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THE AGEING MALE

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					The
  Ageing Male




      Paul Andrew Bourne
Table 1
JAMAICAN MALE: 1993, 2009 AND 2050
Exponential Interpolation of Population by Age
------------ -------------- -------------- --------------
Item or             Earlier          Later   Interpolated
age              population     population     population
------------ -------------- -------------- --------------
Type of interpolation                   1    Exponential
(Enter "0" for linear or "1" for exponential)

Year                 1993           2009           2050
Month                  12             12             12
Day                    31             31             31
                31-Dec-93      31-Dec-09      31-Dec-50

  All ages       1,198,697      1,329,341     #DIV/0!

Under 1              28,755         21,998          11,074
1 to 4              117,104         90,641          47,017
5 to 9              136,491        122,599          93,118
10 to 14            137,388        143,524         160,527
15 to 19            127,754        127,619         127,274
20 to 24            111,495        100,758          77,731
25 to 29             97,652        102,328         115,358
30 to 34             84,649        105,659         186,480
35 to 39             68,535        107,459         340,227
40 to 44             57,262         97,903         386,962
45 to 49             46,190         67,064         174,364
50 to 54             39,380         61,465         192,347
55 to 59             32,926         45,354         103,037
60 to 64             30,723         33,464          41,656
65 to 69             26,919         31,443          46,817
70 to 74             21,986         28,296          54,015
75 to 79             33,488         41,767          73,567
80+                       0              0     #DIV/0!
------------ -------------- -------------- --------------
Source: Statistical Institute of Jamaica (Demographic Statistics, 2009)
Table 2
JAMAICAN MALE: 1993, 2009 AND 2050
Linear       Interpolation of Population by Age
------------ -------------- -------------- --------------
Item or             Earlier          Later   Interpolated
age              population     population     population
------------ -------------- -------------- --------------
Type of interpolation                   0         Linear
(Enter "0" for linear or "1" for exponential)

Year                 1993           2009           2050
Month                  12             12             12
Day                    31             31             31
                31-Dec-93      31-Dec-09      31-Dec-50

  All ages       1,198,697      1,329,341      1,664,111

Under 1              28,755         21,998          4,683
1 to 4              117,104         90,641         22,831
5 to 9              136,491        122,599         87,001
10 to 14            137,388        143,524        159,247
15 to 19            127,754        127,619        127,273
20 to 24            111,495        100,758         73,245
25 to 29             97,652        102,328        114,310
30 to 34             84,649        105,659        159,496
35 to 39             68,535        107,459        207,200
40 to 44             57,262         97,903        202,044
45 to 49             46,190         67,064        120,553
50 to 54             39,380         61,465        118,057
55 to 59             32,926         45,354         77,200
60 to 64             30,723         33,464         40,488
65 to 69             26,919         31,443         43,036
70 to 74             21,986         28,296         44,465
75 to 79             33,488         41,767         62,982
80+                       0              0              0
------------ -------------- -------------- --------------
Source: Statistical Institute of Jamaica (Demographic Statistics, 2009)
The
    Ageing Male




           i 

 
The
             Ageing Male




Paul Andrew Bourne
Director, Socio-Medical Research Institute (Formerly, Research Fellow and
Biostatistician, Dept of Community Health and Psychiatry, The University of
the West Indies, Mona, Jamaica)




                                     ii 

 
©Paul A. Bourne, 2011 

First Published in Jamaica, 2011 by 
Paul Andrew Bourne 
66 Long Wall Drive 
Stony Hill, 
Kingston 9, 
St. Andrew 
 
 
National Library of Jamaica Cataloguing Data 
 
 
The Ageing Male  

                                          
Includes index 
 
ISBN 
 
Bourne, Paul Andrew 
 
 
All rights reserved. Published, 2011 
 
Cover designed by Paul Andrew Bourne 




                                        iii 

 
Contents

Preface                                                                                  v 
Acknowledgement                                                                         vi 
1 Population Ageing                                                                     1 
2 The changing faces of diabetes, hypertension and arthritis in a  
  Caribbean population                                                                 36 
 
3 Sex and older adulthood                                                              60 

 
4 Activities of daily living, instrumental activities of daily living, and predictors  
  of functional capacity of older men in Jamaica                                        68 
 
5 The role of social networks among late adult men in Jamaica                          95 

6 A cross‐sectional survey of the health status, life satisfaction and happiness  
  of older men in Jamaica ‐ associations between questionnaire scores            119 
 
7 Cognitive functionality of older men in St. Catherine, Jamaica                 143 
 
8 Happiness among Older Men in Jamaica: Is it a health issue?                      169 

9 Happiness, life satisfaction and health status in a Caribbean nation:  
  Using a cross‐sectional survey                                                      202 
 
10 Social determinants of physical exercise in older men in Jamaica                   235 

11 Comparative Analysis of Health Status of men 60+ years and  
    men 73+ years in Jamaica: Are there differences across municipalities?            263 

                                            iv 

 
Preface



Between 1910 and 1912 averaged life expectancy for Jamaican males was 55.7 years and this has

increased by 1.3 times for 2006-2008. The current life expectancy for Jamaican males (71.3

years) is as a result of 1) improvements in sanitation, 2) better water and food quality, 3)

vaccination, and 4) improvements in general living standards. One of the critical factors that is

responsible for the present life expectancy of peoples is the shift from communicable (acute)

conditions to non-communicable (chronic) diseases. During earlier centuries, communicable

diseases such as smallpox, yellow fever, cholera, and malaria were responsible for high

mortality, and low life expectancy.

       The lowering of mortality and increased life expectancy are as a result of advancement in

technology and the development of peninsulin. People are now living longer, but they are to

having to experience more diseases (diabetes, arthritis, hypertension, heart conditions, neoplasm,

et cetera). In recognition of the living with diseases, the World Health Organization (WHO) has

developed DALE, which discount life expectancy based on the number of years that the

individual is likely to live with disabilities and health conditions. This has resulted in health life

expectancy, which is the number of years with which the individual lives without disabilities

and/or illness. The WHO has discounted life expectancy for peoples living in the developing

world by 6 years. This means that healthy life expectancy for Jamaican male is about 66 years.

Although this offers some understanding of older adulthood, this is highly narrow and requires

more examination.

                                                  v 

 
       It is well established in biological literature that organism ages and deceleration of

physical functioning is associated with biological ageing (as well as chronological ageing). This

fact does not only recognize the lowered health of aged people, but the need to evaluate the

subjective health in older adulthood. In Jamaica, averaged annual growth of males (using data for

1995-2009) was 0.995% for elderly males (60+ years old), and this was even greater among

those 75+ years old (1.25%) while the averaged growth rate for the entire population was 0.51%.

There is no denial of ageing of the Jamaican male population and this requires extensive

examination to offer policy makers with information for better intervention programmes.

       This book will offer a broader view of the some of the issues surrounding ageing males in

Jamaica. It will expand the literature, and provide health practitioners, administrators, social

workers, sociologists, policy makers, and students in the social sciences with germane

information in understanding men in older adulthood in Jamaica.



                                                                  Paul Andrew Bourne
                                                                              Director
                                                       Socio-Medical Research Institute
                                                                            March 2011




                                               vi 

 
Acknowledgements




Like many books that have been written prior to this one, I am also indebted to many people
have contributed differently and some invariably to the completion of this project. I would like to
extend my sincere gratitude to them. These persons are 1) Ms. Neva South-Bourne for her advice
in penning my ideas, 2) Mrs. Evadney Bourne, my wife, for support, understanding and patience
when things were difficult and surmountable at times, 3) all my co-writers, 4) God, for his
wisdom, 5) the Data Bank in Sir Arthur Lewis Institute of Social and Economic Studies, the
University of the West Indies, Mona, Jamaica for making the dataset available for use in this
study, and 6) all my associates (including best friends) whose love, support and encouragement
provided the impetus that I drew from to complete this project. I would also like to single out the
different journals that gave me the permission to reproduce some of the chapters – including
North American North of Medical Sciences, and Current Research in Social Sciences.




                                                vii 

 
The
    Ageing Male




           viii 

 
                                                                           Chapter 1
Population Ageing
Paul A. Bourne



Introduction
       Ageing is not a recent phenomenon; it goes back centuries. Currently, the differences are
pace and level. The distinction here is, pace denotes the rate of growth per annum; and level
represents the percentage of the population who are experiencing a certain event. These concepts
will be made clearer with the use of various illustrations throughout this paper. As in 2007, it is
estimated that the percentage of people 65 years or over is estimated to be 7.5% and come 2050,
the figure is projected to reach 16.1%, which is a 115% increase in 43 years. On the contrary,
between 1950 and 2007, the percentage of people ≥ 65 years rose by only 2.2% (Table 1.1).
However, by 2030, 1 in every 8 (12.5% of the globe’s population) humans will be 65 years and
older, and this is coming from 6.9% in 2000. But there is a discourse as to whether or not ‘old
age’ begins are 60 or 65 years; hence, we will present the figures as if we were using 60 years.
Thus, if we are to use 60 years and older, the trends are relatively similar to those for ages 65
year or over. As in 1950, the world’s population aged 60 years and older was 1 in 15 (8.2%); but
in 2007, the figure rose to 1 in 9 (10.7%), and the projected 21.7 percent (or 1 in 5) by 2050
(United Nations, 2007:72) (Table 2). Based on percentages, the world’s elderly population (≥ 60
years) between 1950 and 1975 increased by 0.4%. However, between 1975 and 2007, the
percentage of ‘old people’ rose by 2.1% but for 2025-2050, the increase is expected to be 6.6%.

       Insert Table 1.1.

       Presently, China, United States, Germany, India, Sweden, Italy, and Japan have in excess
of 50 percent of the world’s population who are 65 years or older. But, does population-- ageing
stop with those societies only? The yardstick for measuring an ageing population is having 8-
10% of the population reaching at least 65 years. As of 2025, the Caribbean will have an
estimated 11.4% of its population ≥ 65 years. Statistics show that the percentage of Caribbean
population ≥ 65 years is more than that for the combined of Latin American and the Caribbean
(See Tables 2.1, 2.2). “Since population ageing refers to changes in the entire age distribution,
any single indicator might appear insufficient to measure it” (Gavrilov, and Heuveline, 2003:3),
which appears to have befallen many Caribbean states. This is evident in the political landscape
of Caribbean nations as the issue of demographic ageing has not taken on as a serious issue as
debt burden, inflation, unemployment, crime and international relations. The rationale for this
delay is embedded in perception that critical as that time. But this position is far from the truth.
For the reason that, apart from the demographic transition that is taking place globally and
equally within the Caribbean, there is another aspect to this phenomenon. As the implications of
ageing range from pension schemes problems, higher health care costs and initiatives. These do
not cease there, as there are two important issues that we have yet to address, how we will be
dealing with production and productivity within the context of an ageing nation (‘shrinking
labour force because of ageing’; ‘possibly the bankruptcy of social security systems’). One
medium has written that two-thirds of people ≥ 65 years are alive today (BRW, 1999), which
strengthens the issue of taking population ageing to the forefront of national debate. Thus, it is
clear that population ageing is a global phenomenon; but what is the extent of this in Caribbean
states? To further comprehend this phenomenon or to explain this unbounded demographic
reality; I will contextualize this paper within a global framework, with particular emphasis on
selected Caribbean and more so on Jamaica.

       Insert Table 1.2

       Ageing Defined.

       Ageing is a significant but neglected dimension of social stratification and the life-course
       is an essential component of the analysis of status (Turner 1998:299)


        “Where ‘Old age’ begins is not precisely defined, the onset of older age is usually
considered 60 or 65 years of age” (WHO 2002:125). The indecisiveness to reach consensus on a
definition of ageing in spite of the United Nations’ perspective on the elderly, which is
chronological ageing that begins at 60 years, yet demographers and many statisticians continue


                                                 2
to conceptualize this variable as beginning at age 65 years (Lauderdale 2001; Elo 2001; Manton
and Land 2000; Preston et al. 1996; Smith and Kington 1997; Rudkin 1993). This moot point
will not be settled in this paper, but what will happen here is that the various perspectives will be
presented to the readers. As a demographer, however, I will primarily be using the chronological
age of 65 years and older to present the commencement of ‘old age’ (or ageing). But one should
keep in mind (as Turner date outlines) that ageing is a ‘social stratification’ which is neglected
within the discourse of social stratification.

       In medieval times, Thane (2000) notes that ‘old age’ were defined as 60 years and older.
She justified this by forwarding 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. Ancient Rome, on the other hand, ‘old age’ began from early 40 to
70 years, with 60 years being “some sort of annus climactorius”. Demographers see the seniors -
the elderly or the aged (old people) - as individuals 65 years and older, and not an individual who
is 60 years of age. 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. Irrespective of
the commencement age of the elderly, there is a wholesale agreement that the aged at the
beginning of the next generation will be a real social challenge. One 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
“elderly” is using 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, Eldermire questioned academics and other scholars for their rationale in using
65 years. I will now classify the ageing in two main categories, (1) chronological and (2)
biological ageing.

       Chronological ageing

       Within the study of demography, the 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 has elapsed
since birth (Erber 2005; Iwashyna et al. 1998; Preston, et al. 1996; Smith and Waitzman 1994).
However, based on the monographs from other scholars (such as - Marcoux 2001; Eldemire
1997; PAHO and WHO 1997; Eldemire 1995; Eldemire 1994; Barrett 1987), the issue of the



                                                 3
aged begins at 60 years.        Hence, the issue of the aged continues to battle from non-
standardization. For those who use 60 years, they adopt this value because of the World
Assembly on Ageing (in Vienna, Austria: July-August 1982), which postulates that ageing
begins at the chronological of 60 years.

       The Canadian statistical agency used age 65 years as the dividing line between “young”
and “old” (Moore et al. 1997, 2; Smith and Waitzman 1994; Preston, et al., 1996). The issue of
using the chronological age of 65 years to measure older adulthood according to one academia
comes from the minimum age at which the Social Security System begins disbursing payment
for pension to people living with the United States (Erber 2005:12). It is argued that in 1935, the
U.S. government modeled this from the German’s retirement system. This explains the use of 65
years of age by many scholar, 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?

       Biological ageing

       Organisms age naturally, which explains biological ageing. 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 state
of the cells. Embedded in this apparatus is the genetic composition of the survivor. This occurs
where the body’s longevity is explained by genetic components. Gompertz’s law in Gavriolov
and Gavrilova (2001) shows that there is a fundamental quantitative theory of ageing and
mortality of certain species (the examples here are as follows – humans, human lice, rats mice,
fruit flies, and flour beetles (, 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 an adult, but that this becomes less progressive in advanced ageing.
Thus, biological ageing is a process where the human cells degenerate with years (the cells die
with increasing in age), which is explored in evolutionary biology (see Charlesworth 1994). But
studies have shown that using evolutionary theory for “late-life mortality plateaus”, can fail
because of the arguably the unrealistic set of assumptions that the theory uses to establish itself.


                                                  4
       Reliability theory, on the other hand, is a better fitted explanation for the ageing of
humans than that argued by Gompertz’s law as the ‘failing law’ speaks to deterioration of human
organisms with age (Gavrilov and Gavrilova 2001) as well as a non-ageing term. The latter
based on Gavrilov and Gavrilova (2001) can occur because of accidents and acute infection,
which is called “extrinsic causes of death”. While Gompertz’s law speaks to mortality in ageing
organism 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, it 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 to measure ageing.
Nevertheless, this construct is able to compare and contrast organisms in relation to the number
of years, a cell may be likely to exist. Erber (2005) argues that this is undoubtedly subjective, as
we are unable within a definite realm to predict the life span of a living cell (Erber 2005:9).
Interestingly, the biological approach highlights the view that the ageing process comes with
changes in physical functioning. The oldest-old categorization is said to be the least physical
functioning compared to the other classification 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 (Erber 2005; Brannon and Fiest 2004).

       In order to avoid such pitfalls in constructions that may arise with the use of the
biological approach, ergo, for all intent and purposes, given the nature of policy implications in
effective planning, the researcher is forwarding the perspective that seniority in age commences
at age 65 years – using the chronological ageing approach.

       In summarizing the ageing transition, both chronological and biological ageing have a
similar tenet; in that, as we move from young-old to oldest-old, the body deteriorates and what
was of low severity in the earlier part of the ageing process becomes crucial 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 positive, as he/she
becomes older – using the ageing transition (65 years and older) – the losses (or negatives)
outweigh the positives. This simply means that the functionality limitation of the body falls, and



                                                 5
so opens the person up to a higher probability of becoming susceptible to morbidity and
mortality. Secondly, their environment, which may not have been problematic in the past, now
becomes a health hazard. One University of Chicago scholar summarizes this quite well in Table
1.3:




         Table 1.3: Characteristics of the Three Categories of Elderly, and Ageing transition

               Characteristic                                         The Ageing Transition


                                                             Young-old                Aged          Oldest-Old

               Heath 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 other                          Low                 Moderate High

               Social isolation                             Low                 Moderate High

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

              1
                  Donald Bogue (1999) used aged (age 75 – 84 years) to refer to what this paper calls old-old


       Historical Issues on Population Ageing: Global Perspectives.

              Ageing has emerged as a global phenomenon in the wake of the now virtually
              universal decline in fertility and, to a lesser extent, of increases in life expectancy
              (Marcoux 2001:1)
              In the earlier centuries, pandemic and pestilence would destroy millions of lives.
An example here is, in the fourteenth century, the ‘Black Death’, killed approximately 40 million
people worldwide. One scholar argues that this disease ‘wiped out’ about one-third to one-half
of European’s and Asian’s human population (Rowland, 2003). As during the 1700s, smallpox



                                                                  6
killed an estimated 100 peoples worldwide. This reality explains why population ageing was not
a phenomenon then, as the deaths were high and widespread. Therefore, the person was not
likely to live beyond fifty years. Following those pandemics and plagues, the discoveries of
peninsulin along with proper sanitation and public health have seen a significant reduction in
mortality. Whereas low mortality is not synonymous with all nations, low death rates have been
the experience of a plethora of the developed societies. This reality is also happening in many
developing and emerging nations. Accompanying mortality decline is the issue of the fertility
transition that began in France in the 19th century. It is argued, that reduction in fertility is
primarily a cause of population ageing today as well as a steady decline in mortality rates.

        Even though, the ageing process is life long and though it may be constructed differently
within each society, many decades have elapsed since Galton’s study on the health status of
people. Despite changes in human development and the shifts in world population toward
demographic ageing – people living beyond 65 years (see ILO, 2000; Wise, 1997), the issues of
the aged and their health status, in particular general wellbeing, have not taken front stage on the
radar of demographers, unlike many other demographic issues.

       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 (Bubonic Plague), smallpox and ‘diphtheria’ to diseases such as cancers, heart
illnesses, and diabetes. Although diseases have shifted from infectious to degenerate, chronic
non-communicable illnesses have arisen and are still lingering within all the advances in science,
medicine and technology. One demographer showing the extent of human destruction due to the
Black Death mentioned that this plague reduced Europe’s population by one-quarter (Rowland,
2003:14). Accompanying this period of the ‘age of degenerative and man-made illnesses’ is life
expectancies that now exceed 50 years. So while people aged 70 years and beyond in many
developed and a few developing states, 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?

       Before the establishments 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 (physical functioning or illness and/or disease-causing organism),



                                                 7
(Brannon, & Feist, 2004:9). Many official publications used either (i) reported illnesses and
ailments, or (ii) prevalence of seeking medical care for sicknesses. 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
patients. To illustrate this more vividly, the researcher will quote a sentiment made by a medical
doctor in ‘The Caribbean Food and Nutrition Institute Quarterly, 1999.          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 …” (quoted in the editorial of Caribbean Food and Nutrition Institute
1999:180).

        A demographer, Alain Marcoux, measured population ageing in an article titled
‘Population ageing in developing societies: How urgent are the issues?’ as a specified valuation
of the general population being 60 years and older. The benchmark that was used to establish this
situation is the proportion of the population who are aged 60 years and over exceeds 10%
(Marcoux 2001:1), whereas another group of scholars Gavrilov & Heuveline (Gavrilov, &
Heuveline, 2003) used 65 years and beyond that exceeds 8-10%. These include for example -
Germany, Greece, Italy, Bulgaria and Japan; U.S.A; Sweden (Goulding, & Rogers, 2003).
Interestingly, Greece and Italy’s aged population (people 60 years and older) in 2000 stood at
least 24% of the total population (Mirkin, & Weinberger, 2001), which indicates the completion
of the fertility and mortality transition, and the high burden being placed on the working
population. Those societies’ fertility decline began early and their mortality at older ages has
been declining; this justifies their ageing population. This is not only confined to developed
societies as it is spreading to the entire world.

        Demographic Trends: The Global perspective

        Globally, trends in population ageing are such that demographic ageing is seen as a
fundamental phenomenon of concern both inside and outside of the intelligentsia class. I will
display the issue in great detail below, as the figures will speak of the trends that we have seen
more so since the 1900s. And that this progression will continue in the next 50 years. The aged
persons >65 years and older in 1950 was 5.2%, and by 1995 the figure rose to 6.5%. But, during



                                                    8
the 1950s-1960s, the 65+ age cohort rose by 0.1%, which may be marginal but it earmarks the
beginning a demographic phenomenon.

       In 1999, persons aged 65 years and older were 410.5 million, and one year later the figure
rose to 420 million, which is a 2.3 percentage increase over the previous year. In addition during
2000 to 2030, it is estimated that aged persons >65 years, will rise from an approximated 550
million to a projected 973 million (76.9%). By 2050, the persons aged 65 years and beyond, will
be some 13.8% of the world’s population.             Currently, the developed nations share
disproportionately more of the aged persons >65 years, this reality is not projected to change in
the future. However, by 2030, the absolute number of aged >65 years in the developing societies
is expected to triple, which will not be the same for the developed nations (from 249 million in
2000 to 690 million by 2030). In summary, during 1950-2000, the elderly population (persons
65+) increased by 1.7%. However, from 2000-2050, the same aged cohort will rise by 6.9%,
which denotes a 100% increase in 50 years.

       The statistics reveal that come 2050 most of the aged population will be residing in
developing countries. In addition, by 2030 the population 65-and older in developing societies
would have increased by 140 percent, which is 40% more elderly in developing nations than in
the world. Importantly, the aged are on the upper end of the ageing spectrum; and this affects the
population dynamics of the society. The total human population, within any geographic area,
constitutes children, youth, working aged people and the elderly. With this said, the “graying”
(spelling not consistent throughout) of a population is caused by fertility decline, reduced
mortality and migration of the young and return of retirees coupled with increases in life
expectancies. Where the elderly population outgrows the younger population, this constricts the
population structure at younger ages and expanding it at older ages (Rowland, 2003:98). This is
referred to as demographic transition. It is the experience of many developed countries that
started with France, but has increasingly become a phenomenon for many developing nations.

       The demographic development of the world is not limited to the increase in persons 65
years and older but the reduction of the children population (persons 0 – 14 years). In 1950, the
children population was 34.3% of the globe’s population, and in 1975 the figure rose to 36.8%,
and in 2007 the United Nations (2007:72) wrote that this is expected to be 27.6% and come
2050, 20.2%. Accompanying this reduction in the children population is the increase in the


                                                9
median age of the world’s population. As at the state of the 1950, this was 23.9 years, it fell to
22.4 years in 1975 and is estimated to rise to 28.1 years in 2007 and project to reach 37.8 years,
which is an indication of population ageing. The increase in proportion of people ≥ 65 and
changes in the median age can be simply explained by mortality changes, which demographers
use life expectancy to explain. In life expectancy at birth during 1950-1955 was 46.6%, in 1975-
1980, 59.9 years, and 2005-2010, 66.5 years and come 2045-2050 it is expected to reach 75.1
years.

         In the more developed nations, currently (in 2007) estimated by the United Nations,
2007:74), 20.7% of the population are persons ≥ 60 years, 15.5% are persons ≥ 65 years, and
3.9% are persons ≥ 80 years. The life expectancy for people in these regions is more than the
world’s figure, as the United Nations (2007:75) writes that during 2005-2010, it is 76.2 years.
However, in Northern Europe, it is 78.7 years, Southern Europe; it is 79.1 years, Western
Europe, 79.6 years, and in Northern America, 78.2 years. Thus, population ageing is indeed a
global phenomenon and more so in developed nations, but what about the Caribbean and in
particular Jamaica?

         Demographic trends: Selected Caribbean Nations

         Ageing inevitably means longer life that affects the population composition and structure.
Due to the fact that as the population ages, the base of the population pyramid narrows, while the
upper portion expands. Demographers argue that this is substantially due to the fertility transition
and reduced mortality at older ages. If reduced fertility continues without any major catastrophe
in the future, what we are likely to experience is people living longer, and the death rates at older
ages will begin to naturally increase thereby changing the population age structure further.
Global life expectancy has risen from 47 years in 1950-1955 to 65 years and beyond in 2000-
2005 and 2005-2015, which is similar for Jamaica, Trinidad and Tobago, Bahamas and Barbados
(United Nations, 2006:87-89; United Nations, 2005: xxii: STATIN, 2003). One of the
probabilistic results of ageing is the reduction on the working aged and the youthful population.
These provide shifts in the population pyramid as it contracts at younger ages and expand at
older ages. This is reiterated in a publication of the Caribbean Food and Nutrition Institute
(1999) that stated, “By the year 2050, there will be (shouldn’t more go here) older persons than
children in the world, the majority of whom will be females and widowed or without a partner.


                                                 10
The Caribbean is likely to mirror this phenomenon…” (Caribbean Food and Nutrition,
1999:191). The Statistical Institute of Jamaica pointed out that those societies that were at the
early stage of the demographic transition in which fertility remains high and mortality decline are
now experiencing an increase in the younger population. However, for those that are at the late
stage, where fertility is declining and mortality is stationary, the younger sector of the population
is smaller than the segment 60 years and older (STATIN, 2003). This is in keeping with the
global perspective on demographic transition.

        I will present a graphical display of the populations of the World and the Caribbean of
two age cohorts, children (0-14 years) and elderly (65+), as an indication of the similarities these
demographic trends. A further subdivision of selected Caribbean nations’ proportion of children
and elderly populations are presented in Table 1.4.



Table 1.4: Percentage of Estimated or Projected Populations of Selected Caribbean Nations,
1980, 2000, 2005 and 2020
                     1980                 2000                   2005                 2020




Country       0-14      60+ yrs    0-14       60+         0-14 yrs 60+         0-14      60+
              yrs                  yrs        yrs                  yrs         yrs       yrs

Barbados      29.6      14.1       22.5       14.1        18.9      13.2       19.4      19.3

Guyana        40.9      5.7        30.2       6.3         29.4      7.4        23.0      11.3

Jamaica       40.3      9.3        28.3       9.0         31.2      10.2       20.4      12.4

Suriname      39.8      6.3        32.4       7.9         30.1      9.0        24.2      9.8

Trinidad 34.3           8.1        28.6       8.4         21.5      10.7       23.5      13.3
& Tobago

Caribbean 36.7          8.6        29.9       9.9         27.7      10.7       24.2      14.2

Source: United Nations. 2005c: World Population Prospects: The 2004 Revision




                                                     11
       Demographic development in the Caribbean has taken a similar path like the rest of the
world (Population Reference Bureau, 2007; STATIN, 2006; United Nations, 2005c). Over the
years, the movement has being such that mortality and fertility has been declining, and the
population 65 years and older has been increasing proportionately more than proportion who are
children (See Tables 1.5, 1.6).
.

       By the standard that if a population of aged person using ≥ 60 years exceeds 8-10% of the
population, there is the issue of demographic ageing. So since 1980, countries like Barbados,
Jamaica, Trinidad and Tobago and generally the Caribbean have been experiencing this
phenomenon (Table 1.4). From the Table, by 2020, Barbados’ elderly population will be higher
than that of the Caribbean’s average. Among the factors of population ageing are mortality and
fertility. Thus, merely using the proportion of persons who are either 65+ or 0-14 years is an
indicator of demographic transition but mortality and fertility are critical determinants of ageing
population. According to the United Nations (2007:5),

       Decreasing fertility has been the primary cause of population ageing because, as fertility
       moves steadily to lower levels, people of reproductive age have fewer children relative to
       those of older generations, with the result that sustained fertility reductions eventually
       lead to reduction of the proportion of children and young persons in a population and a
       corresponding increase of the proportion in older groups (UN, 2007:5)


       The United Nations’ perspective has highlighted the importance of including fertility in
demographic transition discourse as well as mortality. Statistics reveal that the total fertility rate
(TFR) for 1970-1975 for the world was 4.49 and for 2000-2005, it fell to 2.65; whereas in Latin
America and the Caribbean between 1970-1975, it was 5.05 and this was further reduced to 2.55
in 2000-2005 (United Nations 2005c, xxi). Concurrently, in 2005, total fertility in The Bahamas
is 2.2, in Barbados it is 1.5, for Jamaica 2.3 and for Trinidad and Tobago, 1.6 (United Nations
2006, 87-89). Barbados and the twin islands of Trinidad and Tobago are experiencing below
replacement level fertility (Total Fertility Rate – TFR of 2.1 – United Nations 2000, 4), a
problem presently faced by many developed nations such as those in Southern and Easter Europe
and the United States (United Nations 2005c, xxi). I have presented Table 5Table 5, for a more
detailed assessment of the total fertility trends of selected Caribbean States, the Caribbean and



                                                 12
Latin America, in an effort for us to see the trend in this phenomenon, and the implications of
this for population ageing come 2050.

          Table 1.5: Total Fertility Rate for Selected Caribbean Nations, Caribbean, and Latin
                              American: 1950-1955 to 2045-2050

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

        Bahamas                4.1         3.2          2.2          1.9       1.9
        Barbados               4.7         2.2          1.5          1.8       1.9
        Belize                 6.7         6.2          2.8          2.0       1.9
        Dominican Rep          7.4         4.7          2.6          2.1       1.9
        Guyana                 6.7         3.9          2.1          1.9       1.9
        Haiti                  6.3         6.0          3.6          2.5       2.1
        Jamaica                4.2         4.0          2.3          2.0       1.9
        Suriname               6.6         4.2          2.4          2.0       1.9
        Trinidad &             5.3         3.4          1.6          1.8       1.9
        Tobago
        Caribbean              5.2         3.6          2.4          2.1       1.9
        Latin America &        5.9         4.5          2.4          2.0       1.9
        Caribbean

        Source: World Population Ageing 2007



       Another determinant of the demographic transition is mortality. The mortality statistics
are used to compute the life expectancies, and so the researcher will use the latter as it is an
indicator of the former. Mortality in the Caribbean has been falling and this can be seeing from
the increased life expectancies, which are highly comparable with those in developed nations,
which is beyond 71 years(United Nations 2007 – See Table 1.6, below).



         Table 1.6: Life Expectancy at Birth of both Sexes for Selected Caribbean Nations, the
                                Caribbean, and Latin American



                                                 13
         Countries              1950-       1975-        2005-        2025-      2045-
                                1955        1980         2010         2030       2050

         Bahamas                59.8        67.2         72.1         78.0       82.0
         Barbados               57.5        71.4         76.4         79.2       81.4
         Belize                 57.7        69.7         71.7         74.0       78.0
         Dominican Rep          45.9        61.9         68.6         73.8       77.7
         Guyana                 52.3        60.7         65.4         70.6       74.2
         Haiti                  37.6        50.6         53.5         62.2       70.1
         Jamaica                55.8        70.1         71.1         75.0       77.7
         Suriname               56.0        65.1         70.2         74.7       78.1
         Trinidad &             59.0        68.3         70.1         74.1       78.5
         Tobago
         Caribbean              52.2        64.5         68.7         73.2       76.9
         Latin America &        51.4        63.0         72.9         76.8       79.5
         Caribbean

       Source: World Population Ageing 2007



       Demographic Trends: Jamaica

       The use of life expectancy, mortality, and total fertility rates are just some of the ways
with which demographic development can be shown. Instead of showing both mortality and life
expectancy, for this section of the paper the researcher will use life expectancy. As mortality
rates are used to calculate the life expectancy at various ages (Table 1.7). Another way of
depicting population changes is through the use of a population pyramid. In this section, the
researcher will use Jamaica’s population pyramid since 2000 to depict the demographic
transition occurring in this society, and then percentages of the elderly people with regard to the
total population. It should be noted that the nation’s population pyramid in the year 2000
showed a narrow top and a broad base. But by 2025, the population narrows at the base and
begins to expand at the middle, and come 2050, note how the population contrasts at the base as
we move toward an ageing population.



                                                14
       Come 2050 and beyond, Jamaica’s oldest elderly will be substantially more females. The

“graying” of the Jamaica’s population is coming, and has already made its way within the

society.   From a demographic perspective, relatively speaking a society is said to be old

whenever the population of person aged 60 or over (and some scholars use 65 years or over)

exceeds 8-10%, which is the case in Jamaica (Appendix I). This is not the only indicator as life

expectancy can be used to show population ageing. 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’ life expectancy rose to 71.26 years and that of the females’ to 77.07 years, which is

a clear indictor of demographic ageing (See Table 1.7).



             Table 1.7: 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)


       From records of the Population Division of the United Nations, Jamaica’s population 60
years and older in 2050, using the medium (should it be median) variant, is likely to be 24% of
the entire population, with 18.1% being 65 years and older, compared to approximately 5%
being 80+ years. These shifts mean more degenerated conditions at older ages, increased
disability and diminished quality of life.   The disparity in gender composition speaks to the
higher morbidity in women and higher mortality for men (see Newman 2000: 8).



                                               15
       In 2004, Jamaica’s old-aged population stood at 7.7 percent. According to WHO/SEARC
(1999), India’s elderly population was 7.7 percent. During 2004-1991, the elderly population of
Jamaica rose by 3.28 percent. When the elderly is strictly operationalized within a
demographer’s space (65 years and beyond), on an average the elderly population grew by 3.62
percent. The data in Appendix II reveal that for every 100 working-aged of the population there
are approximately 13 elderly that is dependent on them. This reality is within approximately 30
percent of the population being children. Over the same period, the number of child-to-total-
population grew by - 4.4 percent and by -10.08 percent for the youth. Within this context, there
is a need to analyze the labour force participation of aged Jamaicans as there would be socio-
economic implications if this were to be declining in the nation.

       There is little debate within the public arena about the increasing decline of the labour
force participation rate of aged Jamaicans. In 1980, the labour force participation rate (in %) was
46.4% and it is estimated that this to be 26.6% in 2007. This represents a 43% reduction in the
number of people 65+ years who were actively involved in the labour force. When the labour
force participation rate is decomposed by sexes, the figures reveal a more telling disparity. As
for females, in 1980, there were 30.4% of women actively involved within the labour force, but it
is estimated to be 13.8% in 2007, which is a 55% reduction in the number of employed females.
With respect to males’ involvement in the labour force, it is projected to fall to 41.4% in 2007,
which is coming from 65.3% in 1980. The labour force participation rate for men will fall by
23% compared to that of females that will decline by 55%. This is within the context of females
living longer than their male counterparts, and that the retirement age for females is 60 years and
not 65 years (Table 1.8). Therefore, if we are to extrapolate a reduced 5 years for females, the
labour force participation rate will increase further by at least percentage points.




                                                 16
Table 1.8: Jamaica: Selected demographic variables, Labour Force Participation (in %).
Total (% of population4)        1950            1975          2007           2025            2050
         60+                    5.8             8.5           10.3           15.0            23.6
         65+                    3.9             5.8           7.6            10.3            17.7
         80+                    0.2             0.8           2.0            2.3             5.6
Female                          1950            1975          2007           2025            2050
         60+                    6.6             9.0           10.7           16.1            25.9
         65+                    4.4             6.3           8.1            11.0            19.9
         80+                    0.3             1.0           2.2            2.6             6.9
Male                            1950            1975          2007           2025            2050
         60+                    5.0             8.0           9.9            13.8            21.3
         65+                    3.2             5.3           7.1            9.7             15.4
         80+                    0.2             0.6           1.8            2.0             4.3
                                1950            1975          2007           2025            2050
Median age                      22.2            17.0          24.9           30.7            39.3
Labour Force Participation      1980            1990          2007           2010            2020
        65+                     46.4            37.1          26.6           26.6            25.1
        65+                     30.4            23.6          13.8           13.1            12.3
        65+                     65.3            53.6          41.4           40.7            39.6
United Nations, 2007:308-309
         Another variable that can be used to indicate population ageing is the median age. The
median age denotes a value that where one-half of the population is above or below that age.
Continuing, the median age for Jamaica’s populace in 1950 was 22.2 years and it is estimated to
reach 24.9 years in 2007 and come 2025 31 years, and by 2050 it should increase by another 8.6
years. It should be note here, that demographers use a median age of 30 years to indicate an
ageing population. Thus, population ageing is without a doubt a Jamaican phenomenon like the
National debt problem and other social issues such as crime and teenage pregnancy.

         Without effective population planning for the elderly, come the next four decades, the
old-aged population will become a burden to the working aged-populace in respect to medical
care, nursing care, pension, other social insurance and survivability cost. With this impending
social reality, there is a high probability that the old-aged will be called on to provide
increasingly more of their needs for themselves within the construct of limited resources from
developing societies. The physiological changes with ageing such as loss of hair, wrinkling of
the skin, decrease in height, and loss of teeth are not the only issue of old age but there are other
critical factors that affect their wellbeing.

         State of the Elderly, with emphasis on Caribbean and Jamaica

         The Caribbean like many developed countries is now faced with the daunting task of
addressing the “graying” of its population, because of mortality and fertility decline, which


                                                  17
began1960s. To show that this is a challenge to geographic topography, the region launched its
first forum titled ‘The Caribbean Symposium on Population Ageing’ in November 2004 in Port
of Span, Trinidad and Tobago, in order to strategize about this inevitable demographic transition,
which began in earnest in developed societies. This is a precursor to its predecessor which was
held in Vienna in 1982 called ‘The First Assembly on Ageing’ and another named ‘Second
World Assembly on Ageing’, which was in Madrid in 2002. Like the developed world, the
Caribbean islands are cognizant that policy implementation and mechanism are needed to forge
an equitable solution for this phenomenon. With the Symposium comes the recognition that
ageing is not limited to its call but that it affects the general society, future generations and
political decisions. Ergo, what is the state of the grayed population in Caribbean and more so
within Jamaica.

       A study revealed that there is a statistical causal relationship between socioeconomic
conditions and the health status of Barbadians. The findings revealed that 5.2% of the variation
in reported health status was explained by the traditional determinants of health. Furthermore,
when this was controlled for current experiences, this percent fell to 3.2% (falling by 2%).
When the current set of socioeconomic conditions were used they account for some 4.1% of the
variation in health status, while 7.1% were due to lifestyle practices compared to 33.5% that was
as a result of current diseases (see Hambleton et al. 2005). It holds that importance place by
medical practitioners on the current illnesses – as an indicator of health status – is not unfounded
as people place more value on biomedical conditions as responsible for their current health
status. Despite this fact, it is obvious from the data – using 33.5% - that there are other
indicators that explain some 67.5% of the reason why health status is as it is. Furthermore, with
an odds ratio of 0.55 for number of illness, there is clearly suggesting that the more people
reported illness, the lower will be their health status. (See Hambleton 2005); and this was equally
so for more disease symptoms – odds ratio was 0.71)

       Accompanying the reduction in physical functioning which is a feature of biological
ageing (Erber 2005) is the fact that the Jamaican elderly spend the most number of days
receiving medical care for illnesses and/or injuries (see PIOJ and STATIN 2002:4.1). In addition,
they experience the highest rate of protracted illness the country, with the “… very young and
the elderly being the most vulnerable” (PIOJ and STATIN 1997:45). Embedded in this finding is



                                                18
the poor health status of the elderly despite living longer. Essentially, this particular group is
suffering from ill health caused by diabetes, stress, psychiatric disorders and chronic diseases,
which translates into lower quality of life while their life is prolonged (see PIOJ and STATIN
1994:22.1; 1990:20.1), which means they are living longer but suffering more - the high cost of
longevity of life.

        A Ministry of Health (MOH) report notes that the prevalence of chronic illnesses has also
increased with ageing and that this is even more pronounced for those 65 years and older, with
more males than females spending more time in health care facility (MOH, 2004:75), using the
discharge rate – 975.1 per 10,000 for males compared to 817.1 per 10,000 females. Interestingly,
when a detailed analysis was done of the data, seniors who reside in rural areas were suffering
more than their counterparts who live in other zones (PIOJ and STATIN 2000:58). A PIOJ and
STATIN (1995:32) report summarizes the wellbeing status of those 60 years and older, when
they say “… our 60 year olds exhibited the highest prevalence of protracted illness/injuries”. The
situation is speaksof is a state of well-being for the elderly that is not in keeping with the
positives of the advancement in medicine and medical technology. There is definitely a disparity
between the seniors’ wellbeing reality and their lived years, which reiterates the need to measure
wellbeing outside of the traditional biomedical model.

        From the findings of a cross-sectional study conducted by Powell, Bourne and Waller
(2007) of some 1,338 Jamaicans, 19.0% of respondents perceived that their economic well-being
to be ‘very bad’. In addition, when they asked, “Does your salary and the total of your family’s
salary allow you to satisfactorily cover your needs”, 57.4% of them felt that this “does not cover”
their expenses (Powell, Bourne and Waller 2007:29). What is the situation of the elderly seeing
that this group is even more (or equally) vulnerable than other age cohorts? The answer to this is
embedded within JSLC reports. The JSLC (1997) makes it clear that the aged population
(22.6%) and the children (less than five years – 14.7%) reported the highest number of
illness/injury, with those who resided in the rural areas being more vulnerable than those in other
zones are. In order to capture the severity of the issues faced by the Jamaican aged, if we are to
convert the mean number of days of reported illnesses into monetary terms, then the medical
expenditure of the elderly would have helped to erode their well-being, along with the illnesses
and their severity. Then, when retirement, loss of income, the cost associated with protracted
ailments, and the psychological challenges associated with ageing are collated and included in


                                                19
the daily life of the elderly, within the context of a shrinking economy, rising prices, the poor and
the elderly in particular the poor aged would be more vulnerable than other age groups within
this society.      There is an interconnection between economics and demography.                            In that,
economists are concerned about human economic decisions at the micro and the macro level.
The demographer, on the other hand, invests time in studying the science of human population.
Therefore, while the demographer is not interested in the costing of decisions, the economist
requires a thorough understanding of the principles of the human population, in an effort to
effective comprehend how people within a particular geographic area are probable able to make
decision.      The interconnectivity is evident that at the London School of Economics, the
department of demography is a subsection.

            A study on the elderly published in the Caribbean Food and Nutrition Institute’s
magazine Cajanus found that 70% of individuals who were patients within different typologies
of health services were senior citizens (Caribbean Food and Nutrition Institute 1999; Anthony
1999). Among the many issues that the research reported on are the six major causes of
morbidity and mortality identified by the Caribbean Epidemiology Centre that is of paramount
importance to this discussion; the influence of - cerebrovascular, cardiovascular, neoplasm,
diabetes, hypertension and acute respiratory infection (Figure 1.1). The diagram below depicts
the ranked order of the five leading causes of death for people 65 and over of selected Caribbean
countries in 1990.

            Trinidad &
             Tobago


              St. Lucia
                                                                                        A cute respiratory
                                                                                        inf ections
            Monts errat                                                                 Hypertension
    Cut y




              Jam aica                                                                  Diabetes
     onr




                                                                                        Neoplasms
               Guyana

                                                                                        Cardiovascular
             Dom inica                                                                  disease

                                                                                        Cerebrovascular
                                                                                        disease
             Barbados


             Baham as


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




Figure 1.1: Ranked Order of the five leading causes of mortality in the population 65 yrs and older, 1990




                                                        20
Source: adopted from Caribbean Food and Nutrition Institute 1999: 222



        In seeking to explain the severity of the health status of Caribbean nationals, using

Barbados and Jamaica, the Caribbean Food and Nutrition Institute (1999) presents the 5-leading

causes of morbidity as reported by seniors. The data revealed that the primary cause of illnesses

in Barbados and Jamaica was hypertension. In both countries, hypertension was a female

phenomenon – in Barbados, females reporting 44.6% compared to 33.1% for males and in

Jamaica it was 55.4% for females and 30.3% of males (Figure 1.2, below).



                              Str oke




                      Heart disease
                                                                                         Jamaica
                                                                                         Female
            D a s
             ise se




                                                                                         Jamaica Male
                            Arthritis

                                                                                         Barbados
                                                                                         Female
                            Dia betes                                                    Barbados
                                                                                         Female
                                                                                         Barbados
                                                                                         Male
                      Hyp erte nsi on



                                        0         20           40         60
                                                   Percentage



                      Source: Figure taken from Caribbean Food and Nutrition Institute 1999:225.
                 Figure 1.2: Leading causes of self-reported morbidity in the population
        of seniors, by gender in Barbados and Jamaica.




        The data in Figure 1.2 shows that hypertension and arthritis are morbidities that
significantly plague both men and women in both Caribbean countries. These chronic non-



                                                          21
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. 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 the daily living could further add stresses to the status
of life experienced by the elderly. Hence, living longer although it is directly related to reduced
mortality, this 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, show there is an
association between chronic conditions and functional limitation – which include difficulty
walking, bending, blindness in at least one eye and deafness (Costa 2002).              Among the
significant findings is – (i) the predictability between congestive heart failure of men and
functional limitation (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 further add to the difficulties of movement of the aged, be it man or woman.

       Like many developed countries, Jamaica is able to boast of its notable achievement in
progress made toward advancing the health status of its populace, during the twentieth century –
the postponement of death, lowering fertility, high nutrition and sanitation and more importantly
the increasing life expectancy. Analyzing data on life expectancy indicate that the country’s
health status is reasonably good, as the values for life span is similar to those in some First
World societies – over 70 years.

