Inequalities in multiple health outcomes by education, sex, and race in 93 US counties: why we should measure them all

Int J Equity Health. 2014 Jun 13;13:47. doi: 10.1186/1475-9276-13-47.

Abstract

Introduction: Regular reporting of health inequalities is essential to monitoring progress of efforts to reduce health inequalities. While reporting of population health became increasingly common, reporting of a subpopulation group breakdown of each indicator of the health of the population is rarely a standard practice. This study reports education-, sex-, and race-related inequalities in four health outcomes in each of the selected 93 counties in the United States in a systematic and comparable manner.

Methods: This study is a cross-sectional analysis of large, publicly available data, 2008, 2009, and 2010 Behavioral Risk Factor Surveillance System (BRFSS) Selected Metropolitan/Micropolitan Area Risk Trends (SMART) and 2008, 2009, and 2010 United States Birth Records from the National Vital Statistics System. The study population is American adults older than 25 years of age residing in the selected 93 counties, representing about 30% of the US population, roughly equally covering all geographic regions of the country. Main outcome measures are: (1) Attribute (group characteristic)-specific inequality: education-, sex-, or race-specific inequality in each of the four health outcomes (poor or fair health, poor physical health days, poor mental health days, and low birthweight) in each county; (2) Overall inequality: the average of these three attribute-specific inequalities for each health outcome in each county; and (3) Summary inequality in total morbidity: the weighted average of the overall inequalities across the four health outcomes in each county.

Results: The range of inequality across the counties differed considerably by health outcome; inequality in poor or fair health had the widest range and the highest median among inequalities in all health outcomes. In more than 70% of the counties, education-specific inequality was the largest in all health outcomes except for low birthweight.

Conclusions: It is feasible to extend population health reporting to include reporting of a subpopulation group breakdown of each indicator of the health of the population at a small jurisdictional level using publicly available data. No single group characteristic or health outcome represents the whole picture of health inequalities in a population. Examining multiple group characteristics and outcomes in a comparable manner is essential in reporting health inequalities.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Behavioral Risk Factor Surveillance System
  • Birth Weight*
  • Continental Population Groups*
  • Cross-Sectional Studies
  • Educational Status*
  • Ethnic Groups*
  • Female
  • Health Status Disparities*
  • Health*
  • Humans
  • Male
  • Mental Health
  • Sex Factors
  • United States