‘HIV Infection Does Not Disproportionately Affect the Poorer in Sub-Saharan Africa’

Macro International Inc., Calverton, Maryland, USA.
AIDS (London, England) (Impact Factor: 6.56). 12/2007; 21 Suppl 7(Suppl 7):S17-28. DOI: 10.1097/01.aids.0000300532.51860.2a
Source: PubMed

ABSTRACT Wealthier populations do better than poorer ones on most measures of health status, including nutrition, morbidity and mortality, and healthcare utilization.
This study examines the association between household wealth status and HIV serostatus to identify what characteristics and behaviours are associated with HIV infection, and the role of confounding factors such as place of residence and other risk factors.
Data are from eight national surveys in sub-Saharan Africa (Kenya, Ghana, Burkina Faso, Cameroon, Tanzania, Lesotho, Malawi, and Uganda) conducted during 2003-2005. Dried blood spot samples were collected and tested for HIV, following internationally accepted ethical standards and laboratory procedures. The association between household wealth (measured by an index based on household ownership of durable assets and other amenities) and HIV serostatus is examined using both descriptive and multivariate statistical methods.
In all eight countries, adults in the wealthiest quintiles have a higher prevalence of HIV than those in the poorer quintiles. Prevalence increases monotonically with wealth in most cases. Similarly for cohabiting couples, the likelihood that one or both partners is HIV infected increases with wealth. The positive association between wealth and HIV prevalence is only partly explained by an association of wealth with other underlying factors, such as place of residence and education, and by differences in sexual behaviour, such as multiple sex partners, condom use, and male circumcision.
In sub-Saharan Africa, HIV prevalence does not exhibit the same pattern of association with poverty as most other diseases. HIV programmes should also focus on the wealthier segments of the population.

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Available from: Robert Greener, Sep 01, 2015
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    • "In a recent supplement to the Journal of the International AIDS Society devoted entirely to structural drivers of HIV transmission, Seeley et al. (2012) noted that elimination of HIV will require 'a comprehensive HIV response, that includes meaningful responses to the social, political, economic and environmental factors that affect HIV risk and vulnerability'. Also, a prevailing view emphasizes the role of poverty in the spread of HIV, despite numerous studies demonstrating an inverse relationship between HIV serostatus and poverty status in sub-Saharan Africa, which is opposite to the case in the developed world and contrary to common expectations about disease susceptibility and poverty status (Shelton et al., 2005; Gillespie et al., 2007; Mishra et al., 2007; Parkhurst, 2010). Commenting in The Lancet, Shelton et al. (2005, p. 1058) suggested that both wealth and economic disadvantage may play pivotal roles in HIV transmission through sexual concurrency networks, with wealth being 'associated with the mobility, time, and resources to maintain concurrent partnerships' and where women 'might improve their economic situation by having more than one concurrent partner.' "
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    ABSTRACT: Summary This 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.
    Journal of Biosocial Science 05/2015; DOI:10.1017/S0021932013000709 · 0.98 Impact Factor
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    • "" Gender inequality " and poverty, the major social drivers of HIV vulnerability among young women in sub-Saharan Africa (s-SA), are examples of this complexity. The fact that there are countries outside s-SA with greater poverty and gender inequalities with dissimilar gender differentials in HIV infection as compared to s-SA (Mishra et al., 2007; Obermeyer, 2006) adds to this complexity. There are specific pathways through which these social drivers operate in influencing vulnerability to HIV and these pathways include other contextual factors which can be targeted for intervention efforts (World Health Organization [WHO], 2007). "
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    ABSTRACT: There is increasing focus on social and structural factors following the marginal success of individual-level strategies for HIV prevention. While there is evidence of decreased HIV prevalence among young individuals in South Africa, there is still a need to monitor HIV incidence and prevalence in this vulnerable group as well as track and prevent high-risk sexual behavior(s). This study investigated the social and structural factors that shape the context of vulnerability to increased risk of exposure to HIV infection. A mixed-methods approach including qualitative and quantitative design components was employed. Young adults in the age group 18-24 were interviewed from four provinces in South Africa. The qualitative results produced strong support for the effectiveness of loveLife's HIV prevention programs. The household-based survey results showed that the strongest predictors of self-reported HIV infection (indicating a greater chance of being infected) using adjusted odds ratios (aOR) are: being diagnosed with an STI in a lifetime (aOR 13.68 95% Confidence Interval (CI) [4.61-40.56]; p < .001), inconsistent condom use (aOR 6.27 95% CI [2.08-18.84]; p < .01), and difficulty in accessing condoms (aOR 2.86 95% CI [1.04-7.88]; p < .05). The strongest predictors that indicated a decreased chance of being infected with the HI virus are: talking with partner about condom use in the past 12 months (aOR .08 95% CI [.02-.36]; p < .001) and having a grade 8 (aOR .04 95% CI [.01-.66]; p < .05) and higher educational level (aOR .04 95% CI [.01-.43]). These results show that social and structural factors serve as risk and protective factors for HIV prevention among young people. Intervention programs need to continue to focus on effective communication strategies and healthy relationships. Structural adjustments have to be made to encourage school attendance. Finally, social/health policies and health service delivery have to also be refined so that young people have access to youth friendly health services.
    Psychology Health and Medicine 07/2014; 20(3):1-11. DOI:10.1080/13548506.2014.936883 · 1.53 Impact Factor
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    • "Although there is good evidence that migration can increase individuals’ risk of HIV in the context of specific risky practices [7,41], we could find no evidence of migration affecting HIV prevalence at a population level. The findings presented here are similar to those of studies that have found no ecological evidence to support other widely touted socioeconomic determinants of GHEs – poverty [46,47], conflict and displacement [48]. It is important to note that these findings are not at odds with the findings that migrants from high HIV prevalence regions may contribute disproportionately to the total number of HIV infections in certain low HIV prevalence regions such as Western Europe [47]. "
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    ABSTRACT: Background Correctly identifying the determinants of generalized HIV epidemics is crucial to bringing down ongoing high HIV incidence in these countries. High rates of migration are believed to be an important determinant of HIV prevalence. This study has two aims. Firstly, it evaluates the ecological association between levels of internal and international migration and national peak HIV prevalence using thirteen variables from a variety of sources to capture various aspects of internal and international migration intensity. Secondly, it examines the relationship between circular migration and HIV at an individual and population-level in South Africa. Methods Linear regression was used to analyze the association between the various measures of migration intensity and peak national HIV prevalence for 141 countries and HIV prevalence by province and ethnic group in South Africa. Results No evidence of a positive ecological association between national migration intensity and HIV prevalence was found. This remained the case when the analyses were limited to the countries of sub-Saharan Africa. On the whole, countries with generalized HIV epidemics had lower rates of internal and external migration. Likewise, no association was found between migration and HIV positivity at an individual or group-level in South Africa. Conclusion These results do not support the thesis that migration measured at the country level plays a significant role in determining peak HIV prevalence.
    BMC Infectious Diseases 06/2014; 14(1):350. DOI:10.1186/1471-2334-14-350 · 2.61 Impact Factor
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