June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Assessing the geographic distribution of vision impairment and care access disparities in the state of Ohio using national and state-specific health surveillance data.
Author Affiliations & Notes
  • Megan Hurley
    Ohio State University College of Optometry, Columbus, Ohio, United States
  • Lisa Jordan
    Ohio State University College of Optometry, Columbus, Ohio, United States
  • ERICA SHELTON
    Ohio State University College of Optometry, Columbus, Ohio, United States
  • Dean A VanNasdale
    Ohio State University College of Optometry, Columbus, Ohio, United States
  • Footnotes
    Commercial Relationships   Megan Hurley, None; Lisa Jordan, None; ERICA SHELTON, None; Dean VanNasdale, None
  • Footnotes
    Support  CDC/NACDD VI2020A to Ohio State University (PI VanNasdale)
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 3363. doi:
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      Megan Hurley, Lisa Jordan, ERICA SHELTON, Dean A VanNasdale; Assessing the geographic distribution of vision impairment and care access disparities in the state of Ohio using national and state-specific health surveillance data.. Invest. Ophthalmol. Vis. Sci. 2020;61(7):3363.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To quantify the correlation between county-level estimates of vision impairment (VI) and unmet need for vision care services in the state of Ohio.

Methods : Data from the 2017 American Community Survey (ACS) were used to determine county-level prevalence estimates for vision impairment in the state of Ohio. Responses from the 2017 Ohio Medicaid Assessment Survey (OMAS), which also samples from the non-Medicaid population, were used to estimate unmet vision care need for each county. Correlations between vision impairment prevalence and unmet vision care need were assessed using linear regression. Prevalence and access differences between the VI and non-VI cohorts were stratified by age, gender, and Medicaid eligibility (<138% Federal Poverty Limit, FPL) and compared.

Results : The overall prevalence of vision impairment in the adult population in the state of Ohio was 2.8%. County-level prevalence estimates ranged from 1.1% to 5.2% and percentage with unmet vision care needs ranged from 6.2% to 15.4%. County-level vision impairment and unmet vision care need were positively correlated (R2 = 0.32, p < 0.001). Adults below 138% Federal Poverty Level were significantly more like to report unmet vision care needs than those above 138% FPL (p < 0.001). Women were more likely than men to be visually impaired (t-test, p = 0.005), though there was no difference in access to care (p = 0.91). There was also no statistically significant difference across age categories with respect to care access (p = 0.46), but vision impairment did vary (p < 0.001), with the 65 years and older cohort experiencing the highest prevalence followed by the 35-64 years old cohort and 18-34 years old cohort, respectively.

Conclusions : The county-level prevalence of vision impairment is positively correlated with unmet vision care need in the state of Ohio. National and state-specific health surveillance data provide important insight into the burden and underlying determinants of vision impairment.

This is a 2020 ARVO Annual Meeting abstract.

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