8
Residence         Other Towns
                                        12.8            11.2             9.8
                  KMA

                  Total                 1940            793              276



           Of the sampled population of elderly Jamaicans (n=3009), most of them

resided in rural Jamaica 66.8% - the young old (65.9%), the old-old (67.3%), and

the oldest-old (71.4%).        Marginally more young-old dwell in KMA (12.8%)

compared to the old-old (11.2%), with the oldest-old accounting for 9.8% (Table

9.1.5.i)
                                                                                   173


Table 9.1.5.ii: Percentage of Area of Residence by Elderly Cohort
 Sex                                                             Aged Population
                                                                                    Oldest-
                                                         Young-Old     Old-Old       Old
 Male              Area of Residence   Rural Areas
                                                                69.2        70.2         69.1
                                       Other Towns
                                                                20.4        18.8         21.6
                                       KMA
                                                                10.4        11.0          9.3
                   Total                                        636         356           97

 Female            Area of Residence   Rural Areas
                                                                65.4        65.0         72.6
                                       Other Towns
                                                                21.8        23.6         17.3
                                       KMA
                                                                12.8        11.4         10.1
                   Total                                        615         437          179



Further examination of area of residence by elderly cohort with regard to sex of

the respondents revealed some interesting results. Initially the data indicated that

most of the oldest-old resided in rural areas. However, when area of residence

and elderly cohort was disaggregated by sex, the findings showed that marginally

more females within the oldest-old cohort dwelled in rural zones, with the most

for males being in the age cohort of the old-old (See Table 9.1.5.ii). The findings

depict that less than 13% of the elderly reside in the Kingston Metropolitan Area.
                                                                                      174


Table 9.1.6: Percentage of Elderly Receiving National Insurance Scheme (NIS)

                                                     Elderly Cohort
Details
                                        Young Elderly       Old           Oldest
                                                            Elderly       Elderly

                No                              94.5           91.4           92.8
NIS
               Yes                               5.5            8.6            7.2

Total                                          1930           793            276



Table 9.1.7.i: Percentage of Elderly Receiving Government or Private Pension by
Elderly Cohort

                                                     Elderly Cohort
Details
                                                         Old        Oldest
                                         Young Elderly Elderly      elderly
                                           (60 - 74 yrs)   (75 –    84   (85+ yrs.)
                                                           yrs)


                  No                          80.6           76.7            75.4
Pension
                  Yes                         19.4           23.3            24.6

Total                                          1931          793              276


          Approximately 7% of the sampled population received social security (i.e.

NIS). Most of those who received social security (i.e. NIS) were the old elderly

8.6%, with 7.2% of those who were oldest-old compared to 5.5% of the young-

old.    On the other hand, three times (20.9%) the number of the surveyed

population received private and/or government pensions. However, marginally

more of the oldest-old (24.6%) got private and/or government pensions compared
                                                                              175


to the old-old, with only 19.4% of the young-old receiving this pension (see

Tables 9.1.6 and 9.1.7.i)



Table 9.1.7.ii: Percentage of Sampled Population who Receive NIS by Pension
(Government or Private)

                                                      Pension
Details

                                              No                    Yes



               No                             94.5                  89.8
 NIS
              Yes                             5.5                   10.2

Total                                  2373                         626


Approximately 95% of elderly Jamaicans have not received private and/or

government pensions, nor have they received a pension from the National

Insurance Scheme (NIS) (Table 9.1.7.ii). Of the 626 elderly persons who declared

having received private or government pensions, only 10.2% have received both

NIS and private or government pensions. On the other hand, 90% of those who

received private and/or government pensions reported that they have not received

any NIS pension.
                                                                           176


Table 9.1.7.iii: Percentage of Sampled Population who Receive NIS by Area of
Residence

                                              Area of Residence
Details
                                     Rural Areas       Other Towns       KMA


             No                         95.0                 93.2         85.7
 NIS
            Yes                          5.0                  6.8         14.3

Total                                   2003                  633         363



Of the total number of rural residents (2003), 5.0% received NIS, compared to
6.8% of those who dwell in other towns, and 14.3% who live in the Kingston
Metropolitan Area (KMA) (Table 9.1.7.iii). On the other hand, Table 9.1.7.iv
revealed that 17.0% of rural elderly persons indicated having got private or
government pensions, compared to 31.1% of those who live in other towns, and
24.5% of those reside in KMA.


Table 9.1.7.iv: Percentage of Sampled Population who Receive Pension by Area of
Residence

                                              Area of Residence
Details
                                     Rural Areas       Other Towns       KMA


             No                         83.0                 68.9         75.5
 Pension
            Yes                         17.0                 31.1         24.5

Total                                   2003                 634         363
                                                                           177


Table 9.1.7.v: Percentage of Sampled Population who Receive NIS by Sex

                                         Sex
Details
                          Male          Female          Total


          No              93.0               93.9                         93.5
 NIS
          Yes              7.0               6.1                           6.5

Total                    1419              1580                          2999



In excess of 100 percent more aged Jamaicans received private and government
pensions (20.9%) compared to 6.5 % of those who received NIS pensions (see
Table 4.1.4v and Table 4.1.7vi). Based on Table 4.1.7 (v), more males received
NIS (7%) compared to 6.1% of females.


Table 9.1.7.vi: Percentage of Sampled Population who Receive Private Pension by
Sex

                                         Sex
Details
                          Male          Female          Total


          No               80.5              77.8                79.1
Pension
          Yes              19.5              22.2                20.9

Total                    1420                1580               3000
                                                                                     178


Table 9.1.8: Physical Health Status by Elderly Cohort

              Details                                   Elderly Cohort

                                       Young-Old        Old-Old             Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)

               Five conditions                    0.0                 0.0                0.0

               Four conditions                    0.3                 0.1                0.4


               Three conditions                   4.3                 8.9            12.4
Health
conditions                                                                           26.7
               Two conditions                    26.8             32.5

               One condition                      7.6                 9.8            13.2


               No condition                      60.9             48.7               47.4


               Total                            1910              785                266




In order to assess the health status of aged Jamaicans, a cross tabulation was done

between physical health status and elderly cohort. The findings show that 56.4%

of elderly Jamaicans did not report an illness, injury or ailment over the 4-week

period, with 8.7 % indicating having one ailment, 28.3% experiencing two health

conditions, and 6.3% reporting three, compared to 0.3% saying that they are

affected by four health conditions. Further analysis of the physical functioning of

elderly Jamaicans revealed that approximately 60.9 % of the young-old did not

indicate an illness, injury or ailment compared to 48.7% of the old-old, whereas

47.4% of the oldest-old did not report being affected by any form of injuries,

ailments or sicknesses. None of the sampled elderly Jamaicans reported having

suffered (or been affected by) more than four health conditions (Table 9.1.8).
                                                                           179




Figure 9.1.2: Percentage of Health Conditions Reported by Sex




Substantially more men (62.4%) reported not to have been affected by an illness

(or physical dysfunction) compared to females (51.0%). On the other hand, the

reverse was the case for two ailments. However, for more than two illnesses,

males in the survey reported more dysfunctions than their female counterparts.

(See Figure 9.1.2)
                                                                                 180


Table 9.1.9.i: Descriptive Statistics for Health Care Expenditure of the Elderly
Cohort

                                        Descriptive Statistics


 Elderly      N           Mean             Std. Deviation        Minimum   Maximum
 cohort

 Young-old
              594         1664.55          3495.80               .00       40500.00
 (60 - 74)


 Old-old
              329         1588.59          2906.37               .00       30000.00
 (75 -84)


 Oldest-old
              104         1625.35          2516.52               .00       17000.00
 (85+)


 Total        1027        1636.24          3224.99               .00       40500.00



         When the respondents were asked to report on the amount expended on

cost of health care (including hospitalization expenditure and medication) for a

four-week period, on an average elderly Jamaicans spent $1, 636.24 ± $3,224.99,

with the mode being $0.00. The most spent by an elderly person was $40,500.00,

and the least $17,000. From Table 4.1.9 (i), the young-old spent the most on an

average on health-care $1,664.55, followed by the oldest-old ($1,625.59) which

was less than the mean amount spent by the old-old ($1,588.59). Of importance

here is that the young-old spent more than the average amount spent by the

elderly population ($1, 636.24) (Table 9.1.9.i).
                                                                              181


Table 9.1.9.ii: Descriptive Statistics for Health Care Expenditure based on Area
of Residence

Area of           N               Mean         Std. Deviation     Maximum
Residence

Rural Area        758             1401.79      2154.68            23000.00


Other Towns       170             2504.84      5650.41            40500.00


KMA               99              1939.85      4017.50            30000.00


Total             1027            1636.24      3224.99            35000.00



Table 9.1.9.ii shows that the elderly in rural areas spent on an average $1,401.79
on health care with a maximum of $23,000, which is less than the overall average
of $1,636.84 compared to the elderly who reside in KMA, who spent on average
$1,939.85 while those who live in other towns spent on an average $2,504.84.
This means that elderly people who reside in other towns and KMA spent more
than the elderly who dwell in rural areas with residents in both KMA and other
towns having spent more than the general average.
                                                                              182


Table 9.1.9.iii: Descriptive Statistics for Health Care Expenditure based on Sex

                  N               Mean         Std. Deviation     Maximum


      Male        411             1,974.55     4,188.23           40,500.00
Sex
                  616             1,410.53     2351.47            28,750.00
      Female

Total             1027            1636.24      3224.99



On average, males spent $1,974.55 on health care compared to females who spent

$1,410.53. Based on Table 9.1.9.iii, the most that was expended on cost of health

care by females was $28,750.00 with males spending $40,500.00. It should be

noted here that only 34.1% of the surveyed population were used for this analysis.



        A small percentage, (17.5%), of the sample reported being employed

(n=527). Of the employed elderly, 71.9% were ‘young-old (i.e. ages 60 to 64

years), compared to 4.2% who were within the oldest-old age cohort. Further

decomposition of the aforementioned findings revealed that unemployment was

substantially a female phenomenon. Of the young-old who were employed

(n=379), 65.6% were males compared to 34.6% females. With regard to the

oldest-old who were employed, 59% were males with only 41% females. In

summary, the unemployment rate among the elderly was very high (82.5%), with

there being a gender bias against females in regard to employment.
                                                                                183


In an effort to understand the state of the Jamaican elderly, we examined the
relationship between the per-capita population quintile and age group. We found
that there is a statistical association between the previous mentioned variables (χ2
(8) = 17.72, ρ value=0.023 < 0.05). Although there is a relationship between the
mentioned variables, the association is a weak one (cc=0.77 or 7.7%). Thus, 1%
of the variance in the per-capita population quintile can be explained by a change
in age group of the individual.
    Further analysis of the per-capita population quintile and age groups revealed
that the young-old (ages 60 to 74 years) had marginally more people being
classified in the richest quintile compared to the other age cohorts. On the other
hand, significantly more of the oldest-old cohort (ages 85 years and over) were in
quintile 2, which denotes poor (see Figure 9.1.3).




Figure 9.1.3: Per-capita Population Quintile, by Age Group of Respondents
                                                                                184




Further analysis of the per-capita population quintile by age group of elderly,
when controlled by sex, revealed that there is no statistical difference based on the
sex of respondents. The cross-tabulations had values of χ2 (8) = 15.2, ρ
value=0.52 > 0.05 for males and χ2 (8) = 5.8, ρ value=0.67 > 0.05 for females. A
detailed report of the findings with regard to per-capita quintile, age group and
sex can be seen in Figure 9.1.4 below.




Figure 9.1.4: Per-capita Population Quintile, by Age group Controlled for Sex
                                                                                              185


                                      Chapter Ten


                   FINDINGS: The Multivariate Analysis


        The wellbeing of aged Jamaicans is expressed in the equation below:


W ii =ƒ (P mc , ED, A i , E n, G, MS, AR, P, N, O, H, T, V)                         [1]


        Individual wellbeing, Wi , is a function of cost of medical care P mc ,

educational level of the individual ED, elderly cohort A i , where i is 65 years and

over), the environment En, gender of the respondents G, marital status MS, area

of residents AR, positive affective conditions P, negative affective conditions N,

occupancy per room O, home tenure H, property ownership T, and crime and

victimization, V.


        From function (1), using the coefficients in Table 4.1.10, the result is a

linear function (2):

      W = α 0 + β 1 R + β 2T + β 3 E + β 4 H + β 5 M + β 6 P + β 7C - β 8A – β 9N – β 10O – β 11 Ec
(2)
            (Where α is the constant, and each β is the coefficient of each factor)


        The findings in Table 4.1.10 below, show that the wellbeing of Jamaica’s

elderly is determined by the following conditions: (i) physical environment; (ii)

psychological conditions; (iii) cost of health care; (iv) area of residence; (v)

elderly cohort; (vi) average occupancy per room; (vii) marital status; (viii)

property tax; (ix) crime, and (x) educational level. A few conditions were found
                                                                              186


not to have any statistical significance for wellbeing – such as the gender of the

respondents, and home ownership. These will be discussed in detail below.

Table 10.1.1: A Multivariate Model of Wellbeing of the Jamaican Elderly,
N=629
                               Model
         Dependent variable: Wellbeing of the Jamaican Elderly

Independent variables:                 Unstandardized     Standardardized
                                       coefficient        coefficient

Constant                                         2.628
Physical Environment                            -0.763*              -0.190
Positive Affective Conditions                    0.065*               0.085
Negative Affective Conditions                   -0.090*              -0.140
ln Cost of medical (health) care                 0.237*               0.148
Elderly                                         -0.024*              -0.098

Area of Residence
Rural Area****
Other Towns                                     0.859*                0.164
Urban Area                                      1.386*                0.154

ln Average occupancy per room                   -0.650*              -0.229
                                                                      0.110
Marital Status
Single****                                      0.428*
Divorced, separated, and widowed
Married                                         0.405*                0.102
                                                0.575*                0.122
Property ownership
Crime                                           0.041*                0.098
Sex                                              0.096

Home tenure
Squatted****
Rented                                            0.000
Owned                                            -0.702

Educational level
Primary and below
Post-secondary and secondary                     0.092
Tertiary                                        2.561*                0.173

R = 0.645, Adjusted R2 = 0.401
                                                                                  187


Error term = 1.56
F statistics [16,613] = 27.355, P= 0.001
* significant p value < 0.05
**** Reference group



         The model has a Pearson’s correlation coefficient of 0.645 (or 64.5%),

which means that the association between wellbeing and the selected factors used

in the model is a moderate one.        The adjusted coefficient of determination,

adjusted r2, (in Table 10.1.1) is 0.401 (or 40.1%). This denotes that a 1 percent

change in physical environment, psychological conditions, cost of health care,

area of residence, age of respondents, average room occupancy, marital status,

property taxes, crime and educational level in the predictor changes the predict,

and by 40.1 percent. This denotes that 40.1 percent of the total variation in the

wellbeing of elderly Jamaicans can be explained by the selected variables used in

the model. As such, the Model, Testing Ho: β=0, with an α = 0.05, the researcher

can conclude that the linear model provides the best fit to the data from an F value

[16,613] is 27.355, p < 0.05.

        Of the 12 selected variables that were used to test the general hypothesis,

10 were found to be statistically significant. These are as follows – (1) marital

status; (2) physical environment; (3) area of residence; (4) average occupancy per

room; (5) property ownership; (6) cost of medical (or health) care; (7)

psychological conditions, which include – (i) positive and (ii) negative affective

conditions; (8) crime, (9) a part of the educational attainment, that is, education at

the post-secondary level and (10) age of respondents. Thus, those that were not
                                                                               188


found to be factors are as follows – (1) sex of respondents; and (2) home tenure;

and (3) education at the secondary level.

       From the selected variables of this study, we have found that there are 10

factors involved in wellbeing. Wellbeing of the Jamaican elderly is affected by (i)

psychological conditions - positive and negative affective conditions; (ii) area of

residence; (ii) crime; (iv) marital status; (v) physical milieu; (vi) property

ownership; (vii) educational level; (viii) cost of health care, (ix) average

occupancy per room. The five most important factors impacting on the wellbeing

of the Jamaican elderly in descending order are as follows: Average occupancy

per room (β = -0.229), physical environment (β = -0.190), education (β = 0.173),

area of residence (β = 0.0.164); and cost of health care (β = 0.148). Thus, the

significance of this paper is that we now have a quantitative model that can be

used to evaluate the wellbeing of elderly Jamaicans.

       Disaggregating the data reveals some interesting results, such as, with all

other things being constant, the wellbeing of the Jamaican elderly is 3 out of 14

(i.e. low, within the bottom 25% of the wellbeing index). Of the 12 determinants

of wellbeing for the sampled population, 4 came up with negative associations

(i.e. physical environment, negative affective conditions, age of elderly, and

average occupancy per room), with 6 being positive. These are as follows – cost

of health care, area of residence, marital status, property ownership, educational

level and crime.

       W = 2.628+ 0.859Area_Residence2 + 1.386Area_Residence3 +
       0.575Property Ownership + 2.561Edu_ level3 + 0.237lncost of health care
       + 0.428marstatus1+ 0.405marstatus2+ 0.065Positive affective conditions
                                                                               189


       + 0.041Crime - 0.09Negative affective conditions – 0.763Environments –
       0.65lnaveraged Occupancy per room-0.024Age of elderly…………. (3)

       From the wellbeing model, the physical environment decreases the

wellbeing (Pearson Correlation = - 0.13, ρ value = 0.02) of the elderly by 0.763

units, being pessimistic about the present or future equally diminishes wellbeing

(Pearson’s correlation = -0.318, ρ value = 0.001) but by a small unit, 0.09. The

average number of people who occupy a room affects wellbeing negatively

(Pearson’s correlation = -0.367, ρ value = 0.001) by 0.650 units. On the other

hand, an optimistic elderly Jamaican is likely to increase (Pearson’s correlation =

0.25, ρ value = 0.001) his/her wellbeing by 0.065 units.

       Based on Table 10.1.1, the wellbeing of Jamaica’s seniors who are

divorced, separated and widowed is higher when referenced to those who are

single (Pearson correlation = 0.178, ρ value = 0.001), and for each time that the

elderly moves from never married to separated and/or divorced and toward

marriage, his/her wellbeing improves by 0.236 units. The model reveals that for

each time that the aged moves up the rung of the educational level his/her

wellbeing simultaneously increases (Pearson’s correlation = 0.109, ρ value =

.007) by 0.332 units. Although no statistically significant relationship was found

between owing a home and general quality of life (ρ value = 0.379), a positive

association existed between property ownership (Pearson’s correlation = 0.183, ρ

value = 0.001) and wellbeing by 0.575 units. This implies that those who own

property will have a higher wellbeing than those who do not, which includes land

and premises.
                                                                               190


       There was a positive association between area of residence and wellbeing.

Those of the surveyed elderly, who lived in other towns, when referenced to rural

areas, had a higher wellbeing by 0.859 units.     When KMA was referenced to

rural areas, the surveyed population dwelling in KMA had a greater wellbeing by

1.386 units. Based on unstandardized b values for area of residence, the elderly

who lived in KMA had a higher wellbeing than those who resided in other towns,

when these were referenced to rural areas.

       One of the paradoxical findings of this study was the association between

crime and wellbeing (Pearson’s correlation = 0.112, ρ value = 0.006). On the face

of it, it would seem as though there should be a negative relationship between

crime and wellbeing. However, in this study, the finding was the opposite

position. From the model, crime was + 0.041, which denotes that with all other

things being constant, a 1 percent change in crime will result in a direct increase

in wellbeing by 0.04 units. Embedded in this finding is a paradox, as crime is

committed to a greater degree against families with more material resources. It

should be understood here how wellbeing is constituted (50% of it is from

material possessions) with the higher number of possessions attracting more

crime. This same premise explains the positive relationship between the cost of

health care and wellbeing (Pearson’s correlation = 0.297, ρ value = 0.001). From

the model, a 1 percentage change in the cost of health care is explained by a 30%

higher wellbeing among the elderly. This suggests that ‘good’ health care can be

judged by higher income, or better affordability. A finding that should be noted
                                                                                 191


here is that as elderly people age (from young-old to old-old to the final stage of

oldest-old), (s) their health status falls (Spearman rho = -0.063, ρ value = 0.003).

          In wanting to understand why gender was not significant (ρ value =

0.127), the researcher used the ‘Independent Sample Test’ to measure whether

any difference existed between the mean wellbeing of men and women. The test

showed that the average (i.e. mean) wellbeing of men was approximately 3.8 (i.e.

3.7952) compared to that of approximately 3.8 (i.e. 3.8258) for females, with a

significance of 0.747 – Levene’s test, F=0.017, ρ value=0.896. From the findings,

only 26.7% (n=606) of the sampled population had never been married. It follows

that 77.3% (n=1614) of the sampled populace would have had been in a legal

marriage at some point, or are still in one. Hence, in establishing any difference

in wellbeing between the sexes, it can only be attained using those who were

never married, as this group would report differences in assets, income and so on.

          The independent sample t-test analysis (See Appendix VI) indicates that

292 never married males in the sample had an average wellbeing of 2.8 units, with

314 never married females having a mean wellbeing of 3.3 units, and that the

mean difference does differ significantly at the p value of 0.05 (note: ρ value =

0.001).     Levene’s test for Equality of Variance indicates that the never married

males and the never married females do differ significantly from each other (note:

ρ value = 0.001) in their level of wellbeing (Table 10.1.2). Therefore, there is a

difference in wellbeing between the sexes, in which females have a higher

wellbeing than males, but this is only identifiable for people who were never

married.
                                                                                    192


         It was found that there was no statistical association between loneliness

and wellbeing (ρ value = 0.3 > 0.05), but that it was correlated with union status,

paying property taxes and ownership of a home. Hence, when it was included

within the wellbeing model, union status came out not to be significant (ρ value =

0.3), and it was (ρ value = 0.001 < 0.05), with a contribution of 1.8% to the

general wellbeing. Another important finding was that vulnerability of females

was not significantly related to the wellbeing of the elderly (ρ value = 0.286 >

0.05).


APPLICATION OF THE WELLBEING MODEL:

         W   = 2.628+ 0.859Area_Residence2 + 1.386Area_Residence3 +
         0.575Property Ownership + 2.561Edu_ level3 + 0.237lncost of health care
         + 0.428marstatus1+ 0.405marstatus2+ 0.065Positive affective conditions
         + 0.041Crime - 0.09Negative affective conditions – 0.763Environments –
         0.65lnaveraged Occupancy per room-0.024Age of elderly…………. (3)


Scenario 1: What is the Wellbeing of an Elderly Person who Lives in Another
Town or in KMA?

Table 10.1.3: Difference in Wellbeing of Jamaican Elderly based on Area of
Residence (assume that only Area of Residence changes in equation 3)


                       Dwell in Other Towns    Reside in KMA
Constant           2.628                       2.628
Area of Residence:
    0.859*AR2      0.859                       -
    1.386*AR3      -                           1.386

Wellbeing              3.487                   4.014


Wellbeing Index Scale: very low - from 0 to 3; low - 4 to 6; moderate 7 to 10 and high
11 to 14.
                                                                              193


Generally, the wellbeing of the Jamaican elderly is very low (approximately 3,
with all things being equal or constant). However, from Table 10.1.3, a score of
3.5 denotes low wellbeing for an elderly person who dwells in other towns, in
reference to rural areas, compared to 4 (i.e. low wellbeing) for an elderly person
who resides in KMA with reference to rural dwellers. It should be noted that
while the wellbeing of an aged Jamaican is very low, an elderly person who lives
in KMA on an average will have the highest wellbeing among those who live in
different regions in Jamaica.
                                                                                  194


APPLICATION OF THE WELLBEING MODEL:

       Scenario 2 Assume that elderly persons 1, 2 and 3 were not affected by
       any adverse physical environment conditions; the three elderly persons are
       all positive about life, elderly person 1 is 70 years old, elderly person 2 is
       81 and elderly person 3 is 65 years old. Calculate the wellbeing for each
       elderly person. It should be noted that all other things were constant.

Table 10.1.4: Wellbeing of different elderly persons based on years lived
                                        Model

                                                Elderly 1       Elderly 2       Elderly 3

Constant                                              2.628          2.628           2.628
Physical Environment             -0.441xEn                0              0               0
Positive Affective                 0.065xP            0.065          0.065           0.065
Conditions
Negative Affective                -0.090xN                  0               0               0
Conditions
lnCost of medical                0.237xP mc                 0               0               0
(Health) care
Area of residence                0.816xAR                  0             0               0
Elderly                          -0.024xA i            -1.68        -1.944           -1.56
lnAverage occupancy               -0.766xO                 0             0               0
per room
Marital Status                   0.236xMS                   0               0               0
Home tenure                        0.637xT                  0               0               0
Crime                              0.041xV                  0               0               0
Educational level                0.332xED                   0               0               0

Total Wellbeing                                       1.013        0.749            1.133


Wellbeing Index Scale – Very low - from 0 to 3; low - 4 to 6; moderate 7 to 10
and high 11 to 14.


Based on Table 10.1.4, with the given stipulated scenario, all the aged Jamaicans
in this case have a very low wellbeing. However, elderly person number 2 who is
the oldest has the least wellbeing, 0.749, compared to the wellbeing of elderly
person number 1 (1.013), and the highest wellbeing is had by the youngest elderly
person (1.133). It should be noted here that by varying the positive affective
condition and age of the elderly, the difference in wellbeing is minimal.
                                                                          195


Table 10.1.5: Decomposing General Wellbeing Model: Physical Functioning
Model, N= 629
                                Model
   Dependent variable: Physical Functioning of the Jamaican Elderly

Independent variables:                Unstandardized   Standardardized
                                      coefficient      Coefficient

Constant                                      -1.628
Physical Environment                          -0.039
Positive Affective Conditions                 0.016*              0.092
Negative Affective Conditions                 -0.001
lnCost of medical (Health) care               -0.019
Elderly                                      -0.007*             -0.134

Area of residence
Rural Area
Other Towns                                    0.011
Urban                                         -0.041

lnAverage occupancy per room                   0.034
                                              -0.042
Marital Status
Single****
Divorced, separated or widowed
Married                                       -0.049

Property ownership                              0.01
Crime                                          0.002
Sex                                           -0.029

Home tenure
Squatted***
Rented                                         0.000
Owned                                          0.206
                                                                 -0.123
Educational level
Primary and below****
Post-secondary and secondary                 -0.115*
Tertiary                                       0.165

R = 0.237, Adjusted R2 = 0.032
F statistics [16,613] = 2.284, P= 0.003
* significant p value < 0.05
**** Reference group.
                                                                                 196


Of the 12 selected variables used in general wellbeing, 4 of them were not

significant. These were (1) home tenure; (2) age of respondents; (3) sex of

respondents and (4) a part of education – secondary level education. However,

when physical functioning was used to evaluate the wellbeing of the surveyed

population, only 3 of the 12 selected factors were statistically significant. These

were (1) age of respondents, and (2) part of education – education level 2, and

positive affective conditions.

       Based on Table 10.1.5, of the three factors of physical functioning of an

aged elderly person within the survey, age is the most influential factor followed

by education at secondary level with reference to primary education, and finally

positive affective conditions. It should be noted here that there is a direct

association between age and physical dysfunctions, primary level education and

an increase in health conditions.     However, being optimistic about life (i.e.

positive affective condition) will reduce physical dysfunctions.

       From the results in the regression model in Table 10.1.5, physical

condition is a difficult proxy of wellbeing of the Jamaican elderly (i.e. adjusted r2

is 3.2%, meaning that the model only explains approximately 3% of the variance

in wellbeing, using physical functioning to proxy quality of life of the surveyed

elderly people.
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Table 10.1.6: Decomposing General Wellbeing Model: Economic Model, N=629
                             Model
   Dependent variable: Economic Wellbeing of the Jamaican Elderly

Independent variables:               Unstandardized   Standardardized
                                     coefficient      coefficient

Constant                                      8.170
Physical Environment                        -1.580*             -0.190
Positive Affective Conditions                0.192*              0.124
Negative Affective Conditions               -0.171*             -0.133
lnCost of medical (Health) care              0.477*              0.146
Elderly                                     -0.056*             -0.113

Area of Residence
Rural Area****
Other Towns                                  2.073*              0.197
Urban                                        3.056*              0.181

lnAverage occupancy per room                -1.248*             -0.216

Marital status
Single****
Divorced, separated or widowed               0.862*              0.106
Married                                      0.807*              0.102

Property ownership                           1.286*
Crime                                        0.082*              0.097
Sex                                           0.214

Home tenure
Squatted****
Rent                                          0.000
Owned                                        -0.856
Educational level
Primary and below****
Post-secondary and secondary                  0.270
Tertiary                                     4.275*              0.153

R = 0.654, Adjusted R2 = 0.413
Error term = 3.04
F statistics [16,613] = 28.66, P= 0.001
* significant p value < 0.05
**** Reference group
                                                                               198


Based on Table 10.1.6, using economic resources (including income, and material

resources excluding owning a home) to evaluate the wellbeing of the surveyed

population, only 3 of the 12 selected factors were not statistically significant.

These were (1) home tenure (i.e. dwelling), (2) part of education – education level

2, and (3) sex of respondents.

       The model explains 41.3% of the variance in economic wellbeing of the

surveyed elderly population.     The five most important factors of economic

wellbeing are: average occupancy per room (β = -0.216); area of residence (β =

0.197); physical environment (β = -0.190), education (β = 0.153), and cost of

health care (β = 0.146). It should be noted here that the five most important

factors of economic wellbeing are the same for general wellbeing. What does this

mean? Generally, using economic wellbeing to operationalize wellbeing is a

better measure to proxy the wellbeing of the Jamaican elderly than physical

functioning. Based on Table 10.1.6, the model explains 41.3% of the variance in

wellbeing of the surveyed population. This is more than the composite model that

explains 40.1% (see Table 10.1.1).
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                                Chapter Eleven

                                      EPILOGUE


        Population ageing is synonymous with an increase in certain health

conditions (i.e. diabetes mellitus, hypertension, heart diseases, cerebrovascular

and cardiovascular diseases and acute respiratory infections), and it is not limited

to developed nations, but is equally a reality for developing countries. Greying

of a population is also a Caribbean phenomenon (Barbados, Trinidad and Tobago,

Cuba, and Suriname), and a similar situation has been observed in Jamaica. Since

the 1960s, population ageing has been a reality in Jamaica. Public health and

reproductive health measures are primarily responsible for population ageing in

Jamaica, and could be as a result of improvements in the standard of living of the

general populace.   Society has been experiencing reduced birth and death rates

and while net migration has been negative since the 1940s with a few exceptions,

an influx of return migrants at older ages (retirement ages) is helping to increase

the number of ageing Jamaicans. Reference to ageing in many societies

sometimes conjures up different images of social negatives (i.e. ageism);

however, this text does not seek to examine ageism; instead the author is

concerned about the determinants of wellbeing in order that they may guide the

National Policy for the Aged.

        Based on the National Population Policy of Jamaica which was revised in

1995, quality of life is an important condition which the nation seeks to achieve in

the future. In order to attain this objective of improvement in the quality of life,
                                                                                200


we need to examine and understand the possible factors that influence wellbeing

in Jamaica.

        The Planning Institute of Jamaica (PIOJ) has been collating data on the

health status of Jamaicans, but this has only been done for certain age cohorts.

Although life expectancy is high in Jamaica and owes itself to sanitation, water

quality, public health improvements, vaccination, and reduced chronic illnesses,

the elderly are still a vulnerable group. The PIOJ (2005) reported that 60 percent

of admissions to public health facilities for chronic ailments were senior citizens.

While the aforementioned issue provides some knowledge about the wellbeing of

aged Jamaicans, it does not open a comprehensive insight on the matter. In 2008,

the Planning Institute of Jamaica and the Statistical Institute of Jamaica’s report

(JSLC 2007) revealed that 40.2% of elderly people reported a health condition in

the last 4 weeks, with 75.1% of them indicating that this condition was a recurrent

one. Although life expectancy has been increasing and will continue to increase,

so are self-reported illnesses. In 1997, self-reported illness was 22.6% and in

2007, it increased by 93.8%, which was 2.8 times more than the overall self-

reported illness of the population. Concurrently, 71.6% of elderly Jamaicans

sought medical care in 2007, compared to 66.0% of the general populace, while

Powell, Bourne and Waller’s research in 2007, using a nationally representative

stratified probability sample of 1,338 Jamaicans, found that the subjective

wellbeing of the age cohort was very high (7.1 out of 10 ± 1.5), which does not

concur with this study – 3.9 out of 14 ± 2.3. Continuing, from this study we know
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that 56.4% of elderly Jamaicans did not report a health condition, and 28.3%

indicated 2 conditions, compared to 6.5% who reported 3 or more illnesses.

         The difference in the outcome of wellbeing between the two

aforementioned groups can be due to the operational definition in each case.

Powell, Bourne and Waller used a Likert scale of Abraham Maslow’s needs to

evaluate wellbeing, which is in keeping with a multidimensional approach to the

assessment of quality of life, while the current study used material possessions

and self-reported health conditions. This disparity cannot be resolved in the

current work as this was not the purpose of the study; the focus was on factors

that can predict (or determine) the wellbeing of aged Jamaicans. What determines

the wellbeing of aged Jamaicans, and their relative importance?

        This study provides a broad range of health or wellbeing factors regarding

elderly Jamaicans, and these include psychosocial factors. Household crowding

was found to be the most influential predictor of wellbeing in elderly Jamaicans,

followed by physical environment, tertiary level education and area of residents.

The rural elderly had the least wellbeing compared to aged people who resided in

other towns or urban areas. Aged residents of other towns had the greatest

wellbeing of all other elderly residents in Jamaica.

        In 2007, medical practitioners were still utilizing the biomedical model as

the chief approach to the examination of patient care (see Ali, Christian and

Chung 2007). The expert scholars and practitioners identified that the elderly

person was faced with multiple medical conditions, but in the entire ‘case history’

nothing outside of medical problems was investigated, in an attempt to
                                                                                202


comprehend the complexities of a case that has gone on for many years. With the

study conducted by Ali, Christian and Chung (2007), the authors recognized that

some of the features of ‘epilepsy’ in the elderly, more so than the young, are

confusing to present day medicine. Although medical practitioners were confused

by the number of failed trials in attempting to address the conditions of elderly

patients, they continued without any inclusion of possible factors which were

outside of medical sciences. And then the medical doctors argued that they had

cured the patient, and made the statement that:

        The stereotyped nature of the events was recognized and initiation of
        antiepileptic drug treatment resulted in the complete cessation of events
        and the return of an acceptable quality of life. (Ali, Christian and Chung
        2007:379)


        Inherent within the perspective of Ali, Christian and Chung is the direct

association between the absence of ailment and quality of life. This argument is

not only old but is equally not in keeping with the expanded definition offered by

the WHO in 1948. It is accepted by these scholars that no hospitalization because

of the absence of ailment is an indicator of improvement in wellbeing (or quality

of life). The issue of freedom from hospitalization or disease does not imply the

‘return of an acceptable quality of life’, as humans are multidimensional, and so

should not be linked to one single factor in explaining wellbeing.

        However, increased hospitalization of aged Jamaicans (i.e. according to

PIOJ 2005, 23.13, 60% of admission to hospitals for chronic diseases are elderly)

due to health conditions, are indicators of the erosion of the health status of this

age cohort, and by extension some degree of the quality of the life of people 60
                                                                                  203


years and beyond, but the wellbeing of this group goes beyond this one-

dimensional tenet. With 10.7% of the total population of Jamaica being elderly

people, 40.2% reported ill-health, 75.9% of those with dysfunctions indicated that

they were recurrent, and the reality of the possibilities of medical issues as well as

the cost of health care should be enough reasons for the study of the wellbeing of

this age cohort. But the issues surrounding age are not limited to those conditions

as the elderly require retirement planning and spending, as well as changes in

population composition and structure. It is clear from within the tradition of

Western culture that our emphasis is on medical conditions or the over

applicability of the biomedical model, despite the contributions of the WHO,

Grossman and other scholars that this conceptual definition is too narrow and

does not capture the multidimensional tenet of humans. Thus, it begs the question,

what about the sociopsychological and ecological issues, and do they affect the

quality of life of elderly people?

        Hence, this study is timely as it provides an analysis of the wellbeing of

our elderly. There is a cultural belief that aged people are among the most

vulnerable within all societies, and this is equally so in Jamaica. This assumes

that on an average the quality of life of this cohort of people is lower than that of

the economically and physically active population. This study concurs with the

overall suspicion of Jamaicans that the aged constitute a vulnerable group (the

average wellbeing of Jamaicans is 3.9 out of 14 – low wellbeing with a mode of

3.5). The research went further than computing a general self-reported index of

wellbeing, to build a model which constitutes demographic, psychosocial and
                                                                                 204


ecological variables that can be used to determine the quality of life of elderly

Jamaicans.

       Now, a study exists that measures the wellbeing of old aged Jamaicans.

The perspective from which quality of life is operationalized is different from its

predecessors in Jamaica, as it encompasses biological, socioeconomic,

psychological and ecological conditions.      The study finds that 40.1% of the

variation in aged peoples’ subjective wellbeing is explained by the 10 factors.

The model is comprised of eleven determinants which are as follows – area of

residence, environmental conditions, educational attainment of the person, cost of

health care, marital status, psychological conditions (i.e. positive and negative

affective conditions), age, crime, average occupancy per room and property

ownership. Of the major determinants, the five most important determinants are

average occupancy per room, area of residence, cost of health care, positive

affective conditions, and property ownership. It should be noted here that the

factor which most affects the subjective wellbeing of aged Jamaicans is average

occupancy per room, which implies that they prefer their own personal space.

Then, the region in which the elderly person dwells as in Kingston Metropolitan,

other towns or rural areas, makes a difference with regard to wellbeing. Those

aged Jamaicans who live in rural areas had the least wellbeing, compared to those

who reside in the Kingston Metropolitan Area, who had the highest quality of life.

In addition, cost of health care plays the second most influential role, which

means that wellbeing can be bought followed by positive affective conditions.

The positive cognition of individuals has a direct bearing on the quality of life, as
                                                                                   205


it acts through self-actualization, self-esteem, self- fulfilment and attitudes that are

agents of higher wellbeing. The paying of property taxes which is a proxy for

land ownership plays the fifth most important role in determining wellbeing. This

implies that the holder of more property has a greater wellbeing compared to an

aged person who owns less property or none at all.

       Despite the five most influential factors that determine the wellbeing of

aged Jamaicans there are some that are equally significant, but play a lesser role

than the five conditions that were previously mentioned. The findings show that

both the age of the respondents and negative affective conditions are inversely

related to quality of life. It follows that the older an individual becomes the lower

the quality of life he/she will have. An important finding is that individuals with

negative affective conditions such as hopelessness or pessimism will have a lower

wellbeing, as their attitude will result in stressors, inabilities, disabilities and

unhappiness, which are negative determinants of wellbeing. Crime, which has

become a staple in the Jamaican society, is the seventh condition affecting the

quality of life of aged people. This finding shows that it is positively related to

wellbeing, which means that more crimes are experienced by aged Jamaicans with

more resources. On the other hand, marital status and environmental factors are

inversely related to quality of life. The variable which contributes the least to the

wellbeing of the elderly is marital status followed by environmental conditions.

       Pacione (2003) has generalized that environmental quality plays a

significant role in determining the quality of life of people. This, he argues,

results from population density, crowding, poor housing, design of built
                                                                                   206


environment, temperature, and pollutant levels which may result in fatigue and

reduced ability to cope with issues that influence wellbeing. Because the human

body relies on the environment for oxygen, and indeed for survival, airborne

pollutants will affect the quality of life of aged people, as the biological process is

influenced by the environment (Eldemire 1994). Airborne particles can cause

respiratory or cardiovascular illnesses that substantially plague the elderly

(Cajanus 1999) and are a reason for the deaths in this age cohort (O’Neil et al.

2007; American Thoracic Society 2002). Another scholar went further in the

process, generalizing that people between 65 and 74 years, following exposure to

air pollutants, had a higher death rate than children of less than one year (Sastry).

Where the literature has clearly indicated a correlation between the environments,

this study concurs with them, but must say that it is the least factor in predicting

the subjective wellbeing of the Jamaican elderly.

       Having identified that the wellbeing of aged people is influenced by a

number of conditions, from the explained variation of 40.1%, may one be tempted

to argue that the model is useless or of little significance, as the unexplained

events are still to be investigated and are not found? A number of rationales

justify such a finding. But before they are embarked upon, this study must be

properly contextualized within a broader framework, as it has external validity.

A similar study called the SABE project, conducted in Barbados in 2005 by

Hambleton et al., found that 38.2% of the variations in the quality of life of aged

Barbadians (ages 60 or over) are explained by the model of determinants. Those

factors include lifestyle behaviours (exercise, conditions relating to smoking or
                                                                                 207


non-smoking), historical conditions (such as socioeconomic experiences early in

life), diseases, and current socioeconomic conditions (e.g. education of family

members, household room density, and all sources of income – including

pensions, retirements and social networks). Thus, this study is in keeping with

what exists in Barbados and is therefore a platform upon which further

investigations should be launched, with the inclusion of all other germane factors

that were omitted in these two works.

       The literature has shown that wellbeing is influenced by educational

attainment (Koo, Rie, Park 2004; Ross and Mirowsky 1999; Preston and Elo

1995; Smith and Kington 1997) which is also agreed on by this project. This

study concurs with Koo, Rie and Park that education is a predictor of subjective

wellbeing, but equally agrees with Roos et al.’s work (2004) that the association

is small (Pearson’s correlation = 10.5%). Based on the model of this study,

education is the ninth influential variable out of 11 on the subjective wellbeing of

aged Jamaicans. It should be noted that the relationship between educational

attainment and years of schooling is not a linear one. A recently conducted

research project disagreed with the aforementioned scholars, as the researchers

found a linear statistical correlation between self-rated wellbeing and education of

the youth and elderly (Bourne and Eldemire-Shearer 2009a). There is clearly a

disparity between the two studies, as the latter examined the youth and elderly and

not the entire population, whereas the former study investigated a population, and

this can offer some explanation of the middle age group (ages 26 to 59 years).
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         Ross and Mirowsky (1999) find that the well educated are more likely to

exercise, and that they are likely to be moderate drinkers and that they practice

more whole lifestyle behaviours, which are all factors that influence wellbeing

(see Hambleton et al. 2005). Owing to the limitation of this study, in that no data

were available on lifestyle risk behaviour, these were not included within the

model, and so validation of this fact was not possible. Another channel through

which education influences quality of life is occupation and employment.

         The SABE’s project used occupation and employment within its model,

which could further justify the difference of 1.4% in the explained variation (i.e.

36.8% - for this study and 38.2% for SABE’s project). Although employment

status was in this dataset, it could not be used in the model, as only 22.3%

(n=518) of the sampled elderly were employed, with a non-response rate of

77.2%.     Employed people 65 years or over are within different occupational

types, but from the high percent of missing data, it had to be omitted from the

model. Occupation is an indicator of social class and/or societal standings

(Palmore 1981) and so with such a high valuation of non-responses for the

employed sampled population, there was no sense in including this factor as well.

Thus, these two factors were excluded from the final model, but based on the

literature they are equally important determinants of health status and subjective

quality of life (see Adler and Newman 2002; Palmore 1981). Adler and Newman

2002 found that the health status of the employed is higher than that of the

unemployed, but this could not be collaborated by this research, as they were not

used.
                                                                              209


       Apart from the direct association between occupation, education and

quality of life, Adler and Newman argue that education and occupation are

complex determinants in relation to their association with health status. This

happens in that education and occupation are strong predictors of income, social

class, ability to access information and certain resources that are themselves

factors of wellbeing. Social class, occupation and typologies of employment

status are indicators of marital status, which takes the researcher to the next

factor, marital arrangement.

       Moore et al.’s work (1997) shows that people who dwell with their

spouses, compared to those who reside alone, enjoy higher subjective wellbeing.

This research also agrees with studies by Moore et al, Smith and Waitzman

(1994) and Delbes and Gaymu (2002) in that higher subjective wellbeing is

experienced by married couples compared to other union typologies. Roos et al.’s

study (2004) justifies this situation, when they show that couples practice less

risky lifestyle behaviours, and eat better, and Smith and Waitzman (1994) add that

wives are more likely to have their husbands seek preventative care, although this

may go against the male’s socialization. To further understand the role of marital

status, Elwert and Christakis’ work (2006) is fitting here. They find that after

bereavement, mortality is higher among the sexes (also see Baro 1985), which

means that separation by death or other eventualities such as divorce will

influence subjective wellbeing and further justify a higher quality of life for

married people, as compared to non-married individuals. Even though there was a

clear association between marital status and the subjective wellbeing of elderly
                                                                                 210


people, it was a low one (β = -0.088), which means that it contributed second to

the least to the quality of life of aged people. Generally, marriages in Jamaica are

between males and females, and so this begs the question - is there a difference

between the subjective wellbeing of the sexes?

       One of the contradictions of this study is the fact that gender was not

found to be a factor in determining the subjective wellbeing of elderly people.

Such a finding means that there is no statistical difference between the quality of

life of a male or a female (ρ value = 0.127).         The literature, however, has

demonstrated that the economic wellbeing of males is greater than that of their

female counterparts (Rudkin 1993). Haveman et al.’s work (2003) finds that the

material resources of retired men are greater than those of females, which goes

further to justifying why their economic wellbeing is higher than that of their

female counterparts. Schoen et al.’s study contradicts the general hypothesis that

males’ health status is greater than females, by arguing that men are more stressed

and so they are less healthy. Herzog (1989) analyzing ‘physical and mental health

in older women’ concludes that the rate of depression for females is higher than

for males, which contravenes Schoen et al.’s work. What this research concludes

is that there is a statistical difference between the wellbeing of the sexes, but that

it is for single people (Levene’s Test F=12.41, ρ value = 0.001).

       In this study, the wellbeing of single aged females is higher compared to

that of single aged males. Unlike studies that use income (or GDP per capita) to

evaluate wellbeing, or illnesses/ailments and disabilities to measure health, this

work twins both factors in its assessment of a subjective wellbeing index. This
                                                                                 211


difference may not have emerged because approximately 73% of the sampled

population was married at some point or they are still married, and such unions

share income and material possessions including durable assets. Therefore, the

differences between gender wellbeing may be problematic as household income

and other resources are reported jointly. However, there is a clear distinction

between the incomes of single persons; reported items are for a specific individual

and not joint custody.

       On the issue of possessions, the ownership of houses that is established in

the literature as having an influence on wellbeing did not turn out to be so for this

study (ρ value = 0.379 > 0.05). The works of Barresi et al. (1983) and Breeze et

al. (2004) have categorically showed that aged people who possess their own

homes experience greater wellbeing than those who pay rent or lease their

dwellings. Breeze et al.’s work, using medical data in Britain, finds that seniors

who own their homes are less likely to report poor quality of life. Within the

context of Jamaica, elderly people are less likely to view a home as a tool for

investment; as such, they use their homes as collateral. Thus, the house is seen as

a piece of property that must be left for the upcoming children. In addition, with

67.8% of the sampled population residing in rural areas, a house is less likely to

generate income (i.e. rent) than in urban areas, which further justifies why paying

property taxes was significant related to subjective wellbeing. The paying of

property taxes by elderly Jamaicans was a proxy variable for land ownership.

Land in rural Jamaica is more an investment, which the elderly are able to use for
                                                                                 212


income generation. In addition, land ownership in rural Jamaica is used as a

measure of social status which further brings about a certain psychological state.

