Open AccessInformation Loss in Harmonizing Granular Race and Ethnicity Data: Descriptive Study of Standards
Author(s) -
Karen Wang,
Holly K. Grossetta Nardini,
Lori Ann Post,
Todd L. Edwards,
Marcella Nuñez-Smith,
Cynthia Brandt
Publication year - 2020
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/14591
Subject(s) - ethnic group , race (biology) , harmonization , data collection , descriptive statistics , geography , gerontology , medicine , political science , sociology , statistics , social science , gender studies , mathematics , physics , acoustics , law
Background Data standards for race and ethnicity have significant implications for health equity research. Objective We aim to describe a challenge encountered when working with a multiple–race and ethnicity assessment in the Eastern Caribbean Health Outcomes Research Network (ECHORN), a research collaborative of Barbados, Puerto Rico, Trinidad and Tobago, and the US Virgin Islands. Methods We examined the data standards guiding harmonization of race and ethnicity data for multiracial and multiethnic populations, using the Office of Management and Budget (OMB) Statistical Policy Directive No. 15. Results Of 1211 participants in the ECHORN cohort study, 901 (74.40%) selected 1 racial category. Of those that selected 1 category, 13.0% (117/901) selected Caribbean; 6.4% (58/901), Puerto Rican or Boricua; and 13.5% (122/901), the mixed or multiracial category. A total of 17.84% (216/1211) of participants selected 2 or more categories, with 15.19% (184/1211) selecting 2 categories and 2.64% (32/1211) selecting 3 or more categories. With aggregation of ECHORN data into OMB categories, 27.91% (338/1211) of the participants can be placed in the “more than one race” category. Conclusions This analysis exposes the fundamental informatics challenges that current race and ethnicity data standards present to meaningful collection, organization, and dissemination of granular data about subgroup populations in diverse and marginalized communities. Current standards should reflect the science of measuring race and ethnicity and the need for multidisciplinary teams to improve evolving standards throughout the data life cycle.