OBJECTIVE: To examine the relationship between multiple dimensions of socioeconomic status (SES) and HIV seroprevalence in Tanzania. METHODS: Using a large nationally representative sample of 7515 sexually active adults drawn from the 2003-04 Tanzania HIV/AIDS Indicator Survey, we analysed the relationship between multiple SES measures and HIV seroprevalence using weighted logistic regression models. RESULTS: In adjusted models, individuals in the highest quintile of standard of living had increased odds ratio (OR) of being HIV-positive (male: OR 2.38, 95% CI 1.17-4.82; female: OR 3.74, 95% CI 2.16-6.49). Occupational status was differentially associated with HIV in men and women; women in professional jobs had higher OR of being HIV-positive (OR 1.54, 95% CI 1.02-2.38), whereas unemployed men had higher risk of being HIV-positive (OR 3.49, 95% CI 1.43-8.58). No marked association was found between increasing education and HIV seroprevalence for men (P = 0.83) and women (P = 0.87). CONCLUSION: Contrary to the prevailing perception that low SES individuals tend to be more vulnerable to HIV-infection, we found a positive association between standard of living and HIV-infection. Strategies aimed at reducing HIV-infection needs to be cognizant of the complex social heterogeneity in the patterns of HIV-infection.
OBJECTIVE: To examine the relationship between multiple dimensions of socioeconomic status (SES) and HIV seroprevalence in Tanzania. METHODS: Using a large nationally representative sample of 7515 sexually active adults drawn from the 2003-04 Tanzania HIV/AIDS Indicator Survey, we analysed the relationship between multiple SES measures and HIV seroprevalence using weighted logistic regression models. RESULTS: In adjusted models, individuals in the highest quintile of standard of living had increased odds ratio (OR) of being HIV-positive (male: OR 2.38, 95% CI 1.17-4.82; female: OR 3.74, 95% CI 2.16-6.49). Occupational status was differentially associated with HIV in men and women; women in professional jobs had higher OR of being HIV-positive (OR 1.54, 95% CI 1.02-2.38), whereas unemployed men had higher risk of being HIV-positive (OR 3.49, 95% CI 1.43-8.58). No marked association was found between increasing education and HIV seroprevalence for men (P = 0.83) and women (P = 0.87). CONCLUSION: Contrary to the prevailing perception that low SES individuals tend to be more vulnerable to HIV-infection, we found a positive association between standard of living and HIV-infection. Strategies aimed at reducing HIV-infection needs to be cognizant of the complex social heterogeneity in the patterns of HIV-infection.
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