       Nevertheless, those positives are not sufficient to outweigh the increases in chronic non-
communicable diseases - hypertension, diabetes, cardiovascular diseases, neoplasm, depression
and arthritis. These diseases are on the rise in the world and are no different in Jamaica. They
continue to plague those who are more so 60 years and older, of a particular socioeconomic
status, and who live in rural Jamaica (Ministry of Health 2004, 133; Jamaica Social Policy
Evaluation 2003; Planning Institute of Jamaica [PIOJ] and Statistical Institute of Jamaica
[STATIN] 2000:58). In an article published by Caribbean Food and Nutrition Institute, the
prevalence rate of diabetes mellitus affecting Jamaicans is higher than in North America and
“many European countries”. (Callender 2000:67). Diabetes Mellitus is not the only challenge
faced by patients, but McCarthy (2000) argues that about 30% to 60% of diabetics also suffer
from depression, which is a psychiatric illness. Such a situation further complicates the woes of


                                                 22
the elderly as they seek to balance other psychosological conditions with the diabetes and
hypertension along with the stress which is frequently associated with the illness.

            Furthermore, in attempting to contextualize the state of the Jamaican elderly, the
researcher will provide a diagram depicting the five main causes of death by different age groups
between 2002 and 2004. The diagram shows that while life expectancies are increasing, that
mortality from non-communicable diseases such as heart diseases, cerebrovascular diseases and
diabetes are indeed high for the elderly and are thereby lowering their wellbeing (Figure 1.3).

            In 2003, data presented by the Ministry of Health Jamaica in its ‘Annual Report’ showed
that of the patients who are 65 years and older, 29.7% of them were discharged from inpatient
care because of ‘circulatory system diseases’, and nutrition and endocrine ailments accounted for
12.6%. While it is true that these diseases influence physical inactivity, the conditions of coping
with these as well as the cost of care undoubtedly should be aiding to lower the wellbeing status
of these people.


                      70+
                                                                           Other heart
                                                                           disease
                    60-69

                                                                           Ischaemic

                    50-59
      A cohorts




                                                                           Homocides
                    40-49
       ge




                                                                           Diabetes
                    30-39



                    15-29                                                  cerebrovascu
                                                                           lar

                  under 15


                             0         20        40         60       80

                             Percent dis tribution of 5 m ain caus es of
                                               deaths




Figure 1.3.: Percentage distribution of 5 main causes of deaths by age: 2002-2004



                                                       23
Source: Adopted from the Demographic Statistics, 2005, (STATIN 2006:x).

       Findings from studies by the Planning Institute of Jamaica show that while the general
health status is commendable, increases in chronic illnesses are undoubtedly eroding the quality
of life enjoyed by people who are 65 years and older (PIOJ and STATIN 2000:58-59; 1997:45).
The report revealed that, “In 2000, the survey also demonstrated the importance of recurrent
(chronic) illness as the cause of ill health among the elderly” (PIOJ and STATIN 2000:58). How
is the status of elderly within general setting of higher recurrence of chronic non-communicable
diseases and their severity among senior citizens? Within the macho culture of Jamaica,
generally, men do not seek preventative care because it is seen as weak. Such a position is learnt
from the culture, which states that boys should “suppress reaction to pain” (Chevannes 2001:37).



       State of the Elderly: Disparity in the Sexes

       Chevannes provided the explanation for this behaviour by men, that it is entrenched in
social learning theory. Where the young imitates the roles of society’s members through role-
modeling of what constitutes acceptable and good roles which is supported by reinforcement
(Chevannes 2001:17). The gender role of sexes is not limited to Jamaica or the Caribbean but a
study carried out by Ali and Muynck (2005) of street children in Pakistan found a similar gender
stereotype in that nation. It was a descriptive cross-sectional study carried out during September
and October 2000, of 40 school-aged street children (8-14 years). The sample was substantially
males (80%), with a mean age of 9 years (± 2 years). The methods of data collection were (i)
semi-structured interviews, and (ii) a few focus group discussions. Ali and Muynck (2005)
found that the sampled population would seek medical care based on severity of illnesses and
financial situation. Another finding was that they referred to use home remedy. The reason
being that mild ailment is not severity enough to barr them from physical functioning, which
mean that they are okay; and so some morbidities are not for-hospital, which was so the case in
Nairobi slums (Taff and Chepngeno 2005:421).

       PIOJ and STATIN (1998) report that “The difference by gender was significant, with
10.9 per cent of females reporting illness, compared with 8.5 per cent of males” (PIOJ and
STATIN 1998:45), which is the case even in 2002, that is the rate was 14.6% for females and
10.4% for males, and in 2004 it was 13.6% for females and 8.9% for male (PIOJ and STATIN


                                               24
2006; 2003). From statement in the JSLC 2000 “Women have traditionally utilized health care
services more than men and these interactions have allowed closer monitoring and earlier
diagnosis of health conditions among women” (PIOJ and STATIN 2001:58), then this begs the
question – Are the aggregate data reported reflecting the views of the elderly or more so the
females? However, what is true is that they [men] will visit health practitioners because the
states of their chronic impairments are severe. This is evident in the higher number of treated
cases in some ailments over that of females – from the hospitalization discharge rate for the
persons 65 years and over, the rate for men is 975.1 per 10, 000 compared to 817.1 per 10, 000
females. (Ministry of Health 2004:75, 133). The elderly, on the other hand, are more responsive
to their ill-health and seek medical attention readily, but what about the psychological state of
this age cohort from things such as – loss of partner, reduction in social support, fear of being
victimized and so forth. As a result, it should not be surprising that the elderly Jamaicans seek
more medical attention than other age cohorts, which is captured in them indicating more self-
reported illnesses and injuries and a higher mean number of days spent in medical care (PIOJ and
STATIN 2006; 2003; 1998). Hence, is the state of the elderly worse than that which is reported
in the JSLC? It should be noted that the data presented in all the official statistics on the health
status of Jamaicans are still measuring health using the old biomedical model (using reported and
treated illnesses and/or injuries) - (JSLC; MOH 2004). This approach is single focused as it
omits the role environment, social exclusion, fear of crime and victimization as well as
depression, and stress among other factors as determinants of individuals’ wellbeing.

       Conclusion

       This paper responds to the underlining concerns of the continuous increase in population
ageing in the world. The fast ageing of populations, unless managed in a proactive manner, could
impose serious challenges for policy makers in the Caribbean and Jamaica. Noteworthy is that a
particular level of economic development is needed in order to deal with the challenges of this
demographic transition. The demographic composition and structure of future world population
and subpopulation must be understood within policy framework. The challenges that are likely
to arise from an ageing population on public expenditure, on pensions and health care,
particularly in the absence of reforms in pensions and health services, could lead to a build-up of
public debt in developing countries in specific Caribbean islands



                                                25
       In conclusion, the graying of population is not restricted to developed societies such as
Japan, Germany, Canada, China, United States and Italy to name a few, but it is a current reality
for nations like Barbados, Trinidad and Tobago and Jamaica. Currently Jamaica does not see the
demographic transition of ageing as an issue but come 2030 or beyond, it will be a problem for
many developing states including that of Jamaica.

       The yardstick that is used as a symbol of the impending problem in demographic ageing
is if a state’s population 60 years or over is between 8 to 10 percent and beyond. The early
signals of demographic ageing, in Jamaica, began as early as in the 1960s, when the society
began experiencing mortality and fertility declines. With the introduction of family planning in
the 1970s, the high fertility in the 1960s has been reduced by some 300%. Statistics reveal that
the aged population of Jamaica is in excess of 10 percent as of 2005, within the context of an
increasing decline in the population 0 to 14 years. This population (age cohort 0-14 years) stood
at 40.3 percent in 1980 and in 25 years (2005), the population has being reduced to 31.2 percent.
The conditions of ageing in Jamaica are not only a demographic issue but are disproportionately
becoming a social, economic and political matter. In keeping with public health measure in the
form of better sanitary, food and water security and quality and vaccination, mortality was cut,
which is explanation for the high life expectancy of in excess of 75 years since 2004, to the best
of the researcher’s knowledge, no study has sought to examine the likely socioeconomic costs of
ageing come 2015 to 2050 and beyond.

       Despite all the gains of technology, public health, education, lifestyle behavioural
practices and high life expectancy, non-communicable diseases are on the rise and continue to
plague people age 60 years or over. Thus, accompanying population ageing is more ill-well
senior citizens. Within this general setting, there is a need for medical research on the way
forward in patient care as well as a demand exist for advanced quantitative assessment of the
model, which will evaluate wellbeing of the Jamaican elderly. This will foster a comprehensive
understanding of how health should be operationalized, and we then would be able to plan for
ageing in more informed manner than what presently obtains in our society.

       One of the socioeconomic and political challenges that the Caribbean in particular
Jamaica faces is the difficulty with which population ageing will become an economic cost.
Population ageing does not simply mean “graying” of population (or proportionately more


                                               26
persons ages 60 years or older or 65+) but with living longer comes the responsibility of paying
social security like pension for a longer period of time. Another issue that we have failed to
address in all of this discussion is the lowered taxes that are going to be collected as a result of
demographic ageing. Within the same construct is the dwindling of the children population and
lowered fertility, which means that come 2010 and beyond the elderly dependency ratio will be
increasingly more than in previous years. These developments will mean challenges for public
budgets, and health care expenditures. The reality is, demographic ageing is here in the
Caribbean and equally so in Jamaica. Systems and structures are needed to addressing the new
demand for this age cohort, along with the biopsychosocial state of ageing.




                                                27
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                                                 33
Table 1.1: Observed & Forecasted Percentage of Elderly 65 years or over in Selected Regions, and
   the World Countries: 1950, 1975, 2025 and 2050.

                           1950          1975          2007          2025          2050

                           %             %             %             %             %

World                      5.2           5.7           7.5           10.5          16.1

Africa                     3.2           3.1           3.4           4.2           6.7

Latin America &
the Caribbean              3.7           4.3           6.3           10.1          18.4

Caribbean                  4.5           5.4           7.8           11.4          18.9

China                      4.5           4.4           7.9           13.7          23.6

India                      3.3           3.8           5.4           8.1           14.8

Japan                      4.9           7.9           27.9          35.2          41.7

Europe                     8.2           11.4          16.1          21.0          27.6

Italy                      8.3           12.0          20.4          26.4          35.5

Germany                    9.7           14.8          19.6          23.9          25.4

Sweden                     10.3          15.1          17.6          22.1          24.7

USA                        8.3           10.5          12.4          17.7          20.6
Source: United Nations, 2007




                                                34
Table 1.2: Observed & Forecasted Percentage of Elderly 60 years or over in Selected Regions, and
   the World Countries: 1950, 1975, 2025 and 2050.

                           1950          1975          2007          2025          2050

                           %             %             %             %             %

World                      8.2           8.6           10.7          15.1          21.7

Africa                     5.3           5.0           5.3           6.4           10.0

Latin America &
the Caribbean              6.0           6.5           9.1           14.5          24.1

Caribbean                  6.9           8.1           11.1          16.4          24.8

China                      7.5           6.9           11.4          20.1          31.0

India                      5.6           6.2           8.1           12.0          20.7

Japan                      7.7           11.4          27.9          35.2          41.7

Europe                     12.1          16.4          21.1          28.0          34.5

Italy                      12.2          17.4          26.4          34.4          41.3

Germany                    14.6          20.4          25.3          32.1          35.0

Sweden                     14.9          21.0          24.1          28.3          30.9

USA                        12.5          14.8          17.2          23.8          26.4
Source: United Nations, 2007




                                                35
                                                                                  Chapter 2
The changing faces of diabetes, hypertension and arthritis in a
Caribbean population



Paul A. Bourne, Samuel McDaniel, Maxwell S. Williams, Cynthia Francis,
Maureen D. Kerr-Campbell, & Orville W. Beckford



Globally, chronic illnesses are the leading cause of mortality, and this is no different in developing
countries, particularly in the Caribbean. Little information emerged in the literature on the changing
faces of particular self-reported chronic diseases. This study examines the transitions in the
demographic characteristics of those with diabetes, hypertension and arthritis, as we hypothesized that
there are changing faces of those with these illnesses. A sample of 592 respondents was drawn from
the 2002 and 2007 Jamaica Survey of Living Conditions. Only respondents who indicated that they
were diagnosed with these particular chronic conditions were used for the analysis. The prevalence of
particular chronic diseases increased from 8 per 1,000 in 2002 to 56 per 1,000 in 2007. The average
annual increase in particular chronic diseases was 17.2%. Diabetes mellitus showed an exponential
average annual increase of 185% compared to hypertension (+ 12.7%) and arthritis (- 3.8%). Almost
5 percent of diabetics were less than 30 years of age (2.4% less than 15 years), and 41% less than 59
years. Three percent of hypertensive respondents were 30 years and under as well as 2% of arthritics.
The demographic transition in particular chronic conditions now demands that data collection on those
illnesses be lowered to < 15 years. This research highlights the urgent need for a diabetes campaign
that extends beyond parents to include vendors, confectionary manufacturers and government, in order
to address the tsunami of chronic diseases facing the nation.



Introduction
Globally, chronic illnesses are the leading cause of mortality (60%) [1, 2], and this is no different in

developing countries, particularly in the Caribbean [2-6]. Statistics indicate that 79% of all mortalities

are attributable to chronic diseases, and that they are occurring in developing countries such as those

in the Caribbean [3]. Using data for 1989 and 1990, Holder & Lewis [7] showed that hypertension

and diabetes mellitus were among the 5 leading causes of mortality in the English-speaking Caribbean

                                                   36
and Suriname. The findings from Holder and Lewis indicated that mortality resulting from

hypertension was highest in Dominica (over 90 per 100,000 of the population) and diabetes crude

death rates per 100,000 of the population were the greatest in Trinidad and Tobago (over 85 per

100,000).


       The 20th century has brought with it massive changes in the typology 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 complaints and diabetes.

Although diseases have moved from infectious to degenerate, chronic non-communicable illnesses

have arisen and are still lingering in spite of all the advances in science, medicine and technology.

Morrison [8] titled an article ‘Diabetes and Hypertension: Twin Trouble’ in which he established that

diabetes mellitus and hypertension have now become two problems for Jamaicans and people in the

wider Caribbean. This situation was corroborated by Callender [9] and Steingo at the 6th International

Diabetes and Hypertension Conference, which was held in Jamaica in March 2000. They found that

there is a positive association between diabetic and hypertensive patients - 50% of individuals with

diabetes had a history of hypertension [9, 10]. Prior to those scholars’ work, Eldemire [11] found that

34.8% of new cases of diabetes and 39.6% of hypertension were associated with senior citizens (i.e.

ages 60 and over). In an article published by Caribbean Food and Nutrition Institute, the prevalence

rate of diabetes mellitus affecting Jamaicans is noted to be higher than in North American and “many

European countries” [9].


       Chronic illnesses have been on the rise in the Caribbean. In a 1996 study conducted by

Morrison and colleagues in Trinidad and Tobago [12], they noted that there is an alarming rise in the

prevalence rate of diabetes mellitus (15-18%). A study in Barbados found that between 1988 and 1992

the prevalence rate of diabetes mellitus for the population was 17.5%; 12.5% in mixed population

(black/white), 6.0% in white/other and 0.3% in the younger population [13]. Another research, in
                                                  37
Europe, found that the prevalence among newly diagnosed diabetics in Europeans was 20%; African-

Caribbeans, 22%; and in Pakistanis, 33% [14]. They also postulated that there is an association

between poverty and diabetes. Van Agt et al. [15] went further when they found that poverty was

greater among the chronically ill, with which a later study by the World Health Organization [16]

concurred. The WHO [16] stated that 80% of chronic illnesses were in low and middle income

countries, emphasizing the association between not only diabetes and poverty, but chronic conditions

and poverty. The relationship between poverty and chronic conditions extends to premature mortality

[17]. Findings from the WHO [4] showed that 60% of global mortality is caused by chronic illness,

which offers an explanation of the face for those with these particular conditions. Within the context

of a strong association between poverty and chronic illness, the high prevalence of diabetes mellitus,

hypertension and other chronic conditions in developing countries should not be surprising [16, 18].


       Yach et al. [18] further opined that the global figure for diabetes is projected to move from 171

million (2.8%) in 2000 to 366 million (6.5%) in 2030. Of this figure 298 million of these persons will

be in developing countries, which reinforces the poverty-illness relationship. Chronic diseases can be

likened to a tsunami [19] in developing nations [20-22], and it seems to be spiralling because of the

unhealthy lifestyle of people. The tsunami of chronic illnesses in the developing countries is equally

reflected in the Americas [20, 21], and particularly Jamaica. The face of chronic illness in developing

nations is therefore for (1) lower socioeconomic strata, (2) rural residents, (3) adults, (4) gender

differences, (5) lower educational level, and (6) married people.


       A great deal of research exists on the management of chronic illnesses, and rightfully so, as

these go to the health status and mortality of a population [23, 24]. The profiles of those with chronic

diseases have never been examined in Latin America and the Caribbean, and studies outside of this

region have used a piecemeal approach to the investigation of chronic conditions. Hence information

is available on one or a few of the aforementioned faces of chronic illness, and some research has
                                                   38
examined diabetes mellitus and hypertension but not arthritis. The present gap in the literature will be

lowered by this study examining the faces of chronic illness from half a decade of data. Using data for

2002 and 2007, the current paper will investigate the changing faces of chronic diseases in Jamaica.

The study will utilize three chronic diseases (i.e. diabetes mellitus, hypertension, and arthritis), and

analyze health status, health insurance status, health care utilization, chronic illness and other

sociodemographic characteristics in order to ascertain the transition occurring in the population. We

hypothesized that there are changing faces of those with diabetes, hypertension and arthritis over the

last half a decade (2000-2007).




Materials and methods


Data

The current study extracted a sample of 592 respondents from the 2002 and 2007 Jamaica Survey of

Living Conditions (JSLC). Only respondents who indicated that they were diagnosed with particular

chronic conditions were used for this analysis (i.e. diabetes mellitus, hypertension, and arthritis). The

present subsample represents 0.8% of the 2002 national sample (25,018) and 5.7% of the 2007 sample

(6,783). The JSLC is an annual and nationally representative cross-sectional survey that collects

information on consumption, education, health status, health conditions, health care utilization, health

insurance coverage, non-food consumption expenditure, housing conditions, inventory of durable

goods, social assistance, demographic characteristics and other issues [25]. The information is from

the civilian and non-institutionalized population of Jamaica. It is a modification of the World Bank’s

Living Standards Measurement Study (LSMS) household survey [26].                   A self-administered

questionnaire was used to collect the data.

                                                   39
        Overall, the response rate for the 2007 JSLC was 73.8% and 72.3% for 2002. Over 1,994

households of individuals nationwide are included in the entire database of all ages [27].         The

residents of a total of 620 households were interviewed from urban areas, 439 from other towns and

935 from rural areas. This sample represents 6,783 non-institutionalized civilians living in Jamaica at

the time of the survey. The JSLC used complex sampling design, and it is also weighted to reflect the

population of Jamaica.


Statistical analysis


Statistical analyses were performed using the Statistical Packages for the Social Sciences for Windows

16.0 (SPSS Inc; Chicago, IL, USA). Descriptive statistics such as mean, standard deviation, frequency

and percentage were used to analyze the socio-demographic characteristics of the sample. Chi-square

was used to examine the association between non-metric variables, and an Analysis of Variance was

used to test the equality of means among non-dichotomous categorical variables. Means and frequency

distribution were considered significant at P < 0.05 using chi-square, independent sample t-test, and

analysis of variance f test.


Measures


Table 2.1 presents the operational definitions of some of the variables used in this study.


Results

Health care utilization, health insurance status, particular chronic illness (i.e. diabetes mellitus,

hypertension and arthritis), and sociodemographic characteristics are presented in Table 2.2. The

findings in Table 2.2 showed that the average annual increase in the particular chronic illness was

17.2% between 2002 and 2007. Arthritis showed an average annual reduction of 3.8%, hypertension, +

12.7% and diabetes mellitus, + 185.0%. Furthermore, the average annual increase in health care

                                                   40
utilization (visits to health care institutions) was 11.9% (public hospital, + 8.2%; private hospital, +

10.7%; public health care centre, + 8.4%; private health care centre, + 17.1%). On average the annual

increase in health insurance coverage was + 148%; while the health care utilization (health seekers)

increased by 11.7%. The particular chronic illnesses have shifted mostly from urban (67.6%) to rural

residents (55.1%). This shift could be attributed to cultural factors affecting how and what individuals

eat in rural versus urban areas. The sedentary lifestyles of urban areas also added to the overall

dramatic increase in chronic illnesses.


       Table 2.3 presents information on self-reported diagnosed particular chronic illness by sex of

respondents for 2002 and 2007. On average, the annual increase in particular chronic illness in males

was 19.0% compared to 16.5% in females. Diabetes mellitus showed the highest annual percentage

increase (males 186.7% and females 184.4%), while arthritis fell in females (average annual 7.9%)

compared to an increase in males (average annual 10.0%). Hypertension increased more in females

(average annual 14.0%) compared to 9.7% in males. This could be attributed to the increasing

absorption of females into the upper echelons of management in stressful occupations such as banking

and finance, law, and the police force.


       Table 2.4 examines information on health coverage, health status, health care utilization and

some sociodemographic characteristics by self-reported diagnosed particular chronic illnesses for

2002 and 2007. Based on Table 2.4, although particular chronic illnesses have decreased in rural

respondents, rural dwellers continue to be the face of chronic conditions as well as married, primary,

uninsured, private health centres and those in the lower class. The average annual increase in

particular chronic illnesses increased by 22.9% for those in the lower strata compared to 11.0% for

those in the middle class and 16.0% for those in the wealthy socioeconomic strata. However, the

greatest increase occurred in diabetics belonging to the upper class (average annual + 200%)

compared to those lower class (116.7%). On the other hand, the highest average annual increase in
                                                  41
hypertension occurred in the lower socioeconomic group (26.9%) as compared to those in the middle

class (7.4%) and upper socioeconomic strata (7.1%). The massive increase in cases of diabetes within

the upper class is clearly not due to the lack of resources for seeking health care. A more detailed

analysis of their diet and lifestyle is needed to ascertain the real causes for the drastic increase relative

to other socioeconomic groups.


       Table 2.5 presents information on the age of respondents and particular self-reported chronic

conditions for 2002 and 2007. Based on this information, there is a change in the face of particular

chronic ailments in Jamaica. The face is changing to reflect the inclusion of those less than 30 years of

age (including children) as distinct from the elderly population.


Discussion

The present study revealed that the prevalence of particular chronic diseases (i.e. diabetes mellitus,

hypertension and arthritis) increased from 8 per 1,000 in 2002 to 56 per 1,000 in 2007. The average

annual increase of particular chronic illnesses was 17.2%. Diabetes mellitus showed an exponential

average annual increase of 185% compared to hypertension (+ 12.7%) and arthritis (- 3.8%). While

hypertension remained the most prevalent of the particular chronic diseases in this study, diabetes

mellitus showed the greatest annual increase. The transitions of particular chronic conditions are

accounted for by (1) urban-to-rural shift, (2) female-to-male, (3) aged-to-young people, and (4) lower

socioeconomic strata to upper class. The average annual increase in particular chronic diseases was

greatest among those in the lower socioeconomic groups. However when the particular chronic

ailments were disaggregated, the findings indicated that those in the wealthy socioeconomic group had

the largest prevalence increase in diabetes mellitus, hypertension was greatest among those in the

lower class and those in the upper class had the greatest reduction in arthritic cases. Particularly of

note is the switching from public health care utilization by particular chronically ill respondents to

                                                     42
private health care utilization. Similarly, the prevalence of health insurance coverage on average saw

an exponential annual increase of 148%, while health care seeking behaviour over the same period

showed a marginal increase of 12%.


       There is an emerging body of literature to support the changing face of people with particular

chronic diseases from old ages (30+ years) to younger people including children [28-32]. Traditionally

chronic conditions such as diabetes mellitus were mostly prevalent among the elderly. This reality

supports the large reservoir of literature on elderly diabetic, hypertensive and arthritic patients. With

the emergence of epidemiological and population transition, much attention was placed on diseases in

middle and later ages as well as those conditions that accounted for most of the mortality and

morbidity in a population. Because lifestyle practices were mostly responsible for chronic illness,

many researchers limited their investigation to people 30+ years old [8-11, 23, 33 and 34].


       The present paper supports the literature that particular self-reported chronic diseases (such as

diabetes, hypertension and arthritis) are found mostly among the elderly (60+ years). The findings

revealed that the mean ages of those with the specific self-reported chronic ailments have fallen

marginally in Jamaica over the period (2002-2007). This is somewhat deceptive as 41% of those with

diabetes were less than 60 years of age, compared to 40% of those with hypertension and 31% of

arthritic respondents. Two percent of diabetic respondents were less than 15 years of age, but no

children had hypertension or arthritis. Similarly, increases were observed in diabetes and arthritis for

the young adult (diabetics aged 15 – 30 years) for the period. This is evidence that self-reported

particular chronic diseases are changing face as almost 5% of diabetics were less than 31 years old in

2007 compared to 0% in 2002. Another emerging face of particular self-reported chronic illness is that

of those with arthritis, as almost 2% of cases were among people ages 15-30 years of age.




                                                   43
       The young face of those with diabetes and other chronic diseases can be accounted for by (1)

maternal nutrition during pregnancy [31], (2) diet [35] and the environment [30]. The sedentary

lifestyles of the youth in the population are further entrenched by the modern electronic games which

have removed the young person from the playing field and see him spending longer periods on the

couch in front of the television. This hooked-on-egame syndrome has also resulted in the increased

consumption of sweet snacks and other so-called junk food. The new face of those with particular

chronic diseases is changing, and this reality is therefore a cause for public health concern. This means

that policy makers, health care practitioners, educators and the wider community need to recognize

that chronic conditions such as diabetes, hypertension and arthritis have begun manifesting in young

people as well as children. There is an urgent rationale for an intervention campaign that will sensitize

educators, medical practitioners, parents, and children about the current reality of children and young

adults being diagnosed with particular chronic illnesses. The intervention programme that should be

formulated must include signs of ailments, place of reference, chronic disease management, nutrition,

and medical practitioners understanding that testing for diabetes, hypertension and arthritis must be a

rudimentary part of medical examinations, even of children, and further, even if their parents are not

experiencing those conditions.


       The emerging young face of diabetics, and hypertensive and arthritis patients requires a new

thrust in the study of mortality and morbidity data for health planning. Although diabetes,

hypertension and arthritis may not be among the 10 leading causes of mortality in Jamaica [36] or the

developing society, the emergence of those conditions requires researchers, demographers,

epidemiologists and policy makers to embark on the inclusion of data on those conditions in

publications in order that they can be examined. In a recently conducted study by Wilks et al. [37],

they used teens of 15+ years to present information on those with particular diseases, but neglected to

mention the new reality of children of younger ages with particular chronic illnesses. The new reality

                                                   44
means that researchers, policy makers and the general society need to be cognizant of these facts. This

will be accommodated by researchers, and in particular the statistical agency, publishing findings on

the new reality in order to commence the discourse and intervention campaign. With the absence of

information on the matter, this can be construed as a miniscule problem. However, the new findings

are reflecting the early onset of diabetes (< 15 years) and the provision of data beginning at 15 years

omits 0.8% of infected children or 2.4% of diabetics.


        The present paper unearths more information on the new faces of those with particular chronic

conditions at younger ages. Fifty-four out of every 100 persons with particular chronic diseases (i.e.

diabetes, hypertension and arthritis) had hypertension, 32 out of every 100 had diabetes and 15 out of

every 100 had arthritis. Despite the majority of those with particular chronic illnesses having

hypertension, the prevalence rate for those with diabetes increased exponentially more than the other

conditions. Many studies have established a relationship between poverty and illness [1, 2, 16 and 22],

and particularly poverty and chronic illness [15]. Van et al.’s work [15] revealed that chronic diseases

were greater among those in the lower socioeconomic strata than the other social classes, but this

study found that more people in the wealthy class had diabetes, while more hypertensive and arthritic

respondents were in the lower socioeconomic group. The current findings are providing some

clarification for Van et al.’s research.


        Although the prevalence rate of particular chronic illnesses was greater among the wealthy

strata for 2002 and 2007, those in the lower socioeconomic group recorded the greatest average annual

percentage change. On disaggregating the particular chronic diseases, the present paper showed that

the prevalence of diabetes was greater among the upper than the lower class, and the opposite was

noted for hypertension and arthritis. This finding does not only clarify Van et al.’s research, but

provides pertinent information on the unhealthy lifestyle practices among the wealthy, and reinforces

the role of material deprivation on health, health conditions and mortality.
                                                   45
       Two scholars opined that money can buy health [38], implying that health is a transferable

commodity, and that unhealthy lifestyle practices by the wealthy can be reversed with money. Clearly

Smith and Kington’s claim [38] can be refuted as 42 out of every 100 chronically ill respondents were

in the upper class, and more than half of those with diabetes were part of the wealthy income group.

For any postulation to hold true about money purchasing health, one of the key axioms that needs to

be looked at is the health conditions being lower among the wealthy than those in the lower class. The

wealthy will continue to live by their desires, and at the onset of chronic ailments, may be able to

reverse this by medical expenditure. It is well established that income is positively correlated with

health, as money affords a particular diet, nutrition, medical facilities, safe drinking water, proper

sanitation, leisure and good physical milieu, but the reality is that whenever unhealthy lifestyle

practices become the choice of an individual, his/her money will not be able to eradicate the onset of

diabetes, hypertension, heart disease, or other chronic diseases. Therefore, money enhances the scope

of better health, but it cannot buy good health as this is not transferable from one person to the next.


       The very reason that health is non-transferable is the rationale behind the mortality of the

wealthy elderly, and morbidity among the upper class. Socioeconomic status was found to be the

strongest determinant of variations in health [39, 40], as wealth allows for particular choices,

opportunities, access, resources and privileges that are not available to the poor. While those matters

provide a virtual door leading to better health, money or wealth does not reduce the risk of ill-health

arising from poor choices. A study by Wilks et al. [37] found that most (71%) of those in the upper

socioeconomic strata currently use alcohol which is more than those in the lower class (59%) and the

middle class (64%). Twice as many people in the upper class (14%) had heart attacks compared to

those in the middle class (7%) and 6% in the lower class [37]. The evidence is in that concretizes and

refutes the proposition that ‘money can buy health’, and although the association between income and

health is well established, unhealthy lifestyle choices cannot be reversed with money.

                                                    46
       The carbonated soft drink industry is experiencing a boom in the USA and the Caribbean [41,

42]. Recently, research conducted by Ha et al. [41] found that carbonated soft drinks and milk were

the two most popular non-alcoholic beverages in the USA. They accounted for 39.1% of total

beverage consumption. This explosion in carbonated soft drinks means that added sugar is infesting

the dietary intake of young people and children more than in previous decades. Another study showed

that among children aged 6 to 19 years there was a positive significant statistical association with soft

drink consumption and a negative one with milk intake [43]. A sedentary lifestyle along with the

consumption of sugar, salted food and fast food are accounting for the overweight and obesity in the

world. According to Bostrom and Eliasson [44], over 50% of men and 33.3% of women between the

ages of 16 and 74 years in Sweden are overweight and obese. Wilks et al. [37] found that 73% of

Jamaicans aged 15 to 74 years practice a sedentary lifestyle, and obesity was the third most popular

disease (5.6% of the population, 8.5% of females and 2.7% of males) behind hypertension (20.2%)

and diabetes mellitus (7.6%).


       The growing global tsunami of chronic diseases in developing countries, and in particular

Jamaica, requires urgent policy and public health intervention. The carbonated soft drink industry has

infiltrated the consumption intake of young adults and children. Sugar in the form of sweets (lollipops,

candies, et cetera) is sold in every shop and supermarket, and at school gates in Jamaica. Children and

young adults are fed a diet of more sugar than vegetables, beans, legumes, nuts, protein, diary

products, fruits and fibre. Embedded in the increase in diabetes in children and young adults in

Jamaica are parents’ and children’s nutritional intake (or lack thereof), as the dietary habits of

Jamaicans have changed to include more fast foods and less nutrient dense diets. This extends beyond

Jamaica to Barbados [44] and the USA [41].


       With the exponential increase in diabetes over the last 5 years in Jamaica, and the increase in

unhealthy lifestyle practices of the people, coupled with the sales explosion of the carbonated soft
                                                   47
drink industry and the increase in fast food outlets, Jamaica is experiencing a diabetes epidemic which

cannot be resolved without government and policy interventions. As is clearfrom the literature, with

the increase in carbonated soft drinks, reduction in milk intake and influx of fast food entities in the

Americas, the diabetes epidemic of Jamaica may become a reality across the Americas. This is not just

affecting countries in the Americas, as studies have shown that Type 2 diabetes has become a global

public health problem [46, 47]. The WHO contextualized the global public health Type 2 Diabetes

epidemic when it stated that during 1999-2025 the prevalence of this ailment will be 40% in the

developed nations and 170% in the developing countries. Clearly this paper is showing that diabetes

has now reached an epidemic state in Jamaica, and may no longer be an epidemic but a pandemic

disease. Type 2 diabetes is no longer an “adult” or “later life” disease, as was the case a generation

ago, as it is now being diagnosed in children in Jamaica and other countries [48, 49].


       This study highlights the changing image of those with particular chronic diseases (i.e.

diabetes, hypertension and arthritis) in Jamaica. With 2 out of every 100 diabetics being children (< 15

years) and the new image of hypertensive and arthritic patients being 15 – 30 years, plus the

exponential increase in diabetes in the wealthy class, the present research highlights significant public

health problems. In the last half a decade (2002-2007), the average annual increase in diabetes mellitus

has risen by 185% indicating the unhealthy lifestyle practices of pregnant women, children and other

young adults.


       The image of particular chronic illness in Jamaica continues to be lower class female and rural

residents, but the average annual increase in diabetes mellitus was 200% for those in the wealthy class,

compared to 117% of those in the lower socioeconomic class. Forty-seven out of every 100

chronically ill people in Jamaica utilize public health care facilities, which denotes that the matter is a

public one and not solely individual. The cost of public health care in the next 5-10 years will increase

phenomenally, as greater proportions of the population who rely on the public health care system will
                                                    48
be afflicted with these chronic diseases. This has serious implications for the sustainable development

of developing countries as well as their future achievements regarding the United Nations Millennium

developments goals. To act now will not only save lives but will also save the various developing

countries billions of dollars that can be spent on other development programmes.


       The demographic transition, in particular chronic conditions, now demands that data collection

on those illnesses be lowered to < 15 years. Apart from the lowering of the ages in the data collection

process, public health specialists need to address the massive changes in new diabetic cases. This is an

obvious problem, which requires public health intervention as well as lifestyle management of

diabetes. This sensitization and lifestyle management campaign must extend to include educators,

parents, children, vendors (especially those at schools), and the government.


       Governments need to regulate the sugar content of products in Jamaica (carbonated soft drinks,

confectionary and fast food) as this is contributing to a public health problem which will cost the

government and people in the medium to long-term. Diabetes can be likened to a tsunami in Jamaica

and one that demands government intervention. Currently, there is a lifestyle campaign dealing with

sexual behaviour, condom usage, and cancer in Jamaica; this research highlights the urgent need for a

diabetes campaign that extends beyond parents to include vendors, confectionaries, soft drink

manufacturers and government, in order to sensitize the public about this new public health problem.

The gravity of the situation is that such a programme cannot be delayed for some time in the future as

the opportunity costs of delay are (1) higher public expenditure, (2) increasing cost of diabetic care

and management, (3) lower production cost, (4) increased unemployment benefits, (5) the imputed

cost of ignorance, and (6) an increased mortality rate.


Conclusion




                                                   49
       In summary, the theoretical position that underlines testing for diabetes among other chronic

diseases should be abandoned, as the findings show the need to begin rudimentary health examinations

of all ages. The new thrust of governments, public health specialists and researchers is to commence a

mandate that addresses confectionary products’ ingredients, and institution guidelines about the sugar

and salt components of manufactured commodities. The wider confectionary and food industry cannot

be left unregulated as the chronic diseases tsunami is upon us, and it will require a concerted effort

from everyone to combat this public health problem as the nation addresses the diabetes epidemic.

Diabetes has risen to such epidemic proportions that it now requires a policy initiative aimed at

reducing the level of increases in a managed way.


Conflict of interest
The authors have no conflict of interest to report.

Disclaimer
The researchers would like to note that while this study used secondary data from the Jamaica Survey
of Living Conditions, none of the errors in this paper should be ascribed to the Planning Institute of
Jamaica or the Statistical Institute of Jamaica, but to the researchers.




                                                      50
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                                                54
Table 2.1: Operational definitions of particular variables

Variable            Operational definition             Coding
Self-evaluated      This is taken from the question “In general, would you say your health is
health status (or   excellent, good, moderate, poor or very poor?”
health status)
Sex                 Being male or female
Age group           Age group is classified into 4           Children - ages < 15 years old
                    categories.                              Young adults - 15 to 30 years old
                                                             Other age adults – 31- 59 years old
                                                             Young old – 60 – 74 years old
                                                             Old old – 75 – 84 years old
                                                             Oldest old – 85+ years old
Social hierarchy    Income quintiles were used to            Low = poorest 20% to poor; middle =
                    measure social class, and these          middle quintile and upper = wealthy to
                    range from quintile 1 (poorest           wealthiest 20%
                    20%) to 5 (wealthiest 20%)
Health care-        Visits to pharmacies, medical            1 = visits to health care professionals,
seeking             practitioners, nurses in the last        0=otherwise
behaviour           4-weeks
(health seeking
behaviour)
Self-reported       Have you had any illness or injury during the past four weeks? For example,
illness             have you had a cold, diarrhoea, asthma, diabetes, hypertension, arthritis or
                    other?
Chronic illness     These can be broadly defined as conditions which prolonged, do not resolved
                    spontaneously, and are infrequently curable. This is taken from the question
                    ‘What are the illnesses that you have been diagnosed with –
                    Cold, diarrhoea, asthma, diabetes mellitus, hypertension, arthritis, other
                    chronic conditions (unspecified)?
                    The chronic conditions were diabetes mellitus, hypertension and arthritis.




                                                        55
Table 2.2. Demographic characteristic of sample, 2002 and 2007
                                                    2002                        2007
Characteristic                                      n           %               n           %
Chronic illness
  Diabetes mellitus                                12          5.8            123         31.9
  Hypertension                                    126        60.9             206         53.5
  Arthritis                                        69        33.3              56         14.5
Sex
  Male                                             58        28.0             113         29.4
  Female                                          149        72.0             272         70.6
Marital status
  Married                                          95        46.1             163         42.8
  Never married                                    50        24.3             130         34.1
  Divorced                                          1          0.5             14          3.7
  Separated                                         3          1.5             10          2.6
  Widowed                                          57        27.7              64         16.8
Income quintile
  Poorest 20%                                      29        14.0              83         21.6
  Poor                                             40        19.3              65         16.9
  Middle                                           49        23.7              76         19.7
  Wealthy                                          39        18.8              79         20.5
  Wealthiest 20%                                   50        24.2              82         21.3
Health care utilization
  Public hospital                                  51        28.8              72         25.5
  Private hospital                                 15          8.5             23          8.2
  Public health centre                             43        24.3              61         21.6
  Private health centre                            68        38.4             126         44.7
Health care utilization
  Sought medical care                             163        79.1             258         67.4
  Did not seek care                                43        20.9             125         32.6
Health insurance status
  Insured                                          15          7.2            126         32.8
  Uninsured                                       192        92.8             258         67.2
Age cohort
  Children                                          0          0.0              3          0.8
  Young adults                                      2          1.0             10          2.6
  Other age adults                                 49        23.7             137         35.6
  Young-old                                        90        43.5             132         34.3
  Old-old                                          58        28.0              82         21.3
  Oldest-old                                        8          3.9             21          5.5
Area of residence
  Urban                                            24        11.6              95         24.7
  Semi-urban                                       43        20.8              78         20.3
  Rural                                           140        67.6             212         55.1


Table 2.3. Self-reported diagnosed chronic illness by sex of respondents, 2002 and 2007
                                                 56
                                 20021                   20072
Characteristic             Sex of respondents      Sex of respondents
                             Male        Female      Male      Female
                             n (%)         n (%)     n (%)       n (%)
Chronic illness
 Diabetes mellitus           3 (5.2)     9 (6.0)   31 (24.7) 92 (33.8)
 Hypertension              39 (67.2)   87 (58.4)   58 (51.3) 148(54.4)
 Arthritis                 16 (27.6)   53 (35.6)   24 (21.2) 32 (11.8)
                                 58         149         113       272
1
    χ2 = 1.39, P = 0.499
2
    χ2 = 6.09, P = 0.048




                           57
Table 2.4: Particular demographic and health variable by diagnosed chronic illness, 2002 and 2007
                                        2002                                          2007
                                   Chronic illness                               Chronic illness
Characteristic         Diabetes    Hypertension      Arthritis    Diabetes      Hypertension      Arthritis
                       mellitus                                   mellitus
                             n (%)           n (%)         n (%)        n (%)              n (%)        n (%)
Area of residence
 Urban                     1 (8.3)       15 (11.9)      8 (11.6)    32 (26.0)          47 (22.8)    16 (28.6)
 Semi-urban                1 (8.3)       29 (23.0)     13 (18.8)    27 (22.0)          41 (19.9)     10(17.9)
 Rural                   10 (83.3)       82 (65.1)     48 (69.6)    64 (52.0)         118 (57.3)    30 (53.6)
Marital status
 Married                  4 (33.3)       61 (48.4)     30 (44.1)    48 (40.0)          91 (44.4)    24 (42.9)
 Never married            4 (33.3)       30 (23.8)     16 (23.5)    39 (32.5)          69 (33.7)    22 (39.3)
 Divorced                  0 (0.0)          0 (0.0)       1 (1.5)    10 (8.3)             3 (1.5)      1 (1.8)
 Separated                 0 (0.0)          2 (1.6)       1 (1.5)     4 (3.3)             5 (2.4)      1 (1.8)
 Widowed                  4 (33.4)       33 (26.2)     20 (29.4)    19 (15.8)          37 (18.0)      8 (14.3)
Health utilization
 Public hospital          3 (30.0)       31 (29.5)     17 (23.0)    27 (32.9)          35 (25.5)    10 (32.3)
 Private hospital         1 (10.0)          9 (8.6)       5 (6.8)   11 (13.4)             7 (5.2)     5 (16.1)
 Public centre            2 (20.0)       21 (20.0)     20 (27.0)    23 (28.1)          34 (24.8)      4 (12.9)
  Private centre          4 (40.0)       44 (41.9)     32 (43.2)    21 (25.6)          61 (44.5)    12 (38.7)
Health seekers
 Did not                   1 (9.1)       26 (20.6)     16 (23.2) 34 (27.6)†           66 (32.0)†   27 (48.2)†
 Sought                  10 (90.9)      100 (79.4)     53 (76.8) 89 (72.4)†          140 (68.0)†   29 (51.8)†
Education
  Primary                 8 (66.7)       73 (59.8)     43 (63.2) 121 (98.4)           205 (99.5)   56 (100.0)
  Secondary               4 (33.3)       47 (38.5)     24 (35.3)      2 (1.6)             0 (0.0)      0 (0.0)
  Tertiary                 0 (0.0)          2 (1.6)       1 (1.5)     0 (0.0)             1 (0.5)      0 (0.0)
Health coverage
  Uninsured              11 (91.7)      114 (90.5)     67 (97.1) 69 (56.1)†          148 (71.8)†   41 (74.5)†
  Insured                  1 (8.3)        12 (9.5)        2 (2.9) 54 (43.9)†          58 (28.2)†   14 (25.5)†
Social class
  Lower                   6 (50.0)       35 (27.8)     28 (40.6) 41 (33.3)†           82 (39.8)†   25 (44.6)†
  Middle                   0 (0.0)       35 (27.8)     14 (20.3) 16 (13.0)†           48 (23.3)†   12 (21.4)†
  Upper                   6 (50.0)       56 (44.4)     27 (39.1) 66 (53.7)†           76 (36.9)†   19 (33.9)†
Health status
 Very good                      NI              NI             NI     5 (4.1)           10 (4.9)       1 (1.8)
 Good                           NI              NI             NI   21 (17.1)          45 (21.8)    12 (21.4)
 Fair                           NI              NI             NI   67 (54.5)          91 (44.2)    25 (44.6)
 Poor                           NI              NI             NI   26 (21.1)          52 (25.2)    18 (32.1)
 Very poor                      NI              NI             NI     4 (3.3)             8 (3.9)      0 (0.0)
NI – No information
† Significant (P < 0.05)




                                                      58
Table 2.5. Age of respondent by particular chronic illness, 2002 and 2007
                                     2002                                     2007
                                 Chronic illness                          Chronic illness
Characteristic       Diabetes    Hypertension Arthritis       Diabetes Hypertension Arthritis
                     mellitus                                 mellitus
                           n (%)          n (%)        n (%)       n (%)          n (%)       n (%)
Age cohort
  Children               0 (0.0)        0 (0.0)      0 (0.0)      3 (2.4)        0 (0.0)    0 (0.0)
  Young adult            0 (0.0)        2 (1.6)      0 (0.0)      3 (2.4)        6 (2.9)    1 (1.8)
  Other age adult       5 (41.7)      31 (24.6) 13 (18.8) 44 (35.8)           76 (36.9)   17 (30.4)
  Young-old             5 (41.7)      54 (42.9) 31 (44.9) 49 (39.8)           61 (29.6)   22 (39.3)
  Old-old               2 (16.7)      32 (25.4) 24 (34.8) 19 (15.4)           49 (23.8)   14 (25.0)
  Oldest-old             0 (0.0)        7 (5.6)      1 (1.4)      5 (4.1)       14 (6.8)    2 (3.6)
Age Mean (SD)               62.1    67.2 (12.8)         68.4         60.9    62.5 (16.8)       64.3
                          (12.6)                      (11.5)       (16.0)                    (14.5)
† Significant (P < 0.05)




                                                59
                                                                                Chapter 3

Sex and older adulthood
Paul A. Bourne


Life expectancy of Jamaicans is about 74 years (females, 77.1 years; males, 71.3), with healthy life

expectancy being 6 years less than those for life expectancy. Embedded in these facts are 1) long life,

and 2) active ageing. Many demographers are primarily concerned with life expectancy (including

healthy life expectancy) and little attention is placed on active ageing. A search of literature in the

Caribbean on sex and older adulthood revealed no such work. Yet ageing is an active process, which

denotes that ageing does not cease life, expressions and behaviour. If ageing is a continuous process to

death (the absence of life), then ageing studies must include active ageing that examine sex and older

adulthood because sex does not end with entry into older adulthood (60+ or 65+ years, depending on

the chronological commencement of old age).


