June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Risk factors for glaucoma in the National Health and Nutrition Examination Survey 2005-2008
Author Affiliations & Notes
  • David S Friedman
    Ophthalmology, Johns Hopkins Wilmer Eye Inst, Baltimore, MD
    Dana Center for Preventive Ophthalmology, Johns Hopkins University, Baltimore, MD
  • Michael V Boland
    Ophthalmology, Johns Hopkins Wilmer Eye Inst, Baltimore, MD
  • Di Zhao
    Dana Center for Preventive Ophthalmology, Johns Hopkins University, Baltimore, MD
    Welch Center for Epidemiology, Johns Hopkins University, Baltimore, MD
  • Priya Gupta
    Ophthalmology, Johns Hopkins Wilmer Eye Inst, Baltimore, MD
  • Eliseo Guallar
    Dana Center for Preventive Ophthalmology, Johns Hopkins University, Baltimore, MD
    Welch Center for Epidemiology, Johns Hopkins University, Baltimore, MD
  • Fang Ko
    Moorfields Eye Hospital, London, United Kingdom
  • Footnotes
    Commercial Relationships David Friedman, None; Michael Boland, None; Di Zhao, None; Priya Gupta, None; Eliseo Guallar, None; Fang Ko, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 4341. doi:
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    • Get Citation

      David S Friedman, Michael V Boland, Di Zhao, Priya Gupta, Eliseo Guallar, Fang Ko, ; Risk factors for glaucoma in the National Health and Nutrition Examination Survey 2005-2008. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):4341.

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

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Abstract

Purpose: To determine risk factors for glaucoma in a representative population-based study in the United States.

Methods: We evaluated 6797 participants age 40 and older from the National Health and Nutrition Examination Survey (NHANES) from 2005-2008, who received questionnaire, physical examination, laboratory and vision tests including visual acuity, autorefraction, and fundus imaging. Images were initially graded by a reading center; those with a cup-to-disc ratio (CDR) ≥ 0.6 were re-graded by glaucoma specialists for quality, vertical CDR, notching of neuroretinal rim, excavation of optic cup, optic disc hemorrhage, disc tilting, and disc size. Likelihood of glaucoma (No, Possible, Probable, Definite, Unable) was determined. A participant was designated as having glaucoma if consensus expert grading in either eye was “Probable” or “Definite.”

Results: 5746 people received fundus photos, and 172 were identified as having glaucoma. Participants with glaucoma were significantly older, more likely to be black race, have education less than high school, have diabetes, have central obesity, have systolic hypertension or diastolic hypotension, and be non-smokers. Among those 65 years and older, those with glaucoma were more likely to have a combination of private and government-sponsored insurance, and less likely to have government insurance only. There were no significant differences among other types of insurance, or among those younger than 65 years old. There was no statistically significant association with gender, poverty, lack of access to healthcare, fasting glucose, insulin dependence, BMI ≥ 30, high triglyceride/HDL/LDL/total cholesterol level, diastolic hypertension, systolic hypotension, obstructive sleep apnea, and marijuana use. In multivariate regression modeling there was a statistically significant association of glaucoma with older age, black race, and poverty. Of note, diabetes was statistically significant if triglyceride levels were excluded from the model, but diabetes was not significant when triglyceride levels were included. Sex, education less than high school, insurance status, and body mass index ≥ 30, were not significant.

Conclusions: People who are older, of black race, and have lower income levels are at higher risk of glaucoma. A novel effect between the association of diabetes, triglyceride levels, and glaucoma was also identified.

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