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Does the ‘inverse equity hypothesis’ explain how both poverty and wealth can be associated with HIV prevalence in sub-Saharan Africa?
  1. James R Hargreaves1,
  2. Calum Davey1,
  3. Richard G White2
  1. 1Department of Social and Environmental Health Research, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, UK
  2. 2Department of Infectious Disease Epidemiology Faculty of Epidemiology & Population Health, London School of Hygiene and Tropical Medicine
  1. Correspondence to Dr James R Hargreaves, Department of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; james.hargreaves{at}

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Whether it is relative wealth or relative poverty that drives the HIV epidemic in sub-Saharan Africa, is a controversial aspect of HIV/AIDS epidemiology. We suggest that the social epidemiology of HIV in Africa is changing. Previously, new infections were more rapidly acquired by those of relatively higher socioeconomic position (SEP). More recently, those of relatively low SEP are at greater risk. If confirmed, we further suggest in this paper that this pattern would be compatible with Cesar Victora's ‘inverse equity hypothesis’, first articulated in relation to child morbidity and mortality. The hypothesis suggests that those of higher SEP benefit first from new health interventions.1

Reviews draw different conclusions about the association between SEP and HIV infection within sub-Saharan African countries. Some authors stress that poverty is a key driver of HIV, and that poverty alleviation is the only sustainable solution.2 Others show that higher education and greater relative wealth are associated with greater HIV risk, making HIV unusual in this respect.3 A 2010 study suggests that contextual factors are key, and that ‘being poor or being wealthy may be associated with sets of behaviours that are either protective or risky for HIV infection’.4

There might be several methodological reasons for diversity in the association between SEP and HIV infection rates noted in African studies. First, a range of different populations have been studied. Some studies have analysed data from unlinked anonymous HIV testing of samples collected among antenatal clinic attendees, while others have recruited study participants in household surveys of the general population. Both types of study can suffer from biases affecting the reported association between SEP and HIV.5–7

Second, study sampling frames vary. Some studies recruit participants from within small geographic areas while others have sampled nationally. Heterogeneity in SEP among study participants will …

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  • Contributors JRH conceived the paper and wrote the first draft. CD extracted data from DHS reports and contributed to the writing. RGW did the mathematical modelling work for the paper.

  • Funding JH was supported by STRIVE, a Research Programme Consortium funded by UKaid from the Department for International Development. STRIVE is a collaboration dedicated to tackling the structural drivers of HIV. RGW is funded by a Medical Research Council (UK) Methodology Research Fellowship (G0802414), the Consortium to Respond Effectively to the AIDS/TB Epidemic (19790.01), and the Bill and Melinda Gates Foundation (21675).

  • Competing interests None.

  • Provenance and peer review Not commissioned; externally peer reviewed.