Project Summary Accumulating research suggests that barriers to eliminating the persistent racial disparities in cardiovascular disease (CVD) are related to structural-level social determinants of health (SDOH). The majority of this evidence is cross-sectional, from studies using administrative datasets (i.e., US Census) to quantify structural SDOH and structural racism associations with ecological-level measures of CVD. Prospective and clinical CVD outcome data are needed to advance from descriptive-level evidence; however, well-established cohort studies typically lack access to novel structural determinants. The scientific objective of the research plan is an innovative solution to generate the needed high-quality dataset, by employing data fusion techniques to link structural determinants from administrative datasets with prospective cohort data. I will generate four structural-level determinants at the neighborhood-level using geographic linkages between the Women’s Health Initiative (WHI) cohort with 1) US Census 2) American Community Survey (ACS) 3) Center for Disease Control and 4) Neighborhood Redlining Maps. Each structural determinant includes a measure of racialization and adheres to recent conceptual frameworks for advancing the quantification of structural racism in CVD research. I uniquely measure determinants longitudinally to account for changes in residence and the duration of exposure. In Aim 1 (K99 phase), I will quantify structural racism at the intersection of race and income using the index of concentration at the extremes (ICE). The causal effects of ICE on CVD incidence over 30 years of follow-up will be estimated. This mentored research and training prepare me for the R00 phase research. In Aim 2, I propose to link the Social Vulnerability Index to evaluate a hypothesized structural intervention on CVD. In Aim 3, I propose to estimate CVD risk associated with racial residential segregation and residence in a historically redlined neighborhood. Evaluating causal mechanisms, temporality, life-course exposure, and accounting for race and gender intersectionality would markedly advance the current level of evidence. The public health implications of which may help design future interventions to target modifiable structural policies and practices. The career development plan will advance my scientific training in data fusion techniques, the modeling of structural racism, and pathways to CVD. Through mentored training combined with this research plan, the MOSAIC K99/R00 will prepare me to transition to an independent investigator in a tenure-track faculty position. This award would advance three Objectives of the NHLBI Strategic Vision through the use of (3) an emerging opportunity in data science to accelerate understanding of (7) factors that account for differences in health among populations, led by (8) a scientist who would diversify the scientific workforce.