Exploring the connections between HIV serostatus and individual, household, and community socioeconomic resources: Evidence from two population-based surveys in Kenya

Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA.
Social Science [?] Medicine (Impact Factor: 2.56). 11/2011; 74(2):185-95. DOI: 10.1016/j.socscimed.2011.10.019
Source: PubMed

ABSTRACT The positive association between health and socioeconomic status (SES) is well documented. However, available empirical evidence on the SES gradients of HIV serostatus is mixed, and few studies have explored the effects of community SES indicators on individual's HIV risk. Using nationally representative data of women and men from the 2003 Demographic and Health Survey and the 2007 AIDS Indicator Survey from Kenya, we assessed the associations between HIV serostatus and SES as measured by educational attainment and household wealth at the individual/household and community levels. Additionally, we explored changes in these associations between 2003 and 2007. Results from bivariate and cohort analyses showed that during this period, HIV burden shifted from higher to lower SES subgroups at both the individual/household and community levels, particularly among women aged 15-24 years. Results from multi-level logistic regression models showed that this shift was generally significant among women. In addition, communities' collective educational attainment, measured as the percentage of residents with some secondary schooling or higher, was a more significant predictor and protective factor for HIV risk than individual/household-level SES indicators for women in 2007 and men in both years. Our findings highlight the relevance of community-level SES to HIV dynamics in Kenya between 2003 and 2007.

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    • "For this reason, people living in disadvantaged areas may have heightened risk of HIV beyond their individual risk factors. It is possible that individual and area level measures of socio-economic-position may influence the rates of progression of HIV in infected subjects and their risk of death (Ishida et al., 2012). Because we do not have data about time since sero-conversion, we cannot distinguish between effects of socio-economic-position on survival and effects on risk of infection. "
    Dataset: Cameroon
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    ABSTRACT: HIV infection prevalence shows strong regional variations in Cameroon, with the North West and the East as the most affected regions. Studies which have attempted to investigate the variation in HIV prevalence in Sub-Saharan countries found that the geographical heterogeneity in Human immunodeficiency virus (HIV) prevalence between high and low prevalence areas still existed after considering the different distribution of unsafe sexual behaviours. Individual and area level socio-economic-positions are both related to HIV transmission but the only study carried out in Cameroon that investigated HIV seroprevalence and socio-economic factors used only individual-based measures. We carried out this study to investigate the full extent of socio-economic influences on HIV sero-prevalence. We analysed data from 4,672 men and 5,227 women, aged 15 to 49, who participated in the Cameroon Demographic and Health survey (CDHS). Among men, HIV risk increased with household wealth at the individual level and there was a positive association between HIV seropositivity and variation in wealth within a region. Among women, there was no evidence of association between living in a relatively disadvantaged region (regional wealth index) and being HIV positive, but HIV seropositivity was associated with variation in wealth within a region. The main direct link between income inequality and HIV is likely to be through transactional sex. High income inequality would stimulate risky sexual behaviours and the diffusion of illicit sexual relationships, especially for wealthy men. Public-health interventions should be carried out, paying particular care in raising the awareness of wealthy men towards less risky sexual behaviours. Policy makers should define intervention strategies to reduce the socio-economic differences within regions.
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    AIDS Care 02/2013; 25(6). DOI:10.1080/09540121.2013.764382 · 1.60 Impact Factor
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    AIDS Care 08/2013; 26(3). DOI:10.1080/09540121.2013.824540 · 1.60 Impact Factor
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