       Among the negative concepts of old age (ageism) is sexual abstinence. A study by Wilks and

colleagues (2008), using stratified random sample of 2,848 Jamaicans based on the general population

of individuals aged 15-74 years old, found that 19.0% of respondents aged 15-24 years old had not had

sexual intercourse in the past 12 months compared to 1.9% of those aged 24-34 years; 0.4% aged 35-

44 years; 1.3% of those 45-54 years; 0.2% aged 55-64 years and 1.4% of individuals aged 65-74 years

old. This emphasizes the concept of active ageing of Jamaicans.


       Using the United Nations standard of age 60 years to denoted ‘older’ (elderly, seniors, aged)

people, this clearly is not the beginning of inacative ageing. Older adulthood does not describe sexual

                                                  60
abstinence as sex is confined to younger ages. People are indeed living longer and the quality of their

lives continues into older adulthood including their sexual practices. There may be a slower of the

frequency of sexual expressions, but older adulthood does not signal the end of sexual intercourse,

sexual experimentations, sexual role plays, and intense sexual behaviour. In Wilks et al.’s work, they

found that 13.5% of individuals aged 65-74 year indicated having sex about once per week compared

to 26.0% of those aged 55-64 years; 40.2% of individual aged 45-54 years; 63.1% of those aged 35-44

years; 64.3% of Jamaicans aged 25-34 years and 41.5% of young adults (ages from 15-24 years).


       Active ageing of Jamaicans in regard sexual expression among individuals aged 65-74 years

old was 4.8 times more for males (23.0%) than females (having sexual intercourse < once per week)

and this was 3.3 times more among males aged 55-64 years (39.6%) than their female aged

counterparts. Clearly ageing does not eliminate sexual expression among those in older adulthood. As

1.0% of males aged 65-74 years reported having had a sexual transmitted infection in the last 12

months compared to 0% of their female counterparts, suggesting that family planning cannot be

limited in scope to young people as even among those in older ages, there is the issue of sexual

irresponsibility, particularly among males.


       So, older adulthood is an active process. This indicates that we need to examine the

reproductive health matters among aged people. Almost 6% of aged people 65-74 years old used a

condom, and this was about 12% for males and 0% of females. Among those aged 55-64 years, 19.1%

used a condom (males, 31.4%; females, 6.4%). The implication from this is simple, inconsistent

condom usage among Jamaicans at the older aged is high; this speaks to the cultured perspective

against condom usage. Man must have “nuff gal” (many women) which is a cultural mantra held by

many men, reinforced by females accepting that their men are highly likely to have other sexual

partnerships (women). The lower percentage of older females using a condom and older males having

multiple relationships speaks to concretized culture. Older females having fewer sexual relationships
                                                  61
are testament to the sexual discrimination between the sexes. And the power relations in unions are

held by males as well as in the society, which promulgate the male dominated culture. And this

cultured females into reduced control over their lives.


       The economic power of males is such that even during older adulthood, males still experience

more economic authority than females and this explains females’ discontinuation of contraception.

The discontinuation of contraception by females dates back to younger ages because of the economic

power disparity between the sexes. The economic power that older men possess, suggests that they are

able to stipulate the sexual choices of females. With females at younger ages allowing males to veto

their reproductive health choices, it appears that this cultured position continues into older adulthood.

Or, the trust in the union is such that females knowing that they are infecundity may not seek the need

to utilise condoms.


       If older females believe that the sexual expressions of their male partners chances with time or

vice versa, this would be naive and simplistic of them. As young males in the Caribbean are socialized

to be ‘studs’, promiscuous and father children (Chevannes, 2001; Gayle, 2002), then it follows that

inconsistent condom usage must be practice and multiple partnerships. Among Jamaicans aged 65-74

years old, 26.3% of them indicated having one sexual partner (males, 38.9%; females, 14.8%)

compared to 46.7% of those aged 55-64 years old (males, 56.2%; females, 37.0%; Wilks et al., 2008).

Before one begins to berate the sexual expressions of older people in Jamaica, the aforementioned is

constraint by those who do not have a sexual partner. In Wilks et al.’s study, they found that 68.4% of

individuals aged 65-74 years did not have a sexual partner in the last 12 months (males, 50%; females,

85.2%) compared to 40.8% of those aged 55-64 years old (males, 20.3%; females, 62.0%).


       Clearly, the cultured sexual lessons forwarded to younger males are embedded into the social

psychology of older males (Bourne & Charles, 2010; Gibbison, 2007; Chevannes, 2001; Gayle, 2002).


                                                   62
Males (aged 65-74 years old) are more engaged in sexual promiscuity (11.1%) compared to their

female aged counterparts, indicating the sexual disparity and inequality in the culture. The practice is

even greater among those individuals aged 55-64 years old (males, 23.8%; females, 1%). Again active

ageing is evident as 1) older people are engaged in sexual activities; 2) infrequent condom usage; 3)

multiple sexual partnership; 4) contracting STIs, particularly males; 5) health risk; and 6) security risk.


       Ageing, therefore, must go with not only positive experience, longer life, and continuous

opportunities, but also understanding their sexual expressions must be critical in population planning.

If older males are engaged in risky sexual behaviour (inconsistent condom usage), then some of them

will be fathering children with younger females with whom they are having sexual relations. From the

life course approach, ages during the older ages indicate a slower of functions, but it is not an end to

active ageing (including sexual relations). The evidence is here that people in older adulthood are

sexually expressive, active, and cultured the same way as the younger ages, so older people do not

symbolize sexual abstinence or no risk sexual behaviour.


       With 23.0% of older males (ages ranging from 65 to 74 years) indicated having sexual

relations about once per week and with only 2.2% of those males aged 65-74 years saying that they

use the withdrawal method of contraception and 11.5% used a condom, it follows that risky sexual

behaviour is a part of active ageing in Jamaica. As people age, their behaviour lowers but not stopped

with some miraculous wand. People are sexual animals (being), therefore, ageing must incorporate

sexual expression in active ageing alongside optimizing opportunities on health, quality of life,

security and participation in order to aid quality of life of older people.


       Older adulthood means retirement, illness, dependency, changes in cognitive and physical

functionality; it is also associated with sexual being, promiscuity and poor sexual practices. Although

to some individuals continue to see older people as feeble, ‘sickly’, and retired, the males are still able


                                                     63
to impregnate a female of the reproductive ages (15 – 49 years and < 15 year), making them critical to

any discourse on sexuality, sex, sexual expressions, fertility, and other reproductive health matters.


          Another fact that emerged from Wilks and colleagues’ research was the high percentage of

older males having sex at least once per month. The findings revealed that almost 53% of males 65-74

years had sexual relations at least once per month compared to 21.6% of those aged 55-64 years;

14.0% of those 45-54 years; 1.8% of males 35-44 years; 4.3% of males aged 25-44 years and 23.5% of

males 15-24 years old. Sexual relations (sex) are not constraint by age, making sex normal throughout

the life course (all ages). People are socialized to be sexual beings. Older ages, therefore, do not stop

sexual expressions. Older adulthood does reduce the frequency and severity of sexual relations,

provides a different appetite for sex and lowers the cultured risky sexual behaviour. Sex is natured,

nurtured and a normal part of human existence. Just as how age is a continuous construct over the life

course, sex is desired, practiced and loved by humans irrespective of the time interval over that life

course.


          Contemporary Jamaica cannot hide the fact of older males are fathering children, dying

sometimes shortly after fathering child(ren), young females being actively engaged in sexual

relationships with older males (ages 60+) and sexual active males at older aged having vetoing powers

over the sexual and reproductive practices of younger females. These males have the economic

resources that are sought by younger females, yet the rate of fathering children among older males is

still unknown. There is no such thing as inactive sexual aged male. Public health practitioners and

policy makers need to be cognizant those facts. What are roles of older males fathering children? What

percentage of yearly births fathered by older males? How much financial assistance is allocated for

children of older males? Or, should the state assist in fathering children of older men on their death?




                                                   64
       The ageing male is a human with sexual desires like the young male. Empirical evidence

showed that the ageing male experiences changes in biological functioning (including decreased libido

and erectile dysfunction). Decreased libido and erectile dysfunctions go to the core of the masculinity

of Caribbean males. Because sexual expression is associated with manhood for the Caribbean nations,

particularly among Jamaicans, sexual dysfunctions cripple the foundations of the man. The

devastating effects of sexual dysfunctions are such that the Caribbean male is silent on those issues.

Silence impacts on health care utilisation, manhood, self-esteem, and cognitive functionality of all

men in the Caribbean. According to Swerdloff and Wang (2003; 207), “As men get older, there is a

decline in many biological systems; the endocrine systems are not spared”. But this reality does not

stop the sexual expression of males in Jamaica. Apart of the rationale for the sexual drive is the culture

which accounts for the use of testosterone gels.


       “After treatment with testosterone gel, the group [aged males] sexual desire, and enjoyment

without partner and enjoyment with partner, percentage total erection and self-assessment of

satisfaction with erections were statistically significantly improved and were maintained throughout

the treatment” (Swerdloff and Wang, 2003; 209). Embedded in the aforementioned finding is fact that

ageing is an active process and it does not cease with older adulthood. Older males are males and

desire sexual gratification. Thus, older males will use testosterone gel if they unable to have and

sustain an erection because sex is a part of their existence as consuming food, water and oxygen.

Because serum testosterone falls with ageing, older men are likely to enhance their sexual

performance with gels or oral medical (Viagra) as they will not be robed of the experiences. Manhood

is tied to sexuality. Therefore, older men will seek and use androgen treatment in order to protect the

perceived manhood.


       The author is, therefore, recommending 1) research on sexual desires and choices over the life

course; 2) fatherhood over the life course; 3) the financial provisions of children fathered by aged
                                                   65
males (60+ years old); 4) the mortality patterns of aged males after fathering children; 5) the

demographic profile of males who father children; 6) the mortality patterns of children fathered by

older males; 7) epidemiological studies on children fathered by older males; 8) demographic studies

on the life span and expectancy of children fathered by older males, and 9) the vetoing power of older

males in regard reproductive health matters of their younger sexual partners. If there is no information,

the gateway to advanced knowledge is clogged and policies will be distanced from the current realities

of the people. So academics, researchers and health practitioners need to commence enquiries into the

aforementioned issues.


       Outside of the above-mentioned recommendations, the author is proposing an ageing male

clinic in Jamaica. This clinic should address the following issues 1) endocrinology, 2) andrology

(including decreased libido and erectile dysfunctions); 3) medical psychological services (depressed

mood; anxiety, irritability, reduced cognitive capacity), 5) general wellbeing, and 6) urological

services. Sex among older men is a normal part of life as such a clinic is needed to address all issues

relating to aged men.




                                                   66
Reference

Bourne PA, Charles CAD. Contraception usage among young adult men in a developing country.
    Open Access J of Contraception 2010; 1:51-59.

Chevannes B. Learning to be a man: Culture, socialization and gender identity in five Caribbean
      communities. Kingston, Jamaica: The Univer. of the West Indies Press; 2001.

Gayle H. Adolescent Male Survivability in Jamaica. Kingston: The Jamaica Adolescent Reproductive
      Health Project (Youth. now); 2002.

Gibbison GA. Attitude towards intimate partner violence against women and risky sexual choices of
     Jamaican males. West Indian Med J 2007; 56(1):66-71.

Henry-Lee A. Women’s reasons for discontinuing contraceptive use within 12 months: Jamaica.
     Reproductive Health Matters 2001; 9(17):213-220.

Jamaica, National Family Planning Board (NFPB). Reproductive Health Survey, 2002. Kingston:
     NFPB; 2005.

Swerdloff RS, Wang C. Three-year follow-up of androgen treatment in hypogonadal men: preliminary
    report with testosterone gel. The Aging Male 2003;6:207-211.

Wilks R, Younger N, Tulloch-Reid M, McFarlane S, Francis D. Jamaica health and lifestyle survey
     2007-8. Kingston: Tropical Medicine Research Institute, University of the West Indies, Mona;
     2008.




                                               67
                                                                                 Chapter 4

Activities of daily living, instrumental activities of daily
living, and predictors of functional capacity of
older men in Jamaica

Paul Andrew Bourne
An extensive search of the literature found no studies that have examined functional capacity
(Activities of Daily Living (ADL) and Instrumental Activities for Daily Living (IADL)) of older
Jamaican men or the factors that determine their functional capacity. current study examines 1) ADL,
2) IADL, 3) self-reported health status, 4) functional capacity, and 5) factors that determine functional
capacity of older men. Stratified multistage probability sampling technique was used to draw a sample
of 2,000 55+ year men. A 132-item questionnaire was used to collect the data. Descriptive statistics
provide background information on the sample, cross-tabulations were used to examine non-metric
variables and logistic regression provides a model of predictors of functional capacity. Fifty-five
percent of the sample indicated good current health status; four percent were mostly satisfied with life;
21.7% had moderate dependence; 77.1% had high dependence (i.e., independence); 1.2% had low
dependence; 21.9% were ages 75 years and older; 35.6% were ages 65 to 74 years; and 42.6% were
ages 55 to 64 years. Functional capacity can be determined by church attendance (β=0.245; 95% CI:
0.264, 1.291), social support (β=0.129; 95% CI: 0.129, 0.258), area of residence (β=-0.060; 95% CI: -
0.427, -0.061), and age of respondents. Aging explains deterioration in the respondents’ IADL,
suggesting the challenges of aging men’s independence. Men from rural areas were rarely satisfied
with life, but more of them had greater functional capacity than urban men. Depression was found to
negatively relate to functional capacity, and church attendees had a greater functional status than non-
attendees.



Introduction


Like many developed nations and even some developing ones, Jamaica is able to boast of its notable

achievement in progress made toward advancing the health status of its populace during the twentieth

century, which is expressed in postponement of death, lowered fertility, high nutrition and sanitation,

and more importantly, increased life expectancy. Life expectancy, which is an indicator of health

status, reveals that the country’s health status is reasonably good, as the life span for Jamaicans was

similar to those in some First World societies: 71.26 years for males and 77.07 years for females [1].
                                                   68
Interestingly, the biological science highlighted that the ageing process comes with changes in

physical functioning. According to ‘The Merck Manual of Health and Aging’ [2] “Older cells

function less well. Also, in some organs, cells die and are not replaced, so the number of cells

decreases”, indicates not only the decline functionality of aged body but also the role of diseases in

this regards. The oldest-old categorization is said to be the least physical functioning compared to the

other classification in chronological aging [3, 4]. 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 [2, 3, 5].


       A study conducted by Costa [6], using secondary data drawn from the records of the Union

Army (UA) pension programme that covered some 85% of all UA, showed that there was an

association between chronic conditions and functional limitation – which include difficulty walking,

bending, blindness in at least one eye and deafness. Those functional activities are classified as ADL

(activities of daily living) or (I) ADL (Instrumental Activities for Daily Living). The ADLs denote

what an individual normally do in his/her daily living. These include activities such as feeding oneself;

bathing, dressing, grooming, work, homemaking and leisure. The (I) ADL are those activities whose

accomplishment is necessary for continued independent residence in the community. The independent

activities of daily living are more sensitive to subtle functional deficiencies than ADL’s and

differentiate among task performance including the amount of help needed to accomplish each task.

Within the context of aging and the reality of having chronic diseases, ones ADL and (I) ADL will be

hampered somewhat.


       Some illnesses, such as Huntington's Disease, hypertension, heart diseases, diabetes mellitus,

cancer, cataract, and stroke, result in a gradual loss of the ability to provide self-care and some result

in an immediate dependence or lowered functional capacity and sometimes even mortality. Hence,


                                                   69
even if aging were associated with no ailments, it still comes with reduced functional capacity.

According to Eldemire [7], “The majority of older Jamaican persons are physically and mentally well

and living in family units,” suggesting that illnesses are eroding some of the functional capacity of

elderly Jamaicans, which is synonymous with aging. Despite Eldemire’s findings, a study on the

elderly published in the Caribbean Food and Nutrition Institute’s magazine (i.e., Cajanus) found that

70% of individuals who were patients within different typologies of health services were senior

citizens [8], suggesting that elderly Jamaicans were not only spending more time utilizing health care

services than other age cohorts, but that they were experiencing lowered functional capacity.


       The aforementioned health literature has shown that diseases positively influence functionality,

and Kim et al.’s work [9] provided more information on functional capacity (i.e., IADL). They found

that MCI (i.e., mild cognitive impairment) patients performed significantly worse on four out of a total

15 items (e.g., telephone, transportation, finances and household appliances) than elderly 60+ year old.

Another descriptive study conducted by Natividad and Zimmer [10] went further than Kim et al. in

2000; they found that 11.5% of older Filipinos were having difficulties walking in the house; 8.0%

had difficulty bathing; 6.3% had a hard time dressing themselves; and 4.6% had difficulty eating. On

the issue of IADL, Natividad and Zimmer found in 2000 that 18.5% had difficulty with using

transportation; 17.6% had difficulty shopping; 13.8% had a difficult time preparing meals; 13.8% had

a problem with doing light housework; and 9.4% found it hard to manage their money. In that same

study, using logistic regression, Natividad and Zimmer went further and found that age was the

significant factor that determined ADL (OR=1.08, P <0.05), while age (OR = 1.07, P <0.05) and area

of residence (i.e., rural: OR=0.66, P <0.05) were determinants of IADL. Furthermore, they found that

marital status, education, and gender were not statistically significant determinants of ADL or IADL.




                                                  70
       This study is timely as it aimed to examine ADL and IADL, and sought to investigate those

determinants of functional capacity of older men in Jamaica. Using data for 2007 on 2,000 Jamaican

men aged 55+ years, the current study evaluated activities of daily living (ADL), instrumental

activities (IADL), and self-reported health status; using logistic regression we were able to determine

those factors that explain the functional capacity of older men. The current study therefore will not

only provide information upon which public health policies can be fashioned, but it also will help to

provide an understanding of older men and how they perceive health and determine their ADL, IADL,

and those factors that influence their functional abilities. This study does not simply assume that data

obtained on this subject in other localities applies equally to Jamaican men aged 55+ years.




Materials and Methods


The study used primary cross-sectional survey data on men 55 years and older from the parish of St.

Catherine in 2007; the data is also generalizable to the island. The survey was submitted and approved

by the University of the West Indies Medical Faculty’s Ethics Committee. Stratified multistage

probability sampling technique was used to draw the sample (2,000 respondents). A 132-item

questionnaire was used to collect the data. The instrument was sub-divided into a general demographic

profile of the sample: past and current health status, health-seeking behavior, retirement status, and

social and functional status. The overall response rate for the survey was 99% (n=1,983). Data was

stored, retrieved, and analyzed using SPSS for Windows (16.0) (SPSS Inc; Chicago, IL, USA).


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts (ED) or

census tracts. The parish of St. Catherine is divided into a number of constituencies made up of a

number of enumeration districts (ED). The one hundred sixty-two enumeration districts in the parish

of St. Catherine provided the sampling frame. The enumeration districts were listed and numbered

                                                  71
sequentially and the selection of clusters was arrived at by the use of a sampling interval. Forty

enumeration districts (clusters) were subsequently selected with the probability of selection being

proportional to population size (Table 4.1).


       The sample population not only speaks to the parish of St. Catherine, it is generalizable to the

entire island of Jamaica. The sampling frame was men aged fifty-five years and older in the parish of

St Catherine. The parish of St. Catherine was chosen as previous data and surveys [11-13] suggested

that it has the mix of demographic characteristics (urban, rural and age-composition) which typify

Jamaica.



       For the current study, descriptive status was employed to provide background information on

the sample, and chi-square was used to examine non-metric variables. Level of significance was p-

value < 0.05 and the only exclusion criterion was if more than 20% of the cases of a variable were

missing.




Measure


Happiness: this is measured based on people’s own reports on their happiness. It is a Likert-scale

question which ranges from always happy to rarely happy. Health Status: this variable is measured

using people’s own rating of their overall health status, which ranges from excellent to poor health

status. The question was “How would you rate your health today?” The responses available were: (1)

Excellent, (2) Good, (3) Fair, and (4) Poor. Education: The question asked was, “What is [your]

highest level of [education] attained?” The options were: (1) no formal education, (2) basic school, (3)

primary school/all age, (4) secondary/high/technical school, (5) vocational (i.e., apprenticeship/trade),

(6) diploma, (7) undergraduate degree, and (8) post-graduate degree. Physical Exercise: The question


                                                   72
was: “Do you take time out for regular exercise?” The responses were: (1) yes, or(2) no. Type of

physical exercise: “What do you do in terms of exercise?” Childhood illness: “Were you seriously ill

as [a] child?” Responses: (1) yes, or (2) no. And, “Were you frequently ill as a child?” (1) Yes, or (2)

no. If the response to either of the last two questions was yes, this was coded as poor childhood health

status, and if the response was no in both cases, it was coded a good health status in childhood. Age

group is categorized into three sub-groups. These are: (1) ages 55 to 64 years, (2) ages 65 to 74 years,

and (3) ages 75 years and older (i.e., 75+ years).


       Performance of Activities of Daily Living (ADL) is used to describe the functional status of a

person. It is used to determine a baseline level of functioning and to monitor improvement in activities

of daily living (ADL) overtime [14, 15]. Scoring the ADL (Katz), independence was given a value of

1 point while if dependent, a value of 0 was given. There were 6 items (“eating” refers to feeding

oneself; “dressing” denotes getting clothes and getting dressed, including tying shoes; “transferring”

means to get in and out of bed as well as in and out of a chair; “using toilet” refers to going to the

toilet and cleaning afterwards; “bathing” denotes to sponge bath, shower, tub bath, or washing body

with a wet towel; “continence” denotes to control of urination and bowel movement). The reliability

of the items was high, as Cronbach alpha was 0.696. Total scores thus could range from 0 to 6 with

lower scores indicating low independence (i.e., high dependence) and larger scores indicating higher

independence. If there was a score of 0 to 2 (i.e., none to 2 of the six ADL activities were chosen), the

elderly man was classified as low independence; if 3 to 4 of the activities were selected, the elderly

man was classified as moderately independent, and if 5 to 6 items were selected, the elderly man was

classified as highly independent.

       Instrumental Activities of Daily Living (IADL): this tool [16] was the basis for assessing

participants’ difficulty with IADL. IADL are those activities whose accomplishment is necessary for

continued independent residence in the community. The independent activities of daily living are more

                                                     73
sensitive to subtle functional deficiencies than those of ADL, and vary depending on task

performance, including the amount of help needed to accomplish each task. Hence, IADL for older

men in this study used the 8-item choices, like those used for women. These include preparing meals,

shopping, management of medication, money management, transportation, telephone, and laundry.

Scoring the IADL: IADL scores reflect the number of areas of impairment. i.e., the number of

skills/domains in which subjects are dependent. The data was coded as 1 if the respondent is fully

independent to 4 if lowly independent. Scores range from 0 to 8, with higher scores indicating higher

dependence and lower scores indicating greater independence (i.e., low dependence). If none to 3

activities were selected, the elderly person was classified as having low dependence; if 4 to 6 activities

were selected the elder was classified as moderately dependent, and if 7 to 8 items were selected, the

elderly person was classified as highly dependent. Cronbach’s alpha for the 8-item scale was 0.648.



Model

In order to examine the effect of many variables on a single dependent variable, the researcher used

multivariate analysis to test a single hypothesis (physical functioning is determined by current health

status, happiness, area of residence—see equation [1]. Natividad and Zimmer [10] had used logistic

regression to examine factors that determined ADL, IADL, and the self-reported health of older

Filipinos. Using that literature [10], the current study investigated the correlates of functional status of

older Jamaicans within the context of the available data. The proposed model that this research seeks

to evaluate is displayed (Eqn1):



        All the variables were identified from the literature. Using the principle of parsimony, only

those explanatory variables that are statistically significant (P <0.05) were used in the final model to




                                                    74
determine F1 of older men in Jamaica. This final model identified the correlates of Fi of older men in

Jamaica, (Eqn2).

Fi = α0 + α1ARi + α2Ai+ α3SSi + α4CAi + α5Pi εi [2]




       Furthermore, the variables used in this study are based on (1) literature review which shows

that these are likely to correlate with the particular dependent variable, and 2) the correlation matrix

was examined in order to ascertain if autocorrelation (or multicollinearity) existed between

independent variables. Based on Bryman and Cramer [17], correlation can be low (weak) – from 0 to

0.39; moderate – 0.4-0.69; and strong – 0.7-1.0. This correlation was used to exclude (or allow) a

variable in the model. Any of the independent variables which had moderate to high correlation were

excluded from the model. The correlation between life satisfaction and happiness was 0.633;

happiness and social networking (correlation coefficient = 0.12, P = 0.003); happiness and marital

status (correlation coefficient = 0.107, P = 0.026); marital status and income category (correlation

coefficient =0.193, P < 0.001); social networking and marital status (r=0.205, P <0.001); social

networking and age group (correlation coefficient = 0.188, P <0.001); social networking and

occupation (correlation coefficient =0.320, P < 0.001); social networking educational category

(correlation coefficient =0.420, P <0.001); ADL and age cohort (correlation coefficient =-0.813, P

=0.032); income and occupation (correlation coefficient =0.7775, P < 0.001); and, income and

education (correlation coefficient =0.356, P<0.001); employment and education category (correlation

coefficient =0.283, P <0.001), and depression and life satisfaction (correlation coefficient = 0.160, P <

0.001). However, there was no correlation between happiness and present occupation (P =0.761);

happiness and income (P =0.233); happiness and employment status (P =0.516); health status and

depression (p=0.876) as well as life satisfaction and employment status (P =0.261). Hence, life



                                                      75
satisfaction and happiness. and occupation and income category will not be simultaneously used as

explanatory variables.




Results


Demographic Characteristics of Sample


Most of the sample was lowly dependent (77.1%); 55.4% reported moderate health status and 63.6%

indicated that they were satisfied with life sometimes (Table 4.2).


       When functional capacity was disaggregated into ADL and IADL, the following disparities

were observed in the findings. Of the sample, 1.5% had low ADL scores, 1.3% moderate, and 97.2%

had high ADL scores. However, with regards to IADL, 1.9% had low, 18.6% had moderate, and

79.6% had high scores. Of the sample, 43.1% reported that they were suffering from depression,

compared to 56.9% who stated no to the question of whether they were depressed in the survey period.

On examining depression and age cohort, no significant statistical association between both variables

(P = 0.102) was found.


          One-half of the sample indicated that they spent Ja.$100 (US $1.45) monthly for medical

expenditure; 34% of the respondents bought their prescribed medication; 17.1% reported that they

have been hospitalized since their sixth birthday and 65.8% reported that they took no medication. Of

those who mentioned that they were ill during childhood (17.5%, n=350), 34.9% said that the illness

was measles or chicken pox, 26.3% mentioned asthma, 10.0% pneumonic fever, 8.9% polio, 6.6% had

had an accident, 4.6% mentioned jaundice, 1.7% hernia, and 5.1% indicated gastroenteritis. Twenty-

four percent of elderly men indicated that they were rarely happy, 40.5% said sometimes, 31.0%




                                                   76
mentioned often and only 4.5% reported always. Furthermore, 17.7% of the sample reported that they

were seriously ill as children.


       The findings revealed that no statistical correlation existed between ADL and age cohort of the

sample (p=0.205). However, a relationship was found between IADL and the age group of the sample

(χ2 (DF = 4) = 16.011; p=0.003) (Table 3). On further examination, it was revealed that as an older

male increases in age from 55-64 years to 65-74 years and 75+ years, his high level of independence

falls while his moderate dependence increases. Of those who were 55-64 years, 83.0% of them high

independence compared to 78.9% of those aged 65-74 years and 73.9% for those aged 75+ years

(Table 4.3).


       Of the sample, 41.8% of older men were health literate or have been advised on medical relates

conditions, causes, prognosis and precautions compared to 58.3% who were not aware or have been

advised by health care practitioners (including pharmacists, community aides; nurses, or medical

technologists).


       The study revealed that no statistical correlation was found between functional capacity of

older men in Jamaica and health advice (or health literacy) – P =0.845. However, a weak statistical

relationship existed between educational level and health literacy (χ2 (DF = 1) = 110.165, P < 0.001,

correlation coefficient = 0.235) (Table 4.4).


       Table 4.5 revealed that ADL for men 55+ years was very high for each activity, with 88.5% for

continence being the lowest level of independence. For IADL, 56.7% of the sample was still able to

perform heavy duty housework, 62.7% of the respondents were still performing their own laundry,

98.1% managed their money, 77.8% were still shopping, and 70.2% prepared their own meals.




                                                 77
No statistical correlation was found between health status and age cohort of the respondents

(p=0.051), or between life satisfaction and age cohort (P =0.430), or between health status and area of

residence (P =0.190).


       A significant statistical difference was found between life satisfaction of urban and rural older

men in Jamaica – χ2 (DF = 3) = 13.910, P = 0.003. However, that correlation was a weak one

(correlation coefficient = 0.083). On further examination, 35.9% of older rural men revealed that they

were rarely satisfied with life compared to 29.8% of elderly urban men. Concurrently, 37.4% of

elderly urban men reported that they were sometimes satisfied with life compared to 30.2% of rural

men. Twenty-nine percent of urban men indicated that they were satisfied with life most times

compared to 30.5% of rural men.


       A cross-tabulation between life satisfaction and happiness revealed a significant statistical

correlation – χ2 (df = 9) = 1334.448, P < 0.001. The association was a relatively strong one

(correlation coefficient = 0.663) – Table 4.6. Seventy-three percent of those older men who were

rarely happy were rarely satisfied with life, compared to 17.8% of elderly men who indicated being

always happy who were rarely satisfied with life. Forty-seven percent of those who were always

satisfied with life were always happy. Further investigation revealed that 2.1% of those who were

always satisfied with life were rarely happy.


Multivariate Analysis


Based on Table 4.7, the model (Eqn. [2]) is a good fit for the data F [19, 1855] = 6.492, P < 0.00.

Continuing, 36.2% of the variance can be explained by age of respondents, social support, church

attendance, area of residence, the number of people in the household, and depression. Using beta

weights, church attendance was the most significant predictor of functional capacity (β=0.245; 95%

CI: 0.264, 1.291) followed by social support (β=0.129; 95% CI: 0.129, 0.258), area of residence (β=-

                                                  78
0.060; 95% CI: -0.427, -0.061), and lastly, age of respondents. Furthermore, elderly urban men in

Jamaica had a lower functional capacity than rural men, and the study indicates that the older men

become, the more their functional capacity falls—ages 64 to 74 years, β=-0.051; 95%CI: - 0.427, -

0.009; ages 75 years and older, β=-0.054, 95%CI=-0.523, -0.013.




Discussion


Functional capacity of older men in Jamaica was very high as 77 out of every 100 men aged 55+ years

had high independence; 22 out of every 100 had moderate independence, and 1 out of every 100 had

low independence. These levels are somewhat lower than those in Eldemire’s earlier work [7] that

showed that 93.5% percentage of elderly Jamaicans were actively involved in daily management of

the household, 88.5% were physically functional, and 85.9% were mentally competent. Comparatively

though, the functional capacity of elderly men with that of elder Jamaicans (both men and women)

showed that physically functionality of the men aged 55+ years had fallen by 11.5% in 12 years. On

average, the physical functional capacity of older men has been declining by 1% each year since 1995.

Using self-reported depression as an indicator of mental function, the current research revealed that 4

out of every 10 older men were suffering from depression, suggesting that there is also a decline in

mental competency of older men based on Eldemire’s earlier work on elderly people in Jamaica.

Furthermore, older men were predominantly somewhat satisfied with life, having attained at most

primary level education and with good health status. Thirty-four out of every 100 older men in

Jamaica were rarely satisfied with life, with there being more unsatisfied older rural men than older

urban men.




                                                  79
       On disaggregating the current study’s findings using ADL, it was revealed that most men aged

55+ years were able to bathe, feed, use the toilet, and dress themselves with minimal assistance.

However, using IADL, which measures activities that people can continue to accomplish

independently in their residence in the community, it was found that 79.6% needed minimal assistance

(high independence) compared to 18.6% who had moderate and 1.9% low independence.


       There are some similarities and differences between older Filipinos [32], and older men in

Jamaica. With respect to transportation, 18.5% of Filipinos had low independence compared to 1.9%

of older Jamaican men; 17.6% of Filipinos had low independence with shopping compared to 22.3%

of older men in Jamaica; 6.3% of Filipinos needed assistance dressing themselves compared to 2.2%

of elderly Jamaicans; 11.5% of Filipinos had difficulties walking in the house compared to 2.3% of

elderly Jamaicans; and 8.0% of Filipinos had difficulties bathing themselves compared to 2.5% of

elderly Jamaicans in this study. On the matter of self-reported health status, for the current study no

older Jamaican men reported poor or very good health status, while 17.5% and 5.1% of Filipinos

reported poor and very good health status respectively. Nineteen percent of older men in the sample

indicated excellent health compared to 1.0% of older Filipinos. With regards to good health status,

55.4% percent of the current sample reported good health as opposed to 31.5% of Filipinos; and for

fair health status, 25.6% of the current study reported fair health status as opposed to 45.0% of

Filipinos.




                                                  80
       Like Natividad and Zimmer [10], the current study found that as the elderly Jamaicans

aged, their high levels of independence in IADL fall. However, Natividad and Zimmer found a

similar result for ADL, but this research found that there is no statistical difference between

aging for men 55+ years and ADL. Generally, there is a high degree of independence among

older men in Jamaican and older Filipinos. Unlike the Filipino study, which did not examine life

satisfaction, the current study found that only 4 out of every 100 men aged 55+ years were

mostly generally satisfied with life; 64 out of every 100 reported that they were sometimes

satisfied, and 33 out of 100 indicated that they were rarely satisfied with life. In this research, 18

out of every 100 men indicated that their health status as a child was poor. Ten percent of both

elderly Jamaican and older Filipinos (10.1%) had no formal education; 57.1% of the latter group

lived in urban zones compared to 49% in the current research.


       Another similarity between both studies is the use of the starting point of 55+ years,

which is used to examine a functional model. For the current work, the model can explain 36.2%

of the variability in functional capacity of older men in Jamaica. Although Natividad and

Zimmer’s work [10] did not provide such information, age and area of residence were found to

be common predictors of functional capacity in both studies. However, in Natividad and

Zimmer’s study, an older Filipino was 0.34 times less likely to report better IADL than an

elderly urban Filipino. In this study, this was not the case as it was revealed that elderly urban

men aged 55+ years were less likely to report better functional capacity than elderly rural men.


       The current work went further than Natividad and Zimmer’s study by adding some more

variables such as depression, number of people living in household, social support, and church




                                                 81
attendance. These were found to be predictors of functional capacity. Depression was found to

be inversely associated with functional capacity as well as number of people in household.


       Like Natividad and Zimmer, this study found that marital status and education were not

statistically significant determinants of functional capacity (i.e., ADL or IADL). However, the

significant statistical correlation between church attendance and functional capacity is embedded

in the ability to walk or the use of limb functions [18-20]. Hence, the findings do not support any

perspective that church attendees were healthier, but that they were highly probable to higher

functional independence than non-attendees, and this is also the case for those who attend other

social institutions. The researcher needs to make the aforementioned distinction as the current

research did not seek to investigate when those who attended church were healthier, but that they

were more likely to be functionally independent than non-attendees. or for that matter, those who

take part in other social networks. The lowered functional capacity of those who aged explain not

only reduced activities outside of the home, but also speaks volumes about those who are able to

attend outside activities (including church functions) such as that they have a higher level of

independence [21].


       Depression can be used to measure cognitive function, and so the negative correlation

between depression and functional capacity concurs with the findings in other studies that

reported strong correlations between cognitive functions and functional capacity [22, 23]. The

matter of depression affects 4 in every 10 older men in Jamaica, and with the inverse association

between it and functional capacity, there is expected to be a decline in functional capacity of this

cohort [18, 23]. Although depression and life satisfaction are weakly correlated in this sample,

the reality is that depression is further depleting the quality of life lived by men aged 55+ years


                                                82
in Jamaica, and so the correlation offers some insight into the further decline in the functional

capacity of this cohort. While depression is permanent, and to some extent fluid, rate of

depression in the current older Jamaican men is too high and offers another explanation for the

high mortality of elderly men compared to elderly women.


        In a study conducted by Yi and Vaupel [24] of 8,805 people aged 80-105 years in China,

self-reported health status was found to be significantly correlated to functionality and morality

of older people, which was also found in earlier studies [25, 26]. In spite of those findings, the

current study did not concur with those results as it was revealed herein that childhood health

status or current health status were not significantly associated with functional capacity. This

research also concurs with Yi and Vaupel’s work that there was no statistical difference between

urban-rural residents in current health status. Although no statistical correlation was found

between the two aforementioned variables, only a minimal number of elderly men in Jamaica

had a high level of dependence on others (2 out of every 100) and none of them indicated poor

health status.


        Chevannes’s work [27] begins the explanation of the cultural health care-seeking

behavior of males in a broader context of culturalization of boys. Chevannes provided the

explanation for this behavior by men, that it is embedded in social learning theory in which the

young imitate the roles of society members through role modeling; they learn what constitutes

acceptable and good roles by seeing which are supported by reinforcement. The gender role of

sexes is not limited to Jamaica or the Caribbean; a study carried out by Ali and de Muynck [28]

of street children in Pakistan found a similar gender stereotype in that nation. It was a descriptive

cross-sectional study carried out during September and October 2000, of 40 school-aged street


                                                 83
children (8-14 years). The sample was substantially males (80%) with a mean age of 9 years (± 2

years). The methods of data collection were (1) semi-structured interviews, and (2) a few focus

group discussions. Ali and de Muynck [28] found that the sampled population would seek

medical care based on severity of their illnesses and their financial situation. Another finding

was that they preferred to use home remedies, the reason being that mild ailments are not severe

enough to bar them from functioning physically. There is a perception that some morbidities do

not require hospitalisation because the individual thinks he is okay, which was the case in

Nairobi slums [29]. Therefore, like the cases in Pakistan and Nairobi, Jamaican men similarly do

not report illness or seek health-care primarily because of their societal perceptions. This is tied

into the macho culture with which they are grow up, as pointed out by Chevannes. They believe

that they should suppress response to pain and this belief was similarly displayed in the works of

Ali and Muynck and Taff and Chepngeno.




Conclusions


The current study revealed that a miniscule percentage of older men in Jamaica were mostly to

always satisfied with life; many of them had low levels of dependence; few indicated fair health

status and no significant statistical correlation was found between ADL and age cohort, although

one existed between IADL and age groups. The findings revealed that as men age (i.e., from 55

years), there is a deterioration between aging and IADL, suggesting that there are challenges

associated with aging as well as with some aspects of functional capacity. Concurrently, six

factors explain functional capacity of older men in Jamaica (area of residence, age, social

support, church attendance, number of people in household, and depression). Men from more

                                                84
rural areas were rarely satisfied with life, but more of them had a greater functional capacity than

urban men. Depression was found to negatively relate to functional capacity, and church

attendees had a greater functional status than non-attendees. The present findings can be used to

guide policy intervention and future studies in Jamaica.


Acknowledgement

This work is made possible from the dataset of the doctorial work of Chole Morris.




                                                85
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                                             88
Table 4.2: Demographic Characteristics of Sample
Variable                                           Frequency   Percent
Functional Status
    High dependence                                      24       1.2
    Moderate dependence                                 434      21.7
    Low dependence (independence)                      1542      77.1
Marital Status
    Single                                              686      34.3
    Married                                             894      44.7
    Separated                                           112       5.6
    Common law                                          136       6.8
    Widowed                                             172       8.6
Age group
    55- 64 years                                        851      42.6
    65 – 74 years                                       712      35.6
    75 years and older                                  437      21.9
Employment Status
    Employed                                            511      25.6
    Unemployed                                          412      20.6
    Retired                                            1077      53.9
Education
    No Formal Education                                 200      10.0
    Primary and basic                                  1661      83.0
    Secondary                                           102       5.1
    Tertiary                                             37       1.9
Self-rated Health Status
    Excellent                                           357      19.0
    Good                                               1038      55.4
    Fair                                                480      25.6
Social Networking
    Yes                                                 817      59.1
    No                                                 1183      40.9
Life Satisfaction
    Rarely satisfied                                     658     32.9
    Sometimes                                          1,272     63.6
    Most                                                  70      3.5
Childhood Health status
   Good                                                1650      82.5
   Poor                                                 350      17.5
Area of residence
   Urban                                                981      49.0
   Rural                                               1019      51.0



                                            89
Table 4.3: ADL and (I)ADL by Age group
                                     Age group
Variable         Ages 55-64 years 65-74 years         75+ years          pvalue
ADL                                                                      0.205
  Low                     12 (1.4)         12 (1.7)            6 (1.4)
  Moderate                 7 (0.8)         15 (2.1)            4 (0.9)
  High                  832 (97.8)       685 (96.2)         427 (97.7)
Total                         851              712                437

(I)ADL                                                                 pvalue
   Low                    13 (1.5)         16 (2.2)            8 (1.8) 0.003; χ2 (df = 4)
   Moderate             132 (15.5)       134 (18.8)         106 (24.3) = 16.011
   High                 706 (83.0)       562 (78.9)         323 (73.9)
Total                         851              712                437




                                         90
Table 4.4: Health literacy by High level of education attained

                                                           HIGHEST EDUCATIONAL LEVEL
                                                                     Sec /High     Trade
                         No Formal                      Primary /All    /Tech  /Apprenticeship     Certificate
                           Edu.         Basic School        Age       /Compre    /Vocational        /Diploma        Bachelor         Total
                                        N (%)           N (%)        N (%)     N (%)              N (%)            N (%)         N (%)

  Variable                 N (%)
                 No
 Health advise             111 (55.5)      752 (68.1)     249(44.7)    31(39.2)        8 (34.8)         9 (39.1)      5 (35.7)      1165 (58.3)

                 Yes
                            89 (44.5)      352 (31.9)     308(55.3)    48(60.8)       15 (65.2)       14 (60.9)       9 (64.3)       835 (41.8)


Total                          200         1104          557           79                  23               23            14            2000
        χ2 (df = 1) = 110.165, P < 0.001, correlation coefficient = 0.235




                                                                        91
Table 4.5: Disaggregating ADL and (I)ADL of Sample
                            ADL                             (I)ADL
Activity          Low           High         High        Low              Never do
                  independence Independent independent   independence     activity

Bathe                 2.5        97.6
Toilet                1.7        98.3
Dressing              2.2        97.9                    Not Applicable
Continence            11.6       88.5
Transferring           2.9       97.1
Feeding               2.3        97.8

Preparing meals                                70.2           23.4            6.5
Shopping                                       77.8           22.3             -
Managing medication                            64.8           35.3             -
Money management                               90.8            9.2             -
Transport                                      98.1            1.9             -
Telephone                                      98.3            1.7
Laundry                                        62.7           26.3            11.1
House work (heavy)                             56.7           29.6            13.8




                                         92
Table 4.6. Life satisfaction by happiness

Life satisfaction   Happiness

                    Rarely              Sometimes        Most times      Always

                    N (%)               N (%)            N (%)           N (%)

Rarely                 348 (72.5)           172 (21.2)      122 (19.7)      16 (17.8)

Sometimes               82 (17.1)           460 (57.7)      116 (18.7)      10 (11.1)

Most times               40 (8.3)           160 (19.8)      376 (60.6)      22 (24.4)

Always                   10 (2.1)           12 (19.8)        6 (1.0)        42 (46.7)

Total                        480                810              620             90




                                                93
Table 4.7: Multiple Regression of Functional Status by Some Explanatory Variables, N=1,875

                                           Unstandardized          Standardized
                                            Coefficients           Coefficients   95% Confidence Interval
    Variable
                                        Coefficient   Std. Error           Beta     Lower           Upper
    Constant                               12.140           .263              -     11.624         12.656
    Current Health Status                     .074          .117           .016      -.156           .304
    Life Satisfaction                         .032          .112           .007      -.187           .251
    Poor Childhood health status              .009          .109           .002      -.205           .222
    Urban                                    -.244          .093          -.060      -.427        -.061**

    Elderly (ages 65 to 74 years)            -.218          .107          -.051       -.427        -.009*
    Elderly (ages 75 years and older)        -.268          .130          -.054       -.523        -.013*
    Elderly (ages 55 to 64 years) †

    Social Support                            .533          .140           .129       .258       .807***
    Church Attendance                        1.028          .134           .245       .764      1.291***

    Primary schooling                        -.145          .154          -.027       -.447          .157
    Secondary or Tertiary                    -.144          .225          -.019       -.586          .297
    No formal education†

    Household Head                            .027          .144           .004       -.255          .310

    Married                                  -.021          .106          -.005       -.229          .187
    Separated, Divorced or Widowed           -.137          .147          -.024       -.426          .152
    Single†

    Number of people in household            -.051          .023          -.053       -.096         -.006*
    Employed                                 -.109          .107          -.024       -.318           .101
    Dummy Health Advise                      -.028          .097          -.007       -.218           .163
    Dummy Take Medication                    -.087          .098          -.020       -.280           .107
    Dummy Depression                         -.446          .095          -.108       -.633      -.259***
R = 0.602
R squared = 0.362
F [19, 1855] = 6.492, P < 0.001
†Reference group




                                                      94
                                                                           Chapter 5

The role of social networks among late adult men in Jamaica


Paul Andrew Bourne
Social networks and the social support that emanate from these networks is an important
determinant of health status. However, the relationship between social networks and health status
of elderly men of Jamaica is an under researched area in this developing country.
This study seeks to understand the role of social network in the lives of older men in Jamaica as
this impacts their health status. A 132-item questionnaire that included items, on social network,
happiness, health status, activities of daily living (ADL) and IDL (functional dependence),
education and other demographic variables was used to collect the data. The sample consists of
2000 randomly selected older men 55 years and older from the parish of St. Catherine, Jamaica.
The majority of men in the sample have low functional dependence but good health status, and
high cognitive functionality. There are five predictors of the role social networks. These
predictors are health advice (OR = 2.21, 95%CI: 1.09, 4.49), functional status (OR = 0.84,
95%CI: 0.71, 1.00), health plan (OR = 0.02, 95%CI: 0.01, 0.10), number of siblings alive
(brothers - OR = 12.31, 95%CI:3.07, 49.29; sisters - OR = 0.18, 95%CI: 0.05, 0.58) and
depression (OR = 2.48, 95%CI: 1.29, 4.78). The role of social network in the health status of
older men is determined by health advice, functional status, health insurance plan, the number of
siblings alive and depression. There is need for more research that takes into account other
factors such as social class, varied age cohorts, gender, race and ethnicity and rural urban
dichotomy.


