The UCLA Center for Health Policy Research responds to proposed revisions to federal race and ethnicity standards
A team of UCLA researchers presents the Office of Management and Budget with feedback to revise standards for collecting and reporting race and ethnicity data
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In 2022, the United States Office of Management and Budget (OMB) announced a formal review to revise OMB’s Statistical Policy Directive No. 15: Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity, which was last updated in 1997. On January 26, 2023, OMB released an initial set of revisions, and encouraged the public to respond by Wednesday, April 27, 2023.
The UCLA Center for Health Policy Research’s California Health Interview Survey (CHIS), Data Equity Center, and Native Hawaiian and Pacific Islander (NHPI) Data Policy Lab each submitted letters to OMB for review.
Feedback from these programs includes a response to OMB’s initial proposals for updating race and ethnicity statistical standards.
Some suggestions include:
- Ensuring that individuals from small racial and ethnic groups that are often overlooked and rendered invisible in data collection efforts can identify themselves.
- Combining the race and Hispanic origin question helps reduce the burden Latino respondents face in providing race data. Researchers do note that there are concerns about the impact of a combined race and Hispanic origin question on those who identify as Afro-Latino.
- Addressing the impacts of adding write-in responses to white or Black or African American responses.
- Adding new race categories, including Middle Eastern and North African (separate from white), Native Hawaiian and Pacific Islander, and Asian subgroups.
- Encourage communities to participate in decennial census, household surveys, and federal administrative forms.
Data show that inequities between subgroups within broad categories can often be larger than those between the minimum categories. Researchers cite examples from their work on the importance that OMB considers further data disaggregation, and how it plays a key role in improving data quality and equity.
One example of how a lack of data disaggregation has perpetuated inequities is the lumping of Native Hawaiians and Pacific Islanders (NHPI) into the Asian race category, despite wide variations in sociodemographic and economic characteristics and health conditions between and within these two racial groups. During the early days of the COVID-19 pandemic, datasets that included NHPIs in the Asian category showed that other racial and ethnic groups were in far more jeopardy. However, in the few states that disaggregated NHPIs, data showed that the community was dying at the highest rates of any racial or ethnic group.
Detailed NHPI and Asian subgroup data collections can more precisely detect health risks and target health policies and programs. For example, California 2020 restricted mortality data show that among NHPIs, COVID-19 death rates were higher for Samoans, and among Asians, Filipinos had the highest burden of health care worker deaths.
“Data disaggregation is paramount to understanding the unique experiences and needs of various racial and ethnic groups that have been hidden for decades,” said Ninez A. Ponce, PhD, MPP, director of the Center and principal investigator of CHIS. “The successful revision of federal standards would help us better serve all communities and bring the country one step closer to achieving health equity."
About the UCLA Center for Health Policy Research
The UCLA Center for Health Policy Research (CHPR) is one of the nation’s leading health policy research centers and the premier source of health policy information for California. UCLA CHPR improves the public’s health through high quality, objective, and evidence-based research and data that informs effective policymaking. UCLA CHPR is the home of the California Health Interview Survey (CHIS) and is part of the UCLA Fielding School of Public Health.