Alzheimer's & Dementia Behavior & Socioeconomics of Aging · Sep 17, 2025

Cognitive data harmonization across two racially diverse cohorts in the United States

By Flesaker M, Kraal AZ, Avila-Rieger JF et al.

INTRODUCTION: Few cohorts have sufficient diversity to identify drivers of racial disparities in cognitive aging. Pooling data from different samples can increase sample size and diversity. METHODS: We statistically harmonized cognitive function data from two US cohorts: 2010 Health and Retirement Study (HRS; n=18,422) and 2009-2013 Reasons for Geographic and Racial Differences in Stroke waves (REGARDS; n=19,690). We used confirmatory factor analysis (CFA) to derive harmonized scores for general and domain-specific cognitive function, leveraging common cognitive test items across studies and retaining those unique to each study. We assessed validity of the cognitive scores by regressing them on age, sex/gender, and education. RESULTS: The combined sample had a mean age of 67.69 (SD=10.22) years. CFA models had good fit. Harmonized cognitive scores demonstrated good criterion validity. DISCUSSION: Pooled analyses of harmonized cognitive scores are a feasible means to increase cohort diversity for understanding drivers of racial disparities in cognitive aging.

doi.org/10.1002/bsa3.70037Open accessPubMed 40988999AI & data