Skip to main content Accessibility help
Hostname: page-component-7ccbd9845f-ktfbs Total loading time: 0.391 Render date: 2023-01-31T04:34:00.236Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true


Published online by Cambridge University Press:  04 January 2012

Yale School of Public Health, Division of Health Policy and Administration, Yale University, USA


Although health is generally believed to improve with higher wealth, research on HIV in sub-Saharan Africa has shown otherwise. Whereas researchers and advocates have frequently advanced poverty as a social determinant that can help to explain sub-Saharan Africa's disproportionate burden of HIV infection, recent evidence from population surveys suggests that HIV infection is higher among wealthier individuals. Furthermore, wealthier countries in Africa have experienced the fastest growing epidemics. Some researchers have theorized that inequality in wealth may be more important than absolute wealth in explaining why some countries have higher rates of infection and rapidly increasing epidemics. Studies taking a longitudinal approach have further suggested a dynamic process whereby wealth initially increases risk for HIV acquisition and later becomes protective. Prior studies, conducted exclusively at either the individual or the country level, have neither attempted to disentangle the effects of absolute and relative wealth on HIV infection nor to look simultaneously at different levels of analysis within countries at different stages in their epidemics. The current study used micro-, meso- and macro-level data from Demographic and Health Surveys (DHS) across 170 regions within sixteen countries in sub-Saharan Africa to test the hypothesis that socioeconomic inequality, adjusted for absolute wealth, is associated with greater risk of HIV infection. These analyses reveal that inequality trumps wealth: living in a region with greater inequality in wealth was significantly associated with increased individual risk of HIV infection, net of absolute wealth. The findings also reveal a paradox that supports a dynamic interpretation of epidemic trends: in wealthier regions/countries, individuals with less wealth were more likely to be infected with HIV, whereas in poorer regions/countries, individuals with more wealth were more likely to be infected with HIV. These findings add additional nuance to existing literature on the relationship between HIV and socioeconomic status.

