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December 2, 2020

Centering Health Equity in Population Health Surveys

Author Affiliations
  • 1UCLA Center for Health Policy Research, California Health Interview Survey, Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California
JAMA Health Forum. 2020;1(12):e201429. doi:10.1001/jamahealthforum.2020.1429

Health policy researchers are in the midst of what may be the greatest shift in the way we view population health research since we began using race/ethnicity data to identify disparities. In 1985, Secretary of Health and Human Services Heckler’s landmark report on Black and minority health uncovered the appalling degree to which outcomes can vary by race/ethnicity: life expectancy among Black individuals was nearly 6 years less than that of White individuals, and infant mortality for Black individuals was nearly double.1 But, in the 35 years since that landmark report, we are only now reckoning with how disparities research has failed to achieve equity and has even contributed to the preservation of systemic racism.2,3 While we have not nearly addressed the structural changes needed to eliminate racial/ethnic health disparities, we have made some strides in population health data collection.

In the Black and minority health report,1 Asian/Pacific Islanders were depicted as a group that had high life expectancy and low infant mortality and were “healthier than all racial/ethnic groups in the United States.” Quick to recognize the lack of disaggregation of the Asian/Pacific Islander category, 2 national health advocacy organizations were born—the Asian & Pacific Islander American Health Forum and the Association of Asian Pacific Community Health Organizations.4 These organizations motivated the Asian and Pacific Islander Health Improvement Act of 1990, calling for the disaggregation into Asian and Native Hawaiian and Pacific Islanders (NHPI) categories by the National Center for Health Statistics. And finally, in 1997, the Asian/NHPI racial category was separated when the Office of Management and Budget revised the federal data standards.

Disaggregation of race/ethnicity in population health surveys was pivotal to understanding the vast differences between the Asian and NHPI experience. A study using the National Health Interview Survey to compare NHPI populations with Asian populations showed that NHPI individuals have significantly higher rates of cancer, asthma, psychological distress, hypertension, heart disease, and unhealthy body weight.5 More recently, these vulnerabilities of the NHPI population captured by state population health surveys unfortunately manifested in coronavirus disease 2019 (COVID-19) mortality data. In some states, NHPI individuals suffered disproportionately from COVID-19 deaths than any other racial/ethnic group.6 If not for the advocacy work to create the NHPI category, the burden of disease shouldered by NHPI people would be hidden in the data. With available data, the NHPI community leaders have been mobilizing efforts informed by the NHPI COVID-19 Data Policy Lab Dashboard to protect the further spread of COVID-19 in NHPI communities.7

Researchers and community-based partners and advocates rely on population-based survey data to address specific health needs. More so than other health care data sources, population health surveys ask about living conditions, education, occupation, income, and trauma history—piecing together the “backstory” that may explain the racial/ethnic inequities in health access and health outcomes. Population health surveys have the unique position to be the magnifying glass that can uplift populations and be a tool for health system accountability. This is especially critical for those who would be otherwise unseen, neglected, and hidden in an aggregate grouping that belies unknown risks. It is thus imperative that we get the story right (ie, more precise identification of racial/ethnic group affiliation) and that we uncover as many stories as possible by reducing coverage bias through the design of sampling frames, multicultural/multilingual recruitment, and oversampling.

The California Health Interview Survey (CHIS) offers an example of how population health surveys can effectively gather and analyze data about small racial/ethnic groups to inform policy and programming. Conducted since 2001, CHIS is the largest state-based population health survey in the US. Consistent with federal guidance and National Academies guidance, CHIS collects subgroup data within the Hispanic/Latino, Asian, NHPI, and American Indian/Alaska Native (AIAN) racial/ethnic categories.

