Social Capital and Rates of Gonorrhea and Syphilis in the United States: Spatial Regression Analyses of State-Level Associations

We conducted spatial regression analysis to account for spatial clustering of sexually transmitted diseases (STDs) and to examine the state-level association between social capital (using Putnam’s public use data set) and rates of gonorrhea and syphilis. We conducted the analysis for the 48 contiguous states of the United States for 1990, 1995, and 2000 and controlled for the effects of regional variation in STD rates, and for state variation in poverty, income inequality, racial composition, and percentage aged 15–34 years. We compared the results of the spatial regression analysis with those of ordinary least squares (OLS) regression. Controlling for all population-level variables, the percentage of variation explained by the OLS regression and by the spatial regression were similar (mid-90s for gonorrhea and low-70s for syphilis), the standardized parameter estimates were similar, and the spatial lag parameter was not statistically significant. Social capital was not associated with STD rates when state variation in racial composition was included in the regression analysis. In this analysis, states with a higher proportion of residents who were African-American had higher STD rates. When we did not control for racial composition, regression analysis showed that states with higher social capital had lower STD rates. We conjecture that sexual networks and sexual mixing drive the association between social capital and STD rates and highlight important measurement and research questions that need elucidation to understand fully the relationship between social capital and STDs

Social capital and rates of gonorrhea and syphilis in the United States: Spatial regression analyses of state-level associations

We conducted spatial regression analysis to account for spatial clustering of sexually transmitted diseases (STDs) and to examine the state-level association between social capital (using Putnam's public use data set) and rates of gonorrhea and syphilis. We conducted the analysis for the 48 contiguous states of the United States for 1990, 1995, and 2000 and controlled for the effects of regional variation in STD rates, and for state variation in poverty, income inequality, racial composition, and percentage aged 15-34 years. We compared the results of the spatial regression analysis with those of ordinary least squares (OLS) regression. Controlling for all population-level variables, the percentage of variation explained by the OLS regression and by the spatial regression were similar (mid-90s for gonorrhea and low-70s for syphilis), the standardized parameter estimates were similar, and the spatial lag parameter was not statistically significant. Social capital was not associated with STD rates when state variation in racial composition was included in the regression analysis. In this analysis, states with a higher proportion of residents who were African-American had higher STD rates. When we did not control for racial composition, regression analysis showed that states with higher social capital had lower STD rates. We conjecture that sexual networks and sexual mixing drive the association between social capital and STD rates and highlight important measurement and research questions that need elucidation to understand fully the relationship between social capital and STDs.Social capital Sexually transmitted diseases Spatial regression Sexual mixing Gonorrhea Syphilis USA

Extensions of respondent-driven sampling: a new approach to the study of injection drug users aged 18–25

Researchers generally use nonprobability methods such as chain-referral sampling to study populations for which no sampling frame exists. Respondent-driven sampling is a new form of chain-referral sampling that was designed to reduce several sources of bias associated with this method, including those from the choice of initial participants, volunteerism, and masking. This study expands this method by introducing "steering incentives," supplemental rewards for referral of members of a specific group, injection drug users (IDUs) aged 18-25. The results are based on an interrupted time series analysis in which 196 IDUs from Meriden, CT, were interviewed before introduction of the steering incentives, and another 190 were interviewed afterwards. The steering incentives increased the percentage of younger IDUs sampled by 70%. We compared recruitment patterns with institutional data and self-reported personal networks to determine representativeness and whether volunteerism or masking were present. The results indicated that steering incentives helped to increase recruitment of younger IDUs, that the sample was representative, and that both volunteerism and masking were modest