Problems with the collection and interpretation of Asian-American health data: omission, aggregation, and extrapolation

Ann Epidemiol. 2012 Jun;22(6):397-405. doi: 10.1016/j.annepidem.2012.04.001.

Abstract

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.

MeSH terms

  • Asian / classification
  • Asian / statistics & numerical data*
  • Data Collection / standards*
  • Data Interpretation, Statistical
  • Health Status
  • Health Surveys / statistics & numerical data*
  • Humans
  • United States / epidemiology