Work

Alzheimer’s Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis

Year: 2025

Type: article

Abstract: A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer’s disease (AD) dementia, yet the spatial variability and relative importance of the most influential factors remain underexplored. We compiled various widely recognized factors to examine spatial heterogeneity and associations with AD dementia prevalence via geographically weighted random forest (GWRF) approach. The GWRF outperformed conventional models with an out-of-bag R 2 of 74.8% in predicting AD dementia prevalence and the lowest error (MAE = 0.34, RMSE = 0.45). Key findings showed that mobile homes were the most influential factor in 19.9% of U.S. counties, followed by NDVI (17.4%), physical inactivity (12.9%), households with no vehicle (11.3%), and particulate matter (10.4%), while other primary factors affecting <10% of U.S. counties. Findings highlight the need for county-specific interventions tailored to local risk factors. Policies should prioritize increasing affordable housing stability, expanding green spaces, improving transportation access, promoting physical activity, and reducing air pollution exposure.

Source: American Journal of Alzheimer s Disease & Other Dementias®

DOI: 10.1177/15333175251335570

Authors: Abolfazl Mollalo, George Grekousis, Hermes Florez, Brian Neelon, Leslie A. Lenert, Alexander V. Alekseyenko

Institutions: Medical University of South Carolina, Sun Yat-sen University

Language: English

Topic: Dementia and Cognitive Impairment Research

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,650