Introduction
The Caribbean has been identified as the most rapidly ageing region of the world. Between 1960

and 1995, there was a 76.8% increase in the elderly population [1]. Among its regional island

states, the average growth rate in the elderly population was approximately 5.3% for the 1995-

2000 periods. The elderly as a percentage of total population was 4.3% in 1950 and is estimated

to reach about 15% by 2020 [1]. In Jamaica, a similar pattern has been observed with a clear and


                                               95
rapidly rising trend in the elderly as a proportion of the population [2]. Eldemire [3] noted that

the elderly in Jamaica represents 10% of the population, and that they were for the most part

mentally competent and physically independent. In recent years, that has been a growing interest

in social networks and social support among urban and rural elderly [4].

       Social network analysis is one of the many ways that the social life of the elderly can be

examined. Ideally social networks can be defined as, all the people with whom the individual

interacts, typically including persons who they live with as well those in categories of social

identities such as neighbours, friends and colleagues at work [5]. It is documented in the

literature that social support and social networks have positive effects on the health and well-

being of elderly adults irrespective of where they are living [6,7]. A study carried out in the

United Kingdom examining the contributions of social networks and support to the subjective

wellbeing (i.e. life satisfaction) of older persons found that health status is a greater predictor of

the life satisfaction among urban elderly people than those living in a semi-rural community [8].

Greater source of strain operationalized as activities of daily living (ADL), physical health

problems and economic deprivation were found among institutionalized rural elderly people than

those living alone, those with less education, being white and a woman. These individuals all had

smaller social networks but they were more likely to receive social support. Physical health

status and ADL were highly predictive of life satisfaction and psychological distress among

these rural elderly individuals [9]. Over time, positive health was only moderately associated

with integration in a social support network. People with the poorest health had a low sense of

control and low social support [10].

       The social networks in which older people are embedded constitute a major source of

personal wellbeing and a principal resource for personal care in later life [11]. The wellbeing of

                                                 96
the elderly is associated with the happiness of the people with whom there are socially

connected, indicating that happiness is also a social phenomenon similar to health [12]. The

variance in happiness experienced by elderly people can be explained by basic resources such as

social networks, employment, job training, cognition, extraversion and health. Some of these

resources were mediated by attitudes toward life and self referent beliefs [13]. Older people who

had negative feelings towards the members of their social network were less happy. Also, men

were less happy when they felt that their network was too demanding and when they wanted

more people they could depend on [14]. The network of older people also plays an important role

in their success in finding jobs. However, it is the reciprocal confidant relationship that was

significantly related to finding employment and not other social network variables such family

and friends. This finding means that gaining employment was less related to who these elderly

people knew and more on how involved these people were in their lives [15].

       Social support is defined as the range of interpersonal aids that people require for daily

functioning such as augmentation of self-concept, sense of belonging, cognitive guidance,

concrete assistance in fulfilling tasks, and feeling loved and admired [16]. The apathy of elderly

people who lived alone in a depopulated rural town in Japan significantly influenced their ability

to engage into routine activities of daily living (ADL) [17]. There is a negative association

between homecare and ADL among older Danish men. The provision of home care had a

positive effect on the wellbeing of men who were largely incapacitated [18]. Affective and

cognitive status was independently associated with age, ADL and instrumental activities of daily

living (IADL) among elderly people. The number of medications these people were taking was

also associated with IADL. Global health, the number of medications taken, the number of




                                               97
symptoms and disease and cognitive status were all independently associated with scores on the

physical performance tests [19].

       Despite the fact that network support is perceived as particularly important to African

American men in very old age [4], the social networks of elderly men in Jamaica have not been

widely addressed in the research literature. Therefore policy makers and practitioners in Jamaica

are without the necessary knowledge base and research to create programmes and services that

will engage men and, in particular, the elderly. The structure of social networks, the association

between social support and health and/or wellbeing, quality and quantity of social interactions,

isolation and loneliness, and their association with health are well established in the literature.

Notwithstanding the aforementioned issues, a gap exists in the literature as social network is

oftentimes used as an independent variable. Conceptual, theoretical and methodological

guidelines exist that establish the relationship between social relationship and health [20-23], and

how research should be conducted in the future [21]. This allows for the utilization of

multivariate analyses (models) which indicate different independent variables that are associated

with the dependent variable such as health and cognitive functioning [24,25], using cross

sectional studies [25]. But social network is predominately used as an independent variable, and

its use as a dependent variable is still under-researched, moreso this is the case in Jamaica.

Hence, the current work seeks to (1) evaluate social networks in older men and (2) ascertain

factors which influence social network among older men in Jamaica.

Methods

The study used primary cross-sectional survey data on men 55 years and older from the parish of

St. Catherine, Jamaica in 2007. The survey was submitted and approved by the University of the

West Indies Medical Faculty’s Ethics Committee. Stratified multistage probability sampling

                                                98
technique was used to draw the sample (2,000 participants). A 132-item questionnaire was used

to collect the data. The instrument was sub-divided into general demographic profile of the

sample, past and current good health status, health-seeking behavior, retirement status, social and

functional status. The overall response rate for the survey was 99% (n = 1,983). Data was stored,

retrieved and analyzed, using SPSS for Windows (16.0).

       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts

(ED) or census tracts. The parish of St. Catherine is divided into a number of electoral

constituencies made up of a number of EDs. The one hundred and sixty-two (162) enumeration

districts in the parish of St. Catherine provided the sampling frame. The sample size was

determined with the help of STATIN. The enumeration districts were listed and single-stage

cluster sampling was used to select the sample. The enumeration districts were numbered

sequentially and selection of clusters was determined by calculating a sampling interval. From a

randomly selected starting point, forty (40) ED (clusters) were subsequently selected with the

probability of selection being proportional to population size. Advised by STATIN and utilizing

the C-survey computer software, it was determined that 50 older men in each ED would be

interviewed yielding a sample size of 2000.

       The parish of St. Catherine had approximately 233,052 males, (preliminary census data

2001) of which 33,674 males were 55 years and over. STATIN maintains maps with ED or

census tracts which included the selected EDs and access routes and had references to the

selected site of a starting point household within each ED. The starting point was determined by

randomly selecting a household with a man 55 years and over from the list of persons in each

ED.




                                                99
       Where the selected household did not have an older man the adjacent household was

canvassed. Where households had a man 55 years and older as a resident and he was not at home

a call-back form was left indicating a proposed time that the interviewer would return which

would not be longer than two days after the initial visit. In households where there was more

than one man 55 years old and over, then all were included in the survey.

       The sampling frame was men fifty-five years and older in the parish of St Catherine. The

parish of St. Catherine was chosen as previous data and surveys by STATIN suggest that the

demographic characteristics of this parish are similar to Jamaica.



Measures
Social network is self-reported involvement in church, civic organization, social clubs and

community groups, families and among friends. This is a binary variable, where 1 = social

network, 0 = otherwise. It is taken from the questions, ‘do you attend church, civic organization,

social clubs and community group? And, ‘are you supported by families and/or friends? The

options were yes or no. The variable happiness was measured based on the person’s self-report

about their happiness. It is a Likert scale question, which ranges from always to rarely happy. It

was coded into a binary variable, whether or not the individual had moderate-to-high or low

happiness: 1= moderate to high happiness, 0 = otherwise. The variable health status was

measured using people’s self-rating of their overall health status, which ranges from excellent to

poor. The question was ‘how would you rate your health today?’ The response choices were (1)

excellent; (2) good; (3) fair and (4) poor. Current self-reported health status was a binary

variable, where 1= good (including moderate and excellent health status) and 0 = otherwise. In

terms of the variable life satisfaction, the question was “all things considered, how satisfied are


                                               100
you with your life as a whole nowadays?’Life satisfaction is a binary variable, where 1= good-to-

excellent self-reported overall satisfaction in life, 0 = otherwise. Depression is measured using

response to the question - ‘are you depressed?’ The options were yes or no. In terms of

education, the question that was asked was, ‘what is the highest level of education you have

attained?’ The response choices were (1) no formal education, (2) basic school, (3) primary

school/all age, (4) secondary/high/technical school, (5) vocational (ie apprenticeship/trade), (6)

diploma, (7) undergraduate degree, (8) post-graduate degree. In terms of physical exercise, the

question for this variable was ‘do you take time out of your regular schedule for physical

exercise?’ The response choices were (1) yes and (2) no. In terms of type of physical exercise,

the question for this variable was ‘what are the types of physical exercises you are involved in?’

For childhood illness, the first question for this variable was ‘were you seriously ill as a child?’

The response choices were (1) yes, (2) no. The second question was ‘were you frequently ill as a

child?’ The response choices were (1) yes, (2) no. If the response to either question was yes, it is

coded as poor childhood health status and if the response is no in both cases it is coded a good

health status in childhood. Age group was categorized into three sub-groups. These were (1) ages

55 to 64 years, (2) ages 65 to 74 years and (3) ages 75 years and older (i.e. 75+ years).

       Functional status is the summation of ADL and IADL. Performance of ADL is used to

describe and monitor the improvement in the functional status of a person compared to his or her

baseline level of functioning overtime. There are systems such as the Katz ADL tool that seek to

quantify these functions and obtain a numerical value. These systems are useful for prioritizing

care and resources. Generally though, these should be seen as rough guidelines for the

assessment of a patient’s ability to care for themselves. There are 14 items (including daily

activities, household chores shopping, cooking and paying bills). The reliability of the items was

                                                101
very high, α = 0.801. In scoring the Katz ADL, independence on a given function is given a

score of 1 and being dependent is given a score of 0. Total scores range from 0-14 with lower

scores indicating high dependence and higher scores indicating greater independence.

       The IADL was used to assess the participants’ accomplishment of activities that are

necessary for their continued independent residence in the community. The IADL is more

sensitive to subtle functional deficiencies than the ADL. In addition, the IADL differentiates

among task performance including the amount of help needed to accomplish each task. Since

only men were used as participants in the study, the University of Wollongong’s modified IADL

functional ability scale was used to assess the IADL of men in the study. Consequently the

domains of food preparation, laundry and housekeeping were omitted in this study with regard to

the IADL for older men.

       The IADL scores reflect the number of areas of impairment i.e. the number of

skills/domains in which subjects are dependent. Scores ranged from 0-5. Higher scores indicate

greater impairment and dependence. High dependence ranges from 0 to 5.5; moderate

dependence is from 5.6 to 9.7 and low dependence (i.e. independence) ranges from 9.8 to 14.0.

Independence means without supervision, direction, or active personal assistance. The

performance on the functions can be further classified and analyzed using the format below. The

classification recognizes that combinations of independence/dependence with respect to

particular functions reflect the different degrees of levels of capability with respect to ADL. The

classification outlined below was used to further describe the functional status of men with

regard to ADL. Any variable that had a high correlation was excluded, and well as any variable

that had a non-response rate in excess of 20 percent.




                                               102
Statistical analyses

Descriptive statistics were employed to provide background information on the sample and Chi-

square was used to examine non-metric variables. Logistic regression was used to examine a

binary dependent variable (i.e. physical exercise) and some socio-demographic variables

(employment status, current health status, health status in childhood, number of siblings alive).

Level of significance was P < 0.05. Where collinearity existed (r > 0.7), variables were entered

independently into the model to determine those that should be retained during the final model

construction. To derive accurate tests of statistical significance, we used SUDDAN statistical

software (Research Triangle Institute, Research Triangle Park, NC), and this adjusted for the

survey’s complex sampling design.


Model

In order to examine the effect of many variables on a single dependent variable, the researchers

used multivariate analysis to test a single model. The proposed model that this research seeks to

evaluate is displayed (Eqn1):


SNi = ƒ(Hti ,HAPPi ,LSi ,Ci ,ARi , Ai, CAi , EDi , HHi , MSi , Pi , HEAi , EMi , Di ,TM; AMi, Fi, HPi,

HOi, CFi, ∑Xij, εi)............................................................................................................[1]


Where SNi (social networking) is a function of current good health status of person i, Ht;

happiness, HAPPi; life satisfaction, LSi; children, Ci; area of residence, ARi; age group of

respondent, Ai; church attendance, CAi; educational level, EDi; head of household, HHi; marital

status, MSi;          number of person in household, Pi; poor health status in childhood, HAi;

employment status, EMi; self-reported depression, Di; taking medication, TMi; health advise,

HEAi., functional status, Fi; health insurance plan, HPi; cognitive functionality, CFi; and Xij is a

                                                                    103
vector of the number of siblings the participant has alive. The health insurance plan that is

assessed is that of elderly men which is acquired through private health insurance companies

such as Sagicor, Guardian Life etc or from the Government. Health advice is information on

health related matters that improves a person’s wellbeing whether it is on diagnosis, treatment of

a disease etc.

All the variables were identified from the literature. Using the principle of parsimony, only those

explanatory variables that are statistically significant (P <0.05) were used in the final model to

determine SNi (i.e. social networking) of older men in Jamaica. This final model identified the

correlates of SNi of older men in Jamaica, (Eqn2).


SNi = f(Di, HEAi, Fi, HPi, ∑Xij,εi)……......................................................................................[2]



Results

Demographic characteristics


Of the sampled participants (n = 2,000), 74.2% indicated that they had good health in their

childhood; 74.4% reported good current health status; 51.0% lived in rural areas; 3.5% were

mostly satisfied with life; 10.4% had moderate to high functional dependence; 89.6% had low

functional dependence (i.e. independence); 21.9% were aged 75 years and older; 35.6% were

aged 64.5 to 74 years and 42.6% reported ages 55 to 64 years. In addition, 94.1% had high

cognitive functionality; 43.1% reported that they were depressed; 67.3% reported that they do

some kind of physical exercise; 24.0% indicated being rarely happy; 4.5% mentioned that they

were happy most time and 71.5% claimed occasional happiness. Twenty four percent of elderly




                                                             104
men indicated that they were rarely happy, 40.5% reported sometimes, 31.0% mentioned often

and only 4.5% reported always.

       One half of the participants indicated that they spent Ja.$100 (US $1.45) monthly for

medical expenditure; 34.0% bought their prescribed medication; 17.1% reported that they have

been hospitalized since their sixtieth birthday and 65.8% reported that they took no medication.

Of those who mentioned that they were ill during their childhood (17.5%, n = 350), 34.9% said

that the illness were measles or chicken pox, 26.3% mentioned asthma, 10.0% pneumonic fever,

8.9% polio, 6.6% accident, 4.6% jaundice, 1.7% hernia, and 5.1% indicated gastroenteritis.

Furthermore, 17.7% of the sample reported that they were seriously ill during their childhood.

       Further analysis of the socio-demographic characteristics revealed that there was no

statistical difference between happiness, current health status, social networking, taking

medication, self-rated depression, having children, age of respondents, and area of residence (P >

0.05). There is a statistical difference between ownership of a house and area of residence (P <

0.001). Forty-six percentage of older rural men owned their own home compared with 36.2% of

urban older men (Table 5.1). A statistical difference was also found between childhood health

status and area of residence (P < 0.001). Approximately 78.7% of urban older men reported that

they had good health status in childhood compared to 69.9% of rural older men. The cross

tabulation between marital status and area of residence revealed a correlation (P = 0.002). In

rural Jamaica, there were more older men who were in common law union (7.6%) than in urban

areas (6.05%) and those who were widowed (rural - 10.2%; urban - 6.3%). There were more

urban older men who were married (45.6%) than married rural men (43.9%) (Table 5.1).




                                               105
Multivariate analyses

Of the 21 variables identified by the literature [Eqn. (1)], 5 of them were found to be predictors

of social network [Model (2) or Eqn (2)]. The model [Eqn (2)] used in the study had a statistical

significant predictive power [model χ2 (23) = 318.131, P < 0.001; -2 Log likelihood = 274.486;

Hosmer and Lemeshow goodness of fit χ2 =1.648, P = 0.990]. From the classification matrix,

overall, 91.9% of the data were correctly classified: 52.9% of cases in social network and 98.1%

in no social network. Furthermore, 63.5% of the variability in social network of older men in

Jamaica can be explained by 5 predictors. These variables are self-reported depression (OR =

2.48, 95%CI: 1.29, 4.78); health advice (OR = 2.21, 95%CI: 1.09, 4.49); functional status (OR =

0.84, 95%CI: 0.71, 1.00); health insurance plan (OR = 0.02, 95%CI: 0.01, 0.10); and number of

siblings who are alive (brothers - OR=12.31, 95%CI:3.07, 49.29; sisters – OR = 0.18, 95%CI:

0.05, 0.58) (Table 5.2).



Discussion

Research has indicated that social network size and frequency of contact are important social

factors that can improve quality of life for older adults [26]. This study which investigated the

role of social network among men in late adulthood in Jamaica found that there were five factors

that predicted networks in our sample of older men. These were health advice, functional status,

health insurance plan, the number of siblings alive and depression. In this study just over two-

fifths of the men in both urban and rural areas were married, and 10.2% urban and 6.3% rural

men widowed. Men are more likely than women to arrange their social networks around their

spouse. Thus, women’s social support networks are typically more robust than men’s and

widowed men may be at a particular risk for losing crucial connections to social support

                                               106
networks and drastic reductions in frequency of interaction [27]. Van Tilburg (1995) found that

elderly, unmarried men have the smallest social networks of all groups [28].

       In addition to spouses and children, friends and other relatives located in close proximity

may provide social support and help to promote better mental well-being for older adults. Studies

have found that contact with friends is more effective in decreasing depression in elderly

populations than contact with adult children [29, 30]. Like marriage and parenthood, however,

the influence of friends and family on the mental well-being of older adults may differ by

gender, race, age, and class. Studies by Cloos et al. of the perception of the elderly in six

Caribbean countries about ‘active ageing’ found that some elders receive social and financial

support from relatives while others fear isolation and face deprivation [31]. In this study there is

a positive relationship between health advice from family and friends and social network. This

could indicate that an increase in social network increases the amount of health advice that the

elderly men receives from their family and friends.

       Previous research has suggested that social support and functional status influence the

subjective well-being of the elderly [32]. Deng et al. reported that both social support from

family members and cognitive function appear to be key factors associated with quality of life

among the very old in China [33]. This study showed that there is an inverse relationship

between functional status and social network. This could indicate that as the functional status of

the elderly men decreases their social network increases. Some 74.4% of the men reported

having good current health status and 89.6% of them had low functional dependence. This

suggests that the persons in these older men’ social network provides crucial support in response

to their declining functionality or lack of independence. Seeman and colleagues reported that the




                                                107
people with lowest social support tend to have the poorest health and need more assistance [10].

Moreover, functional health is determined by the levels ADL and IADL [34].

       There is a growing awareness that common mental conditions, such as depression and

other chronic degenerative conditions may contribute strongly to disability, impaired wellbeing

and the use of health services by older people [35,36]. The ageing of Jamaican population

implies greater demand of hospital services. A key finding of this study is a negative relationship

between health insurance plan and social network where the absence of a health insurance plan

leads to an increase in social network. This finding suggests that men who do not have a health

insurance plan, are able to obtain medical care by receiving financial assistance from friends and

family members. There is also evidence in the literature that social involvement with friends and

family may help moderate the negative effects of ill health and depression by offering emotional,

functional, and financial assistance [37,38].

       Moriarty and Butt [39] found that different ethnic groups have not only different

expectations for social support but that their actual forms of social support vary widely in terms

of diversity, consistency, and purpose. Whites were much more likely to only ask their adult

children for help in the case of a crisis as compared to other ethnic groups [39]. African and

Caribbean Americans reported more diverse availability of social support than whites and

Asians, such as extended kin and church community members, a finding that could be found in

our Jamaican population. Blacks are more likely than Whites to live in close proximity to

siblings in adulthood [39]. Despite the closer proximity among Black siblings, an analysis of

sibling neighbours finds no racial difference in exchange of instrumental support. However,

frequent contact with sibling neighbours is more common among Blacks than Whites [39].

Results also indicate that older persons receive more support from nearby siblings when they do

                                                108
not have other core family members (spouses, children or parents) in their family network [40].

Similarly in this study siblings are importantly influences in the core of the elderly men’s social

network. There is a negative relationship between having sisters and social network, and a

positive relationship between having brothers and social network. This is because Jamaica is

patriarchal society where men normally receive more salary than women. Therefore men have

more resources than women to support ailing siblings. These women may also be married or in

common law relationships which reduces the amount of time and resources they can spend with

an ailing sibling.

        Depression a common mental health problem among older adults is associated with

decreased quality of life, difficulties in daily functioning, and increased utilization of health

services as well as risk of suicide [41, 42]. In this study approximately two-fifths of the elderly

men were depressed and just over one-fifth reported that they were rarely happy. A study by

Ritch et al. found that elderly people from ethnic minorities may be at particular risk of suffering

from dementia and depression [43]. Differences in vascular risk profile in Afro-Caribbeans may

result in higher rates of multi-infarct dementia [43], and living in a hostile environment may

predispose to depression [44]. The district areas in the parish of St. Catherine have high levels of

unemployment, show signs of deprivation and have moderate crime rates, and so may be

considered a somewhat hostile environment. So it would not be unreasonable to expect to find

psychiatric or psychological morbidity in these elderly men.

        This study found that there is a positive relationship between depression and social

network. This could indicate that the elderly men who are depressed experienced an increase in

social network. This increase in social network and support can improve mood and social

wellbeing. Happiness is a social phenomenon because people’s happiness is associated with the

                                                109
happiness of the people with whom they have social connections [18]. This increase in social

network is of critical importance because some 64.5% of the men in our sample reported that

they were rarely happy or sometimes happy. However, other studies have shown that although

higher numbers of friends is associated with higher levels of subjective well-being, this effect

does not hold for African Americans in old age [45]. Thus, the oldest African Americans may be

at risk for depression not only because they are experiencing shrinking friend and family

networks with age but also because the influence of friends on well-being may decrease with age

in black populations. Although family and friend proximity is often indicative of strong social

support and thus better wellbeing for older adults, there are a few studies that conclude that kin

interaction has no concrete impact on elderly well-being [46, 47] or even a negative effect [45].

Despite, the depressed mood among a large portion of our sample, 94.1% of the men in our study

have high cognitive functionality which is a surprising finding because cognitive functionality

decreases with the existence of depression. The importance of affect and cognition is

underscored by the findings of Hansen and colleagues that among elderly people there were

independent associations between affective and cognitive status and ADL, IADL and age [18].

This study has highlighted the importance of social network in the health and functional

dependence of older men in Jamaica which is an under researched area. These is need for more

research on social network on health in Jamaica among different social classes and racial and

ethnic groups, people in rural and urban areas, among women, and a more wide ranging age

cohort of people.

       There are some limitations to this study. The sample was drawn from the parish of St.

Catherine so the results should not be generalized to the entire country. Also, there is the

possibility that social desirability bias occurred. The participants may have told the interviewers

                                               110
what they wanted to hear to get the approval of the interviewers. In addition, the attributions

people make to their behaviours and their functional and health status is sometimes incorrect and

lies below conscious awareness.



Conclusion

This study looked at the role of social network among late adulthood men in Jamaica. The

majority of older men reported good current health status, high cognitive functionality but low

functional dependence. The role of social network among older men was predicted by health

advice, functional status, health insurance plan, the number of siblings alive and depression. This

study provides pertinent insights into social network among older men, and has far reaching

implications for public health and future research in Jamaica. Despite the information which

emerged from this paper, there is the need for more research on social network and health that

will extend to population in order to obtain further understand the phenomena, and evaluate any

differences between the population, older men and older women. These areas of research are

needed to increase our understanding of the social network and health in Jamaica.



Acknowledgement

This work is made possible from the dataset of the doctorial work of Chole Morris.




                                               111
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                                              116
Table 5.1: Socio-demographic characteristics of sample by area of residence


                                                Area of Residence
Variable                                     Urban              Rural                 P
Age                                                                               0.141
 55 – 64 years                                   438 (44.6)          413 (40.5)
 65 – 74 years                                   342 (34.9)          370 (36.3)
 75+ years                                       201 (20.5)          236 (23.2)
Marital Status                                                                    0.002
 Single                                           359(36.6)          327 (32.1)
 Married                                         447 (45.6)          447 (43.9)
 Separated                                          54 (5.5)           58 (5.7)
 Common-law                                         59 (6.0)           77 (7.6)
 Widowed                                           62 (6.3)          110 (10.8)
Ownership of dwelling                                                             0.001
 No                                              626 (63.8)          550 (54.0)
 Yes                                             355 (36.2)          469 (46.0)
Self-reported depression                                                          0.316
 No                                              564 (57.5)          574 (56.3)
 Yes                                             417 (42.5)          445 (43.7)
Take Medication                                                                   0.060
  No                                             662 (67.5)          653 (64.1)
  Yes                                            319 (32.5)          366 (35.9)
Have Children                                                                     0.155
  No                                               39 (4.0)            31 (3.0)
  Yes                                            942 (96.0)          988 (97.0)
Social Networking                                                                 0.053
  No                                             562 (57.3)          621 (60.9)
  Yes                                            419 (42.7)          398 (39.1)
Self-reported Health in Childhood                                                 0.001
  Good                                           772 (78.7)          712 (69.9)
  Poor                                           209 (21.3)          307 (30.1)
Self-rated Current Health Status                                                  0.458
  Good                                           683 (74.6)          712 (74.2)
  Poor                                           233 (25.4)          247 (25.8)
Employment status                                                                 0.292
 Employed                                        257 (26.2)          254 (24.9)
 Unemployed                                      188 (19.2)          224 (22.0)
 Retired                                         536 (54.6)          541 (53.1)
Happiness                                                                         0.213
 Rarely                                          229 (23.3)          251 (24.6)
 Occasionally                                    700 (71.4)          730 (71.6)
 Most time                                         52 (5.3)            38 (3.7)

                                             117
Table 5.2: Logistic regression of social network by some variables

 Variable
                                                                        Odds     CI (95%)
                                              Coefficient       P       ratio
   Dummy Own Dwelling                                0.525      0.147     1.69     0.83, 3.44
   Cognitive Functionality                          -0.060      0.721     0.94     0.68, 1.31
   Dummy Have Children                               0.201      0.833     1.22     0.19, 7.87
   Dummy Depression                                  0.910      0.006     2.48     1.29, 4.78
   Dummy Take Medication                             0.567      0.092     1.76     0.91, 3.41
   Dummy Education                                   0.919      0.266     2.51    0.50, 12.67
   Dummy Health Advise                               0.795      0.027     2.21     1.09, 4.49
   Functional status                                -0.173      0.048     0.84     0.71, 1.00
   Dummy area of residence (1=urban)                 0.416      0.210     1.52     0.79, 2.91

   Elderly (ages 64 to 74 years)                    -0.083      0.828     0.92     0.44, 1.95
   Elderly (ages 75 years and older)                -0.440      0.372     0.64     0.25, 1.69
   †Elderly (ages 55 to 64 years)                                         1.00

   Dummy Current Health Status                       0.412      0.235     1.51     0.77, 2.98
   Dummy Happiness                                  -0.110      0.777     0.90     0.42, 1.92
   Life Satisfaction                                 0.133      0.747     1.14     0.51, 2.56
   Health status in childhood                        0.065      0.867     1.07     0.50, 2.30
   Household Head                                    0.072      0.890     1.07     0.39, 2.97

   Married                                           0.082      0.825     1.09     0.53, 2.24
   Separated, Divorced, or Widowed                  -0.231      0.679     0.79     0.27, 2.37
   †Single (include common-law)                                           1.00

   Health plan                                      -3.835      0.000     0.02     0.01, 0.10
   Employed                                          0.441      0.246     1.56     0.74, 3.28
   Number of Brother (s) Alive                       2.510      0.000    12.31    3.07, 49.29
   Number of Sister(s) Alive                        -1.742      0.004     0.18     0.05, 0.58
χ2 (23) =318.131, P < 0.001
-2 Log likelihood = 274.486
Hosmer and Lemeshow goodness of fit χ2=1.648, P = 0.990
Nagelkerke R2 =0.635
†Reference group




                                                          118
                                                                            Chapter 6

A cross-sectional survey of the health status, life satisfaction and happiness of
older men in Jamaica - associations between questionnaire scores



Paul A. Bourne, Chloe Morris, Denise Eldemire-Shearer


Empirical evidences have shown that happiness, life satisfaction and health status are strongly
correlated with each other. In Jamaica, we continue to collect data on health status to guide
policies and intervention programmes, but are these wise? The current study aims to fill the gap
in the literature by examining life satisfaction, health status, and happiness in order to ascertain
whether they are equivalent concepts in Jamaica as well as the coverage of the estimates. The
current study used a cross-sectional survey of 2000 men 55 years and older from the parish of St.
Catherine in 2007. Data were stored, retrieved and analysed using SPSS for Window version
15.0 (SPSS Inc; Chicago, IL, USA). Ordinal logistic regression techniques were utilized to
examine determinants of happiness, life satisfaction and health status. Happiness was correlated
with life satisfaction - Pseudo r-squared = 0.311, -2LL = 810.36, χ2 = 161.60, P < 0.0001. Life
satisfaction was determined by happiness - Pseudo r-squared = 0.321, -2LL = 1069.30, χ2 =
178.53, P < 0.0001. Health status was correlated with health status age, income, education and
area of residence - Pseudo r-squared = 0.313, -2LL = 810.36, χ2 = 161.60, P < 0.0001. The
current study refuted the empirical finding that there is an association between self-reported
happiness and health status, but one between life satisfaction and happiness. This shows the
geopolitical differences as well as age in determining these associations.



Introduction
For many centuries, health was measured on the further extreme of the illness pendulum. Health

therefore meant that people were not experiencing physical illnesses (or ailments). This approach

was negative in scope [1], but the advantage of this measure was its precision in objectification.


                                                119
Illness (or ill-health) denotes being diagnosed with a particular pathogen which caused the

present state. It follows that the hospital system, technology, the study of medicine and treatment

of ill-health was fashioned around this biomedical approach. The biomedical approach (or

model) was more than dominant in medicine, technology, health care system and treatment of ill-

health, but people used this as a definition of their wellbeing (or ill-being). Then in the 1940s, the

World Health Organization recognizing the uni-dimensional nature of this measure forwarded a

conceptual definition of health that argued for the inclusion of social, economic and

psychological conditions in the study of health. This was documented in the Preamble to the

WHO’s Constitution in 1946 [2]. Engel, a psychiatrist, apparently adopted the broad conceptual

framework offered by the WHO, when he forwarded a ‘biopsychosocial model’ in the treatment

of mentally ill patient [3-6]. He opined that the people are as such body as they are social,

psychological and economic being. This means that patient care should not be solely about the

biological conditions of the ill-patient, but on the psychosocial and economic components.


       Many decades later, many scholars continue to use morbidities and mortality in the

discussion of health and health outcome [7-12]. This is also the practice by Latin America and

Caribbean scholars [13-25]. Again the dominance of morbidities and mortality studies are owing

the (1) structure of the world around the biomedical model, (2) objectivity of those measures and

(3) training of many scholars that knowledge through the objective science is superior to

subjective (or “soft”) science. This is reinforced by Bok who opined that the WHO’s

concepualisation of health is too broad and so can be objectively measured and operationalized

for researchers to use with the element of subjectivity and by this reducing the objectivity of the

measure. While the WHO’s conceptual definition of health includes an element of subjectivity,

this in no way diminish the quality of science or information that is obtained from people. The

                                                 120
WHO introduced wellbeing in the discussion of health measurement, and this is an expansion

from the negative approach to the conceptualisation of health.


       Embodied in wellbeing is measure of people living standard or general life, which

extends beyond illness (or ill-health) [2, 26, 27]. The dominance of positivism or quantitative

scholars like the arguments raise in health opined that wellbeing must be measure using

quantifiable approach such as income, expenditure, consumption, Gross Domestic Product or per

capita income [28-30]. In a material entitled ‘Objective measures of wellbeing and the

cooperation production problem’, Gaspart [28] provided arguments that support the rationale

behind the objectification of wellbeing. His premise for 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.


       According to WHO, health is multifaceted. If “Health is state of complete physical,

mental and social well, and not merely being the absence of disease or infirmity” [2], then

subjectivity must be an aspect of its measurement. In order to forward an understanding of what

constitutes wellbeing or ill being, a system must be instituted that will allow us to coalesce a

measure that will unearth peoples’ sense of overall quality of life from either economic-

welfarism [31] or psychological theories [32-35]. The discourse on people’s assessment of their

lives was driven by their experiences including cognitive judgements and affective reactions

[36]. This meant that the study of wellbeing could now expand to include subjective measures


                                                121
such as self-rated health, life satisfaction, and happiness [37]. Wilson [37] found that happier

people were healthier, well-educated, well-paid, extroverted, optimistic, worry-free, religious,

married, and of high self-esteem among other positive psychological conditions. One scholar

opined that satisfaction with life and positive affective conditions were among subjective

wellbeing as happiness [36]. The uses of subjective indexes such as happiness, life satisfaction,

perceived quality of life or wellbeing have been examined by even some economists [38-44].

The economists have only concurred with what psychologists have been postulating for years

[32-35].


       An economist in the 1970 utilized another subjective index (i.e. self-reported health status

or health status) to measure health [45].         Ringen [46] in a paper entitled ‘Wellbeing,

measurement, and Preferences’ argued that non-welfarist approaches to measuring wellbeing are

possible despite its 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 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 forwarded arguments which show that people’s choices are sometimes

‘irrational’, which is the make for the departure from empiricism.


       Many empirical studies have been done on the using particular subjective indexes such as

happiness, self-reported health status and/or health conditions to measure health or wellbeing. In

the Caribbean Hambleton et al. [47] utilized health status and health conditions and found that a

strong correlation between both variables. Another group of Caribbean scholars used self-


                                                122
esteem, life satisfaction, and health status to assess wellbeing, but that these were not all tested in

one multivariate analysis [48]. They used illnesses (i.e. acute and chronic) to measure health.

Concurrently, it was revealed that acute illnesses were not correlated with wellbeing but there

was a statistical correlation between chronic illness and wellbeing. Using wellbeing and life

satisfaction as dependent variable, they found that illnesses were not correlated with the

dependent variable. In a non-Caribbean clinical gerontology study, the researchers found that

neither self-rated health nor illness (i.e. chronic, neurological or surgical) was correlated with

physical action on fear of falling [49]. There are also studies on happiness and health status [50].

However in Jamaica 2007 was the first time in 2 decades (1988-2008) that the Planning Institute

and the Statistical Institute began collection data on health status and health conditions. In

previous years, they collected data on illnesses, but is health and illness wide enough concept

that measure wellbeing. The current study aims to fill the gap in the literature by examining three

hypotheses (1) factors of life satisfaction, (2) determinants of health status, (3) variables that are

associated with happiness, in order to ascertain whether life satisfaction, health status and

happiness are equivalent concepts in Jamaica as well as the coverage of the estimates. This

research will use primary cross-sectional survey data on older men (ages 55+ years) to assess the

aforementioned issue.


Method and Measure

The study used primary cross-sectional survey data on men 55 years and older from the parish of

St. Catherine in 2007; it also generalizable to the island. The survey was submitted and approved

by the University of the West Indies Medical Faculty’s Ethics Committee. Stratified multistage

probability sampling technique was used to draw the sample (2,000 respondents). A132-item


                                                 123
questionnaire was used to collect the data. The instrument was sub-divided into general

demographic profile of the sample; past and Current Good Health Status; health-seeking

behaviour; retirement status; social and functional status.


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts

(ED) or census tracts. The parish of St. Catherine is divided into a number of constituencies

made up of a number of enumeration districts (ED). The one hundred and sixty-two (162)

enumeration districts in the parish of St. Catherine provided the sampling frame. The

enumeration districts were listed and numbered sequentially and selection of clusters was arrived

by the use of a sampling interval. Forty (40) enumeration districts (clusters) were subsequently

selected with the probability of selection being proportional to population size (Table 6.1).


       The enumeration districts in the parish of St. Catherine provided the sampling frame and

the sample size determined with the help of the Statistical Institute of Jamaica (STATIN). The

enumeration districts were listed and single-stage cluster sampling was used to select the sample.

The enumeration districts were numbered sequentially and selection of clusters was arrived at by

calculating a sampling interval. From a randomly selected starting point, forty (40) enumeration

districts (clusters) were subsequently selected with the probability of selection being proportional

to population size. It was determined that 50 older men in each enumeration district would be

interviewed yielding a sample size of 2000.


       The parish of St. Catherine had approximately 233,052 males, (preliminary census data

2001) of which 33,674 males were 55+ years. STATIN maintains maps with enumeration

districts or census tracts which included the selected EDs and access routes and had references to

the selected site of a starting point household within each ED. The starting point was determined

                                                124
by randomly selecting a household with a man 55 years and over from the list of persons in the

ED. With this information the interviewers would travel in a north-easterly or closest to north-

easterly direction beginning with the first selected household, and would conduct interview until

the requisite number of interviews for that ED was completed. (North-East was randomly

selected by STATIN as the direction of travel from the starting point).

       Where the selected household was found to be subsequently devoid of an older man (due

to out-migration or death), an adjacent household was canvassed. Where households had a man

55+ years as a resident and he was not at home a call-back form was left indicating a proposed

time that the interviewer would return which would not be longer than two days after the initial

visit. In households where there was more than one man 55 years old and over, then all were

included in the survey.

       The sample population does not only speak to the parish of St. Catherine, it is

generalizable to the island of Jamaica. The sampling frame was men fifty-five years and older in

the parish of St Catherine. The parish of St. Catherine was chosen as previous data and surveys

[13, 17, 27] suggest that it has the mix of demographic characteristics (urban, rural and age-

composition) which typify Jamaica.

Measures


Happiness. This is measured based on people’s self-report on their happiness. It is a Likert scale

question, which ranges from always to rarely happy.

Current Health Status. This variable is measured using people’s self-rate of their overall health

status, which ranges from excellent to poor health status. The question was ‘How would you rate

your health today?’ (1) Excellent; (2) Good; (3) Fair and (4) Poor.



                                               125
Life satisfaction is a Likert scale variable which is measured from ‘Generally, are you satisfied

with your life?’ The options were (1) rarely, (2) sometimes, (3) most times, and (4) always.

Social network is self-reported involvement in church; civic organization; social clubs; or

community groups. This is a binary variable, where 1=social network, 0=otherwise.



Education. What is [your] highest level of [education] attained? The options were (1) no formal

education; (2) basic school; (3) primary school/all age; (4) secondary/high/technical school; (5)

vocational (ie apprenticeship/trade); (6) diploma; (7) undergraduate degree; (8) post-graduate

degree.



          Performance of Activities of Daily Living (ADL) is used to describe the functional status

of a person. It is used to determine a baseline level of functioning and to monitor improvement

in activities of daily living (ADL) overtime [51, 52].          Scoring the ADL findings (Katz)

Independence on a given function received a score of 1 point while if dependent, 0 point was

given. There were 6 items (“eating” refers to feeding oneself; “dressing” denotes getting clothes

and getting dressed, including typing shoes; “transferring” means to get in and out of bed as well

as in and out of a chair; “using toilet” refers to going to the toilet and cleaning afterwards;

“bathing” denotes to sponge bath, shower, tub bath, or washing body with a wet towel;

“continence” denotes to control of urination and bowel movement). The reliability of the items

was high, as Cronbach alpha was 0.696. Total scores thus could range from 0 to 6 with lower

scores indicating low independence (ie. high dependence) and larger scores indicating higher

independence. If there was a score of 0 to 2 (ie none to 2 of the six ADL activities was chosen),

the older person was classified as low independence; if 3 to 4 of the activities were selected, the

                                                126
older man was classified as moderately independent and if 5 to 6 items were selected the older

was classified as highly independent.

       Instrumental Activities of Daily Living IADL. The Instrumental Activities of Daily

Living tool [53] was the basis for assessing participants’ difficulty with IADL. IADL are those

activities whose accomplishment is necessary for continued independent residence in the

community. The independent activities of daily living are more sensitive to subtle functional

deficiencies than ADL’s and differentiate among task performance including the amount of help

needed to accomplish each task. Hence, IADL for older men in this study used the 8-item

choices as is used for women. These are preparing meals; shopping; management medication;

money management; transportation; telephone and laundry. Scoring the IADL. IADL scores

reflect the number of areas of impairment i.e. the number of skills/domains in which subjects are

dependent. The data were coded as 1 if fully independent to 4 if lowly independent. Scores range

from 0 to 8, with higher scores indicating higher dependence and lower scores greater

independence (ie low dependence). If none to 3 activities were selected, the older person was

classified as high dependence; if 4 to 6 activities were selected the elder was classified as

moderately dependent and if 7 to 8 items were selected the elder was classified as highly

dependent. The Cronbach alpha for the 8 item scales was 0.648.The classification outlined below

(as developed based on Katz [51] and Katz et al [52]) was used to further describe the functional

status of men with regard to ADL.

Statistical Analyses

Data were stored, retrieved and analysed using SPSS for Window version 15.0 (SPSS Inc;

Chicago, IL, USA). For the current study descriptive statistics (frequency, percentages) were

employed to provide background information on the sample; and chi-square was used to examine

                                              127
non-metric variables. Logistic regression was used to examine a binary dependent variable (ie

physical exercise) and some socio-demographic variables (such as employment status, current

health status, and health status in childhood, number of bother and/or sister (s) alive). Level of

significance was p<0.05 and the only exclusion criteria was if more than 20% of the cases of a

variable were missing. Using Cohen and Holliday [54] correlation coefficients – low, < 0, 4,

moderate, 0.5-0.69; high, 0.7 – 1.0 - were used in the present study to exclude (or allow) a

variable. Where collinearity existed (strong correlation), variables were entered independently

into the model to determine which one should be retained during the final model construction.

This was used to ascertain the variables’ contribution to the predictive power of the model and

the goodness of fit [55]. To derive accurate tests of statistical significance, the researcher used

SUDDAN statistical software (Research Triangle Institute, Research Triangle Park, NC), and

this adjusted for the survey’s complex sampling design.

Model


In order to examine the effect of many variables on a single dependent variable, the researcher

used multivariate analysis to test a single model. Using the literature the current study

investigates the correlates of social networking of older Jamaicans within the context of the

available data. The proposed model that this research seeks to evaluate is displayed (Eqn1):


HAPPi = ƒ(,Hti,LSi , ,ARi , Ai, EDi, MSi , Pi , HHi, ADL, IADL, εi)..........................................[1]


LSi = ƒ(,Hti SNi , HAPPi , ,ARi , Ai, EDi , MSi , Pi , HHi , ADL, IADL, εi)...............................[2]


Hti = ƒ(HAPPi ,LSi , ,ARi , Ai, EDi , MSi , Pi , HHi, ADL, IADL, εi)..........................................[3]




                                                         128
Where happiness of person i, HAPPi; current health status of person i, Ht; life satisfaction of

person i, LSi; area of residence of person i, ARi; age group of respondent i, Ai; educational level

of person i, EDi; marital status of person i, MSi; number of person in household of person i, Pi;

head of household of person i, HHi , ADL, IADL and an error term of person i, εi.


Results: Demographic Characteristic


Of the sampled respondents (n=2,000), 74.2% indicated that they had good health in their

childhood; 74.4% reported good current health status; 51.0% lived in rural areas; 3.5% were

mostly satisfied with life; 10.4% had moderate to high functional dependence; 89.6% had low

functional dependence (ie independence); 21.9% were ages 75 years and older; 35.6% were ages

645 to 74 years and 42.6% reported ages 55 to 64 years. In addition, 94.1% had high cognitive

functionality, 43.1% reported that they were depressed, 67.3% reported that they do some kind of

physical exercise and 24.0% indicated being rarely happy, 4.5% mentioned that they were happy

most time and 71.5% claimed occasional happiness.

       One half of the sample indicated that they spent Ja.$100 (USD1.45) monthly for medical

expenditure; 34% of the respondents bought their prescribed medication; 17.1% reported that

they have been hospitalized since their sixth birthday and 65.8% reported that they took no

medication. Of those who mentioned that they were ill during childhood (17.5%, n=350), 34.9%

said that the illness was measles or chicken pox, 26.3% mentioned asthma, 10.0% pneumonic

fever, 8.9% polio, 6.6% accident, 4.6% jaundice, 1.7% hernia, and 5.1% indicated

gastroenteritis. Twenty four percent of elderly men indicated that they were rarely happy, 40.5%

said sometimes, 31.0% mentioned often and only 4.5% reported always. Furthermore, 17.7% of

the sample reported that they were seriously ill in their children.

                                                 129
Multivariate analyses

Table 6.2 presents information on determinants of happiness. Of the 10 variables that were tested

in the model, only one was correlated with happiness – life satisfaction - Pseudo r-squared =

0.311, -2LL = 810.36, Model χ2 = 161.60, P < 0.0001. Furthermore, the model was a good fit for

the data - χ2 = 767.67, P < 0.0001.



Table 6.3 shows information that was tested which examined life satisfaction and some

variables. Happiness was the only determinant of life satisfaction of 10 variables that were

tested in the model - Pseudo r-squared = 0.321, -2LL = 1069.30, Model χ2 = 178.53, P < 0.0001.

The model was a good fit for the data - χ2 = 2294.26, P < 0.0001.



Table 6.4 highlights information that examined possible determinants of health status. Four

social determined emerged as correlated with health status - Pseudo r-squared = 0.313, -2LL =

810.36, Model χ2 = 161.60, P < 0.0001. The model was found to be a good fit for the data - χ2 =

767.67, P < 0.0001. The determinants of the model were age, income, education and area of

residence.


Limitation of study

The sample used for the current research is older men and cannot be used to represent males,

older females, females or Jamaicans.




