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Measuring the Impact of Young Adult

Mortality on the Wellbeing of Older

Persons in KwaZulu-Natal, South Africa



Marjorie Opuni-Akuamoa

Advisor: Dr David Bishai



Department of Population, Family and Reproductive Health

Johns Hopkins Bloomberg School of Public Health



First Annual Research Conference,

Population Impacts on Economic Development

London, 1-3 November, 2006

Presentation Outline



• Study Background

• Specific Aims

• Conceptual Framework

• Study Data

• Research Methods

• Strengths and Limitations

Increase in Young Adult Mortality

• Increase in young adult mortality in

Southern Africa over last 20 years

• In KwaZulu-Natal, South Africa

– The probability of dying between 15 and 60

years was 58% for women and 75% for

men in 2000 (Hosegood et al., 2004)

• In Zimbabwe

– The probability of dying between 15 and 60

years was 50% for women and 65% for

men in 1997 compared to 33% for both in

1985 (Feeney, 2001)

Log Odds of Dying, 2001

Northern KwaZulu-Natal, South Africa









Case and Ardington, 2005

Demographic Consequences of

Increase in Young Adult Mortality

• Orphans

– Millions of children (under the age of 18)

have lost one or both parents

– In sub-Saharan Africa the number of

orphans has increased by one third since

1990 (UNAIDS, UNICEF, USAID, 2004)

– 13% of South African children were orphans

in 2003 (projected to increase to 19% by

2010) (UNAIDS, UNICEF, USAID, 2004)

Demographic Consequences of

Increase in Young Adult Mortality

• Bereaved Parents

– Many older adults (50 years and above)

are living to see their adult children die

rather than the reverse

– South African women aged 60 years and

above with no surviving children projected

to increase from 10% to 20% between

1995 and 2010 (Merli and Palloni, 2004)

Young Adult Mortality

and Household Members

• Ill health and mortality among adults of

reproductive age can affect:

– Household composition

– Household labor allocations

– Household income, assets and

savings

– Household consumption patterns

– Health and wellbeing of household

members

Over et al., 1992

Young Adult Mortality

and Persons Aged 50+ Years (1)

• A lot of media and advocacy attention to

grandparents caring for orphans

• Few quantitative studies on the

association between young adult

mortality and the health and wellbeing of

older adults (Knodel et al., 2001, 2002, 2003; Ainsworth and Dayton,

2003, 2004; Hosegood and Timaeus, 2005)

Young Adult Mortality

and Persons Aged 50+ Years (2)

• Older persons rely on their children and

grandchildren for money, food and other

support

• Illness and mortality of young adults can

result in reductions in support while

expanding care-giving and financial

burdens of older adults

Rationale for Study

• “Without a better research foundation,

developing appropriate programs and

policies to address the special needs of

older persons or to use their potential as

human resources in addressing the

consequences of the dramatic

increases in young adult mortality will

be difficult” (Knodel, Watkins, Van Landingham, 2003)

Specific Aims (1)



• To assess whether the occurrence

of a young adult death affects the

probabilities of not working, working

part time and working full time for

non-pensionable older women

(aged 50-59 years) and non-

pensionable older men (aged 50-64

years).

Specific Aims (2)



• To assess if the occurrence of a

young adult death is associated with

the value of assets of households

where persons aged 50 years and

above live.

Specific Aims (3)



• To examine if the occurrence of a

young adult death is affects the

self-reported health status of

persons aged 50 years and above.

Conceptual Framework

Distal Determinants Proximate Determinants

Health Food intake by older

older person

person

time t-1

Community Medical care used

endowment by older person







Household Time used to

endowment produce health Health

by older person older

person

time t

Level of education Individual

of older person endowment of older

person





Health Genetic endowment

young of older person

person

time t-1

Economic Model (1)

Where:

Hi= Health of household member i

Xi= Consumption of household member i

TiL= Leisure time of household member i

n= Number of individuals in household

Max U  U ( H i , X i , Ti ), i  1,...n

L

Ij= Non wage income

wk= Vector of market wages in community k

s.t. Ti= Total time household member i has to

allocate to work, leisure and health

n n n Pk= Vector of prices in community k

I j   Ti wk   X i pk   Ti wk

L Ni= Food intake of household member i

Mi= Medical care used by household

i 1 i 1 i 1 member i

Ti H= Time used by household member i on

and health

Ei= Level of education of household

H i  H ( N i , M i , Ti , Ei , Ci ,i , C j , Ck )

H member i

ηi= genetic endowment of household

member i

Ci=vector of other individual endowments

Cj=vector of household endowments

Ck=vector of community endowments



Behrman and Deolalikar, 1988 adapted by Ainsworth and Dayton, 2003

Economic Model (2)

• Maximizing household utility subject to

the budget constraint and the health

production function, the following

reduced form equation is obtained:



Hi  H ( Ei , Ci ,i , C j , I j , Ck , pk , wk )

*

Study Data

• KwaZulu-Natal Income Dynamics

Survey (KIDS)

– University of KwaZulu-Natal (UKZN), University of

Wisconsin-Madison, International Food Policy

Research Institute (IFPRI), London School of

Hygiene & Tropical Medicine (LSHTM) and

Norwegian Institute of Urban and Regional

Studies (NIBR)

– Household surveys - Living Standard

Measurement Survey - 1993, 1998, 2004

– 1,354 households in 1993; 1,132 households in

1998; 841 households in 2004

– Community surveys – 1993, 1998, (2004)

KwaZulu-Natal, South Africa

• Population: 9.5

million (20% of South

African population)

• Ethnic composition:

85% African; 12%

Indian

• GNP per capita:

9,713 Rand (approx.

1,300 USD)

• ANC HIV prevalence:

41%

Methods: Aim 1 & Aim 3

• Data: KIDS, 2004

• Outcomes: Employment status (Aim 1) and

self-reported health status (Aim 3)

• Method: Ordered probit

• Covariates include: for older persons –

gender, age, marital status, education; values

of assets; unearned income; unemployment at

community level; measures of community

health and infrastructure; mortality of elderly in

households; occurrence of young adult death

– 1-2 years and 3-4 years before the survey

Methods: Aim 2

• Data: KIDS, 1998, 2004

• Outcome: Value of assets

• Method: Fixed effects

• Covariates include: for older persons –

gender, age, marital status, education;

unearned income; unemployment at

community level; measures of community

health and infrastructure; mortality of elderly in

households; occurrence of young adult death

– 1-2 years and 3-4 years before the survey

Instrumental Variable Estimation

• Research on impact of young adult

illness and mortality plagued by three

methodological concerns: unobserved

heterogeneity, selection and reverse

causality

• All of these can cause endogeneity

• Solution:

– Instrumental variable estimation (Lundberg

et al., 2000)

– Propensity score matching

Strengths



• Detailed socioeconomic information

for households

• Population based data and not

convenience sample

• Systematic analysis attempt to

control for endogeneity of young

adult mortality

Limitations



• Limited health outcomes for older

persons

• Self-report - measurement error

• Limited cause of death information

• Measure impact of young adult

mortality within household only

Thank you!



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