       On the matter of psychological state, which may be either positive or

negative affective, Lyubomirsky (2001) shows that happier people view life in a

positive manner. This attitudinal state explains how decisions are taken, and

moods are experienced. A positive mood provides a better quality of life, as the

individual thinks, acts, builds and carries out his/her life’s task with more self-

assurance (Leung et al. 2005).      The opposite is equally so, as a pessimistic

individual is more likely to have lower self-esteem, self-fulfillment, and be less

self-actualized than someone who is optimistic. DeNeve and Cooper (1998) find

that happier people are more optimistic and positivistic in nature. Diener and

Seligman (2002) point out that moods are not stationary, and so happy people can

have negative moods, which means that positive individuals do not dwell on the

negatives indefinitely.   Harris et al’s work     (2005) establishes that negative

affective conditions such as guilt, fear, anger and disgust inversely affect

subjective wellbeing, as positive factors directly influence wellbeing (also see

Fromson 2006). The literature has shown that the elderly seek more health care

than any other age cohort, and so the issues of biological conditions will result in

a certain psychological state, where, if an elderly individual does not perceive that

he/she has control over illnesses or disabilities, it may result in self-destructive

behaviour (McCarthy 2000), which will influence his/her wellbeing. McCarthy

offers a further justification for the correlation between psychological state and

subjective wellbeing, when he writes that diabetic patients are six to seven times
                                                                                213


more likely to suffer from psychiatric illnesses, anxiety and depression. In this

research, however, the ranking of positive affective conditions and negative

affective conditions was different, as the positive affective was the fourth most

influential determinant of wellbeing, whereas the negative affective condition was

the sixth of 11 determinants. Although scholars did not distinguish between the

positions of each, being happy and optimistic contributes more to one’s subjective

wellbeing than being negative, which reduces it. Religion is one factor that

fosters optimism (or a positive attitude to life’s challenges) – (also see Wiegand,

and Weiss 2006).

        Like Marx, the researcher believes that religion is a tranquilizer to many

realities. Religion is not merely a practice but it is an institution with tenets,

which teaches one to put a greater value on future life. Within this setting, people

are able to endure present difficulties for the promise of future pleasure, as the

opportunity cost of foregoing for futuristic immortality in peace, prosperity and

affluence is greater than the cost of earthly pleasures. Thus, by accepting religion

within the Jamaican society, the individual is socialized to pass all his/her

‘troubles’ on to God. In addition, he/she is culturalized to accept his/her present

situation as Robert Nesta ‘Bob’ Marley argues “for every little thing is going to be

alright”.   This reality symbolizes the optimistic attitude that is adopted for

survival (Diener, Suh and Emmon 1984), so it should come as no surprise that

religion should have a positive influence on subjective wellbeing. Scholars like

Frazier et al. (2005), Edmondson et al. (2005) and Kart (1990) have all agreed

that the influence of spirituality on wellbeing is definite.    The belief is that
                                                                               214


through religion, many behavioural habits such as heavy drinking of alcohol,

smoking and unhappiness are averted (Kart 1990). One researcher found that

cancer rates were lower in people who accepted spirituality than those who did

not (Gardner and Lyon 1982a, 1982b). Those studies are all on non-Caribbean

geo-political spaces and a research done by Hutchinson et al. (2004) on Jamaicans

concurred with the findings in other geographical locations. They found that

religiosity was positively related to the psychological wellbeing of some 2,580

respondents.

       Church attendance (or frequent visits or religiosity – that is not based on

special occasions such as weddings, funerals, christenings, baptisms, graduations

and other such events) is singly not only about a positive mindset, but the church

is a meeting place for the elderly and a source of emotional and financial support.

As such, when an elderly person becomes involved in high religious activities,

he/she becomes a part of a body of similar-minded individuals, who share, care,

and are equally concerned about the self-development and self-needs of the

elderly. Even the nature of prayer with or among people is another technique for

reducing blood pressure (Callender 2000), which affects the health status as well

as the subjective quality of life of the elderly. It follows that religion and/or

religiosity is an important predictor of wellbeing (also see Watt, Dutton, and

Gulliford 2006), but it could not be investigated within this study because it was

not available in the dataset, and so this may further explain the high-unexplained

variation of the model.
                                                                                215


       This study has expanded on Smith and Kington’s model by adding a

number of new factors such as crime and victimization, positive and negative

affective conditions, ecological factors, area of residence, and age of respondents.

Another important inclusion in this model is how wellbeing was constructed, as

demographers (see Crimmins, Hayward and Saito 1994) use functional ability

(i.e. health status) to evaluate wellbeing, and so do Smith and Kington, while

economists use income per capita. However, for this study wellbeing was

considered to be a composite value of health status and income. This definition,

therefore, is a cross between what the economists use (i.e. income) and what

many demographers use - functional ability. A critical finding in this paper is that

using self-reported health status to measure wellbeing is problematic, and that an

objective approach is a better yardstick than subjective health conditions. Owing

to the limitations of the dataset, the researcher did not use some of their

determinants. The examples are as follows – previous health status (i.e. stock of

health), lifestyle behaviours and religion or religiosity. Those exclusions from the

model definitely explain the reason behind the low explanation valuation for this

project. While this study or the SABE’s project may not have fully provided a

statistically strong explanation of the quality of life of the aged in either of the

two societies, we are sure that the subjective wellbeing of aged people is affected

by biological, psychological, socioeconomic and ecological conditions, and that

these studies can be a platform for further work to be carried out.

       The current work has shown that using self-reported health conditions to

conceptualize wellbeing is not a good approach, as its explained variance is 2.4%,
                                                                                216


which is lower than that of an objective approach (40.1%). Despite the lesser

explanatory power of a subjective assessment of wellbeing compared to an

objective evaluation, the former is more in keeping with a multi-disciplinary

perspective on humans, as was offered by the WHO in the Preamble to its

Constitution in 1946, and equally supported by Dr. George Engel. In addition,

psychosocial and ecological conditions do influence the composite wellbeing of

the elderly in Jamaica. A rationale that can justify the low power for the

subjective assessment of wellbeing is the difficulty of measuring it precisely as

against the objective assessment of wellbeing in which each factor is

operationalized and measured with a greater degree of precision. This does not

militate against the reality of subjective variables, and unlike Bok and Crisp, the

author believes that currently we may not have captured the precise unit of

measurement for evaluating subjective wellbeing, but that reverting to the past

(economic wellbeing) is not an option. Instead, the author urges researchers to

develop a subjective measurement that captures the reality of people, rather than

this one-directional economic assessment. Researchers such as Richard Easterlin,

Edward Diener, Rutt Veenhoven and others have argued that happiness is a good

proxy of the general state of an individual, but this again can be questioned as

happiness is highly subjective. Subjectivity does not mean it is not real, as we are

cognizant of issues such as pain, fear, anxiety, depression, fatigue and other

psychological conditions which influence the effective operation of an individual,

and it is in this context that the author urges researchers to come up with a

subjective-objective method of assessing wellbeing as against economic
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wellbeing. Like Dr. George Engel, the author knows that many biological

conditions are owing to non-economic and non-priced conditions; hence the need

to capture them in the mix of wellbeing, especially for the elderly whose

wellbeing is more subjective than economic.

       Among the many attributes of ageing is the individual’s ability to cope in

adverse situations, as his/her current perspective is fashioned by history and past

challenges. This tool is acquired with time and is oftentimes a potent life coping

skill for the elderly. Embedded here is the ability of the aged to demonstrate

greater resilience than younger people, and the issue of compliance is greater

among the former than the latter group. These are among the laden gifts of ageing

compared to youth, and these enhance the quality of life that an individual lives.

They are intangible assets which are highly subjective and must be excluded in

any monetary assessment.

       The general wellbeing of the       elderly in Jamaica is affected by (i)

psychological conditions - positive and negative affective conditions; (ii) area of

residence; (ii) crime; (iv) marital status; (v) physical milieu; (vi) property

ownership; (vii) educational level; (viii) cost of health care, (ix) average

occupancy per room and (x) age of the respondents. The five most important

factors impacting on the wellbeing of the Jamaican elderly in descending order

are as follows: average occupancy per room (β = -0.229), physical environment (β

= -0.190), education (β = 0.173), area of residence (β = 0.164); and cost of health

care (β = 0.148). Thus, the significance of this paper is that we now have a

quantitative, empirical model that can be used to evaluate the wellbeing of elderly
                                                                                  218


Jamaicans.

       Among the findings of this study, that has shown no statistical relationship

between itself and wellbeing, is home ownership. The literature established that

there is a clear association of the aforementioned factors, but this study has

revealed a disassociation between the two variables. Within the concept of the

elderly, home is an investment for the children and so they are not likely to

venture into activities that will incur a risk of foreclosure on their asset. Thus, the

elderly are least likely to use their homes as a risky income-generating

investment; and so owning a home does not add any benefit to wellbeing, except

within the qualitative respect of leaving something for the children (or

grandchildren) after their death. In 1997 Eldemire noted that 74.6% of elderly

Jamaicans own their own home, but           the PLC – Jamaica Survey of Living

Conditions - (2002) found that this had increased by 11.3% (i.e. 85.9%). Some

people may be inclined to arbitrarily use this numeric increase in assets as an

indicator of an improvement in the quality of life, but is it?

       Then there is the issue of owning a home, but being unemployed, single,

old, living alone and having no health insurance, and so the fact of having

somewhere to call your own does not contribute to an improvement in quality of

life. Eldemire (1997:90) cites that in 1990, the aged were self-employed for a

substantially significant proportion of their lives. Although we are not able to say

that this has changed in 2001 and beyond, based on our reading we can say that in

excess of 75% of the elderly are unemployed. The economic reality of ‘elderly

Jamaicans’ does not cease there, as in 2002 6.5% of them received payments from
                                                                                  219


the National Insurance Scheme (i.e. NIS) and 20.9% got private and government

pensions, with 10.2% having received both NIS and pension payments. Another

reality of the ‘elderly’ in Jamaica is that most of them reside in rural areas

(approximately 66%).     However, the rural elderly received the least in NIS and

pension payments compared to their aged counterparts who dwell in other towns

or the Kingston Metropolitan Region (i.e. KMR) – 17% of the elderly in rural

Jamaica received private or government pension payments, and 5% received NIS.

The reality of the ‘elderly’ is further complicated as the findings revealed that

most of them are living alone (i.e. in a one-member household).           Eldemire

(1997:90) explains a possible question that you may be asking – ‘How do they

survive?’ - saying that 65.2% of them are supported financially by their families,

and that 39.2% receive government food stamp benefits.

        As distinct from the unrelatedness between home tenure (i.e. own, squat,

owning a house) and wellbeing, there is a positive association between quality of

life and property ownership, which is conceptualized as owning land and/or

buildings. Embedded in this finding is the fact that elderly Jamaicans use land as

an income-generating asset. But culturally a house is an asset to which Jamaicans

cleave, unlike land or other non-house buildings.         A house is a personal

accomplishment, and so it has intrinsic benefits for the recipient. Therefore, the

elderly are even less likely to risk such an asset, as they consider themselves

decreasingly less likely to replace it in the event of a loss. Thus it is important

for them to leave a house for their loved ones after their death, and they will

forego current consumption for their family’s future benefits and satisfaction.
                                                                              220


       Undoubtedly the ‘elderly’ require economic and social support within the

context that many of them would have lost a substantial portion of their income

due to retirement, or a reduction in their working time due to ageing, as well as

the fact that some of them would have outlived their partners and associates and

so they must depend on the extended community. It also follows that the priority

of the elderly has shifted away from material possessions, and therefore they

would place more emphasis on intangible things – post mortality, humanity,

social support and so on – from which they derive more utility (or satisfaction).

But this quantitative evaluation of their wellbeing was not captured or examined.

However the fact is, the elderly gain more utility from intangible things. Thus,

what is the real contribution of this study?

       The use of dysfunction or income to measure wellbeing is limited and

unidirectional. However, a composite approach to this discussion reduces many

of the limitations to the single method. In addition, it is a better approach to

examine a multidimensional perspective as it reduces the number of negatives.

This study did not address the challenges of population in the form of public

health concerns, productivity and production, economic development, social

security, and retirement planning. However, we are now provided with at least a

basis upon which we can extrapolate on important issues that affect the quality of

life of society, the individual and the elderly. It is inevitable that demographic

ageing will mean changes in retirement planning. But policy makers should not

avoid the possibility of changing the age of retirement, which would be in keeping

with the changes in age dependency ratio, elderly dependency ratio, and the
                                                                                 221


burden it will mean for the quality of life of elderly people post-retirement.

        In addition to the aforementioned situations, we have identified several

factors which influence the wellbeing of the Jamaican elderly. But up to this

point, we have not examined specific factors such as loneliness, culture,

religiosity, HIV/AIDS, bereavement and death of close family members,

unemployment, and other issues relating to the quality of wellbeing of an elderly

person. We are arguing that despite the contributions of this study to an empirical

framework of wellbeing in Jamaica, there is still a definite need to investigate the

quality of the wellbeing indicators as well as other issues. It should be noted here

that the wellbeing of aged Jamaicans is such that a qualitative assessment of the

quantitative factors is needed in order to establish a deeper understanding of the

‘quality’ of wellbeing of aged Jamaicans from their perspective.

       Any assessment of wellbeing cannot be completed without an evaluation

of the subjective aspects of life, as people essentially know themselves better than

an external source. Scholars like Edward Diener and others (J. Larson; S. Levine;

R.A. Emmon; M. Suh, and E. Lucas) have shown that psychological wellbeing is

a ‘good’ measure of wellbeing, like the objective measure that was proposed and

widely used by many quantitative scholars (A. Sen; Becker, Philipson and Soares

2004; Gaspart (1998) Thomas Hurka (1993). We will repeat an important point

that was put forward in the early part of this work. Summers and Heston (1995)

note that “However, GDP POP is an inadequate measure of the immediate material

wellbeing of countries, even apart from the general practical and conceptual

problems of measuring their national outputs.” Generally, from that perspective,
                                                                                222


the measurement of quality of life is, therefore, highly economic and excludes

psychosocial factors. People’s psychological state is associated with self-esteem,

life tasks and goals, a sense of belonging, realization and temperament, which

undoubtedly affect the quality of life of the elderly. Within this work we have not

examined life satisfaction as an indicator of wellbeing, and it is a fact that

people’s past experiences (or lack of) affect their current wellbeing. Thus,

people’s behaviour and attitudes toward health, life practices, and illnesses, guide

their wellbeing; and these are not captured in any quantitative assessment, as was

examined by this study.

       In spite of the twofold increase in the life expectancy of Jamaicans over

1880-1882 and 2002-2004, which has resulted in population ageing owing to

advances in technology, science, public health, and literacy, our elderly

population continues to survive within a poorer socioeconomic and political

milieu. In Jamaica, the decline in fertility since the 1970s, accompanied by some

of the aforementioned conditions, accounts for many of the island’s problems. It

is clear that the changing population dynamics require current redress as they will

have futuristic challenges for the society. The futuristic problems which are

implied here are not owing to retirement income payments, but to issues such as

increased cost of hospitalization, increased dependency at older ages, increased

demand for medication, reduced contributions to income tax and a changing

pattern of diseases. Population ageing is also associated with a shift in sex ratio

towards the feminization of ageing. Accompanying the demographic transition

are some of the aforementioned issues, but there is a changing demand for
                                                                                  223


particular goods and increased dysfunctions. The challenges expand beyond

biological and economic conditions, to include the failure to effectively plan for

population ageing, as the needs are changing, and they must be addressed within

the context of the current economic downturn in the United States.

       Planning in the Caribbean, and in particular Jamaica, has not included in

economic growth calculations on population ageing, feminization owing to this

phenomenon, and the likelihood of stationary population in the future. There is

another potent component that has yet to be brought into the economic discourse

of this society, and that is the power structure that will result from population

ageing, and the implications of the likelihood of an increase in the age of

retirement, with the consequences of this reality on opportunities for youths. It

appears that policy makers in Jamaica are saying that time will tell, and that God

will take care of the future, so we can just plan for the present. The author doubts

that this is the cosmology of Jamaican social policy makers, legislators,

government, or the populace; however, policies and thoughts about concerns on

population ageing have not begun in earnest. The best planners are those who plan

for expectations, shifts, and social, physical and other demographic changes in the

population. In short, the author is convinced that this book will commence the

debate from which policy shifts will emerge. On the contrary, if the debate is

confined to verandahs, then the future of society is left to the gods, like other

psychosocial challenges currently facing the island – high crime and

victimization, unemployment, the economic downturn, low morale, distrust and

corruption. It should not be forgotten that the population of a society is its greatest
                                                                                224


resource, and failing to plan for it does not mean that we have planned for all

forms of challenges including zero-growth, non-functionality of pension schemes,

costly hospitalization expenditure, sterilization of social programmes, and the

need to devise a population measurement for the ageing population, like that

which has been devised to address high fertility.

       In summary, like Cajanus (1999:230), we believe that “the importance of

the elderly population needs to be recognized, and a life-stage approach to the

issue adopted by countries…” as this cohort of individuals is here to stay, and will

contribute increasingly more to Caribbean populations, Jamaica in particular.

This study has provided us with a basis upon which we can now construct a

comprehensive plan of action to adequately cater to the needs of this group, as

well as a modification of the existing dominance of the biomedical model in

patient care, and the conceptualization of health care in Jamaica. If we are agreed

on the premise that the elderly represent a vulnerable group of people, the time to

examine this group is now. Although Jamaica as well as some other Caribbean

islands – for example, Barbados and Trinidad and Tobago - can boast of its high

life expectancy, with the corresponding increase in chronic diseases, we must

abandon our emphasis on diseases (or dysfunctions) in the conceptual definition

of health. This study, although it does not claim to provide all the answers (or for

that matter, even the majority of them), has revealed that a multidimensional

approach to the study of health is possible. Since Caribbean societies cannot turn

back the hands of time regarding demographic ageing, we should forge ahead

with a plan that seeks to understand not only population ageing and the needs of
                                                                                 225


this group, or the chronic diseases, but a systematic structure that addresses the

reality of an ageing population. This plan of action should incorporate socio-

psychological, environmental and biological issues that affect the quality of life of

the elderly, which must be a deviation from the present emphasis on life

expectancy and our preoccupation with dysfunctions (or ailments), instead of

quality of lived years.        Come the next four decades, the country’s elderly

population is expected to more than double (see Figure 11.1.1) and within the

findings of this study; I will be presenting ‘The Way Forward’.




              Elderly (60 years and over) as a percentage
                 of total population with time, Jamaica
    30.0%

    25.0%

    20.0%

    15.0%

    10.0%

     5.0%
         1850                   1900               1950          2000      2050
  Figure 11.1.1: Constructed by author using data from
                                                      Year
  http://www.un.org/esa/socdev/ageing/workshops/vn/jamaica.pdf
Figure 11.1.1: Percentage of Elderly (ages 60+ years) of Jamaica, 1850-2050

The Way Forward

George Engel (1960, 1977a, 1977b, 1978, 1980) was the first to develop what is

known as the biopsychosocial model. He contends that health care must be

addressed from biological and socio-psychological dimensions, as humans are

both body and mind, which means that any single definition of health that fosters
                                                                                 226


its image, must cater to this reality. This is still nothing new, as it is in keeping

with the WHO’s conceptualization of health, that includes complete physical,

psychological, and social wellbeing, and not simply the absence of disease or

infirmity (WHO, 1948).

       In an ethnographic study carried out during September and October 2000

with some 40 school-aged street children in Pakistan, Ali & de Muynck (2005)

concur with the perspective that health must be viewed outside of biological

conditions. In their study, they found that the children reveal that they seek

health-care based on (i) severity of ailment, and (ii) financial situation. It should

be noted, however, that this is primarily based on the biomedical

conceptualization of the phenomenon of health, and that this is not in keeping

with the World Health Organization’s definition of health, which expands beyond

biological conditions to “a state of complete physical, psychological, and social

wellbeing…” (WHO, 1948). Despite WHO efforts on the widening of the

construct of health, and by extension research on health care, within many

societies health demand (i.e. health-seeking behaviour) continues to be gender,

education, age and information-sensitive as well as emphasizing biomedical

conditions.

       Some health practitioners, and equally some people outside of the health

profession, believe and continue to see health within a one-dimensional tenet –

sickness, diseases, or infirmity - which guides how they respond to health matters.

In Jamaica, ergo, a visit to a health practitioner is an indicator of weakness,

infirmity or disease, and not a fundamental approach to preventative care, as
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health is a curative care matter. Becker and Rosenstock’s work (1984) shows that

people’s health demand is a factor of their beliefs. This speaks to the value of

culture and socialization in health demand, and it means that they will seek care

based on (i) perceived susceptibility to diseases or illnesses or disability, (ii)

severity of the diseases and/or disability, (iii) benefits of health-enhancements,

and (iv) perceived hindrances to health-enhancing behaviour, including financial

inability; as such, health-seeking behaviour is not limited to diseases and/or

disabilities and one’s sex.

        Many men are only willing to visit health practitioners in the event that the

ailment or disability is severe and extensive, and may result in death. Their first

point of contact in case of dysfunction, or their perception of ill-health occurring,

is to use self-care or self-medication, compared to women who are eager and

willing to seek heath-care on the smallest of perceived symptoms of ill-heath, and

even for preventive care. A group of researchers found that men are only willing

to report life-threatening illnesses like heart disease; this is also reiterated by Low

et al. (2006) who argue that even when men suffer from erectile dysfunction only

10.5% of them seek help. These barriers to health-seeking behaviour are all

embedded in one’s beliefs, which could be as a result of perceived personal

control of the situation, level of optimism (Clarke et al. 2000), ethnic background

and level of risk taking. These cultural happenings are not limited to Jamaica and

the Caribbean, as a study conducted in Malaysia shows similar health-seeking

behaviour to that in Jamaica and in Pakistan (1). Low and colleague (2006) cite

that:
                                                                                 228


       Erectile dysfunction (ED) is a common sexual disorder affecting men. [1-
       3]. Although new treatments for ED have emerged for many years, this
       does not directly translate into men actively seeking treatment for their
       ED problem (Low, et al. 2006)

       A substantial aspect of this is the emphasis that is placed on biomedical

treatment, and people’s perceptions of issues that are classified as health related.

This is even evident in how information is collected on health, how health is

measured in many studies, and how people internalize those symbols. This

explains how society deals with particular health-related matters. Low et al. state

that “some men did not see ED as a medical problem, while others accepted it as a

normal sequence of aging” (Low, 2006). But still the reality lingers, health is

substantially seen as a biomedical phenomenon – that is, communicable diseases,

maternal and prenatal conditions, nutritional deficiencies and non-communicable

diseases as the causes of changes to health status and/or death. But a question still

remains: Are we responsible for the one-dimensional health-seeking behaviour of

people?

       While the physical and social environment shapes behavior, people are
       not passive in the process, since they in turn can change their
       environments – a reciprocal dynamics. (Murphy, 2005),

       Human      existence    is   continuously    interfacing   social,   cultural,

psychological, and political experiences, and so biomedical theorizing is a

simplistic perspective on the subject matter as health is the absence of illnesses

[biomedical] and the psychosocial state of an individual.           People casually

perceive health from the perspective of physical illnesses, so much so that in the

absence of certain physiological indicators they perceive of themselves to be

healthy, and so they will address matters relating to care based on their socio-
                                                                                   229


cultural attitudes and valuations (Low et al., 2006).            Health, despite its

fundamentality to existence, is not limited to a single space (i.e. quantification), as

human beings are physiological, social, psychological and highly subjective.

Thus, health-care-seeking behaviour should not be constricted to mere absence of

physical illnesses because this is quantifiable, but the phenomenon must be

analyzed from within a psychosocial space in addition to traditionalist theorizing.

       The dominance of positivistic science in measuring health speaks to a

number of the psychosocial ills that are unaddressed by countless Jamaicans, and

this will continue into the distant future if the traditional viewpoint of health does

not abate with proper education. Furthermore, if the level of education of a group

of people is relatively low or even mediocre, what are the possible outcomes of

their perspectives on many issues, including that of health-care?

       Health and its care are not only indicators of wellbeing, but health status is

also a determinant of human development, and so must become a concern for

policy-makers. Thus, the one-dimensional perspective of health and health-care

permeates the human space and explains the high preponderance of research on

this conceptual definition. This explains why there are no statistical agencies in

Jamaica that are collecting data on issues such as the frequency of visits to

gymnasiums, knowledge and healthy eating and ‘best practice’ in regard to

preventative care. The importance of this phenomenon has helped the author’s

investigation of the matter. In order to present a perspective of Jamaicans on

health-care, the author will use a secondary data source. The purpose of this
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approach is to establish external validity, and to formulate a theoretical

framework on the health demand (i.e. health-care behaviours) of Jamaicans.

       It is extremely difficult to conceptualize health in an operational manner

that is simple, as the concept is multi-dimensional in part, and must include a

social realm. Hence, health will be conceptualized within the operationalization

of the WHO’s Constitution of 1946: “Health is a state of complete physical,

mental, and social wellbeing and not merely the absence of disease or infirmity”

(WHO, 1948). This, therefore, comprises biomedical conditions, lifestyle habits,

access to care and quality of life conditions. Such a view on the subject aptly

describes the matter that health is to be judged from the aspects of how well

people perform everyday activities, to what extent they are capable of taking part

in social activities, and the harmonious relationship that they have with the

environment.

       This study seeks to examine the determinants of health of Jamaicans.

Jamaica’s population continues to increase while young male adults are

experiencing increasing injuries; in addition, there are concerns for care for the

elderly. Injuries, for example, are among the leading causes of treatment at

government hospitals, and thus demand the continuous use of such facilities. This

diagnosis could be very costly for a Jamaican government that intends to

effectively plan for and implement health-care for the populace.          Therefore,

researchers strongly believe that this issue would be of paramount importance to

health analysts, health practitioners and planners. Within the construct of the

socio-demographic realities of this society, the research seeks to postulate a causal
                                                                                  231


relationship between health and biomedical characteristics as well as other

sociodemographic and economic variables. We now know those factors that are

important to the wellbeing (or health) of the elderly, and so their demand for

health care must be dependent upon those factors which drive their wellbeing.

       The way forward in public health is to plan for the elderly around the

importance of each factor that determines their wellbeing.          This study is a

theoretical model, unlike that which offered by Dr. George Engel, or for that

matter by the WHO in the Preamble to its Constitution in 1948. The experiences

outside of Jamaica are not necessarily the same, nor the applications to the

elderly, and this means that public health practitioners must use research on

elderly Jamaicans to guide policies, programmes and measures to address their

health and survivability, although valuable information can be had outside of the

country’s shores. This study is the catalyst for the way forward, and health

education and health promotion from this point onwards must address all the

tenets identified in this study in order for aged Jamaicans to effectively attain

healthy life expectancy.

       It is well established in the research literature that ageing (i.e. biological,

chronological or social ageing) is synonymous with 1) morbidity and 2) mortality.

Even if an individual were never to become ill, he/she will die from old age. This

means that death is a natural part of the life span, and that it occurs normally as

the cells in the human body gradually die, resulting finally in death. Mortality

which has been the focus of demographers for centuries – as an indicator of health

status – is undeniably unidirectional within a multidimensional space, and so I
                                                                                 232


will show the shift in typologies of diseases since the 1940s. Within the context

that the cell dies normally before the finality of death, people can live longer, but

this does not necessarily mean healthier. During the 1900s, the leading causes of

death were communicable and chronic diseases – these include tuberculosis,

syphilis, nephritis, pneumonia and influenza – but since the 1990s, an

epidemiological transition has occurred in non-communicable diseases (Wilks,

2007). These dysfunctions include malignant disease, cardiovascular and

cerebrovascular disorders and diabetes mellitus. While this text is a study on the

wellbeing of the aged, and given that most of the aforementioned dysfunctions

primarily affect older people, they have also occurred in younger people, and so

care should be taken in addressing all age groups in terms of diseases.

       Literature has provided evidence from both the developed and developing

world, suggesting that although the majority of the elderly enjoy reasonably good

health, and perceive their health as good, or lead purposeful lives (Powell, Bourne

and Waller, 2007; Kaplan 2003, Parsons1993, Clausen et al. 2000), many

challenges related to morbidity and morbidity control still exist. The tendency of

elderly persons to overestimate their level of wellbeing has been recognized

(O’Connor and Daley 1984). A study conducted in Botswana noted that

conditions relating to musculoskeletal, circulatory, neurological and eye disorders

are common among older persons (Clausen et al 2000). Kalache, Aboderin and

Hoskins (2002) have argued that chronic diseases occur at earlier ages in

developing countries, citing that the majority of people with diabetes, for

example, are in their productive years, i.e. aged 45–64 years. They noted also that
                                                                                233


the overall compression of morbidity (i.e. increased longevity with greater

proportions of old age being spent disability-free, and postponement of disability

to later life, with shorter intervals between disability onset and death) is yet to

occur in the developing world. Additionally, compared with developed countries,

older persons arrive at old age with fewer reserves (Kalache 1998).

       The way forward is for Caribbean scholars to develop an index of

wellbeing for aged people that will account for more than our current

understanding (i.e. 41%) of it. In addition to the aforementioned proposition, the

time has come for policy-makers within the region to fashion measures that will

be geared towards the improvement in wellbeing of the aged populace within the

context of the current findings. Population ageing in the Caribbean is here to stay,

and ageing in Jamaica is expected to double in 2050, plus with the reality that

increasingly more Jamaicans will be retired because of the current retirement age

coupled with the stressors on governments to provide social assistance for more

people, it means that the dependency ratio will become even more burdensome

for the working age population (ages 15 through 60 years). Hence, it is time for

us to begin a dialogue on the retirement age for Jamaica, and begin to build homes

that will cater to this ageing population as well as find transportation, work, and

technology for them.

       Population ageing signifies demographic transition (Bourne and Eldemire,

2008b), and reduced birth rate, which coupled with higher life expectancies,

means that people will be living across the technological era. During the

transition, many of the elderly will be left outside of this space, and the growth
                                                                                234


and developmental stage of these individuals will mean than they will not be able

to re-socialize themselves to this time period. The technological period may be

such that a plethora of activities will change and many elderly persons will be

excluded from the process. Hence, another way forward is for Caribbean scholars

to examine the psychological state of elderly people owing to changes in eras; and

this affects their living standard, personal health and wellbeing.

       Based on the high life expectancy of Jamaicans and the feminization of

ageing, the process signifies more than demographic or epidemiological

transition, as it includes the imbalance of power in that society. Caribbean

societies – in particular Jamaica - have not included in their policies the ‘balance

of power’ that accompanies population ageing, as we are yet to recognize the

image of ageing and the reality of the power dynamics that underpin demographic

transition. The elders are power brokers, and so with increasingly more of them,

how will youths become leaders within the general context of population ageing

and longer living people? How will the balance of power be transferred to the

youth, and when? The ‘imbalance of power’ and transition in power must be

included in Caribbean discourse, as answers must be put forward to address this

pending reality. This study does not have the answers to this issue; however, I am

putting forward the awareness of gerontological imagination – the awareness of

the process of ageing and an understanding of the scientific contributions of a

variety of researchers to the study of ageing and ‘balance of power’.

Gerontological imagination is a multidisciplinary sensitivity to ageing, and this

must incorporate a stock of knowledge of ‘imbalance of power’ arising from
                                                                                235


population ageing, in order to have empirical evidence that can be used to address

this pending social reality.

       Another way forward is for the training of many doctors in social

gerontology, as ageing is multidimensional, and includes physical, social,

psychological and societal aspects. Gerontology, which is the scientific study of

old age – coined by Metchnikoff in 1903 for this field of inquiry (Elie

Metchnikoff 1903) - must be incorporated into the curriculum of medical

practitioners, social workers, sociologists, police officers, counsellors, pastors,

policy analysts, accountants, economists, educators, high schools, and researchers,

as ageing must be as normal as it is a natural occurrence, and this will enhance the

multidisciplinary approach to understanding wellbeing, addressing it and

removing some of the stereotypes. The needs of older people are not the same as

those of children, the youth, working age people or infants, and so there is a need

for medical gerontologists to cater specifically to this age cohort, or geriatrics –

the systematic study of ageing (IL. Nasher 1909).

       Ageing is a normal process in the course of life, and this means that health

promotion experts and health educators need to educate the population about the

differences between ageism (the disproportionately negative connotations

associated with ageing) and ageing, and this process should begin with politicians.

I hope that this text – GROWING OLD IN JAMAICA: Population Ageing and

Senior Citizens’ Wellbeing – will provide for everyone an invaluable

understanding of elderly people’s health status, and be used as the new way

forward in examining and addressing the lives of aged people.
236
                                                                               237


                                           Glossary

Age:     Age is the total number of years which have elapsed since birth

(Demographic Statistics, 2005); or, the length of life of the individual (i.e.

existence).



Elderly (i.e. aged, or seniors, older adulthood): This terminology refers to the

chronological age beginning at 60 years and beyond.

Elderly cohort: Elderly cohort comprises the three categories into which elderly

people are grouped. These are as follows:

         (1) Young elderly (60 – 74 years);

         (2) Old elderly (75 – 84 years), and

         (3) Oldest elderly (85+ years).

Wellbeing: Wellbeing is defined as the summation of an individual’s physical

functioning (subjective wellbeing), and the ownership of material resources

(objective wellbeing).     Material resources consist of income, ownership of

different types of durable goods excluding a house, and/or the receipt of pensions.

Physical functioning, on the other hand, is the summation of five different health

conditions as reported by the individual. These health conditions include injuries

due to stabbing, diarrhoea, et cetera.

Sex: Sex is the biological makeup of males and females.

Educational level: Educational level is the highest grade of schooling that an

individual has completed. It ranges from no formal schooling to the post graduate

level.
                                                                                  238


Marital Status: This is defined as a conjugal arrangement between people,

which is based on the law of the country or its customs. These arrangements must

be between consensual adults (from ages of 16 years and older).

Household: A household is “one person who lives alone or a group of persons

who, as a unit, jointly occupy the whole or part of a dwelling unit, who have

common arrangements for housekeeping, and who generally share at least one

meal” (STATIN 2004, viii). A household does not necessarily consist of people

who are biologically related, as the individuals may be biologically related or

unrelated or a combination of both.

Household crowding (i.e. average occupancy per room): This is the arithmetic

mean number of persons who live in a room, of a defined household.

Crime: A crime is an act carried out by an individual which contravenes the legal

statutes of the country. For this study, it includes acts committed against a person,

or his/her close associates or people within the same household.

Environment:        The external physical surroundings affecting the growth,

development and survival of an organism. The organism in this case is the human

being. The elements here consist of air, water, land, soils, minerals, oceans, et

cetera.

Psychological factors: The mental state of a person which arises as a result of

his/her experience with the environment or a social happening. These are

classified as either:

(1) Negative Affective Conditions – negative emotions (e.g. loss of breadwinner,

loss of house, redundancy, failure to meet household and other obligations), or
                                                                                  239


2) Positive Affective Conditions – positive emotions or moods (e.g. hopeful,

optimistic).

Income (the proxy is population quintile). This is, as defined by STATIN, based

      on consumption patterns of individuals from a predefined basket of goods

      and other commodities. Its groupings range from the poorest group [quintile

      1 (i.e. those below the poverty line) to the richest group (quintile 5)].

Area of residence – This means the geographic location of one’s place of abode

(KMA, other towns and rural areas).

Cost of medical (i.e. health) care – The total amount in Jamaican dollars that is

spent on medication and hospitalization, which includes preventative care and

doctors’ visits.

Home Tenure: This refers to different types of home occupancy, including

owning, renting, leasing and squatting on land.

Property Ownership (using paying property taxes): The payment of taxes to

government for the ownership of property (i.e. land), which indicates ownership

of that geographical space.

Population Ageing is the percentage of the population age 60 years and older,

based on the World Assembly of Ageing definition of elderly (ages 60 years and

beyond) (United Nations, 1982, p.29).        Growth rate is the total number of

persons added to (or subtracted from) a population in a given period of time

owing to natural increase (births and deaths) and net migration, expressed as a

percentage of the population at the beginning of the time period.


ANALYTIC MODEL OF WELLBEING
                                                                                                240


DEPENDENT VARIABLE


Wellbeing: Wellbeing is one-half of the summation of material resources minus
one-half of the summation of physical functioning. In this study, self-reported
health conditions are used to measure physical functioning. Material resources
are measured by income, ownership of durable goods and financial support (see
below).

       Health status 1           1= Respondents having injury (i.e. gunshot, stabbing,
                                 accidental fall) during the past 4 weeks; 0 otherwise

       Health status 2           1=Respondents who have had any illnesses due to
                                 injury (cold, diarrhoea, asthma attack, hypertension,
                                 diabetes, or any other illnesses); 0 otherwise

       Health status 3           1=Respondents having recurring chronic illnesses (such
                                 as colds, diarrhoea, asthma, diabetes, hypertension,
                                 arthritis); 0 otherwise

       Health status 4           1=Respondents having physical or mental disabilities
                                 (i.e. mental, sight only, hearing only, hearing and
                                 speech, legs and arms or multiple disability); 0
                                 otherwise

       Health status 5           1=Respondents’ perception of what causes their ‘poor’
                                 health (i.e. dust, toxins and chemicals, dirty gullies and
                                 infection via food or water; 0 otherwise


       NB: Physical Functioning Index = Σ           Hi, where i ranges from health status 1
       to 5. The least score is 0 and the maximum score is 5, where 5 denotes
       experiencing all 5 health conditions.


       Income, Yi 3              1=Respondents being in quintile 1,
                                 2=Respondents in quintile 2;
                                 3=Respondents in quintile 3;
                                 4=Respondents in quintile 4;
                                 5=Respondents in quintile 5.




3
    Yi , where Y denotes the income measured by population quintile and i means each quintile
                                                                                  241


       Durable goods 4
       j601                       1=Respondents owning sewing machine; 0 otherwise
       j602                       1=Respondents owning gas stove; 0 otherwise
       j603                       1=Respondents owning electric stove; 0 otherwise
       j604                       1=Respondents owning fridge or freezer; 0 otherwise
       j605                       1=Respondents owning air conditioner; 0 otherwise
       j606                       1=Respondents owning fans; 0 otherwise
       j607                       1=Respondents owning portable radio etc; 0 otherwise
       j608                       1=Respondents owning stereo equipment; 0 otherwise
       j609                       1=Respondents owning other stereo equip; 0 otherwise
       j610                       1=Respondents owning TV sets; 0 otherwise
       j611                       1=Respondents owning VCR/DVD; 0 otherwise
       j612                       1=Respondents owning video equip.; 0 otherwise
       j613                       1=Respondents owning washing machine; 0 otherwise
       j614                       1=Respondents owning dryer; 0 otherwise
       j615                       1=Respondents owning bicycle; 0 otherwise
       j616                       1=Respondents owning motorbike; 0 otherwise
       j617                       1=Respondents owning cars; 0 otherwise
       j618                       1=Respondents owning computer; 0 otherwise
       j619                       1=Respondents owning computer scanner; 0 otherwise
       j620                       1=Respondents owning CD burner; 0 otherwise
       j621                       1=Respondents owning DVD burner; 0 otherwise
       j622                       1=Respondents owning other electrical equipment; 0
                                  otherwise
       j623                       1=Respondents owning musical equipment; 0 otherwise


Durable goods, DG = Σ j, ranging from 0 to 23, where 0 denotes owning no
                      assets.

Financial Support:
   Social security                1=Respondents receiving NIS; 0 otherwise
   Other pension                  1=Respondents receiving private, government or other
                                  pension fund; 0 otherwise

NB. Financial support, FS = Σ (NIS, Private pension, Government pension,
other pensions), ranging from 0 to 2, where 0 represents not receiving any form
of pension payment to higher score indicating receiving more.

Material resources, MR =DG + FS + Yi where the index ranges from 0 to 25, in
which low score indicates low economic wellbeing and higher score greater
economic wellbeing

Wellbeing Index = ½ [MR] - ½[Σ Hi ], where higher values denote more
subjective wellbeing. The index ranges from a low of -1 to a high of 14. A score


4
    See Appendix VIII for detailed listing of the question from the instrument
                                                                                 242


from 0 to 3 denotes very low, 4 to 6 indicates low; 7 to 10 is moderate and 11 to
14 means high wellbeing.

INDEPENDENT VARIABLES

Socio-demographic and psychological indicators

1.    Elderly
2.    Sex                     1=Respondent is male and 0 equals to Otherwise
3.    Marital status:
      maristatus1             1=Divorced, separated and widowed, 0=Otherwise
      maristatus2             1=Married
      The reference group is single

4.    Average occupancy per room –

      This variable equates to the number of persons per household divided by the
      number of rooms (excluding kitchen, verandah, and sanitary conveniences)

5.    Area of Residence:
      Area_Residence2          1=Other Towns, 0= Otherwise
      Area_Residence3          1=KMA, 0=Otherwise
     The reference group is rural area

6.    Cost of care               a12=cost of health care in public facilities
                                 a13=cost of health care in private facilities
                                 a27=cost of medication in public facilities
                                 a28=cost of medication in private facilities

NB Cost of health care = Σa i , where i denotes 12, 13, 27 and 28; ranging from
Ja$0.00 to Ja$2,000 (in this period US$1=Ja$50.97)

Negative Affective
          1. Difficulty meeting         1=school related costs, 0 otherwise
                                        1=health related expenses, 0 otherwise
                                        1=transportation costs, 0 otherwise
                                        1=food costs, 0 otherwise
                                        1=entertainment costs, 0 otherwise
                                        1=clothing costs, 0 otherwise
                                        1=loans, 0 otherwise
                                        1=vacation needs, 0 otherwise
                                        1=utilities, 0 otherwise
                                        1=other expenses, 0 otherwise
           2. Inability to pay          1=electricity, 0 otherwise
                                        1=telephone, 0 otherwise
                                        1=water, 0 otherwise
                                                                                243


                                      1=cable, 0 otherwise
                                      1=other (specify), 0 otherwise

          3. Household experience     1=loss of breadwinner, 0 otherwise
                                      1=unexpected loss of house, 0 otherwise
                                      1=crop failure, 0 otherwise
                                      1=redundancy, 0 otherwise
                                      1=loss of remittances, 0 otherwise
                                      1=other (specify), 0 otherwise
7.    Positive Affective
            P1: How do you feel about your present conditions?
                               -1=Respondents who say hopeless
                               0=Respondents who say don’t know
                               1=Respondents who say unsure
                               2=Respondents who say hopeful
            P2: Over the past 12 months have you been able to make any
                   significant progress in your life?
                               0=Respondents who say no
                               1=Respondents who say somewhat
                               3=Respondents who say yes

            P3: How do you view the future?
                            -1=Respondents who say hopeless
                            0=Respondents who say don’t know
                            1=Respondents who say unsure
                            2=Respondents who say hopeful

     NB. The positive affective conditions equate to the summation of p1 to p3;
     and the negative affective conditions equal the total of 1, 2 and 3.

     The ‘positive affective condition’ index ranges from 0 to 6, where from 0 to 2
     is low, 3 is moderate and 4 through 6 is high.

     The negative affective condition index means that from 0 to 4 is very low, 5-8
     is low, moderate is 9 through 12 and high is from 13 to 19.

8. Crime                     1=Respondents who say yes, 1-2 times
                             2=Respondents who say yes, 3+ times
                             0=Respondents who say no
        Weights are assigned based on degree of crime
                             1=had something valuable stolen/robbery/burglary
                             2=attacked with or without weapons, fight with or
                             without weapons (not a gun)
                             3=threatened with a gun or attacked with a gun
                             4=sexually assaulted or raped, injured in a fight or
                             murdered
                                                                          244



NB. Crime Index = Σ ki Tj, where K i

    The equation represents the frequency with which an individual
    witnessed or experienced a crime, where i denotes 0, 1 and 2, in which 0
    indicates not witnessing or experiencing a crime, 1 means witnessing 1
    to 2, and 2 symbolizes seeing 3 or more crimes.
    Ti denotes the degree of the different typologies of crime witnessed or
    experienced by an individual (where j=1 …4, in which 1=valuables
    stolen, 2=attacked with or without a weapon, 3= threatened with a gun,
    and 4= sexually assaulted or raped. The summation of the frequency of
    crime by the degree of the incident ranges from 0 to a maximum of 51.

9. Education
    Edu_level1                1=Secondary and vocational, 0=Otherwise
    Edu_level2                1=Tertiary, 0=Otherwise
    The referent group is primary and below education

10. Environment              1=Respondents who say that they have been
                             affected by landslide, floods, or other natural
                             disasters during the last 12 months, 0 otherwise.
11. Home tenure:
   Dwelling1                 1=Rent, 0=Otherwise
   Dwelling2                 1=Owned, 0=Otherwise
 Reference group is squatting, rent free
                                                                               245


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                                                                                    275


Appendix I

Table 2.1.1: Average Growth Rate of Selected Age Group and Total Population
of Jamaica, using Census data: 1844-2050 (in %)

Year                     0-14             15-64           65+3             Total


1844-1861                 *              *                *                0.87
1861-1871                  *              *                *               1.25
1871-1881                   *            *                *                1.25
1881-1891                0.94            1.07             -0.4             0.86
1891-1911                1.39            1.19             0.90             1.25
1911-1921                0.18            0.33             0.85             0.29
1921-1943                1.27            1.77             2.08             1.59
1943-19501               1.39            1.76             0.55             1.57
1950-19602               2.25            1.06             1.74             1.55
1943-1960                2.12            1.00             1.65             1.46
1960-1970                2.07            0.03             3.36             1.08
1982-1991                -0.32           1.04             1.18             0.55
1991-2001                0.33            1.46             1.43             1.08
2001-2006                -1.61           1.33             1.10             0.42
2005-2010                *               *                1.0**            0.4**
2025-2030                *               *                3.3**            0.0**
2045-2050                *               *                2.0**            -0.6**
Source: Computed by Author from Statistical Yearbooks and Demographic Statistics
              * Missing data
              ** Taken from the World Population Ageing 2007:309
1
 The figures for 1943 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
2
 The figures for 1960 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
3
    The rationale that explains the use of 65+ to represent elderly is solely due to the
      statistical data that is available prior to 1991. Before 1991, the Statistical
      Institute of Jamaica’s operational definition for the elderly was 65 years and
      older. Hence, their publications between 1844 and 1991 did not produce years
      for 60+. However, post 1992; the organization began providing data for both
      ages. As such, the researcher used 65+ because he wanted to examine figures
      from 1844 to 2006.
                                                                                                                                        276




Appendix II

Table 2.1.2a: Percentage of estimated or projected populations by selected age groups of different Caribbean nations: 1950, 1975,
2007 and 2050
                 1950               1975              2007                2025               2050

Country
              0-14 yrs   60+ yrs   0-14 yrs   60+ yrs    0-14 yrs   60+ yrs   0-14 yrs   60+ yrs   0-14 yrs   60+ yrs
Barbados      33.2       8.5       31.5       13.6       18.4       13.6      15.4       25.3      14.7       35.9

Guyana        41.1       6.7       44.1       5.5        28.7       7.7       19.9       15.0      13.3       35.2

Jamaica       36.0       5.8       45.2       8.5        30.2       10.3      24.4       15.0      18.5       23.6

Suriname      40.0       8.4       47.6       5.8        29.5       9.2       23.3       15.4      16.7       27.6

Trinidad  40.4           6.1       38.0       7.6        20.7       11.4      19.2       20.2      16.6       32.5
& Tobago
Caribbean 38.6           6.9       39.9       8.1        27.1       11.1      23.0       16.4      18.6       24.8

Source: United Nations. 2007: World Population Ageing, 2007, and United Nations. 2005c: World Population Prospects: The 2004 Revision
                                                                                                                                        277




Table 2.1.2b: Percentage of estimated or projected populations by selected age groups of different Caribbean nations: 1950, 1975,
2007 and 2050
            1950               1975              2007               2025              2050

Country       15-59                15-59                 15-59                15-59                15-59
Barbados      58.3                 54.9                  68.0                 59.3                 49.4

Guyana        52.3                 50.4                  63.6                 65.1                 51.5

Jamaica       58.2                 46.3                  59.4                 60.6                 57.9

Suriname      51.6                 46.5                  61.3                 61.4                 55.7

Trinidad  53.5                     54.3                  67.9                 60.6                 50.9
& Tobago
Caribbean 54.5                     52.0                  61.8                 60.6                 56.7

Source: United Nations. 2007: World Population Ageing, 2007, and United Nations. 2005c: World Population Prospects: The 2004 Revision
                                                                                                                  278




Appendix III

Table 3.1.5: Growth Rate (in %) for Selected Regions, and Countries based on certain Time Periods: 1950 to 2050

Regions and/or
Countries                    1950-1955     1975-1980     2005-2010     2025-2030      2045-2050


World                        1.8           1.7           1.1           0.7            0.4
More developed regions       1.2           0.7           0.2           0.0            -0.1
Less developed regions       2.1           2.1           1.3           0.9            0.5
Least developed countries    2.0           2.5           2.3           1.9            1.3

Africa                       2.2           2.8           2.1           1.7            1.2
Asia                         2.0           1.9           1.1           0.6            0.2
Europe                       1.0           0.5           -0.1          -0.3           -0.4
Latin America &
Caribbean                    2.7           2.3           1.3           0.7            0.2

Caribbean                    1.8           1.5           0.8           0.4            -0.1
Central America              2.7           2.7           1.4           0.8            0.2
South America                2.8           2.3           1.3           0.7            0.3
Northern America             1.7           1.0           0.9           0.6            0.4
Oceania                      2.1           1.5           1.2           0.8            0.4

Source: World Population Ageing, 2007
                                                                       279


Appendix IV


Table 4.1.2: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004

                            Average Expected Years of Life at Birth
Period:                     Male                       Female

1880-1882                   37.02                      39.80

1890-1892                   36.74                      38.30

1910-1912                   39.04                      41.41

1920-1922                   35.89                      38.20

1945-1947                   51.25                      54.58

1950-1952                   55.73                      58.89

1959-1961                   62.65                      66.63

1969-1970                   66.70                      70.20

1979-1981                   69.03                      72.37

1989-1991                   69.97                      72.64

1999-2001                   70.94                      75.58

2002-2004                   71.26                      77.07
Sources: Demographic Statistics (1972-2006)
                                                                                                                                                                      280




Appendix V


Table 4.1.2: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004

                                                                                                 Std. Error
                       Single Elderly           N              Mean          Std. Deviation      Mean
 General_Wellbeing_2   1=Male                   292            2.7688        1.83994             .10767
                       2=Female                 314            3.3137        2.20539             .12446

                                                                                 Independent Samples Test

                                                    Levene's Test for Equality
                                                    of Variances                 t-test for Equality of Means
                                                                                                                                  Mean         Std.    Error 95% Confidence Interval
                                                    F             Sig.           t              df              Sig. (2-tailed)   Difference   Difference    of the Difference

                                                                                                                                                            Lower           Upper
 General_Wellbeing_2    Equal           variances
                        assumed                     12.410        .000           -3.289         604             .001              -.54486      .16565       -.87017         -.21955
                        Equal variances       not
                        assumed                                                  -3.311         597.101         .001              -.54486      .16457       -.86807         -.22165
                                                                                       281




“Growing Old in Jamaica: Population Ageing and Modelling Senior Citizens' Wellbeing
is a well-researched discussion by Paul Bourne about the social, economic, and political
ramifications of increased longevity and an elderly population that outnumbers the
population of youth.

