METHODS: Data are a subset (N=30,999) of 18-65 year olds from the National Epidemiological Survey of Alcohol and Related Conditions III (NESARC-III), a nationally representative study of adults in the United States. Of this sample, 3,349 (10.8%) were classified as SM based on their sexual attraction, behavior, or identity. Logistic time-varying effect models (TVEMs) were used to compare the age-varying odds of experiencing each of seven health outcomes in the past year (major depressive episode (MDE); generalized anxiety disorder (GAD); drug, alcohol, and tobacco use disorders; STD, cardiovascular disease), and how these odds differed by SM status.
RESULTS: The odds of experiencing all health outcomes in this analysis were generally higher among SM compared to non-SM individuals. For GAD and MDE, the largest disparities were seen in early adulthood; for example, at age 18 SM individuals had nearly four times greater odds of GAD compared to non-SM individuals. These associations steadily decreased until age 60, when the odds of experiencing either mental health outcome were not significantly different by SM status. Differences in alcohol, drug, and tobacco use disorders by SM status peaked in the late forties/early fifties and then declined. Sexual minority status was also significantly associated with STD diagnosis. The association between SM status and STD peaked around age 30, when SM had 5 times greater odds than non-SM. Finally, the odds of cardiovascular disease were not statistically different until age 40, when the odds nearly doubled for SM individuals.
DISCUSSION: Our findings provide evidence of the health disparities affecting sexual minority individuals and how these disparities persist across the life course. Our results indicate there are key periods of increased odds of disease for SM individuals. For example, mental health disparities are greatest in early adulthood, while the disparity related to STD diagnoses and cardiovascular disease peaks at age 30 and 40, respectively. These findings provide information to spur more nuanced examinations of health disparities and can help researchers determine critical ages periods for interventions.