title: Does knowing someone with AIDS affect condom use? An analysis from South Africa.
abstract: Prior research in Africa suggests that personally knowing someone with HIV/AIDS or who died of AIDS (PWA) may positively influence HIV-preventive behaviors such as condom use, by countering denial and increasing perceived risk. This article uses data from the 1998 South Africa Demographic and Health Survey (DHS) of women to examine this hypothesis in South Africa, where AIDS mortality is high. Logistic regression was applied to assess whether knowing a PWA was associated with condom use, net of the effects of possible confounders. Contrary to previous findings, analyses showed no association between condom use and having known a PWA. Condom use was strongly associated with knowledge that condoms can prevent HIV/AIDS, sex with a non-marital partner, higher education level, younger age, and urban residency. Findings suggest that communities should expand preventive efforts given the current level of AIDS mortality. Campaigns must reinforce messages that condoms are effective, and reach rural, less educated women, for whom HIV risk is high in South Africa.
authors.affiliation: Africa Centre for Health and Population Studies, South Africa. cscamlin@yahoo.com
authors.forename: Carol S
authors.initials: CS
authors.lastname: Camlin
authors.forename: Chiweni E
authors.initials: CE
authors.lastname: Chimbwete
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000453:epidemiology* / Q000523:psychology*; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D017280:Condoms / Q000706:statistics & numerical data*; D005114:Extramarital Relations; D005260:Female; D033062:Friends / Q000523:psychology*; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D007398:Interpersonal Relations; D008393:Marriage / Q000706:statistics & numerical data; D008875:Middle Aged; D015999:Multivariate Analysis; D012044:Regression Analysis; D012424:Rural Population / Q000706:statistics & numerical data; D021841:Safe Sex / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D013019:South Africa / Q000453:epidemiology; D014505:Urban Population / Q000706:statistics & numerical data