Research Article
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Barham, B. & Boucher, S. (1998) Migration, remittances, and inequality: estimating the net effects of migration on income distribution. Journal of Development Economics 55, 307331.CrossRefGoogle ScholarPubMed
Barnett, T., Whiteside, A. & Decosas, J. (2000) The Jaipur paradigm: a conceptual framework for understanding social susceptibility and vulnerability to HIV. South African Medical Journal 90, 10981101.Google Scholar
Bärnighausen, T., Bor, J., Wandira-Kazibwe, S. & Canning, D. (2011) Correcting HIV prevalence estimates for survey nonparticipation using Heckman-type selection models. Epidemiology 22(1), 2735.CrossRefGoogle ScholarPubMed
Bärnighausen, T., Hosegood, V., Timaeus, I. M. & Newell, M-L. (2007) The socioeconomic determinants of HIV incidence: evidence from a longitudinal, population-based study in rural South Africa. AIDS 21(S7), S2938.CrossRefGoogle ScholarPubMed
Bärnighausen, T. & Tanser, F. (2009) Rethinking the role of local community in HIV epidemic spread in sub-Saharan Africa: a proximate-determinants approach. HIV Therapy 3(5), 435445.CrossRefGoogle ScholarPubMed
Buve, A. M., Hayes, R. J., Auvert, B., Ferry, B., Robinson, N. J. & Anagonou, et al. (2001) The multicentre study on factors determining the differential spread of HIV in four African cities: summary and conclusions. AIDS 15(S4), S127131.CrossRefGoogle ScholarPubMed
Coovadia, H. M. & Hadingham, J. (2005) HIV/AIDS: global trends, global funds and delivery bottlenecks. Globalization and Health 1, 13.CrossRefGoogle ScholarPubMed
Drain, P. K., Smith, J. S., Hughes, J. P., Halperin, D. T. & Holmes, K. K. (2004) Correlates of national HIV seroprevalence: an ecologic analysis of 122 developing countries. Journal of Acquired Immune Deficiency Syndrome 35(4), 407420.CrossRefGoogle ScholarPubMed
Epstein, H. (2007) The Invisible Cure: Africa, the West, and the Fight Against AIDS. Farrar, Strauss, Giroux, New York.Google Scholar
Fenton, L. (2004) Preventing HIV/AIDS through poverty reduction: the only sustainable solution? Lancet 364, 11861187.CrossRefGoogle ScholarPubMed
Filmer, D. & Pritchett, L. (2001) Estimating wealth effects without expenditure data- or tears: an application to educational enrollments in states of India. Demography 38(1), 115132.Google ScholarPubMed
Filmer, D. & Scott, K. (2008) Assessing Asset Indices: Policy Research Working Paper No. 4605. World Bank. URL: Scholar
Forston, J. G. (2008) The gradient in sub-Saharan Africa: socioeconomic status and HIV/AIDS. Demography 45(2), 303322.Google Scholar
Fox, A. M. (2010) The social determinants of serostatus in sub-Saharan Africa: an inverse relationship between poverty and HIV? Public Health Reports 125(S4), 1624.CrossRefGoogle ScholarPubMed
Fisher, A. A. & Way, A. A. (1988) The Demographic and Health Surveys program: an overview. International Family Planning Perspectives 14(2), 1519.CrossRefGoogle Scholar
Gelman, A. & Hill, J. (2007) Data Analysis using Regression and Multilevel/Hierarchical Models. Cambridge University Press.Google Scholar
Gilbert, L. & Walker, L. (2002) Treading the path of least resistance: HIV/AIDS and social inequalities – a South African case study. Social Science & Medicine 54, 10931110.CrossRefGoogle ScholarPubMed
Goldstein, H. (1999) Multi-Level Statistical Models. London Institute of Education.Google Scholar
Hargreaves, J. (2011) Investigating the inverse equity hypothesis: the changing social epidemiology of HIV in Tanzania. Presented at the Structural Drivers of HIV Conference, 9th September 2011, Norwich, UK.Google Scholar
Hargreaves, J. R., Bonell, C. P., Boler, T., Boccia, D., Birdthistle, I., Fletcher, A. et al. (2008) Systematic review exploring time trends in the association between educational attainment and risk of HIV infection in sub-Saharan Africa. AIDS 22(3), 403414.CrossRefGoogle ScholarPubMed
Harling, G., Ehrlich, R. & Myer, L. (2007) The social epidemiology of tuberculosis in South Africa: a multilevel analysis. Social Science & Medicine 66(2), 492505.CrossRefGoogle ScholarPubMed
Heise, L. L. & Elias, C. (1995) Transforming AIDS prevention to meet women's needs: a focus on developing countries. Social Science & Medicine 40(7), 931943.CrossRefGoogle ScholarPubMed
Hirsch, J. S. & Wardlow, H. (2006) Modern Loves: The Anthropology of Romantic Courtship & Companionate Marriage. Tor/Forge.CrossRefGoogle Scholar
Human Science Research Council. (2005) South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey. HSRC Press, Cape Town.Google Scholar
Hunter, M. (2002) The materiality of everyday sex: thinking beyond ‘prostitution’. African Studies 61, 99120.CrossRefGoogle Scholar
Hunter, M. (2007) The changing political economy of sex in South Africa: the significance of unemployment and inequalities to the scale of the AIDS pandemic. Social Science & Medicine 64, 689700.CrossRefGoogle ScholarPubMed
Hunter, M. (2010) Love in the Time of AIDS: Inequality, Gender, and Rights in South Africa. Indiana University Press, Bloomington, IN.Google Scholar
Kennedy, B., Kawachi, I., Prothow-Stith, D., Lochner, K. & Gupta, V. (1998) Social capital, income inequality and firearm violent crime. Social Science & Medicine 47(1), 717.CrossRefGoogle ScholarPubMed
Kuznets, S. (1955) Economic growth and income inequality. American Economic Review 45, 128.Google Scholar
LaChaud, J.-P. (2007) HIV prevalence and poverty in Africa: micro- and macro-econometric evidences applied to Burkina Faso. Journal of Health Economics 26, 483504.CrossRefGoogle ScholarPubMed
LeClerc-Madlala, S. (2004) Transactional sex and the pursuit of modernity. Social Dynamics 29(2), 121.Google Scholar
Link, B. G. & Phelan, J. (1995) Social conditions as fundamental causes of disease. Journal of Health and Social Behavior 35 (Extra) Issue, 8094.CrossRefGoogle Scholar
Luke, N. (2005) Confronting the ‘sugar daddy’ stereotype in urban Kenya. International Family Planning Perspectives 31(1), 614.CrossRefGoogle ScholarPubMed
