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African Population Studies
Union for African Population Studies
ISSN: 0850-5780
Vol. 25, No. 2, 2011, pp. 457-470
Bioline Code: ep11037
Full paper language: English
Document type: Research Article
Document available free of charge

African Population Studies, Vol. 25, No. 2, 2011, pp. 457-470

 en Household HIV/AIDS status and sexual debut among adolescents in Kenya
Magadi, Monica & Olayo, Rose


Adolescents in households affected by HIV/AIDS may be at an increased risk of poorer reproductive health than other adolescents due to the impoverishing effects of AIDS in households or lack of parental guidance. In this paper, we examine the effect of parents’ HIV status on adolescent sexual and reproductive health, focusing on early sexual debut among adolescents in Kenya. The analysis places particular emphasis on comparisons of the relative disadvantage of different groups of adolescents aged 15-17 years, with particular reference to those living in households where an adult is infected with HIV. The data come from the 2003 and 2008 Kenya Demographic and Health Surveys (KDHS). The results suggest increased vulnerability among adolescent boys and girls living in households where an adult is infected with HIV, especially when other household factors are controlled for. On average, adolescent boys and girls living in households where at least one adult is infected with HIV have about 50% higher odds of having initiated sexual activity compared to their counterparts of similar age and gender in households where no adult is HIV positive. The odds are more than 60% higher when household characteristics and circumstances relating to wealth, household head and living arrangements are controlled for. Further analysis reveals that the observed vulnerability among adolescents living in households with HIV infected adults is partly explained by background factors relating to region of residence and ethnicity and to a lesser extent by school non-attendance and mass media exposure.

Adolescent sexual debut; adolescents affected by HIV/AIDS; Kenya; Demographic and Health Surveys; logistic regression models

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