Chronic Disease Disparities by County Economic Status and Metropolitan Classification, Behavioral Risk Factor Surveillance System, 2013

Abstract

Introduction: Racial/ethnic disparities have been studied extensively. However, the combined influence of geographic location and economic status on specific health outcomes is less well studied. This study's objective was to examine 1) the disparity in chronic disease prevalence in the United States by county economic status and metropolitan classification and 2) the social gradient by economic status. The association of hypertension, arthritis, and poor health with county economic status was also explored.

Methods: We used 2013 Behavioral Risk Factor Surveillance System data. County economic status was categorized by using data on unemployment, poverty, and per capita market income. While controlling for sociodemographics and other covariates, we used multivariable logistic regression to evaluate the relationship between economic status and hypertension, arthritis, and self-rated health.

Results: Prevalence of hypertension, arthritis, and poor health in the poorest counties was 9%, 13%, and 15% higher, respectively, than in the most affluent counties. After we controlled for covariates, poor counties still had a higher prevalence of the studied conditions.

Conclusion: We found that residents of poor counties had a higher prevalence of poor health outcomes than affluent counties, even after we controlled for known risk factors. Further, the prevalence of poor health outcomes decreased as county economics improved. Findings suggest that poor counties would benefit from targeted public health interventions, better access to health care services, and improved food and built environments.

Figure

Prevalence (weighted estimates and 95% CIs) of hypertension by county metropolitan classification and economic category, adults (≥18 y), Behavioral Risk Factor Surveillance System, 2013. Hypertension was defined by self-report of ever having been told by a health professional that they had hypertension. Metropolitan and nonmetropolitan categories were determined by using the Office of Management and Budget’s February 2013 delineations and data from the U.S. Census Bureau, Population Division (http://www.census.gov/population/metro/). County economic status was determined by using 2013 unemployment rate, per capita market income, and poverty rate for each county. An index was used to order counties into quintiles (poorest, poor, median, affluent, and most affluent). Abbreviations: CI, confidence interval; metro, metropolitan; nonmetro, nonmetropolitan. [Table: see text]