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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.
This 4-year, NIH funded study (1R01HL169503-01A1) 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 explore risk and protective factors for harmful CHB among diverse YSGM.
Further, this study will demonstrate the utility of the predictive models and variable creation for future CHB Just in Time interventions.
Evidence indicates that race/ethnicity-, sexual orientation, and gender-related discrimination is linked to increased harmful cardiometabolic health behaviors (CHB; e.g., sleep, physical activity, and tobacco and alcohol use). However, there is limited research demonstrating the influence of online discrimination, a critical social determinate of health, on CHB among potentially vulnerable groups of SGM.
This 4-year NIH funded (1R01HL173882-01A1) study will illuminate how discrimination operates in online environments and physical spaces, which can be used to better distill risk and inform targeted mediums for harmful CHB prevention interventions among SGM.