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SummaryThis paper investigates whether community-level wealth inequality predicts HIV serostatus using DHS household survey and HIV biomarker data for men and women ages 15–59 pooled from six sub-Saharan African countries with HIV prevalence rates exceeding 5%. The analysis relates the binary dependent variable HIV-positive serostatus and two weighted aggregate predictors generated from the DHS Wealth Index: the Gini coefficient, and the ratio of the wealth of households in the top 20% wealth quintile to that of those in the bottom 20%. In separate multilevel logistic regression models, wealth inequality is used to predict HIV prevalence within each statistical enumeration area, controlling for known individual-level demographic predictors of HIV serostatus. Potential individual-level sexual behaviour mediating variables are added to assess attenuation, and ordered logit models investigate whether the effect is mediated through extramarital sexual partnerships. Both the cluster-level wealth Gini coefficient and wealth ratio significantly predict positive HIV serostatus: a 1 point increase in the cluster-level Gini coefficient and in the cluster-level wealth ratio is associated with a 2.35 and 1.3 times increased likelihood of being HIV positive, respectively, controlling for individual-level demographic predictors, and associations are stronger in models including only males. Adding sexual behaviour variables attenuates the effects of both inequality measures. Reporting eleven plus lifetime sexual partners increases the odds of being HIV positive over five-fold. The likelihood of having more extramarital partners is significantly higher in clusters with greater wealth inequality measured by the wealth ratio. Disaggregating logit models by sex indicates important risk behaviour differences. Household wealth inequality within DHS clusters predicts HIV serostatus, and the relationship is partially mediated by more extramarital partners. These results emphasize the importance of incorporating higher-level contextual factors, investigating behavioural mediators, and disaggregating by sex in assessing HIV risk in order to uncover potential mechanisms of action and points of preventive intervention.

SummaryThis paper investigates whether ethnic diversity at the Demographic and Health Surveys (DHS) cluster level predicts HIV serostatus in three sub-Saharan African countries (Kenya, Malawi and Zambia), using DHS household survey and HIV biomarker data for men and women aged 15–59 collected since 2006. The analysis relates a binary dependent variable (HIV positive serostatus) and a weighted aggregate predictor variable representing the number of different ethnic groups within a DHS Statistical Enumeration Area (SEA) or cluster, which roughly corresponds to a neighbourhood. Multilevel logistic regression is used to predict HIV prevalence within each SEA, controlling for known demographic, social and behavioural predictors of HIV serostatus. The key finding was that the cluster-level ethnic diversity measure was a significant predictor of HIV serostatus in Malawi and Zambia but not in Kenya. Additional results reflected the heterogeneity of the epidemics: male gender, marriage (Kenya), number of extramarital partners in the past year (Kenya and Malawi, but probably confounded with younger age) and Muslim religion (Zambia) were associated with lower odds of positive HIV serostatus. Condom use at last intercourse (a spurious result probably reflecting endogeneity), STD in the past year, number of lifetime sexual partners, age (Malawi and Zambia), education (Zambia), urban residence (Malawi and Zambia) and employment (Kenya and Malawi) were associated with higher odds of positive serostatus. Future studies might continue to employ multilevel models and incorporate additional, more robust, controls for individual behavioural risk factors and for higher-level social and economic factors, in order to verify and further clarify the association between neighbourhood ethnic diversity and HIV serostatus.