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. 2022 Oct 10;17(10):e0275807.
doi: 10.1371/journal.pone.0275807. eCollection 2022.

Geospatial analysis of blindness within rural and urban counties

Facundo G Sanchez  1   2 , Stuart K Gardiner  2 , Shaban Demirel  2 , Jack P Rees  1 , Steven L Mansberger  1   2
Affiliations

Geospatial analysis of blindness within rural and urban counties

Facundo G Sanchez et al. PLoS One. .

Abstract

Purpose: To determine the associations of blindness within rural and urban counties using a registry of blind persons and geospatial analytics.

Methods: We used the Oregon Commission for the Blind registry to determine the number of persons who are legally blind, as well as licensure data to determine the density of eye care providers (optometrists and ophthalmologists) within each county of the State of Oregon. We used geospatial statistics, analysis of variance, and logistic regression to determine the explanatory variables associated with blindness within counties.

Results: We included 8350 individuals who are legally blind within the state of Oregon in the calendar year 2015. The mean observed prevalence of registered blindness was 0.21% and ranged almost 9-fold from 0.04% to 0.58% among counties (p < .001). In univariate models, higher blindness was associated with increasing median age (p = .027), minority race (p < .001), decreased median household income (p < .001), increased poverty within a county (p < .001), and higher density of ophthalmologists (p = .003). Density of optometrists was not associated with prevalence of blindness (p = .89). The final multivariable model showed higher blindness to be associated with lower median household income, higher proportion of black race, and lower proportion of Hispanic race (p < .001 for all).

Conclusion: Geospatial analytics identified counties with higher and lower than expected proportions of blindness even when adjusted for sociodemographic factors. Clinicians and researchers may use the methods and results of this study to better understand the distribution of individuals with blindness and the associated factors to help design public health interventions.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
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.
See this image and copyright information in PMC

References

    1. Wittenborn JS, Rein DB. Cost of vision problems: The economic burden of vision loss and eye disorders in the United States. NORC at the University of Chicago (2013). Chicago, IL.
    1. Varma R, Vajaranant TS, Burkemper B, et al.. Visual Impairment and Blindness in Adults in the United States: Demographic and Geographic Variations From 2015 to 2050. JAMA Ophthalmol. 2016;134(7):802–809. doi: 10.1001/jamaophthalmol.2016.1284 - DOI - PMC - PubMed
    1. Belkin M, Kalter-Leibovici O, Chetrit A, Skaat A. Time trends in the incidence and causes of blindness in Israel. Am J Ophthalmol. 2013;155(2):404. doi: 10.1016/j.ajo.2012.09.017 - DOI - PubMed
    1. Gibson DM. Eye care availability and access among individuals with diabetes, diabetic retinopathy, or age-related macular degeneration. JAMA Ophthalmol. 2014;132(4):471–477. doi: 10.1001/jamaophthalmol.2013.7682 - DOI - PubMed
    1. O’Colmain U, Anijeet D, Vosoughi M, Sinclair A, Sanders R. Glaucoma blind registration in Fife (2000–2009)—a retrospective cohort study. Ophthalmic Physiol Opt. 2011;31(4):360–366. doi: 10.1111/j.1475-1313.2011.00849.x - DOI - PubMed