Bourne very thoroughly addresses the concept of wellbeing, being sure the reader
understands how he is defining the wellbeing of the Jamaican elderly as opposed to other
definitions of wellbeing that may be presented in popular statistics. This concept
encompasses health care, economic comfort, relationships, education, residency, and
much more.

Bourne’s approach is highly analytical, with detailed statistics, sources, and mathematics.
This informative piece may appeal to readers interested in a meticulous exposition of the
wellbeing of the ageing Jamaican population”

   -   Katherine Smith, Editorial Coordinator, Dorrance Publishing Co. Inc
                                                                  September 28, 2008
                                                                              282


                              About the Author




Paul Andrew Bourne is currently a health research scientist in the Department of
Community Health and Psychiatry, Faculty of Medical Sciences, the University of
the West Indies, Mona Campus, Kingston 7, Jamaica. He also lectures in Research
Methods, and Elements of Reasoning, Logic and Critical Thinking at the Jamaica
Constabulary Staff College. Bourne teaches Mathematics; Marketing; Marketing
Management, and Science, Medicine and Technology at the University of the West
Indies Open Campus sites; and lectures in Mathematics and Social Research at the
Montague Teacher’s College.


He was a political sociologist in the Department of Government, Mona Campus.
Bourne has recently co-authored two monographs - (1) Probing Jamaica’s Political
Culture: Main Trends in the July-August 2006 Leadership and Governance Survey,
Volume 1; and (2) Landscape Assessment of Corruption in Jamaica.


Bourne was employed as a consulting biostatistician to the Caribbean Food and
Nutrition Institute, an affiliate of PAHO/WHO in Jamaica.
Paul Andrew Bourne’s areas of interest include Statistics, Demography, Political
Sociology, Wellbeing, The Elderly, Political Polling and Research Methods.


Department of Community Health and Psychiatry
Faculty of Medical Sciences
The University of the West Indies, Mona Campus, Kingston, Jamaica




                                                            ISBN 978 976 41 0232 8
                                                                                   1


                                 Chapter One

                                 Introduction

       Ageing is not a recent phenomenon. It goes back centuries, from time

immemorial. The total human population, within any geographical area, is made

up of children, youth, people of working age and the elderly. This latter grouping

is a phenomenon not only in developed nations but also in many developing

societies. For many Caribbean countries, this is also their reality. The factors that

explain the “greying” of the world’s population are fertility decline, reduced

mortality at ‘older ages’ and the external migration of the young, as well as the

return of retirees. Those conditions, coupled with increases in life expectancies

due to public health improvement and better water qualities, have significant

consequences for population size and structure. Where the elderly population

outgrows the younger, the population structure at younger ages is constricted and

at older ages it expands (Rowland 2003, 98). This is an aspect of demographic

transition which will change significantly in the 21st century.

       Demographic ageing at the micro and macro levels implies a demand for

certain services such as geriatric care. In addition to preventative care, there will

be a need for particular equipment and products (i.e. wheelchairs, walkers). Then

there are future preparations for pension and labour force changes, along with the

social and economic costs that are associated with ageing, as well as the policy

base research to better plan for the reality of these age groups. The World Health

Organization (WHO), in explaining the ‘problems’ that are likely to occur

because of population ageing, argues that the 21st century will not be easy for
                                                                                      2


policy makers, who are pivotal in the preparation process to postpone ailments

and disability and in the challenge of providing a particular standard of health for

the populace within the context of an ageing population (WHO 1998, 5). What

constitutes population ageing?        Some demographers have put forward the

benchmark of 8-10% as an indicator of population ageing (Gavrilov and

Heuveline 2003). Within the construct of Gavrilov and Heuveline’s perspective,

the Jamaican population began experiencing this significant population ageing as

of 1975 (using 60+ years for ageing) or of 2001 (if ageing is 65+ years) (See

Tables 1.1.1 and 1.12), and the world since the 1950s (Table 1.1.3). The numbers

comprising the ageing population will double come 2050 irrespective of the

chronological definition of ageing (see Table 1.1.2 and Table 1.1.3), but what

about the      quality of life of the elderly? This book is concerned not about

population ageing in the world, the Caribbean or for that matter Jamaica, but we

will examine the wellbeing of aged Jamaicans within the reality of population

ageing.

Table 1.1.1: Selected Age Groups of Jamaican Population, using Census data:
1881-2001 (in %)

Age groups       1881   1891   1911    1921   1943   1960    1970   1991       2001



0 – 14 yrs.      38.8   38.7   39.8    39.4   36.6   41.1    45.9     35.2     32.2


15 – 64 yrs.     56.5   57.5   56.7    56.9   59.2   54.5 48.5       57.5      57.6

65+ yrs.         4.7    3.8     3.5    3.7    4.2    4.4     5.6     7.3       10.2

Source: Computed by Author from Statistical Yearbook of Jamaica: 1973-1989 &
Demographic Statistics: 1973-2006.
                                                                                          3


Table 1.1.2: Selected Age Groups of Jamaican Population: 1950, 1975, 2007,
2025 and 2050 (in %)

Age groups      1950             1975             2007            2025             2050

0 – 14 yrs.     36.0             45.2             28.6*           24.4             18.5

15 – 59 yrs.    58.2             46.3             60.7*           60.6             57.9

60+ yrs.        5.8              8.5              10.7*           15.0             23.6

65+ yrs.        3.9              5.8              8.0*            10.3             17.7

80+ yrs.        0.2              0.8              2.0**           2.3              5.6

Source: United Nations, 2007, pp308-309
* Using figures taken from Demographic Statistics 2006 for the same year
** Estimate for 2005 from United Nations, 2007


Table 1.1.3: World Percentage of Population at Older Ages, 1950—2050
Details      Age       1950        1975        2000        2025    2050

Total          60+         8.2          8.6           10.0         15.0         21.1
               65+         5.2          5.7           6.9          10.4         15.6
               80+         0.5          0.8           1.1          1.9          4.1
Female         60+         9.0          9.7           11.1         16.3         22.7
               65+         5.9          6.6           7.9          11.6         17.3
               80+         0.7          1.0           1.5          2.5          5.0
Male           60+         7.3          7.5           8.9          13.6         19.4
               65+         4.5          4.8           5.9          9.2          14.0
               80+         0.4          0.6           0.8          1.4          3.1
Source: Population Division, DESA, United Nations, in United Nations. 2004. World Population
Ageing 1950-2050. New York: United Nations, pp. 46




         Caribbean demographers, like other demographers, have been using life

expectancy for years as the measure for wellbeing.             Over the years, we have

accepted the perspective of those scholars who used life expectancy as an

indicator of health status and by extension quality of life, but this approach

accepted that a quantitative assessment of years allows us to understand the
                                                                                  4


quality of those years lived by someone. Life expectancy (or population ageing)

speaks to number of years, but this focus fails to address the other tenets of this

subject. We will present an example that illustrates the disparity between long life

and quality of years lived. Ali, Christian and Chung, who are medical doctors,

cite the case of a 74 year-old man who had epilepsy, and presented their findings

in the West Indian Medical Journal.

       They write that:

       Elderly patients are frequently afflicted with paroxysmal impairments of
       consciousness usually because they often have chronic medical disorders
       such as diabetes mellitus and hypertension and can also be on many
       medications. The differential diagnosis of transient impairment of
       sensorium in the elderly is wide and includes metabolic encephalopathies
       e.g. medication side effects, syncope, including cardiogenic syncope,
       transient ischaemic attacks and strokes, the syndrome of transient global
       amnesia, psychogenic fugue states and epileptic seizures. Many elderly
       patients may have more than one cause for this symptom. (Ali, Christian
       and Chung 2007, 376)


       The case presented by the medical doctors emphasizes the point we have

been arguing, that long life does not imply quality of life years. Although the case

study cited here does not constitute a general perspective on all the elderly, other

quantitative studies have concurred with Ali, Christian and Chung’s general

findings. Scientists agree that biological ageing means degeneration of the human

body (also see: Hooyman and Kiyak 2005; The Merck Manual of Aging 2004;

Eldemire-Shearer 2003; Kalache 2003; Ling and Bathon 1998), and such a reality

means that longer life will not mean quality years. Thus population ageing, like

life expectancy, does mean more than increased number of people for the human

population. Population ageing is going to be a socioeconomic, psychological and
                                                                                5


political challenge today, tomorrow and in the future for developing countries and

nations like Jamaica. However, this paper is concerned with the wellbeing of the

aged from the perspective of the biopsychosocial model and its determinants, and

the state of the elderly in Jamaica.    The biospsychosocial model posits that

biological, sociological, and psychological conditions play a significant role in

determining the wellbeing of an individual. How was this study conducted? And

what is the prescribed model that is being put forward here that will drive the

study?

         Research Design

         The research design for this study is an explanatory one. This study

utilizes cross-sectional data from a reputable data collections agency in order to

identify and explain the determinants of wellbeing among the Jamaican elderly.

The use of multivariate analysis to generate a model for the phenomenon clearly

indicates a mathematical demographic approach.

         Many scholars, (for example Crotty 2005; Neuman 2006; Boxill,

Chambers and Wint 1997; Babbie 2000; Heiman 1995; Shaughnessy and

Zechmeister 1990; Bryman and Cramer 2005) have written on social research

methods, but the researcher has found Michael Crotty’s monograph aptly fitting

for this paper, as it summarized the research process in a diagrammatic and

systematic manner while providing elaborate details of each component. In the

text titled ‘The foundations of social research: Meaning and perspective in the

research process’, Crotty (2005) aggregated the research process in four schema

(i.e. four questions which must be answered in examining social phenomena),
                                                                                  6


namely (1) methods, (2) methodology, (3) theoretical perspective, and (4)

epistemology.

       The four schema of the research process according to Crotty (2005, 2-4)

are encapsulated into a flow chart (See Figure 4.1). Michael Crotty, a lecturer in

education and research study at the Flinders University of South Australia,

believed that the purpose of research guides the choice of methodology and

method. In this way, the chosen methodology and method clearly depict the set

of assumptions the researcher has about reality (Crotty 2005, 2) (i.e. what [he/she]

brings to the work).

       The schema of the research process is not simply a unidirectional model

(Crotty 2005, 2-4). Crotty (2005) pointed out that this process may begin with

epistemology, theoretical perspective, methodology and method, but noted that it

may flow from method, methodology, theoretical perspective and lastly

epistemology. Embedded in this schema is not the preciseness of the direction but

that those areas are a must within a research process.

       Survey Design

       This book for its research design used secondary data taken from a

reputable statistical agency      to   examine socio-political, ecological and

psychological factors and how they influence the wellbeing of elderly Jamaicans.

The institution began collecting data to aid planning in the late 1980s when the

institution collaborated with another, and adopted, with some modifications, the

World Bank's Living Standards Measurement Study (LSMS) household surveys.

The PLC has its focus of policy implications of government programmes, and so
                                                                                   7


each year a different module is included with the aim of evaluating a particular

programme. The PLC is a self-administered instrument (questionnaire) where

respondents are asked to recall details of information on particular activities. The

questionnaire covers demographic variables, health, immunization of children 0 to

59 months, education, daily expenses, non-food consumption expenditure,

housing conditions, inventory of durable goods and social assistance. Interviewers

are trained to collect the data, which is prepared by the household members. The

survey is usually conducted between April and July annually.

       The current study extracted data on public-private health care utilization,

mean cost for visits to public-private health care facilities in the last 4 weeks of

the survey period, and health insurance coverage from the PLC. Information was

extracted on the annual inflation rate from 1988 to 2007. Scatter diagrams

(graphical plots) were on variations of public-private health care utilization by

inflation, mean cost of care for visits, as well as other graphic presentations used

to assess whether any statistical association exists between the dependent variable

and the independent variable; and some of the graphs were only interpreted. In the

current study, sub-samples of 3,009 elderly Jamaicans (60 years and older) were

extracted from the PLC’s survey that had 25,018 respondents. The rationale for

the use of PLC 2002 was based on two critical issues: 1) it was the largest dataset

ever collected by the two Institutions, and 2) it was the first time in the annals of

the PLC that crime and victimization, demographic characteristics, household

consumption, education, health, social welfare and related programmes, and

housing were collected together. Hence, within the context of a large dataset and
                                                                                     8


the number of conditions that are related to the cohort in investigation, I believe

that it was fitting to use this period as against other occasions with less than 3,000

respondents and not having data on crime and victimization, which is a major

problem faced by countless Jamaicans.


General Hypothesis: The mathematical model which drives this paper.



W iki =ƒ (P mc , ED, A i , En , G, MS, AR, P, N, O, H, T, V)

        W i is the wellbeing of the Jamaican elderly, i, is a function of the cost of

medical (health) care, (P mc ), the educational level of the elderly individual, (A i ,

where i is an elderly individual ), the environment (En), gender of the respondents

(G), marital status (MS), area of residents (AR), positive affective conditions (P),

negative affective conditions (N), average occupancy per room (O), home tenure

(H), property ownership (T), and crime and victimization (V).

        The sample survey research methodology requires objectification in the

investigation of phenomena. The primary purpose in using this methodology is

objectivism, as some scientists argue that things exist out there independently of

our consciousness and experiences. As such, the positivists’ paradigm is the most

suitable and preferred theoretical framework to execute the specified

methodology. Positivism is fundamentally based on (1) science (i.e. free from

value judgment – science is guided by observation and not opinion or beliefs), and

(2) measurement - that if a phenomenon cannot be measured, it should not be

studied – which explains why positivists embody theories in hypotheses that are

testable.
                                                                                9


       The positivists’ philosophy is carried out by hypothesis testing through

conducting experiments (i.e. observation) and the manipulation of variables. This

is referred to as the scientific method – that is, logical reasoning, with an

emphasis on experience (i.e. observation) and measurement.

       A renowned methodologist, Neuman (2003), penned the following

perspective that aptly summarized positivism, when he said that:

       Positivism sees social sciences as an organized method for combining
       deductive logic with precise empirical observation … in order to discover
       and confirm a set of probabilistic causal laws that can be used to predict
       general patterns in human activity (Neuman 2000, 66).

       Embedded in positivist research are the techniques used in obtrusive and

controlled measurement. This guides the data-gathering process (also see Waller

2006) – by way of survey, experiments, case-control studies, statistical records,

structured observation, content analysis, and other quantitative techniques. The

very nature of this research on wellbeing, was not the collection of data through

observation, but that a primary institution gathered pertinent data from Jamaicans

based on the people’s belief (i.e. self-reported), which makes for value

judgements (see for example, Trochim 2006). Hence, in its truism form, the

researcher did not use positivism. Instead, a hybrid methodology was used.

       Based on the fact that the researcher used a survey (Jamaica Survey of

Living Conditions) which collected data from people within Jamaica, and that the

data given are individuals’ perspective on how they conceptualize what they see,

the researcher used mixed positivism, which captures what the post-positivist (see

Trochim    2006)   called   constructivism    while   applying     causation   and

objectification. Constructivism speaks to the position of each person, and from an
                                                                                   10


objective reality (i.e. through precise measurement – that is using the scientific

method).

       From the post-positivism stance, the researcher in an attempt to reach “the

goal of getting it right about reality” (Trochim 2006) put forward the idea that this

can only be attained through triangulation, and so did not use this in its entirety.

       Nevertheless, based on the type of data gathered by the Statistical Institute

of Jamaica (i.e. self-reported information from each respondent on how he/she

conceptualizes his/her surrounding); the researcher will use this self-reported data

to guide the analysis of a wellbeing function. The function will apply regression

analysis to construct a model for wellbeing for the Jamaican elderly, using

hypothesis testing, precise measurement of concepts and some econometric

modelling techniques (see Explanatory Model, p.124; also see Methodology and

Method (Chapter 3) – i.e. hypotheses).

       The use of multivariate analysis to generate a model for the phenomenon

clearly dictates that a mathematical–demographic approach had to be taken;

hence, positivism was the preferred and appropriate choice of methodology.

       Furthermore, the study will test a number of hypotheses by first carefully

analyzing the data through cross tabulation – to establish relationship, and then,

secondly, by removing all confounding variables. After this, the researcher will

use model building in order to finalize a causal model. Hence, the positivist

paradigm is the appropriate choice.           The positivists’ paradigm assumes

objectivity, impersonality, causal laws, and           rationality.   This   construct

encapsulates scientific method, precise measurement, and deductive and
                                                                                         11


analytical division of social realities. From this standpoint, the objective of the

researcher is to provide internal validity for the study, which will rely totally on

scientific methods, precise measurement, value free sociology and impersonality.

        The study will design its approach in a similar way to that of natural

science by using logical empiricism. This will be done by precise measurement

through statistics (chi-square and modelling – logistic regression). By using

hypotheses testing, value free sociology, logical empiricism, cause-and-effect

relationships, precise measurement through the use of statistics and survey and

deductive logic with precise observation, this study could not have used the

interpretivist paradigm, as the latter seeks to understand how people within their

social setting construct meaning in their natural setting, which is subjective rather

than the position taken in this research – an objective stance. Conversely, this

study does not intend to transform peoples’ social reality by way of

empowerment, but is primarily concerned with unearthing a truth that is out there,

and as such, that was the reason for the non-selection of the Critical Social

Scientist paradigm.

Limitation to the Study Model

This model W=ƒ (P mc , ED , Ai, E n, G, M, A R , P, N, O, H t , T,   V, S ,   H S) + ei is a

linear function

W= 1.922+ 0.197P mc + 1.091A R 2 + 1.698 A R 3 – 0.633 En + 0.341 M1 + 0.560
M2 + 0.240 E D 2 + 1.700 ED 3 + 0.210S – 0.691O + 0.606 T + 0.105P -0052N-
0.022 A i + ei

Therefore we are unable to distinguish between the wellbeing of two individuals

who have the same typology, and the wellbeing of an individual that may change
                                                                                  12


over short time intervals that do not affect the age parameter.         As such in

attempting to add further tenets to this model in order to be able to fashion a close

approximation of reality, the following modifications are being recommended.

         Each individual’s wellbeing will be different even if that person’s

valuation for quality of life is the same as someone else who shares similar

characteristics. Hence, a variable P representing the individual should be

introduced to this model in a parameter α (p). Secondly, the wellbeing of the

elderly is different throughout the course of the year, and so time is an important

factor. Thus, we are proposing the inclusion of a time-dependent parameter in the

model.     Therefore, the general proposition for further studies is that the linear

function should incorporate α (p, t) a parameter depending on the individual

and time.
                                                                                                    13


EXPLA
 Home Tenure
   Property
  ownership


Sex




Environment




Marital Status




Area of residence



Cost of Health                                                                                Wellbeing
care




Level of
Education



Average
occupancy per
household


Psychological:
Positive
Affective, and
Negative
Affective


Elderly




          Figure 1.1.1: Bourne’s Linear Conceptual Model of Wellbeing for Elderly Jamaicans
                                                                                 14


                                    Chapter Two

                                    Ageing Transition




       The issue of ageing and its conceptualization date back to earlier centuries.

The scientific study of this phenomenon in addition to that of older adulthood is a

more recent debate – nineteenth century – and it began as early as in 1835. This

fascination that people have for ageing, older adulthood and the ageing process is

a longstanding debate, and it emerged because of man’s eagerness to reduce the

ageing process. History has recounted that a Spanish explorer – during 1460 to

1521- in his quest to reclaim youth by rescinding the ageing process, discovered

Florida as a result. This explains the pilgrimage and people’s fascination with

bath fountains, health spas, dietary requirements, gyms, physical exercise and

their willingness to extend themselves in healthy lifestyle practices. Although we

have spent millions of dollars on DALY (i.e. Disability Adjusted Life Years)

lifestyle issues, we still cannot stop the ageing process. On a point of emphasis,

the developing world’s populations are even ageing at a faster rate than in the

developed world (Bourne and Eldemire-Shearer 2008b; Bourne 2007; United

Nations 2004, 2005; Eldemire-Shearer 2003; Kalache 2003). Thus, what is

ageing? And, what is the ageing process?

       There are many indicators of ageing (i.e. median age, the proportion of the

population older than 60 years, mean age of the population, and the dependency

ratio), but how do we know when it begins? In this chapter, the author will

examine different conceptualizations of ageing, in order to evaluate the process of
                                                                               15


ageing and when ageing commences.

        Chronological ageing

        However the author, using the available data for Jamaica from the

Statistical Institute of Jamaica, was able to compute the average growth rate for

children (i.e. ages less than 15 years), work age population (ages 15 through 64

years) and the elderly (ages 65+) from as far back as 1844. The author has

concluded that while he was unable to definitely say that population ageing

began in the mid 1960s, the average growth rates show that the ageing of the

nation’s population occurred between 1960 and 1970. Between 1950 and 1960,

the average growth rate was 1.74%, and it rose to 3.36% between 1960 and 1970,

with no other period before 1950 and post 1970 showing an average growth rate

close to 3.4%. (See Appendix I - Tables 2.1.1). The average growth rate for 1991

to 2001 stood at 1.43%. Professor Denise Eldemire-Shearer, a Jamaican public

health and ageing expert, on the other hand, did not substantiate her claim as to

why she argued that population ageing in Jamaica began in the ‘mid 1960s’. The

author, using a percentage of the elderly population (i.e. ages 60+ years) cannot

substantiate Eldemire-Shearer’s claim, but what can be said with authority is that

it occurred between 1960 and 1970 (also see Appendix II – Table 2.2.2a and

Table 2.2.2b), and for the world (see Table 1.1.3), Barbados and Suriname (Table

2.2.2a) it started in the 1950s.

        With regard to global population, 10.4% of individuals are 60 years or

older (United Nations 2005c). Jamaica’s elderly population in 2005 rose

marginally by 0.3% to 10.7% in 2006 (PIOJ 2007). The United Nations data show
                                                                                16


that 8% of people in developing nations are 60 years or over (United Nations

2005c), which is approximately 2% less than the number of aged people in

Jamaica. According to the Demographic Statistics (2006), 10.9% of Jamaicans

females are 60 years and older compared to 10.3% of males.

       Despite the indecisiveness in reaching consensus on a definition of ageing

from the United Nations’ perspective on the elderly, ‘old age’ begins at 60 years

while other scholars conceptualize ageing to commence at age 65 years or older

(See for example Lauderdale 2001; Elo 2001; Manton and Land 2000; Preston et

al. 1996; Smith and Kington 1997a; Rosenberg, M.W., and E.G. Moore. 1997;

Smith and Waitzman 1994; Rudkin 1993). The WHO says that we can either use

the chronological age of 60 or 65 years or over to indicate the beginning of ageing

(WHO 2002, 125). So why is there no standardized definition for the elderly or

where ageing begins? Thane (2000) noted that ‘old age’ for all people was

defined as 60 years in medieval times. She justified this by putting forward an

argument for the established age. In medieval England, men and women ceased at

60 years to be liable for compulsory service under labour laws or to participate in

military duties. In Ancient Rome, on the other hand, ‘old age’ began from early

40 to 70 years, with 60 years being ‘some sort of annus climactorius’. Some

Demographers see seniors - the elderly or the aged (old people) - as beginning at

the chronological age of 65 years and older, and not an individual who is 60 years

of age. Up to 1992, the Statistical Institute of Jamaica defined old-age as those

people 65 years and older (Demographic Statistics 1992).         At that time the

Professor of Demography at the University of the West Indies at Mona was
                                                                                 17


primarily responsible for much of the output from that Institution, and for the

training of staff. This may explain why the Statistical Institute of Jamaica used 65

years in its conceptualization of old-age. Furthermore, Western societies use 65

years and older to represent the elderly (seniors) as this is the period when people

become fully eligible for Social Security benefits.

       One Caribbean scholar emphasized that there is no absoluteness in the

operational definition of the “elderly” (Eldemire 1995, 1). She commented that

from the World Assembly of Ageing (which was held in Vienna in 1982), the

term “elderly” uses the chronological age of 60 years and older ‘as the beginning

of the ageing process’. Jamaica having signed the Vienna Declaration of Ageing,

which defines ageing to begin at 60 years, Eldemire questioned academics and

other scholars over their rationale in using 65 years. Many demographers use 65

years and older to represent the commencement of the ageing process, but that is

due primarily to the nature of the study. Demographers use 65 years and beyond

when they examine the elderly and this is used more in the context of retirement

matters. However, these scholars frequently use 60 years and older in situations

when health is being examined, which is in keeping with the medical perspective

that the chronological age of 60 years is the beginning of the ageing process.

       Within the study of demography, elderly begins at the chronological age

of 65 years – using the unit of analysis of time, based on the number of years and

months that have elapsed since birth (See for example Erber 2005; Iwashyna et al.

1998; Preston, Elo, Rosenwaike, and Hill 1996; Smith and Waitzman 1994).

However, based on the monographs from other scholars (such as - Marcoux 2001;
                                                                                 18


Eldemire 1999; Ministry of Labour, Social Security and Sports 1997; Eldemire

1997; PAHO and WHO 1997; Eldemire 1995a; Eldemire 1994; Barrett 1987), the

issue of the aged begins at 60 years. Hence, the operational definition of the

‘elderly’ continues unabated in non-standardization. Those who use 60 years

adopt this value because of the World Assembly on Ageing (in Vienna, Austria:

July-August 1982), which puts forward the idea that ageing begins

chronologically at 60 years.

       In a discussion with Professor Eldemire (on 7th April, 2008), she opined

that among the reasons for the non-standardization of the term ‘elderly’ was the

disparity in the actual commencement of the ageing process. Eldemire pointed

out that, although the World Health Organization (WHO) recommended that we

use 60 years to indicate the beginning of ‘old age’, some people start ageing at the

chronological age of 60 years, and there are others who begin this stage at a later

age – 65 years. Eldemire’s position is in keeping with the arguments put forward

by the WHO on the rationale for the non-standardization of the operational

definition of when “older age” begins.

       The Canadian statistical agency used age 65 years as the dividing line

between “young” and “old” (Moore et al. 1997, 2; also see Smith and Waitzman

1994; Preston, Elo, Rosenwaike and Hill 1996).           The issue of using the

chronological age of 65 years to measure older adulthood, according to one

academic, comes from the minimum age at which the Social Security System

begins disbursing payment for pensions to people living in the United States

(Erber 2005, 12). It is argued that in 1935, the U.S. government modelled this on
                                                                                 19


the German retirement system. This explains the use of 65 years of age by many

scholars, practitioners and non-professionals ever since.      This approach sub-

divides ageing into three categories. These are (i) young-old (ages 65 through 74

years), (ii) old-old (ages 75-84 years) and oldest-old (ages 85 years and beyond).

However, is there a difference between biological and chronological ageing?

       The WHO (2002) offered us a rationale for ‘old age’ in one of its

publications entitled ‘World Report on Violence and Health’, that it is based on

‘physical decline’ (or functional limitation) of people in regard to them “no longer

[being able to] carry out their family or work roles. Embedded in the rationale for

the operational definition offered by the WHO is the recognition that ‘old age’ is

both a chronological as well as a biological phenomenon. Hence, what is the

discussion on biological ageing?

       Biological ageing

       As cells age, they function less well. Eventually, they must die, as a
       normal part of the body’s functioning (The Merck Manual of Health and
       Aging, 2004, 5)


       As the years pass, most people experience changes in the way their body
       functions. Some changes are obvious. For example, before age 50, most
       people begin to have trouble seeing objects that are up close. Other
       changes are hardly noticeable. For example, few people are aware that the
       kidneys may become less able to filter waste products out of the blood,
       because the kidneys usually continue to filter the blood well enough to
       avoid problems. Most people learn that their kidneys have aged only if a
       disorder develops (The Merck Manual of Health and Aging 2004, 5)



       Organisms age naturally, which explains biological ageing, including

kidney issues, vision, hearing, reduced mobility and even natural death owing to
                                                                                  20


ageing organisms. Here ageing implies growth, development and maturity (Ross

and Mirowsky 2008). This approach emphasizes the longevity of the cells, in

relation to the number of years the organism can live. Thus, in this construction,

the human body (an organism) is valued based on physical appearance and/or the

state of the cells. Embedded in this apparatus is the genetic composition of the

survivor.   This occurs when the body’s longevity is explained by genetic

components (See for example Yashin and Iachine 1997, 32). Gompertz’s law in

Gavriolov and Gavrilova (2001) shows that there is a fundamental quantitative

theory of ageing and mortality in certain species (the examples here are as follows

– humans, human lice, rats, mice, fruit flies, and flour beetles (also see, Gavriolov

and Gavrilova 1991).     Gompertz’s law went further to establish that human

mortality increases twofold with every 8 years of an adult life, which means that

ageing increases in geometric progression. This phenomenon means that human

mortality increases with the age of the human adult, but that this becomes less

progressive in advanced ageing. Thus, biological ageing is a process where the

human cells degenerate with years (i.e. the cells die with increasing age), which is

explored in evolutionary biology (see Medawar 1946; Carnes and Olshansky

1993; Carnes et al. 1999; Charlesworth 1994). But studies have shown that using

evolutionary theory for “late-life mortality plateaus” fails, because of the arguably

unrealistic set of assumptions that the theory uses to establish itself (Mueller and

Rose 1996; Charlesworth and Partridge 1997; Pletcher and Curtsinger 1998;

Wachter 1999).

       Reliability theory, on the other hand, is a better fitted explanation for the
                                                                                     21


ageing of humans than that argued by Gompertz’s law, as the ‘failing law’ speaks

to the deterioration of human organisms with age (Gavrilov and Gavrilova 2001)

as well as the non-ageing term. The latter, based on Gavrilov and Gavrilova

(2001), can occur because of accidents and acute infection, which are called

“extrinsic causes of death.” While Gompertz’s law speaks to mortality in ageing

organisms due to age-related degenerative illnesses such as heart diseases and

cancers, a part of the reliability function is Gompertz’s function, as well as the

non-ageing component.

        When the biological approach is used to measure ageing, this may be

problematic, as two different individuals with the same organs and physical

appearance may not be able to perform at the same rates, which speaks to the

difficulty in using this construct in measuring ageing.

        Nevertheless, this construct is able to compare and contrast organisms in

relation to the number of years that a cell may be likely to exist. Erber (2005)

argues that this is undoubtedly subjective, as we are unable with any definiteness

to predict the life span of a living cell (Erber 2005, 9). Interestingly, the biological

approach highlights that the ageing process comes with changes in physical

functioning.   The oldest-old categorization is said to be the least physically

functioning compared to the other classifications in chronological ageing. The

young-old, on the other hand, are more likely to be the most functioning, as the

organism is just beginning the transition into the aged arena (see for example

Erber 2005; Brannon and Fiest 2004).

        It is important to avoid such pitfalls in constructions as may arise with the
                                                                                 22


use of the biological approach, ergo, for all intents and purposes, given the nature

of policy implications in effective planning, the researcher is putting forward the

perspective that seniority in age commences at age 65 years – using the

chronological ageing approach.

        In the ageing transition, both chronological and biological ageing have a

similar tenet. It should be noted that as an individual shifts from young-old to

oldest-old, the body deteriorates and what was of low severity in the earlier part

of the ageing process becomes of critical mass in the latter stage. Hence, at the

introductory stage of the ageing transition, the individual may feel the same as

when he/she was in the working-age population, but the reality is that the body is

in a declining mode. Because humans are continuously operating with negatives

and positives, as he/she becomes older – using the ageing transition (i.e. 65 years

and older) – the losses (or negatives) outweigh the positives. This simply means

that the functionality limitation of the body falls, and so opens the person to a

higher probability of becoming susceptible to morbidity and mortality. Secondly,

the environment, which may not have been problematic in the past, now becomes

a health hazard. One University of Chicago scholars summarizes this quite well

in Table 2.1.3:

       This study seeks to evaluate the wellbeing of the aged and not those who

are eligible for Social Security Benefits. Hence, for this study ‘old age’ or the

elderly (seniors) will begin from the chronological age of 60 years and older.
                                                                                                23


Table 2.1.3: Characteristics of the Three Categories of Elderly, and the Ageing
Transition
Characteristic


                                           The Ageing Transition

                                   Young-old           Aged 1      Oldest-Old

Health problems                   Low              Moderate      High

Physical disability               Low              Moderate      High

Demand for medical care           Low              Moderate      High

Demand for public service Low                      Moderate      High

Demands on children               Low              Moderate      High

Dependency on others              Low              Moderate      High

Social isolation                  Low              Moderate      High

Source: This is taken from Essays in Human Ecology 4. Bogue 1999, 3.

         Eldemire’s classifications differ somewhat from the perspective put

forward by Donald Bogue (1993). Old age (i.e. elderly) according to Bogue

begins at 65 years, whereas Eldemire believes that this should be 60 years and

older, which is in keeping with the conceptual definition of elderly based on the

United Nations’ charter. This discourse of the operational definition of ageing and

the values for the categories of age cohorts also differ marginally between the two

scholars. Like Bogue, Denise Eldemire has three age groups into which she

classifies the elderly. These are (1) young-old (ages 60 to 74 years); old-old (ages

75 to 84 years) and (3) oldest-old (i.e. 85 + years). Both researchers used the

1
  Donald Bogue (1999) used aged (age 75 – 84 years) to refer to what this paper calls old-old; 65
to 74 years to denote young-old and from 85 years and older to indicate oldest-old.
                                                                                  24


three groups because they represent the ‘stages of ageing’. The three ‘stages of

ageing’ are widely accepted in gerontology as indicators of the biological

transition which the elderly pass through, accompanied by progressive

physiological deterioration of the human body.

        Elderly patients are frequently afflicted with paroxysmal impairments of
       consciousness usually because they often have chronic medical disorders
       such as diabetes mellitus and hypertension and can also be on many
       medications (Ali, Christian and Chung, 2007, 376)


       Despite the claims made by a few medical doctors (Ali, Christian and

Chung), another medical practitioner wrote that “The majority of Jamaican older

persons are physically and mentally well and living in family units” (Eldemire

1995a, i). Professor Eldemire has extensively researched issues relating to the

Jamaican elderly for some time now, and as such she formulated a perspective of

this group that encompasses more than biology in examining elderly people’s

quality of life.   Therefore this speaks to the need for us to understand the

difference between biomedical and biopsychosocial models of wellbeing. The

implied issue within Eldemire’s monograph is the inadequacy of measuring

quality of life using only physiological status. Clearly, with elderly Jamaicans

physically and mentally well, it is safe to argue that their wellbeing is high, given

the old model of measuring quality of life (i.e. biomedical – using physical illness

or lack thereof). However, this measure is simplistic. Can we say in Jamaica that

the high crime rate, the death of loved ones, widowhood, unemployment,

retirement (separation from employment), insufficient financial resources and cost

of living, loneliness, lifestyle changes, dependence on family members or friends,
                                                                                 25


childless old people, and other psychosocial conditions will not affect the health

and wellbeing of the aged? This is answered in later Chapters. Before we begin

the discussion on wellbeing, or wellbeing of the aged, we need to address the

issue of population ageing.

       Functional Ageing

       Functional ageing is having to deal with one’s ability and capability to

carry out a physiological functioning – competence in executing a physical task.

One of the differences with this phenomenon is that each individual’s competence

is not determined at the same chronological ageing – and equally the biological

process of each individual is not necessarily the same, as people’s genes

predominantly explain what is likely to affect them and at what age. Hence, an

individual may not be to perform a particular task at a certain chronological age,

but his/her colleague at the same age may be able to execute the same function.

Within the same breath, the functional limitation of the same individual can

change based on a particular event, time, situation or mass.     For instance, a 90

year old man may be able to drive himself to the supermarket and purchase his

groceries - but he is not able to open his zipper to urinate.

       Using physical functioning for definition ageing (or ageing transition), an

individual who is 60 years old who is able to perform all physiological activities

without assistance as well as being able to run a mile, do miniature things like

threading a needle, combing his/her hair, clipping his/her finger and toe nails,

lifting his luggage or carrying a container of a particular weight, could be defined
                                                                                   26


as functionally young, whereas by using chronological ageing he/she would have

already shifted from young to old age.

       In a monologue with my PhD. Supervisor – Professor Denise Eldermire-

Shearer – she noted that although the World Assembly on Ageing uses the

chronological age of 60 years to mark the commencement of the ageing process –

which earmarks the transition from young to middle age to old age – this is not

necessarily the experience of each individual. Embedded in Eldemire-Shearer’s

perspective is the acceptance that the ageing transition is not a static chronological

valuation that we have formulated as the benchmark for ageing, as this is not

necessarily the same across ethnicity, genetic composition and traits, or gender of

individuals.

       In summary, ageing is accompanied by normal declines in function as body

cells undergo senescence. Age-associated disease is also increasingly evident. Non-

communicable diseases and pathological impairment manifest as morbidity, disability,

and loss of function among older persons. These factors combine to diminish the

capacity to continue to carry out Activities of Daily Living (e.g. eating, bathing,

dressing, toileting, transferring (walking) and continence) and Instrumental Activities

of Daily Living (e.g. using the telephone, shopping, managing medication and handling

finances). As the capacity to fulfil these functions declines, so does the ability to

maintain independence and to ‘age in place’. As early as 1987, Jette and Bottomley

provided substantial evidence of the magnitude of the increase of disability with age;

disability defined as needing help in accomplishing or inability to perform one or more

of the Activities of Daily Living or Instrumental Activities of Daily Living. Among
                                                                               27


persons 65-74 years, 5% had some level of disability with respect to the Activities of

Daily Living (ADL). The prevalence was slightly more than twice that proportion in the

75- to 84-year-old group (11.4%), and among those 85+ years, 35 % had disability with

regard to the ADL. The pattern was similar with regard to the Instrumental Activities of

Daily Living (IADL) where 40% of elders of 85 years of age or more required help

compared with 5.7% of those 65 to 74 years old (Jette and Bottomley 1987). As

functional loss or decline increases, the need for support services (intra-familial and

extra-familial) to age in place also tends to increase.
                                                                               28


                                  Chapter Three

                  Population Ageing: Historical and Global

       In the late 1800s (1884) an Englishman named Francis Galton, who was

both a mathematician and medical doctor, set out collecting data on ‘physical and

mental functioning’ of some 9,000 people between the ages of 5 and 80 years

(Erber 2005, 4), because of his interest in life expectancy and the state of older

people. This was not the first time that such an examination had been done as in

1835 Adolphe Quetelet published a text in which he discussed the physical and

behavioural features of people at different ages. Like his predecessor, Galton

wanted to understand the human life span, but this time from an empirical

perspective. The epistemology at the time was based on authority, tradition,

speculation and mere non-scientific observation. Thus in keeping with his interest

and training as a mathematician, Galton wanted some empirical basis on which to

formulate a position on the matter. Thus, he sponsored an exhibition that would

allow for the gathering of pertinent data that would aid empiricism. The data were

later analyzed by several scientists. The process culminated with a published text

in 1922 by G.S. Hall titled ‘Senescence: The Second Half of Life’. The findings

not only concurred with the existing literature in physiology, medicine, anatomy

and philosophy but provided empiricism to the knowledge that existed at that

time. This begs the question – what explains that fascination of man in seeking to

understand ageing, and in particular, his/her intrigue with the aged and their

wellbeing?

       Globally, changes in Public Health – namely sanitation and nutrition, have
                                                                                 29


added a substantial number of years to people’s life expectancies. This is evident

in the life expectancy for the world as it increased from 46.5 years in 1950-1955

to 66.0 years in 2000-2005 (i.e. a 29.5% increase in approximately 50 years) and

come the next 50 years it will increase by 13.1%, suggesting that the changes in

public health measures and standard of living have improved life expectancy

more in the early 5-decades than the next half a century. In addition, it is equally

attributed to the introduction of antibiotics in the treatment of patient care. This

goes further to explain the reason for the demographic transition toward an aged

population. Prior to its development and implementation, pestilence and pandemic

would have limited life expectancy to below 50 years, in many instances. During

the pre-20th centuries, death statistics were used to measure health status and

mortality along with quality of life, which explains why physicians would be

preoccupied with illnesses and diseases as a measure of how to effectively address

the wellbeing of people. This is captured in a study done by Mckeown (1965)

which found a correlation between mortality and diseases from data for 1851 to

1900. He found that reduced mortality for the period was primarily due to

infectious diseases such as tuberculosis, typhus, typhoid, cholera and smallpox

(Mckeown, 1965, p. 57).

       The 20th century has brought with it massive changes in typologies of

diseases, where deaths have shifted from infectious diseases such as tuberculosis,

pneumonia, yellow fever, Black Death (i.e. Bubonic Plague), smallpox and

‘diphtheria’ to diseases such as cancer, heart illnesses, and diabetes. Although

diseases have shifted from infectious to degenerate, chronic non-communicable
                                                                                   30


illnesses have arisen and are still lingering in spite of all the advances in science,

medicine and technology. Non-communicable diseases such as heart disease,

hypertension, and diabetes mellitus are among the leading causes of mortality in

the Caribbean region (McKenzie and Bell 2004). Although a shifting away from

communicable and infectious diseases has occurred in the region, there is a

remarkable increase in some communicable and infectious ones such as HIV,

sexually transmitted infections (STIs), and in one particular country in the region,

Jamaica, since 2004 there have been reports of an outbreak of malaria and cholera

in particular geographical areas. In spite of morbidities and mortality causing

pathogens (Mckeown 1965), non-communicable diseases are responsible for more

deaths in the region than communicable diseases.

       This situation also exists among the Jamaican population where Morrison

(2000) in an article entitled ‘Diabetes and Hypertension: Twin Trouble’

establishes that diabetes mellitus and hypertension have now become two

problems for Jamaicans and in the wider Caribbean. This situation was supported

by Callender (2000) and Steingo (2000), at the 6th International Diabetes and

Hypertension Conference, which was held in Jamaica in March 2000, each

identifying a positive association between diabetic and hypertensive patients -

50% of individuals with diabetes who had a history of hypertension evident in old

age had their origin in childhood and early adulthood. Eldemire (1995a) argues

that hypertension and arthritis are two diseases that plague the Jamaican elderly,

but that they would have begun in early adulthood. In 2006, 34.8% of new cases

of diabetes and 39.6% of hypertension were associated with senior citizens, i.e.
                                                                          31


ages 60 and over (PIOJ, 2007).    Accompanying this period of the ‘age of

degenerative and man-made illnesses’ are life expectancies that now exceed 50

years. (Table 3.1.1)
                                                                            32


Table 3.1.1: Life Expectancy at Birth for Selected Regions by Both Sexes: 1950-
2050 (in years)

                                         Period
Regions:

              1950-1955   1975-1980   2005-2010    2025-2030   2045--2050

World         46.6        59.9        66.5         71.1        75.1
More
developed     66.1        72.3        76.2         79.5        82.1
regions
Less
developed     41.1        56.9        64.6         69.6        74.0
regions
 Least
developed     36.1        45.9        52.5         59.9        66.5
regions

Africa        38.4        48.7        49.9         58.0        65.4

Asia          41.4        58.6        68.8         73.5        77.2

Europe        65.6        71.5        74.3         77.8        80.6
Latin
America and
Caribbean
              51.4        63.0        72.9         76.8        79.5

Caribbean     52.2        64.5        68.7         73.2        76.9

Central       49.1        63.5        74.8         78.3        80.3
America

South         52.0        62.6        72.7         76.6        79.4
America
Northern
America       68.8        73.3        78.2         80.5        82.7

Oceania       60.4        67.4        75.1         78.6        81.2
Source: World Population Ageing, 2007
                                                                                   33


          Generally when one speaks about population ageing, people begin to think

of reduced fertility and mortality and an increase in the population older than 60

or 65 years, and this is rightly so, but having given information on life

expectancy, the author will examine the feminization associated with population

ageing. While life expectancy for the globe has moved from 46.5 years from birth

during 1950-1955 to 66.0 years in 2000-2005, women continue to outlive men.

During 1950-1955, global life expectancy for women was 47.9 years, which was

2.7 years more than that of men in the same period, and during 2000-2005, the

difference increased by 4.2 years (which is a 55.6% increase). While the gap will

narrow come 2025 to 2030 and for 2045 to 2050, life expectancy will still have a

feminization to it as women will be still outliving men in the future (Figure 3.1.2).

Table3.1.2: World Life Expectancy by Specific Aged Cohorts and by Gender, 1950—
2050
Details         Age        1950-       1975-       2000-       2025-       2045-
                           1955        1980        2005        2030        2050
Life
Expectancy:
Total        Birth      46.5       59.8       66.0        72.4       76.0
             60         ..         ..         18.8        21.0       22.2
             65         ..         ..         15.3        17.2       18.2
             80         ..         ..         7.2         8.2        8.8
Female       Birth      47.9       61.5       68.1        74.7       78.5
             60         ..         ..         20.4        22.8       24.1
             65         ..         ..         16.7        18.7       19.9
             80         ..         ..         7.9         9.0        9.7
Male         Birth      45.2       58.0       63.9        70.1       73.7
             60         ..         ..         17.0        19.1       20.2
             65         ..         ..         13.8        15.5       16.4
             80         ..         ..         6.3         7.1        7.6
Source: Population Division, DESA, United Nations, in United Nations. 2004.
World Population Ageing 1950-2050. New York: United Nations, pp. 47
                                                                                   34



          Globally, apart from the feminization of life expectancy, what else is there

on population ageing? During 1950 to 1955, the rate of growth of the world’s

population was 1.8 percent and it was the same for the elderly population, and it

was 3.1 percent (72% more than the general growth rate for the world’s

population) for elderly 80 years and beyond (Table 3.1.4). The rate of growth of

different regions of the world can be analyzed in Table 3.1.5. On further

examination of the total growth rates (Table 3.1.4) and that of the aged

population, the population 80+ was increasing faster than the other elderly age

cohorts (Table 3.1.4).      Come 2045-2050, the rate of growth for the globe’s

population will be 0.5% while it would be 6 times more for elderly 80+ years.



Table 3.1.4: World Growth Rate (in %) by Aged Cohorts, 1950—2050

Details        Age        1950-        1975-       2000-       2025-       2045-
                          1955         1980        2005        2030        2050

Total                 1.8        1.7        1.2          0.8        0.5
           60+        1.8        1.8        1.9          2.8        1.6
           65+        2.1        2.6        2.3          3.1        1.6
           80+        3.1        2.7        3.8          3.9        3.0
Source: Population Division, DESA, United Nations, in United Nations. 2004.
World Population Ageing 1950-2050. New York: United Nations, pp. 49




          While people are living to age 70 years and beyond in many developed

and in some developing states (see Table 3.1.1), the question is - are they living a

healthier life – how is their wellbeing within the increases in life expectancy?

