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Wealth Status and Risky Sexual Behaviour in Ghana and Kenya
Authors: Awusabo-Asare, Kofi; Annim, Samuel K.
Source: Applied Health Economics and Health Policy, Volume 6, Number 1, 2008 , pp. 27-39(13)
Topic(s): Sexual behavior
Wealth Index
Country: Africa
  Ghana
  Kenya
Published: 2008
Abstract: Abstract: Background: Emerging evidence seems to suggest that there is some association between individual socioeconomic status and sexual risk-taking behaviour in sub-Saharan Africa. A number of broad associations have emerged, among them, positive, neutral and negative relationships between wealth status and sexual risk-taking behaviour. Reduction in the number of sex partners as a behavioural change has been advocated as an important tool in HIV prevention, and affecting such a change requires an understanding of some of the factors that can influence social behaviour, interactions and activities of subpopulations. Objectives: To further explore the determinants of sexual risk-taking behaviour (individuals having multiple sex partners), especially the effects that variations in household wealth status, gender and different subpopulation groups have on this behaviour. Methods: The relationship between wealth status and sexual risk-taking behaviour in the context of HIV/AIDS infection in Ghana and Kenya was assessed using raw data from the 2003 Demographic and Health Surveys of each country. Wealth quintiles were used as a proxy for economic status, while non-marital and non-cohabiting sexual partnerships were considered indicators for risky sexual behaviour. Results: For females, there appears to be an increasing probability of sexual risk taking by wealth status in Kenya, while, in Ghana, an inverted J-shaped relationship is shown between wealth status and sexual risk taking. When controlled for other variables, the relationship between wealth status and sexual risk-taking behaviour disappears for females in the two countries. For males, there is no clearly discernable pattern between wealth status and sexual risk-taking behaviour in Ghana, while there is a general trend towards increasing sexual risk-taking behaviour by wealth status in Kenya. For Ghana, the highest probabilities are among the highest and the middle wealth quintiles; in Kenya, high probabilities were found for the two highest wealth quintiles. Controlling for the effects of other factors, the pattern for Ghana is further blurred (not statistically significant), but the relationship continues to show in the case of Kenya, and is significant for the highest quintile. In general, for both Ghana and Kenya, men in the highest wealth quintile were found to be more likely to have multiple sexual partners than the other groups. Conclusion: The changing phases of HIV infection indicate that it is no longer poverty that drives the epidemic. Rather, it is wealth and a number of other sociodemographic factors that explain sexual risk-taking behaviour that puts people at risk. Understanding local specific factors that predispose individuals towards sexual risk taking could help to expand the range of information and services needed to combat the HIV pandemic.