Statistical analysis
REGRESSION
We summarized participants' demographic data using medians and interquartile ranges (IQRs) for continuous variables and frequency counts and percentages for categorical variables. Frequency counts and percentages with 95% confidence intervals (CIs) were calculated for the prevalence estimate of each individual STI and prevalence of any STI. To account for participation bias, we calculated weighted prevalence estimates to account for the stratified sample design, calculated as the inverse probability of study participation in strata defined by age group and sex. We used logistic regression to estimate the odds ratios and 95% CIs for factors associated with the presence of any curable STI and factors associated with treatment in univariate and multivariable models. Age and sex were included a priori in the multivariable model; other factors with 