We developed contingency tables to compare the independent variables with the outcome. Three bivariate analyses of independent variables and outcomes were done: being screened versus not being screened, which included all patients enrolled; refusing screening versus not being screening for unknown reasons, which included patients that were not screened; and HIV positive versus negative, which included all those screened. Odds ratios (OR) were calculated with 95% confidence intervals (CI). Two multivariate models were constructed using logistic regression, one for predictors of being screened for HIV, and one for predictors of opting out among those not screened for HIV. Both multivariate analyses were done in a stepwise backward manner. Variables associated with the outcome at a p < 0.2 significance as well as others relevant for each of the two outcomes were included in the multivariate model. We excluded missing data in the analysis of the determinants of not being screened for HIV. We included 1197 patients (98 were excluded for missing data: 88 on socio economic status and 10 for all other independent variables) in the multivariable model.