Epidemiology and risk factors of glaucoma in a comprehensive health screening baseline report from the Gangnam Eye Cohort Study

Epidemiology and risk factors of glaucoma in a comprehensive health screening baseline report from the Gangnam Eye Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Epidemiology and risk factors of glaucoma in a comprehensive health screening baseline report from the Gangnam Eye Cohort Study Eunoo Bak, Jin-Soo Kim, Dae Joong Ma, Jinho Lee, Baek Lok Oh, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5661349/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 8 You are reading this latest preprint version Abstract We investigated the epidemiology and systemic risk factors of glaucoma in a health screening center-based cohort. The Gangnam Eye Cohort Study included 75,154 participants who completed initial comprehensive health check-up examinations in 2003–2010. In this baseline report, the prevalence of glaucoma was estimated, ocular and systemic factors were compared between glaucoma and normal control groups, and risk factors were analyzed by logistic regression. The prevalence of glaucoma was 2.8%; 3.4% in men and 2.1% in women, and increased with age (P < 0.001). Mean age of the glaucoma group (52.8 ± 10.9 years) was older than that of the normal group (48.1 ± 10.3 years, P < 0.001). Mean intraocular pressure (IOP) of the glaucoma group (14.6 ± 3.1 mmHg) was higher than that of the normal group (13.2 ± 2.5 mmHg, P < 0.001). Older age (P < 0.001), male sex (P < 0.001), presence of retinal arteriosclerosis (P < 0.001), higher IOP (P < 0.001), higher household income (P = 0.045), higher education (P < 0.001), overweight status (P = 0.001), higher serum creatinine (P = 0.013) and uric acid (P = 0.008) were significantly associated with glaucoma. In this largest health screening center-based cohort study, considering the associations of glaucoma with retinal microvascular abnormality, obesity, and serum creatinine and uric acid, a common pathway such as arteriosclerosis or oxidative stress may be the vascular problem underlying glaucoma. Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors comprehensive health screening epidemiology risk factor glaucoma Figures Figure 1 Introduction Glaucoma is the leading cause of irreversible blindness and affects over 70 million individuals worldwide. 1 , 2 Previous large-scale epidemiology studies have revealed the prevalence of glaucoma; primary open-angle glaucoma and primary angle-closure glaucoma, to be 0.5–8.8%. 3–5 The prevalence of glaucoma in the Republic of Korea has been documented in a few population-based studies. The Namil study estimated the prevalence of glaucoma to be 3.5%, 6 and it was 4.7% in the Korea National Health and Nutrition Examination Survey (KNHANES). 7 Researchers have also attempted to identify risk factors for glaucoma. 8 , 9 Identified risk factors include older age, 1 , 7 , 9 non-white race, 5 , 10 family history of glaucoma, 11 – 13 elevated intraocular pressure (IOP), 14 , 15 and several systemic risk factors, such as diabetes mellitus (DM), 16 low blood pressure, 17 metabolic syndrome, 18 arterial stiffness, 19 and chronic kidney disease (CKD). 20 , 21 Unlike Western countries, most Asian nations have reported a higher prevalence of glaucoma with an IOP of 21 mmHg or lower. 6 , 22 – 24 Therefore, this population provides a good opportunity to investigate risk factors for glaucoma besides IOP. Consistently, the Namil study revealed age and history of thyroid disease as glaucoma risk factors, 6 while the KNHANES identified older age, male sex, myopia, hypertension (HTN), and non-overweight status as glaucoma risk factors. 7 Recently, health screening centers that provide comprehensive health check-up programs have become popular. They reflect the paradigm shift of medical care toward disease prevention and early diagnosis, which plays a significant role in national healthcare system. In fact, early detection of glaucoma has increased in the Republic of Korea since health check-up programs with screening fundus photography became commonplace. In parallel, participants undergo health interview surveys, anthropometry, physical examinations, various blood tests, and imaging studies. Therefore, in addition to population-based studies, large-scale health screening center-based scientific data could provide physicians with new insights for diagnosing and analyzing the risk factors of major ocular diseases, such as glaucoma. In the same context, we established a large healthcare center-based retrospective ophthalmic cohort, the Gangnam Eye Cohort, composed of consecutive subjects who visited Seoul National University Hospital (SNUH) Healthcare System Gangnam Center (HSGC) from the opening in October 2003. The primary goal of this ongoing cohort study is to investigate incidences and risk factors of major ophthalmic diseases causing visual loss such as age-related macular degeneration, glaucoma, and diabetic retinopathy based on