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Summary: American Indian and Alaska Native (AIAN) people are underrepresented and often invisible in public health data and research. AIAN health data capacity is impeded by the quality of information collected, released, and reported on AIANs in population-based surveys. AIANs are either put in a residual “other” category or, typically, depicted as single-race non-Latinx AIANs. 

Findings: Though the figure varies substantially across federal surveys, fewer than two in five AIANs report as single-race non-Latinx AIANs. Drawing population inferences based on single-race AIANs also fails to capture the considerable segment of the AIAN population that comprises individuals of more than one race. To promote more accurate insights on the health of the AIAN population, authors examined eight population datasets, including pooled 2011-2014 California Health Interview Survey (CHIS) data, that focus on health, health status, health behaviors, and health access. For each survey, authors assessed whether it is possible to identify AIAN respondents from (1) readily accessible public-use data files and (2) restricted data files. They also assessed the extent to which data users can distinguish three major subgroups within the AIAN race category from these data files: single-race non-Latinx AIAN, single-race Latinx AIAN, and AIAN of more than one race. In this policy brief, authors discuss the implications of the limited accessibility of AIAN information in population datasets and provide some recommendations that may help improve the availability of AIAN health information.

he application of a currently proposed differential privacy algorithm to the 2020 United States Census data and additional data products may affect the usefulness of these data, the accuracy of estimates and rates derived from them, and critical knowledge about social phenomena such as health disparities. We test the ramifications of applying differential privacy to released data by studying estimates of US mortality rates for the overall population and three major racial/ethnic groups

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Racial and ethnic health disparities and inequities can only be eliminated if high-quality information is available by which to track immediate problems and the underlying social determinants of health. Such information can guide the design and application of culturally specific approaches to medicine and public health. Often, health outcomes are disaggregated only by broad racial and ethnic categories such as White, Black, or Hispanic. However, the great, and growing, diversity of the American population means that people’s actual experiences are much more specific.

The U.S. has numerous compelling reasons to build and maintain a much more robust practice of disaggregating data below the level of major racial groups and to link these data to the factors that influence health. Improving how we create, understand, and handle disaggregated data about race and ethnicity is central to the pursuit of health equity and a deeper appreciation of American society overall.

This report has been made possible through a grant to PolicyLink from the Robert Wood Johnson Foundation. UCLA Center for Health Policy Research researchers Ninez Ponce, Riti Shimkhada, AJ Scheitler, Tara Becker and Priya Thaker contributed to the report.

The purpose of the study is to describe the current practice of data collection and reporting for Asian American, Native Hawaiian and Pacific Islanders (AANHPI) groups in health-related population surveys. The group makes up 6 percent of the U.S. population based on the 2010 Census and is estimated to account for 11 percent by 2050. Authors present a scan of the current sources of AANHPI data on health and health-related determinants, and provide insights on the challenges population-based surveys face in collecting and reporting data to inform policies and programs targeted towards AANHPI populations. California Health Interview Survey is examined as part of the literature review. The report was presented to the Robert Wood Johnson Foundation.