The survey has facilitated the generation of population-based Asian and NHPI subgroup estimates used in studies nationwide. The CHIS uses oversampling to ensure that sufficient numbers of Asian and AIAN individuals are included in data collection procedures. It also conducts interviews in several Asian languages (ie, Cantonese, Mandarin, Korean, Vietnamese, and Tagalog), in addition to English and Spanish. Such strategies facilitate participation by a diverse cross-section of Californians with various immigration histories and socioeconomic levels and have led to important policy reforms. For instance, these data allowed English language proficiency to be tracked among Californians, critical to the drafting of California’s Health Care Language Assistance Act (SB-853) in 2003. This act was the first of its kind to require health plans to collect data on enrollees’ race/ethnicity and language. Effectively, protections offered to Medicaid enrollees were extended to enrollees in commercial insurance, including providing interpreter services and translated materials.

Health policy research requires representative survey data that reflect growing population diversity. Our ability and capacity to measure disparities among disaggregated racial/ethnic groups has improved over the last few decades, particularly for Asian populations. Serious deficits remain for other racial/ethnic groups. For example, use of the Middle Eastern and North African category to disaggregate this group from White people remains limited; efforts to disaggregate the Black race category are only beginning; and the extent of reporting estimates for those who identify as NHPI or 2 or more races is uneven across surveys.

Centering equity in population surveys means that there is an explicit measurement objective to eliminate health inequities. The CHIS is coproduced by community-based partners through advisory committees, including one that is explicitly tasked with improving the value of the survey across multicultural populations. With organizational commitment and community accountability, population health surveys will have the equity objective front and center. And, the quality of insights to formulate policies improving population health will improve.

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Article Information

Open Access: This is an open access article distributed under the terms of the CC-BY License.

Corresponding Author: Ninez A. Ponce, PhD, MPP, UCLA Center for Health Policy Research, California Health Interview Survey, Department of Health Policy and Management, UCLA Fielding School of Public Health, 10960 Wilshire Blvd, Ste 1550, Los Angeles, CA 90024 (nponce@ucla.edu).

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by the Robert Wood Johnson Foundation Data Disaggregation Project.

Role of the Funder/Sponsor: Robert Wood Johnson Foundation had no role in the preparation, review, or approval of the manuscript and decision to submit the manuscript for publication.

Additional Contributions: I thank Riti Shimkhada, PhD, for reviewing the manuscript.

References
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Heckler  M.  Report of the Secretary’s Task Force Report on Black and Minority Health. US Department of Health and Human Services; 1985.
2.
Hardeman  RR, Karbeah  J.  Examining racism in health services research: a disciplinary self-critique.   Health Serv Res. 2020;55(suppl 2):777-780. doi:10.1111/1475-6773.13558PubMedGoogle ScholarCrossref
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Bailey  ZD, Krieger  N, Agénor  M, Graves  J, Linos  N, Bassett  MT.  Structural racism and health inequities in the USA: evidence and interventions.   Lancet. 2017;389(10077):1453-1463. doi:10.1016/S0140-6736(17)30569-XPubMedGoogle ScholarCrossref
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Ponce  NA, Bautista  R, Sondik  EJ,  et al.  Championing partnerships for data equity.   J Health Care Poor Underserved. 2015;26(2)(suppl):6-15. doi:10.1353/hpu.2015.0058PubMedGoogle ScholarCrossref
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Galinsky  AM, Zelaya  CE, Simile  C, Barnes  PM.  Health conditions and behaviors of Native Hawaiian and Pacific Islander persons in the United States, 2014.   Vital Health Stat 3. 2017;(40):1-99.PubMedGoogle Scholar
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Kaholokula  JK, Samoa  RA, Miyamoto  RES, Palafox  N, Daniels  SA.  COVID-19 special column: COVID-19 hits Native Hawaiian and Pacific Islander communities the hardest.   Hawaii J Health Soc Welf. 2020;79(5):144-146.PubMedGoogle Scholar
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Chang  RC, Penaia  C, Thomas  K. Count Native Hawaiian and Pacific Islanders in COVID-19 data—it’s an OMB mandate. Health Affairs Blog. August 27, 2020. Accessed November 24, 2020. https://www.healthaffairs.org/do/10.1377/hblog20200825.671245/full/
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