                                              130
Discussion

The current study revealed that older men in Jamaica perceived health status narrower than life

satisfaction and happiness. While happiness and life satisfaction are determinants of each other,

neither of the two variables is correlated with health status. Health status is determined by social

factors such as age, income, education, and area of residence, but these were not determinants of

happiness or life satisfaction. The findings showed that happiness accounted for 32.1% of the

variability in life satisfaction, and that life satisfaction accounted for 31.1% of the variance in

happiness of older men, suggesting that more than 30% of respondents’ happiness or life

satisfaction can be explained by either life satisfaction or happiness. The disparity between the

aforementioned figures indicated that happiness is a strong predictor of life satisfaction that is

life satisfaction of happiness of older men. The study also indicated that the more older men are

happier, the more likely that they are satisfied with life and vice versa.

       The present research highlighted the dominance of illness in men’s perception of health

and there health status is synonymous with illness and not the borrower concept with which the

term denotes in the literature. In a study by Ross and Mirowsky [56] measured health as

“...physical functioning and perceived health. Physical functioning assesses physical mobility

and functioning in daily activities” which emphasises the biological conditions (or the biological

model) and not the intended broad concept of health that WHO offered in 1948. This extends

even to the Caribbean as Hambleton et al’s work [47] found that 88% of the variability in health

status of elderly Barbadians was accounted for by illness. From the empirical findings, it can be

extrapolated that illness are health status are synonymous concepts and that is limited to older

men. In a study of oldest-old (ie. Ages 85+ years) in China, Liu and Zhang [57] defined from the

Likert scale connotation of good-to-very poor health, which denotes that the respondents would

                                                 131
interpret self-rated health status within the perspective of illness continuum. This can be

extrapolated from the findings as illness were strong correlated with self-rated health status and

this reinforced the issue of health being the opposite of illness and illness denotes ill-health or

poor health status, which highlights the dominance of ill-health in health research. In a study in

Rawalpindi and Islamabad, Pakistan, Ali and de Muynck [58] found that street boys sought

health care when illnesses are severe, and this speaks to their perception of health. Health is on

the extreme of the illness pendulum, and that it is not conceptualised as broader that illness. If

follows that illness is synonymous with ill-health which appears to be constant across the globe.

       If health is to be in keeping with broader conceptual framework written in the Preamble

to the Constitution of WHO, then could life satisfaction or happiness be used measure this

construct. The WHO used wellbeing in defining health, which is well-being – more that not

having an illness. The literature showed that health is associated with happiness, but this is not

the case for older men in Jamaica. Diener [36] noted that research had found that there was not a

substantial correlation between happiness and health, but what the current research revealed is

that not experiencing illness is not associated with happiness or life satisfaction. The present

results even more refuted a study which found a strong correlation between health status and

happiness (r = 0.85) [58]. Older men’s happiness or life satisfaction extends to their quality of

life experiences which include aspirations, self-esteem, optimism job satisfaction, desires, virtue

and/or holiness. It is for those reasons why ADL and IADL are not correlated with happiness and

life satisfaction as old age of itself is an attainment for many people and this mean that others

things now becomes important and not merely working, walking, seeing or ill-health.

       The dominance of illness in conceptualising health is such that wellbeing should be the

new thrust. This could be measure by way of happiness or life satisfaction and not use health as

                                               132
this goes back to the illness or health conditions and not the intended broader concept with which

the WHO outlined in the Preamble to its Constitution. Happiness is the degree to which people

judge their overall quality of life as favourable [34, 60, 61]. According to Konow and Earley

[62], happiness was correlated with unemployment, positive and negative life-events, social

networks and intimate friendships. The current study on older men therefore from within the

context of the literature provides the explanation why happiness was strongly correlated with life

satisfaction as both subjective indexes are broader than health status and incorporate many aspect

of life. Hence, the finding that very happy older men are highly likely to be very satisfied with

life and vice versa suggests that heart disease, hypertension, digestive disorders and headaches

are temporal and as such in assess ones quality of life, they are lowly value and do not contribute

to this overall measure of wellbeing.



Conclusion

Self-rated (or self-assessed, self-evaluated, self-reported) health which is referred to as health

status is a narrow concept in measuring health with the broad ambit of the WHO’s definition of

health. The current study refuted the empirical finding that self-reported happiness depends on

perceived health status for older men in Jamaica. This paper highlight the critical fact that the

intervention and prevention programmes can be tailored to fit one nation based on the finding of

another political locality. The determinants of happiness such as income and social factors as

were found in the literature were not factors of happiness or life satisfaction of older men in

Jamaica, which underlines the fact that the social factors can create differential between nation

and within nations in measuring a particular phenomenon. Just like how cultures differ, people’s

perception also differs and this justifies why public health should rely on research findings

                                               133
within the geographically defined space with which it intends to apply the intervention

campaign. Life satisfaction and happiness are broader construct than health status to measure

quality of life for older men in Jamaica. Inspite of the limitation the current study highlights the

need for further research on the population in order to establish how health data should be

collected in the future as happiness and life satisfaction appears to be more comprehensive a

subjective index in assessing wellbeing than health status. Despite the limitation, health is a

comprehensive concept, and so it is imperative that longitudinal studies be carried out to

establish whether socioeconomic characteristics such as income, marital status, employment,

education and others are parameters of happiness, and life satisfaction of Jamaican as well as if

the findings of the current study are potent to the population as this should provide a new

paradigm in the assessment of health.




                                                134
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Table 6.1: Proportion of Survey (Sample) vs. Proportion of Population
 Age                           2001 Census (St.            2001 Census
              Survey
Group                             Catherine)                (Jamaica)

 (yrs).     n       %         n             %          N            %

 55-59     469    23.45      6577          26.7      38645        23.9

 60-64     413     20.6      5179          21.1      31828        19.7

 65-69     374     18.7      4391          17.8      28901        17.9

 70-74     345     17.2      3594          14.6      24856        15.4

 75-79     189     9.45      2402          9.78      17711        11.0

  80+      210     10.5      2399          9.77      19552        12.1




                                     139
Table 6.2. Parameter estimates of happiness of older men in Jamaica


                                                     Std.
                                          Estimate   Error            CI (95%)
              Variable                                            P
Rarely happy                                -4.376   1.002    0.000   -6.339, -2.412
Sometimes happy                             -2.148   0.991    0.030     -4.091, -.205
Most times happy                             0.669   0.981    0.495    -1.254, 2.591
Age                                         -0.183   0.128    0.151    -0.433, 0.067
Income                                       0.030   0.077    0.694    -0.120, 0.181
                                             0.103   0.117    0.380   -0.127, 0.332
ADL

IADL                                        -0.079   0.048    0.101   -0.173, 0.015
Head of household                           -0.089   0.124    0.474   -0.331, 0.154
 No of people in household                  -0.008   0.044    0.860   -0.094, 0.078
Tertiary education =1                        0.131   0.098    0.184   -0.062, 0.324
Single                                      -0.064   0.417    0.877   -0.881, 0.752
Married                                     -0.030   0.411    0.943   -0.836, 0.777
Separated                                    0.414   0.539    0.442   -0.642, 1.470
Common-law                                   0.530   0.502    0.291   -0.454, 1.513
Widowed                                          0
 Urban                                       0.125   0.173    0.472   -0.215, 0.464
Rural                                            0
Life Satisfaction rarely=1                  -3.854   0.481    0.000   -4.797, -2.911
Life Satisfaction sometimes =2              -2.800   0.473    0.000   -3.727, -1.873
Life Satisfaction most times =3             -1.193   0.463    0.010    -2.100, -.287
Life satisfaction always = 4                     0
Excellent health status                     -0.251   0.288    0.384   -0.816, 0.314
Good health status                          -0.230   0.248    0.353   -0.716, 0.255
Fair health status                               0

Pseudo r-squared = 0.311
-2LL = 810.36
Model χ2 = 161.60, P < 0.0001
Goodness of fit χ2 = 767.67, P < 0.0001




                                               140
Table 6.3. Parameter estimates of life satisfaction of older men in Jamaica

                                                               Std.           P   CI (95%)
                    Variable                      Estimate     Error
Life Satisfaction rarely=1                          -3.157      1.021     0.002   -5.159, -1.156
Life Satisfaction sometimes =2                      -1.481      1.018     0.146    -3.477, 0.515
Life Satisfaction most times =3                      1.428      1.002     0.154    -0.536, 3.393
Age                                                  0.002      0.130     0.990    -0.253, 0.256
Income                                               0.034      0.078     0.662    -0.119, 0.188
ADL                                                 -0.006      0.118     0.957    -0.237, 0.225
IADL                                                -0.019      0.049     0.703    -0.115, 0.078

Head of household                                    -0.037      0.126    0.766   -0.284, 0.209
No of people in household                             0.007      0.044    0.879   -0.080, 0.094
Tertiary education =1                                 0.131      0.098    0.184   -0.062, 0.324
Single                                                0.753      0.441    0.088   -0.111, 1.616
Married                                               0.763      0.436    0.080   -0.092, 1.618
Separated                                             0.694      0.553    0.209   -0.389, 1.777
Common-law                                            0.825      0.525    0.116   -0.204, 1.853
Widowed                                                   0
Urban                                                -0.122      0.176    0.488   -0.466, 0.222
Rural                                                     0
Rarely happy                                         -5.012      0.500    0.000   -5.993, -4.032
Sometimes happy                                      -3.075      0.463    0.000   -3.983, -2.167
Most times happy                                     -2.078      0.460    0.000   -2.979, -1.177
Always happy                                              0
Excellent health status                               0.317      0.290    0.275   -0.252, 0.886
Good health status                                    0.209      0.251    0.405   -0.283, 0.700
Fair health status                                        0

Pseudo r-squared = 0.321
-2LL = 1069.30
Model χ2 = 178.53, P < 0.0001
Goodness of fit χ2 = 2294.26, P < 0.0001




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Table 6.4. Parameter estimates of health status of older men

                                                               Std.       P     CI (95%)
             Variable                             Estimate     Error
Excellent health status                              0.409      0.996   0.681   -1.543, 2.361
Good health status                                   3.371      1.011   0.001    1.389, 5.354
Age                                                  0.287      0.131   0.029    0.030, 0.544
Income                                               0.685      0.080   0.000    0.528, 0.842
ADL                                                 -0.006      0.121   0.963   -0.243, 0.231
IADL                                                -0.049      0.050   0.332   -0.148, 0.050
Head of household                                   -0.054      0.128   0.675   -0.304, 0.197

 No of people in household                           0.017      0.045   0.710    -0.072, 0.106
 Tertiary education =1                              -0.733      0.107   0.000   -0.942, -0.525
  Single                                            -0.302      0.438   0.490    -1.160, 0.556
 Married                                            -0.455      0.433   0.293    -1.304, 0.393
 Separated                                           0.107      0.563   0.849    -0.996, 1.210
 Common-law                                         -0.591      0.525   0.260    -1.621, 0.438
 Widowed                                                 0
 Urban                                               0.407      0.180   0.023    0.055, 0.759
 Rural                                                   0
 Rarely happy                                       -0.173      0.505   0.732   -1.163, 0.817
 Sometimes happy                                     0.130      0.491   0.791   -0.832, 1.092
 Most times happy                                    0.151      0.501   0.763   -0.831, 1.133
 Always happy                                            0
 Life Satisfaction rarely=1                          0.182      0.515   0.724   -0.827, 1.191
 Life Satisfaction sometimes =2                      0.196      0.519   0.705   -0.822, 1.214
 Life Satisfaction most times =3                    -0.238      0.525   0.651   -1.268, 0.792
 Life Satisfaction always=4                              0
Pseudo r-squared = 0.313
-2LL = 810.36
Model χ2 = 161.60, P < 0.0001
Goodness of fit χ2 = 767.67, P < 0.0001




                                              142
                                                                             Chapter 7

Cognitive functionality of older men in St. Catherine, Jamaica



Paul A. Bourne, Christopher A.D. Charles, Stan Warren, Chloe Morris,
Denise Eldemire-Shearer




The scientific literature is replete with factors that influence the cognitive functionality of older
men but no such study has been done in Jamaica. In this study we report our findings on the
cognitive functionality of three cohorts of older men in a rural area. This is the first data
published on the cognitive functionality of older men from Jamaica. The investigation was
carried out with the administration of a 132- item questionnaire. The measure includes items on
demographics, retirement and health status, the seeking and avoidance of medical care, health
treatment, medication use, childhood illness, happiness and the mini-mental status examination.
The measure was given to 2,000 men 55 years and older who were randomly selected from St.
Catherine. The multivariate analysis of the model revealed three significant determinants of
cognitive functionality: Age (OR = 0.346, 95% CI = 0.206, 0.582), social support (OR = 0.683,
95% CI = 0.443, 1.053) and having children (OR = 2.42, 95% CI = 1.130, 5.183). There is a
negative relationship between age and cognitive functionality and a positive relationship between
having children and cognitive functionality. Our main conclusions are that the two significant
determinants of cognitive functionality of older men (age and having children) in Jamaica are
unique given the many determinants of cognitive functioning cited in the scientific literature. The
plethora of factors points to the need for further research to understand the range of factors that
influence the cognitive functionality of older Jamaicans.



Introduction


The cognitive functioning of older men is an under-researched area in Jamaica. It is important to

understand the cognitive functioning of these men as they progress into later life because


                                                143
declining cognitive functions affect their quality of life and their ability to care for themselves.

[1-18] There are many inter-related factors that affect the cognitive functioning of older men.

One such set of factors is genes. Genetic factors in twin pairs of older men accounted for 30 % of

the variance in cognitive scores while shared environmental effects accounted for 16-29% of the

variance. [1] Therefore, the complexity of the environment is an important factor that should be

taken into account with genetic factors. [2] It is important to note that hormones do not mediate

the cognition-age relationship, because when salient factors are considered the direct effects of

hormones on cognition are not significant. [3] Also, older men with higher free testosterone

levels may be able to achieve and sustain visuo-spatial processing speed and visuo-spatial ability

possibly at the expense of some inhibitory functioning. [4]


       Older men, as compared to younger men, showed impaired executive functions,

declarative verbal memory, attention working memory and psychomotor speed. There is a

nonlinear relationship between executive function and age and a linear relationship between age

and verbal memory. These relationships mean that age selectively impacts executive functions.

Increasing age is not necessarily the most influential determinant in cognitive performance,

because the level of education and positive and negative affect are also important determinants.

[5-6] There is a significant association between depression and memory, psychomotor speed and

cognitive mental status. Psychological wellbeing was the most robust determinant of cognitive

function. These findings suggest that there may be a link between the maintenance of cognitive

function and positive affect [7] Personality, like affect, is also relevant because these are

attributes that continue to evolve from middle to old age. Negative and positive affect fluctuates

over time, unlike locus of control which remains stable. There are inverse relationships between



                                                144
external locus of control and cognitive functioning, and an absence of positive affect and

enduring negative affect. [8]


       Other important factors play a role, such as chronic insomnia which is an independent

determinant of incident cognitive decline in older men. [9] Older men who had instrumental self

efficacy beliefs performed better on memory and abstraction tests than a similar cohort of

women. Also, depression and optimism are independent determinants of the men’s functional

status. [10-11] As mentioned earlier, level of education is an important factor in cognitive

functioning because men with a higher level of education performed better on cognitive tasks

than men with a lower level of education. Men also performed worse on verbal memory

compared to women. Therefore, education and gender are important factors in older adults’

cognitive performance. [12] Marital status and living situation also influence cognitive functions

because older men who were unmarried, lost a partner or lived alone had greater cognitive

decline compared to men who were married, just started living with a partner or lived with a

partner. [13]


       Older men who continued working after retirement were healthy and psychologically

committed to work and therefore had a dislike for retirement. There was a positive relationship

between the probability of continued employment and level of education and being married to a

wife who was working. Continued employment was negatively correlated with age and one’s

level of income without a job. [14] The complexity of a medication regimen and the direct

effects of cognition were significant determinants of the capacity of older adults to manage their

use of medication. [15] The parental status of older men influences their subjective wellbeing in

terms of happiness, satisfaction with life and depression. There were significant differences in


                                               145
subjective wellbeing between those who were distant parents and those who were close to their

children, and between those who were childless by circumstances and those who were close to

their children. [16] The social supports older men receive also influence their cognitive

functioning. Among this cohort, the relationship between social support and cognition is

determined by their early childhood experiences which continue into late adulthood. [17]

Geographical location is also important because older men in rural areas were more concerned

about their physical health, rated their health worse, stated that they had more impairment and

had a negative outlook on life compared to older men in urban areas. [18]


       The aim of this research article is to understand the cognitive functionality of a cohort of

older men in St. Catherine, Jamaica, and how this cognitive functioning affects their lives.

Cognitive decline affects the personal autonomy of older men, their quality of life and their

ability to care for themselves at this critical stage of the life course. We now turn to the method

and measures we used.


Method and Measures



The study used primary cross-sectional survey data on men 55 years and older from the parish of

St. Catherine in 2007 (Figures 7.1 and 7.2). The survey was submitted and approved by the

University of the West Indies Medical Faculty’s Ethics Committee. Stratified multistage

probability sampling technique was used to draw the sample (2,000 respondents). A 132-item

questionnaire was used to collect the data. The instrument was sub-divided into general

demographic profile of the sample; past and current health status, health-seeking behaviour,




                                               146
retirement status, social and functional status. The overall response rate for the survey was 99%

(n=1,983). Data were stored, retrieved and analyzed, using SPSS for Windows, version 16.0.


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts

(ED) or census tracts. The parish of St. Catherine was chosen as previous data and surveys by

STATIN suggest that it has a mix of demographic characteristics (urban, rural and age-

composition) which is similar to Jamaica. The parish of St. Catherine is divided into a number

of electoral constituencies made up of a number of enumeration districts (ED). The one hundred

and sixty-two (162) enumeration districts in the parish of St. Catherine provided the sampling

frame. The enumeration districts were listed and numbered sequentially and selection of clusters

was arrived at by the use of a sampling interval. Forty (40) enumeration districts (clusters) were

subsequently selected with the probability of selection being proportional to population size.

Advised by the Statistical Institute of Jamaica (STATIN) and utilizing the C-Survey computer

software, it was determined that 50 older men in each enumeration district would be interviewed

yielding a sample size of 2,000.

       The enumeration districts in the parish of St. Catherine provided the sampling frame and

the sample size was determined with the help of the Statistical Institute of Jamaica (STATIN).

The enumeration districts were listed and single-stage cluster sampling was used to select the

sample. The enumeration districts were numbered sequentially and selection of clusters was

arrived at by calculating a sampling interval. From a randomly selected starting point, forty (40)

enumeration districts (clusters) were subsequently selected with the probability of selection

being proportional to population size.




                                               147
       The parish of St. Catherine had approximately 233,052 males, (preliminary census data

2001) of which number 33,674 males were 55+ years [Table 7.1]. STATIN maintains maps with

enumeration districts or census tracts which include the selected EDs and access routes and have

references to the selected site of a starting point household within each ED. The starting point

was determined by randomly selecting a household with a man 55 years and over from the list of

persons in the ED. The requisite number of interviews for each ED was completed.

       Where the selected household was found to be subsequently devoid of an older man (due

to out-migration or death), an adjacent household was canvassed. Where households had a man

55+ years as a resident and he was not at home, the interviewer would return within two days. In

households where there was more than one man 55 years old and over, then all were included in

the survey.

       For the current study descriptive status was employed to provide background information

on the sample, and chi-square was used to examine non-metric variables. A p-value less than 5%

(2-tailed) was used to indicate statistical significance, and there were two exclusion criteria. One,

in the event a variable has more than 20% of the cases cases missing; and two, collinearity. In

addressing collinearity (r > 0.6) the aim was to independently enter variables in the model to

determine which one should be retained during the final model construction. To retain or exclude

a variable from the model, this was based on the variables’ contribution to the predictive power

of the model and its goodness of fit.

Measure


Several questions were used to measure the health literacy variable. These questions dealt with

health treatment, involvement in physical exercise, retirement plan for health care, taking of

medication, knowledge of the prescribed medication, factors responsible for health status,

                                                148
meaning of good health status, medical care seeking behaviour, avoidance of medical

complications, reasons for not seeking medical care, length of time before seeking medical care,

reason for mother’s death and smoking behaviour. Health communication constitutes a number

of different questions on particular health issues. These include (1) were you diagnosed with an

illness; (2) do you understand the explanations of doctors, nurses, community health aides,

pharmacists; (3) were you advised on smoking, physical exercise, diet, prostate cancer; (4) when

were you diagnosed with the ailment - 1-6 months, 7 – 12 months, 2-5 years, 6-10 years, 11-20

years, 21-30 years, or 30+ years ago. Happiness: This is measured based on people’s self-report

on their happiness. It is a Likert scale question, which ranges from always to rarely happy.

Health Status: This variable is measured using people’s self-rate of their overall health status,

which ranges from excellent to poor health status. The question was ‘How would you rate your

health today?’ (1) Excellent; (2) Good; (3) Fair and (4) Poor. Education: What is [your] highest

level of [education] attained? The options were (1) no formal education; (2) basic school; (3)

primary    school/all   age;   (4)   secondary/high/technical    school;    (5)   vocational   (i.e.

apprenticeship/trade); (6) diploma; (7) undergraduate degree; (8) post-graduate degree. Physical

Exercise: ‘Do you take time out for regular exercise?’ (1) yes and (2) no. Type of physical

exercise: ‘What do you do in terms of exercise?’ Childhood illness: ‘Were you seriously ill as [a]

child? (1) yes, (2) no. And, were you frequently ill as a child? (1) yes, (2) no. If the response to

either question was yes, this was coded as poor childhood health status and if the response was

no in both cases it was coded a good health status in childhood. Age group is a categorized into

three sub-groups. These are (1) ages 55 to 64 years; (2) ages 65 to 74 years; and (3) ages 75

years and older (i.e. 75+ years).




                                                149
Mini- Mental Status Examination (MMSE)


The MMSE, which is a promising tool in the early detection of Alzheimer’s disease, was used to

assess the cognitive functional status of older men. A modified version of the MMSE was used

in this study to reflect the Jamaican situation. For example, the item on national independence

was changed to the date of the Queen’s Birthday. The domains of primary interest that were

measured were: orientation to time and the domain of registration of three words. One point was

assigned to each right answer and zero for each wrong answer (see Appendix One). This was a

7-item scale, with the reliability of the items being moderately high, α = 0.620. The MMSE

Index ranges from 0 to 7, where higher scores indicate greater cognitive functional status of the

older person. Cohen and Holliday stated that correlation can be low/weak (0–0.39); moderate

(0.4–0.69), or strong (0.7–1) [19]. Hence, low cognitive functionality ranges from 0 to 2.7;

moderate cognitive functionality is from 2.8 to 4.8 and high cognitive functionality ranges from

4.9 to 7 1.


Model


In order to examine the effect of many variables on a single dependent variable, the researcher

used multivariate analysis to test a single model. The current study investigates the correlates of

ADL of older Jamaicans within the context of the available data. The proposed model that this

research seeks to evaluate is displayed (Eqn1):


MMSEi = ƒ(Hti ,HAPPi ,LSi ,Ci ,ARi , Ai, SSi , CAi , EDi , HHi , MSi , Pi , HAi , EMi , Di , TM; AMi, εi) ........................[1]



          Where MMSEi (or cognitive functionality) is a function of some current health status, Ht;

happiness, HAPPi; life satisfaction, LSi; have children, Ci; area of residence, ARi; age group of

                                                                150
respondent, Ai; social support, SSi; church attendance, CAi; educational level, EDi; head of

household, HHi; marital status, MSi; number of persons in household, Pi; health status in

childhood, HAi; employment status, EMi; depression, Di; taking medication, TMi; health advise,

HAi.


       All the variables were identified from the literature. Using the principle of parsimony,

only those explanatory variables that are statistically significant (p <0.05) were used in the final

model to determine MMSE (i.e. cognitive functionality) of older men in Jamaica. This final

model identified the correlates of MMSE of older men in Jamaica (Eqn2).


       MMSEi = f(Ai, Ci, SSi εi)……………………….........................................................[2]


Statistical Analysis


The predictive power of the model was tested using the ‘omnibus test of model’ and Hosmer and

Lemeshow’s technique was used to examine the model’s goodness of fit. The correlation matrix

was examined in order to ascertain whether autocorrelation (or multi-collinearity) existed

between variables. As noted earlier, correlation can be low/weak (0–0.39); moderate (0.4–0.69),

or strong (0.7–1) [19]. This was used in the present study to exclude (or allow) a variable.

Finally, Wald statistics were used to determine the magnitude (or contribution) of each

statistically significant variable in comparison with the others, and the odds ratio (OR) for

interpreting each of the significant variables. We present the descriptive results next.




                                                 151
Results: Demographic Characteristics of Sample



Of the sample of respondents (n = 2,000), the majority had high cognitive functionality (94.1%);

good health status (55.4%); satisfied with life (67.1%); good health status in childhood (82.5%);

retired (53.9%); and 83.3% had primary or elementary level education (see Table 7.2). Fifty one

percent lived in rural villages and the remainder in rural towns; 59.1% had some form of social

networking; 42.6% were aged 55 to 64 years and 44.7% were married, while 34.3% were single

(including common-law).


         One half of the sample indicated that they spent Ja.$100 (USD1.45) monthly for medical

expenditure; 34% of the respondents bought their prescribed medication; 17.1% reported that

they had been hospitalized since their sixth birthday and 65.8% reported that they took no

medication. Of those who mentioned that they were ill during childhood (17.5%, n = 350),

34.9% said that the illness was measles or chicken pox, 26.3% mentioned asthma, 10.0%

pneumonic fever, 8.9% polio, 6.6% accident, 4.6% jaundice, 1.7% hernia, and 5.1% indicated

gastroenteritis. Twenty four percent of elderly men indicated that they were rarely happy, 40.5%

said sometimes, 31.0% mentioned often and only 4.5% reported always. Furthermore, 17.7% of

the sample reported that they were seriously ill as children. We report the rest of the results

below.


Results of Multivariate Analysis



The model [Eqn. (2)] is a good predictive one of cognitive functionality of older men in Jamaica

(Hosmer and Lemeshow goodness of fit χ2=3.996, P = 0.858).              On examination of the



                                              152
classification, 94.3% of the data were correctly classified: Correct classification of cases of low

to moderate cognitive functionality = 90.0%, and correct classification of cases of high

functionality = 100.0% (N = 1768) (Table 7.3). There was no multi-collinearity among variables

because the correlation matrix had correlations of less than 0.6. The correlation between

depression and life satisfaction (r = 0.131); depression and social support (r = -0.101); current

health status and health status in childhood (r = 0.128); elderly (ages 75 years and older) and

employment status (r = 0.183), elderly (ages 75 years and older) and married (r = 0.161).


       Three factors can be used to predict the cognitive functionality of elderly men in Jamaica

(χ2 (17) = 40.94, P < 0.001; -2 Log likelihood = 779.63). These are age (ages 75 years and older)

(OR=0.35, 95%CI: 0.21, 0.58) with reference to elderly (ages 55 to 64 years), social support (OR

= 0.68, 95% CI = 0.44, 1.05) and having children (OR=2.42, 95%CI: 1.13, 5.18) (Table 7.3).


Discussion


Very little or no research has been done on the cognitive functionality of older men in Jamaica.

This is the first study that has addressed this important medical and psychological issue in

Jamaica. The findings reveal that the overwhelming majority of older men in our study, some

94.1% of the participants, have high cognitive functionality; at least good health status (74.4%);

are satisfied with life (67.1%) and had good health status during childhood (82.5%). Of the 14

variables identified from the literature review that were present in the current dataset, 3 emerged

as determinants of cognitive functionality of older men in St. Catherine, Jamaica – age, social

support and having children. These significant determinants of cognitive functionality in our

sample are in keeping with past research findings in the literature which give a much broader

range of factors that influence the cognitive functioning of older men.

                                               153
       The 55-64 age cohort is the youngest of the three age cohorts in our sample, the other two

being men 65-74 and 75 years and older. The finding that age is a significant determinant reveals

that there is a negative relationship between age and cognitive functionality, where as the men

get older there is a decline in their cognitive functioning. This finding corroborates some of the

research findings of Silver and colleagues and Lauren. [5-6] These authors find that older men

compared to younger men have impaired psychomotor functions, declarative verbal memory,

executive functions and attention working memory. The authors also note that age is not

necessarily the most influential determinant, because level of education among other factors is

important. Older men with a higher level of education perform better on cognitive tasks than

older men with a lower level of education. However, in our sample, level of education is not an

important factor influencing cognitive functioning, because with the majority of the participants,

some 83.3% only have elementary school education, and a small minority (1.9%) have college

education. It is possible that this difference in finding between our study and the literature may

be due to the difference in the level of socio-economic development, since the findings of the

studies reported in the literature were mostly conducted in developed countries (where there is

greater access to formal schooling) and our study was conducted in a developing country. It is

also possible that the difference in finding may be explained by the communal nature of

Jamaican culture, which offers more social support to cognitive functioning compared to the

more individualistic cultures of developed societies.


       Social support is a determinant of cognitive functionality in our sample, but the

relationship is a negative one, where as cognitive functionality increases social support

decreases. The relationship between social support and cognitive functionality is not in the

expected direction. This counterintuitive finding suggests that older men in St. Catherine who

                                               154
have high cognitive functionality receive less social support because they do not really need it.

The men who really need and receive the social support are those men who are experiencing

cognitive decline. This unexpected finding still underscores the importance of social support in

cognitive functionality. For, as the findings by Bourne and colleagues show, social support

influences the cognition of older men. This relationship is determined by early childhood

experience which continues into the latter part of the life course. [17]


       Since the oldest cohort of men (75 years and older) have greater cognitive deficits than

the two younger cohorts (65-74 years and 55-64), it is possible that the majority of men who are

rarely satisfied with life (32.9%) are in the oldest cohort, whereas the majority of men who are

sometimes satisfied with life (63.6%) and those who are most satisfied (3.5%) are in the two

younger cohorts. There is a link between positive affect and cognitive functioning, and such

positive emotions are associated with cognitive performance and hence life satisfaction. [5-6]

Research done by Connidis and McMullin shows that the subjective wellbeing of older men,

such as their satisfaction with life and their happiness and experience with depression, are

influenced by their parental status. [16] The importance of parental status highlighted by

Connidis and McMullin corroborates the third significant determinant of cognitive functionality

in our study, which is having children. There is a positive relationship between having children

and cognitive functioning in our study, where older men with children have higher cognitive

functionality than older men without children. However, our data did not address the findings by

Connidis and McMullin, that the closeness of the relationship older men have with their children

and whether these men are childless by choice are important influences on their life satisfaction.




                                                155
       There are a couple of limitations in this research. The findings cannot be generalized to

the national cohort of older men since we conducted the research only in one parish. Also, there

is the possibility of social desirability bias in which the participants told the interviewers what

they wanted to hear to get their approval. However, this paper has contributed to the literature by

highlighting the fact that in St. Catherine, Jamaica, the cognitive functionality of older men is

only predicted by age, social support and parental status while the research literature abounds

with significant factors that influence cognitive functionality. This unique finding in Jamaica

calls for more research. As such, future researchers should look at cognitive functionality of

older Jamaicans using stratified random sampling based on level of education, gender and social

class, and not just parental status, but on the quality of the relationship these elderly parents have

with their children. It is also important to move beyond rural village versus rural towns to rural

areas versus urban areas where there are cities with large populations that offer many services.

Future researchers should also identify the kinds and amount of social network and support that

these elderly people use, and the frequency of use, rather than just recording that these elderly

Jamaicans have social networks and support.


Conclusions


The current study has found that the health status, happiness, life satisfaction and cognitive

functionality of older men in St. Catherine are relatively good, high or excellent. Generally, some

people believe that the cognitive functionality of older people is low and is the first to go with

ageing, which is clearly not the case for this sample. Organisms age naturally, which explains

biological ageing and the perception of lowered cognitive functionality. This research is not

arguing that cognitive functionality does not decline with ageing, but dispels the myth of the


                                                 156
exponential reduction that some people hold on cognitive functioning and ageing. Concurrently,

the literature shows many determinants of cognitive functionality of older people, but this study

has only found three that correlate with the cognitive functioning of this cohort. This finding

emphasises the rationale of not widely assuming that what obtains in another geo-political

jurisdiction works in or for another. The findings of only three significant determinants of

cognitive functionality in St. Catherine, Jamaica are unique because the scientific literature is

replete with factors that influence the cognitive functioning of older men.


       In summary, among the ironies of this study is the fact that depression was not correlated

with cognitive functionality. In spite of the afore-mentioned issue, older men in St. Catherine

were experiencing excellent cognitive functionality; they were happy and satisfied with life and

indicated good health status. These findings suggest that there is a need for more research on the

cognitive functionality of older persons in Jamaica, using stratified random sampling that takes

into account education, gender, the rural-urban dichotomy, social class, intimate partner

relationship status, the quality of parental relationship and the type and amount of social support

and social networks and their frequency of use.




Conflict of interest


The authors have no conflict of interest to report.




                                                157
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       cognitive decline in older men: The FINE study. The Journals of Gerontology: Series


       B: Psychological Sciences 2006; 61B (4):213-219.


14.   Parries HG, Sommers DG. Shunning retirement: Work experience of men in their


      seventies and early eighties. Journal of Gerontology 1994; 49(3): S117-S124.


15.   Maddigan SL, Farris KB, Keating N, Wiens CA, Johnson JA. Predictors of older adults'

      capacity for medication management in a self-medication program: A retrospective chart


      review. Journal of Aging and Health 2003; 15(2):332-352.


16.     Connidis IA, McMullin JA. To have or have not: Parent status and the subjective well-


         being of older men and women. The Gerontologists 1993; 33 (5): 630-636.


17.      Bourne VJ, Fox HC, Starr JM, Deary IJ, Whalley LJ. Social support in later life:


         Examining the roles of childhood and adulthood cognition. Personality and Individual


         Differences 2007; 43 (4): 937-948.



                                               160
18.   Grant EG. Health orientations of older rural and urban men. Geriatrics 1967;


      22(10):39-147


19.   Cohen L, Holliday M. Statistics for Social Sciences. London, England: Harper and Row,


      1982. In Bourne PA, McGrowder DA. Rural health in Jamaica: examining and refining


      the predictive factors of good health status of rural residents. Rural and Remote Health 9


      (online), 2009: 1116. Available from: http://www.rrh.org.au




                                             161
Figure 7.1. Map of Jamaica showing St. Catherine and other parishes




                                 162
Figure 7.2. Map of St. Catherine, Jamaica




                                       163
Table 7.1: Proportion of Survey (Sample) vs. Proportion of Population
 Age                           2001 Census (St.            2001 Census
              Survey
Group                             Catherine)                (Jamaica)

 (yrs).     n       %         n             %          N            %

 55-59     469    23.45      6577          26.7      38645        23.9

 60-64     413     20.6      5179          21.1      31828        19.7

 65-69     374     18.7      4391          17.8      28901        17.9

 70-74     345     17.2      3594          14.6      24856        15.4

 75-79     189     9.45      2402          9.78      17711        11.0

  80+      210     10.5      2399          9.77      19552        12.1




                                     164
Table 7.2: Demographic characteristics of sample
Variable                                           Frequency   Percent
Cognitive functionality
    Low                                                  19       1.0
    Moderate                                             99       5.0
    High                                               1882      94.1
Marital status
    Single                                              686      34.3
    Married                                             894      44.7
    Separated                                           112       5.6
    Common law                                          136       6.8
    Widowed                                             172       8.6
Age group
    55- 64 years                                        851      42.6
    65 – 74 years                                       712      35.6
    75 years and older                                  437      21.9
Employment status
    Employed                                            511      25.6
    Unemployed                                          412      20.6
    Retired                                            1077      53.9
Education
    No Formal Education                                 200      10.0
    Primary and basic                                  1661      83.0
    Secondary                                           102       5.1
    Tertiary                                             37       1.9
Self-rated health Status
    Excellent                                           357      19.0
    Good                                               1038      55.4
    Fair                                                480      25.6
Social networking
    Yes                                                 817      59.1
    No                                                 1183      40.9
Life satisfaction
    Rarely satisfied                                     658     32.9
    Sometimes                                          1,272     63.6
    Most                                                  70      3.5
Childhood health status
   Good                                                1650      82.5
   Poor                                                 350      17.5
Area of residence
   Rural town                                           981      49.0
   Rural village                                       1019      51.0




                                             165
Table 7.3: Logistic regression of cognitive functionality and some variables of older men in
Jamaica
                                                                  Std     Odds
 Variable                                         Coefficient    Error    Ratio     95.0% C.I.
  Dummy health advise (1=yes)                            0.034    0.214     1.04       0.68 - 1.57
  Dummy education (1=tertiary)                           0.762    0.528     2.14       0.76 - 6.03
  Dummy purchased medication                            -0.173    0.212     0.84       0.56 - 1.28
  Dummy depression (1=yes)                               0.308    0.214     1.36       0.90 - 2.07
  Dummy have children                                    0.884    0.389     2.42      1.13 - 5.18*
  Life satisfaction (1=moderate-to-excellent)            0.328    0.249     1.34       0.85 - 2.26
  Health status in childhood (1=moderate-to-
                                                        0.052    0.244      1.05       0.65 - 1.70
  excellent)
  Urban area                                           -0.271    0.205      0.76        0.51 - 1.14
  Elderly (ages 65 to 74 years)                        -0.203    0.262      0.82        0.49 - 1.37
  Elderly (ages 75 years and older)                    -1.060    0.265      0.35     0.21 - 0.58**
  †Elderly (ages 55 to 64 years)                                          1.00

   Social support                                      -0.382    0.221      0.68   0.44 - 1.05***
   Separated, divorced or widowed                       0.052    0.311      1.05       0.57 - 1.94
   Married                                              0.106    0.231      1.11       0.71 - 1.75
   Never married                                                            1.00
   Happiness (1=moderate-to-excellent)                 -0.356    0.236      0.70       0.44 - 1.11
   Household head                                      -0.404    0.337      0.67       0.35 - 1.29
   Employment status (1=employed)                       0.259    0.255      1.30       0.79 - 2.14

χ2 (17) =40.938, P < 0.001; n = 1875
-2 Log likelihood = 779.633
Hosmer and Lemeshow goodness of fit χ2=3.996, P = 0.858
Nagelkerke R2 =0.061
†Reference group
*Significance at the 99% level, **significance at 95% level and ***significance at the 90% level




                                                166
Appendix One
MENTAL STATUS EXAMINATION




Correct answer should be given a score of one (1) and incorrect answers should be given a score
of zero.



                           Questions                            0                  1

       01.        What year is this?                           [ ]1              [ ]2

       02.        What month is this?                          [ ]1              [ ]2

       03.        What day of the week is today?               [ ]1             [ ]2

       04.        How old are you?                             [ ]1              [ ]2

       05.        What is the name of the Prime                [ ]1              [ ]2
                  Minister of Jamaica?

       06.        What year was Independence?                  [ ]1              [ ]2



               There are three items I want you to remember; I will ask you what they were
                  later in this interview. Here are the three items, Bed, Chair, Window



       07.        Can you tell me what the three items are?



       Items      Bed 1 [ ] 2 [ ] Chair 1 [ ] 2[ ]            Window 1 [ ]             2[ ]

                              TOTAL




                                               167
168
                                                                                   Chapter 8

Happiness among Older Men in Jamaica: Is it a health issue?




Paul Andrew Bourne, Chloe Morris, Denise Eldemire-Shearer

This study seeks to expand the literature by investigating the effect of health status on happiness,
happiness on health status, life satisfaction on happiness as well as some demographic variables
in order test the existing knowledge on elderly men (ages 60 years and older) in Jamaica. A
stratified random sample of 2,000 elderly men in Jamaica was used to carry out this study. The
data were collected with a 137-item self-administered questionnaire, and entered, retrieved and
stored in SPSS for Windows 16.0 (SPSS Inc; Chicago IL, USA). Happiness was found not to be
correlated with health status of elderly men in Jamaica nor was health status associated with
happiness; and that there was no difference based on area of residence. Happiness and health
status cannot be used to proxy each other for the elderly cohort as they are independent events.



Introduction



Happiness is well established in scientific publications as a good predictor of subjective

wellbeing and/or overall life satisfaction (Graham, 2008; Selim, 2008; Borghesi, & Vercelli,

2007; Mahon et al., 2005; Layard, 2006; Seligman & Csikszentmihalyi, 2000; Diener, Lucas, &

Oishi, 2002; Diener, 1984, 2000; Easterlin, 2001; Veenhoven, 1993). A group of scholars found

that the statistical association between happiness and subjective wellbeing was a strong one -

correlation coefficient r = 0.85 in the 18 OECD countries – (Kahneman, & Riis, 2005), which

emphasizes the importance that people place on happiness in assessing their subjective

wellbeing. Happiness which is an area in positive psychology (Seligman & Csikszentmihalyi,

                                                169
2000; Huppert, 2006; Brannon & Feist, 2007) goes beyond the mere positive state of an

individual to physical health and social life, and economic state to life in general (Borghesi, &

Vercelli, 2007; Lima & Nova, 2004; Stutzer & Frey, 2003; Easterlin 2003; Frey & Stutzer,

2002a, 2002b; Brickman, Coates, & Janoff-Bulman, 1978).


       Happiness is as a result of a number of positive psychological factors such as marriage, a

job, success in life, adaptation to life events, and negative affective conditions such as the lost of

life or property, failed examinations, and dissolution of union deteriorate both health and further

deepen the negative impact on life and by extension happiness (Borghesi & Vercelli, 2007;

Easterlin, 2003; Kahneman, & Riis, 2005). In seeking to unearth ‘why some people are happier’,

Lyubomirsky (2001) approached it from the perspective of positive psychology. She noted that,

to comprehend disparity in self-reported happiness between individuals, “one must understand

the cognitive and motivational process that serve to maintain, and even enhance happiness and

transient mood” (Lyubomirsky, 2001, 239)          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 (see also, Borghesi & Vercelli, 2007;

Kahneman, & Riis, 2005; Frey & Stutzer, 2002a, 2002b; Easterlin, 2003). Those findings only

concurred with an earlier work by Diener, Suh, Lucas, & Smith (1999). Diener, Horwitz &

Emmon (1985) were able to add value to the discourse when they showed that income affects

subjective wellbeing. Frey & Stutzer (2002a) provided more information on the aforementioned

discourse, when he opined that absolute income does not seem to have a strong influence on

happiness or health (or subjective wellbeing). Researchers found that the wealthy (those earning

in excess of US 10-million, annually) had a marginally greater self-reported wellbeing (personal



                                                 170
happiness) than that of those who were lower wealthy (earned less than 10 million US annually)

(Diener, Horwitz & Emmon, 1985).


       People’s cognitive responses to ordinary and extraordinary situational events in life are

associated with subjective wellbeing (Chida & Steptoe, 2008; Steptoe et al., 2008; Pressman &

Cohen, 2005; Lyubomirsky, 2001; Sheldon & Lyubomirsky 2006). It is found that happier

people are more optimistic and as such conceptualize life’s experiences in a positive manner.

Studies revealed that positive moods and emotions are associated with wellbeing (Fowler &

Christakis, 2008; Leung, Moneta, & McBride-Chang, 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, & Diener, 2005).        This situation is later internalized,

causing the individual to be self-confident from which follows a series of positive attitudes that

guide further actions (Sheldon & Lyubomirsky, 2006). Positive mood is not limited to active

responses by 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 & Lyubomirsky, 2006;

Abbe, Tkach, & Lyubomirsky, 2003). Recently conducted meta-analysis longitudinal studies

revealed that happiness and other positive moods are not only positively correlated with health

status; but that they are negatively associated with mortality Chida Y, Steptoe A. (2008),

suggesting the value of happiness to life. Happiness is not a mood that does not change with time

or situation; hence, happy people can experience negative moods (Diener & Seligman, 2002);

and happiness is a good proxy for assessing subjective wellbeing.




                                               171
       Human emotions are the coalesced 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 & Lightsey, 2005; Kashdan 2004). From Evans and colleague, Harris & Lightsey

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 concurred in a study conducted by Fromson (2006); and by

other scholars (McCullough et al. 2001; Watson and Clark et al 1988a, 1988b). Acton & Zodda

(2005) aptly summarized the negative affect 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.”


       Previously mentioned studies using happiness to examine wellbeing were on population

and not on elderly cohorts (ages 60 years and older). McConville et al. (2005) in ‘Positive and

negative mood in the elderly: the Zenith study’ established that different moods of people affect

both their physical as well as their mental well-being. They argued, “Poor quality moods were

associated with deficits in diverse areas of cognitive function, health, and social relationship”

(McConville et al., 2005). The Zenith study was to examine the quality of positive and negative

attitudes on health status. The population was 387 individuals from three European countries

(France, Italy and Ireland). Another study on the elderly population found that biological

changes of humans do affect their psychological state, and that psychological and psychosocial

changes influence biological functioning (or physical health) (Kart, 1990)


       Well-being for some scholars, therefore, is a state of happiness (ie positive feeling status


                                               172
and life satisfaction) (Diener, 1984; Easterlin, 2003; Diener, Larson, Levine & Emmon, 1999).

Simply put, well-being is subjectively what is ‘good’ for each person (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 ‘well-being’ instead of ‘happiness’ (Crisp, 2005). O’Donnell and Tait

(2003) believed that health is a primary indicator of well-being; and so provide an understanding

of the correlation between health, subjective wellbeing, happiness, and life’s satisfaction

(O’Donnell & Tait, 2003; Ringen, 1995). From the scientific literature, self-rated health status is

highly reliable to proxy for health which ‘successfully crosses cultural lines’ (Ringen 1995).

O’Donnell and Tait concluded from their study that self-reported health status can be used to

indicate wellbeing as all respondents who had chronic diseases reported very poor health.


       From the literature, happiness and health status, happiness and wellbeing, and happiness

and life satisfaction are associated. Using the scientific findings on the aforementioned issue, an

extensive review of the literature found no study that has every examined happiness and health

status of elderly men in Jamaica, which is the rationale for the current study. Given that

happiness covers life satisfaction and health, an examination of happiness and health status of

elderly men in Jamaica will provide invaluable information as to the state of this group.


