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.