A predictive model for cognitive decline using social determinants of health.

ABSTRACT:

Background

Early diagnosis of Alzheimer's disease and related dementias (AD/ADRD) is critical but often constrained by limited access to fluid and imaging biomarkers, particularly in low-resource settings.

Objective

To develop and evaluate a predictive model for cognitive decline using survey-based data, with attention to model interpretability and fairness.

Methods

Using data from the Mexican Health and Aging Study (MHAS), a nationally representative longitudinal survey of adults aged 50 and older (N = 4095), we developed a machine learning model to predict future cognitive scores. The model was trained on survey data from 2003 to 2012, encompassing demographic, lifestyle, and social determinants of health (SDoH) variables. A stacked ensemble approach combined

SUBMITTER: He Y 

PROVIDER: S-EPMC12809124 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature