Problems With the Collection and Interpretation of Asian-American Health Data: Omission, Aggregation, and Extrapolation

Asian-American citizens are the fastest growing racial/ethnic group in the United States. Nevertheless, data on Asian American health are scarce, and many health disparities for this population remain unknown. Much of our knowledge of Asian American health has been determined by studies in which investigators have either grouped Asian-American subjects together or examined one subgroup alone (e.g., Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese). National health surveys that collect information on Asian-American race/ethnicity frequently omit this population in research reports. When national health data are reported for Asian-American subjects, it is often reported for the aggregated group. This aggregation may mask differences between Asian-American subgroups. When health data are reported by Asian American subgroup, it is generally reported for one subgroup alone. In the Ni-Hon-San study, investigators examined cardiovascular disease in Japanese men living in Japan (Nippon; Ni), Honolulu, Hawaii (Hon), and San Francisco, CA (San). The findings from this study are often incorrectly extrapolated to other Asian-American subgroups. Recommendations to correct the errors associated with omission, aggregation, and extrapolation include: oversampling of Asian Americans, collection and reporting of race/ethnicity data by Asian-American subgroup, and acknowledgement of significant heterogeneity among Asian American subgroups when interpreting data.

Introduction

Asian Americans are the fastest growing racial/ethnic group in the United States, with a population of more than 14 million as of 2010, and projected to grow to nearly 38 million in 2050 (1). The six largest Asian-American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese) comprise approximately 97% of the Asian American population (single race) (2). Asian Americans are also a heterogeneous group, with unique socioeconomic profiles and language abilities (Table 1) (3). There is a wide spectrum of education, household income, and language ability with Asian Indians in the higher and Koreans and Vietnamese in the lower range of these standard sociodemographic indicators. However, Asian-American subgroups are frequently combined into a single Asian category, masking heterogeneity among the subgroups. Data on Asian American health, particularly for the Asian subgroups, are scarce, and many health disparities for this population remain unknown.

Other researchers and advocacy groups have highlighted the importance of collecting and reporting data by Asian-American subgroups 4, 5, 6, 7. The Federal Government has recently taken steps to improve the collection of Asian American health data. In 2009, President Obama signed Executive Order 13515, reinstating President Clinton's Executive Order 13125 that established the President's Advisory Commission, the Federal Interagency Working Group, and the Office of the White House Initiative to improve the health, education, and economic status of the Asian-American and Pacific Islander community (8). President Obama highlighted the need to disaggregate data by Asian American subgroup (8).

As of 2010, Section 4302 of the Affordable Care Act requires that all health surveys sponsored by the Department of Health and Human Services (HHS), such as the National Health Interview Survey (NHIS), the National Medical Expenditure Panel Survey, and the National Immunization Survey, include standardized information on race, ethnicity, sex, primary language, and disability status (Table 2) (9). Disaggregation is only the first step in providing meaningful health data for this group. We must also seek to adequately sample Asian subgroups to provide statistically stable estimates across groups and to offer surveys in appropriate languages and through translators to ensure adequate representation of limited English proficiency and low health literacy populations.

Previous research and recent federal policy changes address the important issue of disaggregation of Asian-American health data by subgroup. However, few papers have examined the errors in interpretation of Asian-American health data, which are ongoing in the literature. This article will address the implications of recent federal policy changes data collection and reporting, as well as identify methods to improve the collection and interpretation of Asian-American health data, focusing on omission, aggregation, and extrapolation.