Assessing racial disparities in dementia-related vulnerabilities: a machine learning analysis of social, environmental, and climate factors.

Abstract

Introduction: Racial differences in exposure to area-level social determinants of health (SDoH) may contribute to distinct vulnerability profiles among people living with dementia.

Methods: This cross-sectional study used data from the OCHIN Community Health Equity Database to examine SDoH factors among patients with dementia and mild cognitive impairment. SDoH measures encompassed social, environmental, and climate vulnerability factors. We trained Random Forest classifiers to identify the most influential SDoH features distinguishing racial groups.

Results: Common SDoH factors - those ranking among the top features across multiple racial groups - included percentage of minority populations, limited English proficiency, exposure to diesel particulate matter or fine particulate matter, impaired watershed, and frequency of extreme heat and wildfire smoke days. Distinct SDoH factors - those identified as top-ranked for only one or two groups - included unemployment and disability rates in ZIP codes where American Indian and/or Alaska Native patients lived; lack of walkability in areas where Asian patients resided; hurricane occurrences in ZIP codes where Black patients lived; low educational attainment in Native Hawaiian or other Pacific Islander communities; and housing cost burden, lack of internet access, and older housing stock in areas where Multiracial patients lived.

Discussion: These findings highlight the importance of incorporating multidimensional SDoH measures when assessing structural contexts in dementia research.