Uncovering Disparities in Vision Health in Rural vs Urban Areas: Is There a Difference?

Main Article Content

Karen Allison Leah Greene Chanbin Lee Deepkumar Patel

Abstract

Background: Blindness describes a condition in which patients have low vision, are legally blind, or totally blind. Disparities in vision health is a public health concern because it decreases quality of life and subsequently leads to a series of other health-related issues. These disparities exist across demographics, socioeconomic status, disease history, genetics, and geographic location, particularly in the urban vs. rural setting. Public health professionals need to shed light on these disparities to properly address them to ensure that individuals affected by blindness can receive proper care.


Objective: To investigate if there are discrepancies or inequalities in vision care in a rural setting vs. urban setting.


Methods: A multivariate binary logistic regression analysis using cross-sectional data from the Vision and Eye Health Surveillance System (VEHSS) was done using SAS Studio. Blindness, the outcome of interest, was defined as best-corrected visual acuity at less than 20/200 in the better-seeing eye. Each demographic subgroup was assessed in the counties included for upstate New York and downstate New York. Prevalence rates are expressed as a percent.


Results: The multivariate binary logistic regression analysis showed that non-Hispanic black individuals from upstate New York and downstate New York were most likely to be blind compared to white, non-Hispanic, any Hispanic, and other individuals. Factors that were significantly associated with blindness include the female gender, individuals aged 65 years and older, non-Hispanic black individuals, and those without Medicare. Residents from upstate New York had a slightly increased likelihood to develop blindness, 1.04 (1.01, 1.07), compared to residents in downstate New York.


Conclusions and Relevance: Blindness prevalence was highest in upstate New York, among non-Hispanic black individuals, the female gender, and individuals 65 years and older. Despite the blindness prevalence highest upstate, the difference was not clinically significant compared to downstate New York, despite a considerably larger number of resources present downstate compared to upstate. Given the severity of blindness as a public health concern, the discrepancies in eye care in urban vs. rural settings need to be investigated further.

Keywords: Disparities in Vision Health in Rural vs Urban Areas, Vision Health in Rural vs Urban Areas, Vision Health in Rural Areas, Vision Health in Urban Areas, Vision Health, Vision, Health

Article Details

How to Cite
ALLISON, Karen et al. Uncovering Disparities in Vision Health in Rural vs Urban Areas: Is There a Difference?. Medical Research Archives, [S.l.], v. 11, n. 3, apr. 2023. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/3664>. Date accessed: 20 apr. 2024. doi: https://doi.org/10.18103/mra.v11i3.3664.
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References

