Geospatial analysis of blindness within rural and urban counties
Fig 1
a. Prevalence of registered individuals with blindness per county in Oregon. b. Number of ophthalmologists in each Oregon county per 100,000 persons (year 2015). Counties with higher densities of ophthalmologists registered more people with blindness from any cause (OR 6.5 for blindness with one more ophthalmologist, p = .003, in a multivariable model using county data including median household income and race/ethnicity). c. Number of optometrists in each Oregon county per 100,000 persons (year 2015). The density of optometrists was not associated with blindness (p = .889) in a multivariable model using county data including median household income and race/ethnicity. d. Multivariable model for the odds of blindness per 10,000 persons by county (year 2015). Multivariable model using county data (median household income and race/ethnicity) in addition to density of ophthalmologists to predict the odds of blindness per 100,000 persons by county.