ABSTRACT. Alzheimer's Disease and Related Disorders (ADRD) are leading causes of death in the United States that disproportionately impact individuals with less education and income. There is substantial evidence that ADRD is strongly patterned by socioeconomic status across the lifecourse. However, little prior work has evaluated whether socioeconomic interventions to increase socioeconomic status reduce the population burden of ADRD, or if there are differentially effects by sociodemographic subgroup, resulting in smaller disparities; this proposal addresses this critical gap in the literature. We evaluate socioeconomic interventions that increased years of education (Aim 1) and income security (Aim 2) to determine if such interventions impacted dementia risk overall, and whether structurally minoritized groups (Black Americans, individuals from low childhood SES backgrounds, and people who grew up in rural areas or the South) differentially benefited (Aim 3). We will use data from Health and Retirement Study (HRS), the Reasons for Geographic and Racial Differences in Stroke cohort (REGARDS), and the National Longitudinal Survey of Youth, 1979 cohort to evaluate these aims. Our research team has previously published using all three data sets. Aim 1 will evaluate whether expansion of college access reduced ADRD risk; hypothesis 1 evaluates college geographic accessibility via increases in 2 and 4-year higher education institutions per capita, while hypothesis 2 evaluates college financial accessibility via a large social intervention that subsidized college education (the Vietnam War GI Bill). Aim 2 will evaluate whether policies that increased income security reduced ADRD risk; hypothesis 1 evaluates the long-term effects of a working age poverty-alleviation policy (the earned income tax credit), while hypothesis 2 evaluates retirement income security (Social Security). Aim 3 will evaluate whether the education and income security interventions examined in Aims 1 and 2 reduced socioeconomic, racial, and geographic disparities in ADRD; differential effects will be evaluated using interaction terms, quantile regression, and distributional decomposition. If our hypotheses are confirmed, results from this research will provide direct evidence for solutions to reduce the future population burden of ADRD and disparities in ADRD. Our work can also inform targeting of interventions to those who benefit most. This research will provide immediately actionable evidence, because the interventions we evaluate are specific and feasible.