PROJECT SUMMARY/ABSTRACT Inequality in health outcomes in relation to Americans’ socioeconomic position (SEP) is rising, despite recent evidence that the life expectancy gap between black and white Americans may be decreasing1. The disparity in life expectancy (given survival to age 50) between individuals in the top and bottom deciles of career earnings has nearly doubled over the last 20 years.2 Emerging research has indicated that these inequalities are also observed in studies of cognitive decline, with racial and ethnic minorities and persons of low socioeconomic status demonstrating earlier onset or more rapid cognitive decline in multiple studies. An analysis of the Health and Retirement Study has further found that neighborhood socioeconomic position (SEP) and cardiovascular risk factors increase the odds of poor cognitive function among older adults. Our current NIA-funded study, “Modeling and Forecasting Atherosclerotic Risk: A Complex Systems Approach” (R01AG055480) is utilizing electronic health record (EHR) data in a first-of-its-kind regional, population-derived registry to understand how neighborhood social contexts influence cardiovascular risk across the life course. The NEOCARE Learning Health Registry includes data collected from 1999 to 2019 on more than 3.1 million unique individuals, diverse by race and ethnicity in Northeast Ohio. In this supplement we will implement a multifaceted, systems-based approach for jointly modeling risk of cognitive and cardiovascular disorders. Our work will evaluate the influence of neighborhood conditions on incidence and prevalence of Alzheimer’s and related dementias. We will also describe the relationship between hypertension and cognitive function across the socioeconomic spectrum, with a special focus on the mediating influence of antihypertensive therapies. Lastly, we aim to investigate and compare the influence of immuno-hematologic function, obesity and cardiovascular disease and SEP on cognitive function. The results of our study are expected to improve the effectiveness and delivery of primary care services by (i) promoting a deeper understanding about how short and long-term contextual factors involving patients’ social and physical environments lead to variation in Alzheimer’s disease onset and outcomes; and (ii) identifying and quantifying the importance of modifiable risk factors across heterogeneous populations that can be used to develop population-specific interventions to prevent or delay the onset of Alzheimer’s and dementia. This research is anticipated to yield new mechanistic insights, hypotheses for testing in future research applications, more accurate and representative models for predicting Alzheimer’s disease and dementia, and a basis for informing decisions at multiple strategic and programmatic levels.