Sexually transmitted diseases · 2020
County-Level Social Capital and Bacterial Sexually Transmitted Infections in the United States.
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Owusu-Edusei Kwame, McClendon-Weary Bryttany, Bull Lara, Gift Thomas L, Aral Sevgi O
Аннотация
BACKGROUND: The association between county-level social capital indices (SCIs) and the 3 most commonly reported sexually transmitted infections (STIs) in the United States is lacking. In this study, we determined and examined the association between 2 recently developed county-level SCIs (ie, Penn State Social Capital Index [PSSCI] vs United States Congress Social Capital Index [USCSCI]) and the 3 most commonly reported bacterial STIs (chlamydia, gonorrhea, and syphilis) using spatial and nonspatial regression techniques.
METHODS: We assembled and analyzed multiyear (2012-2016) cross-sectional data on STIs and 2 SCIs (PSSCI vs USCSCI) on counties in all 48 contiguous states. We explored 2 nonspatial regression models (univariate and multiple generalized linear models) and 3 spatial regression models (spatial lag model, spatial error model, and the spatial autoregressive moving average model) for comparison.
RESULTS: Without exception, all the SCIs were negatively associated with all 3 STI morbidities. A 1-unit increase in the SCIs was associated with at least 9% (P < 0.001) decrease in each STI. Our test of the magnitude of the estimated associations indicated that the USCSCI was at least 2 times higher than the estimates for the PSSCI for all STIs (highest P value = 0.01).
CONCLUSIONS: Overall, our results highlight the potential benefits of applying/incorporating social capital concepts to STI control and prevention efforts. In addition, our results suggest that for the purpose of planning, designing, and implementing effective STI control and prevention interventions/programs, understanding the communities' associational life (as indicated by the factors/data used to develop the USCSCI) may be important.
METHODS: We assembled and analyzed multiyear (2012-2016) cross-sectional data on STIs and 2 SCIs (PSSCI vs USCSCI) on counties in all 48 contiguous states. We explored 2 nonspatial regression models (univariate and multiple generalized linear models) and 3 spatial regression models (spatial lag model, spatial error model, and the spatial autoregressive moving average model) for comparison.
RESULTS: Without exception, all the SCIs were negatively associated with all 3 STI morbidities. A 1-unit increase in the SCIs was associated with at least 9% (P < 0.001) decrease in each STI. Our test of the magnitude of the estimated associations indicated that the USCSCI was at least 2 times higher than the estimates for the PSSCI for all STIs (highest P value = 0.01).
CONCLUSIONS: Overall, our results highlight the potential benefits of applying/incorporating social capital concepts to STI control and prevention efforts. In addition, our results suggest that for the purpose of planning, designing, and implementing effective STI control and prevention interventions/programs, understanding the communities' associational life (as indicated by the factors/data used to develop the USCSCI) may be important.