Uncovering Disparities in Vision Health in Rural vs Urban Areas: Is There a Difference?
1. U.S. Department of Health and Human Services. (n.d.). Minority Health and Health Disparities: Definitions and parameters. National Institute of Minority Health and Health Disparities. Retrieved February 5, 2022, from
https://www.nimhd.nih.gov/about/strategic-plan/nih-strategic-plan-definitions-and- parameters.html
2. WeihLM, HassellJB, KeeffeJE. Assessment of the impact of vision impairment. Invest Ophthalmol Vis Sci. 2002;43:927–935.
3. McCarty CA, Nanjan MB, Taylor HR. Vision impairment predicts 5 year mortality. Br J Ophthalmol. 2001 Mar;85(3):322-6. doi: 10.1136/bjo.85.3.322. PMID: 11222339; PMCID: PMC1723877.
4. Zambelli-Weiner A, Crews JE, Friedman DS. Disparities in adult vision health in the United States. Am J Ophthalmol. 2012 Dec;154(6 Suppl):S23-30.e1. doi: 10.1016/j.ajo.2012.03.018. Epub 2012 May 24. PMID: 22633355.
5. Schuster DP, Duvuuri V. Diabetes mellitus. Clin Podiatr Med Surg. 2002 Jan;19(1):79-107. doi: 10.1016/S0891-8422(03)00082-X. PMID: 11806167.
6. Wykoff CC, Khurana RN, Nguyen QD, Kelly SP, Lum F, Hall R, Abbass IM, Abolian AM, Stoilov I, To TM, Garmo V. Risk of Blindness Among Patients With Diabetes and Newly Diagnosed Diabetic Retinopathy. Diabetes Care. 2021 Mar;44(3):748-756. doi: 10.2337/dc20-0413. Epub 2021 Jan 20. PMID: 33472864; PMCID: PMC7896265.
7. GBD 2019 Blindness and Vision Impairment Collaborators; Vision Loss Expert Group of the Global Burden of Disease Study. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study. Lancet Glob Health. 2021 Feb;9(2):e144-e160. doi: 10.1016/S2214-109X(20)30489-7. Epub 2020 Dec 1. Erratum in: Lancet Glob Health. 2021 Apr;9(4):e408. PMID: 33275949; PMCID: PMC7820391.
8. What is legal blindness? OCFS. (n.d.). Retrieved February 5, 2022, from https://www.ocfs.ny.gov/programs/nyscb/FAQ.php
9. U.S. Census Bureau (2021). QuickFacts Kings County, New York. Retrieved from [https://www.census.gov/quickfacts/fact/table/kingscountynewyork/HCN010212].
10. Kings County, NY. Data USA. (n.d.). Retrieved January 29, 2022, from https://datausa.io/profile/geo/kings-county-ny
11. Lee SY, Mesfin FB. Blindness. [Updated 2021 Aug 11]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK448182/
12. Wang, W., & Lo, A. (2018). Diabetic Retinopathy: Pathophysiology and Treatments. International journal of molecular sciences, 19(6), 1816. https://doi.org/10.3390/ijms19061816
13. Mitchell P, Liew G, Gopinath B, Wong TY. Age-related macular degeneration. Lancet. 2018 Sep 29;392(10153):1147-1159. doi: 10.1016/S0140-6736(18)31550-2. PMID:30303083.
14. Pennington KL, DeAngelis MM. Epidemiology of age-related macular degeneration (AMD): associations with cardiovascular disease phenotypes and lipid factors. Eye Vis (Lond). 2016 Dec 22;3:34. doi: 10.1186/s40662-016-0063-5. PMID: 28032115; PMCID: PMC5178091.
15. Magliah, S. F., Bardisi, W., Al Attah, M., & Khorsheed, M. M. (2018). The prevalence and risk factors of diabetic retinopathy in selected primary care centers during the 3-year screening intervals. Journal of family medicine and primary care, 7(5), 975–981. https://doi.org/10.4103/jfmpc.jfmpc_85_18
16. Schuster AK, Erb C, Hoffmann EM, Dietlein T, Pfeiffer N. The Diagnosis and Treatment of Glaucoma. Dtsch Arztebl Int. 2020 Mar 27;117(13):225-234. doi: 10.3238/arztebl.2020.0225. PMID: 32343668; PMCID: PMC7196841.
17. Allison K, Patel D, Alabi O. Epidemiology of Glaucoma: The Past, Present, and Predictions for the Future. Cureus. 2020 Nov 24;12(11):e11686. doi: 10.7759/cureus.11686. PMID: 33391921; PMCID: PMC7769798.
18. Nizami AA, Gulani AC. Cataract. 2021 Aug 1. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan–. PMID: 30969521.
19. Liu YC, Wilkins M, Kim T, Malyugin B, Mehta JS. Cataracts. Lancet. 2017 Aug 5;390(10094):600-612. doi: 10.1016/S0140-6736(17)30544-5. Epub 2017 Feb 25. PMID:28242111.
20. West SK, Valmadrid CT. Epidemiology of risk factors for age-related cataract. Surv Ophthalmol. 1995 Jan-Feb;39(4):323-34. doi: 10.1016/s0039-6257(05)80110-9. PMID: 7725232.
21. U.S. Census Bureau (2021). QuickFacts Monroe County, New York. Retrieved from [https://www.census.gov/quickfacts/fact/table/monroecountynewyork/HCN010212].
22. Data downloads. (n.d.). Retrieved February 5, 2022, from https://data.hrsa.gov/data/download
23. County Health Rankings & Roadmaps. (n.d.). Retrieved February 5, 2022, from https://www.countyhealthrankings.org/app/new-york/2021/measure/factors/4/datasource
24. Education. USDA ERS - Data Products. (n.d.). Retrieved February 6, 2022, from https://data.ers.usda.gov/reports.aspx?ID=17829
25. Research center. unitedforalice. (n.d.). Retrieved February 6, 2022, from https://www.unitedforalice.org/state-overview/NewYork
26. Office of the professions. NYS Optometry:License Statistics. (n.d.). Retrieved February 6, 2022, from http://www.op.nysed.gov/prof/optom/optomcounts.htm
27. Flaxman AD, Wittenborn JS, Robalik T, et al. Prevalence of Visual Acuity Loss or Blindness in the US: A Bayesian Meta-analysis. JAMA Ophthalmol. 2021;139(7):717– 723. doi:10.1001/jamaophthalmol.2021.0527
28. Centers for Disease Control and Prevention. (2021, August 10). Vision Health Data and surveillance. Centers for Disease Control and Prevention. Retrieved March 28, 2022, from https://www.cdc.gov/visionhealth/data/index.html
29. Vision and Eye Health Surveillance System (VEHSS). NORC at the University of Chicago. (n.d.). Retrieved March 28, 2022, from https://www.norc.org/Research/Projects/Pages/vision-and-eye-health-surveillance- system.aspx
30. Centers for Disease Control and Prevention. (2021, May 3). Prevalence estimates. Centers for Disease Control and Prevention. Retrieved March 28, 2022, from https://www.cdc.gov/visionhealth/vehss/estimates/index.html
31. U.S. Census Bureau (2021). QuickFacts Monroe County, New York. Retrieved from [https://www.census.gov/quickfacts/fact/table/kingscountynewyork/RHI125220].
32. Paula Braveman, MD, MPH, Laura Gottlieb, MD, MPH: The Social Determinants of Health: It’s Time to Consider the Causes of the Causes: Public Health Reports /2014 supplements2 / Volume 129
33. McGinnis JM, Williams-Russo P, Knickman JR. The case for more active policy attention to health promotion. Health Affairs (Millwood)2002;21:78-93