       An extensive review of the literature revealed that there has never been a study done in

the Caribbean, in particularly Jamaica on happiness of this vital cohort, so this is a critical

rationale for the study as it will provide insight in this cohort along with an understanding of how

they perceive things and life which can guide public policy. Another rationale is happiness, a

predictor of health status which would allow for the collection of data on whether or not they are


                                                173
good predictors of each other. The current study examined whether (1) happiness is a function

of health status; (2) happiness is a function of health status and some demographic variables; (3)

health status is a function of happiness; (4) health status is a function of happiness and some

demographic variables in order to provide information on this cohort. Using probit analysis, this

study sought to model the aforementioned issues from data on elderly men (ages 55 years and

older) in Jamaica.


Methods

Participants and questionnaire

The study used primary cross-sectional survey data on men 55 years and older from the parish of

St. Catherine in 2007; it is also generalizable to the island. The survey was submitted and

approved by the University of the West Indies Medical Faculty’s Ethics Committee. Stratified

multistage probability sampling technique was used to draw the sample (2,000 respondents).

A132-item questionnaire was used to collect the data. The instrument was sub-divided into

general demographic profile of the sample; past and current health status; health-seeking

behaviour; retirement status; social and functional status. The overall response rate for the survey

was 99% (n=1,983). Data was stored, retrieved and analyzed, using SPSS for Windows (16.0).


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts

(ED) or census tracts. The parish of St. Catherine is divided into a number of constituencies

made up of a number of enumeration districts (ED). The one hundred and sixty-two (162)

enumeration districts in the parish of St. Catherine provided the sampling frame. The

enumeration districts were listed and numbered sequentially and selection of clusters were

arrived at by the use of a sampling interval. Forty (40) enumeration districts (clusters) were


                                                174
subsequently selected with the probability of selection being proportional to population size

(Table 8.1).

       The enumeration districts in the parish of St. Catherine provided the sampling frame and

the sample size was determined with the help of the Statistical Institute of Jamaica (STATIN).

The enumeration districts were listed and single-stage cluster sampling was used to select the

sample. The enumeration districts were numbered sequentially and selection of clusters was

arrived at by calculating a sampling interval. From a randomly selected starting point, forty (40)

enumeration districts (clusters) were subsequently selected with the probability of selection

being proportional to population size. The sample of 2000 was selected based on a proportion of

the Census Data (Table 8.1).


       The parish of St. Catherine had approximately 233,052 males, (preliminary census data

2001) of which 33,674 males were 55+ years. STATIN maintains maps with enumeration

districts or census tracts which included the selected EDs and access routes and had references to

the selected site of a starting point household within each ED. The starting point was determined

by randomly selecting a household with a man 55 years and over from the list of persons in the

ED. With this information the interviewers travelled in a north-easterly or closest to north-

easterly direction beginning with the first selected household, and conducted interviews in each

household that had a male 55 years and older. Only one male per household was selected; and in

households with more than one individual fitting the characteristic of the sample, a coin was

tossed to determine the person who will be interviewed. (North-East was randomly selected by

STATIN as the direction of travel from the starting point).

       Where the selected household was found to be subsequently devoid of an older man (due

to out-migration or death), an adjacent household was canvassed. Where households had a man

                                               175
55+ years as a resident and he was not at home a call-back form was left indicating a proposed

time that the interviewer would return which would not be longer than two days after the initial

visit.

         The sample population does not only speak to the parish of St. Catherine, it is

generalizable to the island of Jamaica. The sampling frame was men fifty-five years and older in

the parish of St Catherine. The parish of St. Catherine was chosen as previous data suggested that

it has the mix of demographic characteristics (urban, rural and age-composition) which typify

Jamaica surveys (Statistical Institute of Jamaica 2004; Wilks 2007; Jackson et al. 2003)

         For the current study descriptive status was employed to provide background information

on the sample; and chi-square was used to examine non-metric variables. Level of significance

was pvalue<0.05 and the only exclusion criteria was if more than 20% of the cases of the

variable were missing.

Measure


Happiness is measured based on people’s self-report on their happiness (Frey & Stutzer, 2002a,

2002b; Easterlin 2001; Borghesi, & Vercelli, 2007). This operationalization is based on a basic

indicator proposed by Diener (2000), including a more emotional component referring to

happiness (‘Taking all things together, how happy would you say you are?’). It is a Likert scale

question, which ranges from high to low happiness. It was coded into a binary variable, whether

or not the individual had moderate-to-high or low happiness: 1=moderate to high happiness, 0 =

otherwise.

Life satisfaction. Diener (2000) had proposed that happiness includes emotional components and

a more cognitive component referring to life satisfaction (‘All things considered, how satisfied

are you with your life as a whole nowadays?’), for this paper the researcher separated happiness

                                               176
(emotional) from cognitive (life satisfaction). Life satisfaction is a binary variable, where 1=

good-to-excellent self-reported overall satisfaction in life, 0=otherwise.


Health Status is measured using people’s self-rate of their overall health status (Kahneman, &

Riis, 2005), which ranges from excellent to poor health status. The variable used in this study

for health status is a binary one, whether or not the person had good-to-excellent or poor health

status. It was then coded as a dummy variable, 1=good-to-excellent health status, 0=otherwise.

Age group is categorized into three sub-groups. These are (1) ages 55 to 64 years; (2) ages 65 to

74 years; and (3) age 75 years and older (ie 75+ years).

Listing of covariates

Residence is a binary variable, 1=lives in urban area, 0=lives in rural area.

Employment status is a binary variable, where 1=employed, 0=otherwise.

Health retirement plan is a binary variable, where 1=having a health retirement coverage,

0=otherwise.

Occupation is a binary variable, where 1=current or past occupation which was in the category

of professional, 0=otherwise.

Marital status is a non-binary variable, where 1=married, 0=otherwise; 1= separated, divorced or

widowed, 0=otherwise and single is the reference group.

Childhood health status is a binary variable, 1=self-reported poor health status, 0=otherwise.

Household head is a binary variable, 1=self-reported head of household, 0=otherwise.

Social networking is operationalized based on yes or no to being a member of a social club;

civic organization; or community organization. This was dichotomized to be 1 if yes and 0 if

otherwise. This variable excludes being a member of a church.



                                                177
ADL. This is a functional status of 12 events. These include eating; bathing; dressing; using

toilet; shopping; preparing meals; feeding oneself; continence; taking or using transportation;

managing medication; money management; and laundry.

Model

Theoretical background

According to micro econometric happiness function, subjective wellbeing (ie happiness) is a

function of different variables (including some demographic ones) (Stutzer & Frey 2003) [Model

(1)].

        Wit = α + βXit + εit…………………………………………………..……….. [1]

        Where Wit represents subjective well-being, Xit denotes x1, x2, x3, and so on, in which

x1 to xn are variables – ‘sociodemographic’, ‘environmental’, and ‘social’, ‘institutional’ and

‘economic conditions’

        In this study, the literature (ie micro econometric happiness function) will be expanded to

include health status in childhood, current health status, life satisfaction, and area of residence by

testing this theory using elderly men in Jamaica [Model (1)]. In addition to the aforementioned

micro econometric happiness function, the study will also seek to examine health status.

Variables such as happiness, life satisfaction and some demographic variables will be

investigated simultaneously [Model (2)].

Estimation Model

The interests of this study are to examine whether happiness can be predicted by health status as

well as the role of life satisfaction, and self-reported childhood health status on happiness of

elderly men in Jamaica. Continuing, it is also to investigate whether health status can be


                                                 178
predicted by happiness; what are the demographic factors that can predict either happiness or

health status of elderly men in Jamaica as well as determine, if there is a difference between rural

and urban areas. The multivariate model used in the current study is an expansion of the

literature (Stutzer and Frey’s work on happiness) which is displayed in equations (2) and (3).


Hit = β0 + β1HSit + β2HSi(t-1) + β3LSit+ βijDij+ εi ...……….………………..………...[2]



HSit = β0 + β1Hij + β2HSi(t-1) + β3LSit + βijDit+εi ………………………….…….…….[3]



where Hit denotes happiness of person i in time period t (current period); HSit means health

status of person i in current time period t; HSi(t-1) denotes the childhood health status of period i

previous period (t-1); LSit is life satisfaction of person i in current time period (t); Dit = d1, d2,

d3, d4…..dn, which include sociodemographic and socioeconomic variables of individual i in

current time period (t). β0 indicates happiness at the beginning of the period; β1 to βij denotes

the parameter for each variable from variable 1 to j.


       The models [Eqn. (2) and (3)] allow for each factor that is associated with happiness

[Eqn. (2)] or health status [Eqn. (3)] to be examined separately. Those approaches have been

widely and successfully applied in a plethora of studies on the correlates of happiness (Easterlin

2001; Veenhoven 1993, Stutzer & Frey 2003; Frey & Stutzer 2002; Frey & Stutzer 2002;

Blanchflower & Oswald 2004; Argyle 1999) and/or health status (Bourne 2008a, 2008b;

Grossman 1972; Smith & Kington 1997; Hambleton et al. 2005; Bourne & McGrowder 2009)

This is the rationale for the usage of micro-econometric happiness function (Lima & Nova




                                                 179
2006), Bourne and McGrowder’s (2009) health status function as they allow for the analysis of

current study.


       Because the dependent variable for the current study, happiness or health status, is a

binary one, probit analysis was used to estimate the impact of life satisfaction, current health

status, childhood health status, including other socio-demographic variables (such as

employment status, education, marital status, age of elderly, social support, and church

attendance) on happiness or current health status of elderly men in Jamaica. Furthermore, the

current study will mainly report the results of those variables that are statistically significant

(p<0.05).


       Furthermore, the variables used in this study are based on (1) literature review which

shows that these are likely to correlate with the particular dependent variable, and 2) the

correlation matrix was examined in order to ascertain if autocorrelation (or multicollinearity)

existed between independent variables. Based on Cohen and Holliday (1982), correlation can be

low (weak) - from 0 to 0.39; moderate – 0.4-0.69, and strong – 0.7-1.0. This was used to exclude

(or allow) a variable in the model. Any of the independent variables which had moderate to high

correlation was excluded from the model. The correlation between life satisfaction and happiness

was 0.633; happiness and social networking (correlation coefficient = 0.12, p = 0.003); happiness

and marital status (correlation coefficient = 0.107, p = 0.026); marital status and income category

(correlation coefficient =0.193, p< 0.001); social networking and marital status (r=0.205,

p<0.001); social networking and age group (correlation coefficient = 0.188, p<0.001); social

networking and occupation (correlation coefficient =0.320, p< 0.001); social networking

educational category (correlation coefficient =0.420, p<0.001); ADL and age cohort (correlation


                                               180
coefficient =-0.813, p=0.032); income and occupation (correlation coefficient =0.7775, p <

0.001); and, income and education (correlation coefficient =0.356, p<0.001); employment and

education category (correlation coefficient =0.283, p<0.001). However, there was no correlation

between happiness and present occupation (p=0.761); happiness and income (p=0.233);

happiness and employment status (p=0.516); as well as life satisfaction and employment status

(p=0.261). Hence, life satisfaction and happiness; occupation and income category will not be

simultaneously used as explanatory variables.


Results: Socio-demographic Characteristics of Sample

The sample was 2,000 men ages 55 years and older (42.6% were 55 to 64 years; 35.6% were 65

to 74 years; 21.9% were 75 years and older). Fifty one percent of the sample lived in rural areas;

59.1% had social network; 55.4% reported good health status and 25.6% indicated poor health

status; 53.9% were retired, 25.6% were actively employed and 20.6% unemployed; 58.8% did

not own their homes, and 34.3% were single and 44.7% were married elderly men. Majority of

the sample had primary or elementary level education (83.1%); 85.9% reported that they do not

regularly exercise; 82.5% reported good health in childhood; and 88.12% were heads of their

households (Table 8.2). One half of the sample indicated that they spent Ja. $100 (US $1.45)

monthly for medical expenditure; 34% of the respondents bought their prescribed medication;

17.1% reported that they have been hospitalized since their sixth birthday and 65.8% reported

that they took no medication. Of those who mentioned that they were ill during childhood

(17.5%, n=350), 34.9% said that the illness was measles or chicken pox, 26.3% mentioned

asthma, 10.0% pneumonic fever, 8.9% polio, 6.6% accidents, 4.6% jaundice, 1.7% hernia, and

5.1% indicated gastroenteritis. Twenty four percent of elderly men indicated that they were



                                                181
rarely happy, 40.5% said sometimes, 31.0% mentioned often and only 4.5% reported always.

Furthermore, 17.7% of the sample reported that they were seriously ill as children.

       Of the sample (n=2,000), 24.0% indicated that they were rarely happy; 40.5% indicated

sometimes; 31.0% mentioned most times and 4.5% reported always. Hence, approximately 65%

of the sample was happy at least sometimes. With respect to life satisfaction, 32.9% of the

sample indicated that they were rarely satisfied with their life; 33.7% revealed sometimes; 29.9%

mentioned most times and 3.5% reported always.

       Of the sample, 62.7% revealed that they were able to carry out particular daily activities

compared to 37.4% who reported that they were unable to perform daily activities.



Results: Multivariate Analysis

The results from the probit regression analyses of happiness are presented in Table 8.3. The

results for the current health status are presented in Table 8.4. Therefore, the current study

will mainly report the results of those variables that are statistically significant (p<0.05).


       Current happiness of elderly men in Jamaica was found to be statistically influence by

life satisfaction (95% CI: 0.417, 1.215; p <0.001) and aged men 75 years and beyond (95% CI: -

1.193, -0.054; p=0.032) with reference to those 55 to 64 years of age. For life satisfaction,

Current and childhood health status as well as education, age of elderly men, social support,

church attendance, occupation (both current and past), and marital status were found not to

influence current happiness (p > 0.05). Continuing, current happiness of elderly men was the

same whether they live in urban or rural areas (p=0.813) (Table 8.2). Based on Table 8.3, the

model is a good fit for the data (log likelihood=153.039; chi-square = 106.479, P=0.985).



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       Current health of the sample was found be significantly statistically influenced by age of

the elderly (ages 65 to 74 years – 95%CI: -1.513, -0.622; ages 75+ - 95% CI: -2.130, -1.022;

p<0.001), social support (95% CI: 0.016, 1.315, p=0.045) and area of residence (95% CI: -0.959,

-0.085, p=0.019) (Table 8.4). Continuing, urban elderly men had a lower current health status

than their rural counterparts. Variables such as life satisfaction, employment status, education,

head of household, occupational type (both past and current), health status in childhood, church

attendance and happiness were not found to statistically influence current health status of elderly

men in Jamaica. Based on Table 8.4, the model is a good fit for the data (log likelihood=149.068;

chi-square = 102.798, P=0.971).


Discussion


The study revealed 24 elderly men in every 100 were rarely happy, 41 in every 100 were

happy sometimes, 31 in every 100 indicated most times and 5 in every 100 reported always;

and that 55 out of every 100 were in good health, 26 in every 100 said fair and 19 out of

every 100 said excellent health status. The survey evidence presented here suggested that

there was no statistical correlation between happiness and health status of elderly men in

Jamaica, and it goes further to show that happiness cannot be a predictor of health status as

well as health status cannot be a predictor of happiness. Happiness was found not to correlate

with health status of elderly men in Jamaica nor was health status associated with happiness;

and that there was no difference based on area of residence. This denotes that happiness does

not provide an understanding of health status and vice versa as well as the fact that overall

life satisfaction of elderly men in Jamaica is not explained by health status. However, life

satisfaction was a predictor of happiness for older men.


                                               183
      In this research health status does not influence happiness which is contrary to the

other studies (Siahpush et al., 2008; Borghesi, & Vercelli, 2007; Kahneman, & Riis, 2005;

Easterlin, 2003; Brickman, Coates & Janoff-Bulman 1978; Stutzer & Frey 2003; Frey &

Stutzer 2002a, 2002b; Blanchflower & Oswald, 2003; Argyle 1999; Michalos, Zumbo, &

Hubley, 2002). One scholar went further than the negative statistical association between

happiness and health status when he argued that over life’s course, happier people were

healthier people which suggest that correlation is even in later life for both sexes. This study

cannot concur with such a finding as there is no statistical relationship between happiness

and health status at older ages for men in Jamaica, suggesting that happiness is not a good

predictor of health status. Happiness therefore can be used to proxy health status of older

men in Jamaican.


      Research literature has long established that life satisfaction and happiness are

estimates for each other and encapsulate the overall experiences of the individual (Selim,

2008; Siahpush et al., 2008). Happiness is a crucible pursuit of human existence (James

1902). It is multidimensional and thus justifies its usage in measuring wellbeing instead of a

traditional approach of income per capita (Gross Domestic Product per capita, GDP) (Diener,

Lucas, & Oishi, 2002; Diener, 1984, 2000; Easterlin, 2003; Diener, Larson, Levine, &

Emmon, 1999) Happiness which was first introduced by a psychologist (Diener, 1984) as a

subjective measure in assessing wellbeing has been accepted by some economists as a good

proxy for wellbeing (Graham, 2008; Borghesi, & Vercelli, 2007; Mahon et al., 2005; Layard,

2006; Easterlin, 2001; Veenhoven, 1993; Argyle, 1999; Stutzer & Frey 2003; Easterlin,

2003; Brickman, Coates & Janoff-Bulman, 1978; Frey & Stutzer,                   2002a, 2002b;

Blanchflower & Oswald, 2004). Based on this established fact, information is now available

                                               184
on the multidimensional state of elderly men in Jamaica. Although happiness is fluid, the

current study has revealed that a small proportion of elderly men in Jamaica reported that

they were always happy (approximately 5 out of every 100) compared to 24 out of every 100

who claimed they were rarely happy. Embedded in this finding is the negative psychological

state of many elderly people as this is reflected in their happiness (or unhappiness); and their

happiness is not influenced by their health status.


      Lyubomirsky (2001) forwarded a number of issues that justified happy from unhappy

people. She 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. In this study, 44% were married; 88% heads of household; 26% employed; 54%

retired, 83% had primary or elementary education, for those who are employed 93% earned

less than US $283.23 per month (Ja$70.61=1US$) and although those variables were found

not to statistically influence happiness, the aforementioned studies declared that they do.

According to Borghesi, & Vercelli (2007), education, employment status, social capital and

environmental variables influence happiness, this is not the case for older men in Jamaica.

Neither is marital status, occupational type, social support or church attendance. However,

Borghesi & Vercelli Kim-Prieto et al. (2005) and Smith et al. (2005) identified that

educational attainment; employment status; social support; genetic endowment; and the

social (Fowler & Christakis, 2008) and physical milieu are correlated with happiness and

while this is not the case for older men in Jamaica; those variables do influence life

satisfaction (Mroczek, & Spiro, 2005; Gwozdz, & Sousa-Poza, 2009) which indirectly

impact health status.



                                                185
      According to Gwozdz & Sousa-Poza (2009) life satisfaction decline with old age,

which may explain why in the current study only 4 out of every 100 Jamaican older men

reported being always happy and 30 out of 100 reported being happy most of the time. Like

the literature this study concurs that there is a correlation between life satisfaction and marital

status; life satisfaction and occupation; and life satisfaction and area of residence; but they

were weakly related to each other. However, it was revealed also that there was no

significant statistical association between employment status and life satisfaction, and life

satisfaction and income, suggesting that the variables which influence life satisfaction as well

as happiness for the elderly men are not necessarily the same as those that affect happiness or

life satisfaction of the population (Selim, 2008; Siahpush et al., 2008). Furthermore, another

important finding is the disparity in factors that influence life satisfaction or health status of

older men in Germany and Jamaica (Gwozdz, & Sousa-Poza, 2009).


      With the down turn in the American economy, Jamaicans have been experiencing a

significant reduction in remittances which act as an income for many families including the

elderly. This will further erode the life satisfaction of elderly men as they will be

incapacitated by the inability to afford basic necessities and their independence will be

threatened as they must now seek the assistance of church, friends and other social networks

in order to survive. Although social networking and employment status were not found to be

statistical associated with happiness in the current work, men equate the ability to provide for

their families and spend on particular things as they desire, as apart of their happiness.

Hence, income or wealth is a good predictor of happiness for this cohort (see also, Frey &

Stutzer, 2002a, 2002b; Borghesi & Vercelli, 2007; Graham, 2008), not having data on wealth

hampers a possible explanation instead of many of the other variables that were tested.

                                                 186
      The literature has provided a plethora of studies that showed the correlation between

happiness and health status; but this is not the case for elderly men in Jamaica. Using

stratified probability sampling technique of 2,000 elderly men, this study found no

association between the happiness and current health status, and vice versa. What accounts

for this disparity? While health and happiness are correlated in the general populace of the

world, other nations, and many countries outside of Jamaica, it is not the case for men ages

55 years and older in Jamaica based upon men’s unwillingness to seek openly and truthfully

about their health. This brings into question the validity of value judgement or the self-

reported health of this study.


      The validity of using people’s assessment of their life satisfaction and health is old and has

already been resolved. Nevertheless, it will be succinctly forwarded here for those who are not

cognizant of this discourse. Scholars have established that there is a statistical association

between subjective wellbeing (self-reported wellbeing) and objective wellbeing (Diener, 2000;

Lynch, 2003) and Diener (1984) went further when he found a strong correlation between the

two variables. Gaspart (1998) opined about the difficulty of objective quality of life (GDP per

capita) and the need to use self-reported wellbeing in assessing wellbeing of people. 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) which

speaks to the necessity of using a measure that captures more to the this multidimensional

construct than continuing with the traditional income per capita approach. Another group of

scholars emphasized the importance of measuring wellbeing outside a welfarism and/or purely

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

                                               187
that enhances economic wellbeing” (Becker, Philipson & Soares, 2004, 1) and that wellbeing

depends on both the quality and the quantity of life lived by the individual (Easterlin 2001).

      The discourse of subjective wellbeing using survey data cannot deny that it is based on the

person’s judgement, and must be prone to systematic and non-systematic biases (Schwarz &

Strack, 1999). In an earlier work, Diener (1984) argued that the subjective measure seemed to

contain substantial amounts of valid variance. This will not be addressed in this paper as this is

not the nature or its scope. Despite this limitation, a group of economists noted that ‘happiness or

reported subjective well-being is a satisfactory empirical approximation to individual utility’

(Frey & Stutzer, 2005) and this is a rationale for its usage in wellbeing research.

       The current study has not only provided pertinent research information on happiness v

health status in elderly men in Jamaica, it also examined health status and happiness as well as

other variables such as childhood health status, life satisfaction and some other

sociodemographic variables. Life satisfaction; employment status; education; health insurance;

head of household; marital status; childhood health status; church attendance; and happiness of

elderly Jamaicans do not statistically influence health status. All those variables are well

established in research literature as statistically significant correlates with health status. Studies

have moved beyond those variables being mere correlates to predictors of health status (Bourne,

2008a, 2008b; Grossman, 1972; Smith & Kington, 1997; Hambleton et al., 2005; Bourne &

McGrowder, 2009). A recently published study on rural Jamaican by Bourne and McGrowder

(2009) identified 12 explanatory predictors of good health and another by Bourne (2008b) found

11 predictors of wellbeing of aged Jamaicans. The aforementioned studies are different from the

current as there is a difference in regards to the measurement of health status. Those studies

operationalized health (or subjective wellbeing) as health conditions whereas this one used

                                                 188
general self-reported health status which is keeping with literature (Grossman, 1972; Smith &

Kington, 1997; Hambleton et al., 2005), but departs in respects to the predictors.

        There is a convergence of predictors as this study concurred with the literature that

ageing is associated with lower health status; social support (Fowler & Christakis, 2008), and the

place of residence are determinants of health status. Area of residence is not only a correlate of

health status; but the current study found that elderly men who lived in urban areas have lower

health status, suggesting that healthier old men in Jamaica resided in rural areas.

        Functional capacity of the elderly is well established in health literature as influencing

health status and by extension happiness (Yi & Vaupel, 2002; Bogue, 1999). The young-old

(ages 60 to 64 years) 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 & Fiest, 2004). This

phenomenon means that human mortality increases with age of the human adult, but that this

becomes less progressive in advance ageing. Thus, biological ageing is a process where the

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

inverse association between ageing and subjective wellbeing (Netuveli et al. 2006; Prause et al.

2005). Bogue (1999:3) summarized the characteristics of three elderly cohorts (young-old – ages

60 to 74; aged or old-old – 75 to 84 years and oldest old - 85+ years), when he showed that as the

elderly ages from young-old to aged their health problems increased from low to moderate and

thus increased to high for the oldest-old and that this is similar to their physical disability.

        Performance of Activities of Daily Living (ADL) is used to describe the functional status

of a person. It is used to determine a baseline level of functioning and to monitor improvement

in activities of daily living (ADL) overtime. There are systems such as the Katz ADL tool that

seek to quantify these functions and obtain a numerical value. These systems are useful for the

                                                  189
prioritizing of care and resources. Generally though, these should be seen as rough guidelines for

the assessment of a patient’s ability to care for themselves. Scoring the ADL findings (Katz)

Independence on a given function received a score of 1 point while if dependent, 0 point was

given. There were 14 items (including daily activities; household chores; shopping; cooking;

paying bills). The reliability of the items was very high, α = 0.801. Total scores thus could range

from 0-14 with lower scores indicating high dependence and higher scores indicating greater

independence. Instrumental Activities of Daily Living (IADL) The Instrumental Activities of

Daily Living tool (IADLs; Lawton & Brody, 1969) was the basis for assessing participants’

difficulty with IADL.     IADL are those activities whose accomplishment is necessary for

continued independent residence in the community.

       The independent activities of daily living are more sensitive to subtle functional

deficiencies than ADL’s and differentiate among task performance including the amount of help

needed to accomplish each task. Due to the fact that the study was being conducted among men

only, some tasks which are normally done by women would not apply. Thus consistent with

international practice, the University of Wollongong’s modified IADL functional ability scale

which uses a scale of 5 points for men and eight for women to assess the IADL functional ability

of men in the study (Centre of Health Service Development 2001). Consequently the domains of

food preparation, laundry and housekeeping were omitted in this study with regard to the

Instrumental Activities of Daily Living for older men. Scoring the IADL: IADL scores reflect

the number of areas of impairment, i.e. the number of skills/domains in which subjects are

dependent. Scores range from 0-5. Higher scores thus indicate greater impairment and

dependence.




                                               190
       Hence, Functional status is the summation of ADL and IADL. Cohen & Holliday1 stated

that correlation can be low/weak (0–0.39); moderate (0.4–0.69), or strong (0.7–1). Hence, high

dependence ranges from 0 to 5.5; moderate dependence is from 5.6 to 9.7 and low dependence

(ie independence) ranges from 9.8 to 14. Independence means without supervision, direction, or

active personal assistance. The performance on the functions can be further classified and

analyzed using the format below. The classification recognizes that combinations of

independence/dependence with respect to particular functions reflect the different degrees of

levels of capability with respect to ADL. The classification outlined below (as developed based

on Katz et al 1970 and Katz et al 1993) was used to further describe the functional status of men

with regard to ADL. Based on the aforementioned discussion on ageing and health status as well

as ageing and functional capacity, ADL and IADL are strongly correlated which indicates that

ageing and functional capacity should not be a separate independent variable as there would be

high multicollinearity between those two factors. Hence, ageing category was used instead of

functionality capacity as an independent variable.



Conclusion



The current work has shown that happiness is not influenced by health status nor is it determined

by employment status, educational attainment; marital status; church attendance or any other

form of social networking which means that health status is not synonymous with happiness nor

is happiness equivalent to health status for older men in Jamaica. Happiness is not correlated

with health status and vice versa for elderly Jamaicans, and so understanding happiness is not

comprehending health status. Happiness and health status cannot be used to proxy each other for

                                               191
the elderly cohort as they are mutually exclusive events. Happiness however, is correlated with

life satisfaction and people’s general perception about their life is a good predictor of happiness;

suggesting that life satisfaction can measure happiness. A qualitative assessment is needed to

understand elderly men’s value system, as this will provide answers for the disparity between the

two phenomena. In spite of the need to do further studies on the issue, research findings are now

available upon which better public policies can be framed from here onwards.


Disclosure


The author has no disclosure to declare.




                                                192
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                                              197
Table 8.1: Proportion of Survey (Sample) vs. Proportion of Population
 Age                           2001 Census (St.            2001 Census
              Survey
Group                             Catherine)                (Jamaica)

 (Yrs).     n       %         n             %          N            %

 55-59     469    23.45      6577          26.7      38645        23.9

 60-64     413     20.6      5179          21.1      31828        19.7

 65-69     374     18.7      4391          17.8      28901        17.9

 70-74     345     17.2      3594          14.6      24856        15.4

 75-79     189     9.45      2402          9.78      17711        11.0

  80+      210     10.5      2399          9.77      19552        12.1




                                     198
Table 8.2: Socio-demographic Characteristics of Sample: Descriptive Statistics
Variable                                                                Frequency     Percent
Marital Status
    Single                                                                      686     34.3
    Married                                                                     894     44.7
    Separated                                                                   112      5.6
    Common law                                                                  136      6.8
    Widowed                                                                     172      8.6
Head of Household
    Self                                                                       1763     88.1
    Partner                                                                     122      6.1
    Children                                                                     63      3.2
    Sibling/Parent                                                               52      2.6
Age group
    55- 64 years                                                                851     42.6
    65 – 74 years                                                               712     35.6
    75 years and older                                                          437     21.9
House Ownership
    Yes                                                                         824     41.2
    No                                                                         1176     58.8
Employment Status
    Employed                                                                    511     25.6
    Unemployed                                                                  412     20.6
    Retired                                                                    1077     53.9
Education
    No Formal Education                                                         200     10.0
    Primary and basic                                                          1661     83.0
    Secondary                                                                   102      5.1
    Tertiary                                                                     37      1.9
Self-rated Health Status
    Excellent                                                                   357     19.0
    Good                                                                       1038     55.4
    Fair                                                                        480     25.6
Social Networking
    Yes                                                                         817     59.1
    No                                                                         1183     40.9
Regular Exercise
    Yes                                                                         282     14.1
     No                                                                        1718     85.9
Childhood Health status
   Good                                                                        1650     82.5
   Poor                                                                         350     17.5
Area of residence
   Urban                                                                        981     49.0
   Rural                                                                       1019     51.0




                                                  199
Table 8.3: Results of Probit Analysis of Happiness and Some Sociodemographic Variables
                                                                     95% Confidence
    Variable                                                Std.        Interval
                                               Estimate     Error   Lower     Upper
    Life Satisfaction                            0.816      0.203    0.417   1.215***
    Employed                                     0.793      0.926   -1.023       2.609

    Primary schooling                            0.065      0.291   -0.505      0.636
    Secondary and beyond                         0.191      0.429   -0.649      1.031
    †No formal education

    Health Retirement plan                       0.099      0.354   -0.595      0.793
    Household Head                              -0.009      0.308   -0.613      0.594

    Married                                     -0.046      0.212   -0.462      0.370
    Separated, Divorced or Widowed              -0.137      0.315   -0.754      0.481
    †Never married

    Professional                                 0.007      0.288   -0.558      0.571
    Current good Health Status                  -0.189      0.224   -0.628      0.251
    Childhood health status                     -0.093      0.240   -0.563      0.377
    Area of residence (1=Urban)                 -0.052      0.218   -0.478      0.375

    Elderly 1 (ages 65 to 74 years)             -0.238      0.225   -0.680      0.203
    Elderly 2 (ages 75 years and older)         -0.624      0.291   -1.193    -0.054*
    †Elderly (ages 55 to 64 years)

    Social Support                               0.034      0.316   -0.586      0.654
    Church attendance                           -0.151      0.239   -0.619      0.317
    Intercept                                   -1.459      1.042   -2.501     -0.417
Log likelihood = 153.013
Pearson Good of Fit test: Chi-square = 106.479, P=0.971
†Reference group
*p < 0.05, **p < 0.01, ***p < 0.001




                                                      200
Table 8.4: Results of the Probit Analysis of Health Status by Some Sociodemographic variables
    Variable                                                 Std.    95% Confidence Interval
                                                  Estimate   Error    Lower       Upper
    Life Satisfaction                               0.381    0.251   -0.109           0.872
    Employed                                        0.385    0.609   -0.809           1.579

    Primary schooling                              -0.421    0.272   -0.956           0.113
    Secondary and beyond                            0.886    0.489   -0.074           1.845
    †No formal education

    Health Retirement plan                         -0.456    0.388   -1.217           0.306
    Household Head                                  0.058    0.330   -0.590           0.705

    Married                                         0.033    0.217   -0.392           0.459
    Separated, Divorced or Widowed                 -0.073    0.321   -0.703           0.557
    †Never married

    Professional                                    0.081    0.316   -0.539           0.701

    Childhood Health Status                        -0.414    0.246   -0.897          0.068
    Area of residence (1=Urban)                    -0.522    0.223   -0.959        -0.085*

    Elderly 1 (ages 65 to 74 years)                -1.067    0.228   -1.513      -0.622***
    Elderly 2 (ages 75 years and older)            -1.576    0.283   -2.130      -1.022***
    †Elderly (ages 55 to 64 years)

    Social Support                                  0.666    0.331    0.016         1.315*
    Church attendance                              -0.052    0.243   -0.528          0.424
    Intercept                                       0.785    0.722    0.063          1.507
Log likelihood = 149.068
Pearson Good of Fit test: Chi-square = 102.798, P = 0.985
†Reference group
*p < 0.05, **p < 0.01, ***p < 0.001




                                                       201
                                                                                   Chapter 9

Happiness, life satisfaction and health status in a Caribbean nation: Using a
cross-sectional survey


Paul A. Bourne, Chloe Morris, Denise Eldemire-Shearer, Christopher A.D.
Charles, Neva South-Bourne



Not much is known about the health of older men in Jamaica and the factors that determine
happiness of these individuals. This paper examines happiness, life satisfaction and health status
of older men (55+ years) in Jamaica in order to ascertain whether they are synonymous
measurements as well as to establish a happiness model for older men. The study used a
multistage stratified sample of 2,000 elderly men (42.6% ages 55 to 64 years; 35.6% ages 65 to
74 years and 21.9% of ages 75 years and older) to evaluate the psychological wellbeing (ie
happiness) of this age cohort. Overall, the general happiness of older men was moderate (40.5%
reported that they were happy sometimes) and that this was similar for self-reported health status
(55.4% reported good health status). Using ordered probit analysis, the micro-econometric
happiness function of aged men can be explained by employment status; functional status and
church attendance (ie religious beliefs). Happiness and life satisfaction are highly statistically
related (cc = 0.833, P = 0.001), but happiness is not correlated with health status ( P = 0.767) nor
is life satisfaction associated with health status ( P = 0.667). The current study has provided us
with much information on the overall quality of life of elderly men in Jamaica. It has refuted
previous literature which showed that life satisfaction, happiness and health status are
synonymous measurements. The findings are far reaching can be used to guide future research
and how subjective wellbeing is examined, and how interventions are planned.



Introduction

This study investigates health, happiness and satisfaction with life of older men in a middle-

income developing country. Happiness, life satisfaction, and health status are among some of the

subjective indexes used to evaluate health (or wellbeing) of an individual, community or


                                                202
population. Subjective indexes cover a wider gamut of an individual’s life compared to

diagnosed health conditions, morbidity, reproductive health and life expectancy. Jamaica has

been collecting data since 1989, and this has been used to measure health of the population,

gender of the participants and health within area of residence. The use of illness to measure

health is negative and does not cover health. Happiness therefore like life satisfaction and health

status provide a comprehensive coverage of people’s quality of life than ill-health. The use of

objective indexes such as diagnosed illness, gross domestic product; life expectancy and

mortality are among measured that are said to be limited in scope, and justify the usage of the

subjective indexes by some scholars.


       Initially when happiness was put forward by Diener1 as a measure of wellbeing, it was

rigorously opposed by some scholars as subjective and so cannot be used to measure health or

wellbeing. Many traditional economists believed that happiness was subjective and that this

could not be precisely measured, and this accounted for their reservations and refusal to accept it.

They believed that Gross Domestic Product per capita (GDP per capita) or income per capita was

an objective measure and one that can be precisely quantified unlike happiness, life satisfaction

or other subjective indexes. This dates back to classical school of thought. Unlike traditional

economists, Diener, a psychologist, theorized that happiness can be used to operationalized

subjective wellbeing1,2 and this was later adopted by some economists like Easterlin3-6, Frey and

Stutzer7,8 , Stutzer and Frey9 , Oswald10, Ng11,12 , Veenhoven13,14 and Blanchflower and

Oswald15.


       Easterlin found a statistical association between happiness and income.3-6 He argued that

“The relationship between happiness and income is puzzling”3 and that people with higher


                                                203
incomes were happier than those with lower incomes; but that economic growth does not means

happiness. Easterlin used happiness to operationalize subjective well-being, which was found to

be highly correlated with income. He went further when he said that “Then, with aspirations

essentially the same those with higher income will be better able to fulfill their aspiration and,

and other things being equal, on an average, feel better off”3 Like Easterlin, all the

aforementioned economists used happiness to evaluate subjective wellbeing as they accepted that

happiness is an indicator of people’s judgement of their overall quality of life.13,14 Randomly

selecting Europeans and Americans from the 1970s to 1990s, Di Tella et al.16 using ordered

probit analysis, did not find this complex relation between income and happiness. They however

noted that some variables such as unemployment, unemployment benefits and others are

exogenous variables as they are influenced by political decisions and do influence income.


       Diener2 argued that well-being can be explained outside of welfare theory and/or purely

objective utility approach, and this was supported by other scholars.17-21 Arthaud-day et al’s

work22 applied structural modeling and found that subjective well constituted of (1) cognitive

evaluations of one's life (i.e., life satisfaction or happiness); (2) positive affect; and (3) negative

affective conditions. Unlike Arthaud-day et al, Diener2 proposed that subjective wellbeing can be

operationalized by some basic indicators such as emotional components (‘Taking all things

together, how happy would you say you are?’) and cognitive components or life satisfaction

(‘All things considered, how satisfied are you with your life as a whole nowadays?’).

       Summers and Heston23 noted that “…GDPPOP is an inadequate measure of countries'

immediate material well-being, even apart from the general practical and conceptual problems of

measuring countries' national outputs.”23 Generally, from that perspective, the measurement of

quality of life is, therefore, a highly economic and excludes the psychosocial factors. But, quality

                                                 204
of life extends beyond monetary objectification. Using data for developing countries, Camfield24

in looking at well-being from a subjective vantage point noted that subjective well-being

constitutes the existence of positive emotions and the absence of negative ones within a space of

general satisfaction with life. Cummins21 argued that ‘subjective and objective measures of

material well-being’ along with the absence of illnesses, efficiency, social closeness, security,

place in community, and emotional well-being means that life’s satisfaction comprehensively

envelopes subjective well-being. Diener2 in an article titled ‘Subjective Well-Being: The Science

of Happiness and a Proposal for a National Index’ theorized that the objectification of well-being

is embodied within satisfaction of life. This explains the rationale for the use of life satisfaction

and/or happiness to operationalize wellbeing instead of GDP per capita (or income per capita).


       In seeking to operationalize well-being, the United Nations Development Programme

(UNDP) supported the inclusion of subjective measures, when they conceptualized human

development as a “process of widening people’s choice as well as the level of achieve

wellbeing.”25 Embedded within this definition is the emphasis of materialism in interpreting

quality of life. Based on UNDP’s Human Development Index it “… 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). Another economist writing on ‘objective well-being’ 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.”26


       Globally, the literature on happiness and life satisfaction is well established, but extensive

review of the literature turned up one study in Jamaica that has examined life satisfaction.27 In


                                                205
this study, the scholars found that women had a lower overall life satisfaction (72%) than men

(76%; p=0.04). Employment status; education; gender; union status; church attendance; self-

esteem, and current health status were determinants of life satisfaction. In Di Tella et al’s work,

they found income, employment status, interpersonal trust, health status, marital status,

education, sex and inflation, the rate of change of consumer prices in the country, unemployment

benefits, and the number of children in households was predictors of happiness. In descending

order, they found that marital status, income and employment status had the greatest influence on
                             16
happiness. Di Tella et al.        also found that correlation between happiness and life satisfaction

was 0.56. Disaggregating happiness and life satisfaction for the sample, they found that in the

United States’ sample, 32.66% was very happy; 55.79% pretty happy and 11.55% not too happy.

Further disaggregation of the sample by gender revealed that 31.95% of the males indicated

being very happy compared to 33.29% of females. For the European’s sample, life satisfaction

was 27.29%, very satisfied; 53.72% fairly satisfied; 14.19% not very satisfied and 4.8% not at all

satisfied; with marginally more females reported very satisfied, 27.75% compared to 26.81% of

males.

         No study emerged from the literature search on happiness in the Caribbean or in

particular Jamaica and none was found on happiness of elderly people (ages 60 years and older).

Although there is very little or research study in the English speaking Caribbean on happiness of

the general populace or on the elderly population, Stutzer and Frey9 have identified a few

predictors   of   happiness       using   micro-econometric    analysis:   income;   aspiration;   and

unemployment. Konow and Earley’s study27 revealed that employment status, positive and

negative affective conditions; social support and marital status were correlated with happiness;

and some of these (ie employment status, marital status, living arrangement, age, education,

                                                   206
gender) were also recorded as being statistical associated with happiness in Blanchflower and

Oswald’s study.15 Despite having identified predictors of happiness and life satisfaction,

Blanchflower and Oswald’s work found that those variables accounted for a low explanation

(Pseudo R2= 0.189 and 0.0232 respectively). Using ordinary least square regression, Easterlin       3



established that unemployment as well as income was predictor of happiness.

       Happiness is related to subjective wellbeing which incorporates the negatives and

positives of how individuals experience their lives. People in different cultures, regions and cities

perceive wellbeing differently as measured by the personal wellbeing index. Spirituality and

religiosity are important additions to personal wellbeing.31 Subjective wellbeing is significantly

influenced by personality traits such as extraversion, neuroticism          and self esteem. Life

experience is also an important factor. Likewise, culture is important because of wealth, and the

normative values guiding the appropriate feelings and the perceived importance of subjective

wellbeing and the cultural tendencies of approach versus avoidance.32 Happiness is the extent to

which people favorably evaluate the overall quality of their life as a whole. As mentioned earlier,

this differs from the approach the UNDP uses to evaluating poverty in human development

which is arbitrary. People perceive happiness differently from the perspective of UNDP. Higher

level of education, better healthcare and increased income does not automatically increase

happiness. Therefore, the UNDP should integrate happiness in its analysis of poverty.33

Happiness is not a predictor of longevity among the sick but happiness is a predictor of longevity

among the healthy. This finding suggests that happiness cannot cure sickness but it is a buffer
                         34
against becoming sick.        . Others like Pavot and Diener35 and Watson and Clark36 have also

examined and established the importance of happiness and subjective wellbeing. .

       A comprehensive examination of the happiness and health status literature in the

                                                207
Caribbean in particular Jamaica found no empirical study that has assessed the happiness status

of older men. Concurrently, researchers have failed to evaluate health status, happiness, life

satisfaction of older men (ages 55+ years) in spite of the fact that in 2007 they constituted 13.2%

of the male population and 6.6% of the general population. This research studies happiness of

older men (ages 55+ years) in Jamaica. Further in the same period 15.5% of the population

reported having had an illness in a 4-wwek survey period compared to 40.2% of elderly 60+

years. Over a twenty year period (1988-2008), women outnumber men in seeking medical care

expect on 4 occasions, suggesting that not examining the subjective wellbeing of men is to

eliminate a critical approach in understanding their health behaviour and remedy the life

expectancy gap between males and females (6 years). Unlike Blanchflower and Oswald who

were able to show that wellbeing has declined in United States and Great Britain over the last 25

years, and that those findings were in keeping with the earlier works of Easterlin29, 30, this paper

is the first of its kind and forms the platform for other works in the area. The current study will

fill the gap in the literature by examining happiness, life satisfaction and health status in a single

research with particular reference to older men in Jamaica.

Method

Sample


       The study used primary cross-sectional survey data on men 55+ years from the parish of

St. Catherine in 2007. The survey was submitted and approved by the University of the West

Indies Medical Faculty’s Ethics Committee. Stratified multistage probability sampling technique

was used to draw the sample (2,000 respondents). A132-item questionnaire was used to collect

the data. Data were collected by way of a self-administered instrument. The instrument was sub-

divided into general demographic profile of the sample; past and current health status; health-

                                                 208
seeking behaviour; retirement status; social and functional status. Data was stored, retrieved and

analyzed, using SPSS for Windows version 16.0 (SPSS Inc; Chicago, IL, USA).


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts

(ED) or census tracts. The parish of St. Catherine is divided into a number of constituencies

made up of a number of enumeration districts (ED). The one hundred and sixty-two (162)

enumeration districts in the parish of St. Catherine provided the sampling frame. The

enumeration districts were listed and numbered sequentially and selection of clusters was arrived

by the use of a sampling interval. Forty (40) enumeration districts (clusters) were subsequently

selected with the probability of selection being proportional to population size.

       The sampling frame was men fifty-five years and older in the parish of St Catherine. The

parish of St. Catherine was chosen because previous data and surveys37-39 suggest that the parish

has the mix of demographic characteristics (urban, rural and age-composition) similar to

Jamaica.

Measures


Happiness. This is measured based on people’s self-report on their happiness. It is a Likert scale

question, which ranges from always to rarely happy. Health Status. This variable is measured

using people’s self-rate of their overall health status, which ranges from excellent to poor health

status. The question was ‘How would you rate your health today?’ (1) Excellent; (2) Good; (3)

Fair and (4) Poor. Education. What is [your] highest level of [education] attained? The options

were (1) no formal education; (2) basic school; (3) primary school/all age; (4)

secondary/high/technical school; (5) vocational (ie apprenticeship/trade); (6) diploma; (7)

undergraduate degree; (8) post-graduate degree. Physical Exercise. ‘Do you take time out for


                                                209
regular exercise?’ (1) yes and (2) no. Type of physical exercise. ‘ What do you do in terms of

exercise?’ Childhood illness. ‘Were you seriously ill as [a] child? (1) yes, (2) no. And, were you

frequently ill as a child? (1) yes, (2) no. If the response to either question was yes, this was

coded as poor childhood health status and if the response was no in both cases it was coded a

good health status in childhood. Age group is a categorized into three sub-groups. These are (1)

ages 55 to 64 years; (2) ages 65 to 74 years; and (3) ages 75 years and older (ie 75+ years).