minimum 10-year follow-up examinations. Meanwhile, it is meaningful to share baseline characteristics and statistical analysis data to understand the cohort and verify the feasibility of follow-up studies. Accordingly, the purpose of this study was to investigate glaucoma epidemiology and risk factors using baseline data of the Gangnam Eye Cohort, a health screening center-based cohort. To the best of our knowledge, this is the first study to report such data with comprehensive biometric screening in the Korean population 18 years of age or older using 8 years of data. Methods Study Design and Population The present study was based on the Gangnam Eye Cohort Study, an ongoing health screening center-based retrospective ophthalmic cohort survey conducted at SNUH HSGC which is one of the largest and leading health screening facilities in the Republic of Korea. The SNUH HSGC health screening system is an active follow-up mass screening system that allows participants to voluntarily visit the center, usually at a one-year follow-up interval, for repeated measurement and assessment of their overall health status. Other detailed information about the general cohort recruited through SNUH HSGC has been published elsewhere. 25 , 26 In this study, we used baseline data of the Gangnam Eye Cohort. The study population comprises Korean subjects aged 18 years or older who participated in a health screening program at SNUH HSGC between October 2003 and December 2010. This study was approved by the SNUH Institutional Review Board (IRB No. H-1906-141-1043). All of the procedures adhered to the tenets of the Declaration of Helsinki. Written informed consent to participate was obtained from all of the participants. Comprehensive Health Screening Examinations and Definition of Variables The health screening examination consisted of 2 parts: (1) the health interview survey and (2) the health examination survey, including a comprehensive ophthalmologic examination. The details of these examinations have been described elsewhere. 26 The health interview survey included standardized questionnaires on demographic variables and current and past medical conditions (e.g., DM, HTN, dyslipidemia, coronary heart disease, cerebral stroke, cancer), health-influencing behaviors (e.g., smoking status, drinking status), and socioeconomic status (e.g., household income, education). Regarding age, participants were divided into 6 age groups: younger than 40, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 years or older. Smoking status was categorized as never smoker, former smoker, and current smoker. Drinking status was categorized as never drinker, former drinker, and current drinker. Household income status was categorized as more than 50% of the household income and 50% of the household income or less of the average household income of Koreans. Regarding education status, participants were divided on the basis of whether they had at least a college degree and or had not graduated from college or lower-level schooling. The health examination survey included anthropometric measurements. Height, weight, waist circumference (WC), and blood pressure were measured by trained nurses. body mass index (BMI) was calculated as the ratio of weight (in kilograms) divided by square height (in meters). Subjects were categorized into 2 groups according to BMI: BMI less than 25 kg/m 2 and BMI of 25 kg/m 2 or more. Participants were divided into 2 groups by WC: WC < 90 cm for men and < 85 cm for women and WC ≥ 90 cm for men and ≥ 85 cm for women. Metabolic syndrome was defined based on criteria described elsewhere. 27 The ophthalmologic screening examination included measurement of visual acuity by Snellen chart, IOP measurement by noncontact tonometer (CT-80; Topcon Inc., Tokyo, Japan), and nonmydriatic fundus photography with a 45° field angle digital fundus camera (CR6-45NW; Canon Inc., Tokyo, Japan) in a dark room. Retinal arteriosclerosis grade (from 0 to 4) was determined using Scheie’s classification system with a slight modification to infer the ischemic status of the retina. Positive signs included diffuse arteriolar narrowing, arteriovenous compression, focal constriction or copper/silver-wire appearance. 28 In the present study, grades 0 and 1 were defined as normal, and grade 2 or more was considered to indicate significant arteriosclerosis. Individuals were excluded if they had poor-quality photo interference with visualization of the fundus, pathologic myopia obscuring visualization of the retinal nerve fiber layer (RNFL), 29 or non-glaucomatous abnormal optic disc. 30 The blood tests included total calcium, inorganic phosphorus, blood urea nitrogen (BUN), creatinine, aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, direct bilirubin, uric acid, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglyceride (TG), total protein, albumin, high-sensitivity C reactive protein (Hs-CRP), complete blood cell count (red blood cell, white blood