Revisiting population taxonomy: using a social equity framework to analyze health disparities among obese Black American ethnic subgroups
Creators: name: Gabrel, Celia S.
Publisher: name: Maryland Shared Open Access Repository
Year: 2011
Subjects: Black Americans
data collection
ethnic subgroup
health disparity
obesity
social equity

description: The United States (US) is becoming increasingly racially and ethnically diverse primarily due to the surge of immigrants from around the world.  These immigrants have differing cultures, religions, and values, which can impact their interaction with the healthcare, housing, education, and other sectors.  Yet the current US government official policy for classifying race and ethnicity does not capture the diversity in the population, which has implications for the instruments utilized for monitoring in national and other surveys.  The accurate assessment and classification of race and ethnicity is vital for public officials since policy implementation, developing regulations, as well as the management and assessment of results against goals require timely and accurate data.  These public administration functions are impeded when the data lack precision or fail to make meaningful distinctions among groups for whom the consequences may differ.  

This study examines whether the current federal policy for classifying race/ethnicity or the routinely used taxonomies for race/ethnicity in national health surveys capture the diversity in the US population.  To demonstrate the importance of assessing the diversity in the US population, this study also examines the heterogeneity in one of the racial categories, the Black population, by utilizing secondary data from a nationally representative survey to investigate differences in health, health care access and utilization.  Specifically, it utilized a social equity framework to assess the differences in health, health care access and utilization among obese persons within three of the largest Black American subpopulations (US-born Blacks, African-born Blacks, and West Indian-born Blacks) and Whites. 

The results show that the current federal policy, "The Standards for the Classification of Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15)" requires federal agencies and programs to record, collect, and present data on race and ethnicity using one ethnicity (Hispanic or Latino) and five racial categories (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White).  These categorizations however, fail to address the diversity in the US population and most national health survey instruments only collect information on this minimum requirement.  Of the five national surveys reviewed only one, the National Health Interview Survey (NHIS), collected detailed information that can be used to decipher the diversity in the population. 

The findings from an analysis of the NHIS indicate that differences in health, health care access and utilization exists, and it varies between and within the Black ethnic subgroups and Whites.  These findings present several implications and opportunities for public administrators.    The analysis highlighted subgroup heterogeneity within the growing Black American population and as this population continues to grow; understanding and tracking this heterogeneity will become more important to ensure that our policy and administrative institutions operate more effectively to meet the needs of this population.

There is a need to standardize the classification of race and ethnicity in the US to capture information on the diversity in the population.  This may be accomplished by expanding the established standards by providing a comprehensive list of categories that include national origin/ancestry ethnicity categories.  This expanded categorization would allow government and other officials to accurately assess the population and develop and monitor policies geared towards addressing health and other disparities or inequities.