Alternatively, is it that we are just stuck on life expectancies and diseases as

primary predictors of wellbeing – or health status?
                                                                                 35


          Before the establishment of the American Gerontology Association in the

1930s and their many scientific studies on the ageing process (Erber 2005), many

studies were done based on the biomedical model, that is, physical functioning or

illness and/or disease-causing organism (Brannon and Feist 2004, 9). Many

official publications use either (i) reported illnesses and/or ailments, or (ii)

prevalence of seeking medical care for sicknesses, to speak of health status.

Some scholars have still not moved to the biopsychosocial predictors of health

status.    The biopsychosocial model incorporates the mind (i.e. psychological

conditions), along with biology and social conditions (i.e. culture, belief systems,

demographic characteristics). The dominance of the biomedical approach is so

strong and present within the twenty-first century, that many doctors are still

treating illnesses and sicknesses without an understanding of the psychosocial and

economic conditions of their patients. To illustrate this more vividly, a public

health nutritionist, Dr. Kornelia Buzina, says that “when used appropriately, drugs

may be the single most important intervention in the care of an older patient …

and may even endanger the health of an older patient …” (Caribbean Food and

Nutrition Institute, 1999:180)

          Global Issues on Ageing

          Even though the ageing process is lifelong, and although it may be

constructed within each society differently, many decades have elapsed since

Galton’s study on the health status of people. Despite changes in human

development and the shift in world population toward demographic ageing –

people living beyond 65 years (see ILO 2000; Wise 1997), the issues of the aged
                                                                                                                     36


and their health status have not taken front stage on the radar of demographers

unlike many other demographic issues. This is equally true for many Caribbean

nations. (See Figure 3.1.1 below).


                                                                         U.S.A
                                                                      Sw eden

               Major Area, region and country
                                                                      Germany
                                                                           Italy

                                                                        Europe
                                                                         Japan

                                                                          India

                                                                         China
                                                Latin America and the Caribbean

                                                                         Africa
                                                                         World

                                                                                   0   10     20     30      40
                                                                             Percentage of the Elderly (65+ years)

                                                                                       1950   2000   2050




       Figure 3.1.1: Selected regions and their percent of pop. 65+ years
       Source: United Nations 2005: World Population Prospects: The 2004 revision (page 20)




Again, as we mentioned earlier, global changes in Public Health have added
substantially more years to life expectancies, which is captured in the proportion
of elderly population come 2050 (Figure 3.1.1). Remarkably, the majority of the
world’s population come 2050 will be experiencing population ageing because
they would have had more people 65 years and older. Thus, there is a
demographic transition toward an aged population. In addition, this is attributed to
the introduction of vaccination, in particular to the discovery of penicillin.



       The issue of non-communicable diseases is not only a phenomenon

specific to Jamaica, but is equally a Caribbean challenge for policy makers. (See

Figure 3.1.2 below)
                                                                                                    37



              Trinidad &
               Tobago


               St. Lucia
                                                                             Acute respiratory
                                                                             infections
              Montserrat                                                     Hypertension


               Jamaica                                                       Diabetes
    Country




                                                                             Neoplasms
                Guyana

                                                                             Cardiovascular
              Dominica                                                       disease

                                                                             Cerebrovascular
                                                                             disease
              Barbados


              Bahamas


                           0        1       2        3       4        5
                           Ranked Order of 5 leading causes of mortality




Figure 3.1.2: Ranked order of five leading causes of mortality in the population 65 yrs and older, 1990
Source: Adopted from Caribbean Food and Nutrition Institute1999, 222
                                                                                                                      38




                      Stroke




                Heart disease
                                                                        Jamaica
                                                                        Female
     Diseases

                                                                        Jamaica Male
                     Arthritis

                                                                        Barbados
                                                                        Female
                    Diabetes                                            Barbados
                                                                        Female
                                                                        Barbados
                                                                        Male
                Hyp ertension



                                 0   20        40         60
                                     Percentage



Source: Figure taken from Caribbean Food and Nutrition Institute1999, 225.
Figure 3.1.3: Leading causes of self-reported morbidity in the population of seniors, by gender in Barbados and Jamaica.




                The data in Figure 3.1.3 shows that hypertension and arthritis are

morbidities that significantly plague both men and women in both Caribbean

countries. These chronic non-communicable diseases continue to interface within

the functional lives of the elderly, which mean that they are indeed living longer

but are faced with lowered wellbeing. In a study, generalizable to the Jamaican

population, Sargeant et al. (2004) reported that among persons aged 45-74 years,

the overall prevalence of diabetes was 22.4%, and much existing diabetes was

undetected.                Furthermore, among persons aged 45-74 years, the overall

prevalence of diabetes was 22.4%. Another study, based on the Jamaica Lifestyle

Survey 2001, documents the gender-specific prevalence of 66% (males) and 71 %
                                                                                 39


(females) among persons 65+years old (Wilks, 2007). These observations provide

further evidence of the eminence of non-communicable disease among older

persons in Jamaica. Ageing, though not a disease itself, may be accompanied by

increased frequency of disease.

       Secondly, if they are poor with proper and adequate health care coverage –

which could be private or public - the implications of the cost of care along with

daily living could add further stresses to the status of life experienced by the

elderly. Hence, living longer, although it is directly related to reduced mortality,

does not speak to the lifestyle changes and their positive influences on the

wellbeing of seniors. A study conducted by Costa, using secondary data drawn

from the records of the Union Army (UA) pension programme that covered some

85% of all UA, shows that there is an association between chronic conditions and

functional limitation – which include difficulty walking and bending, blindness in

at least one eye and deafness (Costa 2002). Among the significant findings is the

predictability between congestive heart failure in men and functional limitation

(i.e. walking and bending). Although Costa’s study was on men, this equally

applies to women as biological ageing reduces physical functioning, and so any

chronic ailment will only add further to the difficulties of movement of the aged,

be it man or woman.

       Some scholars have still not moved to the post-biomedical predictors of

health status. The dominance of this approach is so strong and present within the

twenty-first century, that many doctors are still treating illnesses and sicknesses

without an understanding of the psychosocial and economic conditions of their
                                                                                   40


patients.   Among those who have studied health are demographers. Is there a

difference between the approach of the other scholars (or scientists) and

demographers?

        Demographers have spent years studying mortality, and this has been used

as an indicator of life expectancy, such as the Coale and Demeny Model life

tables, and by extension health status. Life expectancy, on the other hand, has

always been viewed as the avenue through which demographers evaluate the

health status of people; as lived years is an indicator of living beyond certain

health conditions. Thus, health and wellbeing are tied to mortality patterns, which

is rightfully so, but this approach puts little emphasis on conditions that are likely

to decrease morbidity and thereby reduce mortality. With this being the case,

demographers have consumed more time assessing mortality, life expectancy and

morbidity because of their close approximation of wellbeing (or health status),

and this is similarly the case for Caribbean demographers.
                                                                                41


                               Chapter Four

  Population Ageing: Caribbean Demographic Trends, with Emphasis on

                                    Jamaica

       The Caribbean has been identified as the most rapidly ageing region of the

world. During the 1960 -1995 period, there was a 76.8% increase in the elderly

population (UN.org). The mean growth rate in the elderly population was 5.3%,

which was recorded for the period 1995-2000. The elderly as a percentage of total

population has been projected to reach about 15% by 2020, an almost four-fold

increase over the 1950 figure of 4.3% (PAHO, 1997).

       Demographic development in the Caribbean has taken a path similar to the

rest of the world (Population Reference Bureau 2007; STATIN 2006; United

Nations 2005c). Over the years, the movement has been such that mortality and

fertility have been declining, and the population 60 years and older has been

increasing proportionately more than the percentage increase in children (aged

less than 15 years) and/or the working age (15 through 59 years) population.

Jamaica as well as the rest of the Caribbean and Latin America is said to be at the

second stage of the demographic transition model (STATIN 2007). Cajanus

(1999) argues that what has changed since the 1960s in the Caribbean is the pace

of population ageing. He commented that “…demographic changes … began in

earnest in the 1960s” (p. 217) to describe what is known as demographic ageing

(or population ageing), which is a feature in many developed nations and some

developing societies. This is now a characteristic of some states in the Caribbean

like Jamaica, Cuba, Barbados, and Trinidad and Tobago.
                                                                                 42


       Several Caribbean countries, such as the aforementioned ones, could be

said to be approaching the third stage of the transition. The demographic

transition refers to the changes in population growth that are attributable to

transition from high to lower levels of fertility and mortality. So for countries to

be at the third stage of the transition, they would be experiencing population

ageing due to persistently low fertility, and even lower mortality. Like the rest of

the world, these changes also brought improvements in living conditions,

advancement in medicine, improvements in health care and discovery and use of

family planning measures.

       Statistics revealed that the total fertility from 1970 to 1975 for the world

was 4.49 and from 2000 to 2005, it fell to 2.65; whereas in Latin America and the

Caribbean between 1970 and 1975, it was 5.05 and this was further reduced to

2.55 from 2000 to 2005 (United Nations 2005c, xxi). As early as 2005, some

countries in the Caribbean had reached replacement level fertility. Total fertility

per woman reached in the Bahamas is 2.2, Barbados 1.5, Jamaica 1.93

(Demographic Statistics, 2006) and Trinidad and Tobago, 1.6 (United Nations

2006, 87-89). Barbados, Jamaica and the twin islands of Trinidad and Tobago are

currently experiencing below replacement level fertility (Total Fertility Rate –

TFR of 2.1 – United Nations 2000, 4). Since 2005, this has become a

demographic reality for many developed nations. The examples here are some

countries in Eastern Europe (TFR, 1.3) Southern Europe (TFR, 1.4) Northern

Europe (TFR, 1.7) and the United States, 2.0 (United Nations 2007; 2005c, xxi).

In addition, mortality in the Caribbean has been falling, coupled with increased
                                                                               43


life expectancies comparable with those in developed nations, beyond 71 years.

(United Nations 2005c, xxii), which according to Rowland (2003, 18) are

components within the demographic transition model.

       Return migration also plays a significant role in the ageing of the

Caribbean’s population. Jamaica, like Trinidad and Tobago and Barbados, is

experiencing the return of some of those who migrated in the 1950s-1960s, and

who are now elderly. In addition to return migration of aged Jamaicans, the

continuously high emigration of young people (Caribbean Food and Nutrition

Institute 1999) has further exacerbated population ageing in the country. From

the data reported in Table 4.1.1, at least 65 percent of the net migration is

accounted for by ages less than 30 years. Even though the negative net migration

of Jamaicans has been reduced by more than half over the last twenty years

(1988-2006), the pattern of those who emigrate has remained the same. However,

in ages 60 years and above, based on the available data in Table 4.1.1, there is

predominantly a net inflow of migration to Jamaica. This explains the return

migration of elderly Jamaicans within the context of net outflow at the younger

ages, which depletes the human resources of the country. Although the net

migration outflow of migrants from Jamaica, for each year, has never surpassed 1

percent of the total population for the year in question, the cumulative effect of

this over a long period is equally significant in the explanation of the nation’s

ageing population.
                                                                                 44


Table 4.1.1: Net External Migration of the Population by Selected Age Groups,
Jamaica: 1988-2006

                              Net Migration

Year                                  Age Groups
                     0 – 14          15 – 29     30 – 59           60+        Total

     1988            -7,857         -17,411        -12837          -802     -38,935
    1989           -8,508          -10,435          5,638        2,859      -10,446
    1990           -9,184          -15,021        -2,192           305      -26,092
    1991           -7,914          -12,296        -7,227         1,525      -25,912
    1992                *                *          *               *       -20,462
    1993           -8,068           -16,731        2,637           973      -21,319
    1994               *                *            *               *      -18,984
    1995           -1,822          -5065          -7,771         -3011       -17669
    1996                *             *              *              *       -18,096
    1997                *              *             *              *       -19,773
    1998                *              *            *               *       -20,133
    1999               *               *            *              *        -20,959
    2000                *              *            *               *       -21,834
    2001               *               *             *            *         -21,742
    2002               *              *              *             *        -23,160
    2003                *             *              *             *        -17,679
    2004            -4,209         -10,239        -5,786          2,365     -17,798
    2005               *             *              *              *        -17,169
    2006               *              *              *             *        -17,087
Source: Computation was done by Author from Demographic Statistics, various years.
* Missing data

       Therefore, many Caribbean countries began experiencing population

ageing since as early as in the 1950s and/or the 1960s. In 1950, 8.5 percent of

Barbados’ population was 60 years and older; Cuba, 7.3%; Suriname, 8.4%,

which was higher than 6.9 percent for the Caribbean and 8.2 percent for the

world. (Table 4.1.2 to Table 4.1.5). Jamaica’s population ageing, on the other

hand, did not begin until the 1960s (see Table 4.1.6), which coincides with

Eldemire 1997). Using the growth rate of the population for different age groups

as an indictor of ageing population, Jamaica’s population 65 years and over
                                                                                  45


doubled from 1960-1970 and 1943-1960, which only occurred in this age group.

Although Professor Denise Eldemire believes and uses the chronological age of

60 years and older to operationalize the elderly and the data below utilizes 65+

years, it should be noted that the general conclusion of population ageing between

both scholars is the same. It should be noted here that even though the author

believes, like Eldemire, that old age commences at 60 years, which is in keeping

which the United Nations’ operational definition of elderly (i.e. old age), the

Statistical Institute of Jamaica, like demographers, uses 65+ years. Based on the

records of statistical publications by the Statistical Institute of Jamaica, prior to

1991 the agency used 65 years as the benchmark of old age. This approach, I

believe, is due substantially to the fact that Professor Roberts, who was a

demographer, was the chief advisor to the organization. However, post-1991, the

Statistical Institute of Jamaica has incorporated 60 to 64 years as a part of its

publication on the elderly.

       However, in the Caribbean, the matter has recently begun to be of concern

(Caribbean Food and Nutrition Institute 1999, 192, 217). The reason for this

thrust is because of the rate of increase of this age cohort compared to the other

age cohort. By 2050, the population of people 60 years and older in some

Caribbean nations will more than double, while the young population (ages 0 to

14 years) would have been reduced by half.

       Some developing states such as Barbados, Trinidad and Tobago and

Jamaica are currently experiencing a shift toward an ageing population (see

Appendix IV). In 2007, all three Caribbean nations had in excess of 10 percent
                                                                              46


of their population ages 60 years and older. Barbados, on the other hand, has the

largest percentage of persons ≥ 60 years (13.2%).
                                                                                                                                        47


Table 4.1.2: Estimated or projected populations by Selected Age Groups of different Caribbean Nations: 1950, 1975, 2007 and 2050
(in %)
                  1950               1975             2007             2025                2050


               0-14yrs    60+ yrs    0-14 yrs   60+ yrs   0-14 yrs   60+ yrs   0-14 yrs   60+ yrs   0-14 yrs   60+ yrs
Country:

Barbados       33.2       8.5        31.5       13.6      18.4       13.6      15.4       25.3      14.7       35.9

Guyana         41.1       6.7        44.1       5.5       28.7       7.7       19.9       15.0      13.3       35.2

Jamaica        36.0       5.8        45.2       8.5       30.2       10.3      24.4       15.0      18.5       23.6

Suriname       40.0       8.4        47.6       5.8       29.5       9.2       23.3       15.4      16.7       27.6

Trinidad       40.4       6.1        38.0       7.6       20.7       11.4      19.2       20.2      16.6       32.5

Caribbean 38.6            6.9        39.9       8.1       27.1       11.1      23.0       16.4      18.6       24.8

Source: United Nations. 2007: World Population Ageing, 2007, and United Nations. 2005c: World Population Prospects: The 2004 Revision
                                                                                                                     48




Table 4.1.3: Rate of Growth for Selected Regions and Countries, Based on Certain Time Periods: 1950 to 2050 (in %)

Regions and/or
Countries                      1950-1955      1975-1980       2005-2010      2025-2030       2045-2050


World                          1.8            1.7             1.1            0.7             0.4
More developed regions         1.2            0.7             0.2            0.0             -0.1
Less developed regions         2.1            2.1             1.3            0.9             0.5
Least developed countries      2.0            2.5             2.3            1.9             1.3

Africa                         2.2            2.8             2.1            1.7             1.2
Asia                           2.0            1.9             1.1            0.6             0.2
Europe                         1.0            0.5             -0.1           -0.3            -0.4
Latin America &
Caribbean                      2.7            2.3             1.3            0.7             0.2

Caribbean                      1.8            1.5             0.8            0.4             -0.1
Central America                2.7            2.7             1.4            0.8             0.2
South America                  2.8            2.3             1.3            0.7             0.3
Northern America               1.7            1.0             0.9            0.6             0.4
Oceania                        2.1            1.5             1.2            0.8             0.4

Source: World Population Ageing, 2007
                                                                                                               49


 Table 4.1.4: Cuba: Selected Statistics of the Aged Population, 1899-2025

Detail                1899               1919         1950                  1980         2000         2025

 60+ (population,           4.6             4.8              7.3              10.8         13.4            22.1

          %)

   Median age          20.7yrs            18.7yrs          23.3yrs           24.4yrs      32.4yrs         38.6yrs

  Ages-Percent              100            100              100               100          100             100

      60-64             47.7               41.8             33.5              29.9         30.1            32.7

      65-69             19.4               20.9             26.7              25.2         22.5            20.0

      70-74             16.4               15.8             19.7              20.1         19.0            18.2

      75-79                 6.0             8.4             12.4              14.9         13.0            14.3

         80+            10.5               13.1              7.7               9.9         15.5            14.8

 Source: 1899 and 1919: Cuban Population Censuses; 1950-2025: United Nations, 1991, pages
 144-145 in R H. Castellón. 1994. Population Ageing in Cuba. Malta: International Institute of
 Ageing (United Nations – Malta), p. 25.



 Table 4.1.5: Cuba: Life Expectancy by Gender. 1950-1986

 Detail              1900     1950         1955     1960           1965       1970       1975       1980     1986



 Male – at birth     31.2         53.6     58.4      62.0            65.4       68.6      71.1      72.3     72.7

 Female – at birth   35.1         57.9     62.9      66.1            68.9       71.8      74.6      75.8     76.3

 Male – at 60                     15.1     15.1      16.0            16.9       17.7      18.8      19.4     19.5

 Female – at 60                   16.7     17.0      17.7            18.5       19.6      20.7      21.6     21.6

 Male – at 80                     4.8       4.9      5.0             5.2           5.7    6.3       7.5       7.2

 Female – at 80                   5.1       5.5      5.6             5.8           6.7    6.9       8.2       8.0

 Source: Quoted in R H. Castellón. 1994. Population Ageing in Cuba. Malta: International
 Institute of Ageing (United Nations – Malta) p. 32
                                                                                    50


Table 4.1.6: Rate of Growth of Selected Age Groups and of Total Population of
Jamaica, using Census Data: 1844-2050 (in %)

Year                     0-14            15-64            65+3             Total


1844-1861                *               *                *               0.87
1861-1871                 *               *                *              1.25
1871-1881                  *             *                *               1.25
1881-1891               0.94             1.07             -0.4            0.86
1891-1911               1.39             1.19             0.90             1.25
1911-1921               0.18             0.33             0.85             0.29
1921-1943               1.27             1.77             2.08             1.59
1943-19501              1.39             1.76             0.55             1.57
1950-19602              2.25             1.06             1.74             1.55
1943-1960               2.12             1.00             1.65             1.46
1960-1970               2.07             0.03             3.36             1.08
1982-1991               -0.32            1.04             1.18             0.55
1991-2001               0.33             1.46             1.43             1.08
2001-2006               -1.61            1.33             1.10             0.42
2005-2010               *                *                1.0**            0.4**
2025-2030               *                *                3.3**            0.0**
2045-2050               *                *                2.0**            -0.6**
Source: Computed by Author from Statistical Yearbooks and Demographic Statistics
            * Missing data
            ** Taken from the World Population Ageing 2007:309
1
 The figures for 1943 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
2
 The figures for 1960 were taken from the STATIN (1974), and the values for
1950 were taken from the United Nations 2007
3
 The rationale that explains the use of 65+ to represent the elderly is solely due to
the statistical data that are available prior to 1991. Before 1991, the Statistical
Institute of Jamaica’s operational definition for the elderly was 65 years and
older. Hence, their publication between 1844 and 1991 did not produce years for
60+. However, post 1992, the organization began providing data for both ages.
As such, the researcher used 65+ because he wanted to examine figures from
1844 to 2006.
                                                                                 51


       The issue of the ageing of a population cannot be simply overlooked, and

has far-reaching implications for labour supply, pension systems, health care

facilities, product demand, mortality, morbidity and public expenditure, among

other events. Ageing is not simply about mortality, fertility and/or morbidity.

The phenomenon is about people, their environment and how they must coexist in

order to survive. Ageing, therefore, is here to stay.       In order to grasp the

complexities of this phenomenon, Lawson’s monograph adequately provides a

summative position on the matter. She noted that:

       Actually, it is predicted (U.N.) that developing countries are likely to have
       an older generation crisis about the year 2030, that is, about the same time
       as most developed countries (Lawson 1996, 1)

       This demographic transition is not only promulgated by Lawson, but was

argued by Cowgill (1983) who believed that during the next half-century (2050),

there is a strong possibility that this transition will be an issue for some

developing nations. This implies that population ageing, which has been the

experience of many developed nations (Gavrilov and Heuveline 2003; Marcoux

2001; Lawson 1996), will be a reality for some lesser developed countries and

more developing regions in the future.

       Seniors cannot be neglected, as they will constitute an increasingly larger

percentage of total population and sub-populations in different regions than in

previous centuries (UN 2005; WHO 2005; Chou 2005; STATIN 2004; Apt 1999;

Caribbean Food and Nutrition Institute 1999a; Randal and German 1999; US

Census Bureau 1998; Eldemire 1995, 1994; European Foundation for the

Improvement of Living and Working Conditions 1993; Mesfin et al. 1987; Grell,
                                                                                  52


1987; National Health and Welfare 1982). According to Randal and German

(1999), the number of aged persons living in developing countries will more than

double come 2025, ‘reaching 850 million’. The Caribbean is not different, as

according to Grell (1987) the English-speaking Caribbean from the 1970 census

revealed that between 8.8 and 9.8 percent of the populace were 60 years and

older, a matter which Lawson noted had begun in Jamaica since the 1900s

(Lawson 1996, 1-37). From the figures presented in Appendix XIV (i.e. growth

rates in percentage of selected age groups), the author disagrees with Lawson that

population ageing began in the 1900s in Jamaica, but more specifically it started

in the 1960s.

       Demographic Trends: Jamaica

        The annual growth rate for the Jamaican population since 1996 has

always been less than 1.0%, and the figure for 2006 is estimated to be 0.5%

(Demographic Statistics 2006) which is lower than the global average of 1.2

percent (CIA 2007). In order to provide readers with a better understanding of

population ageing in Jamaica, we need to present statistics that can be used to

establish any trends, as well as to be able to provide a more detailed analysis of

this phenomenon. Jamaica’s elderly population (i.e. ages 60+ years) has increased

significantly since the mid 1960s (see Eldemire, 1997, 77), but based on the

statistical publications for the nation the author is unable to concur with Eldemire.

       Jamaica’s life expectancy at birth for males between 1879 and 1882 was

37.02 years and for females it was 39.80 years. Between 2002 and 2004 males

are expected to live for 71.26 years and females 77.07 years, which is a clear
                                                                                              53


indictor of demographic ageing (See Table 4.1.7, below). In order to grasp the

complexity of life expectancy, I will disaggregate the elderly population of the

society, using data from 1991 to 2001. An examination of 5-year age cohorts of

the elderly population in Jamaica revealed that 85+ years is the fastest growing

from the general elderly population (see Figure 4.1.1). Society is experiencing an

oldest-old population explosion never before seen in its history, and this points to

the gains made in public health measures, and improvements in the standard of

living of the general populace since the 20th century.


         50%


         40%


         30%


         20%


         10%


          0%
                    60 - 64       65 - 69        70 - 74       75 - 79        80 - 84   85+
                                               Age Group (yrs.)


       Compiled by author using data from the Statistical Institute of Jamaica (2003)

       Figure 4.1.1: Percentage change in the size of elderly age sub-groups, 1991-2001.

       Does this mean better quality of life or subjective wellbeing? Answers

will be given throughout this book, but an insight will be provided here, as a study

by Powell, Bourne and Waller (2007) found that the psychosocial wellbeing of

Jamaicans was moderately high (mean score = 6.8 out of 10). On examining this,

they found that the subjective wellbeing of those in the lower subjective social
                                                                                54


class had a minimal score (mean score = 5.8 out of 10) compared with those in the

upper class (mean score = 6.5 out of 10) and those in the middle class (mean score

= 6.8 out of 10) (Powell, Bourne and Waller 2007). Furthermore, of the sampled

population, 1,338 randomly stratified Jamaicans (69%), indicated that their

current economic situation was at most average, with 19% reporting that it was

bad. Can we say that a two-fold increase in life expectancy means better quality

of life?




Table 4.1.7: Life Expectancy at Birth of Jamaicans by Sex: 1880-2004 (in yrs)
                            Average Expected Years of Life at Birth
Period:                     Male                         Female

1880-1882                   37.02                        39.80

1890-1892                   36.74                        38.30

1910-1912                   39.04                        41.41

1920-1922                   35.89                        38.20

1945-1947                   51.25                        54.58

1950-1952                   55.73                        58.89

1959-1961                   62.65                        66.63

1969-1970                   66.70                        70.20

1979-1981                   69.03                        72.37

1989-1991                   69.97                        72.64

1999-2001                   70.94                        75.58

2002-2004                   71.26                        77.07
Sources: Demographic Statistics (1972-2006) in Bourne (2007)
                                                                                55


Using the population pyramid for Jamaica, population ageing come 2050 will be

even worse than in 2007 (See Figure 4.1.2-4.1.4).


Pictorial of the population ageing in Jamaica, 2000 – 2050




Figure 4.1.2: Population pyramid of Jamaica by age and gender, 2000


From the U.S. Census Bureau, International Data Base, Jamaica’s population in
2000 showed a relatively young population, which is because of the broad base.
This triangular age profile is an indication of the high proportion of children,
which means that Jamaica in 2000 had high fertility and high mortality rates.




Figure 4.1.3: Population pyramid of Jamaica by age and gender, 2025
However, the young population that was observed in 2000, from all indications, is
                                                                                 56


shifting as the base of the age profile narrows and the middle expands. Within the
demographic transition, this is a representation where the young population is
falling and shifting toward the middle ages, and old type of profile.




Figure 4.1.4: Population pyramid of Jamaica by age and gender, 2050



        While the demographic transition is not necessarily as obvious in 2025 as

in 2050, Jamaica’s population profile will definitely be contracting at the base and

expanding at the middle and old ages. Such a profile is an indication of low

fertility and death rates. A careful look at the diagram reveals that come 2050 and

beyond, Jamaica’s oldest elderly will consist of substantially more females.

Using statistics for 1-decade (data on Jamaica – 1991-2001), I will provide a

synopsis of the ageing phenomenon at a glance in Figure 4.1.5.
                                                                                                                                                                                   57




50%


40%


30%


20%


10%


 0%
         0-4

               5-9

                     10 - 14

                               15 - 19

                                         20 - 24

                                                   25 - 29

                                                             30 - 34

                                                                        35 - 39

                                                                                  40 - 44

                                                                                            45 - 49

                                                                                                      50 - 54

                                                                                                                55 - 59

                                                                                                                          60 - 64

                                                                                                                                    65 - 69

                                                                                                                                               70 - 74

                                                                                                                                                         75 - 79

                                                                                                                                                                   80 - 84

                                                                                                                                                                             85+
-10%


-20%
                                                                                                                                              ©K. James 2008
                                                                       Age group (yrs.)


       Figure 4.1.5: Percentage change in age sub-groups as a proportion of total population
       between 1991 and 2001
       Compiled using data from the Statistical Institute of Jamaica (2003)




                 The “greying” of the Jamaican population is coming, and has already

       made its way within the society. From records of the Population Division of the

       United Nations, Jamaica’s population 60 years and older in 2050, using the

       medium variant, is likely to be 24% of the entire population, with 17.7% being 65

       years and older, compared to approximately 5.6% being 80 years or over (United

       Nations 2007a; 2005c).                                          These shifts indicate the presence of degenerative

       conditions at older ages, increased disability and diminished quality of life. The

       disparity in gender composition at older ages speaks to the higher morbidity in
                                                                              58


women and higher mortality for men (see Newman 2001, 8). With this inevitable

pending socio-economic and political challenge ahead, should demographers be

bothered with studying ageing and the wellbeing of the aged?

         Having established the issue of population ageing and the demographic

transition throughout the world, with particular emphasis on the Caribbean and

especially Jamaica, we will now venture to evaluate the crux of this paper,

wellbeing, and the wellbeing of aged Jamaicans. From the PLC reports published

by the PIOJ and STATIN, which         are primarily focused on the traditional

construct of health using the biomedical model, the researcher is putting forward

a position that if we wish to more effectively capture the wellbeing status of

Jamaicans, we must operationally expand the definition of health in such a

manner that it encompasses biopsychosocial factors such as – (i) biological; (ii)

psychological; (iii) social; (iv) economic, and (v) environmental conditions, as

this vulnerable group may even be worse off than reported, given the definition

chosen to measure health status. There are no published works on the general

wellbeing of the Jamaican elderly in which the researchers have sought to capture

a quality of life index which encompasses biological, sociological, psychological

and environmental conditions. It is within this general framework that this study

of the elderly is timely, as it seeks to expand an assessment of the subjective

wellbeing of aged Jamaicans from the perspective of a more comprehensive

model.
                                                                                59


                                Chapter Five

      AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                      WELLBEING OF THE ELDERLY

                                   PART ONE

        This present study examines the determinants of wellbeing of the

Jamaican aged. The research focuses on the determinants of wellbeing,

specifically on the aged, from the use of the biopsychosocial model. The rationale

behind this approach is embodied in the fact that physical functioning and frailty,

symptoms and diseases for medical attention do not constitute the only

components within the discourse of health and wellbeing. Grossman’s model

highlights socioeconomic conditions such as cost of health care, the educational

level of family members, household income, and biological conditions in the form

of stock of health (i.e. previous health status) and lifestyle practices (such as

exercise, non-smoking and low consumption of alcoholic beverages).

        Although Grossman’s model of measuring wellbeing stops short of

including psychological and ecological conditions, their inclusion in this study is

based on the Ecological Model and the Selective Optimization Model which

undoubtedly argue that the environment influences the wellbeing of aged people.

Furthermore, the Models show that the psychological state of aged persons

changes with years because of frailty and other physiological changes. Stress can

be used as a deciding psychological condition that drives other biomedical

illnesses.   This was put forward by a neuropsychologist from North Ridge

Medical Centre, U.S.A., speaking at the 6th International Conference on Diabetes

and Hypertension in Jamaica. Additionally, seeking to diagnose depression in a
                                                                                60


patient with hypertension and diabetes is problematic, as many of the conditions

overlap (see McCarthy 2000). Therefore, the Selective Optimization and the

Ecological Model have helped the researcher to identify other factors, such as the

environment, and positive and negative affective conditions that are likely to

affect the wellbeing of aged people, as well as variables which were already

identified by Grossman, and later modified by Smith and Kington. Thus, this

study will evaluate different factors aimed at influencing the wellbeing of elderly

Jamaicans, which are in keeping with the model as outlined in the theoretical

framework.

       In putting together these discourses, the writer sought to undertake a

mapping of the scholarly and policy landscape with the aim of developing

taxonomy in this regard. As this paper seeks to examine the wellbeing of the

Jamaican elderly, it will be done in the wider context of the demographic

transition that is ‘sweeping’ our world. One of the primary reasons for this paper

is that “Population ageing is changing the numbers of older persons in relation to

that of other age groups in the population in all regions of the world, with the

changes occurring more rapidly in the more developed regions...” (UNFPA 2002,

8). But there is still insufficient study on the elderly among us.

       In any wellbeing assessment of the elderly, we cannot only focus on

decomposing increased life expectancy or the causes of mortality, in an attempt at

understanding quality of life, as wellbeing goes far beyond those parameters

(Bourne, 2007, 2008a, 2008b, 2008c, 2008d, 2008e, 2009a, 2009b; Longest 2002;

Abel-Smith, 1994). Here the paradigm that is needed in practice, as against a
                                                                                 61


conceptual perspective, must be in keeping with the definition offered by the

WHO in the Preamble to its Constitution in 1948 that it must extend to the social,

psychological, economic and environmental conditions, and not merely biological

conditions.

       Rowland (2003), Preston et al. (2001), Newell (1988), and Shryock et al.

(1976) provided an extensive and elaborate model of life tables (Elo 2001) on

particular patterns from which they compute life expectancy.          Demographic

studies on life expectancy imply that mortality patterns explain people’s health

status (See Crimmins, Hayward and Saito 1994; Vaupel 1986; Pollard 1982), but

despite the procedures and the high applicability of those deterministic models in

projecting life span, the calculations lack socioeconomic and psychological

insight. Studies on mortality have shown that there is a high correlation between

patterns of death and health and/or life expectancy (See for example Vaupel and

Romo 2003; Horiuchi and Wilmoth 1998; Gage 1994). Furthermore, an article in

honour of Nathan Keyfitz’s 90th birthday, using calculus – mathematical formulae

by integration - shows that decomposing change in life expectancy finds that the

‘time derivative of life expectancy’ is a function of (1) the average rate of

improvements in mortality by the number of life-years lost and (2) that a

covariation exists between improvement in death and remaining life expectancies

(See Vaupel and Romo 2003, 201). Even though life expectancy is a good

explanation of people’s wellbeing, it does not speak to the quality of those years

lived by the individual. Hence, ‘hale life expectancy’ is an alternative technique

that bridges the gap between years lived (or to be lived), and years lived (or to be
                           62


lived) in ‘good’ health.
                                                                                63


       Healthy Life Expectancy

       One of the drawbacks to the use of life expectancy is its failure to capture

‘hale’ years of life. Traditionally when life expectancy is measured, it uses

mortality data to predetermine the number of years of life yet to be lived by an

individual, assuming that he/she subscribes to the same mortality patterns of the

group. The emphasis of this approach is on length of life and not on the quality of

those years lived. Hence changes in life expectancy are primarily due to mortality

movements, and imply changes to external conditions in the socio-biological

environment. These changes include public health, water and food quality, the

physical milieu, and technological/medical advancement. With all the

aforementioned conditions that have improved over the last century, increased life

expectancy in the world is not surprising to scholars. One way of evaluating

population ageing in the world or in any geopolitical space is ‘life expectancy’.

Today it should come as no surprise to people that many developing nations have

been experiencing increased gains in additional years of life for members of its

population in comparison to the 20th century.

       Associated with ageing are the high probability of increased dysfunctions

and the unavoidable degeneration of the body. This explains why it is germane to

analyze healthy life expectancy and not merely life expectancy. Healthy life

expectancy is defined as the number of years that an individual is expected to live

in ‘good’ health. Technological advancement is able to prolong life, but it is not

able to remove morbidity, or deterioration in the quality of lived years of the

individual. Thus, while life expectancy in the Caribbean is increasing and though
                                                                                    64


it is in keeping with the rest of the world, there is a simultaneous increase in

chronic diseases. This reality highlights the disparity between the quantity of

years lived and the quality of those lived years, due to sociopsychological

conditions- such as loneliness, bereavement, social support (or the lack of), low

self-esteem, low self-actualization and so on.

        In evaluating health or wellbeing, we must seek to examine more than just

the number of years that an individual is likely to survive, as we should be

concerned about the quality of those years. Even though life expectancy is an

indicator of health, the new focus is on healthy life expectancy. Based on the

Healthy People 2010, the new thrust is on increasing the quality of years of life.

In attempting to capture ‘quality of years lived’, in 1999 the WHO introduced an

approach that allows us to evaluate this, the ‘disability adjusted life expectancy’

(DALE). DALE does not only use length of years to indicate the status of health

and wellbeing of an individual or a nation, but it incorporates the number of years

lived without disabilities.

        DALE is a modification of the traditional ‘life expectancy’ approach in

assessing health. It uses the number of years lived as its principal component.

This is referred to as ‘full health’. In addition, the number of years of ill-health is

weighed, based on severity, as another component in the equation. This is then

subtracted from the expected overall life expectancy to give what is referred to as

years of hale life. Embedded in this approach is the adjustment of years lived in

‘ill-health’.
                                                                                65


       Having arrived at ‘healthy life expectancy’, the WHO has found that

poorer countries lost more from their ‘traditional life expectancy’ than developed

nations. The reasons put forward by the WHO are the plethora of dysfunctions

and the devastating effects of some tropical diseases like malaria that tend to

strike children and young adults. The institution found that these account for a 14

percent reduction in life expectancy from poorer countries and 9 percent from

more developed nations (WHO 2000b). This system is in keeping with a more

holistic approach to the measuring of health and wellbeing which this study seeks

to capture. By using the biopsychosocial model in the evaluation of the wellbeing

of aged Jamaicans, we will begin to understand factors that are likely to influence

the quality of lived years of the elderly, and not be satisfied with the increased

length of life of the populace. Looking at the life expectancy data for Jamaica,

the figure is 74.1 years for both sexes (Demographic Statistics 2006) but using

healthy life expectancy it is 65.1 years (WHO 2003).         This means that life

expectancy has been increasing at a faster rate than ‘healthy life expectancy’.

Therefore, Jamaicans are expected to spend some 9 years of their life in ‘poor

health’.

           Before any further meaningful discourse can take place herein, it is

imperative that we put forward some discussion on wellbeing, as this will allow

us to understand what we are examining, and the likely factors that may account

for the aforementioned changes.
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                                 Chapter Six

      AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                      WELLBEING OF THE ELDERLY

                                   PART TWO
Wellbeing

Wellbeing is used interchangeably with quality of life in different scholarships,

and some intelligentsias have gone on to distinguish between the two constructs.

We believe, however, that there is a clear distinction between the aforementioned

phenomena, and that the ‘quality’ of one’s life affects his/her experienced

wellbeing. Embedded in our argument here is that one’s quality of life is more

narrow that the construct of one’s wellbeing. To illustrate this point we will put

forward a conceptualization offered by Ries and Murphy, “a quality of life is a

state of living in which you are in balance or alignment” (1999, 5). Embodied in

Ries and Murphy’s perspective is the operational functionality of quality of life,

which means an alignment with all the elements of this life which will afford one

the option of having a particular state of life – ‘quality of life’. Thus, we concur

with other scholars that there is a distinction between quality of life and

wellbeing, but in this book we will not make these dissimilarities.      However,

what is wellbeing? And how has wellbeing been operationally defined since

before the 1950s?

       The discussion did not begin with what constituted wellbeing, or how it

should be measured. Instead, the discourse before the 1950s was on health, which

was later expanded to become wellbeing. Men have always been concerned about

the status of their health, and living longer has equally been a fascination for
                                                                                  67


people everywhere.      With this in mind, they have sought healers, ‘obeah

medicine’, ‘miracle spa and water’, and have spent millions of dollars on healthy

life style practices.

        At one point in the annals of human beings, people sought to be cured

from spirits, as they believed that many of the physiological ailments of the day

were due to spirits entering the human body.         With this perspective, man’s

position on health was from a perspective of spirit – manifested in physical

dispositions. But, during 1,800 to 700 BCE – the time of the Babylonians and

Assyrians - they started placing emphasis on diseases, as these were interpreted as

proxy for punishment by the gods. This general perspective was the same for the

Ancient Hebrews between 1,000 and 3000BCE. Thus, the cosmology of health

across different cultures was that of physical dysfunctions, this being the hallmark

of God’s disapproval of humans’ behaviour. It was not until the late 1940s that

there was a thrust afoot to widen this longstanding tradition.

        After WWII ended in September 1945, a number of institutions were

formed to address particular concerns regarding life. These include the IMF, the

World Bank, the United Nations, and the WHO. Each of these entities had a

distinct function and their portfolio was to effectively police certain issues within

the world. In this book, we will not seek to provide a discussion on the World

Bank, the IMF nor the United Nations. It is not our intent to provide information

on the functioning of the WHO or any of its related institutions, but the use of its

name is within the context of its contribution to the current space of health, health

research and health operations, in particular wellbeing.
                                                                                68


       It was during the writing of the WHO charter, at its first convention (1946)

that a caucus at the event was formed, which later developed the current

conceptualization of health (or wellbeing). This was ratified two years later.

What constitutes health from that institution’s perspective? The concept of health

according to the WHO is multifaceted. “Health is a state of complete physical,

mental and social wellbeing and not merely the absence of disease or infirmity”

(WHO 1947, 1948; Wang 2005, 153; Brannon and Feist 2007, 10). From the

WHO’s perspective, health status is an indicator of wellbeing (also see, Crisp

2005). Crisp, however, believes and puts forward the position that such a

conceptualization was elusive, and could not be measured with any level of

accuracy as it was ‘too’ wide. This position brings into the discourse not only a

doubt about the definition of the WHO, but introduces ‘subjective’ in an

operational definition of health (or wellbeing for that matter).

       Some scholars like Crisp predominantly believe that wellbeing should be

objectively measured, which premise is laid out by the positivists in the social

sciences, in an attempt to model the soft science (social science) like the natural

sciences – economic determinism.        With this said, health or wellbeing was

operationalized using disease, a tradition which began in Ancient Hebrew times.

Using diseases to evaluate health or wellbeing, which is referred to as the use of

the biomedical model – using physical dysfunction – was aimed at establishing a

correlation between health and longevity, and health and development. Thus,

scientists became involved in this cosmology and extensive research and finances

were placed in this field. This means that for a number of centuries, scientists
                                                                                 69


believed and explored biomedical cosmology.

       It was at the start of the 20th century that the biomedical model was being

rivalled by an alternative paradigm, the biopsychosocial model. This was during

an era when infectious diseases were replacing non-communicable diseases.

Thus, diseases that once ravished humanity, like the black plague, smallpox,

tuberculosis, polio, cholera, measles and dengue were replaced by hypertension,

heart disease, diabetes and cancer, to name of few which are now prevalent in

humanity.

       Life expectancy has substantially increased since the 1900s, and people

are living longer with some of the aforementioned ailments. Thus, the focus of

health cannot be centred on the mechanistic results of the exposure to specific

pathogens that are disease-causing organisms, since this limits the discourse to

physical conditions, which explains our focus on the panacea to health research.

The antithesis of disease, that is, functionality and a balanced state or quality of

life, are what many people commonly use in the imagining of health (or

wellbeing). Humans are multidimensional, and so using a biomedical model for

the study of health is unidirectional, since it explains disease, pathology and

dysfunctions, but does not deal with health or wellbeing. Nineteen years after the

first expanded definition of health offered by the WHO, Dubos speaks of “the

states of health and disease [as] the expressions of the success or failure

experienced by the organism in its efforts to respond adaptively to environmental

changes” (1965, xvii). This emphasizes the dominance of the antithesis of

diseases in the measurement of health.      In addition, it speaks to the world’s
                                                                                70


obsession with diseases, disability and mortality in the study of wellbeing, which

is a clear indication that health must be expanded beyond dysfunction and

functionality, and must reflect a balanced state. Currently, the discourse on

wellbeing (or health) has shifted from dysfunction, physiological growth and

functionality, to wellbeing.

       Before we begin with a comprehensive discourse of the expanded

definition of wellbeing, we will re-examine the definition put forward by the

WHO - “Health is a state of complete physical, mental and social wellbeing, and

not merely the absence of disease or infirmity”, because it is an embodiment of

physical, social and mental wellbeing, in particular ”completeness”. Some

intelligentsia have explained the fundamentals of the WHO definition, when they

opine that “anything less than complete wellbeing is not health” (Buetow and

Kerse 2001, 74). It follows that any study of wellbeing must be all-inclusive (also

see Pacione 2003, 19), as this will be more in keeping with a multidimensional

human. There are scholars who have argued that, although not stated in the

WHO’s definition of wellbeing, embedded in this construct is the psychological

state, since any ‘complete’ health includes the environment, with people

influencing the milieu and vice versa (also see Dunn 1961, 4-5).     This explains

why, when people are asked ‘what constitutes their health’ they are able to give a

‘good’ sense of their health, which is more comprehensive than the objective

definition. No objectification of wellbeing is able to combine people’s emotions,

beliefs, temperaments, behaviours, situations, experiences and biases, with the

subjective evaluation of events impacting on the individual’s existence (Kashdan
                                                                                  71


2004; Wheeler 1991). Furthermore, what objective valuation can serve as the

input for humour, happiness, joy, and contentment? There is no denial that the

aforementioned issues are directly related to wellbeing, and that they are primary

to an expression of wellbeing or health. Traditionally wellbeing was

conceptualized and operationalized primarily from an objective viewpoint, which

gave rise to the dominance of economic wellbeing. But any measurement of

wellbeing must embrace economic and non-economic conditions, as they both

impact on human existence (also see Sumner 2004). As intelligentsia we are

bastions of more than cosmology, since empiricism must override populist

positions, because science holds no bias. Within this context, we will examine the

various discourses on wellbeing, as this will provide a better understanding of this

book’s rationale for a composite approach to the measurement of wellbeing.

       Wellbeing for some scholars is a state of happiness – the status of life

satisfaction and positive feelings (see for example, Rojas 2005; Easterlin 2003;

Diener, Larson, Levine, and Emmons 1985; Diener 1984), satisfaction of

preferences, desires, health or prosperity of an individual (Diener and Suh 1997;

Jones 2001; Crips 2005; Whang 2005), or what psychologists refer to as positive

effects (Headey and Wooden 2004). Simply put, wellbeing is subjectively what is

‘good’ for each person (See for example, Crisp 2005). It is sometimes connected

with good health. Crisp offered an explanation for this, when he said that “When

discussing the notion of what makes life good for the individual living that life, it

is preferable to use the term ‘wellbeing’ instead of ‘happiness” (Crisp 2005),

which explains the rationale for this project utilizing the term wellbeing and not
                                                                                 72


good health.

       In order to put forward an understanding of what constitutes wellbeing or

illbeing, a system must be instituted that will allow us to coalesce a measurement

that will unearth peoples’ sense of overall quality of life from either economic-

welfarism (see Becker et al. 2004) or psychological theories (Diener, Suh, and

Oishi, 1997; Headey and Wooden 2004; Kashdan 2004; Diener 2000). This must

be done with the general construct of a complex man. Economists like Smith and

Kington, and Stutzer and Frey, as well as Engel, believe that man’s wellbeing is

not only influenced by his biological state but that it is always dependent on his

environment, economic and sociologic conditions. Some studies and academics

have sought to analyze this phenomenon in a subjective manner by way of general

personal happiness, self-rated wellbeing, positive moods and emotions, agony,

hopelessness, depression, and other psychosocial indicators (Arthaud-day et al.

2005; Diener et al. 1999; Skevington et al.1997; Diener 1984).

       An economist (Easterlin) studying happiness and income found an

association between the two phenomena (Easterlin 2001a, 2001b), (also see

Stutzer and Frey 2003; Di Telli, MacCulloch, and Oswald 2001). He began with

the statement that “the relationship between happiness and income is puzzling”

(Easterlin 2001a, 465), and found that people with higher incomes were happier

than those with lower incomes – he referred to it as a correlation between

subjective wellbeing and income (also see, Stutzer and Frey 2003, 8; Rojas 2005).

He did not cease at this juncture, but sought to justify this realty, when he said

that “those with higher incomes will be better able to fulfil their aspirations and,
                                                                                73


other things being equal, on an average, feel better off” (Easterlin 2001a, 472).

Another scholar admits that a statistical relationship exists between income and

happiness (subjective wellbeing), but he went on to refine this, explaining that

the association is dependent on an individual’s conceptual referent for happiness

(Rojas 2005) – “…and as income increases so do total desires; therefore,

happiness does not necessarily increase with income” (Rojas 2005, 2). Using

regression analysis (ordered-probit technique), he had some weak R-Squared

coefficients.   However, what emerged from the finding was that R-Squared

coefficients increased based on the conceptual referent a person held. Rojas found

that people with an outer orientation compared to those with an inner orientation

in their conceptual referent had a high propensity to be happier with income.

