Diabetes, glucose metabolism, and glaucoma: the 2005-2008 National Health and Nutrition Examination Survey.
BACKGROUND
Diabetes may affect vascular autoregulation of the retina and optic nerve and may be associated with an increased risk of glaucoma,but the association of prediabetes, insulin resistance, markers of glucose metabolismwith glaucoma has not beenevaluated in general population samples.


OBJECTIVE
To examine the relation between diabetes, pre-diabetes, metabolic syndrome and its components and the levels of fasting glucose, HbA1c and HOMA-IR with the prevalence of glaucoma in the general U.S. population.


METHODS
Cross-sectional study of 3,299 adult men and women from the 2005-2008 National Health and NutritionExamination Survey (NHANES). The presence of diabetes, prediabetes, the metabolic syndrome and its individual components and biomarkers of glucose metabolisms were based on standardized questionnaire and physical exam data and laboratory tests. The history of glaucoma was assessed through questionnaire during the home interview.


RESULTS
Diabetes was strongly associated with prevalent glaucoma.In fully adjusted models, the odds ratiofor glaucoma comparing participants with diabetes with participants in the reference group with neither pre-diabetes nor diabetes was 2.12 (95% CI: 1.23, 3.67). The corresponding odd ratio comparing participants with pre-diabetes to those in the reference group was 1.01 (95% CI: 0.57, 1.82). Patients with 5 or more years of diabetes duration hadan OR for glaucoma of 3.90 (95% CI: 1.63, 9.32) compared with patients with <5 years of diabetes duration. We also found a hockey-stick shaped associations between biomarkers of glucose metabolisms and the prevalence of glaucoma.


CONCLUSIONS
Diabetes was associated with higher risk of glaucoma. Participants without diabetes but at the higher levels of fasting glucose, fasting insulin, HbA1c and HOMA-IR spectrum may also be at greater risk of glaucoma.
Department of Epidemiology and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Di
D
Zhao
Department of Epidemiology and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea.
Juhee
J
Cho
Saevit Eye Hospital, Goyang, Gyeonggi-do, Korea.
Myung Hun
MH
Kim
Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
David
D
Friedman
Department of Epidemiology and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Eliseo
E
Guallar
D000328:Adult; D000368:Aged; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism; D048909:Diabetes Complications / Q000378:metabolism; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000378:metabolism*; D005260:Female; D005901:Glaucoma / Q000150:complications / Q000453:epidemiology* / Q000378:metabolism*; D005947:Glucose / Q000378:metabolism*; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007333:Insulin Resistance; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D016017:Odds Ratio; D015995:Prevalence; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014481:United States
D001786:Blood Glucose; D005947:Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human