cell, hematocrit[Hct]), fasting blood glucose, glycated hemoglobin (hemoglobin[Hb] A1c), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), hepatitis B surface antigen (HBsAg), hepatitis C antibody (Anti-HCV) and Helicobacter pylori antibody (Anti-HP). The laboratory medicine department at the SNUH is certified by the Korean Society of Laboratory Medicine and participated in the College of American Pathologist’s Survey/Proficiency Testing program. Diagnosis of Glaucoma Three discrete glaucoma reading committees were established, each comprising glaucoma specialists from different institutes to whom other information on the eyes was not revealed, and these specialists evaluated the fundus photographs. The vertical cup-to-disc ratio and rim width were measured on the disc photographs by a glaucoma specialist (EB). Each photograph was evaluated independently by the other 3 examiners to confirm the measurements by the glaucoma specialist (EB) and to detect RNFL defects. A RNFL defect was considered suggestive of glaucoma when its width at the disc edge was larger than a major retinal vessel, diverging in an arcuate or wedge shape. 31 If the decisions of all 3 examiners did not agree, a consensus was obtained by discussion, referring to the fundus color photographs. The criteria for glaucoma diagnosis, which was classified into normal, glaucoma suspect, and glaucoma, were based on the criteria outlined in the previous studies, including the International Society of Geographical and Epidemiological Ophthalmology criteria and other well-designed studies (Table 1 ). 32 – 34 Only eyes classified as (1) normal and (2) glaucoma were included for further analysis; glaucoma suspect cases were excluded from the present study. If there were any signs of glaucoma in one eye, the patient was classified in the glaucoma group. Table 1 The Glaucoma Diagnostic Criteria of this Study Diagnosis Criteria Normal (1) nonglaucomatous optic disc appearance and (2) absence of optic disc hemorrhage or RNFL defect and (3) optic disc not violating the neuroretinal rim thickness order of inferior > superior > nasal > temporal rule Glaucoma suspect (1) vertical cup-to-disc ratio ≥ 0.7 without RNFL defect or (2) rim width ≤ 0.1 of the disc diameter without RNFL defect or (3) presence of optic disc hemorrhage without RNFL defect or (4) a RNFL defect without glaucomatous optic disc change Glaucoma (1) vertical cup-to-disc ratio ≥ 0.9 or (2) rim width ≤ 0.05 of the disc diameter or (3) presence of RNFL defect compatible with optic disc appearance or (4) presence of optic disc hemorrhage corresponding to RNFL defect RNFL = retinal nerve fiber layer Statistical Analysis Statistical analyses were performed with the Statistical Package for Social Sciences (SPSS) version 23.0 for Windows (SPSS, Inc., Chicago, IL) and SAS software version 9.4 (SAS Inc, Cary, NC). A P < 0.05 was considered statistically significant. In cases where both eyes were eligible, one eye was chosen at random using the random sample option in SPSS, and the ophthalmic examination test of that eye was used for further analysis. The demographic characteristics were compared using Student’s t test for continuous variables and the chi-square test for categorical variables. The risk factors for glaucoma were investigated by univariate logistic regression analysis. Variables with P < 0.10 were selected as candidates for the subsequent multivariate analysis by the stepwise selection method. Multivariable regression analyses were performed after correction for multiple testing using Benjamini–Hochberg procedure. Multicollinearity was detected by using the variance inflation factor (VIF) in a regression model. VIF above 10 which indicate variable correlation were evaluated. Variables correlated significantly with each other were not analyzed simultaneously to avoid multicollinearity. Instead, the variable with the highest significance among correlated variables was chosen. Odds ratios with 95% CI values were calculated in all the regression analyses. Results Demographic and Clinical Characteristics A total of 76,030 subjects (40,463 males) visited SNUH HSBC and underwent comprehensive health screening examinations from October 2003 to December 2010. After the exclusion of 496 non-Korean subjects, 75,534 Korean subjects (40,132 males) were enrolled in the Gangnam Eye Cohort Study. Among them, 380 subjects were excluded for reasons including poor photographic image quality (n = 79), concomitant pathological myopia (n = 204), and concomitant binocular disc morphological abnormalities (n = 97). Of the 75,154 eligible subjects with a qualifying fundus photograph for at least 1 eye, 67,683 were normal subjects (control group), 5,378 were glaucoma suspect, and 2,093 were glaucoma (unilateral 1,455 and bilateral 638) (Fig. 1 ). The mean age was 48.4 ± 10.4 years (range, 18–93 years), and mean IOP was 13.3 ± 2.5 mmHg (range, 6–35 mmHg). Patients with glaucoma were significantly older (52.8 ± 10.9 years) and had a significantly