Statistical analysis
HIV primary care clinics in the same region
REGRESSION
Although the study design prevents causal interpretation of our findings, our analyses were motivated by causal questions–in particular, the possible influence of the COVID-19 pandemic on mental health and HIV care. Participants in both cohorts were enrolled at HIV primary care clinics in the same region and recruited using the same study inclusion criteria; however, it is possible that there are underlying differences in the two study populations that could influence the findings. Thus, to adjust for unmeasured confounders we employed a quasi-experimental strategy. Specifically, we estimated prevalence differences in mental health before and during the COVID-19 pandemic using stabilized inverse probability of treatment weighting (IPTW). IPTW creates a pseudo population by weighting individuals such that observed confounders are equally distributed across exposed (during COVID-19) and unexposed (pre-COVID-19) groups. Weights were defined as 1/propensity score for the exposed group and 1/(1—propensity score) for the unexposed group. Propensity scores were estimated using a logistic regression model with known predictors of mental health selected a priori including age, sex, primary language, education, marital status, household head, overall health, and work status as covariates [