Gender Minority Stress, Support, and Inflammation in Transgender and Gender-Nonconforming Youth.

Transgender and gender-nonconforming (TGNC) youth often report higher rates of chronic social stressors such as victimization, discrimination, and rejection. Some of these gender-based stressors may have long-range physical health consequences through inflammation pathways. This study evaluates the feasibility and acceptability of adding biological measures of inflammation to an ongoing prospective clinical study of TGNC youth (ages 9-20 years), initiating affirming medical therapy at a large, urban children's hospital (=56). We also examine the relationship between gender-based sources of stress and support with inflammation. This is the first study to explore how gender identity, social stressors, and social supports may contribute to poorer health in TGNC youth through inflammation and immune dysregulation pathways. Between October 2016 and August 2018, the study team collected dried blood spot (DBS) samples and health measures during clinical visits. Participants also completed computer-assisted surveys assessing gender minority stress and support during these visits. We used regression analysis to evaluate differences in C-reactive protein (CRP) controlling for demographics, health, gender-based stress, and supports. The results from this study indicate that adding DBS samples to assess inflammation was feasible and acceptable in a clinical sample of TGNC youth seeking affirming-medical interventions. We found an association between greater inflammation and the composite score for greater gender-based stressors and lower gender-based supports using the Gender Minority Stress and Resilience Tool (GMSR); however, we did not find statistically significant differences in CRP associated with any of the individual GMSR subscales assessing various types of gender-based supports or stressors. More research is necessary to evaluate how different sources of gender-based support and stress relate to inflammation with larger sample sizes.