higher IOP (14.7 ± 3.1 mmHg) than the individuals in the control group (48.1 ± 10.3 years and 13.3 ± 2.5 mmHg, respectively; all P < 0.001). Prevalence of Glaucoma The overall prevalence of glaucoma was estimated to be 2.8% (n = 2093, 95% CI, 2.6–3.2), and that of glaucoma with an IOP of 21 mmHg or less was 2.7% (n = 2046, 95% CI, 2.5–3.1). Unilateral glaucoma was observed in 1,464 of 2,093 subjects (69.9%). The prevalence of glaucoma in men (3.4%) was higher than that in women (2.1%; P < 0.001). The glaucoma prevalence for the different age groups, younger than 40, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 years or older, was 1.5%, 2.3%, 3.2%, 4.5%, 6.2%, and 13.2%, respectively (Table 2 ); thus, glaucoma prevalence increased significantly with age ( P < 0.001). Meanwhile, the prevalence of glaucoma suspect was estimated to be 7.2% (n = 5,378, 95% CI, 6.9–7.6). Eyes in the (1) normal group and (2) glaucoma group were included for further analysis, and glaucoma suspects were excluded (Fig. 1 ). Table 2 Age-specific Prevalence of Glaucoma Age Group, y Total Male Subjects Female Subjects Cohort population Glaucoma cases Prevalence Cohort population Glaucoma cases Prevalence Cohort population Glaucoma cases Prevalence < 40 16901 254 1.5 8692 175 2.0 8209 79 1.0 40–49 25415 576 2.3 13706 401 2.9 11709 175 1.5 50–59 21117 684 3.2 11113 457 4.1 10004 227 2.3 60–69 9609 436 4.5 5272 256 4.9 4337 180 4.2 70–79 1938 120 6.2 1050 61 5.8 888 59 6.6 ≥ 80 174 23 13.2 121 19 15.7 53 4 7.5 Total 75154 2093 2.8 39954 1369 3.4 35200 724 2.1 Risk Factors for Glaucoma The characteristics compared between participants with and without glaucoma and associated risk factors with univariate analysis are presented in Table 3 . Variables with VIF above 10 were total cholesterol (VIF 43.003) and LDL cholesterol (VIF 31.768). The variables with a P value less than 0.10 were subsequently included in the multivariate analysis. In the multivariate analysis, the prevalence of glaucoma was positively associated with older age ( P < 0.001), male sex ( P < 0.001), higher household income ( P = 0.045), higher education ( P < 0.001), overweight status ( P = 0.001), higher IOP ( P < 0.001), presence of retinal arteriosclerosis ( P < 0.001), higher serum creatinine ( P = 0.013) and uric acid ( P = 0.008) ( Table 4 ) . Table 3 Comparison of Characteristics between Participants with and without Glaucoma and Associated Risk Factors Using Univariate Logistic Regression Analysis Normal (n = 67,683) Glaucoma (n = 2,093) Univariable Odds Ratio 95% CI P Value Demographics Age, n (%) <40 (reference) 15726 (23.2) 254 (12.1) 40–49 23232 (34.3) 576 (27.5) 1.535 1.323–1.782 < 0.001* 50–59 18674 (27.6) 684 (32.7) 2.268 1.961–2.623 < 0.001* 60–69 8293 (12.3) 436 (20.8) 3.255 2.782–3.808 < 0.001* 70–79 1617 (2.4) 120 (5.7) 4.595 3.676–5.743 < 0.001* ≥80 141 (0.2) 23 (1.1) 10.099 6.389–15.964 < 0.001* Gender, n (%) Female (reference) 32420 (47.9) 724 (34.6) Male 35263 (52.1) 1369 (65.4) 1.738 1.587–1.905 < 0.001* Medical condition, n (%) DM 6362 (9.4) 311 (14.9) 1.684 1.489–1.904 < 0.001* HTN 16116 (23.5) 763 (36.5) 1.839 1.680–2.014 < 0.001* Dyslipidemia 15777 (23.3) 491 (23.5) 1.009 0.911–1.119 0.86 Coronary heart disease 2273 (3.4) 114 (5.4) 1.658 1.367–2.012 < 0.001* Metabolic syndrome 15086 (22.3) 602 (28.8) 1.409 1.280–1.552 < 0.001* Cerebral stroke 289 (0.4) 16 (0.8) 1.797 1.084–2.979 0.023* Cancer 1168 (1.7) 42 (2.0) 1.000 1.000–1.000 0.74 Smoking status, n (%) Never (reference) 35294 (52.1) 949 (45.3) Former 15803 (23.3) 638 (30.5) 1.501 1.356–1.663 < 0.001* Current 14186 (21.0) 431 (20.6) 1.130 1.007–1.268 0.038* Drinking status, n (%) Never (reference) 18869 (27.9) 528 (25.2) Former 2019 (3.0) 74 (3.5) 1.310 1.023–1.678 0.033* Current 43985 (65.0) 1401 (66.9) 1.138 1.028–1.260 0.012* Household Income, n (%) < 50 (reference) 23590 (34.9) 683 (32.6) ≥ 50 38310 (56.6) 1243 (59.4) 1.121 1.019–1.232 0.018* Education, n (%) < College (reference) 21781 (32.1) 627 (30.0) ≥ College 44498 (65.7) 1416 (67.7) 1.105 1.005–1.216 0.039* Anthropometric BMI (kg/m2), n (%) < 25 (reference) 48145 (71.1) 1438 (68.7) ≥ 25 19273 (28.5) 643 (30.7) 1.117 1.016–1.228 0.022* WC (cm), n (%) Normal (reference) 49250 (72.8) 1462 (69.9) Abnormal 18144 (26.8) 618 (29.5) 1.147 1.043–1.262 0.005* Blood Pressure Systolic 117.1 ± 15.7 121.2 ± 16.6 1.016 1.013–1.019 < 0.001* Diastolic 75.9 ± 12.0 78.5 ± 12.2 1.018 1.014–1.021 < 0.001* Ocular characteristics IOP (mmHg) 13.3 ± 2.5 14.7 ± 3.1 1.210 1.191–1.229 < 0.001* Retinal arteriosclerosis, n (%) Absent (reference) 65231 (96.4) 1730(82.7) Present 2452 (3.6) 363 (17.3) 5.582 4.950–6.294 < 0.001* Blood tests Ca 9.2 ± 0.4 9.3 ± 0.4 1.191 0.633–2.242 0.58 P 3.7 ± 0.6 3.6 ± 0.6 1.027 0.849–1.243 0.78 BUN 13.6 ± 3.6 14.2 ± 3.9 0.868 0.632–1.192 0.38 Creatinine 1.0 ± 0.2 1.0 ± 0.2 3.417 2.198–5.313 < 0.001* AST 24.2 ± 15.3 25.7 ± 14.6 1.217 1.066–1.389 0.004* ALT 25.9 ± 25.1 27.6 ± 22.8 1.168 1.043–1.309 0.007* ALP 61.9 ± 19.9 64.2 ± 22.1 0.720 