Thus, the effect of income on happiness is greater for people who want to seize

the moment from life’s offerings, compared to those who accept their current state

(happiness is based on internal conditions – e.g. virtues, tranquil life, utopia,

stoicism), and by extension are satisfied therein. Wellbeing, therefore, can be

explained outside of the welfare theory and/or purely on objectification- objective

utility (See for example, Kimball and Willis 2005; Stutzer and Frey 2003).

       Whereas Easterlin found a bivariate relationship between subjective

wellbeing and income (also see Rojas 2005), Stutzer and Frey revealed that the

association is a non-linear one. They concretized the position by offering an

explanation that “In the data set for Germany, for example, the simple correlation

is 0.11 based on 12, 979 observations” (Stutzer and Frey 2003, 9). Nevertheless,

from Stutzer and Frey’s findings, a position association does exist between
                                                                                 74


subjective wellbeing and income, despite differences of linearity or non-linearity.

       The issue of wellbeing is embodied in three theories – (1) Hedonism, (2)

Desire, and (3) Objective List.         Using ‘evaluative hedonism’, wellbeing

constitutes the greatest balance of pleasure over pain (See for example, Crisp

2005; Whang 2005, 154). With this theorizing, wellbeing is simply personal

pleasantness, which indicates that the more pleasantries an individual receives, the

better off he or she will be. The very construct of this methodology is the primary

reason for a criticism of its approach (i.e. ‘experience machine’), which gave rise

to other theories. Crisp (2005), using the work of Thomas Carlyle described the

hedonistic structure of utilitarianism as the ‘philosophy of swine’, because this

concept assumes that all pleasure is on par. He summarized this adequately by

saying “… whether they [are] the lowest animal pleasures of sex or the highest of

aesthetic appreciation” (Crisp 2005).

       The desire approach, on the other hand, is on a continuum of experienced

desires. This is popularized by welfare economics, as economists see wellbeing

as constituting the satisfaction of preference or desires (Crisp 2005, 7; Whang

2005, 154), which makes for the ranking of preferences, and assessment by way

of money. People are made better off if their current desires are fulfilled. Despite

this theory’s strengths, it has a fundamental shortcoming, the issue of addiction.

This is borne out by the possible addictive nature of consuming ‘hard drugs’

because of the summative pleasure it gives to the recipient.

       Objective list theory: This approach in measuring wellbeing lists items

not merely because of pleasurable experiences or ‘desire-satisfaction,’ but that
                                                                               75


every good thing should be included, such as knowledge and/or friendship. It is a

concept influenced by Aristotle, and “developed by Thomas Hurka (1993) as

perfectionism” (Crisp 2005).     According to this approach, the constituent of

wellbeing is an environment of perfecting human nature.        What goes on an

‘objective list’ is based on a person’s reflective judgement or intuition.      A

criticism of this technique is elitism (Crisp 2005), since an assumption of this

approach is that certain things are good for people. Crisp (2005) provided an

excellent rationale for this limitation, when he said that “…even if those people

will not enjoy them, and do not even want them”.

       In the work of Arthaud-day et al., applying structural modelling,

subjective wellbeing was found to constitute “(1) cognitive evaluations of one's

life (i.e. life satisfaction or happiness); (2) positive affect; and (3) negative

affect.” Subjective wellbeing, therefore, is the individual’s own viewpoint. If an

individual feels his/her life is going well, then we need to accept this as the

person’s reality. One of the drawbacks to this measurement is that it is not

summative, and it lacks generalizability.

       Studies have shown that subjective wellbeing can be measured on a

community level (Bobbit et al.2005; Lau 2005; Boelhouwer and Stoop 1999) or

on a household level (Lau 2005; Diener 1984), whereas other experts have sought

to use empiricism (biomedical indicators - absence of disease symptoms, life

expectancy; and an economic component - Gross Domestic Product per capita;

welfarism - utility function).

       Powell (1997) in a paper entitled ‘Measures of quality of life and
                                                                                76


subjective wellbeing’ argued that psychological wellbeing is a component of

quality of life. He believed that this measurement, in particular for the older,

must include the Life Satisfaction Index, as this approach constitutes a number of

items based on “cognitively based attitudes toward life in general and more

emotion-based     judgment”(Powell     1997).     Powell    addressed   this   two-

dimensionally, where those means are relatively constant over time, while in

seeking to unearth changes in the short run, ‘for example an intervention’,

procedures that mirror changed states may be preferable. This can be assessed by

way of a twenty-item Positive and Negative Affect Schedule or a ten-item

Philadelphia Geriatric Centre Positive Affect and Negative Affect Scale (Powell

1997).

         In a reading entitled ‘Objective measures of wellbeing and the cooperation

production problem’, Gaspart (1998) provided arguments that support the

rationale behind the objectification of wellbeing. His premise for the objective

quality of life is embedded within the difficulty as it relates to consistency of

measurement, when subjectivity is the construct of operationalization.         This

approach takes precedence because an objective measurement of concept is of

exactness as non-objectification; therefore, the former receives priority over any

subjective preferences. He claimed that for wellbeing to be comparable across

individuals, population and communities, there is a need for empiricism.

         Gaspart discussed a number of economic theories (Equal Income

Walrasian equilibria, objective egalitarianism, Pareto efficiency, Welfarism),

which saw the paper expounding on a number of mathematical theorems in order
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to quantify quality of life. Such a stance assumes that humans are predictable and

rational which means that we are objectively able to plan our future actions. The

very axioms cited by Gaspart emphasized a particular set of assumptions that he

used for finalizing a measurement for the wellbeing of man, who is a complex

social animal. The researcher points to a sentence that was written by Gaspart

that speaks to the difficulty of objective quality of life; he wrote, “So its

objectivism is already contaminated by post-welfarism, opening the door to a

mixed approach, in which preferences matter as well as objective wellbeing”

(Gaspart 1998).    Another group of scholars emphasized the importance of

measuring wellbeing outside of welfarism and/or pure objectification, when they

said that “Although GDP per capita is usually used as a proxy for the quality of

life in different countries, material gain is obviously only one of many aspects of

life that enhance economic wellbeing” (Becker et al. 2004, 1), and that wellbeing

depends on both the quality and the quantity of life lived by the individual (also

see Easterlin 2001). This is affirmed in a study carried out by Lima and Nova

(2006), which found that happiness, general life satisfaction, social acceptance

and actualizations are all directly related to GDP per capita for a geographic

location (see Lima and Nova 2006, 9). Even though in Europe these were found

not to be causal, income provides some predictability of subjective wellbeing,

more so in poor countries than in wealthy nations. (See Lima and Nova 2006, 11)

       It should be understood that GDP per capita speaks of the market

economic resources which are produced domestically within a particular

geographic space. So increased production in goods and/or services may generate
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an excess which can then be exported, and vital products (such as vaccinations,

sanitary products, vitamins, iron and other commodities) can be purchased, which

can improve the standard of living and quality of life of the same people over the

previous period. One scholar (Caldwell 1999) has shown that life expectancies are

usually higher in countries with high GDP per capita, which means that income is

able to purchase better quality products, which indirectly affect the number of

years lived by people. This realty could explain why in economic recession, war

and violence, when economic growth is lower (or even non-existent) there is a

lower life expectancy.      Some of the reasons for these justifications are

government’s inability to provide for an extensive population in the form of

nutritional care, public health and health-care services. Good health is, therefore,

linked to economic growth, which further justifies why economists use GDP per

capita as an objective valuation of standard of living, and why income should

definitely be a component in the analysis of health status. There is another twist to

this discourse, as a country’s GDP per capita may be low, but life expectancy high

because health care is free for the population. Despite this fact, material living

standards undoubtedly affect the health status and wellbeing of a people, as well

as the level of females’ educational attainment.

       Ringen (1995) in a paper entitled ‘Wellbeing, measurement, and

Preferences’ argued that non-welfarist approaches to measuring wellbeing are

possible despite their subjectivity. The direct approach for wellbeing computation

through the utility function, according to Ringen, is not a better quantification as

against the indirect method (i.e. using social indicators). The stance taken was
                                                                                79


purely from the vantage point that utility is a function ‘not of goods and

preferences’ but of products and ‘taste’. The constitution of wellbeing is based on

choices.   Choices are a function of individual assets and options. With this

premise, Ringen put forward arguments which show that people’s choices are

sometimes ‘irrational’, which is the make for the departure from empiricism.

       Wellbeing can be computed from either the direct (i.e. consumption

expenditure) or the indirect (i.e. disposable income) approach (Ringen 1995, 8).

The former is calculated using consumption expenditure, whereas the latter uses

disposable income.    Ringen noted that in order to use income as a proxy for

wellbeing, we must assume that (1) income is the only resource, and (2) all

persons operate in identical market places. On the other hand, the direct approach

has two key assumptions. These are (1) what we can buy is what we can consume

and (2) what we can consume is an expression of wellbeing. From Ringen’s

monograph, the assumptions are limitations.

       In presenting potent arguments in favour of non-empiricism in the

computation of wellbeing, Ringen highlighted a number of drawbacks to

welfarism. According to Ringen:

       Utility is not a particularly good criterion for wellbeing since it is a
       function not only of circumstances and preferences, but also of
       expectation. In the measurement of wellbeing, respect for personal
       preferences is best sought in non-welfarist approaches that have the
       quality of preference neutrality; …As soon as preferences are brought into
       it, the concept of wellbeing cannot but be subjective. (Ringen 1995, 11)


              The difficulties in using empiricism to quantify wellbeing have not

only been put forward by Ringen, as O’Donnell and Tait (2003) were equally
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forthright in arguing that there were challenges in measuring the quality of life

quantitatively. O’Donnell and Tait believed that health is a primary indicator of

wellbeing. Hence, self-rated health status is a highly reliable proxy of health

which “successfully crosses cultural lines” (O’Donnell and Tait 2003, 20). They

argued that self-reported health status can be used, as they found that all the

respondents of chronic diseases indicated that their health was very poor. To

capture the state of the quality of life of humans, we are continuously and

increasingly seeking to ascertain more advanced methods that will allow us to

encapsulate a quantification of wellbeing that is multidimensional and

multifaceted (Pacione, 2003). Therefore, an operational definition of wellbeing

that sees the phenomenon in a single dimension such as physical health (Steward

and King 1994), medical perspective (Farquhar 1995), or material (Lipsey 1999),

would have omitted indicators such as crime, education, leisure facilities, housing,

social exclusion and the environment (Pacione 2003; Campbell et al 1976) as well

as subjective indicators which cannot be an acceptable holistic measurement of

this construct. This suggests that wellbeing is not simply a single space; and so,

the traditional biomedical conceptual definitions of wellbeing exclude many

individual satisfactions, and in the process reduce the tenets of a superior

coverage of quality of life.

       One writer noted that the environment positively influenced the quality of

people’s lives (Pacione 2003, 20; Bourne, 2007; Bourne 2008a, 2008c); in order

to establish the validity and reliability of wellbeing, empirical data must include

issues relating to the environment. The quality of the environment is a condition
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utilized in explaining elements of people’s quality of life. Air and water quality,

through industrial fumes, toxic waste, gases and other pollutants, affect

environmental quality. This is directly related to the maintenance, or lack thereof,

of societal and personal wellbeing (Pacione 2003).

       Studies have conclusively shown that environmental issues such as

industrial fumes and gases, poor solid waste management, mosquito infestation

and poor housing are likely to result in physiological conditions like respiratory

tract infections (for example lung infection), and asthma.

       According to Langlois and Anderson (2002), approximately 30 years ago,

a seminal study conducted by Smith (1973, 2) “proposed that wellbeing be used to

refer to conditions that apply to a population generally, while quality of life

should be limited to individuals’ subjective assessments of their lives …” They

argued that the distinction between the two variables has been lost with time.

From Langlois and Anderson’s monograph, during the 1960s and 1970s,

wellbeing was approached from a quantitative assessment by the use of GDP or

GNP (also See, Becker, Philipson and Soares 2004), and unemployment rates; this

they refer to as a “rigid approach to the [enquiry of the subject matter] subject.”

According to Langlois and Anderson (2002), the positivism approach to the

methodology of wellbeing was objectification, an assessment that was highly

favoured by Andrews and Withley 1976, and Campbell et al., 1976.

       In measuring quality of life, some writers have thought it fitting to use

Gross Domestic Product per capita (i.e. GDP per capita) to which they refer as

standard of living (Lipsey 1999; Summers and Heston 1995; Hanson 1986).
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According to Summers and Heston (1995), “The index most commonly used until

now to compare countries' material wellbeing is their GDP      POP' .”   The United

Nations Development Programme has expanded on the material wellbeing

definition put forward primarily by economists, and has included life expectancy,

educational attainment (Human Development Reports, 2005, p. 341) and other

social indicators (Diener 1984; Diener and Suh 1997). This operational definition

of wellbeing has become increasingly popular in the last twenty-five years, but

given the expanded definition of health as cited by the WHO, wellbeing must be

measured in a more comprehensive manner than using material wellbeing as seen

by economists.

       Despite the fact that quality of life extends beyond the number of years of

schooling and material wellbeing, in general terms wellbeing is substantially

construed as an economic phenomenon. Embedded within this construct of a

measurement is the emphasis on economic resources, and we have already

established that man’s wellbeing is multifaceted. Hence, any definition of the

quality of life of people cannot simply analyze spending, the creation of goods

and/or services that are economically exchangeable, or the number of years of

schooling and life expectancy, but must include the psychosocial conditions of the

people within their natural environment.

       GDP is the coalesced sum of all the economic resources of people in a

certain topographical area, so this does not capture the psychosocial state of the

individual in attaining the valued GDP. By this approach, we may arrive at a

value that is higher than in previous periods, making it seem as though people are
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doing very well. However, with this increase in GDP, the single component is

insufficient to determine wellbeing, as the increase in GDP may be by (1) more

working hours, (2) higher rates of pollution and environmental conditions, (3)

psychological fatigue, (4) social exclusion, (5) human ‘burn out’, (6) reduction in

freedom, (7) unhappiness, (8) chronic and acute diseases, and so forth. Summers

and Heston (1995) note that “However, GDP POP is an inadequate measure of

countries' immediate material wellbeing, even apart from the general practical and

conceptual problems of measuring countries' national outputs.” Generally, from

that perspective the measurement of quality of life is therefore highly economic,

and excludes the psychosocial factors, and whether the quality of life extends

beyond monetary objectification.

       In developing countries, Camfield (2003), in looking at wellbeing from a

subjective vantage point, notes that Diener (1984) argues that subjective

wellbeing constitutes the existence of positive emotions and the absence of

negative ones, within a space of general satisfaction with life. According to

Camfield, Cummins’ (1997) perspective subsumed ‘subjective and objective

measures of material wellbeing’ along with the absence of illnesses, efficiency,

social closeness, security, place in community and emotional wellbeing, which

implies that “life’s satisfaction” comprehensively envelopes subjective wellbeing.

       Diener (2000) in an article entitled ‘Subjective Wellbeing: The Science of

Happiness and a Proposal for a National Index’ theorizes that the objectification

of wellbeing is embodied within satisfaction of life. His points to a construct of

wellbeing called happiness.
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       He cited that:

       People's moods and emotions reflect on-line reactions to events happening
       to them. Each individual also makes broader judgments about his or her
       life as a whole, as well as about domains such as marriage and work.
       Thus, there are a number of separable components of SWB [subjective
       wellbeing]: life satisfaction (global judgments of one's life), satisfaction
       with important domains (e.g., work satisfaction), positive affect
       (experiencing many pleasant emotions and moods), and low levels of
       negative affect (experiencing few unpleasant emotions and moods). In the
       early research on SWB, researchers studying the facets of happiness
       usually relied on only a single self-report item to measure each construct
       (Diener, 2000, 34).


       Diener’s theorizing on wellbeing encapsulates more than the marginalized

stance of other academics and researchers, who enlightened the discourse with

economic, psychosocial, or subjective indicators. He shows that quality of life is

multifaceted, and coalescing economic, social, psychological and subjective

indicators is more far-reaching in ultimately measuring wellbeing. This work

shows a construct that can be used to operationalize a more multidimensional

variable, wellbeing, which widens the tenet of previous operational definition on

the subject. From the theorizing of various writers, it is clear that wellbeing is

multidimensional, multidisciplinary and multispatial. Some writers emphasize the

environmental components of subject matter (Lui 1976; Pacione 1984; Smith

1973), from the psychosocial aspect (Clarke and Ryff 2000) and from a social

capital vantage point (Glaeser 2001; Putnam 1995; Woolcock 2001).

        Smith and Kington (1997), using H t = f (H t-1 , P m G o , Bt , MC t ED, Ā t , ) to

conceptualize a theoretical framework for “stock of health,” noted that health in

period t, Ht, is the result of health preceding this period (H t-1) , medical care

(MC t) , good personal health (G o) , the price of medical care (P m ), and bad choices
                                                                                 85


(Bt) , a vector of family education (ED) and all sources of household income (Ā t ).

Embedded in this function is the wellbeing that the individual enjoys (or does not

enjoy) (see Smith and Kington 1997, 159-160).

       In seeking to operationalize wellbeing, the United Nations Development

Programme (UNDP) in the Human Development Reports (1997, 2000)

conceptualized human development as a “process of widening people’s choice as

well as the level of achieved wellbeing”. Embedded within this definition is the

emphasis on materialism in interpreting quality of life. From the UNDP’s Human

Development (1993), the human development index (HDI) “…is a normative

measure of a desirable standard of living or a measure of the level of living”,

which speaks to the subjectivity of this valuation, irrespective of the inclusion of

welfarism (i.e. gross domestic product (GDP) per capita). The HDI constitutes

adjusted educational achievement (E= a 1 * literacy + a 2 * years of schooling,

where a1, = 2/3 and a2 = 1/3), life expectancy (demographic modelling) and
                                     1-e
income (W (9y) = 1/ (1 - e) * y        ). The function W(y) denotes “utility or

wellbeing derived from income”.       This income component of the HDI is a

national average (i.e. GDP per capita, which is then adjusted for income

distribution (W*(y) = W(y) {1 - G}), where G = Gini coefficient). In wanting to

disaggregate the HDI within a country, the UNDP (1993) noted that data are not

available for many countries, which limits the possibility.

       An economist writing on ‘objective wellbeing’ summarized the matter

simply by stating that “…one can adopt a mixed approach, in which the

satisfaction of subjective preferences is taken as valuable too” (Gaspart 1998,
                                                                                   86


111) (also see Cummin1997a, 2001, 2005), which is the premise to which this

paper will adhere in keeping with this multidimensional construct, wellbeing.

Wellbeing, therefore, for this paper, will be the overall health status of people,

which includes access to and control over material resources, environmental and

psychosocial conditions, and per capita consumption.

       Both demographers and medical scientists primarily rely on advanced

multivariate statistical techniques to establish the causality of particular variables

on health; and before predictability of the event is forecasted, variations in

wellbeing (or health) must be explained by each variable.
                                                                              87


                               Chapter Seven

     AN OVERVIEW OF THE CONCEPTUAL PERSPECTIVES ON

                       WELLBEING OF THE ELDERLY

                                 PART THREE

         Education, Income, Occupation and Employment

         Studies have analyzed and established a statistical relationship between

socioeconomic status (SES) and health conditions. Those inquires have found that

a strong association exists between SES, income (UNDP 2006; Roos et al. 2004;

Case 2001: Kawachi et at 1997; Smith and Kington 1997a, 1997b), occupation

(Hemingway, Nicholson, and Marriott 1997; McQueen and Seigrist 1982), and

education (Koo, Rie and Park 2004; Ross and Mirowsky 1999; Preston and Elo

1995).

         A group of demographers (Ross and Mirowsky 1999) sought to refine the

association between health status and education, by using ‘The Quantity Model’.

It was established that the number of years of schooling (i.e. The Quantity

Theory) was a crucial predictor of the health status of an individual (Ross and

Mirowsky 1999, 449 and 452).        This, they argued, is attained by access to

information, improved work and economic conditions, and an understanding of

the requirements for better health care and wellbeing (Ross and Mirowsky 1999,

446). Freedman and Martin (1999), using data from the 1984 and 1993 panels on

Survey of Income and Program Participation, narrowed their study more so than

Ross and Mirowsky by looking at the relationship between educational attainment

and the physical function of aged people. They found that there was an

association between the educational level and the physical functioning of people
                                                                                   88


65 years and over.

       Koo, Rie and Park (2004), using multivariate regression, went further than

Ross and Mirowsky’s work of mere association to that of causation. They

concluded that education was a predictor of increased subjective wellbeing (t

[2523] = 7.83, ρ value ≤ 0.001]. The sample size was 2529 randomly selected

adults residing in Seoul and Chunchum, with 956 males and 1573 females. The

ages of those who responded to the survey instrument (questionnaire) were from

43 to 102 years old. Thus, the findings are generalizable because of the sample

design. Roos et al.’s study (Roos et al. 2004) contradicts the significant

relationship between education and health status. They drew their sample from

two Canadian Provinces. The findings revealed that a marginal association exists

between education and mortality. Another survey using data from the Survey of

Income and Program Participation – data collected by the U.S. Census Bureau

1991, finds that trends in educational attainment are associated with particular

functioning such as seeing, lifting and carrying, climbing stairs and walking ¼

mile (Freeman and Martin 1999).

       Freeman and Martin’s work did not merely reflect an associative

relationship between educational attainment and health – defined as physical

functioning – but showed that it was a predictive one (see also Bourne 2008a).

Using logistic regression, the coefficient revealed that having more schooling is

predictive of functioning. The researchers found that “this consistently suggests

that having less than a high school education is associated with approximately

twice the odds [e.g. exp. (0.695) = 2.0] of having functional limitation in late life”
                                                                               89


which was compared to someone who has attained more than secondary level

education (Freeman and Martin 1999, 466); Ross and Mirowsky, on the other

hand, further refined education and its association with health status.

       As if education’s influence on health status was insufficient, Ross and

Mirowsky (1999) refined the discourse when they put forward a theorizing that

years of schooling influence health through choices, knowledge, and capacity of

the recipients. The researchers - using data from a 1995 survey on Aging, Status,

and the Sense of Control, representative of U.S households (some 2,593

respondents ages ranging from 18 to 95 years), found that it is the years of

schooling that expand human capital – skills, abilities and resources.

       According to Ross and Mirowsky (1999), education in and of itself opens

and develops particular skills and the knowledge base of individuals, which is the

catalyst for inquiry, reasoning and lifestyle changes. It is this empowerment

which shapes the health and wellbeing of the educated populace. From Ross and

Mirowsky’s work, it is not merely education that improves DALE lifestyle but

rather the number of years of schooling.

       They (Ross and Mirowsky) found that years of schooling are a predictor of

better health status (also see Headey and Wooden 2003, 16). From their literature

review, using quantity modelling, they argued that a clear predictive association

exists between years of schooling and health (Ross and Mirowsky 1999, 445),

which was corroborated by Lauderdale (2001).           This was supported by the

argument put forward by Ross and Morowsky that in comparison with those with

little schooling, the well educated are more likely to exercise and drink in
                                                                                  90


moderation, as opposed to abstaining or drinking healthily (Ross and Mirowsky

1999, 446).

       Within our society, on an average, people 65 years and over tend to have

less education compared to those who are between 25 and 60 years (Palmore

1981, 150).    Palmore noted this in a study that was done by Harris (1975) in

which “63 percent of those 65 and over never graduated from high school,

compared with only 26 percent of those 18 to 64. As a matter of fact, some aged

acquire more education as they grow older; 5 percent of those aged 55-64 and 2

percent of those 65 and over were enrolled in courses in 1974” (Palmore 1981,

15). He compared the number of years of schooling of young people and aged

persons, and found that younger cohorts were more educated than their older adult

counterparts. But as these educated people move into the senior category, the

mean educational attainment of the aged populace will substantially improve over

previous years.

       Other scholars (Moore et al. 1997) agree that educational attainment

influences people’s health status. The rationale given for this position is that

education directly improves knowledge and access to information. Studies have

shown that people with low incomes or who have significantly shorter life

expectancies are less educated. According to Moore et al. (1997), Crimmins et al.

(1990) showed that life expectancy at age 65 for white women with more than 13

years of schooling is 19.8 years, compared with 18.4 for those with less than 9

years of schooling (p.134). A study by Prause et al. (2005) revealed a contrasting

finding to other studies presented earlier; they found that education does not affect
                                                                                91


SWB. This was refuted by a majority of the literature presented by the experts

themselves (Prause et al. 2005, 364). One of the advantages of more schooling is

its linkage to better jobs, which is a factor in providing higher income and the

tendency for one to improve his/her standard of living.

       In a series of papers presented to the Child Conference in Jamaica in 2008,

scholars found that educational attainments of youth (ages 15 to 25 years) did not

determine self-reported wellbeing, but the educational level of parents strongly

correlated with their children’s quality of life (Bourne and Cornwall, 2008;

Bourne, 2008; Bourne and Beckford 2008). An interesting finding which emerged

from the paper highlighted the fact that youth whose parents had tertiary level

education had greater subjective wellbeing, and that when the female

(parent/guardian) had university education the youth had greater wellbeing.

Embedded in this is that the number of years of schooling does make a difference,

but also that the level which the person reaches will not only expand his/her

personal horizon, but that of his/her child or household, suggesting that education

plays both a social and an economic role in the community. This is in keeping

with   the   aforementioned    scholarships   on   education   and    health,   and

multidimensional tenets on personal, community and society development.

        Based on the caption another germane factor is income and its association

with quality of life. Eldemire in an article captioned The Elderly- A Jamaican

Perspective noted that income and employment, among others issues, were

‘common problems’ affecting the quality of life of the elderly (Eldemire 1987a).

These are simply determinants of wellbeing of the Jamaican elderly.
                                                                                   92


        In a survey conducted by Diener, Sandvik, Seidlitz and Diener (1993),

Diener et al. state that the correlation between income and subjective wellbeing

was small in most countries. Benzeval, Judge and Shouls’s (2001) study concurs

with Diener et al.’s work, in that income is associated with health status.

Benzeval et al. went further, as their research revealed that a strong negative

correlation exists between increasing income and poor health. Furthermore, it

was found that people from the bottom 25 percent of the income distribution self-

reported poorer subjective health by 2.4 times more than people in the fifth

quintile (Benzal and Judge 2001). One renowned scholar, Amartya Sen, argues

against the use of income and durable goods as a measure of wellbeing (Sen

1998). His rationale is tied to the difficulty of evaluating people’s intrinsic values

with the use of money and commodities. People’s value systems play a pivotal

role in how they perceive life, and by extension how they view their wellbeing.

Wellbeing is not simply a function of income, although income is able to afford

someone a ‘good life’. The UNDP’s (UNDP 2006) human development index

(HDI) is an indicator of wellbeing, and it is used for comparisons across

countries. The HDI uses national income (GDP per capita), health status and

education as causal predictors of wellbeing.

       The HDI assumes that increases in economic growth will directly result in

an improvement in health status (Easterlin 2004) and by extension the wellbeing

of peoples within a particular geographic space. If the construct between income

and health status holds true, then should poor countries not have a life expectancy

which is equally comparable with the developed countries? But this is not
                                                                                93


affirmative, as countries like Jamaica and Barbados have life expectancies that are

in excess of 70 years for both sexes, which is keeping with the values for many

societies in first world countries. Even though this income theory of explaining

health may seem applicable, health is not necessarily a function of income, but

rather a set of mechanisms that money can purchase, that can afford a certain

health – and not one single factor (see for example Case 2001), which includes

education, material possessions, durable goods, technology and so on. A group of

scholars, instead of using income, have used the possession of durable goods as

an indicator of wealth and income, and this has proved to be significantly

associated with health (Filmer and Pritchett 2001).

       In another study of 1440 elderly (72 and 77 year olds) from a Danish

survey in 1997, the findings revealed that seniors who were in the low-income

categorization had lesser physiological functioning and poorer psychological

wellbeing (Arendt 2005). Arendt, using ordered logistic models, finds that the

income effects are predictive.

       Marriott, Professor and Head of the Department of Epidemiology and

Public Health, and Director of the International Centre for Health and Society at

the University College of London, asked the question “Does money matter for

health?” He seeks to establish his theorizing through a conceptual framework of

using life expectancy and gross national product per capita of a country, by

examining the 1993 World Bank report based on data available from more than

100 countries. In support of his theorizing, he uses Angus Deaton’s theoretical

framework, which established that there is a nonlinear increase in the probability
                                                                                94


of dying with declining income. Marriott, in putting forward a conclusion on the

relationship between income and health, finds that when education is included in

the model with income, mortality is remarkably reduced (Marriott 2002, 40).


       From research findings, unhealthy living and poor working conditions of

people can be explained through levels of income and typology of occupation

(Lynch 2003). Lynch’s work uses data collected by the National Health Interview

Survey (NHIS) and National Health and Nutrition Examination Survey (NHNES).

The NHIS and NHNES were cross-sectional studies; NHIS sample size was

45,000 households (i.e. 878,317 persons between 1972 and 1993) compared to

6,373 used by NHNES. His findings reveal that there is a strong negative effect

in the probability of individuals who reported fair or poor health and their

educational level.    Lynch (2003, 309) argues that the relationship between

education and health is the most powerful association in social science studies,

and that it is still the most complex to clarify. Educational achievement is an

indicator of occupation types, and so in an investigation of the former on health

status, the latter must be taken into consideration.

       Occupation is a source of social status for many people, and this is typical

for aged people. In Jamaica, occupations such as Medicine, Academics, Law,

Managerial positions and Engineering are all professions of high calibre which

are associated with social clout. Owing to the fact that retirement diminishes this

status, the accompanying psychological losses will influence the wellbeing of

aged people, as they are no longer seen as productive beings because of old

adulthood (Palmore 1981, 16). A group of researchers, in analyzing occupation,
                                                                                95


reported that this variable is intricate, and its valuation is dependent on one’s

theoretical viewpoint on the importance of different aspects of one’s employment

existence (Adler and Newman 2002, 64). The researchers [Adler and Newman]

theorized that employed people are of a higher health status than their

unemployed counterparts. They added that aspects of this relationship are a

function of the ‘health worker’ effect, which suggests that there is evidence that

unemployment and the length of unemployment affect health status. In putting

forward their perspective in a vivid manner, Adler and Newman used scholarly

work to emphasize how the threat of unemployment and job insecurity can

influence the health status of people. They wrote “Ralph Catalano and Seth

Serxner found elevated rates of low birth weight in geographic locales threatened

with high rates of unemployment”.

       It is simplistic to determine from a single study that a sole variable is

responsible for a change in an event without a controlled experiment.          The

lowered birth weight of infants born to persons who were threatened with

unemployment or job insecurity may be incidental to inadequate pre-maternal

care, frustration with present management practices, insufficient nutrition,

environmental factors and current poverty, and while those stressors may result in

changes in blood pressure, they may also have a direct causal effect on the infant.

Thus, retirement is construed by some people as that avenue of refuge from some

of the psychosocial dynamics at work with which they were uncomfortable, but

which they had to tolerate while within the job space.

       Marcia Angel in Adler and Newman (2002) posited that income,
                                                                                   96


education and occupation are complex determinants concerning their influences

on health. They offered the perspective that they are indirect determinants which

are proxies for other predictors. A study known as the SABE project (i.e. Health,

Wellbeing, and Ageing in Latin America and the Caribbean), which was

conducted in Barbados between December 1999 and June 2000, reveals that the

higher one’s level of education, the more likely it is for that individual to self-

report better heath status (Hambleton et al. 2005). This had a minimum sample

size of 1,500 respondents from seven cities in Latin America and the Caribbean,

including Bridgetown, Barbados. The respondents chosen are people who in

1999 were 60 years or older.           In respect of occupation typologies, the

professionals showed a higher degree of self-reported better health status than the

non-professionals and the semi-professionals (the odds ratios are 1.00 for non-

professionals, 1.08 for semi-professionals and 1.55 for professionals). Embedded

within this finding is the fact that professionals are 55 percent more likely to self-

report better health status than non-professionals, and 47 percent better health

status than semi-professionals.

         When socioeconomic status is assessed by income, education, or

occupation concerning health status, education is the most “basic socioeconomic

component since it shapes future occupation opportunities and earning potential”

(Adler and Newman 2002, 60). Winkleby and colleagues in Adler and Newman’s

study (2002) revealed that education was the only socioeconomic variable to

remain statistically significant out of education, income and occupation in relation

to their influence on cardiovascular disease (Adler and Newman 2002, 60).
                                                                                     97


        Poverty and Financial Status

        There is an argument that poverty is higher among the aged populace than

young adults simply because elderly people are substantially outside of the labour

force, as the aged are likely to be the ones who are placed on retirement, which is

the reason for them receiving less income (Palmore 1981, 16). This was recorded

in a Cornel Study of Retirement that showed that retirees’ income declined to

56% of their pre-retirement income, which is a significant reduction in their

purchasing power, and by extension, their standard of living (Palmore 1981, 16).

He argued that tax advantages, housing subsidies, Medicare and income tax

exemptions offset this. This enables the aged to afford to maintain a particular

accustomed standard of living; but the social setting of the aged poor was not

accounted for in Palmore’s theorizing, and the widespread human suffering that

this has on the less educated aged poor. Eldemire (1994) alluded to this finding,

when she suggested that loss of financial resources may result in a change in

people’s lifestyle practices From Eldemire’s monograph, it can be construed that

senior citizens (i.e. elderly) are highly likely to see a change in their lifestyle as a

result of changes in their financial base. Warnes (1982, 4) encapsulated the

importance of resources to the quality of life of the elderly in the statement that

“…much if not more related to their social isolation or integration and to their

physical capacities as to their command of material resources”.

        In a paper entitled Poverty and Health, Murray (2006) argued that there is

a clear interrelation between poverty and health.           She noted that financial

inadequacy prevents an individual from accessing:           food and good nutrition,
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potable water, proper sanitation, medical care, preventative care, adequate

housing, knowledge of health practices and attendance at particular educational

institutions, among other things. The issue of resource insufficiency affects the

ability and capacity of the poor to access the quality of goods and services

comparable to the rich, who are better able to add value to wellbeing. This is

succinctly put forward by Murray in her monograph:

       Poverty also leads to increased dangers to health: working environments
       of poorer people often hold more environmental risks for illness and
       disability (Murray 2006, 923)

       The issue of poverty and health, according to Murray, is interlinked with

money. It is because of financial inadequacies that some people will not be able

to transform a risky physical environment into a safe place for people, in

particular the elderly. Studies exist that clearly show a relationship between

persistent, extended poverty and health, and even mortality (Lynch et al. 1997;

Menchik 1993; Zick and Ken 1991). If poverty is indisputably a primary cause of

malnutrition (Muller and Krawinkel 2005), then access to money plays a pivotal

role in the wellbeing of individuals. In order to grasp the severity of the issue of

money, we need to be brought into the recognition of poverty and health status.

According to Bloom and Canning (2003), ‘ill-health’ significantly affects poor

people. This further goes to explain the higher probability (5 times) of mortality

of the poor than the rich (World Health Organization 1999).

       Actuarial studies carried out in Canada have revealed that effective

planning is needed concerning social programmes for the elderly, otherwise

pension plans will not be able to meet their intended objective (Moore, et al.
                                                                               99


1997, 1). This discourse has taken on a new dimension, which is ‘who should

endow the cost of health care for the elderly, private or public institutions’?

Moore et al. (1997) added that the Canadian population has not only changed in

demographic composition concerning the elderly, but there are increasingly a

greater percentage of people 80 years of age and over (p.3).

       Psychological – Positive and Negative conditions

       In the pursuit of a precise operational definition of subjective wellbeing,

some scholars (see for example, Kashdan 2004; Diener 2000; Lyubomirsky 2001)

categorized the phenomenon into positive and negative psychological conditions.

They believed that happiness is as a result of a number of positive psychological

factors (also see Kim-Prieto, Diener, Tamir, Scollon, and Diener 2005; Easterlin

2003). A few scholars (see for example Liang 1984, 1985; Diener and Emmons

1984) have sought to make a distinction between the positive and negative

psychological conditions.

       In seeking to unearth ‘why some people are happier’, Lyubomirsky (2001)

approached the study from the perspective of positive psychology. She noted

that, to comprehend the disparity in self-reported happiness between individuals,

“one must understand the cognitive and motivational process that serves to

maintain, and even enhance happiness and transient mood’ (Lyubomirsky 2001,

239). Using positive psychology, Lyubomirsky identified comfortable income,

robust health, supportive marriage, and lack of tragedy or trauma in the lives of

people, as factors that distinguish happy from unhappy people, which was

discovered in an earlier study by Diener, Suh, Lucas and Smith (1999). In an
                                                                               100


even earlier study by Diener, Horwitz and Emmon (1985), they were able to add

value to the discourse of income and subjective wellbeing. They found that the

wealthy-affluent (those earning in excess of US 10-million annually) who self-

reported wellbeing (personal happiness of the wealthy affluent) were marginally

more than that of the lower wealthy.

       People’s cognitive responses to ordinary and extraordinary situational

events in life are associated with a different typology of wellbeing (Lyubomirsky,

King, and Diener 2005; Lyubomirsky 2001). It is found that happier people are

more optimistic and as such conceptualize life’s experiences in a positive manner.

Self-fulfilment and self-esteem will transform the individual into a happier person

who, in the long run, views life’s challenges and situations as experiences, and

thereby makes decisions a completely different way from someone who is

negative or pessimistic. Thus, goal achievement and self-actualization are critical

components in positivistic affective conditions, and they do directly influence

people’s wellbeing (Ross and Mirowsky 2008; Richman 2005; Fredrickson 2003;

Gross 1997).

       Studies revealed that positive moods and emotions are associated with

wellbeing (Ross and Mirowsky 2008; Leung et al. 2005), as the individual is able

to think, feel and act in ways that foster resource building and involvement with

particular goal materialization (Lyubomirsky, King, and Diener 2005).         This

situation is later internalized, causing the individual to be self-confident, from

which follow a series of positive attitudes that guide further actions (Sheldon and

Lyubomirsky 2006). Positive mood is not limited to active responses by the
                                                                                 101


individual, but a study showed that “counting one’s blessings”, “committing acts

of kindness”, recognizing and using signature strengths, “remembering oneself at

one’s best,” and “working on personal goals” all positively influence wellbeing

(Sheldon and Lyubomirsky 2006; Abbe et al. 2003). Happiness is not a mood that

does not change with time or situation; hence, happy people can experience

negative moods (Diener and Seligman, 2002).

       Human emotions are the combination of not only positive conditions but

also negative factors (Watson et al. 1999). Hence, depression, anxiety,

neuroticism and pessimism are seen as a measure of the negative psychological

conditions that affect subjective wellbeing (Evans et al. 2005; Harris et al. 2005;

Kashdan 2004).      From Evans and colleague, Harris et al. and Kashdon’s

monographs, negative psychological conditions affect subjective wellbeing in a

negative manner (i.e. guilt, fear, anger, disgust); and positive factors influence

self-reported wellbeing in a direct way – this was        corroborated by a study

conducted by Fromson (2006); and by other scholars (McCullough et al. 2001;

Watson et al 1988a, 1988b). Acton and Zodda (2005) aptly summarized the

negative affective of subjective wellbeing in the sentence that says “expressed

emotion is detrimental to the patient's recovery; it has a high correlation with

relapse to many psychiatric disorders.”

       Marital status

       In wanting to analyze possible determinants of wellbeing of the elderly,

any assessment without marital status in respect to the elderly is missing a critical

aspect of the living arrangements of people. According to Moore et al. (1997,
                                                                                102


29), they concluded that people who reside with a spouse have a different base of

support in the event of poor health, as against those with other social

arrangements (Also see Smith and Waitzman 1994; Lillard and Panis 1996).

Cohen and Wills (1985) found that perceived support from one’s spouse increased

wellbeing (also see Smith and Waitzman 1994), while Ganster et al. (1986)

reported that support from supervisors, family members and friends was related to

low health complaints. The findings of Koo, Rie and Park (2004) revealed that

being married was a ‘good’ cause for an increase in psychological and subjective

wellbeing in old age. Smith and Waitzman (1994) offered the explanation that

wives were found to dissuade their husbands from particular risky behaviours

such as the use of alcohol and drugs, and would ensure that they maintained a

strict medical regimen coupled with proper eating habits (also see Ross et al.

1990; Gore 1973). In an effort to contextualize the psychosocial and biomedical

health status of a particular marital status, one demographer cited that the death of

a spouse signified closure of daily communication and shared activities, which

sometimes translated into depression that affected the wellbeing of the elderly

more than if they had invested in a partner (Delbés and Gaymu 2002, 905). They

pointed to a paradox that this was not necessarily the case among males. In

addition, it was found that the widowed have a less optimistic attitude towards life

than married people, which is not an unexpected result (Delbés and Gaymu 2002,

905) as the widowed person will no longer have the company of another partner

who is able to share and be a part of lived experiences.

       In Smith and Waitzman’s (1994, 488) literature review, they added that
                                                                                103


men’s gains from marriage were greater than those of women (also see Lillard

and Panis 1996, 313). This, then, explains why some scholars made the statement

that “many observers have theorized that married individuals have access to more

informal social support than do non-married individuals” (Smith and Waitzman

1994, 488), which explains the social reality of a higher quality of life in married

couples than ‘non-married’ individuals (also see Lillard and Panis 1996). Some

studies have shown that married people have a lower mortality risk in the hale

category than the ‘non-married’ (see for example Goldman 1993), and this

justifies why they take less life-threatening risks (Smith and Waitzman 1994;

Umberson 1987).

       Using a sample of 1,049 Austrians aged 14 years and over, Prause et al.

(2005) found that married individuals reported better subjective health-related

quality of life index (8.3 ) than divorced persons (7.6) or singles (7.7). Smock,

Manning and Gupta (1999) concurred with Prause et al. and other studies on the

fact that there is a direct relationship between being married (for females) and

economic wellbeing. Drawing longitudinal data from the National Survey of

Families and Households for 1987-1988 (NSHH1) and a follow-up survey

(NSFH2) of some 13, 008, a sample size of 2,665 females of 60 years and older

was used. Each study had a response rate of approximately 74 percent for NSFH1

and 82 percent for NSFH2. The research revealed that married women had

greater economic wellbeing than divorced females. It was found that females

who were remarried experienced the same degree of wellbeing as their married

counterparts, which was greater than that experienced by single females.
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       In Widowhood and Race, a study conducted by Elwert and Christakis

(2006), the findings revealed increased mortality upon bereavement for both

genders. Among the findings is that “For men, the hazard ratio is 1.17, indicating

a 17 percent increase in … death due to widowhood” (Elwert and Christakis 2006,

28). The study used a longitudinal and nationally representative dataset of elderly

married couples in the United States (N=410,272).            One potent tenet of

widowhood is the sociological fact that marital unions (including married and

common-law unions) that experience mortality of one of the two partners have a

decided influence on wellbeing through either psychological depression (i.e.

bereavement) or death of the surviving partner.         Baro (1985) in a PAHO

document titled Toward the Wellbeing of the Elderly declared that loneliness and

bereavement are determinants of the health status of the elderly.

       With the disparity in life expectancies of the sexes, oftentimes the woman

lives alone after the death of her spouse and may have difficulties accessing

friends and/or family for support, which in turn affects her quality of life (Havens

1995). The widow is likely to suffer from chronic and acute conditions, coupled

with the social isolation that results from the death of the partner, which usually

causes irreversible pathology. It should be reiterated that chronic illness can be

burdensome. The aged person is left with pain, frequent physician visits, and the

death of a beloved partner, all of which diminish the quality of life (Kart 1990).

       In studies conducted by Mastekaasa (1992) and Scott (1991) in Diener,

people who were married were found to be happier, so the “causal influence

between subjective wellbeing and marriage may work in both directions” (Diener
                                                                                105


1984). Lee, Seccombe and Shehan (1991) in Diener, noted that married couples

of either gender were found to be more contented than those who were not

married or even divorced or separated.

       Physical Exercise

       In an effort to present a cogent perspective on the value of physical

exercise and its influence on wellbeing, the researcher will use the American

Heart Association’s perspective that “Physical inactivity is a major risk factor for

developing coronary artery disease. It also increases the risk of stroke and such

other major cardiovascular risk factors as obesity, high blood pressure, low HDL

(’good’) cholesterol and diabetes” (American Heart Association, 2006). From the

diseases presented in the American Heart Association’s monograph, senior

citizens are likely to be affected by those conditions. The wellness community, in

wanting people to grasp the critical necessity of physical exercise, noted that

conditions such as stiff joints, breathing problems, skin sores, poor appetite and

mental changes can result from a lack of physical exercise. This is equally

endorsed by a longitudinal study conducted in England, which revealed that

“limitations in physical activities reduced quality of life (mobility -0.434, 95%CI

to -0.545)” (Netuveli et al. 2006, 360).

       In the SABE project, the report shows that people who exercise are 41

percent more likely to report a better health status than those who do not

participate in physical exercise. Of equal importance is the issue of body mass

and reported health status. The findings reveal that the respondents who had a

normal body index reported a 19 percent and 49 percent point better health status
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than the overweight and obese persons respectively.

       A study of 50 U.S states including the District of Columbia and Puerto

Rico in 2001, in which 120 non-institutionalized civilians aged 18 years and older

were contacted by way of telephoning using cross-sectional data, Rie (2004)

revealed that physical activities have been reduced in the case of senior citizens,

and this speaks to the difficulties of health conditions of this group of people.

Studies conducted by a group of researchers concur with the findings of other

studies, in that an association exists between physical exercise and quality of life.

A study by Paw et al. (2002) involving 217 seniors (i.e. 70 years and older), and

conducted between January and July 1997, revealed that a moderate association

existed between physical fitness (r=0.20) and general wellbeing.


       Fertility of the woman (Number of children had), and household size


       Some people argue from a purely economic perspective that the larger the

number of children a female has, the less likely it is that she will be healthy, and

this is from the premise of the socio-demographic conditions of child- rearing and

the socio-economic cost of the process. It may appear simplistic for one to

believe that associated with childbearing is the reality of the psychosocial

condition of the child and the family, and accompanying this are the biomedical

conditions which are usually accepted as given. On the contrary, some people

conceptualize childbearing as a vehicle of social mobility, and some consider their

offspring as material resources for their old age. Within the psyche of the poor,

poverty alleviation is seen through the investment in a child or children, similar
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to what some people see as investing in stocks, bonds, shares or other physical

assets.

          Studies from the RAND Center for the Study of Aging (1998) confirm

some of the epistemological beliefs of people in our society. The institute has

carried out research showing that “Childbearing has often been thought to have a

beneficial effect on a woman's health, primarily because it reduces the risk of

breast, endometrial, and ovarian cancer”, which concretize some of the common

sense thoughts of people on wellbeing and childbearing.        A crucial issue that

needs mentioning is how the RAND’s study highlights the non-socio-

demographic benefits of childbearing. Coupled with this is the frequency of

medical care which the new mother is likely to see, thereby ensuring that she

seeks health care.

          The study appears to be emphasizing the wholesale advantages of

childbearing, but researchers at RAND discovered that with ageing, many of

those advantages become detriments.          RAND’s findings reveal that “in

childbearing histories of women aged 50 and older, the research shows that

women who bore six or more children were likely to suffer poorer health in later

years than those women who had fewer children or no children at all” (RAND,

1998).     This study encapsulates the inverse relationship between number of

children and wellbeing in later years of life. The issue of poor health could also

be tied to certain fertility conditions (i.e. childbirth). An important finding that

arises from RAND’s study is how “women who lost a child during the first year

of its life and women who delivered their first child before they reached 18 years
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of age both had an increased likelihood of poor health at age 50 and beyond.”

Which gives rise to the next issue, how does the environment affect a pregnant

woman, the birth of a foetus, and also the health, and by extension the wellbeing,

of senior citizens?

       Although children are seen in some societies as a pension, which justifies

the poor having many of them, the household directly affects the wellbeing status

of a family, in that the more children a family has, the less that family will have

available to spend on each child (see Zimmer and Kwong 2003). Education,

which for many families means social mobility out of poverty, will be less likely

with larger families, as the income of the family will be spread thinner, and so

fewer resources will be expended on each child for social and economic

development. So even though the family may perceive children as an escape from

poverty (or an old age pension), this possibility will become increasingly less if

the children are not able to develop their capacity to attract high-end employment

when their parents reach retirement.       Keister’s (2003) study finds a strong

association between family size and wellbeing in adult years, which means that

for each additional child in a family, the share of resources available for that child

becomes significantly smaller.