       Performance of Activities of Daily Living (ADL) is used to describe the functional status

of a person. It is used to determine a baseline level of functioning and to monitor improvement

in activities of daily living (ADL) overtime. There are systems such as the Katz ADL that seek to

quantify these functions and obtain a numerical value. These systems are useful for the

prioritizing of care and resources. Generally though, these should be seen as rough guidelines for

the assessment of a patient’s ability to care for themselves. Scoring the ADL findings (Katz et

al)40-42 Independence on a given function received a score of 1 point while if dependent, 0 point

was given. There were 14 items (including daily activities; household chores; shopping; cooking;

paying bills). The reliability of the items was very high, α = 0.801. Total scores thus could range

from 0-14 with lower scores indicating high dependence and higher scores indicating greater

independence. Instrumental Activities of Daily Living (IADL). The IADL tool, Lawton &

Brody43 was the basis for assessing participants’ difficulty with IADL which are those activities

whose accomplishment is necessary for continued independent residence in the community. The

independent activities of daily living are more sensitive to subtle functional deficiencies than

ADL’s and differentiate among task performance including the amount of help needed to

accomplish each task. Due to the fact that the study was being conducted among men only,

some tasks which are normally done by women would not apply. Thus consistent with

                                               210
international practice, the University of Wollongong’s modified IADL functional ability scale

which uses a scale of 5 points for men and eight for women was used to assess the IADL

functional ability of men in the study44. Consequently the domains of food preparation, laundry

and housekeeping were omitted in this study with regard to the Instrumental Activities of Daily

Living for older men. Scoring the IADL. IADL scores reflect the number of areas of impairment

i.e. the number of skills/domains in which subjects are dependent. Scores range from 0-5. Higher

scores thus indicate greater impairment and dependence. Hence, Functional status is the

summation of ADL and IADL. Cohen and Holliday45 stated that correlation can be low/weak

(r=0–0.39); moderate (r=0.4–0.69), or strong (r=0.7–1). Hence, high dependence ranges from 0

to 5.5; moderate dependence is from 5.6 to 9.7 and low dependence (ie independence) ranges

from 9.8 to 14. Independence means without supervision, direction, or active personal assistance.

The performance on the functions can be further classified and analyzed using the format below.

The classification recognizes that combinations of independence/dependence with respect to

particular functions reflect the different degrees of levels of capability with respect to ADL. The

classification outlined above (as developed based on Katz et al 1970 and Katz et al40-42) was used

to further describe the functional status of men with regard to ADL and IADL.43,44

       Cognitive functionality (Mini-Mental Status Examination, ie MMSE) measures the

MMSE assessment (Kurlowicz, & Wallace46) is probably the most widely used measure of

cognitive functions. It has been suggested that the MMSE has been being helpful in the early

detection of Alzheimer’s disease. Elements of the Mini-Mental Status Examination tool used in

this study have been used internationally to assess the cognitive functional status of older

persons. Cultural and social aspects of the Jamaican culture were considered in re-designing

certain questions on the MMSE. For example on the question regarding the date of national

                                               211
independence, date of the Queen’s Birthday was an appropriate substitute. Hence a modified

version of the tool was used in this study. The questions for this study were (1) ‘What year is

this?’; (2) ‘What month is this?’; (3) ‘What day of the week is today?’; (4) ‘How old are you?’;

(5) Name the Prime Minister of Jamaica?’; (6) What year did Jamaica got Independence?’; and

(7) Repeat the 3 multiplications times?’. The domains of primary interest that were measured

were: orientation to time and the domain of registration of three words. One point was assigned

to each right answer and zero for each wrong answer. MMSE Index was the summation of the

each correct answer over the 7 items (α=0.620). Cohen and Holliday45 correlation valuations

were used to categorize MMSE into low/weak (r=0–0.39); moderate (r=0.4–0.69), or strong

(r=0.7–1). Hence, high MMSE ranges from 5 to 7; moderate MMSE is from 3 to 4 and low

MMSE (cognitive functionality) ranges from 0 to 2.

Statistical analysis

        Descriptive statistics was employed to provide background information on the sample;

chi-square was used to examine non-metric variables, and Ordered Probit Analysis was utilized

to establish the happiness model of older men in Jamaica. The confidence interval for the study

was 95% (ie level of significance was 5%). The exclusion criteria were 1) if more than 20% of

the cases of a variable were missing, and 2) strong correlation among the independent variables.

Cohen and Holliday45 correlation coefficients were used to establish correlation among the

independent variables. Low/weak was (0–0.39); moderate, (0.4–0.69); and strong, (0.7–1).

Strong correlation among or between independent variables distort the true impact that the

variable(s) will has/have on the dependent variable. Hence, the present study will mainly report

on the statistically significant variables.




                                              212
       The correlation matrix was examined in order to ascertain if autocorrelation (or

multicollinearity) existed between independent variables. This was used to exclude (or allow) a

variable in the model. Any of the independent variables which had moderate to high correlation

was excluded from the model. The correlation between life satisfaction and happiness was 0.633;

happiness and social networking (correlation coefficient = 0.12, P = 0.003); happiness and

marital status (correlation coefficient = 0.107, P = 0.026); marital status and income category

(correlation coefficient =0.193, P< 0.001); social networking and marital status (r=0.205,

P<0.001); social networking and age group (correlation coefficient = 0.188, P<0.001); social

networking and occupation (correlation coefficient =0.320, P< 0.001); social networking

educational category (correlation coefficient =0.420, P<0.001); ADL and age cohort (correlation

coefficient =-0.813, P=0.032); income and occupation (correlation coefficient =0.7775, P <

0.001); and, income and education (correlation coefficient =0.356, P<0.001); employment and

education category (correlation coefficient =0.283, P <0.001).         However, there was no

correlation between happiness and present occupation (p=0.761); happiness and income

(P=0.233); happiness and employment status (P=0.516); as well as life satisfaction and

employment status (P=0.261). Hence, life satisfaction and happiness; occupation and income

category will not be simultaneously used as explanatory variables.


Theoretical background

       According to micro econometric happiness function, subjective wellbeing (ie happiness)

is a function of different variables (including some demographic ones)9 [Model (1)].

       Wit = α + βXit + εit. …………………………………………………………….. [1]




                                              213
       Where Wit represents subjective well-being, Xit denotes x1, x2, x3, and so on, in which x1

to xn are variables – ‘sociodemographic’, ‘environmental’, and ‘social’, ‘institutional’ and

‘economic conditions.’

       In this study, the literature (ie micro econometric happiness function) will be expanded to

include health status in childhood, current health status, life satisfaction, and area of residence by

testing this theory using elderly men in Jamaica [Model (1)]. In addition to the aforementioned

micro econometric happiness function, the study will also seek to examine health status.

Variables such as happiness, life satisfaction and some demographic variables will be

investigated simultaneously [Model (2)].

Estimation Model

       The interests of this study are to examine whether happiness can be predicted by health

status as well as employment status, self-reported childhood and current health status on

happiness of elderly men in Jamaica in addition to other socio-demographic variables.

Continuing, it is also to investigate whether self-reported happiness differentiate rural and urban

older men in Jamaica. The multivariate model used in the current study is an expansion of the

literature which is displayed in equations (2).


HAPPit = β0 + β1HSit + β2HSi(t-1) + β3EMit+ β4FSit+ β5CFit + β6Pit +βijDij+ εi …….....[2]



where HAPPit denotes happiness of person i in time period t (current period); HSit means health

status of person i in current time period t; HSi(t-1) denotes the childhood health status of period i

previous period (t-1); EMit is employment status of person i in current time period (t); FSit is

functional status of individual i in current time period t; CFit is cognitive functioning of

individual i in time period t, and Pit is physical exercise of person i in time period t. Dit = d1, d2,

                                                  214
d3, d4…..dn, which include sociodemographic (such as home ownership, social support, church

attendance) and socioeconomic of individual i in current time period (t). β0 indicates happiness at

the beginning of the period; β1 to βij denotes the parameter for each variable from variable 1 to j.


        Because the dependent variable for the current study, happiness, is a non-binary one,

ordered probit analysis was used to estimate the impact of current health status, childhood health

status, including other socio-demographic variables (such as employment status, education,

marital status, age of elderly, social support, and church attendance) on happiness of elderly men

in Jamaica. Furthermore, the current study will mainly report the results of those variables that

are statistically significant (p<0.05) [Eqn. (3)].


HAPPit = β0 + β3EMit+ β4FSit+ βijDij+ εi …………………………………………………...………...[3]


Results: Socio-demographic Characteristics of Sample

        The sample was 2,000 men ages 55+ years (42.6% were 55 to 64 years; 35.6% were 65 to

74 years; 21.9% 75 years and older). Fifty one percent of the sample lived in rural areas, 59.1%

had social network, 55.4% reported good health, 53.9% were retired, 25.6% were actively

employed, 58.8% did not own their homes, and 34.3% were single and 44.7% were married

elderly. Majority of the sample had primary or elementary level education (83.1%); 85.9%

reported that they do not regularly exercise; 82.5% reported good health in childhood; and

88.12% were heads of their households (Table 1). One half of the sample indicated that they

spent Ja.$100 (US $1.45) monthly for medical expenditure; 34% of the respondents bought their

prescribed medication; 17.1% reported that they have been hospitalized since their sixth birthday

and 65.8% reported that they took no medication. Of those who mentioned that they were ill

during childhood (17.5%, n=350), 34.9% said that the illness was measles or chicken pox, 26.3%

                                                     215
mentioned asthma, 10.0% pneumonic fever, 8.9% polio, 6.6% accident, 4.6% jaundice, 1.7%

hernia, and 5.1% indicated gastroenteritis. Twenty four percent of elderly men indicated that they

were rarely happy, 40.5% said sometimes, 31.0% mentioned often and only 4.5% reported

always. Furthermore, 17.7% of the sample reported that they were seriously ill as children.

       Eight percentage of sample reported that they sought medical care whenever they are ill;

25.4% knew the name of the medication that they were taking; 38.5% had a retirement health

plan; 28.4% mentioned that good health is ‘physical wellness’, 9.5% said healthy diet, 3.7%

claimed ‘psychological wellness’, 0.7% functional ability, and 2.0% reported religious activities.

In addition, 82.5% of the sample did not respond to the question on health treatment, 7.8%

indicated that they used home remedy (include healers), 2.0% said hospitals and 6.2% mentioned

clinics, with 1.6% said private doctors. Sixty seven percent of the sample reported doing some

form of physical exercise in the survey period.

       Twenty-four percentage of the Jamaica older men reported that they were rarely happy

compared to 5% who indicated that they were always happy (Table 1). Majority of the sample

indicated low functional dependence (89.6%), with 1.2% claimed high dependence on other

person for physical activities (Table 9.1).

       Happiness is not significantly correlated with health status - χ2 (df=6) = 3.333, P = 0.766

(Table 9.2).

       A significant statistical association existed between happiness and life satisfaction - χ2

(df=9) = 1334.448, P = 0.001; with a strong correlation, contingency coefficient = 0.833 (Table

3). Only 2.4% of sample that indicated rarely satisfied with life was always happy compared to

60% of always satisfied with life that was always happiness. However, 1.5% of those who

indicated that they were satisfied with life sometimes were always happy (Table 9.3).

                                                  216
         A cross-tabulation between health status and life satisfaction revealed no significant

statistical relation - χ2 (df=6) = 4.07, P = 0.667 (Table 9.4).



Multivariate Analysis



Using probit analysis, the study tested equation [2] of which happiness being the dependent

variable. Employment status, functional status and one sociodemographic variable (ie church

attendance) were found to be predictors of happiness of older men in Jamaica. Employed older

men in Jamaica had the greatest happiness, with retired older men accounted for the least

happiness (Table 5). Older men who attended church had greater happiness than those who do

not attend (Table 5); and that functional status was negatively related to happiness in older men

in Jamaica. The model [ie. Equation (2)] is a good fit for the data (χ2= 2,361.773, P <0.001).


         Unemployed older men’s coefficient has a small standard error (Columns 1 & 2), which

means that the gap between happiness of older unemployed and retired older men is small (Table

5). Similarly, the gap between the happiness of elderly employed men and retired men was small

(ie standard error); and the standard error of functional status was low and indicated that the

disparity in happiness between elderly men who had greater functional status was marginally

lower.


Limitations to study


         A single cross-sectional survey cannot be used as the only basis upon which policies

should be altered; but it forms a platform with which we can begin to examine the health of older

men outside of the traditional objective indexes of health. Another limitation of the study is the

                                                 217
fact that individuals could be retired and actively involved, and this was not examined in the

survey. In addition to the others, the study was unable to examine income’s effect on happiness

as only 25% of the sample was employed and in hindsight no question was asked on

consumption or total expenditure which could have been used to measure income. Another

limitation is that participants sometimes give inaccurate information in their self reports.


Discussion


       This study examined the health, life satisfaction and wellbeing of older men. The

empirical research has established that happiness is a good measure of health (or subjective

wellbeing). In keeping with broader conceptualization of health, happiness is a better measure of

health than life expectancy, mortality, morbidity or even self-reported health conditions. Over

the last 2 decades, the Planning Institute of Jamaica and the Statistical Institute of Jamaica have

relied on self-reported health conditions, life expectancy, mortality, morbidity and health care-

seeking behaviour in assessing the health status of Jamaicans. The current study found that 24

our of every 100 older men in Jamaica were rarely happiness; 5 out of 100 indicated a moderate

health status and that there was no significant statistical correlation between happiness and health

status; but one existed between happiness and life satisfaction. This study highlights that health

status and happiness as well as health status and life satisfaction are not good predictors of

subjective health as they are not statistical correlated. However, happiness and life satisfaction

are good measures of subjective health as they are moderately related with each other.


       The correlation between happiness and life satisfaction was greater in this study

(correlation coefficient was 0.633) than that in Di Telli et al’s study. The disparity between both

studies did not cease there as substantially more people in the United States were very happy (33

                                                218
out of every 100) than in this sample (5 out of 100); and the figure for males was 33 out of 100.

More than 100% more older men in this study were rarely happy compared to male Americans

(11.7%). The disparity continues as 7.7 times more males in the Europe were very satisfied with

life (or always satisfied) compared to elderly males in Jamaica. On the other side of the life

satisfaction spectrum (ie rarely satisfied or not at all satisfied), 6.8 times more elderly males in

Jamaica reported rarely satisfied compared to European males.

                                     47
       Subramanian et al.’s work          found that people with physical disabilities had similar

levels of happiness as fully functional people.


       An interesting conclusion of the current study, which concurs with the literature, is the

correlation between happiness and employment status. The literature showed that the

unemployed men had lower happiness than employed people15, and this went further as it found

that the retired elderly men were less happy than the employed; but greater than that for the

unemployed. Apart of the explanation for this is may be embedded in psychological state of men

post employment which includes 1) the lost social networks, 2) joblessness, 3) the reduced

income, and lowered levels of self-respect. Happiness, according to Easterlin6 is associated with

wellbeing, and so does ill-being (for example depression, anxiety, dissatisfaction). Easterlin6

argued that material resources have the capacity to improve someone’s choices, comfort level,

state of happiness and leisure, which militates against static wellbeing. The reverse is true as

retirement means not having access to income from employment, and thereby reduces people’s

capacity to purchase material and other resources. Outsides of those realities, self-respect and

social relationships are linked to employment, and a group of scholars found that the impact of
                                                                48
unemployment is even greater than the loss income,                   re-emphasizing the negative


                                                  219
psychological state which accompanies unemployment as well as retirement. This offers some

explanation for the negative relation between unemployment and life satisfaction, and

unemployment and happiness as an aspect to people’s quality of life is reduced and these are not

captured in life expectancy measurement. If retirement comes with other social involvement, the

effects of unemployment will mitigate against and this may not eliminate the loss of

unemployment as it may not offset the degree of socio-economic lost job.


       Two economists studied the ‘impact of wealth and income on subjective wellbeing and

ill-being’; they found that employed people had a higher life and financial satisfaction than their

unemployed counterparts49. Using linear regression analysis, researchers47 found that the

employed had a coefficient of 0.77 in life satisfaction compared to unemployed -3.00; and in the

case of financial satisfaction it was 5.52 and -11.52 respectively. Another study provides further

explanations for lower happiness among retired and unemployed persons than employed

individuals. The Cornel Study of Retirement “estimated that the average retired person’s income

declined to 56 percent of pre-retirement income”50 Palmore50 argued that ‘tax advantage’,

‘housing subsidies’, ‘Medicare’ and ‘income tax’ exemptions offset this. However, for the retired

person in Jamaica, there is no such thing as housing subsidy, and the National Drug for the

elderly programme coverage is minimal and thereby goes not offset the income from

employment. Men substantially tie their success with the ability to provide and this is how

important income and employment are. Hence, by not paying income tax and receiving social

and other types of assistances, this deteriorates the psychological state of men and accounts for

the lowered happiness. The inverse correlation between subjective wellbeing and unemployment

extends beyond that relation to unemployment causing depression, anger, anxiety, loss self-

esteem and disruption in social life. A group of researchers found that even after controlling for

                                               220
fall in income, unemployment inversely influence wellbeing.51


       There is little debate within the public arena about the increasing decline of the labour

force participation rate of aged Jamaicans. In 1980, the labour force participation rate (in %) was

46.4% and it is estimated to be 26.6% in 2007. This represents a 43% reduction in the number of

aged persons ≥ 65 years who were actively involved in the labour force. When the labour force

participation rate is decomposed by gender, the figures reveal a more telling disparity. As for

females, in 1980, there were 30.4% of women actively involved within the labour force, but it is

estimated to be 13.8% in 2007, which is a 55% reduction in the number of employed females.

With respect to males’ involvement in the labour force, it is projected to fall to 41.4% in 2007,

which is coming from 65.3% in 1980. The labour force participation rate for men will fall by

23% compared to that of females that will decline by 55%. This is within the context of females

living longer than their male counterparts, and that the retirement age for females is 60 years and

not 65 years. Therefore, if we are to extrapolate a reduced 5 years for females, the labour force

participation rate will increase further by at least a percentage point.


       With retirement and unemployment at older ages (60 years and older for women and 65

years and older for men), the family and other social network must replace this lost income.

Statistics from the Planning Institute of Jamaica and the Statistical Institute of Jamaica52 showed

that 26.6% of Jamaica received remittances and that the rate rose by 57% (to 41.8%), which

emphasizes the role of the family and social support in supplementing income of man people

including the retired and unemployed elderly men. Eldemire53 agreed with this finding, when she

opined that the loss of financial resources (ie income or employment) result in changes in the

lifestyle practices of older peoples as retirement result of changes in their financial base.


                                                 221
Unemployment or retirement means that those people must now use their past savings

(dissavings) or social support to meet current food and other expenditures. This means that

financial inadequacies will prevent the individual from accessing food and nutritional needs as

well as the inability to meet utilities and other expenses.


       The issue of resource insufficiency affects the ability and capacity of the poor elderly and

other older unemployed and retired men from accessing the quality of goods and services

comparable to the rich that are better able to add value to wellbeing and by extension their

happiness with life. This study disagrees with Di Tella et al.’s work16 which found the least

happiness for the unemployed; but both research agree that the employed had the greatest level

of happiness, indicating that these are constant across America and some European nations as

well as in developing states like Jamaica.


       According to Kart55, religious guidelines aid wellbeing through healthy behavioural

habits such as smoking, drinking of alcohol, and even diet. Researchers found that a positive

association exists between religion and wellbeing.55,     56
                                                               Using church attendance to measure

religious status of older men, this work supports the literature that happier people attend church

than those who do not. The relationship was even stronger for men than for women, and that this

association was influenced by denominational affiliation.        Graham et al’s study57 found that

blood pressure for highly religious male heads of households in Evan County was low. The

findings of this research did not dissipate 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 than those with weaker adherence.58


       Aged individuals experience changes in sensory processes, perception, motor skill and

                                                 222
problem-solving ability. Their perception, self-esteem, drives, mental health status, and emotions

are frequently altered3,48,59-62 because of the psychological and physiological changes caused

through psychopathological conditions of ageing. People’s cognitive responses to ordinary and

extraordinary situational events in live are associated with different typology of wellbeing. 60 It is

found that happier people are more optimistic and as such conceptualize life’s experiences in a

positive manner. Studies revealed that positive moods and emotions is associated with wellbeing
61
     as the individual is able to think, feel and act in ways that foster resource building and
                                                       62
involvement with particular goal materialization.           This situation is later internalized, causing

the individual to be self-confident from which follows a series of positive attitudes that guides

further actions.63 Positive mood is not limited to active responses by 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.


          An interesting finding of this paper is the explanatory power of the micro-econometric

happiness equation. The micro-econometric happiness equation of the current study was 32%,

which is greater that in Blanchflower and Oswald’s work15 (Pseudo R2=4.4% for men in the

United States). Although Di Tella et al’s work16 was not on older men, they found that majority

of men in the United States were pretty happy (56 out of every 100) which was similar for older

men in Jamaica (41 out of every 100). Only 12 out of every 100 men in the United States

reported being ‘not too happy’ compared to 24 out of every 100 older men in Jamaica (ie. ‘rarely

happy). The work of Di Tella et al. used data from the 1970’s to the 1990’s and the present

study used data for 2007, so the disparity may be wider or narrower in 2007 for both nations.



                                                 223
       The literature empirically established that happiness is correlated with health status; but

no study found a strong relation between those two variables. Easterlin 19 found that since World

War II in developed nations, the association between those aforementioned variables is negative

and even non-existence. This study concurs with Easterlin as no significant correlation was

found between the variables in question.


       The current study provides some critical findings in the understanding of older men in

Jamaica. Happiness is not statistical correlated with health status as well as life satisfaction and

health status, while life satisfaction and happiness are good measures of subjective health (ie

wellbeing). Interestingly therefore is that not all three subjective indexes (life satisfaction,

happiness and health status) are good measures of each other. Employed older men are happier

than unemployed ones; and that spirituality increases happiness and by extension life satisfaction

of older men in Jamaica. This paper contradicts the literature that life satisfaction, happiness and

health status are synonymous measures. Although the present research shows that the afore-

mentioned measures are no all synonymous, the limitation of only using older men does not

invalidate the findings. Thus, this adds information to the current literature but the issue as to

whether this hold true for the same cohort of females and the younger population are still

unresolved and need further examination.


Conclusion


       In sum, happiness is strongly related to life satisfaction but not to health status, and life

satisfaction is not statistically associated with health status, suggesting that older men make a

distinction between happiness as well as life satisfaction and health status. This denotes that

satisfaction with life and happiness are good proxy for each other, but neither life satisfaction nor

                                                224
happiness are associated with health status. The present study highlight a differential in the three

identified variable as older Jamaicans generally view health as illness and so happiness and life

satisfaction is a more holistic measure than health status. Thus, happiness or life satisfaction

cannot be used as independent variable in each other’s model. Health is a narrower measure for

quality of life than life satisfaction or happiness. Inspite of the broad definition of health as was

forwarded by WHO in the late 1940s, health for older men in Jamaica is still narrowly

conceptualized and cannot be used to measure quality of life (or subjective wellbeing) like

happiness or life satisfaction.


       There is also the issue of gender where the literature suggest that less women are apart of

the labor force than men. This situation, the feminists argue, is due to the glass ceiling in the

society which denies Jamaican women their rights and opportunities because of their gender. The

role of the glass and grey ceilings on the wellbeing of older Jamaican women should be

researched. This is another double burden in addition to the well known double burden of

professional work and housework that constrains the professional and economic success of

women and hence their wellbeing. The findings are far reaching can be used to influence patient

care outcome as well as other policy intervention programmes.


Competing Interest:

None declared.




                                                225
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                                          229
        Table 9.1: Socio-demographic Characteristics of Sample
Variable                                                       Frequency   Percent
Cognitive Functionality
    Low                                                               19       1.0
    Moderate                                                          99       4.9
    High                                                            1882      94.1
Functional Status
    High dependence                                                   24       1.2
    Moderate dependence                                              184       9.2
    Low dependence                                                  1792      89.6
Age group
    55- 64 years                                                     851      42.5
    65 – 74 years                                                    712      35.6
    75 years and older                                               437      21.9
House Ownership
    Yes                                                              824      41.2
    No                                                              1176      58.8
Employment Status
    Employed                                                         511      25.5
    Unemployed                                                       412      20.6
    Retired                                                         1077      53.9
Happiness
   Rarely                                                            480      24.0
   Sometimes                                                         810      40.5
   Most times                                                        620      31.0
   Always                                                             90       4.5
Self-rated Health Status
    Excellent                                                        357      19.0
    Good                                                            1038      55.4
    Fair                                                             480      25.6
Social Networking
    Yes                                                              817      59.1
    No                                                              1183      40.9
Regular Exercise
    Yes                                                              282      14.1
     No                                                             1718      85.9
Childhood Health status
   Good                                                             1650      82.5
   Poor                                                              350      17.5
Area of residence
   Urban                                                             981      49.0
   Rural                                                            1019      51.0



                                           230
Table 9.2. Happiness and Health Status

Happiness                                   Health status
                           Excellent         Good         Fair (Moderate)        Total
                                   n (%)         n (%)              n (%)        n (%)
Rarely                          86 (24.1)    261 (25.1)         107 (22.3)   454 (24.2)
Sometimes                      137 (38.4)    424 (40.8)         202 (42.1)   763 (40.7)
Most times                     117 (32.8)    313 (30.2)         148 (30.8)   578 (30.8)
Always                           17 (4.7)      40 (3.9)           23 (4.8)     80 (4.3)
Total                                357          1038                480         1875
χ2 (df=6) = 3.333, P = 0.766




                                                 231
Table 9.3. Happiness and life satisfaction

                                                                Life Satisfaction
 Happiness                                Rarely           Sometimes        Most times      Always         Total

 Rarely                                    348 (52.9)           82 (12.2)       40 (6.7)   10 (14.3)   480 (24.0)



                                           172 (26.2)          466 (69.1)     160 (26.7)   12 (17.1)   810 (40.5)
 Sometimes



                                           122 (18.5)          116 (17.2)     376 (62.9)     6 (8.6)   620 (31.0)
 Most times



                                             16 (2.4)            10 (1.5)       22 (3.7)   42 (60.0)     90 (4.5)
 Always

 Total
                                                   658               674            598          70         2000

Χ2 (df = 9) = 1334.448, P = 0.001, contingency coefficient = 0.833




                                                         232
Table 9.4. Health status and life satisfaction

                                                 Life Satisfaction
 Health status                  Rarely       Sometimes     Most times      Always        Total

 Excellent                      113 (18.4)   112 (17.5)     121 (21.7)     11 (17.7)    357 (19.0)



                                346 (56.3)   358 (55.8)     299 (53.7)     35 (56.5)   1038 (55.4)
 Good



                                156 (25.4)   171 (26.7)     137 (24.6)     16 (25.8)    480 (25.6)
 Fair

 Total                                615            641             557         62          1875


χ2 (df = 6) = 4.07, P = 0.667




                                                   233
Table 9.5: Happiness Equation for Older Men in Jamaica (Ordered Probit Regression)

Dependent     variable:    Reported
Happiness
                                        Coefficient     Z        P       CI (95%)
 Unemployed                                0.164      2.386 0.017      0.029 - 0.300
 Employed                                  0.213      3.411 0.001      0.091 - 0.335
 Functional status Index                  -0.035     -2.779 0.005     -0.060 - -0.010
 Logged Cognitive functioning Index        0.005      0.037 0.970     -0.232 - 0.241
 Dummy Home Dwelling                      -0.080     -1.404 0.160     -0.193 - 0.032
 Dummy Brother Alive                      -0.103     -1.296 0.195     -0.259 - 0.053
 Dummy Sister Alive                        0.019      0.283 0.777     -0.114 - 0.153
 Dummy Exercise                            0.012      0.190 0.850     -0.114 - 0.138
 Dummy Mother Alive                       -0.019     -0.266 0.790     -0.160 - 0.122
 Dummy Father Alive                       -0.076     -0.888 0.374     -0.244 - 0.092
 Dummy Have Children                       0.005      0.035 0.972     -0.264 - 0.273
 Dummy Education                           0.105      1.037 0.300     -0.093 - 0.303
 Church Attendance                         0.192      2.574 0.010      0.046 - 0.338
 Social Support                            0.154      1.871 0.061     -0.007 - 0.315
 Urban Area                               -0.033     -0.632 0.528     -0.136 - 0.070
 Childhood Health Status                  -0.022     -0.365 0.715     -0.141 - 0.097
 Current Health Status                    -0.019     -0.296 0.767     -0.148 - 0.109
 Intercept                                -0.719     -2.422 0.015     -1.016 - -0.422
Pearson Goodness of fit Test - Chi-square = 2,361.773, P < 0.001
n = 1,873
Pseudo R2 = 0.320
Log likelihood = 755.268




                                            234
                                                                               Chapter 10


Social determinants of physical exercise in older men in Jamaica


C. Morris, PA. Bourne, D. Eldemire-Shearer, DA. McGrowder



Physical activity interventions have been demonstrated to improve health-related quality of life
and to be of special benefit to older adults with specific chronic conditions including arthritis,
hypertension, diabetes mellitus, and heart disease. This study examined the extent and social
determinants of physical exercise in elderly men in Jamaica. A sample of 2,000 men 55 years of
age and older was extracted from a total of 33,674 males in the parish of St Catherine. A 132-
item questionnaire was used to collect the data. A stratified random sampling technique was
used to draw the sample. Descriptive statistics were used to provide background information on
the sub-sample, and logistic regressions were utilized to model physical exercise. Of the
respondents 55.4% indicated good health status, 51.0% lived in rural areas; 10.4% had moderate
to high functional dependence and 67.3% reported that they did some form of physical exercise.
Of those who indicated involvement in physical exercise (n = 1,345), 77.2% jogged, ran, and/or
walked; 13.3% did aerobics; 4.7% swam; 2.0% cycled and 0.6% did push-ups or sit-ups. The
variables that predicted being engaged in physical exercise were education; age of respondents;
current good health status; household head; health plan; employment status and social support.
Most of the elderly men were engaged in some form of physical activity and had good health.
Age and good health status were the most influential social determinants of physical exercise.
However, effective interventions to promote physical activity in older men in Caribbean
countries such as Jamaica deserve wide implementation.




                                               235
Introduction

The Caribbean has been identified as the most rapidly ageing region of the developing world.

Between 1960 and 1995, there was a 76.8% increase in the elderly population. [1] Among its

regional island states, the average growth rate in the elderly population was approximately 5.3%

for the period between 1995 and 2000. [1] Jamaica has a population of approximately 2.6 million

and has undergone a significant demographic transition in the last 5 decades. [2-3] Some features

of this transition include the increase in the median age of the population from 17 years to 25

years between 1970 and 2000, the doubling of the proportion of persons older than 60 years to

over 10% and the increase in life expectancy at birth from less than 50 years in 1950 to greater

than 70 years in 2000. [4] The main causes of illness and death in Jamaica and many other

Caribbean islands and regions at a similar state of development are chronic non-communicable

diseases. [5]


       There is heightened concern within the Caribbean regarding the need to implement

comprehensive health promotion programmes aimed at the prevention and control of chronic

diseases. [6] Heart disease, hypertension, diabetes and cancer are currently the major conditions

affecting the health of adults in the Caribbean, and they impose a significant burden in terms of

long-term illness, disability and death. [7] The significance of these conditions is reflected in

prevalence rates. Diabetes-related deaths in 1994 had increased 147% over the 1980 level,

representing the third leading cause of loss of years of potential life among women, and the tenth

among men. [8] The English-speaking Caribbean has the highest mortality from this cause in all

the sub-regions of the Americas.



                                               236
       Physical inactivity, a known modifiable risk factor for future disability, also increases

with age. [9, 10] Physical activity interventions have demonstrated multiple benefits among

older adults, including improved functioning and health-related quality of life, [11, 12] and

decreased levels of depression. [13] Physical activity has also been shown to benefit older adults

with specific chronic conditions, including rheumatoid arthritis, heart disease, and diabetes

mellitus. [14] Specifically, studies show that regular physical activity reduces the risk of dying

prematurely and of developing diabetes mellitus, hypertension, and colon cancer; it also reduces

feelings of depression and anxiety, helps control weight, maintains bone mineral density, and

promotes psychological well-being. [15, 16]


       Despite these documented benefits, estimates suggest that 33% of men and 50% of

women over the age of 75 are not engaged in any physical activity. [17] The prevalence of

inactivity varies by racial and ethnic group and by gender, from 47% in White women aged 75

and older to 59% in older Black men and 61% in older Black women. [18] In addition, past

estimates suggest that, of older adults who engage in any physical activity, only 25% aged 65 to

74 and 15% aged 75 and older meet the recommendations for vigorous or moderate physical

activity. [17] Data on physical activity levels in Jamaica and Trinidad & Tobago indicate that

individuals may be experiencing difficulty in initiating and sustaining desired exercise

behaviour. A national study recently conducted in Jamaica revealed that only 21.6% of the

sample participated in planned exercise. [19] In Trinidad, participation rates were even lower,

with 16.6% of men and 5.9% of women reporting that they were taking regular exercise. [20]



       Increasing attention is being placed on preventing and delaying the onset of chronic

diseases among the elderly in order to extend the duration of functional well-being and healthy

                                               237
life expectancy. In addition to new evidence regarding the importance of exercise and physical

activity for healthy older adults, there is now a growing body of knowledge supporting the

prescription of exercise and physical activity for older adults with chronic diseases and

disabilities. Until a relatively short time ago, published evidence on the health of the elderly in

developing nations was lacking and there is little research in the English-speaking Caribbean that

examines exercise and physical activity in the elderly. This study examined the extent of

engagement and the socio-determinants of physical exercise in elderly men in Jamaica.


Materials and Methods
       The study used primary cross-sectional survey data on men 55 years and older from the

parish of St. Catherine in 2007; it is also generalizable to the island. The survey was submitted

and approved by the University of the West Indies Medical Faculty’s Ethics Committee. A

stratified multistage probability sampling technique was used to draw the sample, and a 132-item

questionnaire was used to collect the data. The instrument was sub-divided into general

demographic profiles of the sample; past and current good health status; health-seeking

behaviour; retirement status; social and functional status. The overall response rate for the survey

was 99% (n = 1,983).


       The Statistical Institute of Jamaica (STATIN) maintains a list of enumeration districts or

census tracts in all parishes in Jamaica including St. Catherine. The parish of St. Catherine was

chosen, as previous data and surveys [21, 22] suggest that it has the mix of demographic

characteristics (urban, rural and age-composition) which typify Jamaica. The parish of St.

Catherine had approximately 233,052 males, (preliminary census data 2001) of which 33,674

males were 55 years and older. St. Catherine is divided into several constituencies made up of a


                                                238
number of enumeration districts. The one hundred and sixty-two enumeration districts in the

parish of St. Catherine provided the sampling frame. The enumeration districts were listed and

numbered sequentially and the selection of clusters was arrived at by the use of a sampling

interval. Forty enumeration districts (clusters) were subsequently selected with the probability of

selection being proportional to population size. Using advice from STATIN and the C-Survey

computer software (University of California at Los Angeles and University of Indonesia 1997), it

was determined that 50 elderly men in each enumeration district were interviewed yielding a

sample size of 2,000.


          Measures


          Happiness: This is measured based on people’s self-reporting on their happiness. It is a

Likert scale question, which ranges from always to rarely happy. Health Status: This variable is

measured using people’s self-rating of their overall health status, which ranges from excellent to

poor health status. Questions in the 132-item questionnaire include socio-demographic variables

such as education attained, engagement in regular physical exercise, type of physical exercise

and health status as a child. The age group was categorized into three sub-groups. These are (1)

ages 55 to 64 years; (2) ages 65 to 74 years; and (3) ages 75 years and older (i.e. 75 years and

older).


          Functional status is the summation of Activities of Daily Living (ADL) and Instrumental

Activities of Daily Living (IADL). Performance of ADL is used to describe the lower functional

status of a person. There are systems such as the Katz ADL tool that seek to quantify these

functions and obtain a numerical value. [23] These are useful for the prioritizing of care and

resources. Scoring the ADL findings (Katz) Independence on a given function received a score

                                                239
of 1 point while if dependent, 0 point was given. [24] There were 14 items (including daily

activities, household chores, shopping, cooking and paying bills). The reliability of the items was

very high, α = 0.801. Total scores ranged from 0-14 with lower scores indicating high

dependence and higher scores indicating greater independence. The IADL tool [25] was used for

assessing participants’ difficulty with the complex task of daily living.        The independent

activities of daily living are more sensitive to subtle functional deficiencies than ADL’s, and

differentiate among task performance, including the amount of help needed to accomplish each

task. Due to the fact that the study was being conducted among men only, some tasks which are

normally done by women would not apply. This is consistent with international practice, the

University of Wollongong’s modified IADL functional ability scale which uses a scale of 5

points for men and eight for women was used to assess the IADL functional ability of men in the

study. [26] Consequently the domains of food preparation, laundry and housekeeping were

omitted in this study with regard to the IADL for older men. The IADL scores reflect the

number of areas of impairment i.e. the number of skills/domains in which subjects are

dependent. Scores range from 0-5. Higher scores thus indicate greater impairment and

dependence. Cohen and Holliday [27] stated that correlation can be low/weak (0 - 0.39);

moderate (0.4 - 0.69), or strong (0.7 - 1). Hence, high dependence ranges from 0 to 5.5; moderate

dependence is from 5.6 to 9.7 and low dependence (i.e. independence) ranges from 9.8 to 14.

Independence means without supervision, direction, or active personal assistance. The

performance on the functions can be further classified and analyzed using the format below. The

classification recognizes that combinations of independence/dependence with respect to

particular functions reflect the different degrees of capability with respect to ADL. The

classification was used to further describe the functional status of men with regard to ADL. Also,

                                               240
as in Cohen and Holliday [27] correlation coefficients were used in the present study to exclude

(or allow) a variable. Any variable that had a high correlation was excluded, as well as any

variable that had a non-response rate in excess of 20 percent.



          Statistical Analyses

          Data were stored, retrieved and analyzed, using SPSS for Windows (16.0). For the

current study descriptive statistics (frequency, percentages) were employed to provide

background information on the sample; and chi-square was used to examine non-metric

variables. Logistic regression was used to examine a binary dependent variable (i.e. physical

exercise) and some socio-demographic variables (such as employment status, current health

status, and health status in childhood, number of brother(s) and/or sister(s) alive). The level of

significance was P < 0.05 and the only exclusion criteria were if more than 20% of the cases of a

variable were missing.




          Model


           In order to examine the effect of many variables on a single dependent variable, the

researcher used multivariate analysis to test a single model. Using the literature the current study

investigates the correlates of physical exercise of older Jamaicans within the context of the

available data. The proposed model that this research seeks to evaluate is displayed (Eqn1):


Ei = ƒ(Hti, HAPPi, LSi ,Ci, ARi , Ai, SSi, CAi , EDi , HHi, MSi, Pi, HEAi, EMi, Di,TMi, AMi, Fi, HPi,

HOi, CFi, ∑Xij, εi)............................................................................................................[1]


                                                                    241
Where Ei (physical exercise) is a function of current good health status of person i, Ht; happiness,

HAPPi; life satisfaction, LSi; children, Ci; area of residence, ARi; age group of respondent, Ai;

social support, SSi; church attendance, CAi; educational level, EDi; head of household, HHi;

marital status, MSi; number of person in household, Pi; poor health status in childhood, HAi;

employment status, EMi; self-reported depression, Di; taking medication, TMi; health advise,

HEAi; functional status, Fi; health plan, HPi; cognitive functionality, CFi; Xij is a vector of

siblings alive of respondent i, which number of brother(s) and/or sister(s), and functional status,

FSi.


         All the variables were identified from the literature. Using the principle of parsimony,

only those explanatory variables that were statistically significant (p <0.05) were used in the

final model to determine εi (i.e. physical exercise) of older men in Jamaica. This final model

identified the correlates of εi of older men in Jamaica (Eqn 2).


Ei = f(EDi, Ai, Ht, HHi, HPi, EMi, SSi, εi)……......................................................................[2]


Results
         Demographic Characteristic

         Of the respondents (n = 2,000), 82.5% indicated that they had good health in their

childhood; 55.4% reported current good health status; 51.0% lived in rural areas; 3.5% were

mostly satisfied with life; 10.4% had moderate to high functional dependence; 89.6% had low

functional dependence (i.e. independence); 21.9% were aged 75 years and older; 35.6% were

aged 65 to 74 years and 42.6% reported ages 55 to 64 years. In addition, 94.1% had high

cognitive function and 67.3% reported that they do some kind of physical exercise (Table 10.1).


                                                           242
One half of the sample indicated that they spent Ja. $100 (US $1.45) monthly for medical

expenditure; 34% of the respondents bought their prescribed medication; 17.1% reported that

they had been hospitalized since their sixth birthday and 65.8% reported that they took no

medication. Concurringly, 17.7% of the sample reported that they were seriously ill as children

and 17.5% indicated that they were frequently ill during childhood. Almost 35% reported that the

illness was measles or chicken pox, 26.3% indicated asthma, 10.0% pneumonic fever, 8.9%

poliomyelitis, 6.6% accident, 4.6% jaundice, 1.7% hernia, 9.2% hypertension, and 5.1%

indicated gastroenteritis. Twenty four percent of elderly men indicated that they were rarely

happy, 40.5% said sometimes, 31.0% mentioned often and only 4.5% reported always.



       Table 10.2 revealed that of those who indicated involvement in physical exercise (n =

1,345), 77.2% jogged, ran, and/or walked; 13.3% did aerobics; 4.7% swam; 2.0% cycled and

0.6% did push-ups or sit-ups. Further examination of physical exercise by area of residence

indicated that there was no statistical association between the two variables (χ2 square =10.60, p

= 0.101); Table 10.3.



Multivariate analyses

Of the 22 variables tested in the current study [Eqn. (1)], 7 of them were found to predict

physical exercise [Model (2)] (Table 10.4). These variables are education; age of respondents;

current good health status; household head; health plan; employment status and social support.

The model [Eqn (2)] used in the study had a statistically significant predictive power (model

χ2 (24) =161.609, p < 0.001; -2 Log likelihood = 327.591; Hosmer and Lemeshow [28] goodness

of fit χ2 = 5.456, P = 0.708). From the classification matrix, overall, 90.8% of the data were

                                               243
correctly classified: 97.3% of cases of physical exercise and 34.2% of cases that do not perform

physical exercise. Furthermore, 40.6% of the variability in physical exercise can be explained by

7 predictors.



       There was no multi-collinearity among variables because the correlation matrix has

correlations of less than 0.55. The correlation between happiness and life satisfaction was 0.481

(r-squared). The correlation between self-reported depression and life satisfaction was r = 0.138,

and between employment status and elderly (ages 65 to 74 years), r = 0.301. The correlation

between health status and happiness was r = 0.035; self-reported depression and functional status

r = 0.150; self-reported depression and poor childhood health status r = 0.110; and church

attendance and social support r = 0.524. In addition, the association between functional status

and cognitive functionality was r = - 0.164.


       Of the 7 predictors of physical exercise in older men, age (ages 65 to 74 years: Wald

statistic = 5.338, OR = 0.392, 95%CI = 0.177, 0.868; ages 75 years and older – Wald statistic =

14.646, OR = 0.174, 95%CI = 0.071, 0.426) and social support (Wald statistic = 14.036, OR =

0.214 95%CI = 0.095, 0.479) accounted for the most of the explanation of physical exercise of

older men in Jamaica. Older men with current good health were less likely to become involved

in physical exercise (OR = 0.370, 95%CI: 0.171, 0.801) than those with poor health status.

Employed men were less likely to perform physical exercise than unemployed men (OR = 0.441,

95% CI: 0.223, 0.875) and those with a health insurance plan were more likely to perform

physical exercise (OR = 2.522, 95%CI: 1.094, 5.816).




                                               244
Discussion

       The majority of the respondents reported that they had good health status and were

sometimes happy. Approximately two thirds reported that they did some kind of physical

exercise. There are studies among adults which suggest that knowledge and beliefs about the

health effects of physical activity are positively associated with current physical activity levels.

[29] Perceived enjoyment of and satisfaction with life are positive predictors of physical activity

in both men and women of all ages [30]; however, intentions to be physically active do not

necessarily predict subsequent participation. [31] Concurringly, older men in this study did not

acknowledge the association between exercise and disease management. While the effects of

physical activity on health status may be measured primarily by the physiologic changes that

accompany increased aerobic fitness, [32] recent data suggest that such changes may have an

independent positive impact on various health indicators. Indeed, a growing body of

epidemiological literature shows significant relationships between low- and moderate-intensity

activities and reduced all-cause mortality, [33] as well as morbidity and mortality from

cardiovascular disease, stroke, cancer, and respiratory disease. [34, 35]


       The Caribbean has demonstrated an increasing prevalence of type 2 diabetes mellitus

associated with obesity due to the recent transition to a high consumption of energy dense foods

and increasing inactivity. [36] In Jamaica, the adjusted prevalence rates (95% CI) are 9.5% for

men and 15.7% for women in a population of 2.6 million. [37] Physical activity is inversely

associated with both the prevalence [38] and incidence [39] of type 2 diabetes. Moderate

physical activity significantly reduces the risk of developing type 2 diabetes mellitus. Perry et al.

[40] reported a relative risk of type 2 diabetes mellitus in moderately active men of 0.4 compared


                                                245
with inactive men. Manson and Spelsberg [41] and Hu et al. [42] have also found that between

30 and 50% of new cases of type 2 diabetes mellitus could be prevented by moderate or vigorous

physical activity. A recent randomized controlled trial by Tuomilehto et al., [43] of those at high

risk of type 2 diabetes found that those who were offered nutrition and physical activity

counselling and guidance (intervention group) experienced a significantly reduced risk of type 2

diabetes compared with the inactive control group. The effect of physical activity on type 2

diabetes incidence is probably explained partly by weight reduction and maintenance, and partly

by its positive influence on glucose utilization and insulin sensitivity. [44]


       The study found that 9 out of every 100 older men had hypertension. Ragoobirsingh and

colleagues reported that Jamaica has a point prevalence of hypertension of 30.8% in the 15 years

and over age group. [45] The effects of physical activity on the reduction and prevention of

hypertension have been proven by several well-documented studies. [46, 47] A prospective

cohort study by Hayashi et al. [48] examined the effects of walking to work on the risk of

hypertension in 6,017 Japanese men. Relative risk analysis determined that for every 26.3 men

who walked 20 minutes or more to work, one case of hypertension would be prevented. [48] This

suggests that regular light intensity activity in the form of walking can reduce hypertension.

