Determinants of HIV prevalence among female sex workers in four south Indian states: analysis of cross-sectional surveys in twenty-three districts
- 1 December 2008
- journal article
- research article
- Published by Wolters Kluwer Health in AIDS
- Vol. 22 (Suppl 5) , S35-S44
- https://doi.org/10.1097/01.aids.0000343762.54831.5c
Abstract
In four states in southern India we explored the determinants of HIV prevalence among female sex workers (FSW), as well as factors associated with district-level variations in HIV prevalence among FSW. Data from cross-sectional surveys in 23 districts were analysed, with HIV prevalence as the outcome variable, and sociodemographic and sex work characteristics as predictor variables. Multilevel logistic regression was applied to identify factors that could explain variations in HIV prevalence among districts. HIV prevalence among the 10 096 FSW surveyed was 14.5% (95% confidence interval 14.0-15.4), with a large interdistrict variation, ranging from 2% to 38%. Current marital status and the usual place of solicitation emerged as important factors that determine individual probability of being HIV positive, as well as the HIV prevalence within districts. In multivariate analysis, compared with home-based FSW, the odds of being HIV positive was greater for brothel-based FSW [adjusted odds ratio (AOR) 2.17, P <or= 0.001] and for public place-based FSW (AOR 1.32, P = 0.005). Unmarried FSW and those who were widowed/divorced/separated, or from the devadasi tradition, had higher odds of being HIV positive (AOR 1.79, P <or= 0.001 and 1.98, P < 0.001, respectively), than those currently married. The estimated district level variance in HIV prevalence was lowest (0.152) for brothel-based unmarried FSW, followed by brothel-based widowed/divorced/separated or devadasi FSW (0.192). Heterogeneity in the organization and structure of sex work is an important determinant of variations in HIV prevalence among FSW across districts in India, much more so than the districts themselves. This understanding should help to improve the design of HIV preventive interventions.Keywords
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