       Gender

       The World Health Organization (2005) put forward a position that there is

a disparity between contracting many diseases and the gender constitution of an

individual.   One health psychologist, Phillip Rice, in concurring with WHO,

argued that differences in death and illnesses are the result of differential risks
                                                                              109


acquired from functions, stress, life styles and ‘preventative health practices’

(Rice 1998).

        Biomedical studies showed that there are gender specific diseases. The

examples here are prostate cancer (affecting only men) and uterine cancer (which

plagues only women). Rice believed that this health difference between the sexes

is due to social support.   According to Rice (1998), Rodin and Ickovics (1990)

this can be explained by epidemiological trends. Lifestyle practices may justify

the advantages that women enjoy compared to men concerning health status.

However, a survey done by Rudkin found that women have lower levels of

wellbeing (i.e. economic) than men (Rudkin 1993 222). This finding is further

sanctioned by Haveman et al. (2003) whose study reveals that retired men’s

wellbeing was higher than that of their female counterparts, because men usually

received more material resources, and more retirement benefits compared to

women of ages 65 years and older. Thus, with men receiving more than women,

and having more durable possessions than women, their material wellbeing is

higher in later life.

        The issue extends beyond those two types of chronic illnesses, as

Courtenay (2003) noted from research conducted by the Department of Health

and Human Services (2000) and Centers for Disease Control (1997) that from the

15 leading causes of death except Alzheimer’s disease, the death rates are higher

for men and boys in all age cohorts compared to women and girls. Embedded

within this theorizing are the differences in fatal diseases that are explained by

gender constitution (Seltzer and Hendricks 1989, 7), which Courtenay (2003)
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explained are due to behavioural practices of the sexes, and which explains the

fact that men are dying 6 years earlier than females (U.S. Preventive Services

Task Force, 1996).

       Other studies show agreement with Schoen et al. that men in general tend

to be more stressed and be less hale than females, and further argued that men can

use denial, distraction, alcoholism and other social strategies to conceal their

illness or disabilities (Friedman, 1991; Kopp, Shrabski, and Szedmak, 1998;

Weidner and Collins, 1993; Sutkin and Good, 1987). On the other hand, Herzog

(1989) in Physical and Mental Health in Older Women, using studies from a

number of experts, wrote that females had higher rates of depression than their

male counterparts. Could suicide be used as a proxy for depression? Numbers of

suicides are taken from death registers, and are likely to be under-reported for the

aged, since other illnesses are present, and may be substituted as the cause of

mortality (Herzog 1989).     Herzog noted that data on suicide and depression

yielded different results, and based on this fact, suicide cannot be used as an

indicator for depression.

       Males, nevertheless, are more likely to have heart diseases, gout and high

blood pressure than women. The WHO attributes this biomedical condition to

differences between the genders based on hormonal differentiations, social

networks and support, and cultural and lifestyle practices of the sexes, with which

Courtenay et al. (2002) concurred.

       Based on demographic models from abridged Life Tables, mortality is

different between the genders (Elo 2001). Generally, from the United Nations
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statistical databases, life expectancy for males is lower than for females. This is

particularly true for females in the old aged cohorts (United Nations 2004; Moore

et al. 1997). Moore et al. (1997) added, “Females’ life expectancies are likely to

remain above those of males [Elo 2001] for the foreseeable future, among both

the population as a whole and the elderly” (Moore et al. 1997, 12). Among the

justifications for the differential between life expectancy of the sexes is the link

between the health consciousness of women and their approach to preventative

care. Unlike women, men worldwide have a reluctance to ‘seek health care’

compared to their female counterparts. It follows in truth that women have

bought themselves additional time in their younger years, and it is a practice that

they continue throughout their lifetime, which makes the gap in age differential

what it is – approximately a 4-year difference in Jamaica.

       Elo (2001,106) in his discussion of the findings from the use of the vital

registration and the census dataset, postulating a reduction in infant and sex-

specific mortality, favoured women, and this will account for the disparity in life

expectancy between the sexes. Within the workings of this space, demographers

assume that we are in the third stage of the epidemiological transition (Omran

1971) in which health conditions associated with chronic conditions have replaced

infectious and parasitic illness as the dominant cause of death.

       Studies have revealed that the classification of many diseases affects a

particular gender. For particular chronic ailments, the primary contributor to death

is ischemic heart disease, which is substantially a man’s rather than a woman’s

disease. In a research project conducted jointly by the University of Michigan in
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the United States and the Bureau of Health Promotion in Taiwan on elderly

Taiwanese, between 1989 and 1993, of 4,049 people aged 60 years and beyond, a

number of socio-economic determinants were studied concerning mortality. From

the findings, femininity is negatively related to health conditions as opposed to

age, which is positively related to health conditions. (Zimmer and Martin 2003,

p.17).

         Embedded within Zimmer, Martin and Lin’s findings are the direct

relationship between ageing and health conditions, compared to an inverse

relationship existing between health conditions and females. It is clear from the

socio-economic factors mentioned previously that males who are older than sixty

have a higher propensity to be ill than females.

         It should be noted here that a study conducted by Franzini et al. (2004) on

native Mexicans in Texas found that females had worse mental and self-reported

health than their male counterparts, but not physical health. Franzini et al.’s work

contravenes many findings on gender and health status. Another study on the

socioeconomic determinants of mortality in two Canadian provinces found that

household income and education were significant in predicting mortality. When

gender was introduced within the model, the association dissipated (Roos et al.

2004).

         A study conducted by McDonough and Walters (2001) revealed that

women had a 23 percent higher distress score than men, and were more likely to

report chronic diseases than males (30%). It was found that men believed their

health was better (2% higher) than that self-reported by females. McDonough
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and Walters used data from a longitudinal study named the Canadian National

Population Health Survey (NPHS). The study was initiated in 1994, and data

were collected every second year for a duration of six years. The information was

taken from 20,000 household members who were 12 years of age and older.

        Research carried out by a group of economists (Headey and Wooden)

revealed that “…women are slightly more likely to report higher levels of life

satisfaction than men (mean=78.3, compared with 77.1 for men…” (Headey and

Wooden 2003, 14). Based on the nature of the study, ‘…subjective wellbeing and

ill-being’, the reported wellbeing (measured by life satisfaction) of women is

higher than that of men, but males have greater financial wellbeing than females

(Headey and Wooden 2003, 16).

       HIV/AIDS and the Elderly


       The issue of HIV/AIDS is not solely limited to infected individuals, whose

numbers are substantial between 15 and 24 years (UNAIDS 2004), but the elderly

who will be increasingly asked to support their infected children and other

members of the family. Instead of being the socio-financial support for their

children and other household members, the aged populace will be needed to

absorb the stress of loved ones in addition to their psychosocial and demographic

challenges. According to Knodel et al.’s (Knodel et al. 2001, 1320) study carried

out in Thailand, “59 percent of those who died of an AIDS-related disease co-

resided with a parent at the terminal stage.”    This implies that the aged are

expected to perform caretaking duties. With this social reality, the aged person’s

wellbeing will be affected in a two-fold manner. Firstly, the aged parents are
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expected to care for a dying loved one; and secondly, they are forced to absorb the

stress of this arrangement with the biological and psychosocial conditions of their

ageing organism. In order to understand the stresses of this situation on the aged,

we need to analyze it within the context of the cost and duration of care for the

elderly and the AIDS patients. This can be supported by a study that revealed that

longstanding ailments do diminish quality of life (Neteveli et al. 2006).

       Globally, regionally and nationally, the core for HIV/AIDS infected

candidates is between 15 and 55 years, and these are likely to be the children of

many aged people. Therefore, the social support system that the elderly would

expect is highly likely to be reverted to the children. Day and Livingstone (2003)

found that social support is an effective coping mechanism to deal with stress.

From this established theory, the potential stressors that will be levelled against

the elderly will automatically expand.

       A longitudinal research project which was conducted between 1991 and

1994 on households drawn from North-western Tanzania compared and

contrasted the body weights of some elderly individuals prior to and post the

deaths of a “prime-age adult” in the household.         According to Dayton and

Ainsworth (2004), the findings indicated that the seniors with the lowest physical

wellbeing (measured using body mass index, BMI) were those in poor families

that had not experienced a household adult death in the survey period. The BMI

for the elderly was less after the death of a loved one than before the death of the

household member. Another revelation from the study was the increased time

spent by the elderly in household chores preceding the adult’s death, and
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reduction in waged employment.

       In the event that the HIV/AIDS virus does not infect the children of the

elderly, or other household members, UNADS (2004) reported that less than five

percent of them are infected by the epidemic. This social reality within the

financial constraint of the family typology will become a psychosocial stress for

the elderly. The issue of stress is a determinant of wellbeing as regards the

HIV/AIDS virus.      Lazarus and Folkman (1984) conceptualized stress as a

“relationship between the person and the environment that is appraised by the

person as taxing or exceeding his or her resources and endangering his or her

wellbeing” (p.19).

       With the prevalence and incidence rates of HIV/AIDS, there is a demand

on the aged populace to cope with such a social setting. Coping is embedded in

an individual's cognitive, affective, and behavioural efforts to manage specific

external and/or internal demands (Crocker, Kowalski, & Graham 1998; Lazarus

1999). Studies have shown the positive association between coping and

wellbeing; see for example, Paragment 1997). Epping-Jordan, et al. (1994) did a

study on coping and health (also see Paragment 1997), using a sample of 66

cancer patients diagnosed with a variety of different types of cancer including

breast cancer, gynaecologic cancers, haematological malignancies, brain tumours

and malignant melanoma. The findings revealed that the relationship between

coping and disease progression demonstrates how the relationship between coping

and health is ultimately quite complicated.

       The elderly need to cope with the discrimination, the social exclusion, and
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the psychosocial and financial responsibility of the infected close family member,

in addition to dealing with personal infection within an aged body and the

corresponding demands.

       Rogers (1995) in a study entitled “Sociodemographic Characteristics of

Long-lived and Healthy Individuals” cited that many factors account for long

lives. Rogers’ study was based on secondary data collected by the US Department

of Health and Human Services in 1988, and called The 1984 National Health

Interview Survey. The sample size was 15,938 individuals aged 5 and older. The

findings revealed that females who walk are expected to live 7.5 years more than

males, while females who are physically incapacitated are expected to live 5.5

years more when compared to males. There was association between age, sex,

income, education, physical health, social network participation and emotional

wellbeing and perceived health (Rogers 1995, 41). He wrote “. . . death is more

likely to occur among those who are older, male, less educated, and with

disabilities, chronic conditions, and perceived poor health” (Rogers 1995, 46).

One of the reasons for elderly people attending church is because of the social

networking that this institution provides them.

       Religiosity

       A number of scholars have said that religion is associated with wellbeing

(Krause 2006; Jurkovic and Walker 2006; Wiegand, and Weiss 2006; Ardelt

2003; Willits and Crider 1988; Witter, Stock, Okun and Haring 1985; Graham et

al. 1978) as well as low mortality (House, Robbin and Metzner 1982). Religion is

seen as the opiate of the people from Karl Marx’s perspective, but theologians, on
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the other hand, hypothesize that religion is a coping mechanism against

unhappiness and stress (also see Wiegand, and Weiss 2006). According to Kart

(1990), religious guidelines aid wellbeing in that they restrict behavioural habits

which are health risks, such as smoking, drinking alcohol, and even diet.

       The discourse of religiosity and spirituality influencing wellbeing is well-

documented (Frazier et al. 2005; Edmondson et al. 2005; Moberg 1984; Graham

et al. 1978). Researchers have sought to concretize this issue by studying the

influence of religiosity on quality and life, and they have found that a positive

association exists between the two phenomena (Maskelko and Kubzansky 2006;

Franzini et al. 2004). They found that the relationship was even stronger for men

than for women, and that this association was influenced by denominational

affiliation. Graham et al.’s (Graham, et al. 1978) study found that blood pressure

for highly religious male heads of households in Evan County was low. The

findings of this research were not changed when controlled for age, obesity,

cigarette smoking, and socioeconomic status. A study on the Mormons in Utah

revealed that cancer rates were lower (by 80%) for those who adhere to Church

doctrine (Gardner and Lyon 1982a, 1982b) as opposed to those with weaker

adherence.

       In their study of 147 volunteer Australian males between 18 and 83 years

of age, Jurkovic and Walker (2006) found a high stress level in non-religious as

compared to religious men.       The researchers, in constructing a contextual

literature, quoted many studies that have made a link between non-spirituality and

“dryness”, which results in suicide. Even though, Jurkovic and Walker’s research
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was primarily on spiritual wellbeing, it provides a platform that can be used in

understanding the linkages between the psychological status of people and their

general wellbeing.     In a study which looked at young adult women, the

researchers found that spirituality affects the physical wellbeing of its populace

(Edmondson et al. 2005). Embedded within that study is the positive influence of

spirituality and religion on the health status of women. Edmondson et al.’s work

consisted of 42 female college students of which 78.8 percent were Caucasian,

13.5 percent African-American, 5.8 percent Asian and 92 percent were non-

smokers.

       Cox and Hammonds (1988) found that there is a positive relationship

between religiosity and wellbeing in the elderly; this was also corroborated by

Edward and Klemmack (1973), Hummer et al. (1999) and Spreitzer and Synder

(1974) in separate studies on the same space. Cox and Hammonds, in their

abstract, put forward the perspective that all past studies that have analyzed

religiosity and life satisfaction came to the same conclusion – which is that

individuals   who    attend   church   experience a greater      life satisfaction.

       According to Cox and Hammonds (1988), Guy, in a study on the discourse

of religiosity and life satisfaction, found that the group with the highest score on

the measure of life satisfaction was that which reported the most frequent church

attendance. Other research on the same space agreed with Guy, and Cox and

Hammonds (1988) that religiosity was a determinant of life satisfaction

experienced by the elderly (Markides1983). Cox and Hammonds stated that this

space in the discipline of gerontology has a high degree of scientific bias, as
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scientists are less likely to reflect the secular attitudes of the public. In addition to

the few longitudinal studies on the matter, Cox and Hammonds (1988, 47) argued

that all interpretations of the results and conclusions must be used cautiously.

        In a study conducted by Frazier et al. (2005) exclusively on African

American older people, they found that several multidimensional measures of

religiosity were associated with psychological wellbeing. Kail and Cavanaugh

(2004, 584) captured the experiences of seniors and how religion enhances their

survivability, when they said that "...older adults who are more involved and

committed to their faith have better physical and mental health ..." When asked

'how you deal with the living', respondents listed among coping strategies

spirituality (Kail and Cavanaugh 2004). From studies analyzed earlier, spiritual

support is a mechanism used in coping with life's challenges, as the church offers

a social support system and this is a mantle of hope. Religiosity is a determinant

of the health status of people, and more so for seniors as they continue to grapple

with loss of spouse, work and other psychosocial and biological conditions.

        Violence and fear of criminal victimization

        The statistical association between age and fear of crime is well studied.

“Fear of criminal victimization” (Franzini et al. 2004; Harriott 2003) in our social

space is also another factor which influences the psychosocial state of people.

According to Harriott (2003, 36) “the effects of the fear of criminal victimization

usually extend beyond altering the psychological states of individuals to

influencing their behavioural patterns.”       He added, “It is simply intended to

indicate the wide scope of the impact of the fear of crime, its effect on the quality
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of life. . .” Franzini et al. concurred with Harriott that fear of victimization is

negatively associated with physical and mental health. Harriott mentioned an

issue that has implications for quality in life of Jamaica, in particular the

vulnerable elderly, when he said that “Given the high density and long duration of

this violence … the Jamaican population has been gripped by a high level of

anxiety and fear of criminal victimization” (Harriott 2003, 35). This justifies the

strong association between physical vulnerability and fear of victimization.

Physical vulnerability was categorized based on sex and age.

       Harriott’s sample was 1,340 Jamaicans. He used a probability-sampling

technique, with a sampling error of 3% and a response rate of 96%. Harriott

(2003, 42) found that 40% of the sample regarded themselves as being highly at

risk, and exhibited high levels of ‘worry’ about criminal victimization; those who

were least at risk indicated that they were most fearful; 31% of the victims

expressed serious worry in regard to being murdered whilst 24% of the non-

victims had the same ‘worry’, and a strong direct relationship existed between

physical vulnerability and the fear of victimization.


       Despite the Caribbean, in particular Jamaica, not presently experiencing

the level of conflicts found in Cambodia, Sierra Leone and other countries in

Africa, the degree of conflicts that do arise in certain inner cities in the island may

result in psychological trauma for the aged. The periodic violence in August

Town, Denham Town, Grants Pen, Warehouse et cetera does affect the aged as

regards their visiting health professionals for care. Embedded within the conflicts

are the psychosocial conditions (anxiety, loss of loved ones, depression et cetera)
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that are experienced by the aged. If the aged ARE vulnerable, then conflicts

inversely impact on their quality of life, as this disruption affects people’s lives in

every way (WHO 2002, 226).

       Chadee (2003) conducted a study in Trinidad and Tobago. His research

found that concerning mixed ethnicity, there existed an inverse relationship

between the fear of victimization and age, and non-victims were more fearful than

victims, while persons residing in low crime areas were more fearful compared

with people who were in high crime zones (Chadee 2003, 84). A number of

studies found that the aged who were less likely to be victimized were more likely

to be fearful (Harriott 2003; Chadee 2003; Baldassare 1986; Brillon 1987; Clarke

1984; Cook and Cook 1976). This undoubtedly influences their psychological

state and by extension their wellbeing.

       The World Health Organization aided the discourse on crime,

victimization and health by relating those issues to psychological stress (WHO

2002). According to Quirk and Casco (1994), psychological stresses which relate

to conflict are associated with depression and anxiety, loss of life and status,

psychosomatic ailments, displacement and grief.         The WHO noted that, “the

impact of conflict on health can be very great in terms of mortality, morbidity and

disabilities” (WHO 2002, 222). In the World Report on Violence and Health, the

WHO cited that in Zimbabwe, 13 percent of all physiological dismemberments

and disabilities were due to ‘armed conflict’ This is also common to other

topographies, as in Ethiopia, ‘armed conflict’ resulted in 1 million deaths (Kloos

1992); in Cambodia 36,000 people have lost at least one limb because of
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accidents due to landmines, and a similar situation occurred in Sierra Leone

(Human Rights Watch 1999). There is an inverse relationship between crime,

violence and victimization, based on the studies and expert’s work presented here.

       Home ownership

       In a study analyzing data germane to people and their environment, the

findings indicate that ‘perceived health’ and housing satisfaction contribute the

most to wellbeing among the elderly (Barresi, Ferraro, Hobey 1983, 84).

According to Breeze et al.’s (Breeze et al. 2004) study, using data from the

Medical Research Council in Britain, the aged who were owners of their homes

were less likely to report poor quality of life. A finding of importance was that

dependent seniors in their own housing were no more likely to have poor quality

of life, compared to those who lived in rented dwellings.

       In respect to gender, men’s and women’s home ownership was not found

to influence wellbeing positively. Nevertheless, for men who owned their own

homes, lower scores on wellbeing were found. The results also indicate that while

the quantity of neighbour interaction benefits the wellbeing of men, women

benefit more from the positive sentiments of sociability in the neighbourhood.

This study emphasizes the importance of environmental satisfaction and

neighbourhood sociability as key determinants of wellbeing in later life (Barresi,

Ferraro, Hobey 1983, 84)

       Household Size, Social Support (i.e. Family)

       In a 1992 survey of the Support for the Elderly in Rural and Urban China

(20,000 cases), Zimmer and Kwong (2003) used that data to analyze family size
                                                                                123


and support of older adults in urban and rural China. They found that an increase

of more than one child increases the probability for old-age support.

       In urban China, those having more than three children are less likely to

receive support than those with one child. The data revealed that each additional

child that is born to the elderly increases the likelihood of the elderly receiving

financial support without any diminishing return. The findings showed that

increasing gains from having an additional child are more apparent in rural than in

urban zones (Zimmer and Kwong 2003, 32). With a strong positive association

between the number of children and the likelihood of elderly support, a reduction

in family size will see changes in support for the aged populace. In McNally and

Williams (undated), Martin (1990) put forward the position that in developing

countries, family support plays a significant role in representing the best form of

care for the elderly; a point on which Anthony (1999) and Stecklov (1999)

concur. Anthony commented that the aged are sometimes left alone because of

the death of the other partner, which may result in depression or even low self-

esteem. It is important, then, to comprehend how social isolation impacts on the

wellbeing of the elderly. Steckklov, on the other hand, in his thesis ‘Evaluating

the economic returns to childbearing in Cote d’Ivoire’ sought to prove (or

disprove) the claim that children are economic assets to their parents, and affirms

with the other studies that this is so. He finds that, on an average, the additional

child increases the elderly parent’s material possessions with time. This fact is a

rationale for poor families to increase their family size in an attempt to relieve

them of poverty over time. Despite the difficulties of sharing the ‘little’ that the
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parents have, they perceive that the opportunity cost of high fertility in the future

outweighs the present cost of economic misfortune. This is even more pervasive

in poor households, in rural zones, with low educational attainment.

       The children are not only economic assets, but they stand as social support

in old age. Parents are equally concerned about their old age, and so in planning

for this reality many poor parents believe that one of the roles of their children is

to ‘look after them in old age’. Thus, this becomes a critical aspect of the

socialization of children by their parents, that they (i.e. parents) are expecting to

invest in education and other social products while sacrificing consumption for

them, so as not to be forgotten in their time of need, in old age.



       Environment

       Any study on the quality of life of humans cannot conclude without

examining whether or not the environment has an impact on the health status of

the individual (See Pacione 2003; Pebley 1998). This is because human activities

– in the form of deforestation, urbanization, industrialization, development,

growth and production, interface with the finite physical environment; issues such

as pesticides, radioactive waste, climate change, air and water pollution, emission

of greenhouse gases, asbestos and household waste, must be explored in relation

to their association with health status (Pebley 1998, 384). Pebley (1998) argued

that human activities have transformed the earth’s topography. He believed that

population growth accounted for many of the environmental problems and

hazards that we experience today. This, then, begs the question, does the
                                                                                          125


environment impact on human wellbeing?

          Pebley stated that “environmental factors are likely to play a small but

significant role in mortality and morbidity…” (Pebley 1998, 384); he admits that

an associative role does exist between the environment and the status of human

health (also see Khaleque and Elias 1995). From Pebley’s, and Khaleque and

Elias’ works, environmental factors must be included in any analysis of health

status.




          Figure 7.1.1: Respiratory system of a human.

          Source: Health Canada




          Sastry (2002), believed that the long-term effects on health from exposure

to air pollutants are known to be difficult to detect, but argued that there is a

short-term impact on the respiratory system, and that mortality from airborne

pollutants has been well established.                    A group of practitioners and scholars
                                                                                   126


(O’Neill et al. 2007) disagree somewhat with the position of Sastry in a study of

some 92 diabetes patients in Boston. They have shown a direct association

between air pollution and inflammation and endothelial dysfunction among

people with diabetes. The argument constructed by scholars is that because of the

very susceptible nature of type 2 diabetics, they are more prone to death if

exposed to airborne pollutants than other people, and the researcher believes that

this does not exclude those with asthma or other respiratory ailments, nor does it

exclude young children.

           It was not the mere exposure to airborne particles [i.e. PM 2.5 , “particles

<2.5 µm in aerodynamic diameter, known as fine particles” (O’Neill et al. 2007)]

that led to the possible death of the patients with type 2 diabetes, but it was the

degree of contact with the particles, the present health status and the genetics of

the individuals. Within the context of diabetes being one of the five leading

causes of death of the aged, then undoubtedly the presence of air pollutants is

highly likely to affect the wellbeing of senior citizens, which makes the

environment a component of any study of the wellbeing of this group. Airborne

particles not only affect the aged in regard to mortality, but their physical

functionality is also influenced by these pollutants, thereby affecting their quality

of life.     These are manifested in the form of chronic respiratory ailments or

cardiovascular conditions, anxiety, depression, pain and a sense of diminished

quality of life among the aged. While the sample size of O’Neill et al. (2007) was

92 and bearing in mind that it was not chosen using a probability sampling

technique, this lacks generalizability. Nevertheless, a study carried out by the
                                                                               127


American Thoracic Society (2002) unequivocally shows that airborne pollutants

do affect the quality of life of people.

        Eldemire identifies ageing as a ‘biological process’ which is impacted

upon by the environment (See Eldemire 1994, 33). This argument recognizes the

interplay between the environment and the human body, as regards growing old

and survivability. The human body depends on the environment for oxygen. This

is not the only dependency that exists between the two physical entities; but the

body is able through the process of homeostasis to survive in different ecologic

conditions as dictated by the environment.            Because there is this natural

connection between them, any mishap within the environment is highly likely to

cause a shift in the health status of people, in particular the aged.

        As such, it should come as no surprise that pollutants in the atmosphere

cause illnesses (or ailments) like tuberculosis, viral influenza, cholera, and so

forth. Another matter which is of importance here is how ‘deforestation’ on the

hills (or mountains) results in flooding - which results in either (i) increased

ailments or mortality, or (ii) destroyed water quality and food supply – which

again affects the wellbeing of people. The human body, therefore, depends on the

environment for nutrients, and vital oxygen for survival. Because the body

survives within the environment and relies on it for sustenance, changes in this

physical space directly alter the functioning of people. Such a premise emphasizes

that the human body and the environment are one; as such the lungs depend on

the outside environment (see Appendix 4), the air, to carry oxygen into the body,

and so do the blood cells. Oxygen to the human body is comparable to gasoline
                                                                                     128


in a vehicle, which carries that vital source of life to the engine. Without it the

body is like any other inanimate, lifeless object, and is referred to as a corpse.

       In a study conducted on Malaysians in which the information on causes of

mortality was gathered between 1994 and 1997 from vital statistical records,

Sastry (2002) reported that a strong association exists between deaths and air

pollution. The study indicated that the youngest aged people (less than one year)

and the oldest aged populace (65 to 74 years) who were exposed to air pollution

had a higher probability of mortality. According to Sastry (2002, 15), “deaths

from non-traumatic causes are 19% higher after air-pollution days.” With this

finding, high air pollution implies an increased mortality which is modest for

those aged 75 years and over. This was also the case for infants after a day of high

air pollution. From this research, increased mortality does not occur as a result of

a single day of high air pollution, but it is more related to a five-day duration.

Bascom et al. (1996) and Dockery and Pope (1994) as well as Sastry (2002)

theorized that a direct association existed between air pollution and daily deaths.

Those deaths resulted from cardiovascular and respiratory diseases. Sastry (2002)

warned against a perspective of causality between air-pollution and mortality. He

used the Samet et al. (2000) study to emphasize the disparity.

       In an article entitled ‘Urban environmental quality and human wellbeing -

a social geographical perspective’,     Pacione (2003) argues that environmental

quality within a particular topography influences people’s quality of life, and that

people in developed nations now realize that wellbeing is not necessarily a simple

function of material wealth (Pacione 2003, 19). This theorizing was the bedrock
                                                                                129


upon which Pacione put forward his claim that the quality of the environment

directly affects one’s wellbeing or ‘illbeing.’ Despite the article being on ‘Urban

environmental quality and human wellbeing’, some issues such as deforestation,

climatic change, human encroachment on the natural environment, changes in

farming densities and practices, air pollution, human and animal demography, and

inappropriate sewage disposal are just a few elements, present in both rural and

urban zones in developing countries, which affect the quality of life everywhere

(Planning Institute of Jamaica 1995, 28). Liberato et al (2006) carried out a study

in Bolivia using secondary data and found that the rural/urban locality influence

was the largest on wellbeing, which reiterates that Pacione’s article is applicable

across urban or rural zones.

       A study of some 1,212 Taiwanese elderly (65 years and beyond) selected,

using cluster sampling, from a listing of households in northern Taiwan, revealed

that the elimination of environmental vulnerability is important to the wellbeing

of the elderly (Tzu-Ting 2005).      The research indicated that for seniors the

bathroom was a prime location for environmental hazards in the home. Among

the predictors of ecological perils were (1) living in urban zones, (2) poor

awareness of one’s health status, and (3) seniors (ages 74 years and beyond).

       Pacione (2003, 20) used an illustration of inner city communities in the

UK where the quality of life of the residents is low, and this was attributable to

overcrowding, “amenity deficient housing”, low skills levels, and migration.

Kart (1990) in the text ‘The realities of aging’ attributed particular typologies of

environment to the degree of wellbeing experienced by the elderly. He argued
                                                                                    130


that quiet neighbourhoods with adequately maintained topographies were suitable

for the ‘frail elderly’. According to Kart, using a study by Chapman and Beaudet

(1983), an association exists between the physical qualities of the environs.

        Summary

        This literature review has provided a conceptual framework of the possible

factors which can either be included, or those that are likely to be used, in

building a model on the wellbeing of the aged. Wellbeing is undoubtedly a multi-

dimensional phenomenon. It is not based on a single element, such as biological

condition (i.e. illnesses and injuries). Despite the fact that this plays a critical role

in curative care (SABRE’s project – biological factors account for 33% of a

38.2% model), the literature has shown that psychosocial, environmental and

cultural factors are equally important in influencing wellbeing. In particular, the

quality of life of the aged is associated with biopsychosocial conditions – social

support, home ownership, psychological affective conditions, household density,

ecological factors, ageing, level of education, cost of health care and marital

status; and it does differ based on gender.

        Past works have shown that positive psychological conditions directly

correlate with quality of life, and negative affective conditions inversely relate to

wellbeing, but none of the work that has been reviewed has made a distinction

with regard to degree of influence. The current study will address this gap, as the

researcher is concerned about which of the two psychological conditions has more

influence on the wellbeing of senior citizens.

        On the matter of the environment, which can play a critical role in its
                                                                                   131


effect on the human body and its psychological state, all the previous studies

converge in that it is a significant determinant of quality of life. This study will

isolate the psychological conditions from the environment, and in the process will

evaluate whether or not airborne pollutants and other ecological factors can be

used to predict the quality of life or human wellbeing.

         This takes me into the next variable, crime. One of the issues which this

research seeks to address is whether or not crime does inversely affect the quality

of life of humans. Although fear of anything in life is correlated with a negative

psychological state, by separating the psychological conditions from crime, this

study will distinguish between the two phenomena.            The current work will

differentiate between the fear of crime, which is constituted in the psychological

conditions, and the crime itself, and by so doing this study will be able to address

the matter of who are more likely to have crimes perpetrated against them, and

the correlation with the wellbeing of aged Jamaicans.

         On another factor, the issues of home ownership, property ownership and

areas of residence were not distinguished in other studies. The current work will

single out each condition in an effort to generalize the influence of typologies of

home ownership, property ownership and area of residence on the quality of life

of aged people within the Jamaican context. Past works did not differentiate

between house ownership and property ownership within the construct of where

one lives, to see which, if any, of the three conditions influences the quality of

life, and if so, the degree to which it is affected. This gap will be rectified in this

paper.
                                                                                     132


       There is another gap with which this study will concern itself, and it is of

gender. There are many contradictions in past literature on the quality of life of

males and females. Some studies have shown that the health status of males is

greater than that of females, while other works have disproved this claim. From

the literature, the economic wellbeing of males is higher than that of their female

counterparts, but no single work has twinned both health status and income in

measuring the wellbeing of the aged, while noting any gender differences. Thus,

this present study seeks to address this gap by evaluating wellbeing from the two-

dimensional delimitation of previous works, and in the process see whether or not

a difference exists between the sexes’ subjective wellbeing. This leads me to the

next matter, the influence of education on the quality of life of senior citizens.

       The literature has generalized that years of schooling (i.e. educational

attainment) play a multi-dimensional role in the quality of life of people. It is

argued that education does not only directly influence the wellbeing of people, but

that it inversely does so through occupations, lifestyle practices and typology of

education. Owing to the fact that this study will not be using occupation and

typology of employment status of the delimitation of the dataset (i.e.

approximately 75% of the data are missing), this model will be able to isolate the

single effect of education on the general wellbeing of aged Jamaicans.

       Furthermore, this literature review has even provided information on

religion and/or religiosity that is a critical condition as an indicator of wellbeing,

but because of the limitation of the dataset this has not been evaluated as a part of

this paper, along with lifestyle risk factors and some historical socioeconomic
                                                                                133


indicators (such as childhood diseases, nutrition, health and economic situation in

childhood).    Nevertheless, the generalized finding is that socioeconomic,

ecological and psychological conditions are indeed factors in measuring the

wellbeing of aged people. Given that we have established a plethora of factors

that singly affect wellbeing; this leads us to the next issue, which is the approach

to combining those variables in a single model. The next CHAPTER will address

the aforementioned issues raised.
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                                   Chapter Eight

                               Modelling Wellbeing

       The researcher has employed the Ecological, Selective Optimization with

Compensation Model of Ageing and the economic model of health put forward by

Smith and Kington (1997), in an attempt to understand the state of elderly

Jamaicans. Those models are discussed below.

       While many scholars such as Erber (2005), Brannon, and Feist (2004) had

put forward the idea that this is timely in the measurement of quality of life,

neither of them proposed a mathematical model for the worded construct. Even

though a single ideational purpose drove this paper, the final, biopsychosocial

model was developed through a hybrid approach. The researcher drew variables

and used advanced quantitative statistical analysis from various theories, models

and functions. The building of this model drew its premise from the mathematical

framework outlined by Stutzer and Frey (2003) referred to as the micro-

econometric happiness function – this is written as

       Wit = α + β X it + ε it .      …………………………….. ….. (1)

       Where W it represents subjective wellbeing, X it denotes x 1 , x2 , x 3 , and so

on, in which x 1 to x n are variables – ‘sociodemographic’, ‘environmental’, and

‘social’, ‘institutional’ and ‘economic conditions’ (Stutzer and Frey 2003, 7).

Furthermore, according to Stutzer and Frey (2003, 8), classical economists,

positivists, were not concerned with the valuation of happiness. It was thought to

be highly subjective, in that each person had a different perspective on what

constitutes, for him or her, a ‘good life’.   The indicators of individual wellbeing
                                                                               135


become highly problematic, and should be left to the psychologists. Despite

being economists, Stutzer and Frey ventured into this discourse. They theorized

that subjective wellbeing is a proxy for utility, a construct that economists know

very well.

       The model is primarily shaped by regression analysis. Embedded with

this model was the correlation between sociodemographic, institutional,

environmental and economic conditions, and the wellbeing of each individual

with different time intervals. Engel’s biopsychosocial model was not really a

model. Instead it was a construct which sought to encapsulate body, mind and

social conditions in treating health, as a model represents a theoretical network

through the use of symbols. What he provided was a set of abstractions that are

designed to explain a special theoretical underpinning of health care. Engle

argued for the expansion of the biomedical model but during the process did not

formulate a theory or a model. Thus, Dr. Engel’s work on the biopyschosocial

model did not have a definite set of variables; neither did he advance any

statistical technique to illustrate what he referred to as a model. Two economists,

Smith and Kington, on the other hand, have sought to provide a platform upon

which more studies should be positioned in understanding the health status of a

population, when they used an economic model developed by Grossman.

Grossman’s work was the embodiment of the actual construct outlined by Engel,

the biopyschosocial construct, following which the biopsychosocial construct was

now formulated into a model. It is an econometric model, which uses the

principles of a production function. This is a broader construct of health that
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incorporates biological, psychological, and sociological conditions in assessing

health status:

       W=ƒ ( P mc , ED, Et , A i , En , G, MS, AR, P, N, O, H, T, R t, V).

       The researcher will explain how he arrived at the aforementioned model.

       The overarching theoretical framework that will be adopted in this study is

an econometric model which was developed by Grossman (1972), quoted in

Smith and Kington 1997a, which reads:

       H t = ƒ (H t-1 , G o , B t , MC t , ED) ……………………………………… (2)

       In which the H t – current health in time period t , stock of health (H t-1 ) in

previous period , Bt – smoking and excessive drinking, and good personal health

behaviours (including exercise – G o ), MC t ,- use of medical care, education of

each family member (ED), and all sources of household income (including current

income) - (see Smith and Kington 1997a, 159-160). Grossman’s model was

further expanded upon by Smith and Kington to include socioeconomic variables

(see Equation 3).

       H t = H* (H t-1 , P mc , P o , ED, Et , R t , A t , G o ) …. ……………………… (3)

       Eq. (2) expresses current health status H t as a function of stock of health

(H t-1 ), price of medical care P mc , the price of other inputs Po , education of each

family member (ED), all sources of household income (Et ), family background or

genetic endowments (G o ), retirement related income (R t ), asset income (A t ,)

       Among the limitations in the use of the biopsychologic model that was

used by Smith and Kington are psychological conditions and ecological variables.

Many of the variables used in Eq. (2), because data from this study based on the
                                                                                 137


Jamaica Survey of Living Conditions (PLC) and Labour Force Survey (LFS) were

not primarily intended for this purpose, equally limit this study. The PLC is a

national cross-sectional study that collects data for general policy formulation,

and so we will not be able to track the individuals over time in order to establish a

former health status. The updated PLC and LFS do not have information – such

as preventative lifestyle behaviour, exercise, family background, and smoking

habits. From a model by Smith and Kington in Equation 3, and based on the

limitation of the dataset, we were able to extract some variables that were

compatible across the two studies. These are as follows:

       W=ƒ ( P mc , ED) ……………………………………………………… (4)

       Wellbeing of the Jamaican elderly W is the result of the cost of medical

care (P mc ), the educational level of the individual and not each family member

(ED). Thus, the researcher, having obtained some germane variables from Smith

and Kington, reviewed other theoretical perspectives in an attempt to validate his

position, to expand the definition of wellbeing from that of Smith and Kington,

physical functioning, to a composite index of physical functioning and income, as

well as examining the Ecological, Selective Optimization with Compensation

Model of Ageing to finally arrive at a single model that would reflect a closer

measure of subjective wellbeing of the elderly. With this objective, the researcher

viewed the perspective of using income and self-reported health conditions in an

attempt to assess the possibility of a composite index of wellbeing. After this, he

ventured   into   evaluating   the   Ecological,   Selective    Optimization    with
                                                                                138


Compensation Model of Ageing, which provide the final set of selected variables

for the model.

       The Selective Optimization with Compensation Model of Ageing is

guided by two principal assumptions. These are – (1) man is adaptable to

situations throughout his life and is always redefining himself in an attempt to fit

within the changes and (2) man is continuously interfacing with positives and

negatives during his life but as he becomes older, the losses (i.e. negatives)

outstrip the gains (or positives). With the ageing process, increasingly man’s

physical functioning deteriorates along with his ‘reserve capacity’. Hence, frailty

sets in and ageing of the body makes it fairly unlikely that he will be able to

perform to the highest level. (See Erber 2005, 32).

       Of importance to this theory is how the aged must now select strategies

within a particular domain in an effort to acquire a better life with an increased

lifespan. With the physical changes occurring within the body, the individual

must now replace losses with positives, even though many of the losses can

become psychological conditions during this period. Hence, the developmental

changes that occur will result in the adaptability of the elderly. He/she must now

use perceptual, cognitive, personal and social domains in an attempt to address the

frailty and unstoppable physiological conditions that are changing.             The

optimization that is likely from this model is totally based on the choices and how

they are able to attain that maximum (or optimization), which is a mark for “a

good chance of achieving successful ageing” (Erber 2005, 32).
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       The Ecological model of ageing, on the other hand, that Erber credits to

Lawton and Nahemow, is based on the collaboration between the individual and

his/her milieu. This model still relies on adaptability, but its formulation is based

on affective (i.e. emotional) wellbeing and behaviour. Wellbeing is measured by

using competence, which is valued based on physiologic conditions,

psychological state and social capabilities. The environment, on the other hand, is

operationalized as to how the individual is able to perform within the demands

placed on him/her.      These may be physical, sensory, cognitive, or social.

Therefore, the individual’s level of capability is dominated using his/her

adaptability from the pressures placed on him/her by the environment.

       The model emphasizes how as an individual is placed under more stresses

by the environment, for his/her level of competence to rise, he/she requires a

greater degree of environmental pressure. According to Erber, “…the higher

level of environmental press is needed for positive adaptation” (Erber 2005, 33),

and the opposite holds true.    Implicit in this theorizing is how the aged person

continuously has to adapt to the stressor levied on him/her by the environment.

From this model, it is clear that the aged person is interfacing with his/her

environment, and that he/she is not passively absorbing all the forces distributed

by the environment. The elderly person is an active participant with his physical,

social, economic and psychological surroundings. Thus, this paper uses the

principles of the biopsychosocial model started by Grossman and then later

modified by Smith and Kington. From the recognition in Smith and Kington’s

model that psychological conditions were not inputted,            having used the
                                                                                     140


Ecological, and Selective Optimization with Compensation Model of Ageing,

other conditions in addition to psychological variables, such as environment, age

of respondents, area of residence, occupancy per room and home ownership, were

added to the model. Furthermore, because of the limitations of the dataset, a

number of variables were excluded from the model such as stock of health,

lifestyle practices, price of other inputs and family background, religion, and

depression.


        The PLC, on the other hand, collects data on crime and victimization,

environmental conditions and household size, room occupancy, gender and age of

respondents, which were all important for this model, modified from that used by

Smith and Kington in Equation 4.             Along with the Ecological, Selective

Optimization with Compensation Model of Ageing, the final model for this paper

is:

        W=ƒ (P mc , ED, A i , En , G, MS, AR, P, N, O, H, T, V) ………… (5)

        Wellbeing of the Jamaican elderly W, is the result of the cost of medical

care (P mc ), the educational level of the individual, elderly cohort (A i , where i is 65

years and over), the environment (En), gender of the respondents (G), marital

status (MS), area of residents (AR), positive affective conditions (P), negative

affective conditions (N), occupancy per room (O), ownership of home (H), paying

property taxes, (T), and crime and victimization, (V).

                                      Limitations


One of the fundamental challenges for (or drawbacks to) this study is the use of
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secondary data. The Planning Institute of Jamaica and the Statistical Institute of

Jamaica collect survey data on the health status of Jamaica by way of the

biomedical model.     This model according to Dr. George Engel is simplistic,

which is the reason behind him developing the biopsychosocial model in the

1960s.     Data from the Jamaican policy institutions conceptualize and

operationalize illness, injuries, and degree of sickness as primary to the measure

of health status, which is used as the indicator for quality of life. Hence, based on

how those institutions collect data, in attempting to measure wellbeing using the

biopsychological model, difficulties were encountered. It should be noted here

that fundamentally critical aspects of the lifestyle of the elderly were omitted from

the Jamaica Survey of Living Conditions. From the literature, religion plays an

important role in determining the wellbeing of the elderly, and this was notably

absent from the dataset. Another important factor is loneliness. The literature

shows that many seniors retire from work, and for some their jobs are not merely

financial support, but they form a whole structure of socio-psychological security.

Therefore, when this is coupled with the death of a spouse, and friends and

children moving to reside on their own, it creates a particular loneliness as a result

of the lowered social support.

         More missing links within the dataset were substantial issues relating to

lifestyle and preventative practices. Important questions that were not asked are

as follows: Exercise - can you bathe or dress yourself; can you climb several

flights of stairs; can you bend, kneel, stoop, lift or carry groceries, or heavy

objects? Do you experience depression, loneliness, tiredness or fatigue? Have you
                                                                                 142


felt downhearted and blue, or so down in the dumps that nothing could cheer you

up?

        These factors, that are not included within the dataset, further justify

going to the low explanatory model.          Any model of wellbeing of the aged which

has not included established factors of influence will not only reduce the power of

the explanatory model, but will be a good explanation of the phenomenon that is

being investigated. This is because those variables which are in the model will

explain an aspect of the quality of life of the aged, while the germane variables

which are excluded will significantly alter the degree of explanation that the

model will have.      In summary, because biological ageing is correlated with

functional disabilities and ailments, the exclusion of lifestyle behaviours,

psychological conditions (such as depression, despondence, and fatigue) and past

stock of health as well as religion, must substantially reduce the predictability of

the current model.

        A group of scholars (Hutchinson et al. 2004, 43) - although they did not

provide a mathematical model like the other aforementioned researchers – using a

sample of 2,580 Jamaicans (1,601 females and 979 males, with an average age of

29.7 ± 9.2 yrs; Range: 15 – 50 years) found that a number of socio-demographic

elements do influence psychological wellbeing. Gender, educational attainment,

employment status, union status, religiosity and self-esteem were factors of

psychological wellbeing (p value < 0.05), with age and church attendance not

being statistically significant variables.

        Using multiple regression analyses to establish the aforementioned
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predictors of psychological wellbeing and satisfaction with life, Hutchinson et al.

(2004) did not provide or use the explanatory power of the model.                  This

delimitation hampers the variance that can be explained by the predictive

variables. In addition to what was put forward earlier, the table that the researcher

cited from did not provide us with any beta (β) coefficients – for the linear

multiple regression – or Wald statistics for the logistic regression. It is difficult to

state the effect of each predictive factor of the dependent variable – in one case

this was psychological wellbeing and in another it was life satisfaction. The

application of multivariate analyses to observation survey data is of itself an

embodiment of the econometric model. And with this reality, Hutchinson et al’s

work is subjected to the same set of limitations that befall this current piece of

work. Despite the delimitations of all the models presented in this text, this piece

of work provides some premises which we are able to understand in attempting to

better the wellbeing of Jamaicans, in particular aged people. This now sets the

stage for an examination of the wellbeing of aged Jamaicans from the perspective

of econometric modelling.
                                                                               144


                                   Chapter Nine



        FINDINGS: SOCIO-DEMOGRAPHIC CHARACTERISTICS

                      OF SAMPLED POPULATION



The sample population consisted of 3,009 elderly Jamaicans (ages 60 years and

older). The mean age of the sample is 71 years 10 months ± 8 years 6 months

(Range= 39 yrs, with the maximum age being 99 years) (See Table 9.1.1). Males

constituted 47.3% of the sample compared to 52.7% of females. Disaggregating

the data revealed that 64.5% of the sampled population were young old, 26.4%

were old-old and 9.2% belonged in the oldest-old age cohort (See Table 9.1.1).

With regard to the sex composition of the surveyed population, the sex

distribution was relatively even. However, there was a substantial disparity in the

oldest-old age group where approximately two-thirds (65%) of the cohort were

females. (See Table 9.1.2)

        On an overall average the wellbeing of elderly Jamaicans is low, 3.8 out

of 14, with a mode of 3.5. The wellbeing index ranges from a low of -1 to a high

of 14 (Table 9.1.1). A score from -1 to 3 denotes very low, 4 to 6 indicate low; 7

to 10 is moderate and 11 to 14 denotes high wellbeing.

       Another point of emphasis is that the majority of the sampled population

dwells in rural areas (approximately two-thirds or 66.8%), and approximately

86% of the elderly population own their own home. In addition, less than 4% of

the surveyed population has attained post-secondary level education, with a high

of 63% having had primary level education (See Table 9.1.1).
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Table 9.1.1: Univariate Analyses of Variables used in Wellbeing Model


                                                                                   Percent (n)
Area of residence
       Rural Areas                                                        66.8 (2010)
       Other Towns                                                               21.1 (634)
       Kingston Metropolitan Area                                                12.1 (365)
Gender
       Males                                                                      47.3 (1423)
       Females                                                                    52.7 (1586)
Home Tenure
       Own                                                                         85.9 (2580)
       Rent                                                                         4.9 (147)
       Other (include squat, rent-free, and other)                                  9.3 (278)
Marital Status
       Married                                                                    40.4 (1192)
       Never Married                                                              29.3 (864)
       Divorced                                                                     1.8 (54)
       Separated                                                                    2.1 (63)
       Widowed                                                                    26.4 (778)
Environment
       Affected by landslide etc.                                                38.4 (1848)
       Not Affected by                                                           61.6 (1848)
Level of Education
       Primary/Prep. and below                                                   63.2 (1793)
       Secondary/high                                                            33.4 (949)
       Post-secondary (i.e. tertiary)                                             3.4 (97)
Elderly cohort
       Young-old (60 – 74 yrs.)                                                 64.5 (1940)
       Old-old (75 – 84 yrs.)                                                    26.4 (793)
       Oldest-old (85+ yrs.)                                                     9.2 (276)

Age (mean ± SD) 71yrs.10 mths. ± 8 yrs. 6 mths.

