A data-driven prospective study of incident dementia among older adults in the United States

TL;DR

This study identifies key sociodemographic, health, and social factors associated with incident dementia in older US adults over 14 years, highlighting disparities across racial/ethnic and gender groups.

Contribution

It applies both traditional and data-driven survival analysis methods to uncover diverse predictors of dementia, emphasizing the importance of life course factors and disparities.

Findings

Lower education, loneliness, and lower income are top predictors.

Predictor importance varies across racial/ethnic and gender groups.

Results inform future research on dementia risk and disparities.

Abstract

We conducted a prospective analysis of incident dementia and its association with 65 sociodemographic, early-life, economic, health and behavioral, social, and genetic risk factors in a sample of 7,908 adults over the age of 50 from the nationally representative US-based Health and Retirement Study. We used traditional survival analysis methods (Fine-Gray models) and a data-driven approach (random survival forests for competing risks) which allowed us to account for the competing risk of death with up to 14 years of follow-up. Overall, the top five predictors across all groups were lower education, loneliness, lower wealth and income, and lower self-reported health. However, we observed variation in the leading predictors of dementia across racial/ethnic and gender groups. Our ranked lists may be useful for guiding future observational and quasi-experimental research that investigates understudied domains of risk and emphasizes life course economic and health conditions as well as disparities therein.