0.623–0.832 < 0.001* GGT 34.1 ± 43.4 37.2 ± 41.3 1.184 1.071–1.308 0.001* Total bilirubin 1.1 ± 0.5 1.1 ± 0.4 1.091 0.955–1.247 0.19 Direct bilirubin 0.3 ± 0.1 0.2 ± 0.1 0.367 0.044–3.052 0.35 Uric acid 5.5 ± 1.4 5.8 ± 1.8 1.494 1.287–1.735 < 0.001* Total cholesterol 195.3 ± 34.5 196.3 ± 34.8 1.064 0.975–1.162 0.16 LDL 119.7 ± 32.0 121.3 ± 32.4 1.136 1.038–1.244 0.006* HDL 54.4 ± 13.4 53.3 ± 13.3 1.377 1.123–1.689 0.002* TG 114.0 ± 77.7 119.7 ± 69.8 1.208 1.098–1.329 < 0.001* Total protein 7.2 ± 0.5 7.2 ± 0.4 1.185 0.748–1.876 0.47 Albumin 4.4 ± 0.3 4.4 ± 0.3 1.199 0.379-3.800 0.75 Hs-CRP 0.3 ± 1.1 0.3 ± 1.2 1.344 0.990–1.824 0.06 RBC 4.6 ± 0.5 4.7 ± 0.5 1.018 0.867–1.196 0.83 WBC 5.8 ± 1.8 5.8 ± 1.7 0.873 0.755–1.010 0.07 Hct 42.7 ± 4.4 43.4 ± 4.1 0.838 0.735–0.955 0.008* Fasting blood glucose 98.0 ± 19.3 101.8 ± 24.4 1.381 1.262–1.511 < 0.001* HbA1c 5.7 ± 0.8 5.7 ± 0.9 1.309 1.198–1.431 < 0.001* ApoA1 123.2 ± 22.0 123.2 ± 24.0 1.000 0.988–1.012 0.99 ApoB 95.3 ± 22.3 90.6 ± 22.5 0.990 0.979–1.002 0.11 HBsAg, n (%) 3032 (0.04) 92 (0.04) 0.982 0.794–1.214 0.86 Anti-HCV, n (%) 721 (0.01) 30 (0.01) 1.353 0.937–1.955 0.11 Anti-HP, n (%) 33919 (0.49) 1045 (0.50) 0.980 0.893–1.076 0.67 Data are mean ± standard deviation. Significant values with P < 0.05 are indicated by asterisk. CI = confidence interval; DM = diabetes mellitus; HTN = hypertension; BMI = Body mass index; WC = waist circumference; IOP = intraocular pressure; Ca = calcium; P = phosphorus; BUN = blood urea nitrogen; AST = aspartate transaminase; ALT = alanine transaminase; ALP = alkaline phosphatase; GGT = gamma-glutamyl transferase; LDL = low-density lipoprotein; HDL = high-density lipoprotein; TG = triglyceride; Hs-CRP = high-sensitivity C reactive protein; RBC = red blood cell; WBC = white blood cell; Hct = hematocrit; HbA1c = hemoglobin A1c; ApoA1 = apolipoprotein A1; ApoB = apolipoprotein B; HBsAg = hepatitis B surface antigen; Anti-HCV = hepatitis C antibody; Anti-HP = Helicobacter pylori antibody Table 4 Significant Risk Factors Associated with Glaucoma by Multivariate Logistic Regression Analysis Risk Factors Odds Ratio 95% CI P Value* Demographics Age < 0.001 <40 (reference) 1.000 40–49 1.425 1.177–1.725 < 0.001 50–59 2.139 1.772–2.583 < 0.001 60–69 2.852 2.322–3.502 < 0.001 70–79 4.381 3.277–5.856 < 0.001 ≥80 10.410 5.758–18.820 < 0.001 Gender Female (reference) 1.000 Male 1.495 1.325–1.687 < 0.001 Household Income (%) < 50 (reference) 1.000 ≥ 50 1.120 1.188–1.271 0.045 Education < College (reference) 1.000 ≥ College 1.281 1.131–1.452 < 0.001 Anthropometric BMI (kg/m 2 ) < 25 (reference) 1.000 ≥ 25 1.242 1.120–1.378 0.001 Ocular characteristics Retinal arteriosclerosis Absent (reference) 1.000 Present 4.528 3.904–5.252 < 0.001 IOP (mmHg) 1.120 1.188–1.234 < 0.001 Blood tests Creatinine 1.975 1.157–3.372 0.013 Uric acid 1.281 1.068–1.537 0.008 CI = confidence interval; BMI = Body mass index; IOP = intraocular pressure *Significant after Benjamini-Hochberg procedure. Discussion In this health screening center-based Gangnam Eye Cohort Study, the prevalence of glaucoma was 2.8% which was higher in men and in those of older age. More importantly, the present study revealed that older age, male sex, higher IOP, presence of retinal arteriosclerosis, higher household income, higher education, overweight status, higher serum creatinine and uric acid were independent risk factors for glaucoma. Older age and high IOP are reported as risk factors for glaucoma worldwide and in population-based studies of Asians. 35 – 40 This study also identified age-related increases in glaucoma prevalence and IOP as risk factors for glaucoma. Approximately 98% of our glaucoma patients had an IOP of 21 mmHg or less (14.4 ± 2.8 mmHg; range, 6–21 mmHg). However, the mean IOP of the glaucoma patients (14.6 ± 3.1 mmHg; range, 6–35 mmHg) was significantly higher than that of the control group (13.2 ± 2.5 mmHg; range, 6–21 mmHg). Baseline elevated IOP increased the risk for incident glaucoma by 1.12 for each 1-mmHg increase in the present study. These results indicate that high IOP can play an important role even in patients with an IOP in the normal range. The association between glaucoma and gender has generated inconsistent results across studies. Several studies have reported contradictory findings, while numerous epidemiologic studies worldwide have reported that men are more likely to have glaucoma than women. 9 , 22 , 41 – 43 Likewise, we found that the prevalence of glaucoma was 3.4% in men vs. 2.1% in women, and the risk was 1.5 times higher in men than in women. Interestingly, the odds ratio was almost the same as that of the KNHANES, the largest population-based study involving the same ethnic group. 7 The low prevalence of glaucoma in women has been explained by the protective roles of endogenous estrogen, 44 exogenous hormone use after menopause, 45 and genetic variability. 