How we measure America's rapidly expanding diversity has critical implications for the health of the nation. Too often, the data used to drive policymaking, allocate resources, and combat health disparities is based on broad racial and ethnic categories that can render the unique needs, strengths, and life experiences of many communities invisible.
That is why PolicyLink is excited to release Counting a Diverse Nation: Disaggregating Data on Race and Ethnicity to Advance a Culture of Health, a multifaceted investigation that explores the leading issues and opportunities of racial/ethnic data disaggregation, and its implications for advancing health equity. The report provides a comprehensive assessment of racial and ethnic data disaggregation practices today, and concrete recommendations for improving research methods and promoting government policies that enhance and enable data disaggregation in the future.
Findings and recommendations in the report encompass two areas:
- Best practices for collecting and analyzing data about race and ethnicity at more detailed levels, including research innovations and special considerations for studying marginalized populations;
- Government policies and practices that can enhance and enable data disaggregation, including recent campaigns and policy wins across the nation that are supporting increased representation across racial, ethnic, and cultural identities.
Developed as part of a multiphase project commissioned by the Robert Wood Johnson Foundation, the report reflects two years of collaborative research and input among a diverse set of experts, demographers, practitioners, decision makers, and advocates. Reviews by these researchers of the state of data disaggregation for each major U.S. population group, along with a comparative study of seven other countries, accompany the new report
To learn more about the critical importance of disaggregating racial/ethnic data from researchers, advocates, and other experts who contributed to this report, listen to the archived webinar.