Young and colleagues [49] conducted a study that compared intensity levels for the reduction

and prevention of hypertension in the United States. They examined the blood pressure of 62

sedentary elderly individuals who were participating in either a 12-week moderate intensity

aerobic programme or a light-intensity Tai Chi programme. Blood pressure was lowered in both

groups with no significant difference between the two activity levels. [49]              Therefore,

hypertension can be controlled by regular physical activity even at low levels of intensity.



                                                 246
       Several epidemiological studies indicate that physical activity offers partial protection

against primary or secondary events of coronary heart disease (CHD) and associated mortality

among middle-aged and older men. [50] This is true in older men in whom disability is

particularly frequent. [51] In the Goteborg study, the most active men, after 20 years of follow-

up, had a relative risk of death from CHD of 0.72 [52]. In the British Heart Study, light,

moderate and vigorous activity reduced mortality and heart attacks in older men by 0.61 and 0.65

respectively. [53] In the Honolulu Heart Program, the risk of CHD was reduced in physically

capable elderly men with the distance walked. [54] Various factors have been implicated in this

beneficial effect: a lipid-lowering effect, [55] increased insulin sensitivity, [56] reduced arterial

pressure, [57] increased coronary vasodilatory capacity [58] and coronary perfusion, [59]

correction of endothelial dysfunction, [60] and the antiarrhythmic effect due to the reduction of

heart rate and sympathetic activity. [61] Similarly, experimental [62] and clinical [63] studies

have demonstrated that physical activity can correct most of the cardiovascular alterations

induced by aging.



       The current study also revealed that of those older men who participated in physical

exercise most of them walked or jogged. In addition most of the men in the study had high

cognitive functionality and enjoyed good health. Heikkinen and colleagues [64] found that more

physically active individuals show a higher level of self-reported health and low prevalence of

chronic disease. Duration of activity is also important with elderly men walking less than 0.25

miles/day having 2.04 times an increased risk of CHD compared with men walking over 1.5

miles/day. [65] Furthermore, several trials, [66 - 68] most lasting for some months, have failed


                                                247
to demonstrate any benefit of exercise interventions on cognitive function among older adults,

while other trials [69 - 72] have found improved cognitive performance with physical activity. It

is possible that physical activity may prevent cognitive decline but not improve cognitive

performance during a short period in otherwise high functioning elderly persons. This is

plausible if physical activity–induced effects are associated with long-term protective benefits,

such as a reduction in cardiovascular or cerebrovascular risk factors, but not in short-term

effects. Regular physical activity may reduce serum lipid levels and hypertension and increase

cardiovascular fitness [68] all of which could reduce the risk of vascular dementia and

Alzheimer’s disease [73]. Indeed, Rogers and colleagues [74] found that active elderly persons

had fewer declines in cerebral blood flow during a 4-year period compared with less active

elderly persons, a mechanism that might help maintain cognitive function by maintaining

vascular function.



       Aerobic activity is important for the prevention and control of coronary heart disease.

Just over one-tenth of the men in the study were engaged in aerobic activities. Increases in

duration and/or intensity appear to reduce the risk of CHD. [75] To promote and maintain health,

older adults need moderate-intensity aerobic physical activity for a minimum of 30 min on five

days each week or vigorous intensity aerobic activity for a minimum of 20 min on three days

each week. Also, combinations of moderate- and vigorous-intensity activity can be performed to

meet this recommendation. Moderate-intensity aerobic activity involves a moderate level of

effort relative to an individual’s aerobic fitness. Realistic goals for aerobic activity will

commonly be in the range of 30-60 min of moderate-intensity activity a day, as illustrated by the

Health Canada recommendation for older adults. [76] Interestingly, cross-sectional [77] and


                                              248
randomized intervention [78] research involving older adults has found that moderate amounts of

physical activity/aerobic exercise may protect against age-related declines of executive control.

Indeed, Colcombe and Kramer [79] found that aerobic forms of exercise had general and

selective effects that were beneficial to cognitive function in older adults. That is, despite their

finding that aerobic exercise was beneficial across the breadth of cognitive processes studied

(i.e., speed, visuo-spatial, controlled processing, and executive control), the effects were greatest

for tasks, or task components, involving extensive executive control [79].



       The determinants of physical exercise among the elderly men in this study were age,

social support, current good health status and being employed. Some personal characteristics

appear to be particularly influential determinants of physical activity for older adults including

males. For instance, poor physical condition and health status have been reported to be frequent

barriers to participation in physical activity in older age groups. [80, 81]        Other personal

characteristics that may be especially important in shaping physical activity patterns for older

adults include medical concerns and fears of injury [82, 83], as well as attitudinal barriers, such

as perceived lack of ability and misconceptions or erroneous beliefs about exercise (e.g., that it

must be strenuous or uncomfortable to be efficacious) [84, 85]. Therefore an understanding of

the factors associated with physical activity or inactivity for the aging male may result in the

development of effective interventions for promoting regular physical activity.


Conclusion
       In concluding, the majority of the elderly men were engaged in some form of physical

activity and enjoyed good health status. An older man with medical conditions should engage in


                                                249
physical activity in a manner that reduces his risk of developing other chronic diseases. Given

the breadth and strength of the evidence, physical activity should be one of the highest priorities

for preventing and treating disease and disability in older men. Effective interventions to

promote physical activity in older men in Caribbean countries such as Jamaica deserve wide

implementation.




                                               250
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                                              259
Table 10.1: Socio-demographic characteristics of sample

Variable                                                  Frequency   Percent
Physical Exercise
   Yes                                                        1345      67.3
    No                                                         655      32.8
Functional Status
    High dependence                                             24       1.2
    Moderate dependence                                        184       9.2
    Low dependence                                            1792      89.6
Cognitive Functionality
    Low                                                         19       1.0
    Moderate                                                    99       5.0
    High                                                      1882      94.1
Age group
    55- 64 years                                               851      42.6
    65 – 74 years                                              712      35.6
    75 years and older                                         437      21.9
Employment Status
    Employed                                                   511      25.6
    Unemployed                                                 412      20.6
    Retired                                                   1077      53.9
Happiness
    Rarely                                                     480      24.0
    Sometimes                                                 1430      71.5
    Most times                                                  90       4.5
Self-rated Health Status
    Excellent                                                  357      19.0
    Good                                                      1038      55.4
    Fair                                                       480      25.6
Life Satisfaction
    Rarely satisfied                                            658     32.9
    Sometimes                                                 1,272     63.6
    Most                                                         70      3.5
Childhood Health status
   Good                                                       1650      82.5
   Poor                                                        350      17.5
Area of residence
   Urban                                                       981      49.0
   Rural                                                      1019      51.0




                                             260
Table 10.2: Types of physical exercise

Variable                                       Frequency   Percent
Type of physical exercise
  Job, run and/or walk                             1038      77.2
  Aerobics                                          179      13.3
  Swim                                               63       4.7
  Cycle                                              54       4.0
   Skip                                               2       0.1
  Push-ups and/or sit-ups                             8       0.6




                                         261
Table 10.3: Type of physical exercise engaged in by area of residence

                                             Rural and Urban
                                                                          Total
 Types of physical exercise             Urban             Rural
                                        n (%)             n (%)           n (%)
          Jog, run, walk
                                        502 (51.2)          536 (52.6)    1038 (51.9)
          Aerobics
                                           81 (8.3)            98 (9.6)     179 (9.0)
          Swim
                                           34 (3.5)            29 (2.8)      63 (3.2)
          Cycle
                                           21 (2.1)            33 (3.2)      54 (2.7)
          Skip
                                            1 (0.1)             1 (0.1)       2 (0.1)
          push –ups and/or sit-ups
                                            1 (0.1)             7 (0.7)       8 (0.4)
          None
                                        341 (34.8)          315 (30.9)     656 (32.8)
         Total                                  981               1019            2000


χ2 = 10.60, P = 0.101




                                              262
Table 10.4: Logistic regression of exercise and some variables in older men in Jamaica

 Variable                                                     Std             Odds        95.0% C.I.
                                            Coefficient      Error        P   Ratio   Lower       Upper
   Home ownership (1= yes)                        -0.396      0.342   0.246    0.67      0.34         1.31
   Cognitive functionality                        -0.259     0.189    0.169   0.77       0.53          1.12
   Have children (1=yes)                           0.183     1.006    0.855   1.20       0.17          8.64
   Self-reported depression (1=yes)               -0.316     0.317    0.320   0.73       0.39          1.36
   Take medication (1=yes)                        -0.096     0.311    0.758   0.91       0.49          1.67
   Dummy education                                -1.115     0.492    0.023   0.33       0.13          0.86
   Dummy health advise                             0.015     0.334    0.964   1.02       0.53          1.96
   Functional status                              -0.057     0.081    0.479   0.94       0.81          1.11
   Church attendance                               0.642     0.408    0.115   1.90       0.85          4.23
   Area of residence (1= urban)                   -0.081     0.316    0.797   0.92       0.50          1.71

   Elderly (ages 65 to 74 years)                  -0.937     0.405    0.021   0.39       0.18          0.87
   Elderly (ages 75 years and older)              -1.747     0.457    0.000   0.17       0.07          0.43
   †Elderly (ages 55 to 64 years)                                             1.00

   Current good health status                     -0.995     0.394    0.012   0.37       0.17          0.80
   Happiness                                      -0.107     0.357    0.765   0.90       0.45          1.81
   Life satisfaction                              -0.060     0.374    0.874   0.94       0.45          1.96
   Poor childhood health status                    0.310     0.373    0.406   1.36       0.66          2.83
   Household head                                  0.846     0.385    0.028   2.33       1.10          4.95

   Married                                         0.181     0.353    0.607   1.20       0.60          2.40
   Separated, divorced or widowed                 -0.027     0.459    0.952   0.97       0.40          2.39
   †Single                                                                    1.00

   Health plan                                     0.925     0.426    0.030   2.52       1.09          5.82
   Employment status (1= Employed)                -0.818     0.349    0.019   0.44       0.22          0.88
   Number of brother alive                        -0.276     0.519    0.595   0.76       0.27          2.10
   Number of sister alive                          0.071     0.434    0.870   1.07       0.46          2.51
   Social support (1=yes)                         -1.542     0.412    0.000   0.21     0.1095          0.45

χ2 (24) = 161.609, P < 0.001
-2 Log likelihood = 327.591
Hosmer and Lemeshow goodness of fit χ2 = 5.456, P = 0.708.
Nagelkerke R2 = 0.406
Overall correct classification = 90.8%
Correct classification of cases of exercise = 97.3%
Correct classification of cases of do not exercise = 34.2%
†Reference group




                                                           263
                                                                           Chapter 11
 
Comparative Analysis of Health Status of men 60+ years and men 73+ years in 
Jamaica: Are there differences across municipalities?

Paul Andrew Bourne



Introduction

From 1880–1882, life expectancy at birth for females in Jamaica was 39.8 years compared to
37.02 years for males (Table 11.1). One century later (2004), females were outliving males by 6
years (Table 11.1). In Jamaica, population ageing is a feminized phenomenon. This is typically
the same around the world. From 1950-1955, world statistics showed that life expectancy at birth
for females was 47.9 years compared to 45.2 years for males, indicating that former sex was
outliving the latter by 2.7 years.1,2 The disparity in life expectancy at birth between the sex
cohorts increased to 4.2 years between 2000-2005.1 According to the Demographic Statistics for
           3
Jamaica,       10.9% of females were 60+ years compared to 10.3% of males. For the world, in
2000, 11.1% of the female population was older than 60 years compared to 8.9% of males.
Concomitantly, world statistics indicated that a female who is 60 years old is likely to live for an
additional 20.4 years compared to 17.0 years for males.1 Life expectancy is one of the indicators
of the health status of an individual or population, which implies that females are enjoying a
better health status than males.

Insert Table 11.1 : Life Expectancy at Birth of Jamaicans by Sex: 1880−2004

Courtenay4 noted, from research conducted by the Department of Health and Human Services
and Centers for Disease Control, that from the 15 leading causes of death (except Alzheimer’s
disease), the death rates were higher for men and boys in all age cohorts compared to women and


                                                264
girls. Embedded within this theorizing, are the differences in fatal diseases explained by gender
constitution,5 which Courtenay5 contributed to behavioural practices of the sexes causing men to
die approximately 6 years earlier than females.6




Studies have shown, however, that females have a higher propensity to contract particular
conditions, such as depression, osteoporosis and osteoarthritis.7,8 Herzog8 noted that ’…it
appears that older women are more likely to be impaired by their health problems, while older
men (60 years) are more likely to die from them.’ A study that was conducted by Schoen et al.9
on a group of adolescents, revealed a different finding from what was reported by the WHO.
They found that males were more likely than females to feel stressed, ‘overwhelmed’, or
‘depressed’; they attributed this to the limited nature of men’s social networks.




Schoen et al9 found that men in general tend to be more stressed and less healthy than females,
and further argued that men are more likely to use denial, distraction, alcoholism, and other
social strategies to conceal their illness or disabilities.10-13 On the other hand, Herzog8 in Physical
and Mental Health in Older Women – referring to studies from a number of experts - wrote that
females had higher rates of depression than their male counterparts. Could suicide among the
aged be the result of depression? This is likely to be underreported, because other illnesses are
often present and given as cause of death? He noted that data on suicide and depression yielded
different results, and therefore, suicide is not necessarily an indicator of depression.




Along with the longer life spans, particularly of females, unhealthy years are on the rise in
keeping with the longer life expectancy.14 The WHO14 developed DALE (Disability Adjusted
Life Expectancy) in order to account for unhealthy years in relation to life expectancy. In an
attempt to calculated ‘quality of lived years’, the WHO introduced an approach that allows for
the evaluation this, called the DALE (Disability adjusted life expectancy). DALE does not only
use length of years to indicate health and well-being status of an individual or a nation, but
incorporate the number of years lived without disabilities. The institution found that these
                                                 265
accounted for a 14 % reduction in life expectancy for poorer countries and 9 % for more
developed nations.




Jamaica is a developing country, which means that, according to the DALE, both sexes are
experiencing 14 years of unhealthy life expectancy. In spite of this, yearly on average (since
1990), there are 565 men who cross the threshold of the life expectancy in Jamaica (72 years at
birth). In addition, there are 1842 men who cross the 60+ years bar; 30, 8% are older than their
life expectancy at birth. Males and females are living longer, but the former seek health care less
frequently (Table 11.2). Table 11.2 shows that males reported less illness/injury than females,
sought less medical care, and spent more time in health care facilities, all of which accounts for
the disparity in life expectancy between the sexes.




Insert Table 11.2: Seeking Medical Care, Self-reported illness, and Gender composition of
those who report illness and Seek Medical Care in Jamaica (in %age), 1988-2007




Irrespective of the self-reported health conditions given by males, they experience higher rates of
morbidity and mortality than women in Jamaica.15 The Jamaica Ministry of Health’s publication
showed that of the five leading causes of death– malignant neoplasms, cerebrovascular disease,
heart disease, diabetes mellitus and homicide – men outnumbered women in 3 of them.
Malignant neoplasms is 39% greater for men than women; cerebrovascular 14% higher for
females than males; heart disease was 71.2 per 100 000 for men and 66.1 per 100 000 for
women; and diabetes mellitus was 64% higher for females than males.15




In 2007, approximately 11% of men were older than 60 years (N = 132 931, Table 11.3); 40.2%
of aged Jamaicans reported suffering from at least one dysfunction (N=118 603); 13.1% of men
reported ill-health (N=173 135); 75.1% of aged people who reported ill-health had recurring ill-
health (N=89 071); and 72 % elderly who had self-rated ill-health sought medical care – N=85
                                               266
394.16 It can be extrapolated from the data that approximately 5% of the 13.1% of self-assessed
health conditions are accounted for by aged men. Furthermore, it can be extrapolated from these
statistics that 3.8% of elderly aged men expressed having recurring ill-health. Has the rationale
for not studying older men's ill health conditions been due to the fact that only 5% were subject
to such conditions?

Insert 20.3

Many studies have been done on aged Caribbean nationals, in particular Jamaicans.16-33 An
extensive review of the literature showed that none have examined men’s health, or those factors
which influence good health of older men (60+ years) in Jamaica. In spite of pressure by the
WHO and some scholars in a drive to examine the social determinants of health33-38 the
Caribbean, in particular Jamaica, no work has been done on this subject area. This study is
innovative, as it seeks to investigate the social, psychological and environmental determinants of
the health status of older men. Studies on older Caribbean nationals are not the same as an
investigation of the health status of older men (60 years) in Jamaica. The aims of this study were
to 1) ascertain factors that influence good health status of aged men (ages 60+ years) in Jamaica,
2) determinants of good health status of older men, 3) to determine the potency of each variable,
and 4) distinguish between determinants of the men.




Theoretical framework

Many studies have employed multivariate analyses in the examination of health status.16, 17, 26, 39-
44
     The use of econometric analysis in the study of health was developed by Michael Grossman.44
This approach simultaneously captures biomedical and non-biomedical variables, unlike the
bivariate analysis that is only able to investigate two variables. Based on the WHO’s definition,
health45 is inclusive of biomedical, socio-economic and psychological factors. Health, therefore,
is determined by many factors, and the use of an econometric model makes it possible to identify
these. A multivariate model has a fundamental advantage over bivariate relations, as health is a
multidimensional phenomenon; this model is able to capture more variables and without
excluding some variables which cannot be accommodated in a bivariate association.


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The theoretical framework that underlines the current work was developed by Bourne, 17 which is
a modification of Michael Grossman44 and Smith and Kingston’s works.43 Grossman was the
first to establish an econometric model which evaluated the health status of people. The model
encapsulates some variables that determine health status of people in the world (Eqn. 1).




Ht = ƒ (Ht-1, Go, Bt, MCt, ED)                                                                 (1)

         in which the Ht – current health in time period t, stock of health (Ht-1) in previous period, Bt
–   smoking and excessive drinking, and good personal health behaviours (including exercise –
Go), MCt,- use of medical care, education of each family member (ED), and all sources of
household income (including current income). Grossman’s model was further expanded upon by
Smith and Kington to include socioeconomic variables (Eqn. 2).




Ht = H* (Ht-1, Pmc, Po, ED, Et, Rt, At, Go)                                               (2)




         Eqn. (2) expresses current health status Ht as a function of stock of health (Ht-1), price of
medical care Pmc, the price of other inputs Po, education of each family member (ED), all sources
of household income (Et), family background or genetic endowments (Go), retirement related
income (Rt ), asset income (At,).

         Given that particular conditions influence the aged that are some different from other age
cohort, Bourne used econometric analysis to build a model that captures variables that influence
subjective well-being of elderly Jamaicans. Bourne’s model is as follows (Eqn. 3):




Wi =ƒ (lnPmc , ED, Ai , En, G, MS, AR, P, N, lnO, H, T, V)                               (3)



                                                   268
       In Eqn. 1 Wi is well-being of the Jamaican elderly, is a function of cost of medical
(health) care (Pmc), the educational level of the individual, age (Ai , where i is the individual),
the environment (En), gender of the respondents (G), marital status (MS), area of residents (AR),
positive affective conditions (P), negative affective conditions (N), household crowding (.
average occupancy per room) (O), home tenure (H), property ownership, (T), crime and
victimization, (V). The current study will examine aged men’s health status, and so the Bourne
model is ideal to use in examining this research.




Methods




The current research used secondary data collected jointly by the Planning Institute of Jamaica
(PIOJ) and the Statistical Institute of Jamaica (STATIN). For this paper, the sub-sample was
1,423 aged men (person aged 60+ years). The mean age of the sub-sample was 71.14 years
(SD=7.97 years). Another sub-sample was extracted from the survey, which constituted 633 men
73+ years (men living beyond the life expectancy, for Jamaica it is 72+ years). The two sub-
samples were extracted from a larger, nationally prevalence study, conducted between June and
October 2002, of some 25018 respondents.            Stratified random sampling techniques were
employed to design the survey (. the Jamaica Survey of Living Conditions (JSLC)), and detailed
self-administered questionnaires were used to collect the data from the respondents. The
questionnaire was modeled from the World Bank’s Living Standards Measurement Study
(LSMS) household survey. There were some modifications made to the LSMS as the JSLC is
more focused on policy impacts. The questionnaire covered questions on socio-demographic,
economic and wealth variables, crime and victimization, social welfare, health status, health
services, nutrition, housing, and physical environment. Interviewers who collected the data were
trained to address the questions and concerns of interviewees. Data were stored and retrieved in
the SPSS program (SPSS Inc; Chicago, IL, USA); and for the present research descriptive
statistics were used to provide certain socio-demographic characteristics of the sub-sampled
population.


                                               269
Based on the principles of parsimony (all variables that should be included were included and
not those which should be excluded were not included), the final model would only constitute
those variables that were statistically significant (. p < 0.05). This was attained by the using the
health literature and the variables that were included within the framework of the current data
set.




Demographic characteristics were provided for the sample and the sub-sample of men 60+ years
and 73+ years. Logistic regression was used to establish 1) a model for good health status of
aged men in Jamaica; 2) Wald statistics to examine the contribution of each significant variable
in the model; and 3) the odds ratios interpreted to address the difference within each variable.




Multivariate analysis (logistic regression) was used because the researcher wanted to test a
number of variables simultaneously, and the fact that the dependent variable was binary; the
most fitting statistical technique was logistic regression. The model that was tested in this study
is (Eqn. 4):




Wi =ƒ (Pmc, ED, Ai, En, MS, AR, P, N, O, H, V)                                        (4)




In Eqn. 4 Wi is well-being of the aged men in Jamaica which is a function of cost of medical
(health) care (Pmc), the educational level of the individual, age (Ai), where i is the individual),
the environment (En), marital status (MS), area of residents (AR), positive affective conditions
(P), negative affective conditions (N), household crowding (. average occupancy per room) (O),
home tenure (H), crime and victimization, (V). Property ownership (T) was omitted, owing to
the number of missing cases (in excess of 15%). The study examined aged men’s health status,
and Bourne’s model was considered ideal for use in this research.

                                                270
The results were presented using unstandardized coefficients, Wald statistics, Odds ratio (OR)
and confidence interval (95% CI). The predictive power of the model was tested using Hosmer
and Lemeshow test46 to examine goodness of fit of the model. The correlation matrix was
examined in order to ascertain if autocorrelation (or multicollinearity) existed between variables.
Based on Cohen and Holliday,47 the correlation can be weak (0 - 0.39), moderate (0.4-0.69), or
strong ( 0.7-1.0). This matrix was used to exclude (or allow) a variable in the model. Wald
statistics were used to determine the magnitude (or contribution) of each statistically significant
variable in comparison with the others, and the OR for the interpretation of each significant
variable.




Measure


Health: The self-rated health status of an individual

Good health: This variable is derived from a number of questions which enquired about
particular health conditions. It is a binary variable where 1=not reporting an ill-health and 0 =
reported at least one health condition.39

Age: This is the total number of years lived since birth, measured from one birthday to the next.

Psychological condition: This is the psychological state of an individual, sub-divided into
positive and negative affective psychological conditions.

Positive affective psychological condition: This denotes hopefulness, optimism and life
satisfaction. For this study the variable was measured using a number of responses with regards
to being hopeful and optimistic about the future and life generally.

Negative affective psychological condition: It means the degree to which an individual
experiences feelings of hopelessness, pessimism and fear. In this study these were measured



                                               271
from a number of responses from a person experiencing loss of a breadwinner and/or family
member, loss of property, loss of income, failure to meet household and other obligations.

Household crowding: This indicates the average occupancy of persons per room - the total
    number of individuals in a household divided by the number of rooms occupied by the
    household (excluding the kitchen and bathroom).

Married: A binary variable - where 1 = those who indicated being married, and 0 = otherwise

Poverty level : A binary variable - where 1 = those people who are in two poor quintiles (.
    poorest and poor), and 0 = otherwise (. those in quintiles 3 to the wealthiest, or quintile 5)




Crime: Crime index = Σ kiTj,

This equation represents the frequency with which an individual witnessed or experience a
crime, where i denotes 0, 1 and 2: 0 indicates not witnessing or experiencing a crime; 1 means
witnessing 1 to 2 crimes; and 2 indicates seeing 3 or more crimes.

Ti denotes the degree of the different typologies of crime witnessed or experienced by an
individual: j = 1 valuables stolen; 2 = attacked with or without a weapon; 3 = threatened with a
gun; j = 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.

Aged: An individual who has celebrated 60 years or more.

Area of residence: The general geographic locale in which an individual resides.

1 = Kingston Metropolitan Areas are all the areas which are 100% urban, 0 = otherwise

1 = Peri-urban areas are places which are not 100% urban; 0 = otherwise

The Reference group is from a rural area




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Results

Demographic Characteristic of sampled population:

Men 60+ years

Of the population of 1 432 aged respondents, the mean age was 71.14 years ± 7.97 years (Table
11.4). A substantial majority of the population was married (50%); owned their own homes
(85%); resided in rural areas (68%); and reported good health (63%). The majority men had at
most primary level education (62%); however, 3 % had attained tertiary level education, and
98.6% reported that they were the head of their household. Per capita income quintile was evenly
distributed, with 23.8% being in the wealthiest quintile. Furthermore, crime seems to have a
minimal affects on the respondents.




Results:

Demographic Characteristic of sampled population:

Men 73+

Of the population of 633 men aged 73+ years, the mean age was 78.5 years ± 5.64 years (mode
year= 77yrs, median = 77 yrs). A substantial majority of the population was married (48.8%, N
= 302), 23.6% never married (N=146) and 22.6% widowed (N = 140). Most owned their own
homes (88%, N = 557). In terms of area of residence, 70.9% (N=449) resided in rural areas;
19.3% (N=122) in peri-urban areas; and 9.8% (N=62) in urban areas. A little more than half
(53.5%; N=333) reported good health. The majority of aged men had at most primary level
education (67.4%, N = 402); only, 2.7% had attained tertiary level education. Almost all the men
(98.4%) indicated that they were the heads of their households.




Per capita income quintile was evenly distributed, with the minority being in the wealthiest
quintile (23.4%,N = 148), and the poorest quintile (21.6%, N = 137). In addition, crime seems to


                                              273
have a minimal affects on men 73+ years. The average consumption per person in the men 73+
yearscohort was JA.$77 877.07 (SD=$72 014) – USD1.00 = Ja. 50.97.




Analysis of Logistic Regression on Good Health of Men 60+ years




Of the 16 predisposed variables that were used in the model (Table 11.5), 5 were statistically
significant (p < 0.5). The 5 factors that determine good health of older men in Jamaica – age,
secondary education, health insurance ownership, area of residence and positive affective
psychological conditions – accounted for 27.4% of the model (chi square test (19) = 289.45, p-
value = 0.001, -2 log Likelihood = 1,419.72). Of the 5 predictors of good health, 3 negatively
influence health. These are age, secondary level education and health insurance. The model had
statistically significant predictor power (model χ2 = 289.45, p < 0.001, Homer and Lemeshow
goodness of fit χ2 = 12.84, p = 0.117) and correctly classified 73% of the sample (correctly
classified 93% of those who had good health and 40% of those who did not report poor health).




Of those variables that negatively determine good health, ownership of health insurance carries
the most weight in determining good health (Wald statistic=122.88, 95% CI: 0.03 to 0.09, p =
0.001), followed by age (Wald statistic=39.2, 95% CI: 0.93 to 0.97, p = 0.001). Embedded in
these findings is the revelation that an individual who possessed health insurance is 0.06 times
(odd ratio) less likely to experience good health compared to someone who does not have the
same. Similarly, as older men age, he is 0.95 (odds ratio) less likely to have good health
compared to a younger aged man. In addition, those who had obtained a secondary education, in
comparison to primary level education, is 0.64 times (odds ratio) less likely to report good health
(95% CI: 0.49 to 0.84). Furthermore, there is no statistical difference between men who had at
most primary level education compared to with tertiary level education, suggesting that those
with primary level education have better health.




                                               274
With respect to factors which have a positive affect on health, also positively affected the men’s
psychological conditions (Wald statistic = 11.67, 95% CI: 1.04 to 1.16) and accounted for more
variability than area of residence. On examining positive affective psychological conditions, the
more an aged man experiences a positively affective condition; he is 1.1 times more likely to
report good health. If an aged man experiences a positively affective condition, he is 1.1 times
more likely to report good health. Findings revealed that men who reside in rural areas suffer
from diminished good health. This means that those in peri-urban areas, 1.5 times (odds ratio,
95% CI: 1.06 to 2.13) more likely to report good health compared to an aged man who dwelled
in rural Jamaica. The aged men who resided in the Kingston Metropolitan Area were 1.6 times
(odds ratio, 95% CI: 1.02 to 2.52) more likely to report good health compared to those in rural
Jamaica.




Analysis of Logistic Regression on Good Health of men 73+ years




What factors account for good health of men in the men 73+ years? Table 11.5 shows that, of
the 15 predisposed factors that tested for the initial model (good health of men 73+ years), 5
explain the variability in good health. These determine 27.7% of the variability in good health –
(chi Square (18) = 132.21, p-value = 0.001, Nagelkerke R square = 0.277, -2 log Likelihood =
653.92). They are: age, secondary level education, ownership of health insurance, area of
residence and positive affective psychological conditions. Three of the explanatory variables
negatively contribute to good health (age, secondary level education and health), and two
positively affect good health (area of residence and positive affective psychological conditions).




The model had statistically significant predictor power (model χ2 = 132.21, p < 0.001, Hosmer
and Lemeshow goodness of fit χ2 = 14.474, p = 0.070), and correctly classified 71% of the
sample (correctly classified 84.9% of those who had good health and 55.1% of those did not
report poor health).


                                               275
Ownership of health insurance carries the most weight in determining good health (Wald
statistic=53.6, 95%CI: 0.029-0.129) followed by secondary level education with reference to
primary level education (Wald statistic = 8.38, 95%CI: 0.357-0.820), living in peri-urban areas
(Wald Statistic =7.609, 95%CI: 1.23-3.396) and the least, dwelling in Kingston Metropolitan
Area (Wald statistic=4.396, 95%CI: 1.053-4.577). Embedded in these findings are the realization
1) that good health of men 73+ years are eroded with years of life; 2) those with primary level
education enjoy a better self-reported health than those with secondary and tertiary level
education; 3) owning health insurance does not positively contribute to good health, it is only an
indicator of those who are likely to have poorer health; 4) men 73+ years who dwell in Peri-
urban areas are more likely to enjoy greater self-reported good health, followed by those who
resided in Kingston Metropolitan Area, and lastly by those in Rural areas; and finally 5) men
73+ years that are experiencing more positive affective psychological conditions are 1.1 times
more likely to report good health.




Discussion




All of the United Nations’ and World Health Organizations’ Reports, coupled with those of the
Jamaican Ministry of Health, and the Jamaica Survey of Living Conditions that have been
published on population, ageing, health or gender issues, have shown that women outlive men.
The disparity in the life expectancy rate between the sexes is 6 years in Jamaica, and 8 years
using data on the world. Living longer means more years and defying the odds of mortality. This
occurrence is accounted for by healthy lifestyle practices, implying that unhealthy lifestyle
practices lead to higher mortality and morbidity in men than women. In spite of these realities,
there are men living beyond the life expectancy in their respective geopolitical area of residence.
In Jamaica, the life expectancy for men is 72.3 years. The term the researcher has coined that
refers to men who are alive beyond the life expectancy of their nation’ is men 73+ years.
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Over an 18-year period (ending 2007), there were 40,948 men 73+ years in Jamaica, and the
average yearly increase of men 73+ years the period was 565. This means that there are men
living beyond the expected life expectancy, morality, and disease-causing morality rate. In
addition to the aforementioned, an average of 565 men crosses over in the men 73+ years cohort
years annually. In spite of the high mortality and morbidity of men, the current study provides
information on what constitutes good health for older men.




Literature has shown that the health status of people, as they become older, lessens.48, 49-52 This
study concurs with this finding. The current study found that 63% of men 60+ years reported
good health compared to 53.5% of men 73+ years, indicating that health decreases with ageing.
This point was further reinforced by the finding in which age was a factor of good health in each
of the models. Age as a factor was ranked as the second most influential in determining ‘good’
health (or lack thereof) for men 60+ years compared to being one of the four influential for men
73+ years. However, age is not the only factor that affects good health of elderly men.




Other studies have shown that education influences good health and that tertiary level education
is positively associated with better health. This study agrees that education influences good
health, and that there is no difference between the health status of elderly men with primary and
tertiary level education. Another interesting finding to emerge from this study is the fact that
older men with primary level education in Jamaica have better self-reported health than those
with secondary education. This contravenes other research that have shown that better quality
education determines higher quality of health, but this is not the case for men who are living
beyond 59 years.




Poverty, overcrowding, consumption and marital status in other studies17, 19, 24, 26, 43 have shown
to influence good health; however, and in this study this is not the case for elderly men. The fact

                                               277
that living beyond a particular year of birth (60 years) means that the individual has surpassed
the need for certain material possessions and appetite for some foods; therefore, having financial
resources or not, does not influence current health status – this goes for consumption, as well as
other aforementioned variables that are not statistically significant and so not having financial
resources (or having) does not influence current health status and this goes for consumption and
the other aforementioned issues that are not statistical significant (p > 0.05). Studies done on the
elderly have indicated that overcrowding, consumption and marital status determine well-being,
but in this study it was found not to be the case. The current work has refined the factors which
effect elderly men and established that they are somewhat different from those that influence the
health and well-being of elderly Jamaicans.




Although poverty does not directly relate to good health of aged Jamaicans, good health has been
found to differ based on area of residence. In 1997 the prevalence of poverty in the country was
9.9%, and 10 years later (2007) it had increased by 50.5% (to 19.9%).53 Despite this exponential
decline in prevalence of poverty, 71.3% of the stock of poverty is accounted for by rural areas.
Based on the data for 2007, 46.6% of elderly Jamaicans dwelled in rural areas, 20.9% in peri-
urban areas, and 32.5% in Kingston Metropolitan Area.53 Within the context of the current study,
it was found that the state of health of elderly men in rural areas was worse than other areas of
residence, and that poverty indirectly influences health. Furthermore, the best health is likely to
be experienced by other town dwellers, but not those who dwell in the Kingston Metropolitan
Area (100% cities). The stock of poverty for elderly residents of urban areas was 2.2 times
(19.9%) greater than that of the distribution of poverty in peri-urban areas (8.9%), indicating that
poverty indirectly determines good health of aged residents.




It has well established that positive affective psychological conditions are correlated to
health,17,54-60 and this was concurred by the current study. Lyubomirsky54 shows that happier
people view life in a positive manner.        This attitudinal state explains how decisions are
influenced, and moods experienced. With a positive attitude,           a better quality of life is


                                                278
experienced, as the individual thinks, acts, builds, and carries out his/her life’s task with a more
self-assurance.55 The contrary is also true - a pessimistic individual is more likely to have a
lower self-esteem, less self-fulfillment, and less self-actualized than someone who is optimistic.
DeNeve and Cooper56 have found that happier people are more optimistic and positive in nature.
Diener and Seligman57 point out that moods are not stationary, thus happy people can have
negative moods, but they do not dwell on the negatives indefinitely. Harris and Lightsey58 have
established that negative affective conditions such as guilt, fear, anger, and disgust, inversely
affect subjective, well-being - just as positive factors directly influence well-being.59 However,
this was not the case for aged men in Jamaica. The literature has shown that the elderly seeks
more health care than any other age cohort, so their psychological state is directly influenced by
their physical condition. If an elderly individual does not perceive that he/she has control over an
illness or disability, it may result in self-destructive behavior60 which will negatively influence
well-being. McCarthy offers a further justification for the correlation between psychological
state and subjective well-being, when he writes that diabetic patients are six to seven times more
likely to suffer from psychiatric illnesses, anxiety and depression than non diabetic patients. In
the current work, it was found         that aged men who are experiencing positive affective
psychological conditions are 1.1 times more likely to report good health, and that this variable
minimally contributes to good health for Jamaican elderly men.




Ownership of health insurance coverage does not only indicate health seeking behaviour, it also
means that men who have surpassed 60 years purchased more health insurance if they believed
that they were more likely to become ill. Hence, health insurance is not a preventative measure;
instead it is a product that is more demanded by this cohort of men who are more likely to report
ill-health. This finding denotes that men 60+ years who own this product, are using it as a cost
reduction mechanism because they are aware that as a result of their ill-health, the frequency
with which they will need to visit health facilities will increase.




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Conclusion

In sum, the good health of men 60+ years deteriorates as they become older. The current study
has shown that there is no difference between the factors that determine good health of aged men
and men 73+ years. Good health is strongly influenced by ownership of health insurance
coverage, but not by positive affective psychological conditions. Men 60+ years and men 73+
years who resided in rural Jamaica reported the least good health; and that the greatest self-
reported good health was experienced by those in peri-urban areas. This study is the first of its
kind, no existing literature with which do a comparative study in. This limitation however, does
not hamper it from providing insight into the health status of men 60+ years and the factors
which predict good health for this group, as well as men 73+ years.




Acknowledgement

The author would like to extend sincere gratitude to Ms Neva South-Bourne who offered
invaluable assistance on the final draft of this manuscript.




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                                         286
TABLE 11.1: 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)




                                              287
TABLE 11.2:
Seeking Medical Care, Self-reported illness, and Gender composition of those who report illness
and Seek Medical Care in Jamaica (in %age), 1988-2007
                                                         Reporting Reporting Mean Mean
                                 Seeking Seeking         Illness-   Illness-   Days Days
         Seeking     Health      Medical Medical         Men        Women      Of        Of
         Medical     Insurance Care - Care           -                         Illness Illness
  Year Care          Coverage Men             Women                            Men       Women
  1988 NI            NI          NI           NI         NI         NI         NI        NI
  1989 54.6          8.2         44.7         52.8       15.0       18.5       10.6      11.1
  1990 38.6          9.0         37.9         39.2       16.3       20.3       10.2      10.2
  1991 47.7          8.6         48.5         47.4       12.1       15.0       10.0      10.3
  1992 50.9          9.0         49.0         52.5       9.9        11.3       10.7      10.9
  1993 51.8          10.1        48.0         54.7       10.4       13.5       10.7      10.1
  1994 51.4          8.8         49.0         53.4       11.6       14.3       10.3      10.4
  1995 58.9          9.7         59.0         58.9       8.3        11.3       10.6      10.7
  1996 54.9          9.8         50.5         58.5       9.7        11.8       10.0      11.0
  1997 59.6          12.6        60.0         59.3       8.5        10.9       11.0      10.0
  1998 60.8          12.1        57.8         62.8       7.4        10.1       11.0      11.0
  1999 68.4          12.1        64.2         71.1       8.1        12.2       11.0      11.0
  2000 60.7          14.0        57.4         63.2       12.4       16.8       9.0       9.0
  2001 63.5          13.9        56.3         68.2       10.8       15.9       9         10
  2002 64.1          13.5        62.1         65.3       10.4       14.6       10.0      10.0
  2003 NI            NI          NI           NI         NI         NI         NI        NI
  2004 65.1          19.2        64.2         65.7       8.9           13.6      11.0      10.0
  2005 NI            NI          NI           NI         NI         NI         NI        NI
  2006 70.0          18.4        71.7         68.8       10.3       14.1       9.7       10.0
  2007 66.0          21.2        62.8         68.1       13.1       17.8       10.6      9.3

 Source: Jamaica Survey of Living Conditions, various issues

 NI - No Information was available




                                            288
TABLE 11.3.Number of Older men (60+ years) and difference over each year in Jamaica: 1990-
2007
Year                Older     men Difference over Older men (ages Difference over
                    (ages 73+ yrs) year before         60+ years)         previous year
1990                31,336          -                  101,603            -

1991                   32,441          1,105             110,350             8,747
1992                   32,966          525               111,742             1,392
1993                   33,488          522               113,116             1,374
1994                   34,073          585               114,706             1,590
1995                   34,635          562               116,263             1,557
1996                   35,158          523               117,600             1,337
1997                   35,605          447               118,721             1,121
1998                   36,022          417               119,751             1,030
1999                   36,505          483               121,001             1,250
2000                   37,003          498               122,297             1,296
2001                   37,459          456               123,478             1,181
2002                   37,940          481               124,728             1,250
2003                   38,541          601               126,370             1,642
2004                   39,149          608               128,031             1,661
2005                   39,754          605               129,683             1,652
2006                   40,033          279               131,250             1,567
2007                   40,948          915               132,931             1,681
Source: Calculations for men 73+ years were done by the author, and the figures were extracted
from Demographic Statistics, 2007.




                                             289
TABLE 11.4: Sociodemographic Characteristics of Sample (N=1,432): Men 60+ years
                                        %                          N

Good Health: No                         37.6                        528
               Yes                      62.6                        878
Marital status
       Married                          50.2                        703
       Never married                    30.3                        425
       Divorced                          2.1                        30
       Separated                         2.3                        32
       Widowed                          15.1                        211

Retirement Income: No                   93.0                        1320
                   Yes                  7.0                         99

Health Insurance: No                    87.1                        1212
                  Yes                   12.9                        180

Per capita Income Quintile
       1=Poorest                        18.6                        265
       2                                        17.7                       252
       3                                20.1                        286
       4                                19.7                        281
       5=Wealthiest                     23.8                        339

Home tenure: Squatted or rent free      9.8                         139
              Rented or leased          5.8                         82
              Owned                     84.5                        1201

Area of residence: Rural area           68.0                        968
                   Peri-urban areas             20.1                       286
                   URBAN AREAS                  11.9                       169

Household Head: No                      1.4                         20
                Yes                             98.6                       1402

Educational level: Primary and below            62.3                       843
                   Secondary            34.3                        462
                   Tertiary             3.0                         41

Age (Mean ± SD)                                        71.14 years ±7.97 years
Average Consumption per person (Mean ± SD)             $80,654.69 ± $75,029.21
Household crowding (Mean ± SD)                         1.15 ± 0.89
Crime (Mean ± SD)                                      1.5 ± 7.0;



                                          290
TABLE 11.5:
Logistic Regression: Variables Predicting Good Health of Men 60+ years and 73+ years in
Jamaica
                            60+ years                        73 years or over
                                                                         95.0%
                                         95.0% C.I.                      C.I.
  Variable
                            Odds ratio Lower                 Odds ratio Lower    Upper
 Age                        0.949        0.933      0.965*** 0.961       0.929   0.994*
  Secondary level           0.640        0.488      0.840**  0.541       0.357   0.820**
  Tertiary                  2.327        0.816      6.633    1.755       0.378   8.140
 †Primary and below
                            1.000                            1.000

Medical Expenditure          1.000    1.000     1.000      -           -          -
Married                      0.959    0.731     1.259      0.963       0.651      1.424
Poor                         1.174    0.854     1.613      1.269       0.792      2.032
Household Head               1.129    0.113     11.321     0.871       0.583      1.301
Environment                  0.929    0.706     1.222      0.061       0.029      0.129***
Health Insurance             0.055    0.033     0.092***   2.044       1.230      3.396**
Peri-urban areas             1.505    1.062     2.134*     2.195       1.053      4.577*
Urban areas                  1.605    1.021     2.523*     0.283       0.073      1.104
†Rural areas                 1.000

 House tenure: Rent          0.758    0.360     1.595      0.500       0.231      1.085
               Owned         0.911    0.577     1.438      0.718       0.487      1.060
†Squatted                    1.000

 Social support             0.807        0.621  1.050      0.986        0.755     1.286
 Crowding                   1.056        0.896  1.243      0.975        0.939     1.012
 Crime Index                0.994        0.977  1.011      1.000        0.933     1.071
 Negative Affective         0.976        0.934  1.021      1.097        1.010     1.191*
 Positive Affective         1.098        1.041  1.159**    1.000        1.000     1.000
 Consumption per person     1.000        1.000  1.000      1.000        1.000     1.000
 Chi Square (df = 19) = 289.45, p = 0.001                  Chi Square (df = 18) = 132.21, p =
 Nagelkerke R square = 0.274                              0.001
 -2LL = 1,419.72                                          Nagelkerke R square = 0.277
 Hosmer and Lemeshow goodness of fit χ2=12.843, P = 0.724 -2LL = 653.92
                                                          Hosmer and Lemeshow goodness of
                                                          fit χ2=14.47, P = 0.7

†Reference group
*p < 0.05, **p < 0.01, ***p < 0.001



                                          291
292
                       Jamaica: 1993                                                                                   Jamaica: 2009
                       3. Percent of Total Population                                                                  3. Percent of Total Population




    Male                                                                 Female                 Male                                                                     Female



                                         70-74                                                                                           70-74



                                         60-64                                                                                           60-64



                                         50-54                                                                                           50-54



                                         40-44                                                                                           40-44



                                         30-34                                                                                           30-34


                                                                                                                                         20-24
                                         20-24


                                                                                                                                         10-14
                                         10-14


                                                                                                                                         0-4
                                         0-4




                                                                                                                                               0




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                                                                                            6




                                                                                                       5




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                                               0




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                                                                         5




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                                                                                  7
7




       6




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                                                                                      293
294
The
           Ageing Male
     By Paul Andrew Bourne


This book is geared toward the provision of information for
students in sociology and public health, social workers,
administrators, policy makers, health care practitioners, social
demographers, professionals and businesspeople who are
concerned about understanding, caring and aiding men in older
adulthood.


The Ageing Male commences with a discussion on ageing and
population ageing in the Caribbean, particularly among
Jamaicans, which is the platform for the justification of a book of
this kind. The text provides a partial discussion of issues
surrounding men in older adulthood – including social support,
functionality and sex. It is the first of its kind, and it seeks to
provide an understanding of the issues experienced by aged
males. However, this text is not a comprehensive examination of
matters affecting males in older adulthood, but an introductory
discussion of germane issues that were all selected by the author
in a single volume.


This book, I hope, will expand the discourse on ageing issues on
males in older adulthood in the Caribbean as well as to be
catalysis for more empirical works on this cohort, particularly
among men.

				
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