The disproportionate high risk of HIV infection among the urban poor in sub-Saharan Africa

AIDS Behav. 2013 Jun;17(5):1645-54. doi: 10.1007/s10461-012-0217-y.

Abstract

The link between HIV infection and poverty in sub-Saharan Africa (SSA) is rather complex and findings from previous studies remain inconsistent. While some argue that poverty increases vulnerability, existing empirical evidence largely support the view that wealthier men and women have higher prevalence of HIV. In this paper, we examine the association between HIV infection and urban poverty in SSA, paying particular attention to differences in risk factors of HIV infection between the urban poor and non-poor. The study is based on secondary analysis of data from the Demographic and Health Surveys from 20 countries in SSA, conducted during 2003-2008. We apply multilevel logistic regression models, allowing the urban poverty risk factor to vary across countries to establish the extent to which the observed patterns are generalizable across countries in the SSA region. The results reveal that the urban poor in SSA have significantly higher odds of HIV infection than their urban non-poor counterparts, despite poverty being associated with a significantly lower risk among rural residents. Furthermore, the gender disparity in HIV infection (i.e. the disproportionate higher risk among women) is amplified among the urban poor. The paper confirms that the public health consequence of urban poverty that has been well documented in previous studies with respect to maternal and child health outcomes does apply to the risk of HIV infection. The positive association between household wealth and HIV prevalence observed in previous studies largely reflects the situation in the rural areas where the majority of the SSA populations reside.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Africa South of the Sahara / epidemiology
  • Age Factors
  • Female
  • HIV Infections / epidemiology
  • HIV Infections / etiology*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Poverty / statistics & numerical data*
  • Prevalence
  • Risk Factors
  • Sex Factors
  • Urban Population / statistics & numerical data*
  • Young Adult