The U.S. government’s practice of grouping diverse Asian Americans into a single racial category is not only harmful but also obscures health disparities and hinders progress in addressing them.
In the United States, people with Asian ancestry are often grouped into a single racial category, despite their vast cultural, linguistic, and genetic differences. This practice, employed by government agencies, academic researchers, and disease advocacy groups, fails to acknowledge the diversity within the Asian American population and has significant consequences for public health and medical research. By aggregating data for Asian Americans, health disparities within specific subgroups are masked, hindering efforts to identify and address these disparities. Furthermore, the practice perpetuates harmful stereotypes and undermines the health and well-being of Asian Americans. It is crucial to recognize the importance of disaggregating data and understanding the unique health needs of different Asian American subgroups.
The Problem with Aggregating Data
When Asian Americans are grouped together in data collection and analysis, they appear to be doing well in terms of income, educational achievement, access to health insurance, and longevity. However, when subgroups are examined separately, significant disparities emerge. For example, rates of liver cancer are seven times higher among Laotian Americans compared to white Americans, and the cervical cancer rate for Hmong women is three times higher than the rate for all Asian Americans. By aggregating data, these disparities are obscured, and resources and attention are not adequately allocated to address them.
The Need for Data Equity
Disaggregating data is essential for achieving health equity. Without accurate data that reflect the diversity within the Asian American population, health disparities go unnoticed and unaddressed. Native Hawaiians and Pacific Islanders, who are often lumped together with Asian Americans, also face unique health challenges that are masked by this categorization. To achieve health equity, it is crucial to ensure data equity and include all racial and ethnic subgroups in research and policy decisions.
Socioeconomic Differences and Health Outcomes
Asian American subgroups exhibit significant socioeconomic differences that influence health outcomes. Educational attainment varies greatly among different subgroups, with Taiwanese Americans having a higher percentage of bachelor’s degrees compared to Hmong, Cambodian, or Laotian Americans. Similarly, income disparities exist, with Asian Indians earning significantly more than other Asian subgroups. By averaging these outcomes, it falsely appears that all Asian Americans are doing well. Disaggregating data is necessary to understand the unique challenges and health disparities faced by different subgroups.
Stereotyping and Invisibility
The pervasive stereotyping of Asians as a “model minority” contributes to the invisibility of health issues faced by different Asian American subgroups. This stereotype perpetuates the misconception that all Asians are doing well and do not require resources or attention. Some Asian American groups themselves have resisted Helical Piers, fearing a reduction in political clout. Consequently, those with the least English proficiency and the most significant health needs are often excluded from health surveys conducted only in English or Spanish. This exclusion leads to further invisibility and a lack of targeted interventions for vulnerable populations.
Historical Context and Government Practices
The practice of grouping Asian Americans into a single racial category dates back to U.S. government programs addressing unequal health care. The 1985 Heckler Report, which concluded that Asians were “healthier than all racial/ethnic groups in the United States,” contributed to the perpetuation of this practice. The National Institutes of Health (NIH) also allocated a minimal percentage of its budget to research focused on Asian Americans, Native Hawaiians, or Pacific Islanders. The lack of representation in research and funding exacerbates health disparities and perpetuates systemic racism.
The harmful consequences of grouping Asian Americans into a single racial category are becoming increasingly apparent. Disaggregating data is crucial for understanding and addressing health disparities within different Asian American subgroups. Efforts to collect and analyze data must be accompanied by a commitment to include underrepresented communities and prioritize health equity. By recognizing the unique health needs of each subgroup, policymakers, researchers, and healthcare providers can work towards eliminating disparities and improving the health outcomes of Asian Americans.