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 years) and non- pensionable older men (aged 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 Health older person time t Health older person time t-1 Health young person time t-1 Level of education of older person Household endowment Community endowment Food intake by older person Medical care used by older person Time used to produce health by older person Genetic endowment of older person Individual endowment of older person Proximate DeterminantsDistal Determinants

Economic Model (1) Where: H i = Health of household member i X i = Consumption of household member i T i L = Leisure time of household member i n= Number of individuals in household I j = Non wage income w k = Vector of market wages in community k T i = Total time household member i has to allocate to work, leisure and health P k = Vector of prices in community k N i = Food intake of household member i M i = Medical care used by household member i T i H = Time used by household member i on health E i = Level of education of household member i η i = genetic endowment of household member i C i =vector of other individual endowments C j =vector of household endowments C k =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:

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 , 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

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