Working paper 5 - Measuring the Effects of Prime-age Adult Mortality in Kenya

Author(s):  Yamano, Takashi; Jayne, Thomas


Introduction

Development planners increasingly require solid information on how the death of adults in their prime productive years is affecting household behavior and welfare. In parts of Africa, mortality rates in the 15-54 year age cohort have risen dramatically since the onset of HIV/AIDS. The estimated life expectancy in Sub-Saharan Africa is now 47, down by five years since 1993, and an estimated 15 years shorter than it would have been in the absence of AIDS (UNAIDS/WHO, 2001). One report estimates that deaths caused by HIV/AIDS in the ten most affected African countries will reduce the labor force by 20 percent or more by 2020 (FAO, 2001).

There is widespread agreement that this unprecedented humanitarian disaster will have pervasive economic and food security effects. A number of studies have modeled the impact of HIV/AIDS on economic growth (e.g., Bloom and Mahal, 1997; Cuddington and Hancock, 1995; Cuddington, 1993). These studies typically involve computable general equilibrium or neoclassical growth models in which most of the behavioral consequences are assumed rather than derived from micro-level empirical findings. Other studies have attempted to measure the economic costs of HIV/AIDS through lost workdays valued at average wage levels (e.g., Leighton, 1996). Both approaches suffer from the paucity of quantitative micro-level information on how households respond to HIV/AIDS and the subsequent effects on agricultural production, non-farm income, and other key indicators of welfare.

It is perhaps not surprising that there remains limited survey information on the effects of HIV/AIDS because of the difficulty and cost of obtaining reliable assessments of AIDS-related mortality. Studies assessing cause of death in survey data typically involve a combination of prior serological surveys in which HIV blood tests are required of prime-age adults who are subsequently tracked over time (Urassa et al., 2001), “verbal autopsies” in which medical field workers interview a close caregiver of deceased individuals within sampled households to elicit signs and symptoms of the terminal illnesses and then make a diagnosis (Kahn et al., 1999; Quigley et al., 2000; Garenne et al., 2000; Urassa et al., 2001), and./or algorithm-based computer-generated diagnoses based also on caregiver survey information (Urassa et al., 2001).

The use of multiple sources of information in surveys to determine cause of death is important to reduce the probability of incorrect diagnoses. Because of the difficulties and costs of these approaches, the few available micro-level studies of the effects of HIV/AIDS on rural households are almost always drawn from specific geographic sites purposively chosen because they were known to have high HIV infection rates, such as Rakai in Uganda and Kagera in Tanzania (Barnett and Blaikie, 1992; Barnett et. al., 1995; Lundberg, Over, and Mujinja, 2000; Tibaijuka, 1997). While providing valuable insights into how afflicted households respond to the disease, such studies are limited in their ability to extrapolate to understand national level impacts. We are aware of no nation-wide studies that have quantitatively estimated the effects of the disease on farm production and off-farm income.

The absence of nationally representative micro-level information remains a critical limitation on the generation of more reliable macro-level projections on the effects of HIV/AIDS. An alternative and complementary approach is to focus on understanding the effects of primeage adult mortality more generally, given the substantial AIDS-related increase over the last two decades in the proportion of African households suffering from prime-age adult mortality.

While only a certain proportion of prime-age deaths can be attributed to AIDS, a review of recent epidemiological studies in Eastern and Southern Africa indicates that HIV is the leading cause of disease-related death among adults between 15-49 in all cases (e.g., Ainsworth and Semali, 1998; Kahn et al., 1999; UNAIDS/WHO, 1998). Moreover, a growing emphasis among development planners on understanding the dynamics of poverty requires a better understanding of the effects of prime-age adult mortality, regardless of cause, on household behavior and welfare. The effects of adult mortality can be more readily assessed through standard nationally representative socio-demographic and economic household surveys.

This paper estimates the impact of prime-age adult mortality on household composition, crop production, asset holdings, and non-farm income using nationwide household survey data in rural Kenya. Kenya is one of the most heavily HIV-infected countries in the world: 13.9 percent of adults age between 15 and 49 are estimated to be living with HIV (UNAIDS/WHO, 2000). We use a two-year panel of 1,422 households in 22 districts surveyed in 1997 and 2000 to estimate household fixed-effects models of changes in outcomes. We focus on “reduced form” specifications in which as little structure as possible is put on household behavior, because so little is currently known about the complex and dynamic responses by households to adult mortality (Whiteside, 2002).

The findings of this study highlight the importance of dis-aggregating the effects of prime-age adult death by gender and status (i.e., the role and position of the individual) within the household. We find important gender and status differences in how adult mortality affects households’ size and composition, crop cultivation patterns, agricultural output, and off-farm income. In some cases, these findings are consistent with household coping behaviors described by qualitative studies in the literature.

 

 

Measuring the Effects of Prime-age Adult Mortality in Kenya