Crime Index (means ± SD) 1.2 (± 5.88), median = 0

Cost of Health Care (mean ± SD) $1,636.24 (± $3,224.99), median is $650.00

General Wellbeing 2 (mean ± SD) 3.9 ± 2.3; mode 3.5
Positive Affective conditions (mean ± SD) 2.9 ± 2.5; mode = 4
Negative Affective conditions (mean ± SD) 3.8 ± 3.2; mode = 0
Occupancy per room        (mean ± SD) 1 ± 1; mode = 1, range 11

2
  The index ranges from a low of -1 to a high of 14. A score from -1 to 3 denotes very low, 4 to 6
indicates low; 7 to 10 is moderate and 11 to 14 denotes high wellbeing.
                                                                                  146


 Table 9.1.2: Percentage of Sex of Respondents by Elderly Cohort

                                                             Elderly Cohort

                                                 Young-old     Old-old     Oldest-old
                                                 (60 - 74)     (75 – 84)   (85+)




                                                 50.0          44.9        35.1
                Male

Sex:

                Female                           50.0          55.1        64.9




Total                                            1940          793         276
                                                                            147




       Figure 9.1.1: Area of Residence by Sex of Respondents


       The majority of the sampled population lived in rural Jamaica (66.8%),

with 21.1% residing in other towns, compared with 12.1% who lived in the

Kingston Metropolitan Area (KMA) (Table 9.1.1).             When the data were

deconstructed by sex, marginally more females resided in rural areas compared to

their male counterparts. Marginally more females dwelled in rural areas and KMA

than in other towns (a 9.8% sex disparity) (See Figure 9.1.1).
                                                                                        148


Table 9.1.3: Percentage of Marital Status of Respondents by Elderly Cohort
                                                   Elderly cohort
              Details                Young old      Old-Old        Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)

                 Never married                   31.9            24.1                   25.7

                 Widowed                         17.6            38.4                   54.3

Marital status   Divorced and/or                  4.0                 4.4                2.3
                 separated

                 Married                         46.5            33.1                   17.7

                 Total                         1910               776                   265



A further decomposition of marital status revealed some interesting results. When

a cross tabulation was done for marital status and elderly cohort, the response rate

was 98.1%.       Of the young-elderly, 31.9% were never married, 17.6% were

widowed, and 4.0% were either divorced or separated, compared to 46.5% who

were married. Concerning the old-old, most of them were widowed (38.4%)

compared to 33.1% who were married elderly, and 24.1% were never married. In

the oldest-old group, on the other hand, more than half of them were widowed

(54%), 17.7% were married, with 2.3% being divorced and/or separated,

compared to 25.7% who were never married (Table 9.1.3).

         The majority of the surveyed respondents were living alone (i.e. one-

person households) 97.6%, while 1.7%            were in two-person households,

compared to 0.7% who indicated that they were in three-person households.
                                                                                149


         The composite Crime Index showed that on an average the number of

crimes witnessed or experienced by the household of the elderly in survey was

approximately one (± approximately six crimes), with a mode being 0 crimes.

         The psychological state of the elderly was subdivided into two categories,

(1) positive affective and (2) negative affective conditions.       Concerning the

positive affective conditions, the average score is approximately 3-point (± 2.5),

(moderate) with a maximum score of 6. The index ranges from 0 to 6, where 0 to

2 is low, 3 is moderate and 4 through 6 are high. In relation to the negative

affective conditions of the sampled population, the average score is approximately

4-point (± 3.1) (very low), with the least score being 0 and the most being 14,

while the total for the index is 19-point. Thus, the interpretation of this index is:

from 0 to 4 is very low, 5-8 is low, moderate is 9 through 12 and high is from 13

to 19.
                                                                                     150


Table 9.1.4: Percentage of Educational Level by Elderly Cohort

                                                        Elderly Cohort


               Details                 Young Old        Old-Old             Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)
                                                 61.3             65.2               70.7
               Primary and below
                                                 34.7             32.0               28.1
Educational    Secondary
Level                                             4.0                 2.8                1.2
               Tertiary

               Total                           1844               753                242



        Of the 3,009 elderly people in the survey, 2,839 of them were used for this

cross tabulation. Approximately 63% had attained at most primary level education

– the oldest-old (70.7%); the old-old (65.2%) and the young-old (61.3%). Only

3.4% had obtained post-secondary level education – with 1.2% of the oldest-old,

4.0% compared to 2.8% of the old-old (Table 9.1.4)
                                                                                  151


Table 9.1.5.i: Percentage of Area of Residence by Elderly Cohort

                 Details                                Elderly cohort


                                        Young Old       Old-Old          Oldest-Old
                                        (60 – 74 yrs)   (75-84 yrs)      (85+ yrs)
                                        65.9            67.3             71.4
                  Rural area
Area of
                                        21.2            21.4             18.8
Residence         Other Towns
                                        12.8            11.2             9.8
                  KMA

                  Total                 1940            793              276



           Of the sampled population of elderly Jamaicans (n=3009), most of them

resided in rural Jamaica 66.8% - the young old (65.9%), the old-old (67.3%), and

the oldest-old (71.4%).        Marginally more young-old dwell in KMA (12.8%)

compared to the old-old (11.2%), with the oldest-old accounting for 9.8% (Table

9.1.5.i)
                                                                                   152


Table 9.1.5.ii: Percentage of Area of Residence by Elderly Cohort
 Sex                                                             Aged Population
                                                                                    Oldest-
                                                         Young-Old     Old-Old       Old
 Male              Area of Residence   Rural Areas
                                                                69.2        70.2         69.1
                                       Other Towns
                                                                20.4        18.8         21.6
                                       KMA
                                                                10.4        11.0          9.3
                   Total                                        636         356           97

 Female            Area of Residence   Rural Areas
                                                                65.4        65.0         72.6
                                       Other Towns
                                                                21.8        23.6         17.3
                                       KMA
                                                                12.8        11.4         10.1
                   Total                                        615         437          179



Further examination of area of residence by elderly cohort with regard to sex of

the respondents revealed some interesting results. Initially the data indicated that

most of the oldest-old resided in rural areas. However, when area of residence

and elderly cohort was disaggregated by sex, the findings showed that marginally

more females within the oldest-old cohort dwelled in rural zones, with the most

for males being in the age cohort of the old-old (See Table 9.1.5.ii). The findings

depict that less than 13% of the elderly reside in the Kingston Metropolitan Area.
                                                                                      153


Table 9.1.6: Percentage of Elderly Receiving National Insurance Scheme (NIS)

                                                     Elderly Cohort
Details
                                        Young Elderly       Old           Oldest
                                                            Elderly       Elderly

                No                              94.5           91.4           92.8
NIS
               Yes                               5.5            8.6            7.2

Total                                          1930           793            276



Table 9.1.7.i: Percentage of Elderly Receiving Government or Private Pension by
Elderly Cohort

                                                     Elderly Cohort
Details
                                                         Old        Oldest
                                         Young Elderly Elderly      elderly
                                           (60 - 74 yrs)   (75 –    84   (85+ yrs.)
                                                           yrs)


                  No                          80.6           76.7            75.4
Pension
                  Yes                         19.4           23.3            24.6

Total                                          1931          793              276


          Approximately 7% of the sampled population received social security (i.e.

NIS). Most of those who received social security (i.e. NIS) were the old elderly

8.6%, with 7.2% of those who were oldest-old compared to 5.5% of the young-

old.    On the other hand, three times (20.9%) the number of the surveyed

population received private and/or government pensions. However, marginally

more of the oldest-old (24.6%) got private and/or government pensions compared
                                                                              154


to the old-old, with only 19.4% of the young-old receiving this pension (see

Tables 9.1.6 and 9.1.7.i)



Table 9.1.7.ii: Percentage of Sampled Population who Receive NIS by Pension
(Government or Private)

                                                      Pension
Details

                                              No                    Yes



               No                             94.5                  89.8
 NIS
              Yes                             5.5                   10.2

Total                                  2373                         626


Approximately 95% of elderly Jamaicans have not received private and/or

government pensions, nor have they received a pension from the National

Insurance Scheme (NIS) (Table 9.1.7.ii). Of the 626 elderly persons who declared

having received private or government pensions, only 10.2% have received both

NIS and private or government pensions. On the other hand, 90% of those who

received private and/or government pensions reported that they have not received

any NIS pension.
                                                                           155


Table 9.1.7.iii: Percentage of Sampled Population who Receive NIS by Area of
Residence

                                              Area of Residence
Details
                                     Rural Areas       Other Towns       KMA


             No                         95.0                 93.2         85.7
 NIS
            Yes                          5.0                  6.8         14.3

Total                                   2003                  633         363



Of the total number of rural residents (2003), 5.0% received NIS, compared to
6.8% of those who dwell in other towns, and 14.3% who live in the Kingston
Metropolitan Area (KMA) (Table 9.1.7.iii). On the other hand, Table 9.1.7.iv
revealed that 17.0% of rural elderly persons indicated having got private or
government pensions, compared to 31.1% of those who live in other towns, and
24.5% of those reside in KMA.


Table 9.1.7.iv: Percentage of Sampled Population who Receive Pension by Area of
Residence

                                              Area of Residence
Details
                                     Rural Areas       Other Towns       KMA


             No                         83.0                 68.9         75.5
 Pension
            Yes                         17.0                 31.1         24.5

Total                                   2003                 634         363
                                                                           156


Table 9.1.7.v: Percentage of Sampled Population who Receive NIS by Sex

                                         Sex
Details
                          Male          Female          Total


          No              93.0               93.9                         93.5
 NIS
          Yes              7.0               6.1                           6.5

Total                    1419              1580                          2999



In excess of 100 percent more aged Jamaicans received private and government
pensions (20.9%) compared to 6.5 % of those who received NIS pensions (see
Table 4.1.4v and Table 4.1.7vi). Based on Table 4.1.7 (v), more males received
NIS (7%) compared to 6.1% of females.


Table 9.1.7.vi: Percentage of Sampled Population who Receive Private Pension by
Sex

                                         Sex
Details
                          Male          Female          Total


          No               80.5              77.8                79.1
Pension
          Yes              19.5              22.2                20.9

Total                    1420                1580               3000
                                                                                     157


Table 9.1.8: Physical Health Status by Elderly Cohort

              Details                                   Elderly Cohort

                                       Young-Old        Old-Old             Oldest-Old
                                       (60 – 74 yrs)    (75-84 yrs)         (85+ yrs)

               Five conditions                    0.0                 0.0                0.0

               Four conditions                    0.3                 0.1                0.4


               Three conditions                   4.3                 8.9            12.4
Health
conditions                                                                           26.7
               Two conditions                    26.8             32.5

               One condition                      7.6                 9.8            13.2


               No condition                      60.9             48.7               47.4


               Total                            1910              785                266




In order to assess the health status of aged Jamaicans, a cross tabulation was done

between physical health status and elderly cohort. The findings show that 56.4%

of elderly Jamaicans did not report an illness, injury or ailment over the 4-week

period, with 8.7 % indicating having one ailment, 28.3% experiencing two health

conditions, and 6.3% reporting three, compared to 0.3% saying that they are

affected by four health conditions. Further analysis of the physical functioning of

elderly Jamaicans revealed that approximately 60.9 % of the young-old did not

indicate an illness, injury or ailment compared to 48.7% of the old-old, whereas

47.4% of the oldest-old did not report being affected by any form of injuries,

ailments or sicknesses. None of the sampled elderly Jamaicans reported having

suffered (or been affected by) more than four health conditions (Table 9.1.8).
                                                                           158




Figure 9.1.2: Percentage of Health Conditions Reported by Sex




Substantially more men (62.4%) reported not to have been affected by an illness

(or physical dysfunction) compared to females (51.0%). On the other hand, the

reverse was the case for two ailments. However, for more than two illnesses,

males in the survey reported more dysfunctions than their female counterparts.

(See Figure 9.1.2)
                                                                                 159


Table 9.1.9.i: Descriptive Statistics for Health Care Expenditure of the Elderly
Cohort

                                        Descriptive Statistics


 Elderly      N           Mean             Std. Deviation        Minimum   Maximum
 cohort

 Young-old
              594         1664.55          3495.80               .00       40500.00
 (60 - 74)


 Old-old
              329         1588.59          2906.37               .00       30000.00
 (75 -84)


 Oldest-old
              104         1625.35          2516.52               .00       17000.00
 (85+)


 Total        1027        1636.24          3224.99               .00       40500.00



         When the respondents were asked to report on the amount expended on

cost of health care (including hospitalization expenditure and medication) for a

four-week period, on an average elderly Jamaicans spent $1, 636.24 ± $3,224.99,

with the mode being $0.00. The most spent by an elderly person was $40,500.00,

and the least $17,000. From Table 4.1.9 (i), the young-old spent the most on an

average on health-care $1,664.55, followed by the oldest-old ($1,625.59) which

was less than the mean amount spent by the old-old ($1,588.59). Of importance

here is that the young-old spent more than the average amount spent by the

elderly population ($1, 636.24) (Table 9.1.9.i).
                                                                              160


Table 9.1.9.ii: Descriptive Statistics for Health Care Expenditure based on Area
of Residence

Area of           N               Mean         Std. Deviation     Maximum
Residence

Rural Area        758             1401.79      2154.68            23000.00


Other Towns       170             2504.84      5650.41            40500.00


KMA               99              1939.85      4017.50            30000.00


Total             1027            1636.24      3224.99            35000.00



Table 9.1.9.ii shows that the elderly in rural areas spent on an average $1,401.79
on health care with a maximum of $23,000, which is less than the overall average
of $1,636.84 compared to the elderly who reside in KMA, who spent on average
$1,939.85 while those who live in other towns spent on an average $2,504.84.
This means that elderly people who reside in other towns and KMA spent more
than the elderly who dwell in rural areas with residents in both KMA and other
towns having spent more than the general average.
                                                                              161


Table 9.1.9.iii: Descriptive Statistics for Health Care Expenditure based on Sex

                  N               Mean         Std. Deviation     Maximum


      Male        411             1,974.55     4,188.23           40,500.00
Sex
                  616             1,410.53     2351.47            28,750.00
      Female

Total             1027            1636.24      3224.99



On average, males spent $1,974.55 on health care compared to females who spent

$1,410.53. Based on Table 9.1.9.iii, the most that was expended on cost of health

care by females was $28,750.00 with males spending $40,500.00. It should be

noted here that only 34.1% of the surveyed population were used for this analysis.



        A small percentage, (17.5%), of the sample reported being employed

(n=527). Of the employed elderly, 71.9% were ‘young-old (i.e. ages 60 to 64

years), compared to 4.2% who were within the oldest-old age cohort. Further

decomposition of the aforementioned findings revealed that unemployment was

substantially a female phenomenon. Of the young-old who were employed

(n=379), 65.6% were males compared to 34.6% females. With regard to the

oldest-old who were employed, 59% were males with only 41% females. In

summary, the unemployment rate among the elderly was very high (82.5%), with

there being a gender bias against females in regard to employment.
                                                                                162


In an effort to understand the state of the Jamaican elderly, we examined the
relationship between the per-capita population quintile and age group. We found
that there is a statistical association between the previous mentioned variables (χ2
(8) = 17.72, ρ value=0.023 < 0.05). Although there is a relationship between the
mentioned variables, the association is a weak one (cc=0.77 or 7.7%). Thus, 1%
of the variance in the per-capita population quintile can be explained by a change
in age group of the individual.
    Further analysis of the per-capita population quintile and age groups revealed
that the young-old (ages 60 to 74 years) had marginally more people being
classified in the richest quintile compared to the other age cohorts. On the other
hand, significantly more of the oldest-old cohort (ages 85 years and over) were in
quintile 2, which denotes poor (see Figure 9.1.3).




Figure 9.1.3: Per-capita Population Quintile, by Age Group of Respondents
                                                                                163




Further analysis of the per-capita population quintile by age group of elderly,
when controlled by sex, revealed that there is no statistical difference based on the
sex of respondents. The cross-tabulations had values of χ2 (8) = 15.2, ρ
value=0.52 > 0.05 for males and χ2 (8) = 5.8, ρ value=0.67 > 0.05 for females. A
detailed report of the findings with regard to per-capita quintile, age group and
sex can be seen in Figure 9.1.4 below.




Figure 9.1.4: Per-capita Population Quintile, by Age group Controlled for Sex
                                                                                              164


                                      Chapter Ten


                   FINDINGS: The Multivariate Analysis


        The wellbeing of aged Jamaicans is expressed in the equation below:


W ii =ƒ (P mc , ED, A i , E n, G, MS, AR, P, N, O, H, T, V)                         [1]


        Individual wellbeing, Wi , is a function of cost of medical care P mc ,

educational level of the individual ED, elderly cohort A i , where i is 65 years and

over), the environment En, gender of the respondents G, marital status MS, area

of residents AR, positive affective conditions P, negative affective conditions N,

occupancy per room O, home tenure H, property ownership T, and crime and

victimization, V.


        From function (1), using the coefficients in Table 4.1.10, the result is a

linear function (2):

      W = α 0 + β 1 R + β 2T + β 3 E + β 4 H + β 5 M + β 6 P + β 7C - β 8A – β 9N – β 10O – β 11 Ec
(2)
            (Where α is the constant, and each β is the coefficient of each factor)


        The findings in Table 4.1.10 below, show that the wellbeing of Jamaica’s

elderly is determined by the following conditions: (i) physical environment; (ii)

psychological conditions; (iii) cost of health care; (iv) area of residence; (v)

elderly cohort; (vi) average occupancy per room; (vii) marital status; (viii)

property tax; (ix) crime, and (x) educational level. A few conditions were found
                                                                              165


not to have any statistical significance for wellbeing – such as the gender of the

respondents, and home ownership. These will be discussed in detail below.

Table 10.1.1: A Multivariate Model of Wellbeing of the Jamaican Elderly,
N=629
                               Model
         Dependent variable: Wellbeing of the Jamaican Elderly

Independent variables:                 Unstandardized     Standardardized
                                       coefficient        coefficient

Constant                                         2.628
Physical Environment                            -0.763*              -0.190
Positive Affective Conditions                    0.065*               0.085
Negative Affective Conditions                   -0.090*              -0.140
ln Cost of medical (health) care                 0.237*               0.148
Elderly                                         -0.024*              -0.098

Area of Residence
Rural Area****
Other Towns                                     0.859*                0.164
Urban Area                                      1.386*                0.154

ln Average occupancy per room                   -0.650*              -0.229
                                                                      0.110
Marital Status
Single****                                      0.428*
Divorced, separated, and widowed
Married                                         0.405*                0.102
                                                0.575*                0.122
Property ownership
Crime                                           0.041*                0.098
Sex                                              0.096

Home tenure
Squatted****
Rented                                            0.000
Owned                                            -0.702

Educational level
Primary and below
Post-secondary and secondary                     0.092
Tertiary                                        2.561*                0.173

R = 0.645, Adjusted R2 = 0.401
                                                                                  166


Error term = 1.56
F statistics [16,613] = 27.355, P= 0.001
* significant p value < 0.05
**** Reference group



         The model has a Pearson’s correlation coefficient of 0.645 (or 64.5%),

which means that the association between wellbeing and the selected factors used

in the model is a moderate one.        The adjusted coefficient of determination,

adjusted r2, (in Table 10.1.1) is 0.401 (or 40.1%). This denotes that a 1 percent

change in physical environment, psychological conditions, cost of health care,

area of residence, age of respondents, average room occupancy, marital status,

property taxes, crime and educational level in the predictor changes the predict,

and by 40.1 percent. This denotes that 40.1 percent of the total variation in the

wellbeing of elderly Jamaicans can be explained by the selected variables used in

the model. As such, the Model, Testing Ho: β=0, with an α = 0.05, the researcher

can conclude that the linear model provides the best fit to the data from an F value

[16,613] is 27.355, p < 0.05.

        Of the 12 selected variables that were used to test the general hypothesis,

10 were found to be statistically significant. These are as follows – (1) marital

status; (2) physical environment; (3) area of residence; (4) average occupancy per

room; (5) property ownership; (6) cost of medical (or health) care; (7)

psychological conditions, which include – (i) positive and (ii) negative affective

conditions; (8) crime, (9) a part of the educational attainment, that is, education at

the post-secondary level and (10) age of respondents. Thus, those that were not
                                                                               167


found to be factors are as follows – (1) sex of respondents; and (2) home tenure;

and (3) education at the secondary level.

       From the selected variables of this study, we have found that there are 10

factors involved in wellbeing. Wellbeing of the Jamaican elderly is affected by (i)

psychological conditions - positive and negative affective conditions; (ii) area of

residence; (ii) crime; (iv) marital status; (v) physical milieu; (vi) property

ownership; (vii) educational level; (viii) cost of health care, (ix) average

occupancy per room. The five most important factors impacting on the wellbeing

of the Jamaican elderly in descending order are as follows: Average occupancy

per room (β = -0.229), physical environment (β = -0.190), education (β = 0.173),

area of residence (β = 0.0.164); and cost of health care (β = 0.148). Thus, the

significance of this paper is that we now have a quantitative model that can be

used to evaluate the wellbeing of elderly Jamaicans.

       Disaggregating the data reveals some interesting results, such as, with all

other things being constant, the wellbeing of the Jamaican elderly is 3 out of 14

(i.e. low, within the bottom 25% of the wellbeing index). Of the 12 determinants

of wellbeing for the sampled population, 4 came up with negative associations

(i.e. physical environment, negative affective conditions, age of elderly, and

average occupancy per room), with 6 being positive. These are as follows – cost

of health care, area of residence, marital status, property ownership, educational

level and crime.

       W = 2.628+ 0.859Area_Residence2 + 1.386Area_Residence3 +
       0.575Property Ownership + 2.561Edu_ level3 + 0.237lncost of health care
       + 0.428marstatus1+ 0.405marstatus2+ 0.065Positive affective conditions
                                                                               168


       + 0.041Crime - 0.09Negative affective conditions – 0.763Environments –
       0.65lnaveraged Occupancy per room-0.024Age of elderly…………. (3)

       From the wellbeing model, the physical environment decreases the

wellbeing (Pearson Correlation = - 0.13, ρ value = 0.02) of the elderly by 0.763

units, being pessimistic about the present or future equally diminishes wellbeing

(Pearson’s correlation = -0.318, ρ value = 0.001) but by a small unit, 0.09. The

average number of people who occupy a room affects wellbeing negatively

(Pearson’s correlation = -0.367, ρ value = 0.001) by 0.650 units. On the other

hand, an optimistic elderly Jamaican is likely to increase (Pearson’s correlation =

0.25, ρ value = 0.001) his/her wellbeing by 0.065 units.

       Based on Table 10.1.1, the wellbeing of Jamaica’s seniors who are

divorced, separated and widowed is higher when referenced to those who are

single (Pearson correlation = 0.178, ρ value = 0.001), and for each time that the

elderly moves from never married to separated and/or divorced and toward

marriage, his/her wellbeing improves by 0.236 units. The model reveals that for

each time that the aged moves up the rung of the educational level his/her

wellbeing simultaneously increases (Pearson’s correlation = 0.109, ρ value =

.007) by 0.332 units. Although no statistically significant relationship was found

between owing a home and general quality of life (ρ value = 0.379), a positive

association existed between property ownership (Pearson’s correlation = 0.183, ρ

value = 0.001) and wellbeing by 0.575 units. This implies that those who own

property will have a higher wellbeing than those who do not, which includes land

and premises.
                                                                               169


       There was a positive association between area of residence and wellbeing.

Those of the surveyed elderly, who lived in other towns, when referenced to rural

areas, had a higher wellbeing by 0.859 units.     When KMA was referenced to

rural areas, the surveyed population dwelling in KMA had a greater wellbeing by

1.386 units. Based on unstandardized b values for area of residence, the elderly

who lived in KMA had a higher wellbeing than those who resided in other towns,

when these were referenced to rural areas.

       One of the paradoxical findings of this study was the association between

crime and wellbeing (Pearson’s correlation = 0.112, ρ value = 0.006). On the face

of it, it would seem as though there should be a negative relationship between

crime and wellbeing. However, in this study, the finding was the opposite

position. From the model, crime was + 0.041, which denotes that with all other

things being constant, a 1 percent change in crime will result in a direct increase

in wellbeing by 0.04 units. Embedded in this finding is a paradox, as crime is

committed to a greater degree against families with more material resources. It

should be understood here how wellbeing is constituted (50% of it is from

material possessions) with the higher number of possessions attracting more

crime. This same premise explains the positive relationship between the cost of

health care and wellbeing (Pearson’s correlation = 0.297, ρ value = 0.001). From

the model, a 1 percentage change in the cost of health care is explained by a 30%

higher wellbeing among the elderly. This suggests that ‘good’ health care can be

judged by higher income, or better affordability. A finding that should be noted
                                                                                 170


here is that as elderly people age (from young-old to old-old to the final stage of

oldest-old), (s) their health status falls (Spearman rho = -0.063, ρ value = 0.003).

          In wanting to understand why gender was not significant (ρ value =

0.127), the researcher used the ‘Independent Sample Test’ to measure whether

any difference existed between the mean wellbeing of men and women. The test

showed that the average (i.e. mean) wellbeing of men was approximately 3.8 (i.e.

3.7952) compared to that of approximately 3.8 (i.e. 3.8258) for females, with a

significance of 0.747 – Levene’s test, F=0.017, ρ value=0.896. From the findings,

only 26.7% (n=606) of the sampled population had never been married. It follows

that 77.3% (n=1614) of the sampled populace would have had been in a legal

marriage at some point, or are still in one. Hence, in establishing any difference

in wellbeing between the sexes, it can only be attained using those who were

never married, as this group would report differences in assets, income and so on.

          The independent sample t-test analysis (See Appendix VI) indicates that

292 never married males in the sample had an average wellbeing of 2.8 units, with

314 never married females having a mean wellbeing of 3.3 units, and that the

mean difference does differ significantly at the p value of 0.05 (note: ρ value =

0.001).     Levene’s test for Equality of Variance indicates that the never married

males and the never married females do differ significantly from each other (note:

ρ value = 0.001) in their level of wellbeing (Table 10.1.2). Therefore, there is a

difference in wellbeing between the sexes, in which females have a higher

wellbeing than males, but this is only identifiable for people who were never

married.
                                                                                    171


         It was found that there was no statistical association between loneliness

and wellbeing (ρ value = 0.3 > 0.05), but that it was correlated with union status,

paying property taxes and ownership of a home. Hence, when it was included

within the wellbeing model, union status came out not to be significant (ρ value =

0.3), and it was (ρ value = 0.001 < 0.05), with a contribution of 1.8% to the

general wellbeing. Another important finding was that vulnerability of females

was not significantly related to the wellbeing of the elderly (ρ value = 0.286 >

0.05).


APPLICATION OF THE WELLBEING MODEL:

         W   = 2.628+ 0.859Area_Residence2 + 1.386Area_Residence3 +
         0.575Property Ownership + 2.561Edu_ level3 + 0.237lncost of health care
         + 0.428marstatus1+ 0.405marstatus2+ 0.065Positive affective conditions
         + 0.041Crime - 0.09Negative affective conditions – 0.763Environments –
         0.65lnaveraged Occupancy per room-0.024Age of elderly…………. (3)


Scenario 1: What is the Wellbeing of an Elderly Person who Lives in Another
Town or in KMA?

Table 10.1.3: Difference in Wellbeing of Jamaican Elderly based on Area of
Residence (assume that only Area of Residence changes in equation 3)


                       Dwell in Other Towns    Reside in KMA
Constant           2.628                       2.628
Area of Residence:
    0.859*AR2      0.859                       -
    1.386*AR3      -                           1.386

Wellbeing              3.487                   4.014


Wellbeing Index Scale: very low - from 0 to 3; low - 4 to 6; moderate 7 to 10 and high
11 to 14.
                                                                              172


Generally, the wellbeing of the Jamaican elderly is very low (approximately 3,
with all things being equal or constant). However, from Table 10.1.3, a score of
3.5 denotes low wellbeing for an elderly person who dwells in other towns, in
reference to rural areas, compared to 4 (i.e. low wellbeing) for an elderly person
who resides in KMA with reference to rural dwellers. It should be noted that
while the wellbeing of an aged Jamaican is very low, an elderly person who lives
in KMA on an average will have the highest wellbeing among those who live in
different regions in Jamaica.
                                                                                  173


APPLICATION OF THE WELLBEING MODEL:

       Scenario 2 Assume that elderly persons 1, 2 and 3 were not affected by
       any adverse physical environment conditions; the three elderly persons are
       all positive about life, elderly person 1 is 70 years old, elderly person 2 is
       81 and elderly person 3 is 65 years old. Calculate the wellbeing for each
       elderly person. It should be noted that all other things were constant.

Table 10.1.4: Wellbeing of different elderly persons based on years lived
                                        Model

                                                Elderly 1       Elderly 2       Elderly 3

Constant                                              2.628          2.628           2.628
Physical Environment             -0.441xEn                0              0               0
Positive Affective                 0.065xP            0.065          0.065           0.065
Conditions
Negative Affective                -0.090xN                  0               0               0
Conditions
lnCost of medical                0.237xP mc                 0               0               0
(Health) care
Area of residence                0.816xAR                  0             0               0
Elderly                          -0.024xA i            -1.68        -1.944           -1.56
lnAverage occupancy               -0.766xO                 0             0               0
per room
Marital Status                   0.236xMS                   0               0               0
Home tenure                        0.637xT                  0               0               0
Crime                              0.041xV                  0               0               0
Educational level                0.332xED                   0               0               0

Total Wellbeing                                       1.013        0.749            1.133


Wellbeing Index Scale – Very low - from 0 to 3; low - 4 to 6; moderate 7 to 10
and high 11 to 14.


Based on Table 10.1.4, with the given stipulated scenario, all the aged Jamaicans
in this case have a very low wellbeing. However, elderly person number 2 who is
the oldest has the least wellbeing, 0.749, compared to the wellbeing of elderly
person number 1 (1.013), and the highest wellbeing is had by the youngest elderly
person (1.133). It should be noted here that by varying the positive affective
condition and age of the elderly, the difference in wellbeing is minimal.
                                                                          174


Table 10.1.5: Decomposing General Wellbeing Model: Physical Functioning
Model, N= 629
                                Model
   Dependent variable: Physical Functioning of the Jamaican Elderly

Independent variables:                Unstandardized   Standardardized
                                      coefficient      Coefficient

Constant                                      -1.628
Physical Environment                          -0.039
Positive Affective Conditions                 0.016*              0.092
Negative Affective Conditions                 -0.001
lnCost of medical (Health) care               -0.019
Elderly                                      -0.007*             -0.134

Area of residence
Rural Area
Other Towns                                    0.011
Urban                                         -0.041

lnAverage occupancy per room                   0.034
                                              -0.042
Marital Status
Single****
Divorced, separated or widowed
Married                                       -0.049

Property ownership                              0.01
Crime                                          0.002
Sex                                           -0.029

Home tenure
Squatted***
Rented                                         0.000
Owned                                          0.206
                                                                 -0.123
Educational level
Primary and below****
Post-secondary and secondary                 -0.115*
Tertiary                                       0.165

R = 0.237, Adjusted R2 = 0.032
F statistics [16,613] = 2.284, P= 0.003
* significant p value < 0.05
**** Reference group.
                                                                                 175


Of the 12 selected variables used in general wellbeing, 4 of them were not

significant. These were (1) home tenure; (2) age of respondents; (3) sex of

respondents and (4) a part of education – secondary level education. However,

when physical functioning was used to evaluate the wellbeing of the surveyed

population, only 3 of the 12 selected factors were statistically significant. These

were (1) age of respondents, and (2) part of education – education level 2, and

positive affective conditions.

       Based on Table 10.1.5, of the three factors of physical functioning of an

aged elderly person within the survey, age is the most influential factor followed

by education at secondary level with reference to primary education, and finally

positive affective conditions. It should be noted here that there is a direct

association between age and physical dysfunctions, primary level education and

an increase in health conditions.     However, being optimistic about life (i.e.

positive affective condition) will reduce physical dysfunctions.

       From the results in the regression model in Table 10.1.5, physical

condition is a difficult proxy of wellbeing of the Jamaican elderly (i.e. adjusted r2

is 3.2%, meaning that the model only explains approximately 3% of the variance

in wellbeing, using physical functioning to proxy quality of life of the surveyed

elderly people.
                                                                         176


Table 10.1.6: Decomposing General Wellbeing Model: Economic Model, N=629
                             Model
   Dependent variable: Economic Wellbeing of the Jamaican Elderly

Independent variables:               Unstandardized   Standardardized
                                     coefficient      coefficient

Constant                                      8.170
Physical Environment                        -1.580*             -0.190
Positive Affective Conditions                0.192*              0.124
Negative Affective Conditions               -0.171*             -0.133
lnCost of medical (Health) care              0.477*              0.146
Elderly                                     -0.056*             -0.113

Area of Residence
Rural Area****
Other Towns                                  2.073*              0.197
Urban                                        3.056*              0.181

lnAverage occupancy per room                -1.248*             -0.216

Marital status
Single****
Divorced, separated or widowed               0.862*              0.106
Married                                      0.807*              0.102

Property ownership                           1.286*
Crime                                        0.082*              0.097
Sex                                           0.214

Home tenure
Squatted****
Rent                                          0.000
Owned                                        -0.856
Educational level
Primary and below****
Post-secondary and secondary                  0.270
Tertiary                                     4.275*              0.153

R = 0.654, Adjusted R2 = 0.413
Error term = 3.04
F statistics [16,613] = 28.66, P= 0.001
* significant p value < 0.05
**** Reference group
                                                                               177


Based on Table 10.1.6, using economic resources (including income, and material

resources excluding owning a home) to evaluate the wellbeing of the surveyed

population, only 3 of the 12 selected factors were not statistically significant.

These were (1) home tenure (i.e. dwelling), (2) part of education – education level

2, and (3) sex of respondents.

       The model explains 41.3% of the variance in economic wellbeing of the

surveyed elderly population.     The five most important factors of economic

wellbeing are: average occupancy per room (β = -0.216); area of residence (β =

0.197); physical environment (β = -0.190), education (β = 0.153), and cost of

health care (β = 0.146). It should be noted here that the five most important

factors of economic wellbeing are the same for general wellbeing. What does this

mean? Generally, using economic wellbeing to operationalize wellbeing is a

better measure to proxy the wellbeing of the Jamaican elderly than physical

functioning. Based on Table 10.1.6, the model explains 41.3% of the variance in

wellbeing of the surveyed population. This is more than the composite model that

explains 40.1% (see Table 10.1.1).
                                                                                178


                                Chapter Eleven

                                      EPILOGUE


        Population ageing is synonymous with an increase in certain health

conditions (i.e. diabetes mellitus, hypertension, heart diseases, cerebrovascular

and cardiovascular diseases and acute respiratory infections), and it is not limited

to developed nations, but is equally a reality for developing countries. Greying

of a population is also a Caribbean phenomenon (Barbados, Trinidad and Tobago,

Cuba, and Suriname), and a similar situation has been observed in Jamaica. Since

the 1960s, population ageing has been a reality in Jamaica. Public health and

reproductive health measures are primarily responsible for population ageing in

Jamaica, and could be as a result of improvements in the standard of living of the

general populace.   Society has been experiencing reduced birth and death rates

and while net migration has been negative since the 1940s with a few exceptions,

an influx of return migrants at older ages (retirement ages) is helping to increase

the number of ageing Jamaicans. Reference to ageing in many societies

sometimes conjures up different images of social negatives (i.e. ageism);

however, this text does not seek to examine ageism; instead the author is

concerned about the determinants of wellbeing in order that they may guide the

National Policy for the Aged.

        Based on the National Population Policy of Jamaica which was revised in

1995, quality of life is an important condition which the nation seeks to achieve in

the future. In order to attain this objective of improvement in the quality of life,
                                                                                179


we need to examine and understand the possible factors that influence wellbeing

in Jamaica.

        The Planning Institute of Jamaica (PIOJ) has been collating data on the

health status of Jamaicans, but this has only been done for certain age cohorts.

Although life expectancy is high in Jamaica and owes itself to sanitation, water

quality, public health improvements, vaccination, and reduced chronic illnesses,

the elderly are still a vulnerable group. The PIOJ (2005) reported that 60 percent

of admissions to public health facilities for chronic ailments were senior citizens.

While the aforementioned issue provides some knowledge about the wellbeing of

aged Jamaicans, it does not open a comprehensive insight on the matter. In 2008,

the Planning Institute of Jamaica and the Statistical Institute of Jamaica’s report

(JSLC 2007) revealed that 40.2% of elderly people reported a health condition in

the last 4 weeks, with 75.1% of them indicating that this condition was a recurrent

one. Although life expectancy has been increasing and will continue to increase,

so are self-reported illnesses. In 1997, self-reported illness was 22.6% and in

2007, it increased by 93.8%, which was 2.8 times more than the overall self-

reported illness of the population. Concurrently, 71.6% of elderly Jamaicans

sought medical care in 2007, compared to 66.0% of the general populace, while

Powell, Bourne and Waller’s research in 2007, using a nationally representative

stratified probability sample of 1,338 Jamaicans, found that the subjective

wellbeing of the age cohort was very high (7.1 out of 10 ± 1.5), which does not

concur with this study – 3.9 out of 14 ± 2.3. Continuing, from this study we know
                                                                               180


that 56.4% of elderly Jamaicans did not report a health condition, and 28.3%

indicated 2 conditions, compared to 6.5% who reported 3 or more illnesses.

         The difference in the outcome of wellbeing between the two

aforementioned groups can be due to the operational definition in each case.

Powell, Bourne and Waller used a Likert scale of Abraham Maslow’s needs to

evaluate wellbeing, which is in keeping with a multidimensional approach to the

assessment of quality of life, while the current study used material possessions

and self-reported health conditions. This disparity cannot be resolved in the

current work as this was not the purpose of the study; the focus was on factors

that can predict (or determine) the wellbeing of aged Jamaicans. What determines

the wellbeing of aged Jamaicans, and their relative importance?

        This study provides a broad range of health or wellbeing factors regarding

elderly Jamaicans, and these include psychosocial factors. Household crowding

was found to be the most influential predictor of wellbeing in elderly Jamaicans,

followed by physical environment, tertiary level education and area of residents.

The rural elderly had the least wellbeing compared to aged people who resided in

other towns or urban areas. Aged residents of other towns had the greatest

wellbeing of all other elderly residents in Jamaica.

        In 2007, medical practitioners were still utilizing the biomedical model as

the chief approach to the examination of patient care (see Ali, Christian and

Chung 2007). The expert scholars and practitioners identified that the elderly

person was faced with multiple medical conditions, but in the entire ‘case history’

nothing outside of medical problems was investigated, in an attempt to
                                                                                181


comprehend the complexities of a case that has gone on for many years. With the

study conducted by Ali, Christian and Chung (2007), the authors recognized that

some of the features of ‘epilepsy’ in the elderly, more so than the young, are

confusing to present day medicine. Although medical practitioners were confused

by the number of failed trials in attempting to address the conditions of elderly

patients, they continued without any inclusion of possible factors which were

outside of medical sciences. And then the medical doctors argued that they had

cured the patient, and made the statement that:

        The stereotyped nature of the events was recognized and initiation of
        antiepileptic drug treatment resulted in the complete cessation of events
        and the return of an acceptable quality of life. (Ali, Christian and Chung
        2007:379)


        Inherent within the perspective of Ali, Christian and Chung is the direct

association between the absence of ailment and quality of life. This argument is

not only old but is equally not in keeping with the expanded definition offered by

the WHO in 1948. It is accepted by these scholars that no hospitalization because

of the absence of ailment is an indicator of improvement in wellbeing (or quality

of life). The issue of freedom from hospitalization or disease does not imply the

‘return of an acceptable quality of life’, as humans are multidimensional, and so

should not be linked to one single factor in explaining wellbeing.

        However, increased hospitalization of aged Jamaicans (i.e. according to

PIOJ 2005, 23.13, 60% of admission to hospitals for chronic diseases are elderly)

due to health conditions, are indicators of the erosion of the health status of this

age cohort, and by extension some degree of the quality of the life of people 60
                                                                                  182


years and beyond, but the wellbeing of this group goes beyond this one-

dimensional tenet. With 10.7% of the total population of Jamaica being elderly

people, 40.2% reported ill-health, 75.9% of those with dysfunctions indicated that

they were recurrent, and the reality of the possibilities of medical issues as well as

the cost of health care should be enough reasons for the study of the wellbeing of

this age cohort. But the issues surrounding age are not limited to those conditions

as the elderly require retirement planning and spending, as well as changes in

population composition and structure. It is clear from within the tradition of

Western culture that our emphasis is on medical conditions or the over

applicability of the biomedical model, despite the contributions of the WHO,

Grossman and other scholars that this conceptual definition is too narrow and

does not capture the multidimensional tenet of humans. Thus, it begs the question,

what about the sociopsychological and ecological issues, and do they affect the

quality of life of elderly people?

        Hence, this study is timely as it provides an analysis of the wellbeing of

our elderly. There is a cultural belief that aged people are among the most

vulnerable within all societies, and this is equally so in Jamaica. This assumes

that on an average the quality of life of this cohort of people is lower than that of

the economically and physically active population. This study concurs with the

overall suspicion of Jamaicans that the aged constitute a vulnerable group (the

average wellbeing of Jamaicans is 3.9 out of 14 – low wellbeing with a mode of

3.5). The research went further than computing a general self-reported index of

wellbeing, to build a model which constitutes demographic, psychosocial and
                                                                                 183


ecological variables that can be used to determine the quality of life of elderly

Jamaicans.

       Now, a study exists that measures the wellbeing of old aged Jamaicans.

The perspective from which quality of life is operationalized is different from its

predecessors in Jamaica, as it encompasses biological, socioeconomic,

psychological and ecological conditions.      The study finds that 40.1% of the

variation in aged peoples’ subjective wellbeing is explained by the 10 factors.

The model is comprised of eleven determinants which are as follows – area of

residence, environmental conditions, educational attainment of the person, cost of

health care, marital status, psychological conditions (i.e. positive and negative

affective conditions), age, crime, average occupancy per room and property

ownership. Of the major determinants, the five most important determinants are

average occupancy per room, area of residence, cost of health care, positive

affective conditions, and property ownership. It should be noted here that the

factor which most affects the subjective wellbeing of aged Jamaicans is average

occupancy per room, which implies that they prefer their own personal space.

Then, the region in which the elderly person dwells as in Kingston Metropolitan,

other towns or rural areas, makes a difference with regard to wellbeing. Those

aged Jamaicans who live in rural areas had the least wellbeing, compared to those

who reside in the Kingston Metropolitan Area, who had the highest quality of life.

In addition, cost of health care plays the second most influential role, which

means that wellbeing can be bought followed by positive affective conditions.

The positive cognition of individuals has a direct bearing on the quality of life, as
                                                                                   184


it acts through self-actualization, self-esteem, self- fulfilment and attitudes that are

agents of higher wellbeing. The paying of property taxes which is a proxy for

land ownership plays the fifth most important role in determining wellbeing. This

implies that the holder of more property has a greater wellbeing compared to an

aged person who owns less property or none at all.

       Despite the five most influential factors that determine the wellbeing of

aged Jamaicans there are some that are equally significant, but play a lesser role

than the five conditions that were previously mentioned. The findings show that

both the age of the respondents and negative affective conditions are inversely

related to quality of life. It follows that the older an individual becomes the lower

the quality of life he/she will have. An important finding is that individuals with

negative affective conditions such as hopelessness or pessimism will have a lower

wellbeing, as their attitude will result in stressors, inabilities, disabilities and

unhappiness, which are negative determinants of wellbeing. Crime, which has

become a staple in the Jamaican society, is the seventh condition affecting the

quality of life of aged people. This finding shows that it is positively related to

wellbeing, which means that more crimes are experienced by aged Jamaicans with

more resources. On the other hand, marital status and environmental factors are

inversely related to quality of life. The variable which contributes the least to the

wellbeing of the elderly is marital status followed by environmental conditions.

       Pacione (2003) has generalized that environmental quality plays a

significant role in determining the quality of life of people. This, he argues,

results from population density, crowding, poor housing, design of built
                                                                                   185


environment, temperature, and pollutant levels which may result in fatigue and

reduced ability to cope with issues that influence wellbeing. Because the human

body relies on the environment for oxygen, and indeed for survival, airborne

pollutants will affect the quality of life of aged people, as the biological process is

influenced by the environment (Eldemire 1994). Airborne particles can cause

respiratory or cardiovascular illnesses that substantially plague the elderly

(Cajanus 1999) and are a reason for the deaths in this age cohort (O’Neil et al.

2007; American Thoracic Society 2002). Another scholar went further in the

process, generalizing that people between 65 and 74 years, following exposure to

air pollutants, had a higher death rate than children of less than one year (Sastry).

Where the literature has clearly indicated a correlation between the environments,

this study concurs with them, but must say that it is the least factor in predicting

the subjective wellbeing of the Jamaican elderly.

       Having identified that the wellbeing of aged people is influenced by a

number of conditions, from the explained variation of 40.1%, may one be tempted

to argue that the model is useless or of little significance, as the unexplained

events are still to be investigated and are not found? A number of rationales

justify such a finding. But before they are embarked upon, this study must be

properly contextualized within a broader framework, as it has external validity.

A similar study called the SABE project, conducted in Barbados in 2005 by

Hambleton et al., found that 38.2% of the variations in the quality of life of aged

Barbadians (ages 60 or over) are explained by the model of determinants. Those

factors include lifestyle behaviours (exercise, conditions relating to smoking or
                                                                                 186


non-smoking), historical conditions (such as socioeconomic experiences early in

life), diseases, and current socioeconomic conditions (e.g. education of family

members, household room density, and all sources of income – including

pensions, retirements and social networks). Thus, this study is in keeping with

what exists in Barbados and is therefore a platform upon which further

investigations should be launched, with the inclusion of all other germane factors

that were omitted in these two works.

       The literature has shown that wellbeing is influenced by educational

attainment (Koo, Rie, Park 2004; Ross and Mirowsky 1999; Preston and Elo

1995; Smith and Kington 1997) which is also agreed on by this project. This

study concurs with Koo, Rie and Park that education is a predictor of subjective

wellbeing, but equally agrees with Roos et al.’s work (2004) that the association

is small (Pearson’s correlation = 10.5%). Based on the model of this study,

education is the ninth influential variable out of 11 on the subjective wellbeing of

aged Jamaicans. It should be noted that the relationship between educational

attainment and years of schooling is not a linear one. A recently conducted

research project disagreed with the aforementioned scholars, as the researchers

found a linear statistical correlation between self-rated wellbeing and education of

the youth and elderly (Bourne and Eldemire-Shearer 2009a). There is clearly a

disparity between the two studies, as the latter examined the youth and elderly and

not the entire population, whereas the former study investigated a population, and

this can offer some explanation of the middle age group (ages 26 to 59 years).
                                                                               187


         Ross and Mirowsky (1999) find that the well educated are more likely to

exercise, and that they are likely to be moderate drinkers and that they practice

more whole lifestyle behaviours, which are all factors that influence wellbeing

(see Hambleton et al. 2005). Owing to the limitation of this study, in that no data

were available on lifestyle risk behaviour, these were not included within the

model, and so validation of this fact was not possible. Another channel through

which education influences quality of life is occupation and employment.

         The SABE’s project used occupation and employment within its model,

which could further justify the difference of 1.4% in the explained variation (i.e.

36.8% - for this study and 38.2% for SABE’s project). Although employment

status was in this dataset, it could not be used in the model, as only 22.3%

(n=518) of the sampled elderly were employed, with a non-response rate of

77.2%.     Employed people 65 years or over are within different occupational

types, but from the high percent of missing data, it had to be omitted from the

model. Occupation is an indicator of social class and/or societal standings

(Palmore 1981) and so with such a high valuation of non-responses for the

employed sampled population, there was no sense in including this factor as well.

Thus, these two factors were excluded from the final model, but based on the

literature they are equally important determinants of health status and subjective

quality of life (see Adler and Newman 2002; Palmore 1981). Adler and Newman

2002 found that the health status of the employed is higher than that of the

unemployed, but this could not be collaborated by this research, as they were not

used.
                                                                              188


       Apart from the direct association between occupation, education and

quality of life, Adler and Newman argue that education and occupation are

complex determinants in relation to their association with health status. This

happens in that education and occupation are strong predictors of income, social

class, ability to access information and certain resources that are themselves

factors of wellbeing. Social class, occupation and typologies of employment

status are indicators of marital status, which takes the researcher to the next

factor, marital arrangement.

