Abstract
More than any other racial group, American Indian/Alaska Natives (AIAN) face the risk of imprecise survey estimates due to survey processes regarding the classification, tabulation, and weighting of race/ethnicity. Variations in approaches to classifying racial and ethnic populations in federal and state health statistics have substantial implications for how we measure health status, access to healthcare, healthcare quality, and health equity. We identify strategies to improve data capacity for AIAN in federal health surveys by exploring current approaches to collecting and coding of AIANs across eight population-based health surveys (seven federal surveys and the California Health Interview Survey). Our analysis assesses how different coding and weighting decisions affect the classification and measurement of the AIAN population by comparing single-race non-Hispanic/Latino AIAN to more expansive classifications that include not only those reporting AIAN race alone, but also individuals reporting AIAN race in combination with other races and/or in combination with Hispanic/Latino ethnicity. Our results provide insight into the representativeness of each survey on the AIAN population and our ability to draw conclusions about the health of the AIAN population and the health disparities they face. The results show considerable variation across surveys in their measurement of the AIAN population based on survey classification, tabulation, and weighting approaches.
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Notes
Confirmed by author calculation using 2015 American Community Survey, 1-Year Public Use Data.
Before 2013, the public use data files of the Behavioral Risk Factor Surveillance System (BRFSS) include sufficiently detailed race and ethnicity information to identify the four AIAN classification groups used in this study. Beginning with 2013 BRFSS, this information is no longer provided in the public use data.
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Acknowledgements
This project was funded by the Office of the Assistant Secretary of Planning and Evaluation at the U.S. Department of Health and Human Services. The authors would gratefully like to acknowledge the helpful comments and feedback received from Randall Akee, Tom Anderson, Nancy Breen, Chipper Dean, Bonnie Duran, Carolyn Liebler, Aleta Meyer, Delight Satter, Matthew Snipp, and Maureen Wimsatt and the contributions made to this project by Priya Thaker, Daniel Hanaya, Riti Shimkhada, and AJ Scheitler.
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Becker, T., Babey, S.H., Dorsey, R. et al. Data Disaggregation with American Indian/Alaska Native Population Data. Popul Res Policy Rev 40, 103–125 (2021). https://doi.org/10.1007/s11113-020-09635-2
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DOI: https://doi.org/10.1007/s11113-020-09635-2