“Which Box Should I Check?”: Examining Standard Check Box Approaches to Measuring Race and Ethnicity
Article first published online: 3 DEC 2013
© Health Research and Educational Trust
Health Services Research
Volume 49, Issue 3, pages 1034–1055, June 2014
How to Cite
Eisenhower, A., Suyemoto, K., Lucchese, F. and Canenguez, K. (2014), “Which Box Should I Check?”: Examining Standard Check Box Approaches to Measuring Race and Ethnicity. Health Services Research, 49: 1034–1055. doi: 10.1111/1475-6773.12132
- Issue published online: 16 MAY 2014
- Article first published online: 3 DEC 2013
- Manuscript Accepted: 24 SEP 2013
- National Institute on Minority Health and Health Disparities. Grant Number: P20 MD002290-05
- Measurement of race and ethnicity;
- health disparities research;
- National Institutes of Health (NIH) race and ethnicity reporting;
- racial and ethnic self-identification
This study examined methodological concerns with standard approaches to measuring race and ethnicity using the federally defined race and ethnicity categories, as utilized in National Institutes of Health (NIH) funded research.
Data Sources/Study Setting
Surveys were administered to 219 economically disadvantaged, racially and ethnically diverse participants at Boston Women Infants and Children (WIC) clinics during 2010.
We examined missingness and misclassification in responses to the closed-ended NIH measure of race and ethnicity compared with open-ended measures of self-identified race and ethnicity.
Rates of missingness were 26 and 43 percent for NIH race and ethnicity items, respectively, compared with 11 and 18 percent for open-ended responses. NIH race responses matched racial self-identification in only 44 percent of cases. Missingness and misclassification were disproportionately higher for self-identified Latina(o)s, African-Americans, and Cape Verdeans. Race, but not ethnicity, was more often missing for immigrant versus mainland U.S.-born respondents. Results also indicated that ethnicity for Hispanic/Latina(o)s is more complex than captured in this measure.
The NIH's current race and ethnicity measure demonstrated poor differentiation of race and ethnicity, restricted response options, and lack of an inclusive ethnicity question. Separating race and ethnicity and providing respondents with adequate flexibility to identify themselves both racially and ethnically may improve valid operationalization.