46 Higher levels of education and income were associated with glaucoma in the current study. While previous studies have revealed that lower socioeconomic status is associated with a higher risk of glaucoma, 47 , 48 others have indicated that those with higher socioeconomic status are more aware of their own diseases and are more likely to have access to healthcare providers. 49 The accessibility of medical services affects the detection of glaucoma, which is influenced by socioeconomic status. 50 , 51 Arteriosclerosis is a systemic condition affecting arteries of all sizes, including small ocular arteries. 52 It may result in alteration in circulatory hemodynamics and disruption of ocular autoregulation, thus relating glaucoma development or aggravation. Population-based studies reported retinal arteriolar narrowing associated with glaucoma, while population-based data on the relationship between arteriosclerosis and glaucoma are scarce and inconclusive. 53 – 55 More than retinal arteriolar narrowing, the Gangnam Eye Cohort Study is the first health screening center-based study to investigate the association between glaucoma and retinal arteriosclerosis ; which includes retinal arteriolar narrowing, arteriovenous compression, focal constriction, and copper/silver-wire appearance. Retinal arteriosclerosis was present in 17.3% of glaucoma patients vs. 3.5% of normal control patients, and it increased the risk of glaucoma by approximately 4.5-fold. This adds further information to previous population-based studies and supports the “vascular theory” of glaucoma. 53 – 55 Additionally, obesity and high BMI are associated with an increased risk for both elevated IOP 56 , 57 and vascular dysregulation, such as arteriosclerosis. 58 In our study, overweight participants had a higher risk for glaucoma. Newman-Casey et al. reported an increased glaucoma hazard associated with obesity, although its association with glaucoma remains under debate. 59 One of the most distinct variables associated with glaucoma in this study was high serum uric acid. Uric acid plays an important role in the pathophysiology of CKD and is one of the main ocular antioxidative small molecules. 60 , 61 While being a potent antioxidant in the extracellular environment, uric acid is a pro-oxidant inside the cell where it can induce mitochondrial dysfunction. 62 An imbalance between oxidative stress and antioxidant defense contributes to the pathogenesis of various ocular diseases, including glaucoma. 63 In previous studies on serum uric acid levels and different subtypes of glaucoma, there was no consistent direction of the effect. 64 – 68 Opposite mechanisms could lead to variable outcomes. First, uric acid being a marker of CKD, a presumed harmful process. Second, low uric acid levels have been associated with neurodegenerative disease, possibly via the fact that uric acid has a strong antioxidant capacity. Other possible explanations for this inconsistency are differences in ethnicity or differences in confounding factors. Additionally, in this study, high creatinine was associated with glaucoma. Recent studies have shown that the serum uric acid to creatinine ratio is a good biomarker for detecting the pathogenesis of metabolic syndrome and CKD. 69 – 72 Therefore, these antioxidants may serve as biomarkers for predictive diagnostics and therapeutic targets for glaucoma. This study has some limitations. First, this study was based on a health screening center located in Seoul, the capital of the Republic of Korea. Selection bias may have contributed to data collection making it less representative of the Korean population. Second, approximately 98% of glaucoma participants had an IOP of 21 mmHg or lower; therefore, our findings may be more relevant to glaucoma patients with normal baseline IOP. However, previously diagnosed ocular disease, such as glaucoma, was not included in the initial health interview survey. Possible use of IOP lowering medications or previous surgery of glaucoma may affect IOP and should be interpreted cautiously. Third, we did not perform visual field testing on all subjects because the cohort was based on a healthcare screening program. The glaucoma grading scheme required a glaucomatous optic disc with a RNFL defect to be classified as glaucoma. This approach streamlined the logistics of examining the cohort, but it is possible that some subjects with subtle optic nerve changes were missed. Fourth, angle examination with gonioscopy was not performed; therefore, we could not disaggregate the subtype of glaucoma (i.e., primary open-angle vs. primary angle-closure). Despite this fact, previous reports suggest that the rate of primary angle-closure glaucoma is negligible (0.1%). 