Facilitating Harmonization of Variables from the Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository

Research in stroke prevention requires inclusion of a broad range of data sets from different cohorts. Integrating and harmonizing different data sources are essential to increase generalizability, sample size, and representation of understudied populations-strengthening the evidence for the scientific questions being addressed. To that end, Duke AI Health and the American Heart Association have developed an open metadata repository for the harmonization of stroke risk prediction variables from four large, National Institutes of Health (NIH)-funded cohort studies: REGARDS (Reasons for Geographic and Racial Differences in Stroke), FHS (Framingham Heart Study), MESA (Multi-Ethnic Study of Atherosclerosis), and ARIC (Atherosclerosis Risk in Communities). In this webinar, we will present an overview of the metadata repository and walk through its features, including variable distributions, collection time periods, and search filters. We will also discuss several use cases for incorporating this resource into your research for harmonizing data.