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AN ASSOCIATION BETWEEN NEIGHBOURHOOD WEALTH INEQUALITY AND HIV PREVALENCE IN SUB-SAHARAN AFRICA

Published online by Cambridge University Press:  09 January 2014

PAUL HENRY BRODISH*
Affiliation:
MEASURE Evaluation, Carolina Population Center and Department of Public Policy, the University of North Carolina at Chapel Hill, NC, USA
*

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.

Type
Articles
Copyright
Copyright © Cambridge University Press 2014 

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References

Banerjee, A. & Somanathan, R. (2007) The political economy of public goods: some evidence from India. Journal of Development Economics 82(2), 287314.Google Scholar
Bingenheimer, J. B. (2007) Wealth, wealth indices and HIV risk in East Africa. International Family Planning Perspectives 33(2), 8384.Google Scholar
Commission on Social Determinants of Health (2008) Closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health. Final Report of the Commission on Social Determinants of Health. World Health Organization, Geneva.Google Scholar
Durevall, D. & Lindskog, A. (2012) Economic inequality and HIV in Malawi. World Development 40(7), 14351451.Google Scholar
Epstein, H. (2010) The mathematics of concurrent partnerships and HIV: a commentary on Lurie and Rosenthal. AIDS and Behavior 14(1), 2930.Google Scholar
Epstein, H. & Morris, M. (2011) Concurrent partnerships and HIV: an inconvenient truth. Journal of the International AIDS Society 14(1), 13.Google Scholar
Farmer, P. (2010) Partner to the Poor: A Paul Farmer Reader. University of California Press, Berkeley and Los Angeles.Google Scholar
Fliessbach, K., Weber, B., Trautner, P., Dohmen, T., Sunde, U., Elger, C. E. & Falk, A. (2007) Social comparison affects reward-related brain activity in the human ventral striatum. Science 318(5854), 13051308.Google Scholar
Fox, A. M. (2010) The social determinants of HIV serostatus in sub-Saharan Africa: an inverse relationship between poverty and HIV? Public Health Reports 125, 1624.CrossRefGoogle ScholarPubMed
Fox, A. M. (2012) The HIV–poverty thesis re-examined: poverty, wealth, or inequality as a social determinant of HIV infection in sub-Saharan Africa? Journal of Biosocial Science 44(4), 459480.Google Scholar
Gillespie, S., Kadiyala, S. & Greener, R. (2007) Is poverty or wealth driving HIV transmission? AIDS 21, S516.Google Scholar
Gravelle, H., Wildman, J. & Sutton, M. (2002) Income, income inequality and health: what can we learn from aggregate data? Social Science & Medicine 54(4), 577589.Google Scholar
Gupta, G. R., Parkhurst, J. O., Ogden, J. A., Aggleton, P. & Mahal, A. (2008) HIV prevention 4 – structural approaches to HIV prevention. Lancet 372(9640), 764775.Google Scholar
Howe, L. D., Hargreaves, J. R., Gabrysch, S. & Huttly, S. R. A. (2009) Is the wealth index a proxy for consumption expenditure? A systematic review. Journal of Epidemiology and Community Health 63(11), 871877.Google Scholar
Hunsmann, M. (2009) Political determinants of variable aetiology resonance: explaining the African AIDS epidemics. International Journal of STD & AIDS 20(12), 834838.Google Scholar
Joint United Nations Program on HIV/AIDS (2011) UNAIDS Terminology Guidelines. Joint United Nations Program on AIDS, Geneva.Google Scholar
Joint United Nations Program on HIV/AIDS (2010) MDG6: Six Things You Need to Know about the AIDS Response Today. Joint United Nations Program on HIV/AIDS, Geneva.Google Scholar
Kawachi, I. (2011) Income inequality and population health. Sulzberger Distinguished Lecture Series. Durham, NC.Google Scholar
Leigh, A., Jencks, C. & Smeeding, T. M. (2009) Health and economic inequality. In Salverda, W., Nolan, B. & Smeeding, T. (eds) The Oxford Handbook of Economic Inequality. Oxford University Press, Oxford, pp. 384405.Google Scholar
Lurie, M. & Rosenthal, S. (2010a) The concurrency hypothesis in sub-Saharan Africa: convincing empirical evidence is still lacking. Response to Mah and Halperin, Epstein, and Morris. AIDS and Behavior 14(1), 3437.Google Scholar
