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

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. Highlights We harmonized cognitive function data from two racially diverse US‐based cohorts. Models had good fit, construct validity, and no salient differential item functioning. We demonstrate increased precision in associations among Black participants.