Propensity score analysis assessing the burden of non-communicable diseases among the transgender population in the united states using the behavioral risk factor surveillance system (2017–2019)

Abstract

Research to assess the burden of non-communicable diseases (NCDs) among the transgender population needs to be prioritized given the high prevalence of chronic conditions and associated risk factors in this group. Previous cross-sectional studies utilized unmatched samples with a significant covariate imbalance resulting in a selection bias. Therefore, this cross-sectional study attempts to assess and compare the burden of NCDs among propensity score-matched transgender and cisgender population groups. This study analyzed Behavioral Risk Factor Surveillance System data (2017–2019) using complex weighting procedures to generate nationally representative samples. Logistic regression was fit to estimate propensity scores. Transgender and cisgender groups were matched by sociodemographic variables using a 1:1 nearest neighbor matching algorithm. McNemar, univariate, and multivariate logistic regression analyses were conducted among matched cohorts using R and SPSS version 26 software. Compared with the cisgender group, the transgender group was significantly more likely to have hypertension (31.3% vs. 27.6%), hypercholesteremia (30.8% vs. 23.7%), prediabetes (17.3% vs. 10.3%), and were heavy drinkers (6.7% vs. 6.0%) and smokers (22.4% vs. 20.0%). Moreover, the transgender group was more than twice as likely to have depression (aOR: 2.70, 95% CI 2.62–2.72), stroke (aOR: 2.52 95% CI 2.50–2.55), coronary heart disease (aOR: 2.77, 95% CI 2.74–2.81), and heart attack (aOR: 2.90, 95% CI 2.87–2.94). Additionally, the transgender group was 1.2–1.7 times more likely to have metabolic and malignant disorders. Differences were also found between transgender subgroups compared with the cisgender group. This study provides a clear picture of the NCD burden among the transgender population. These findings offer an evidence base to build health equity models to reduce disparities among transgender groups.