title: Impact of Income Inequality on the Nation's Health.
abstract: Income inequality in the United States has been increasing in recent decades. It is unclear whether income inequality has an independent effect on health outcomes, or whether it simply correlates with increasing levels of poverty. The goal of this study was to evaluate whether income inequality is significantly associated with US county health care expenditures and health care use.
  
  
  
  Cross-sectional analysis of county health expenditure data from the Health Resources and Services Administration's Area Resources File, county income inequality measures (Gini coefficient) from the Census' American Community Survey, and estimates of potentially preventable admissions and potentially discretionary procedures from the Nationwide Inpatient Sample (1998 to 2011). Datasets were linked via county Federal Information Processing Standard codes. Multivariable linear and Poisson regression analyses were performed at the county level adjusting for county characteristics.
  
  
  
  A total of 1,237 counties (of 3,144) were included. Income inequality was associated with higher health care expenditures, with each 1 percentage-point increase in county Gini coefficient associated with a US$40,008 increase in annual county Medicare cost (p = 0.003), and an increase of 174.7 total county Medicare inpatient days per year (p < 0.001). Even after accounting for poverty level and county characteristics, counties with higher inequality had higher potentially preventable admission (eg 4.86 rate ratio for low-birth-weight hospital admissions in the top income inequality quartile compared with bottom quartile; p < 0.001) and a higher incidence of potentially discretionary procedures (eg 1.79 rate ratio for prostatectomy for benign prostatic hyperplasia in the top income inequality quartile compared with bottom quartile; p < 0.001).
  
  
  
  Income inequality is independently associated with higher health care expenditures and more health care use, with increases in both potentially discretionary procedures and in potentially preventable admissions.
authors.affiliation: Francis Weld Peabody Society, Harvard Medical School, Boston, MA.
authors.forename: Diego B
authors.initials: DB
authors.lastname: López
authors.affiliation: Department of Surgery, Massachusetts General Hospital, Boston, MA.
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Loehrer
authors.affiliation: Department of Surgery, Massachusetts General Hospital, Boston, MA. Electronic address: dchang8@mgh.harvard.edu.
authors.forename: David C
authors.initials: DC
authors.lastname: Chang
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006296:Health Services / Q000191:economics / Q000706:statistics & numerical data*; D054624:Health Status Disparities; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D007223:Infant; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D016012:Poisson Distribution; D011203:Poverty / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012959:Socioeconomic Factors; D014481:United States; D055815:Young Adult