PROJECT SUMMARY Sexual and gender minorities are at an increased risk of cardiovascular disease (CVD) at an earlier age than heterosexuals. One of the reasons is that emerging adult (18-29) young sexual and gender minorities (YSGM) have higher rates of harmful cardiometabolic health behaviors (CHB; e.g., physical inactivity, dysregulated sleep, smoking, and alcohol use) than cisgender heterosexuals. One key factor that leads to increased rates of harmful CHB within YSGM is exposure to intersectional discrimination (i.e., the experiences of discrimination occurring amid multiple identities and/or positions [e.g., race/ethnicity, gender identity, sexual orientation]). Although there is currently research demonstrating links between intersectional discrimination and cardiometabolic health behaviors among SGM, much of this research cannot characterize the experiences and effects of intersectional discrimination on CHB in ways that reflect the lived experience of race, place, and identity among YSGM. Thus, to better understand the contextual features that influence intersectional discrimination on CHB, we will employ a geographically explicit ecological momentary assessment (GEMA) and a qualitative mapping approach. This approach will help to reveal the rich, context specific, experiences of intersectional discrimination, protective social and interpersonal factors, and CHB across and within different racial groups of YSGM. The qualitative mapping method involves making maps of participant activities based on their geolocation and EMA data (gathered via GEMA) and then conducting an in-depth qualitative interview to explore participants’ thoughts, feelings, and experiences while in the mapped locations. This approach is critically important as YSGM experience unique exposures to intersectional discrimination based on the geographical locations in which they travel, while also having differing appraisals of discrimination experiences based on the features of these spaces (e.g., time spent in them, purpose [school, home, work], safety). Our overarching approach is to utilize GEMA and qualitative mapping to understand the complex relationships between environmental and interpersonal experiences of intersectional discrimination and related CHB behaviors for YSGM. Specifically, this study aims to; 1) examine how daily experiences of intersectional discrimination and CHB differ by level of structural inequality, measured by the combination of individual GPS and census data among YSGM; 2) examine how social protections (e.g., community relationships, social cohesion) buffer the negative effects of intersectional discrimination on CHB among YSGM; and 3) explore context-specific risks/protective factors associated with CHB across different racial/ethnic groups of YSGM using GEMA methodology. In all, our innovative approach allows reporting of experiences of intersectional discrimination in real time while also considering the situational factors that are associated with these experiences to improve external validity. This study is significant because it will inform tailored harmful CHB prevention interventions for diverse groups of YSGM, including future Just in Time interventions.

PROJECT NARRATIVE Existing approaches to measuring intersectional discrimination (i.e., racial/ethnic-, sexual orientation, and/or gender-related) and related cardiometabolic health behaviors (CHB; i.e., physical inactivity, dysregulated sleep, and tobacco and alcohol use) lack the ability to capture the real-world context in which intersectional discrimination occurs, the momentary appraisal of such events, and resultant behaviors. To address this limitation, we will use a validated novel geographically-explicit momentary assessment (GEMA) method, which allows for the accurate capturing of the duration and frequency of exposure situated within the context in which these behaviors and exposures occur among young sexual and gender minorities (YSGM) as well as explores risk and protective factors for harmful CHB among diverse YSGM. This study will demonstrate the utility of the predictive models and variable creation for future CHB Just in Time interventions.