BACKGROUND: Knowledge of the effect of socioeconomic status on HIV infection in Africa stems largely from cross-sectional studies. Cross-sectional studies suffer from two important limitations: two-way causality between socioeconomic status and HIV serostatus and simultaneous effects of socioeconomic status on HIV incidence and HIV-positive survival time. Both problems are avoided in longitudinal cohort studies. METHODS: We used data from a longitudinal HIV surveillance and a linked demographic surveillance in a poor rural community in KwaZulu-Natal, South Africa, to investigate the effect of three measures of socioeconomic status on HIV incidence: educational attainment, household wealth categories (based on a ranking of households on an assets index scale) and per capita household expenditure. Our sample comprised of 3325 individuals who tested HIV-negative at baseline and either HIV-negative or -positive on a second test (on average 1.3 years later). RESULTS: In multivariable survival analysis, one additional year of education reduced the hazard of acquiring HIV by 7% (P = 0.017) net of sex, age, wealth, household expenditure, rural vs. urban/periurban residence, migration status and partnership status. Holding other factors equal, members of households that fell into the middle 40% of relative wealth had a 72% higher hazard of HIV acquisition than members of the 40% poorest households (P = 0.012). Per capita household expenditure did not significantly affect HIV incidence (P = 0.669). CONCLUSION: Although poverty reduction is important for obvious reasons, it may not be as effective as anticipated in reducing the spread of HIV in rural South Africa. In contrast, our results suggest that increasing educational attainment in the general population may lower HIV incidence.
BACKGROUND: Knowledge of the effect of socioeconomic status on HIV infection in Africa stems largely from cross-sectional studies. Cross-sectional studies suffer from two important limitations: two-way causality between socioeconomic status and HIV serostatus and simultaneous effects of socioeconomic status on HIV incidence and HIV-positive survival time. Both problems are avoided in longitudinal cohort studies. METHODS: We used data from a longitudinal HIV surveillance and a linked demographic surveillance in a poor rural community in KwaZulu-Natal, South Africa, to investigate the effect of three measures of socioeconomic status on HIV incidence: educational attainment, household wealth categories (based on a ranking of households on an assets index scale) and per capita household expenditure. Our sample comprised of 3325 individuals who tested HIV-negative at baseline and either HIV-negative or -positive on a second test (on average 1.3 years later). RESULTS: In multivariable survival analysis, one additional year of education reduced the hazard of acquiring HIV by 7% (P = 0.017) net of sex, age, wealth, household expenditure, rural vs. urban/periurban residence, migration status and partnership status. Holding other factors equal, members of households that fell into the middle 40% of relative wealth had a 72% higher hazard of HIV acquisition than members of the 40% poorest households (P = 0.012). Per capita household expenditure did not significantly affect HIV incidence (P = 0.669). CONCLUSION: Although poverty reduction is important for obvious reasons, it may not be as effective as anticipated in reducing the spread of HIV in rural South Africa. In contrast, our results suggest that increasing educational attainment in the general population may lower HIV incidence.
Authors: Ashley C Schuyler; Zoe R Edelstein; Sanyukta Mathur; Joseph Sekasanvu; Fred Nalugoda; Ronald Gray; Maria J Wawer; David M Serwadda; John S Santelli Journal: Glob Public Health Date: 2015-08-27
Authors: Molly Rosenberg; Audrey Pettifor; William C Miller; Harsha Thirumurthy; Michael Emch; Sulaimon A Afolabi; Kathleen Kahn; Mark Collinson; Stephen Tollman Journal: Int J Epidemiol Date: 2015-02-24 Impact factor: 7.196
Authors: James Ndirangu; Till Bärnighausen; Frank Tanser; Khin Tint; Marie-Louise Newell Journal: Trop Med Int Health Date: 2009-09-07 Impact factor: 2.622