Bridging Social Epidemiology and Policy for ADRD Prevention: Effects of Poverty Alleviation Policies on Alzheimer's Disease and Related Dementias Risk and Disparities

PROJECT SUMMARY/ABSTRACT
Poverty is highly prevalent and increases the risk of and disparities in Alzheimer's disease and related
dementias (AD/ADRD). Numerous social policies and safety net programs have been implemented to alleviate
poverty, but their effects on AD/ADRD risk and disparities remain unknown, despite their potential as powerful
population-level interventions to reduce long-standing health risks and disparities. The candidate seeks this
K99/R00 award to launch an independent research career dedicated to quantifying the effects of social policies
on AD/ADRD and bridging the gap between social epidemiology and policy for AD/ADRD prevention.
The overall objective is to evaluate the effects of poverty alleviation policies on AD/ADRD risk and
disparities by leveraging quasi-experimental variation across states (K99) and countries (R00). In the K99
phase, the candidate will integrate data from the Health and Retirement Study (HRS) with the complete (100%)
Medicare-beneficiary records to quantify state variation in temporal trends in AD/ADRD prevalence from 2012-
2022 for the overall population and by sex/gender and racial/ethnic identity (K99 Aim 1a). These state- and
year-specific estimates can be linked to other data sources, opening the door for numerous future
investigations into the impact of state policies on AD/ADRD. In K99 Aim 1b, she will link the derived
prevalence estimates to state policy databases and apply quasi-experimental methods to evaluate the effect of
the Supplemental Nutrition Assistance Program (SNAP) policies on AD/ADRD prevalence and disparities.
Building on the knowledge and skills acquired from the K99 phase, in the R00 phase, she will use the HRS
international sister studies and the Gateway Policy Explorer to quantify the average effects of social pensions
on cognitive decline (R00 Aim 2). Moreover, she will evaluate the heterogeneous effects of these policies on
cognitive decline using both theory-driven and causal machine learning approaches (R00 Aim 3).
This research is complemented by a career development plan with training in three key areas: 1)
integration of large administrative and survey data to monitor AD/ADRD population trends, a critical skill for
evaluating policies or other population approaches to AD/ADRD prevention; 2) multidisciplinary methods for
translational social policy evaluation, including state-of-the-art causal inference methods for quantifying policy
impact and legislative and advocacy expertise for translating evidence into actionable policy influences; and 3)
cross-national comparisons in AD/ADRD and policy research, including theoretical frameworks and
methodological nuances for capitalizing on similarities and differences across contexts. The research and
training plan, along with a strong multidisciplinary mentorship team and the outstanding training environments
at the Boston University School of Public Health and the Massachusetts General Hospital, will prepare
the candidate for a successful independent research career.

Grant Number: 1K99AG088369-01A1
NIH Institute/Center: NIH
Principal Investigator: Ruijia Chen