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| Funder | NATIONAL INSTITUTE ON AGING |
|---|---|
| Recipient Organization | University of Michigan At Ann Arbor |
| Country | United States |
| Start Date | Apr 01, 2023 |
| End Date | Jan 31, 2028 |
| Duration | 1,766 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10662077 |
Risk of Alzheimer's disease and related dementias (ADRD) is higher for non-Latinx Black older adults than for non-Latinx White older adults. This disparity is not fully explained by commonly measured individual risk factors such as educational disadvantage, apolipoprotein E epsilon 4, or medical comorbidities. Thus, there is
a critical need to identify additional modifiable targets at multiple levels to reduce ADRD inequalities in line with NIA's Strategic Directions for Research and the NIA Health Disparities Framework. The overall goal of this longitudinal study (N=700; 50% Black) is to identify new, modifiable pathways to reduce racial inequalities in
ADRD by leveraging the community-based Michigan Cognitive Aging Project (MCAP), the National Neighborhood Data Archive (NaNDA), and recently released historical data from the 1950 census. Our strong preliminary data support concurrent neighborhood socioeconomic status (nSES) as a unique driver of cognitive
inequalities that operates through modifiable environmental (e.g., public infrastructure), social (e.g., discrimination), psychological (e.g., depressive symptoms), and behavioral (e.g., diet) mechanisms. The current proposal will follow MCAP participants for a critical third time point to enable latent growth curve
modeling of longitudinal cognitive trajectories, expand the cohort to ensure adequate power for between and within group longitudinal analyses in the presence of racial disparities in mortality, and collect structural magnetic resonance imaging (MRI) measures of brain integrity. In addition, this proposal will collect new data
on residential histories to identify life course critical periods for neighborhood level interventions, develop a novel measure of neighborhood racial income inequality that could predict ADRD risk above and beyond nSES, and reveal resilience factors among Black older adults that could interrupt ADRD risk pathways. Recent
studies have linked nSES to brain and cognitive outcomes, but the mechanisms, modifiers, and intersection with racial inequalities in ADRD are not yet understood. Grounded in the bioecological model and a life course model of ADRD inequalities, our overarching hypothesis is that eliminating racial inequalities in ADRD will
require interventions at multiple levels of the exposome, and the current proposal will provide actionable knowledge to guide policies and interventions.
University of Michigan At Ann Arbor
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