title: Variation in access to health care for different racial/ethnic groups by the racial/ethnic composition of an individual's county of residence.
abstract: BACKGROUND
  Although the majority of studies examining racial/ethnic disparities in health care have focused on the characteristics of the individual, more recently there has been growing attention to the notion that an individual's health practices could be influenced by the characteristics of the place where they reside.
  
  
  OBJECTIVE
  The objective of this study was to examine whether access to care for individuals of different racial/ethnic groups varies by the prevalence of blacks and the prevalence of Latinos in their county of residence.
  
  
  METHODS
  We conducted a cross-sectional cohort.
  
  
  METHODS
  Individuals from the 1996 Medical Expenditure Panel Survey, a nationally representative sample of U.S. households, who described their race/ethnicity as white, black, or Latino, and who resided in 1 of 677 counties (n = 14740) were studied.
  
  
  METHODS
  Counties were assigned to 6 groups based on the prevalence of blacks and Latinos who resided there (<6% referred to as "low prevalence," 6-39% referred to as "midprevalence," >or=40% referred to as "high prevalence" separately for both blacks and Latinos). Outcomes included whether during the past year any family members: 1). experienced difficulty obtaining any type of health care, delayed obtaining care, or did not receive health care they thought they needed (referred to as "difficulty obtaining care"); or (2). did not receive a doctor's care or a prescription medication because the family needed money to buy food, clothing, or pay for housing (referred to as "financial barriers").
  
  
  RESULTS
  After controlling for other individual and area-level covariates, blacks reported lower rates of both outcome variables when they lived in a county with a high prevalence of blacks compared with blacks who lived in a county with a low prevalence of blacks (difficulty obtaining care: 4.3% vs. 18.8%, P <0.005; financial barriers: 1.6% vs. 10.5%, P <0.005). There was a similar association for Latinos by the prevalence of Latinos in the county for difficulty obtaining care (high: 5.0% vs. low: 13.4%, P <0.05), but not the financial barriers outcome (high: 2.2% vs. low: 2.4%, P = 0.90). Whites who lived in an area with a high prevalence of Latinos were more likely to report both outcomes compared with whites who lived in a county with a low prevalence of Latinos (difficulty obtaining care: 17.7% vs. 9.4%, P <0.05; financial barriers: 8.5% vs. 3.2%, P <0.005) .
  
  
  CONCLUSIONS
  Blacks and Latinos may perceive fewer barriers to care when they live in a county with a high prevalence of people of similar race/ethnicity. Conversely, whites may perceive more difficulty receiving care when they live in an area with a high prevalence of Latinos. Diminishing disparities in access to health care may require interventions that extend beyond the individual.
authors.affiliation: Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusett 02160, USA. jhaas@partners.org
authors.forename: Jennifer S
authors.initials: JS
authors.lastname: Haas
authors.forename: Kathryn A
authors.initials: KA
authors.lastname: Phillips
authors.forename: Dean
authors.initials: D
authors.lastname: Sonneborn
authors.forename: Charles E
authors.initials: CE
authors.lastname: McCulloch
authors.forename: Laurence C
authors.initials: LC
authors.lastname: Baker
authors.forename: Celia P
authors.initials: CP
authors.lastname: Kaplan
authors.forename: Eliseo J
authors.initials: EJ
authors.lastname: Pérez-Stable
authors.forename: Su-Ying
authors.initials: SY
authors.lastname: Liang
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D005260:Female; D019538:Health Care Surveys; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006630:Hispanic or Latino / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D012111:Residence Characteristics; D014481:United States; D044465:White People / Q000706:statistics & numerical data*