73 Further studies including gonioscopy should be conducted. This study has several strengths. First, to the best of our knowledge, this is the largest health screening center-based study that determined the prevalence of glaucoma and associated risk factors. Additionally, the present study is the first report to include young adults under age 40, with a glaucoma prevalence of 1.5%. This highlights the importance of health screening even in young adults, which leads to early detection required to cope with the growing burden of glaucoma. Additionally, we included comprehensive biometric screenings and revealed risk factors for glaucoma: high BMI, high serum uric acid and creatinine levels. Correction of antioxidant conditions may be recommended, taking into account the harmful associations of overweight status. Our findings also imply a possible different pathophysiologic course of glaucoma with normal IOP. Despite the potential limitations that the present study may have, we believe that this study may serve as a reference for public health policy and planning. In conclusion, the prevalence of glaucoma in the health screening center-based Gangnam Eye Cohort Study was 2.8%. Older age, male sex, high IOP, retinal arteriosclerosis, overweight status, and high serum uric acid and creatinine were independent risk factors for glaucoma. Considering the associations of glaucoma with retinal microvascular abnormalities, obesity, and serum uric acid, a common pathway such as arteriosclerosis or oxidative stress may be the vascular problem underlying glaucoma. Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Declarations Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Acknowledgements None. Author contributions EB and HJC performed the study design. EB and HJC helped in writing the article. Data collection was done by EB, JSK, DJM, JL, BLO, AH, HJC. Analysis and interpretation of the data were done by EB and HJC. EB, DJM, HJC helped in literature search. EB and HJC helped in critical revision of the article. HJC gave the final approval of the article. Additional Information Competing interests: The authors declare no competing interests. Financial Support: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2024-00342696). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. References Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. British Journal of Ophthalmology 2006;90:262. Weinreb RN, Aung T, Medeiros FA. The Pathophysiology and Treatment of Glaucoma: A Review. JAMA 2014;311:1901-1911. Foster PJ, Baasanhu J, Alsbirk PH, Munkhbayar D, Uranchimeg D, Johnson GJ. 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Ophthalmology 2007;114:1058-1064. de Voogd S, Ikram MK, Wolfs RCW, Jansonius NM, Hofman A, de Jong PTVM. Incidence of Open-Angle Glaucoma in a General Elderly Population: The Rotterdam Study. Ophthalmology 2005;112:1487-1493. Wang YX, Xu L, Yang H, Jonas JB. Prevalence of Glaucoma in North China: The Beijing Eye Study. American Journal of Ophthalmology 2010;150:917-924. Vijaya L, George R, Baskaran M, et al. Prevalence of Primary Open-angle Glaucoma in an Urban South Indian Population and Comparison with a Rural Population: The Chennai Glaucoma Study. Ophthalmology 2008;115:648-654.e641. Suzuki Y, Iwase A, Araie M, et al. Risk Factors for Open-Angle Glaucoma in a Japanese Population: The Tajimi Study. Ophthalmology 2006;113:1613-1617. Jiang X, Varma R, Wu S, et al. Baseline Risk Factors that Predict the Development of Open-Angle Glaucoma in a Population: The Los Angeles Latino Eye Study. Ophthalmology 2012;119:2245-2253. Ramakrishnan R, Nirmalan PK, Krishnadas R, et al. Glaucoma in a rural population of southern India: The Aravind comprehensive eye survey. Ophthalmology 2003;110:1484-1490. Yamamoto S, Sawaguchi S, Iwase A, et al. Primary Open-Angle Glaucoma in a Population Associated with High Prevalence of Primary Angle-Closure Glaucoma: The Kumejima Study. Ophthalmology 2014;121:1558-1565. Rahman MM, Rahman N, Foster PJ, et al. The prevalence of glaucoma in Bangladesh: a population based survey in Dhaka division. British Journal of Ophthalmology 2004;88:1493. Lee AJ, Mitchell P, Rochtchina E, Healey PR. Female reproductive factors and open angle glaucoma: the Blue Mountains Eye Study. Br J Ophthalmol 2003;87:1324-1328. Newman-Casey PA, Talwar N, Nan B, Musch DC, Pasquale LR, Stein JD. The Potential Association Between Postmenopausal Hormone Use and Primary Open-Angle Glaucoma. JAMA Ophthalmology 2014;132:298-303. Pasquale LR, Loomis SJ, Weinreb RN, et al. Estrogen pathway polymorphisms in relation to primary open angle glaucoma: an analysis accounting for gender from the United States. Mol Vis 2013;19:1471-1481. Sung H, Shin HH, Baek Y, et al. The association between socioeconomic status and visual impairments among primary glaucoma: the results from Nationwide Korean National Health Insurance Cohort from 2004 to 2013. BMC Ophthalmology 2017;17:153. Oh SA, Ra H, Jee D. Socioeconomic Status and Glaucoma: Associations in High Levels of Income and Education. Current Eye Research 2019;44:436-441. Ramdas WD, Wolfs RCW, Hofman A, de Jong PTVM, Vingerling JR, Jansonius NM. Lifestyle and Risk of Developing Open-Angle Glaucoma: The Rotterdam Study. Archives of Ophthalmology 2011;129:767-772. Zhang X, Beckles GL, Chou CF, et al. Socioeconomic disparity in use of eye care services