AI-Enabled Exposomic Profiling to Explain Rural Cardiovascular Risk
Description: Cardiovascular disease remains the leading cause of mortality in older adults with rural Americans experiencing a disproportionate burden known as the Rural Health Penalty. Current research often relies on broad rural versus urban classifications that fail to capture the specific environmental features driving these disparities. This Career Development Award proposes to use artificial intelligence to characterize the rural exposome and identify modifiable drivers of cardiovascular risk. In Aim 1 the candidate will integrate high dimensional data including satellite imagery street view images and socioeconomic factors to derive a continuous Integrated Environmental Exposure Index and identify distinct rural environmental phenotypes. In Aim 2 the study will determine the causal impact of these environmental exposures on incident major adverse cardiovascular events in a national cohort of older adults. Using modern causal inference frameworks such as Targeted Maximum Likelihood Estimation the candidate will estimate the effect of environmental burden on cardiovascular outcomes and simulate the potential benefit of theoretical interventions. This award will provide the candidate with essential training in causal inference methods, Medicare epidemiology and rural health disparities, facilitating the transition to an leading independent investigator. The findings will generate actionable data driven insights to improve cardiovascular outcomes and reduce inequities among older adults living in rural America.
Funder: American Heart Association
Amount: $230,800
Funding type: fellowship
Funder scheme: Career Development Award
Start date: 2026-04-01
End date: 2029-03-31
Investigators: Zhuo Chen, Zhuo Chen
Institution: Case Western Reserve University - School of Medicine
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Funded outputs count: 0
Funder award ID: 26CDA1615834
OpenAlex ID: G6720053750