97 Neighborhood level stressors, resilience sources, and other characteristics among sexual minority groups - Chen Zhang; Wonkyung Chang; Yu Liu; Yu Yang; Cait Dreisbach (Journal of Clinical and Translational Science)
Objectives/Goals: Sexual minority populations (SMPs), including lesbian, gay, and bisexual groups, disproportionately encounter discriminatory experiences due to bi/homonegativity and systemic inequities across various social domains. We aim to understand how the neighborhood-level stressors and resilience sources differed across specific groups in SMPs. Methods/Study Population: Utilizing the NIH All of Us’ cloud-based platform, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n = 5267), or straight (n  =  349,748). We explored multiple key measures of neighborhood-level stressors (e.g., neighborhood disorder, neighborhood cohesion, and environment index) and resilience sources (e.g., neighbor cohesion, social support), and other factors (e.g., food insecurity, housing insecurity, and housing instability) by their sexual orientations using analysis of variance or Chi-square analyses. Results/Anticipated Results: Our sample comprised 60.8% females and 37.5% males identifying as non-binary or transgender, with an average age of 55.6 years (SD  =  17.1). The racial composition was 56.0% White, 19.4% Black, 18.7% Hispanic, and 5.9% others (e.g., Asian, multiracial). Compared to straight individuals, SMPs reported high neighborhood stressors (e.g., disorder, worse environment) but lower neighborhood-level resilience sources (e.g., social support, cohesion). In addition, bisexual groups reported highest prevalence of housing insecurity (6.7% vs. 2.3%), housing instability (36.0% vs. 19.6%), and food insecurity (26.57% vs. 12.21%). Discussion/Significance of Impact: SMPs, particularly bisexual individuals, face greater neighborhood stressors and fewer resilience sources than their straight counterparts. These findings call for targeted interventions to address these disparities and promote health equity, using large-scale datasets to inform community-based solutions.