Lurie, M. & Rosenthal, S. (2010b) Concurrent partnerships as a driver of the HIV epidemic in sub-Saharan Africa? The evidence is limited. AIDS and Behavior 14, 1724.Google Scholar
Luttmer, E. F. P. (2005) Neighbors as negatives: relative earnings and well-being. Quarterly Journal of Economics 120(3), 9631002.Google Scholar
Mah, T. & Halperin, D. (2010a) Concurrent sexual partnerships and the HIV epidemics in Africa: evidence to move forward. AIDS and Behavior 14(1), 1116.Google Scholar
Mah, T. & Halperin, D. (2010b) The evidence for the role of concurrent partnerships in Africa's HIV epidemics: a response to Lurie and Rosenthal. AIDS and Behavior 14(1), 2528.Google Scholar
Mah, T. & Shelton, J. (2011) Concurrency revisited: increasing and compelling epidemiological evidence. Journal of the International AIDS Society 14(1), 33.Google Scholar
Measure DHS (2012) DHS Overview: HIV Prevalence. ICF International, Calverton, MD.Google Scholar
Mishra, V., Assche, S. R. V., Greener, R., Vaessen, M., Hong, R., Ghys, P. D.et al. (2007) HIV infection does not disproportionately affect the poorer in sub-Saharan Africa. AIDS 21, S1728.Google Scholar
Morris, M. (2010) Barking up the wrong evidence tree. Comment on Lurie & Rosenthal, ‘Concurrent partnerships as a driver of the HIV epidemic in sub-Saharan Africa? The evidence is limited’. AIDS and Behavior 14(1), 3133.Google Scholar
Nattrass, N. (2009) Poverty, sex and HIV. AIDS and Behavior 13(5), 833840.Google Scholar
Nattrass, N., Maughan-Brown, B., Seekings, J. & Whiteside, A. (2012) Poverty, sexual behaviour, gender and HIV infection among young black men and women in Cape Town, South Africa. African Journal of AIDS Research 11(4), 307317.Google Scholar
Parkhurst, J. O. (2010) Understanding the correlations between wealth, poverty and human immunodeficiency virus infection in African countries. Bulletin of the World Health Organization 88(7), 519526.CrossRefGoogle ScholarPubMed
Phelan, J. C., Link, B. G. & Tehranifar, P. (2010) Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications. Journal of Health and Social Behavior 51, S2840.Google Scholar
Rosen, D. (2012) Social networks of disease: ‘Tinderbox,’ by Craig Timberg and Daniel Halperin. The New York Times Book Review.Google Scholar
Sahn, D. E. & Stifel, D. C. (2003) Urban–rural inequality in living standards in Africa. Journal of African Economies 12(4), 564597.Google Scholar
Sawers, L. & Stillwaggon, E. (2010) Concurrent sexual partnerships do not explain the HIV epidemics in Africa: a systematic review of the evidence. Journal of the International AIDS Society 13, 34.Google Scholar
Seeley, J., Watts, C. H., Kippax, S., Russell, S., Heise, L. & Whiteside, A. (2012) Addressing the structural drivers of HIV: a luxury or necessity for programmes? Journal of the International AIDS Society 15 (Supplement 1), 17397.Google Scholar
Shandera, W. X. (2007) Key determinants of AIDS impact in southern sub-Saharan Africa. African Journal of AIDS Research 6(3), 271286.Google Scholar
Shelton, J. D., Cassell, M. M. & Adetunji, J. (2005) Is poverty or wealth at the root of HIV? The Lancet 366(9491), 10571058.Google Scholar
Subramanian, S. V. & Kawachi, I. (2004) Income inequality and health: what have we learned so far? Epidemiologic Reviews 26, 7891.Google Scholar
Wai-Poi, M., Spilerman, S. & Torche, F. (2008) Economic well-being: concepts and measurement using asset indices. Working Paper No. 27. Center for Wealth and Inequality, Columbia University.Google Scholar
Wilkinson, R. & Pickett, K. (2009) The Spirit Level: Why More Equal Societies Almost Always Do Better. Penguin.Google Scholar
Wilkinson, R. G. (2005) The Impact of Inequality: How to Make Sick Societies Healthier. New Press, New York.Google Scholar
Wilkinson, R. G. & Pickett, K. E. (2006) Income inequality and population health: a review and explanation of the evidence. Social Science & Medicine 62(7), 17681784.Google Scholar