Primary Submission Category: Place/Communities
Spatial and neighborhood data in the Collaborative Cohort of Cohorts for COVID-19 Research (C4R)
Authors: Jana Hirsch Lilah Besser Talea Cornelius Stephen Dickinson Stephen Francisco Marcia Jimenez Hoda Abdel Magid Yvonne Michael Elizabeth Oeslner
Presenting Author: Jana Hirsch*
Neighborhood factors may create and reinforce geographic differences in COVID-19 experiences and long-term pandemic impact. These factors include social environments (e.g. employment landscapes), policy implementation (e.g. differences in COVID-19 mitigation mandates), built environment (e.g. housing quality and health care access), and natural environments (e.g. air quality and greenspace). To examine the health impact of neighborhood factors, we need longitudinal datasets of pre-pandemic neighborhood conditions and individual behaviors or health risks. A large, pooled sample with sufficient variability in geographic scope, participant diversity, and area-level neighborhood characteristics is critical to understand the role of context on COVID-19 outcomes. Our primary aim was to evaluate the value of Collaborative Cohort of Cohorts (C4R) for this purpose. C4R is a large geographically, racially/ethnically, and socioeconomically diverse study of 14 pooled cohorts in the US with harmonized data on health outcomes, including vaccination, COVID-19 infection, recovery, death, and more, from over 50,000 participants. We conducted surveys with key data staff for each of the cohorts to assess the spatial scale (e.g., tract, radial buffer, or zip code) and type of neighborhood measures within each cohort. We found that census tracts in which C4R cohort participants have lived covered 28% of the US land area, representing 52% of the US total population. Areas where participants have lived are more dense, urban, affluent, foreign-born, and educated and less car-dependent, employed, and green than the US on average. Ten of the 14 cohorts geocoded participants’ addresses to identify their geographic location and collected neighborhood characteristics – most commonly social environment measures. C4R’s combined sample opens numerous opportunities for well-powered research on the influence of neighborhood characteristics on COVID-19 outcomes across various geographies.