title: Association Between County-Level Characteristics and Eye Care Use by US Adults in 22 States After Accounting for Individual-Level Characteristics Using a Conceptual Framework.
abstract: OBJECTIVE
  Individual-level characteristics are associated with eye care use. The influence of contextual factors on vision and eye health, as well as health behavior, is unknown.
  
  
  OBJECTIVE
  To examine the association between county-level characteristics and eye care use after accounting for individual-level characteristics using a conceptual framework.
  
  
  METHODS
  This investigation was a cross-sectional study of respondents 40 years and older participating in the Behavioral Risk Factor Surveillance System surveys between 2006 and 2010 from 22 states that used the Visual Impairment and Access to Eye Care module. Multilevel regressions were used to examine the association between county-level characteristics and eye care use after adjusting for individual-level characteristics (age, sex, race/ethnicity, educational attainment, annual household income, employment status, health care insurance coverage, eye care insurance coverage, personal established physician, poor vision or eye health, and diabetes status). Data analysis was performed from March 23, 2014, to June 7, 2016.
  
  
  METHODS
  Eye care visit and receipt of a dilated eye examination in the past year.
  
  
  RESULTS
  Among 117 295 respondents who resided in 828 counties, individual-level data were obtained from the Behavioral Risk Factor Surveillance System surveys. All county-level variables were aggregated at the county level from the Behavioral Risk Factor Surveillance System surveys except for a high geographic density of eye care professionals, which was obtained from the 2010 Area Health Resource File. After controlling for individual-level characteristics, the odds of reporting an eye care visit in the past year were significantly higher among people living in counties with high percentages of black individuals (adjusted odds ratio [aOR], 1.12; 95% CI, 1.01-1.24; P = .04) or low-income households (aOR, 1.12; 95% CI, 1.00-1.25; P = .045) or with a high density of eye care professionals (aOR, 1.18; 95% CI, 1.07-1.29; P < .001) than among those living in counties with the lowest tertile of each county-level characteristic. The odds of reporting receipt of a dilated eye examination in the past year were also higher among people living in counties with the highest percentages of black individuals (aOR, 1.20; 95% CI, 1.07-1.34; P = .002) or low-income households (aOR, 1.17; 95% CI, 1.04-1.32; P = .01). However, the odds of reported receipt of a dilated eye examination in the past year were lower in counties with the highest percentages of people with poor vision and eye health compared with counties with lower percentages (aOR, 0.85; 95% CI, 0.77-0.94; P = .002).
  
  
  CONCLUSIONS
  Contextual factors, measured at the county level, were associated with eye care use independent of individual-level characteristics. The findings suggest that, while individual characteristics influence health care use, it is also important to address contextual factors to improve eye care use and ultimately vision health.
authors: Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
authors: Chiu-Fang
authors: CF
authors: Chou
authors: Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
authors: Gloria L
authors: GL
authors: Beckles
authors: Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
authors: Yiling J
authors: YJ
authors: Cheng
authors: Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
authors: Jinan B
authors: JB
authors: Saaddine
mesh_terms: D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D005006:Ethnicity; D005128:Eye Diseases / Q000191:economics / Q000453:epidemiology / Q000628:therapy*; D005260:Female; D006295:Health Resources; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D019458:Insurance Coverage / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D009885:Ophthalmology / Q000706:statistics & numerical data*; D011159:Population Surveillance; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology