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.

与其他种族相比，美洲印第安人/阿拉斯加土著人（AIAN）由于种族/族裔的分类，制表和加权的调查过程而面临不准确的调查估计数的风险。在联邦和州健康统计数据中对种族和族裔人口进行分类的方法有所不同，这对我们衡量健康状况，获得医疗保健，医疗质量和健康公平性的方式具有重大影响。我们通过探索八种基于人口的健康调查（七项联邦调查和加利福尼亚州健康访问调查）中目前收集和编码AIAN的方法，确定了提高联邦健康调查中AIAN数据容量的策略。我们的分析通过将单种族非西班牙裔/拉丁美洲裔AIAN与更广泛的分类进行比较，评估了不同的编码和权重决策如何影响AIAN人口的分类和测量，这些分类不仅包括仅报告AIAN种族的人，还包括报告AIAN种族的人。与其他种族结合和/或与西班牙裔/拉丁美洲裔结合。我们的结果提供了对每项有关AIAN人口调查的代表性的洞察力，以及我们得出有关AIAN人口健康状况和他们所面临的健康差距的结论的能力。结果显示，根据调查分类，列表和加权方法，不同调查对AIAN人口的测量存在很大差异。