       Moore et al.’s work (1997) shows that people who dwell with their

spouses, compared to those who reside alone, enjoy higher subjective wellbeing.

This research also agrees with studies by Moore et al, Smith and Waitzman

(1994) and Delbes and Gaymu (2002) in that higher subjective wellbeing is

experienced by married couples compared to other union typologies. Roos et al.’s

study (2004) justifies this situation, when they show that couples practice less

risky lifestyle behaviours, and eat better, and Smith and Waitzman (1994) add that

wives are more likely to have their husbands seek preventative care, although this

may go against the male’s socialization. To further understand the role of marital

status, Elwert and Christakis’ work (2006) is fitting here. They find that after

bereavement, mortality is higher among the sexes (also see Baro 1985), which

means that separation by death or other eventualities such as divorce will

influence subjective wellbeing and further justify a higher quality of life for

married people, as compared to non-married individuals. Even though there was a

clear association between marital status and the subjective wellbeing of elderly
                                                                                 189


people, it was a low one (β = -0.088), which means that it contributed second to

the least to the quality of life of aged people. Generally, marriages in Jamaica are

between males and females, and so this begs the question - is there a difference

between the subjective wellbeing of the sexes?

       One of the contradictions of this study is the fact that gender was not

found to be a factor in determining the subjective wellbeing of elderly people.

Such a finding means that there is no statistical difference between the quality of

life of a male or a female (ρ value = 0.127).         The literature, however, has

demonstrated that the economic wellbeing of males is greater than that of their

female counterparts (Rudkin 1993). Haveman et al.’s work (2003) finds that the

material resources of retired men are greater than those of females, which goes

further to justifying why their economic wellbeing is higher than that of their

female counterparts. Schoen et al.’s study contradicts the general hypothesis that

males’ health status is greater than females, by arguing that men are more stressed

and so they are less healthy. Herzog (1989) analyzing ‘physical and mental health

in older women’ concludes that the rate of depression for females is higher than

for males, which contravenes Schoen et al.’s work. What this research concludes

is that there is a statistical difference between the wellbeing of the sexes, but that

it is for single people (Levene’s Test F=12.41, ρ value = 0.001).

       In this study, the wellbeing of single aged females is higher compared to

that of single aged males. Unlike studies that use income (or GDP per capita) to

evaluate wellbeing, or illnesses/ailments and disabilities to measure health, this

work twins both factors in its assessment of a subjective wellbeing index. This
                                                                                 190


difference may not have emerged because approximately 73% of the sampled

population was married at some point or they are still married, and such unions

share income and material possessions including durable assets. Therefore, the

differences between gender wellbeing may be problematic as household income

and other resources are reported jointly. However, there is a clear distinction

between the incomes of single persons; reported items are for a specific individual

and not joint custody.

       On the issue of possessions, the ownership of houses that is established in

the literature as having an influence on wellbeing did not turn out to be so for this

study (ρ value = 0.379 > 0.05). The works of Barresi et al. (1983) and Breeze et

al. (2004) have categorically showed that aged people who possess their own

homes experience greater wellbeing than those who pay rent or lease their

dwellings. Breeze et al.’s work, using medical data in Britain, finds that seniors

who own their homes are less likely to report poor quality of life. Within the

context of Jamaica, elderly people are less likely to view a home as a tool for

investment; as such, they use their homes as collateral. Thus, the house is seen as

a piece of property that must be left for the upcoming children. In addition, with

67.8% of the sampled population residing in rural areas, a house is less likely to

generate income (i.e. rent) than in urban areas, which further justifies why paying

property taxes was significant related to subjective wellbeing. The paying of

property taxes by elderly Jamaicans was a proxy variable for land ownership.

Land in rural Jamaica is more an investment, which the elderly are able to use for
                                                                                 191


income generation. In addition, land ownership in rural Jamaica is used as a

measure of social status which further brings about a certain psychological state.

       On the matter of psychological state, which may be either positive or

negative affective, Lyubomirsky (2001) shows that happier people view life in a

positive manner. This attitudinal state explains how decisions are taken, and

moods are experienced. A positive mood provides a better quality of life, as the

individual thinks, acts, builds and carries out his/her life’s task with more self-

assurance (Leung et al. 2005).      The opposite is equally so, as a pessimistic

individual is more likely to have lower self-esteem, self-fulfillment, and be less

self-actualized than someone who is optimistic. DeNeve and Cooper (1998) find

that happier people are more optimistic and positivistic in nature. Diener and

Seligman (2002) point out that moods are not stationary, and so happy people can

have negative moods, which means that positive individuals do not dwell on the

negatives indefinitely.   Harris et al’s work     (2005) establishes that negative

affective conditions such as guilt, fear, anger and disgust inversely affect

subjective wellbeing, as positive factors directly influence wellbeing (also see

Fromson 2006). The literature has shown that the elderly seek more health care

than any other age cohort, and so the issues of biological conditions will result in

a certain psychological state, where, if an elderly individual does not perceive that

he/she has control over illnesses or disabilities, it may result in self-destructive

behaviour (McCarthy 2000), which will influence his/her wellbeing. McCarthy

offers a further justification for the correlation between psychological state and

subjective wellbeing, when he writes that diabetic patients are six to seven times
                                                                                192


more likely to suffer from psychiatric illnesses, anxiety and depression. In this

research, however, the ranking of positive affective conditions and negative

affective conditions was different, as the positive affective was the fourth most

influential determinant of wellbeing, whereas the negative affective condition was

the sixth of 11 determinants. Although scholars did not distinguish between the

positions of each, being happy and optimistic contributes more to one’s subjective

wellbeing than being negative, which reduces it. Religion is one factor that

fosters optimism (or a positive attitude to life’s challenges) – (also see Wiegand,

and Weiss 2006).

        Like Marx, the researcher believes that religion is a tranquilizer to many

realities. Religion is not merely a practice but it is an institution with tenets,

which teaches one to put a greater value on future life. Within this setting, people

are able to endure present difficulties for the promise of future pleasure, as the

opportunity cost of foregoing for futuristic immortality in peace, prosperity and

affluence is greater than the cost of earthly pleasures. Thus, by accepting religion

within the Jamaican society, the individual is socialized to pass all his/her

‘troubles’ on to God. In addition, he/she is culturalized to accept his/her present

situation as Robert Nesta ‘Bob’ Marley argues “for every little thing is going to be

alright”.   This reality symbolizes the optimistic attitude that is adopted for

survival (Diener, Suh and Emmon 1984), so it should come as no surprise that

religion should have a positive influence on subjective wellbeing. Scholars like

Frazier et al. (2005), Edmondson et al. (2005) and Kart (1990) have all agreed

that the influence of spirituality on wellbeing is definite.    The belief is that
                                                                               193


through religion, many behavioural habits such as heavy drinking of alcohol,

smoking and unhappiness are averted (Kart 1990). One researcher found that

cancer rates were lower in people who accepted spirituality than those who did

not (Gardner and Lyon 1982a, 1982b). Those studies are all on non-Caribbean

geo-political spaces and a research done by Hutchinson et al. (2004) on Jamaicans

concurred with the findings in other geographical locations. They found that

religiosity was positively related to the psychological wellbeing of some 2,580

respondents.

       Church attendance (or frequent visits or religiosity – that is not based on

special occasions such as weddings, funerals, christenings, baptisms, graduations

and other such events) is singly not only about a positive mindset, but the church

is a meeting place for the elderly and a source of emotional and financial support.

As such, when an elderly person becomes involved in high religious activities,

he/she becomes a part of a body of similar-minded individuals, who share, care,

and are equally concerned about the self-development and self-needs of the

elderly. Even the nature of prayer with or among people is another technique for

reducing blood pressure (Callender 2000), which affects the health status as well

as the subjective quality of life of the elderly. It follows that religion and/or

religiosity is an important predictor of wellbeing (also see Watt, Dutton, and

Gulliford 2006), but it could not be investigated within this study because it was

not available in the dataset, and so this may further explain the high-unexplained

variation of the model.
                                                                                194


       This study has expanded on Smith and Kington’s model by adding a

number of new factors such as crime and victimization, positive and negative

affective conditions, ecological factors, area of residence, and age of respondents.

Another important inclusion in this model is how wellbeing was constructed, as

demographers (see Crimmins, Hayward and Saito 1994) use functional ability

(i.e. health status) to evaluate wellbeing, and so do Smith and Kington, while

economists use income per capita. However, for this study wellbeing was

considered to be a composite value of health status and income. This definition,

therefore, is a cross between what the economists use (i.e. income) and what

many demographers use - functional ability. A critical finding in this paper is that

using self-reported health status to measure wellbeing is problematic, and that an

objective approach is a better yardstick than subjective health conditions. Owing

to the limitations of the dataset, the researcher did not use some of their

determinants. The examples are as follows – previous health status (i.e. stock of

health), lifestyle behaviours and religion or religiosity. Those exclusions from the

model definitely explain the reason behind the low explanation valuation for this

project. While this study or the SABE’s project may not have fully provided a

statistically strong explanation of the quality of life of the aged in either of the

two societies, we are sure that the subjective wellbeing of aged people is affected

by biological, psychological, socioeconomic and ecological conditions, and that

these studies can be a platform for further work to be carried out.

       The current work has shown that using self-reported health conditions to

conceptualize wellbeing is not a good approach, as its explained variance is 2.4%,
                                                                                195


which is lower than that of an objective approach (40.1%). Despite the lesser

explanatory power of a subjective assessment of wellbeing compared to an

objective evaluation, the former is more in keeping with a multi-disciplinary

perspective on humans, as was offered by the WHO in the Preamble to its

Constitution in 1946, and equally supported by Dr. George Engel. In addition,

psychosocial and ecological conditions do influence the composite wellbeing of

the elderly in Jamaica. A rationale that can justify the low power for the

subjective assessment of wellbeing is the difficulty of measuring it precisely as

against the objective assessment of wellbeing in which each factor is

operationalized and measured with a greater degree of precision. This does not

militate against the reality of subjective variables, and unlike Bok and Crisp, the

author believes that currently we may not have captured the precise unit of

measurement for evaluating subjective wellbeing, but that reverting to the past

(economic wellbeing) is not an option. Instead, the author urges researchers to

develop a subjective measurement that captures the reality of people, rather than

this one-directional economic assessment. Researchers such as Richard Easterlin,

Edward Diener, Rutt Veenhoven and others have argued that happiness is a good

proxy of the general state of an individual, but this again can be questioned as

happiness is highly subjective. Subjectivity does not mean it is not real, as we are

cognizant of issues such as pain, fear, anxiety, depression, fatigue and other

psychological conditions which influence the effective operation of an individual,

and it is in this context that the author urges researchers to come up with a

subjective-objective method of assessing wellbeing as against economic
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wellbeing. Like Dr. George Engel, the author knows that many biological

conditions are owing to non-economic and non-priced conditions; hence the need

to capture them in the mix of wellbeing, especially for the elderly whose

wellbeing is more subjective than economic.

       Among the many attributes of ageing is the individual’s ability to cope in

adverse situations, as his/her current perspective is fashioned by history and past

challenges. This tool is acquired with time and is oftentimes a potent life coping

skill for the elderly. Embedded here is the ability of the aged to demonstrate

greater resilience than younger people, and the issue of compliance is greater

among the former than the latter group. These are among the laden gifts of ageing

compared to youth, and these enhance the quality of life that an individual lives.

They are intangible assets which are highly subjective and must be excluded in

any monetary assessment.

       The general wellbeing of the       elderly in Jamaica is affected by (i)

psychological conditions - positive and negative affective conditions; (ii) area of

residence; (ii) crime; (iv) marital status; (v) physical milieu; (vi) property

ownership; (vii) educational level; (viii) cost of health care, (ix) average

occupancy per room and (x) age of the respondents. The five most important

factors impacting on the wellbeing of the Jamaican elderly in descending order

are as follows: average occupancy per room (β = -0.229), physical environment (β

= -0.190), education (β = 0.173), area of residence (β = 0.164); and cost of health

care (β = 0.148). Thus, the significance of this paper is that we now have a

quantitative, empirical model that can be used to evaluate the wellbeing of elderly
                                                                                  197


Jamaicans.

       Among the findings of this study, that has shown no statistical relationship

between itself and wellbeing, is home ownership. The literature established that

there is a clear association of the aforementioned factors, but this study has

revealed a disassociation between the two variables. Within the concept of the

elderly, home is an investment for the children and so they are not likely to

venture into activities that will incur a risk of foreclosure on their asset. Thus, the

elderly are least likely to use their homes as a risky income-generating

investment; and so owning a home does not add any benefit to wellbeing, except

within the qualitative respect of leaving something for the children (or

grandchildren) after their death. In 1997 Eldemire noted that 74.6% of elderly

Jamaicans own their own home, but           the PLC – Jamaica Survey of Living

Conditions - (2002) found that this had increased by 11.3% (i.e. 85.9%). Some

people may be inclined to arbitrarily use this numeric increase in assets as an

indicator of an improvement in the quality of life, but is it?

       Then there is the issue of owning a home, but being unemployed, single,

old, living alone and having no health insurance, and so the fact of having

somewhere to call your own does not contribute to an improvement in quality of

life. Eldemire (1997:90) cites that in 1990, the aged were self-employed for a

substantially significant proportion of their lives. Although we are not able to say

that this has changed in 2001 and beyond, based on our reading we can say that in

excess of 75% of the elderly are unemployed. The economic reality of ‘elderly

Jamaicans’ does not cease there, as in 2002 6.5% of them received payments from
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the National Insurance Scheme (i.e. NIS) and 20.9% got private and government

pensions, with 10.2% having received both NIS and pension payments. Another

reality of the ‘elderly’ in Jamaica is that most of them reside in rural areas

(approximately 66%).     However, the rural elderly received the least in NIS and

pension payments compared to their aged counterparts who dwell in other towns

or the Kingston Metropolitan Region (i.e. KMR) – 17% of the elderly in rural

Jamaica received private or government pension payments, and 5% received NIS.

The reality of the ‘elderly’ is further complicated as the findings revealed that

most of them are living alone (i.e. in a one-member household).           Eldemire

(1997:90) explains a possible question that you may be asking – ‘How do they

survive?’ - saying that 65.2% of them are supported financially by their families,

and that 39.2% receive government food stamp benefits.

        As distinct from the unrelatedness between home tenure (i.e. own, squat,

owning a house) and wellbeing, there is a positive association between quality of

life and property ownership, which is conceptualized as owning land and/or

buildings. Embedded in this finding is the fact that elderly Jamaicans use land as

an income-generating asset. But culturally a house is an asset to which Jamaicans

cleave, unlike land or other non-house buildings.         A house is a personal

accomplishment, and so it has intrinsic benefits for the recipient. Therefore, the

elderly are even less likely to risk such an asset, as they consider themselves

decreasingly less likely to replace it in the event of a loss. Thus it is important

for them to leave a house for their loved ones after their death, and they will

forego current consumption for their family’s future benefits and satisfaction.
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       Undoubtedly the ‘elderly’ require economic and social support within the

context that many of them would have lost a substantial portion of their income

due to retirement, or a reduction in their working time due to ageing, as well as

the fact that some of them would have outlived their partners and associates and

so they must depend on the extended community. It also follows that the priority

of the elderly has shifted away from material possessions, and therefore they

would place more emphasis on intangible things – post mortality, humanity,

social support and so on – from which they derive more utility (or satisfaction).

But this quantitative evaluation of their wellbeing was not captured or examined.

However the fact is, the elderly gain more utility from intangible things. Thus,

what is the real contribution of this study?

       The use of dysfunction or income to measure wellbeing is limited and

unidirectional. However, a composite approach to this discussion reduces many

of the limitations to the single method. In addition, it is a better approach to

examine a multidimensional perspective as it reduces the number of negatives.

This study did not address the challenges of population in the form of public

health concerns, productivity and production, economic development, social

security, and retirement planning. However, we are now provided with at least a

basis upon which we can extrapolate on important issues that affect the quality of

life of society, the individual and the elderly. It is inevitable that demographic

ageing will mean changes in retirement planning. But policy makers should not

avoid the possibility of changing the age of retirement, which would be in keeping

with the changes in age dependency ratio, elderly dependency ratio, and the
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burden it will mean for the quality of life of elderly people post-retirement.

        In addition to the aforementioned situations, we have identified several

factors which influence the wellbeing of the Jamaican elderly. But up to this

point, we have not examined specific factors such as loneliness, culture,

religiosity, HIV/AIDS, bereavement and death of close family members,

unemployment, and other issues relating to the quality of wellbeing of an elderly

person. We are arguing that despite the contributions of this study to an empirical

framework of wellbeing in Jamaica, there is still a definite need to investigate the

quality of the wellbeing indicators as well as other issues. It should be noted here

that the wellbeing of aged Jamaicans is such that a qualitative assessment of the

quantitative factors is needed in order to establish a deeper understanding of the

‘quality’ of wellbeing of aged Jamaicans from their perspective.

       Any assessment of wellbeing cannot be completed without an evaluation

of the subjective aspects of life, as people essentially know themselves better than

an external source. Scholars like Edward Diener and others (J. Larson; S. Levine;

R.A. Emmon; M. Suh, and E. Lucas) have shown that psychological wellbeing is

a ‘good’ measure of wellbeing, like the objective measure that was proposed and

widely used by many quantitative scholars (A. Sen; Becker, Philipson and Soares

2004; Gaspart (1998) Thomas Hurka (1993). We will repeat an important point

that was put forward in the early part of this work. Summers and Heston (1995)

note that “However, GDP POP is an inadequate measure of the immediate material

wellbeing of countries, even apart from the general practical and conceptual

problems of measuring their national outputs.” Generally, from that perspective,
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the measurement of quality of life is, therefore, highly economic and excludes

psychosocial factors. People’s psychological state is associated with self-esteem,

life tasks and goals, a sense of belonging, realization and temperament, which

undoubtedly affect the quality of life of the elderly. Within this work we have not

examined life satisfaction as an indicator of wellbeing, and it is a fact that

people’s past experiences (or lack of) affect their current wellbeing. Thus,

people’s behaviour and attitudes toward health, life practices, and illnesses, guide

their wellbeing; and these are not captured in any quantitative assessment, as was

examined by this study.

       In spite of the twofold increase in the life expectancy of Jamaicans over

1880-1882 and 2002-2004, which has resulted in population ageing owing to

advances in technology, science, public health, and literacy, our elderly

population continues to survive within a poorer socioeconomic and political

milieu. In Jamaica, the decline in fertility since the 1970s, accompanied by some

of the aforementioned conditions, accounts for many of the island’s problems. It

is clear that the changing population dynamics require current redress as they will

have futuristic challenges for the society. The futuristic problems which are

implied here are not owing to retirement income payments, but to issues such as

increased cost of hospitalization, increased dependency at older ages, increased

demand for medication, reduced contributions to income tax and a changing

pattern of diseases. Population ageing is also associated with a shift in sex ratio

towards the feminization of ageing. Accompanying the demographic transition

are some of the aforementioned issues, but there is a changing demand for
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particular goods and increased dysfunctions. The challenges expand beyond

biological and economic conditions, to include the failure to effectively plan for

population ageing, as the needs are changing, and they must be addressed within

the context of the current economic downturn in the United States.

       Planning in the Caribbean, and in particular Jamaica, has not included in

economic growth calculations on population ageing, feminization owing to this

phenomenon, and the likelihood of stationary population in the future. There is

another potent component that has yet to be brought into the economic discourse

of this society, and that is the power structure that will result from population

ageing, and the implications of the likelihood of an increase in the age of

retirement, with the consequences of this reality on opportunities for youths. It

appears that policy makers in Jamaica are saying that time will tell, and that God

will take care of the future, so we can just plan for the present. The author doubts

that this is the cosmology of Jamaican social policy makers, legislators,

government, or the populace; however, policies and thoughts about concerns on

population ageing have not begun in earnest. The best planners are those who plan

for expectations, shifts, and social, physical and other demographic changes in the

population. In short, the author is convinced that this book will commence the

debate from which policy shifts will emerge. On the contrary, if the debate is

confined to verandahs, then the future of society is left to the gods, like other

psychosocial challenges currently facing the island – high crime and

victimization, unemployment, the economic downturn, low morale, distrust and

corruption. It should not be forgotten that the population of a society is its greatest
                                                                                203


resource, and failing to plan for it does not mean that we have planned for all

forms of challenges including zero-growth, non-functionality of pension schemes,

costly hospitalization expenditure, sterilization of social programmes, and the

need to devise a population measurement for the ageing population, like that

which has been devised to address high fertility.

       In summary, like Cajanus (1999:230), we believe that “the importance of

the elderly population needs to be recognized, and a life-stage approach to the

issue adopted by countries…” as this cohort of individuals is here to stay, and will

contribute increasingly more to Caribbean populations, Jamaica in particular.

This study has provided us with a basis upon which we can now construct a

comprehensive plan of action to adequately cater to the needs of this group, as

well as a modification of the existing dominance of the biomedical model in

patient care, and the conceptualization of health care in Jamaica. If we are agreed

on the premise that the elderly represent a vulnerable group of people, the time to

examine this group is now. Although Jamaica as well as some other Caribbean

islands – for example, Barbados and Trinidad and Tobago - can boast of its high

life expectancy, with the corresponding increase in chronic diseases, we must

abandon our emphasis on diseases (or dysfunctions) in the conceptual definition

of health. This study, although it does not claim to provide all the answers (or for

that matter, even the majority of them), has revealed that a multidimensional

approach to the study of health is possible. Since Caribbean societies cannot turn

back the hands of time regarding demographic ageing, we should forge ahead

with a plan that seeks to understand not only population ageing and the needs of
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this group, or the chronic diseases, but a systematic structure that addresses the

reality of an ageing population. This plan of action should incorporate socio-

psychological, environmental and biological issues that affect the quality of life of

the elderly, which must be a deviation from the present emphasis on life

expectancy and our preoccupation with dysfunctions (or ailments), instead of

quality of lived years.        Come the next four decades, the country’s elderly

population is expected to more than double (see Figure 11.1.1) and within the

findings of this study; I will be presenting ‘The Way Forward’.




              Elderly (60 years and over) as a percentage
                 of total population with time, Jamaica
    30.0%

    25.0%

    20.0%

    15.0%

    10.0%

     5.0%
         1850                   1900               1950          2000      2050
  Figure 11.1.1: Constructed by author using data from
                                                      Year
  http://www.un.org/esa/socdev/ageing/workshops/vn/jamaica.pdf
Figure 11.1.1: Percentage of Elderly (ages 60+ years) of Jamaica, 1850-2050

The Way Forward

George Engel (1960, 1977a, 1977b, 1978, 1980) was the first to develop what is

known as the biopsychosocial model. He contends that health care must be

addressed from biological and socio-psychological dimensions, as humans are

both body and mind, which means that any single definition of health that fosters
                                                                                 205


its image, must cater to this reality. This is still nothing new, as it is in keeping

with the WHO’s conceptualization of health, that includes complete physical,

psychological, and social wellbeing, and not simply the absence of disease or

infirmity (WHO, 1948).

       In an ethnographic study carried out during September and October 2000

with some 40 school-aged street children in Pakistan, Ali & de Muynck (2005)

concur with the perspective that health must be viewed outside of biological

conditions. In their study, they found that the children reveal that they seek

health-care based on (i) severity of ailment, and (ii) financial situation. It should

be noted, however, that this is primarily based on the biomedical

conceptualization of the phenomenon of health, and that this is not in keeping

with the World Health Organization’s definition of health, which expands beyond

biological conditions to “a state of complete physical, psychological, and social

wellbeing…” (WHO, 1948). Despite WHO efforts on the widening of the

construct of health, and by extension research on health care, within many

societies health demand (i.e. health-seeking behaviour) continues to be gender,

education, age and information-sensitive as well as emphasizing biomedical

conditions.

       Some health practitioners, and equally some people outside of the health

profession, believe and continue to see health within a one-dimensional tenet –

sickness, diseases, or infirmity - which guides how they respond to health matters.

In Jamaica, ergo, a visit to a health practitioner is an indicator of weakness,

infirmity or disease, and not a fundamental approach to preventative care, as
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health is a curative care matter. Becker and Rosenstock’s work (1984) shows that

people’s health demand is a factor of their beliefs. This speaks to the value of

culture and socialization in health demand, and it means that they will seek care

based on (i) perceived susceptibility to diseases or illnesses or disability, (ii)

severity of the diseases and/or disability, (iii) benefits of health-enhancements,

and (iv) perceived hindrances to health-enhancing behaviour, including financial

inability; as such, health-seeking behaviour is not limited to diseases and/or

disabilities and one’s sex.

        Many men are only willing to visit health practitioners in the event that the

ailment or disability is severe and extensive, and may result in death. Their first

point of contact in case of dysfunction, or their perception of ill-health occurring,

is to use self-care or self-medication, compared to women who are eager and

willing to seek heath-care on the smallest of perceived symptoms of ill-heath, and

even for preventive care. A group of researchers found that men are only willing

to report life-threatening illnesses like heart disease; this is also reiterated by Low

et al. (2006) who argue that even when men suffer from erectile dysfunction only

10.5% of them seek help. These barriers to health-seeking behaviour are all

embedded in one’s beliefs, which could be as a result of perceived personal

control of the situation, level of optimism (Clarke et al. 2000), ethnic background

and level of risk taking. These cultural happenings are not limited to Jamaica and

the Caribbean, as a study conducted in Malaysia shows similar health-seeking

behaviour to that in Jamaica and in Pakistan (1). Low and colleague (2006) cite

that:
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       Erectile dysfunction (ED) is a common sexual disorder affecting men. [1-
       3]. Although new treatments for ED have emerged for many years, this
       does not directly translate into men actively seeking treatment for their
       ED problem (Low, et al. 2006)

       A substantial aspect of this is the emphasis that is placed on biomedical

treatment, and people’s perceptions of issues that are classified as health related.

This is even evident in how information is collected on health, how health is

measured in many studies, and how people internalize those symbols. This

explains how society deals with particular health-related matters. Low et al. state

that “some men did not see ED as a medical problem, while others accepted it as a

normal sequence of aging” (Low, 2006). But still the reality lingers, health is

substantially seen as a biomedical phenomenon – that is, communicable diseases,

maternal and prenatal conditions, nutritional deficiencies and non-communicable

diseases as the causes of changes to health status and/or death. But a question still

remains: Are we responsible for the one-dimensional health-seeking behaviour of

people?

       While the physical and social environment shapes behavior, people are
       not passive in the process, since they in turn can change their
       environments – a reciprocal dynamics. (Murphy, 2005),

       Human      existence    is   continuously    interfacing   social,   cultural,

psychological, and political experiences, and so biomedical theorizing is a

simplistic perspective on the subject matter as health is the absence of illnesses

[biomedical] and the psychosocial state of an individual.           People casually

perceive health from the perspective of physical illnesses, so much so that in the

absence of certain physiological indicators they perceive of themselves to be

healthy, and so they will address matters relating to care based on their socio-
                                                                                   208


cultural attitudes and valuations (Low et al., 2006).            Health, despite its

fundamentality to existence, is not limited to a single space (i.e. quantification), as

human beings are physiological, social, psychological and highly subjective.

Thus, health-care-seeking behaviour should not be constricted to mere absence of

physical illnesses because this is quantifiable, but the phenomenon must be

analyzed from within a psychosocial space in addition to traditionalist theorizing.

       The dominance of positivistic science in measuring health speaks to a

number of the psychosocial ills that are unaddressed by countless Jamaicans, and

this will continue into the distant future if the traditional viewpoint of health does

not abate with proper education. Furthermore, if the level of education of a group

of people is relatively low or even mediocre, what are the possible outcomes of

their perspectives on many issues, including that of health-care?

       Health and its care are not only indicators of wellbeing, but health status is

also a determinant of human development, and so must become a concern for

policy-makers. Thus, the one-dimensional perspective of health and health-care

permeates the human space and explains the high preponderance of research on

this conceptual definition. This explains why there are no statistical agencies in

Jamaica that are collecting data on issues such as the frequency of visits to

gymnasiums, knowledge and healthy eating and ‘best practice’ in regard to

preventative care. The importance of this phenomenon has helped the author’s

investigation of the matter. In order to present a perspective of Jamaicans on

health-care, the author will use a secondary data source. The purpose of this
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approach is to establish external validity, and to formulate a theoretical

framework on the health demand (i.e. health-care behaviours) of Jamaicans.

       It is extremely difficult to conceptualize health in an operational manner

that is simple, as the concept is multi-dimensional in part, and must include a

social realm. Hence, health will be conceptualized within the operationalization

of the WHO’s Constitution of 1946: “Health is a state of complete physical,

mental, and social wellbeing and not merely the absence of disease or infirmity”

(WHO, 1948). This, therefore, comprises biomedical conditions, lifestyle habits,

access to care and quality of life conditions. Such a view on the subject aptly

describes the matter that health is to be judged from the aspects of how well

people perform everyday activities, to what extent they are capable of taking part

in social activities, and the harmonious relationship that they have with the

environment.

       This study seeks to examine the determinants of health of Jamaicans.

Jamaica’s population continues to increase while young male adults are

experiencing increasing injuries; in addition, there are concerns for care for the

elderly. Injuries, for example, are among the leading causes of treatment at

government hospitals, and thus demand the continuous use of such facilities. This

diagnosis could be very costly for a Jamaican government that intends to

effectively plan for and implement health-care for the populace.          Therefore,

researchers strongly believe that this issue would be of paramount importance to

health analysts, health practitioners and planners. Within the construct of the

socio-demographic realities of this society, the research seeks to postulate a causal
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relationship between health and biomedical characteristics as well as other

sociodemographic and economic variables. We now know those factors that are

important to the wellbeing (or health) of the elderly, and so their demand for

health care must be dependent upon those factors which drive their wellbeing.

       The way forward in public health is to plan for the elderly around the

importance of each factor that determines their wellbeing.          This study is a

theoretical model, unlike that which offered by Dr. George Engel, or for that

matter by the WHO in the Preamble to its Constitution in 1948. The experiences

outside of Jamaica are not necessarily the same, nor the applications to the

elderly, and this means that public health practitioners must use research on

elderly Jamaicans to guide policies, programmes and measures to address their

health and survivability, although valuable information can be had outside of the

country’s shores. This study is the catalyst for the way forward, and health

education and health promotion from this point onwards must address all the

tenets identified in this study in order for aged Jamaicans to effectively attain

healthy life expectancy.

       It is well established in the research literature that ageing (i.e. biological,

chronological or social ageing) is synonymous with 1) morbidity and 2) mortality.

Even if an individual were never to become ill, he/she will die from old age. This

means that death is a natural part of the life span, and that it occurs normally as

the cells in the human body gradually die, resulting finally in death. Mortality

which has been the focus of demographers for centuries – as an indicator of health

status – is undeniably unidirectional within a multidimensional space, and so I
                                                                                 211


will show the shift in typologies of diseases since the 1940s. Within the context

that the cell dies normally before the finality of death, people can live longer, but

this does not necessarily mean healthier. During the 1900s, the leading causes of

death were communicable and chronic diseases – these include tuberculosis,

syphilis, nephritis, pneumonia and influenza – but since the 1990s, an

epidemiological transition has occurred in non-communicable diseases (Wilks,

2007). These dysfunctions include malignant disease, cardiovascular and

cerebrovascular disorders and diabetes mellitus. While this text is a study on the

wellbeing of the aged, and given that most of the aforementioned dysfunctions

primarily affect older people, they have also occurred in younger people, and so

care should be taken in addressing all age groups in terms of diseases.

       Literature has provided evidence from both the developed and developing

world, suggesting that although the majority of the elderly enjoy reasonably good

health, and perceive their health as good, or lead purposeful lives (Powell, Bourne

and Waller, 2007; Kaplan 2003, Parsons1993, Clausen et al. 2000), many

challenges related to morbidity and morbidity control still exist. The tendency of

elderly persons to overestimate their level of wellbeing has been recognized

(O’Connor and Daley 1984). A study conducted in Botswana noted that

conditions relating to musculoskeletal, circulatory, neurological and eye disorders

are common among older persons (Clausen et al 2000). Kalache, Aboderin and

Hoskins (2002) have argued that chronic diseases occur at earlier ages in

developing countries, citing that the majority of people with diabetes, for

example, are in their productive years, i.e. aged 45–64 years. They noted also that
                                                                                212


the overall compression of morbidity (i.e. increased longevity with greater

proportions of old age being spent disability-free, and postponement of disability

to later life, with shorter intervals between disability onset and death) is yet to

occur in the developing world. Additionally, compared with developed countries,

older persons arrive at old age with fewer reserves (Kalache 1998).

       The way forward is for Caribbean scholars to develop an index of

wellbeing for aged people that will account for more than our current

understanding (i.e. 41%) of it. In addition to the aforementioned proposition, the

time has come for policy-makers within the region to fashion measures that will

be geared towards the improvement in wellbeing of the aged populace within the

context of the current findings. Population ageing in the Caribbean is here to stay,

and ageing in Jamaica is expected to double in 2050, plus with the reality that

increasingly more Jamaicans will be retired because of the current retirement age

coupled with the stressors on governments to provide social assistance for more

people, it means that the dependency ratio will become even more burdensome

for the working age population (ages 15 through 60 years). Hence, it is time for

us to begin a dialogue on the retirement age for Jamaica, and begin to build homes

that will cater to this ageing population as well as find transportation, work, and

technology for them.

       Population ageing signifies demographic transition (Bourne and Eldemire,

2008b), and reduced birth rate, which coupled with higher life expectancies,

means that people will be living across the technological era. During the

transition, many of the elderly will be left outside of this space, and the growth
                                                                                213


and developmental stage of these individuals will mean than they will not be able

to re-socialize themselves to this time period. The technological period may be

such that a plethora of activities will change and many elderly persons will be

excluded from the process. Hence, another way forward is for Caribbean scholars

to examine the psychological state of elderly people owing to changes in eras; and

this affects their living standard, personal health and wellbeing.

       Based on the high life expectancy of Jamaicans and the feminization of

ageing, the process signifies more than demographic or epidemiological

transition, as it includes the imbalance of power in that society. Caribbean

societies – in particular Jamaica - have not included in their policies the ‘balance

of power’ that accompanies population ageing, as we are yet to recognize the

image of ageing and the reality of the power dynamics that underpin demographic

transition. The elders are power brokers, and so with increasingly more of them,

how will youths become leaders within the general context of population ageing

and longer living people? How will the balance of power be transferred to the

youth, and when? The ‘imbalance of power’ and transition in power must be

included in Caribbean discourse, as answers must be put forward to address this

pending reality. This study does not have the answers to this issue; however, I am

putting forward the awareness of gerontological imagination – the awareness of

the process of ageing and an understanding of the scientific contributions of a

variety of researchers to the study of ageing and ‘balance of power’.

Gerontological imagination is a multidisciplinary sensitivity to ageing, and this

must incorporate a stock of knowledge of ‘imbalance of power’ arising from
                                                                                214


population ageing, in order to have empirical evidence that can be used to address

this pending social reality.

       Another way forward is for the training of many doctors in social

gerontology, as ageing is multidimensional, and includes physical, social,

psychological and societal aspects. Gerontology, which is the scientific study of

old age – coined by Metchnikoff in 1903 for this field of inquiry (Elie

Metchnikoff 1903) - must be incorporated into the curriculum of medical

practitioners, social workers, sociologists, police officers, counsellors, pastors,

policy analysts, accountants, economists, educators, high schools, and researchers,

as ageing must be as normal as it is a natural occurrence, and this will enhance the

multidisciplinary approach to understanding wellbeing, addressing it and

removing some of the stereotypes. The needs of older people are not the same as

those of children, the youth, working age people or infants, and so there is a need

for medical gerontologists to cater specifically to this age cohort, or geriatrics –

the systematic study of ageing (IL. Nasher 1909).

       Ageing is a normal process in the course of life, and this means that health

promotion experts and health educators need to educate the population about the

differences between ageism (the disproportionately negative connotations

associated with ageing) and ageing, and this process should begin with politicians.

I hope that this text – GROWING OLD IN JAMAICA: Population Ageing

and Senior Citizens’ Wellbeing – will provide for everyone an

invaluable understanding of elderly people’s health status, and be used as the new

way forward in examining and addressing the lives of aged people.
215
                                                                               216


                                           Glossary

Age:     Age is the total number of years which have elapsed since birth

(Demographic Statistics, 2005); or, the length of life of the individual (i.e.

existence).



Elderly (i.e. aged, or seniors, older adulthood): This terminology refers to the

chronological age beginning at 60 years and beyond.

Elderly cohort: Elderly cohort comprises the three categories into which elderly

people are grouped. These are as follows:

         (1) Young elderly (60 – 74 years);

         (2) Old elderly (75 – 84 years), and

         (3) Oldest elderly (85+ years).

Wellbeing: Wellbeing is defined as the summation of an individual’s physical

functioning (subjective wellbeing), and the ownership of material resources

(objective wellbeing).     Material resources consist of income, ownership of

different types of durable goods excluding a house, and/or the receipt of pensions.

Physical functioning, on the other hand, is the summation of five different health

conditions as reported by the individual. These health conditions include injuries

due to stabbing, diarrhoea, et cetera.

Sex: Sex is the biological makeup of males and females.

Educational level: Educational level is the highest grade of schooling that an

individual has completed. It ranges from no formal schooling to the post graduate

level.
                                                                                  217


Marital Status: This is defined as a conjugal arrangement between people,

which is based on the law of the country or its customs. These arrangements must

be between consensual adults (from ages of 16 years and older).

Household: A household is “one person who lives alone or a group of persons

who, as a unit, jointly occupy the whole or part of a dwelling unit, who have

common arrangements for housekeeping, and who generally share at least one

meal” (STATIN 2004, viii). A household does not necessarily consist of people

who are biologically related, as the individuals may be biologically related or

unrelated or a combination of both.

Household crowding (i.e. average occupancy per room): This is the arithmetic

mean number of persons who live in a room, of a defined household.

Crime: A crime is an act carried out by an individual which contravenes the legal

statutes of the country. For this study, it includes acts committed against a person,

or his/her close associates or people within the same household.

Environment:        The external physical surroundings affecting the growth,

development and survival of an organism. The organism in this case is the human

being. The elements here consist of air, water, land, soils, minerals, oceans, et

cetera.

Psychological factors: The mental state of a person which arises as a result of

his/her experience with the environment or a social happening. These are

classified as either:

(1) Negative Affective Conditions – negative emotions (e.g. loss of breadwinner,

loss of house, redundancy, failure to meet household and other obligations), or
                                                                                  218


2) Positive Affective Conditions – positive emotions or moods (e.g. hopeful,

optimistic).

Income (the proxy is population quintile). This is, as defined by STATIN, based

      on consumption patterns of individuals from a predefined basket of goods

      and other commodities. Its groupings range from the poorest group [quintile

      1 (i.e. those below the poverty line) to the richest group (quintile 5)].

Area of residence – This means the geographic location of one’s place of abode

(KMA, other towns and rural areas).

Cost of medical (i.e. health) care – The total amount in Jamaican dollars that is

spent on medication and hospitalization, which includes preventative care and

doctors’ visits.

Home Tenure: This refers to different types of home occupancy, including

owning, renting, leasing and squatting on land.

Property Ownership (using paying property taxes): The payment of taxes to

government for the ownership of property (i.e. land), which indicates ownership

of that geographical space.

Population Ageing is the percentage of the population age 60 years and older,

based on the World Assembly of Ageing definition of elderly (ages 60 years and

beyond) (United Nations, 1982, p.29).        Growth rate is the total number of

persons added to (or subtracted from) a population in a given period of time

owing to natural increase (births and deaths) and net migration, expressed as a

percentage of the population at the beginning of the time period.


ANALYTIC MODEL OF WELLBEING
                                                                                                219


DEPENDENT VARIABLE


Wellbeing: Wellbeing is one-half of the summation of material resources minus
one-half of the summation of physical functioning. In this study, self-reported
health conditions are used to measure physical functioning. Material resources
are measured by income, ownership of durable goods and financial support (see
below).

       Health status 1           1= Respondents having injury (i.e. gunshot, stabbing,
                                 accidental fall) during the past 4 weeks; 0 otherwise

       Health status 2           1=Respondents who have had any illnesses due to
                                 injury (cold, diarrhoea, asthma attack, hypertension,
                                 diabetes, or any other illnesses); 0 otherwise

       Health status 3           1=Respondents having recurring chronic illnesses (such
                                 as colds, diarrhoea, asthma, diabetes, hypertension,
                                 arthritis); 0 otherwise

       Health status 4           1=Respondents having physical or mental disabilities
                                 (i.e. mental, sight only, hearing only, hearing and
                                 speech, legs and arms or multiple disability); 0
                                 otherwise

       Health status 5           1=Respondents’ perception of what causes their ‘poor’
                                 health (i.e. dust, toxins and chemicals, dirty gullies and
                                 infection via food or water; 0 otherwise


       NB: Physical Functioning Index = Σ           Hi, where i ranges from health status 1
       to 5. The least score is 0 and the maximum score is 5, where 5 denotes
       experiencing all 5 health conditions.


       Income, Yi 3              1=Respondents being in quintile 1,
                                 2=Respondents in quintile 2;
                                 3=Respondents in quintile 3;
                                 4=Respondents in quintile 4;
                                 5=Respondents in quintile 5.




3
    Yi , where Y denotes the income measured by population quintile and i means each quintile
                                                                                  220


       Durable goods 4
       j601                       1=Respondents owning sewing machine; 0 otherwise
       j602                       1=Respondents owning gas stove; 0 otherwise
       j603                       1=Respondents owning electric stove; 0 otherwise
       j604                       1=Respondents owning fridge or freezer; 0 otherwise
       j605                       1=Respondents owning air conditioner; 0 otherwise
       j606                       1=Respondents owning fans; 0 otherwise
       j607                       1=Respondents owning portable radio etc; 0 otherwise
       j608                       1=Respondents owning stereo equipment; 0 otherwise
       j609                       1=Respondents owning other stereo equip; 0 otherwise
       j610                       1=Respondents owning TV sets; 0 otherwise
       j611                       1=Respondents owning VCR/DVD; 0 otherwise
       j612                       1=Respondents owning video equip.; 0 otherwise
       j613                       1=Respondents owning washing machine; 0 otherwise
       j614                       1=Respondents owning dryer; 0 otherwise
       j615                       1=Respondents owning bicycle; 0 otherwise
       j616                       1=Respondents owning motorbike; 0 otherwise
       j617                       1=Respondents owning cars; 0 otherwise
       j618                       1=Respondents owning computer; 0 otherwise
       j619                       1=Respondents owning computer scanner; 0 otherwise
       j620                       1=Respondents owning CD burner; 0 otherwise
       j621                       1=Respondents owning DVD burner; 0 otherwise
       j622                       1=Respondents owning other electrical equipment; 0
                                  otherwise
       j623                       1=Respondents owning musical equipment; 0 otherwise


Durable goods, DG = Σ j, ranging from 0 to 23, where 0 denotes owning no
                      assets.

Financial Support:
   Social security                1=Respondents receiving NIS; 0 otherwise
   Other pension                  1=Respondents receiving private, government or other
                                  pension fund; 0 otherwise

NB. Financial support, FS = Σ (NIS, Private pension, Government pension,
other pensions), ranging from 0 to 2, where 0 represents not receiving any form
of pension payment to higher score indicating receiving more.

Material resources, MR =DG + FS + Yi where the index ranges from 0 to 25, in
which low score indicates low economic wellbeing and higher score greater
economic wellbeing

Wellbeing Index = ½ [MR] - ½[Σ Hi ], where higher values denote more
subjective wellbeing. The index ranges from a low of -1 to a high of 14. A score


4
    See Appendix VIII for detailed listing of the question from the instrument
                                                                                 221


from 0 to 3 denotes very low, 4 to 6 indicates low; 7 to 10 is moderate and 11 to
14 means high wellbeing.

INDEPENDENT VARIABLES

Socio-demographic and psychological indicators

1.    Elderly
2.    Sex                     1=Respondent is male and 0 equals to Otherwise
3.    Marital status:
      maristatus1             1=Divorced, separated and widowed, 0=Otherwise
      maristatus2             1=Married
      The reference group is single

4.    Average occupancy per room –

      This variable equates to the number of persons per household divided by the
      number of rooms (excluding kitchen, verandah, and sanitary conveniences)

5.    Area of Residence:
      Area_Residence2          1=Other Towns, 0= Otherwise
      Area_Residence3          1=KMA, 0=Otherwise
     The reference group is rural area

6.    Cost of care               a12=cost of health care in public facilities
                                 a13=cost of health care in private facilities
                                 a27=cost of medication in public facilities
                                 a28=cost of medication in private facilities

NB Cost of health care = Σa i , where i denotes 12, 13, 27 and 28; ranging from
Ja$0.00 to Ja$2,000 (in this period US$1=Ja$50.97)

Negative Affective
          1. Difficulty meeting         1=school related costs, 0 otherwise
                                        1=health related expenses, 0 otherwise
                                        1=transportation costs, 0 otherwise
                                        1=food costs, 0 otherwise
                                        1=entertainment costs, 0 otherwise
                                        1=clothing costs, 0 otherwise
                                        1=loans, 0 otherwise
                                        1=vacation needs, 0 otherwise
                                        1=utilities, 0 otherwise
                                        1=other expenses, 0 otherwise
           2. Inability to pay          1=electricity, 0 otherwise
                                        1=telephone, 0 otherwise
                                        1=water, 0 otherwise
                                                                                222


                                      1=cable, 0 otherwise
                                      1=other (specify), 0 otherwise

          3. Household experience     1=loss of breadwinner, 0 otherwise
                                      1=unexpected loss of house, 0 otherwise
                                      1=crop failure, 0 otherwise
                                      1=redundancy, 0 otherwise
                                      1=loss of remittances, 0 otherwise
                                      1=other (specify), 0 otherwise
7.    Positive Affective
            P1: How do you feel about your present conditions?
                               -1=Respondents who say hopeless
                               0=Respondents who say don’t know
                               1=Respondents who say unsure
                               2=Respondents who say hopeful
            P2: Over the past 12 months have you been able to make any
                   significant progress in your life?
                               0=Respondents who say no
                               1=Respondents who say somewhat
                               3=Respondents who say yes

            P3: How do you view the future?
                            -1=Respondents who say hopeless
                            0=Respondents who say don’t know
                            1=Respondents who say unsure
                            2=Respondents who say hopeful

     NB. The positive affective conditions equate to the summation of p1 to p3;
     and the negative affective conditions equal the total of 1, 2 and 3.

     The ‘positive affective condition’ index ranges from 0 to 6, where from 0 to 2
     is low, 3 is moderate and 4 through 6 is high.

     The negative affective condition index means that from 0 to 4 is very low, 5-8
     is low, moderate is 9 through 12 and high is from 13 to 19.

8. Crime                     1=Respondents who say yes, 1-2 times
                             2=Respondents who say yes, 3+ times
                             0=Respondents who say no
        Weights are assigned based on degree of crime
                             1=had something valuable stolen/robbery/burglary
                             2=attacked with or without weapons, fight with or
                             without weapons (not a gun)
                             3=threatened with a gun or attacked with a gun
                             4=sexually assaulted or raped, injured in a fight or
                             murdered
                                                                          223



NB. Crime Index = Σ ki Tj, where K i

    The equation represents the frequency with which an individual
    witnessed or experienced a crime, where i denotes 0, 1 and 2, in which 0
    indicates not witnessing or experiencing a crime, 1 means witnessing 1
    to 2, and 2 symbolizes seeing 3 or more crimes.
    Ti denotes the degree of the different typologies of crime witnessed or
    experienced by an individual (where j=1 …4, in which 1=valuables
    stolen, 2=attacked with or without a weapon, 3= threatened with a gun,
    and 4= sexually assaulted or raped. The summation of the frequency of
    crime by the degree of the incident ranges from 0 to a maximum of 51.

9. Education
    Edu_level1                1=Secondary and vocational, 0=Otherwise
    Edu_level2                1=Tertiary, 0=Otherwise
    The referent group is primary and below education

10. Environment              1=Respondents who say that they have been
                             affected by landslide, floods, or other natural
                             disasters during the last 12 months, 0 otherwise.
11. Home tenure:
   Dwelling1                 1=Rent, 0=Otherwise
   Dwelling2                 1=Owned, 0=Otherwise
 Reference group is squatting, rent free
                                                                               224


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