Lurie, M. N., Williams, B. G., Zuma, K., Mkaya-Mwamburi, D., Garnett, G. P., Sweat, M. D. et al. (2003) Who infects whom? HIV-1 concordance and discordance among migrant and non-migrant couples in South Africa. AIDS 17(15), 22452252.CrossRefGoogle ScholarPubMed
Lynch, J. W., Davey-Smith, G., Kaplan, G. A. & House, J. S. (2000) Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. British Medical Journal 320, 12001204.CrossRefGoogle ScholarPubMed
Marmot, M. G. (2004) Status Syndrome: How your Social Standing Affects your Health and Life Expectancy. Bloomsbury Publishing, London.Google Scholar
McKenzie, D. J. (2005) Measuring inequality with asset indicators. Journal of Population and Economics 18, 229260.CrossRefGoogle Scholar
Mishra, V. K., Assche, S. B., Greener, R., Vaessen, M., Hong, R., Ghys, P. D. et al. (2007a) HIV infection does not disproportionately affect the poorer in sub-Saharan Africa. AIDS 21 (Supplement 7), S1728.CrossRefGoogle Scholar
Mishra, V. K., Bignami, S., Greener, R., Vaessen, M. & Hong, R. (2007b) A Study of the Association of HIV Infection with Wealth in Sub-Saharan Africa. DHS Working Paper No. 31. URL: Scholar
Mishra, V. K., Vaessen, M., Boerma, T., Arnold, F., Way, A., Barrere, B. et al. (2006) HIV testing in national population based surveys: experience from the demographic and health surveys. Bulletin of the World Health Organization 84(7), 537545.CrossRefGoogle ScholarPubMed
Moran, T. P. (2005) Kuznets's inverted u-curve hypothesis: the rise, demise, and continued relevance of a socioeconomic law. Sociological Forum 20(2), 209244.CrossRefGoogle Scholar
Morris, M. (1997) Sexual networks and HIV. AIDS 11 (Supplement A), S209216.Google ScholarPubMed
Msisha, W. M., Kapiga, S. H., Earls, F. & Subramanian, S. V. (2008a) Socioeconomic status and HIV seroprevalence in Tanzania: a counterintuitive relationship. International Journal of Epidemiology 37, 12971303.CrossRefGoogle Scholar
Msisha, W. M., Kapiga, S. H., Earls, F. & Subramanian, S. V. (2008b) Place matters: multilevel investigation of HIV distribution in Tanzania. AIDS 22, 741748.CrossRefGoogle ScholarPubMed
Opuni-Akuamoa, M. (2009) Issues in assessing the relationship between economic status and HIV infection in sub-Saharan Africa. Doctoral dissertation, Johns Hopkins Bloomberg School of Public Health.Google Scholar
Over, M. (1999) The effects of societal variables on urban rates of HIV infection in developing countries: an exploratory analysis. In Ainsworth, M., Fransen, L. & Over, M. (eds) Confronting AIDS: Evidence from the Developing World. The World Bank, Washington, DC.Google Scholar
Parikh, S. A. (2007) The political economy of marriage and HIV: the ABC approach, “safe” infidelity, and managing moral risk in Uganda. American Journal of Public Health 97(7), 11981208.CrossRefGoogle ScholarPubMed
Parkhurst, J. O. (2008) “What Worked?”: the evidence challenges in determining the causes of HIV prevalence decline. AIDS Education and Prevention 20(3), 275283.CrossRefGoogle ScholarPubMed
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
Poku, N. (2002) Poverty, debt and Africa's HIV/AIDS crisis. International Affairs 78, 531546.CrossRefGoogle Scholar
Potts, M., Halperin, D., Kirby, D., Swidler, A., Marseille, E., Klausner, J. D. et al. (2008) Reassessing HIV prevention. Science 320, 749750.CrossRefGoogle ScholarPubMed
Preston, S. H. (1975) The changing relation between mortality and level of economic development. Population Studies 29, 231248. Reprinted in International Journal of Epidemiology (2007) 36, 484–490.CrossRefGoogle ScholarPubMed
Pronyk, P. M., Kim, J. C., Hargreaves, J. R., Makhubele, M. B., Morison, L. A., Watts, C. et al. (2005) Microfinance and HIV prevention – emerging lessons from rural South Africa. Small Enterprise Development 16, 2638.CrossRefGoogle Scholar
Rapoport, H. (2002) Migration, credit constraints, and self-employment: a simple model of occupational choice, inequality, and growth. Economics Bulletin 15(7), 15.Google Scholar
Rutstein, S. O. & Johnson, K. (2004) The DHS Wealth Index. DHS Comparative Reports No. 6. ORC Macro, Calverton, MD.Google Scholar
Sahn, D. E. & Stifel, D. C. (2003) Urban–rural inequality in living standards in Africa. Journal of African Economies 12(4), 564597.CrossRefGoogle Scholar
Schoepf, B., Schoepf, C. & Millen, J. (2000) Theoretical therapies, remote remedies: SAPs and the political ecology of poverty and health in Africa. In Kim, J. Y., Millen, J. V., Irwin, A. & Gershman, J. (eds) Dying for Growth: Global Inequality and the Health of the Poor. Common Courage Press, Monroe, Maine, pp. 91125.Google Scholar
Shelton, J. D., Cassell, M. M. & Adetunji, J. (2005) Is poverty or wealth at the root of HIV? Lancet 366(9491), 157.CrossRefGoogle ScholarPubMed
Smith, D. J. (2007) Modern marriage, men's extramarital sex, and HIV risk in Southeastern Nigeria. American Journal of Public Health 97(6), 9971005.CrossRefGoogle ScholarPubMed
Stillwaggon, E. (2006) AIDS and the Ecology of Poverty. Oxford University Press.Google Scholar
Talbott, J. R. (2007) Size matters: the number of prostitutes and the global HIV/AIDS pandemic. PLoS ONE 2(6), e543.CrossRefGoogle ScholarPubMed
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. G. & Pickett, K. E. (2006) Income inequality and population health: a review and explanation of the evidence. Social Science & Medicine 62, 17681784.CrossRefGoogle Scholar
Wojcicki, J. M. (2005) Socioeconomic status as a risk factor for HIV infection in women in East, Central and Southern Africa: a systematic review. Journal of Biosocial Science 37(1), 136.CrossRefGoogle ScholarPubMed
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the or variations. ‘’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Available formats

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Available formats

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *