OBJECTIVE: To examine the extent to which the regional and neighborhood distribution of HIV in Tanzania is caused by the differential distribution of individual correlates and risk factors. METHODS: Nationally representative, cross-sectional data on 12,522 women and men aged 15-49 years from the 2003-2004 Tanzanian AIDS Indicator Survey. Three-level multilevel binary logistic regression models were specified to estimate the relative contribution of regions and neighborhoods to the variation in HIV seroprevalence. RESULTS: Spatial distribution of individual correlates (and risk factors) of HIV do not explain the neighborhood and regional variation in HIV seroprevalence. Neighborhoods and regions accounted for approximately 14 and 6% of the total variation in HIV. HIV prevalence ranged from 1.8% (Kigoma) to 6.7% (Iringa) even after adjusting for the compositional make-up of these regions. An inverse association was observed between log odds of being HIV positive and neighborhood poverty [odds ratio (OR) 0.24, 95% confidence interval (CI) 0.09-0.61] and regional poverty (OR 0.97, 95% CI 0.95-0.99). CONCLUSION: Our study provides evidence for independent contextual variations in HIV, above and beyond that which can be ascribed to geographical variations in individual-level correlates and risk factors. We emphasize the need to adopt both a group-based and a place-based approach, as opposed to the dominant high-risk group approach, for understanding the epidemiology of HIV as well as for developing HIV intervention activities.
OBJECTIVE: To examine the extent to which the regional and neighborhood distribution of HIV in Tanzania is caused by the differential distribution of individual correlates and risk factors. METHODS: Nationally representative, cross-sectional data on 12,522 women and men aged 15-49 years from the 2003-2004 Tanzanian AIDS Indicator Survey. Three-level multilevel binary logistic regression models were specified to estimate the relative contribution of regions and neighborhoods to the variation in HIV seroprevalence. RESULTS: Spatial distribution of individual correlates (and risk factors) of HIV do not explain the neighborhood and regional variation in HIV seroprevalence. Neighborhoods and regions accounted for approximately 14 and 6% of the total variation in HIV. HIV prevalence ranged from 1.8% (Kigoma) to 6.7% (Iringa) even after adjusting for the compositional make-up of these regions. An inverse association was observed between log odds of being HIV positive and neighborhood poverty [odds ratio (OR) 0.24, 95% confidence interval (CI) 0.09-0.61] and regional poverty (OR 0.97, 95% CI 0.95-0.99). CONCLUSION: Our study provides evidence for independent contextual variations in HIV, above and beyond that which can be ascribed to geographical variations in individual-level correlates and risk factors. We emphasize the need to adopt both a group-based and a place-based approach, as opposed to the dominant high-risk group approach, for understanding the epidemiology of HIV as well as for developing HIV intervention activities.
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