among US adults with age-related eye diseases: National Health Interview Survey, 2002 and 2008. JAMA Ophthalmol 2013;131:1198-1206. Zhang X, Cotch MF, Ryskulova A, et al. Vision health disparities in the United States by race/ethnicity, education, and economic status: findings from two nationally representative surveys. Am J Ophthalmol 2012;154:S53-62.e51. Hayreh SS. Retinal and optic nerve head ischemic disorders and atherosclerosis: role of serotonin. Prog Retin Eye Res 1999;18:191-221. Mitchell P, Leung H, Wang JJ, et al. Retinal vessel diameter and open-angle glaucoma: the Blue Mountains Eye Study. Ophthalmology 2005;112:245-250. Amerasinghe N, Aung T, Cheung N, et al. Evidence of retinal vascular narrowing in glaucomatous eyes in an Asian population. Invest Ophthalmol Vis Sci 2008;49:5397-5402. Wang S, Xu L, Wang Y, Wang Y, Jonas JB. Retinal vessel diameter in normal and glaucomatous eyes: the Beijing eye study. Clinical & experimental ophthalmology 2007;35:800-807. Klein BE, Klein R, Linton KL. Intraocular pressure in an American community. The Beaver Dam Eye Study. Invest Ophthalmol Vis Sci 1992;33:2224-2228. Karadag R, Arslanyilmaz Z, Aydin B, Hepsen IF. Effects of body mass index on intraocular pressure and ocular pulse amplitude. Int J Ophthalmol 2012;5:605-608. Haslam DW, James WP. Obesity. Lancet 2005;366:1197-1209. Newman-Casey PA, Talwar N, Nan B, Musch DC, Stein JD. The Relationship Between Components of Metabolic Syndrome and Open-Angle Glaucoma. Ophthalmology 2011;118:1318-1326. Nita M, Grzybowski A. The Role of the Reactive Oxygen Species and Oxidative Stress in the Pathomechanism of the Age-Related Ocular Diseases and Other Pathologies of the Anterior and Posterior Eye Segments in Adults. Oxid Med Cell Longev 2016;2016:3164734. Giordano C, Karasik O, King-Morris K, Asmar A. Uric Acid as a Marker of Kidney Disease: Review of the Current Literature. Disease Markers 2015;2015. Sánchez-Lozada LG, Lanaspa MA, Cristóbal-García M, et al. Uric acid-induced endothelial dysfunction is associated with mitochondrial alterations and decreased intracellular ATP concentrations. Nephron Experimental nephrology 2012;121:e71-78. Hsueh Y-J, Chen Y-N, Tsao Y-T, Cheng C-M, Wu W-C, Chen H-C. The Pathomechanism, Antioxidant Biomarkers, and Treatment of Oxidative Stress-Related Eye Diseases. International Journal of Molecular Sciences 2022;23:1255. Elisaf M, Kitsos G, Bairaktari E, Kalaitzidis R, Kalogeropoulos C, Psilas K. Metabolic abnormalities in patients with primary open-angle glaucoma. Acta Ophthalmologica Scandinavica 2001;79:129-132. Yuki K, Murat D, Kimura I, Ohtake Y, Tsubota K. Reduced-serum vitamin C and increased uric acid levels in normal-tension glaucoma. Graefes Arch Clin Exp Ophthalmol 2010;248:243-248. Simavli H, Bucak YY, Tosun M, Erdurmuş M. Serum uric acid, alanine aminotransferase, hemoglobin and red blood cell count levels in pseudoexfoliation syndrome. Journal of Ophthalmology 2015;2015. Li S, Shao M, Tang B, Zhang A, Cao W, Sun X. The association between serum uric acid and glaucoma severity in primary angle closure glaucoma: a retrospective case-control study. Oncotarget 2017;8:2816-2824. Li S, Shao M, Li D, Tang B, Cao W, Sun X. Association of serum uric acid levels with primary open-angle glaucoma: a 5-year case-control study. Acta Ophthalmol 2019;97:e356-e363. Al-Daghri NM, Al-Attas OS, Wani K, Sabico S, Alokail MS. Serum Uric Acid to Creatinine Ratio and Risk of Metabolic Syndrome in Saudi Type 2 Diabetic Patients. Sci Rep 2017;7:12104. Tao J, Shen X, Li J, et al. Serum uric acid to creatinine ratio and metabolic syndrome in postmenopausal Chinese women. Medicine (Baltimore) 2020;99:e19959. Gu L, Huang L, Wu H, Lou Q, Bian R. Serum uric acid to creatinine ratio: A predictor of incident chronic kidney disease in type 2 diabetes mellitus patients with preserved kidney function. Diab Vasc Dis Res 2017;14:221-225. Silva NR, Gonçalves CET, Gonçalves DLN, Cotta RMM, da Silva LS. Association of uric acid and uric acid to creatinine ratio with chronic kidney disease in hypertensive patients. BMC Nephrology 2021;22:311. Wensor MD, McCarty CA, Stanislavsky YL, Livingston PM, Taylor HR. The prevalence of glaucoma in the Melbourne Visual Impairment Project. Ophthalmology 1998;105:733-739. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5661349","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":447526001,"identity":"79690f1b-cede-450e-a0a5-96e76aa40e57","order_by":0,"name":"Eunoo Bak","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Eunoo","middleName":"","lastName":"Bak","suffix":""},{"id":447526002,"identity":"9ab563bf-81fb-4d02-a940-32e8becfbd7c","order_by":1,"name":"Jin-Soo Kim","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jin-Soo","middleName":"","lastName":"Kim","suffix":""},{"id":447526003,"identity":"f03b6208-5c94-4c9f-8a1c-3432bc654f9d","order_by":2,"name":"Dae Joong Ma","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Dae","middleName":"Joong","lastName":"Ma","suffix":""},{"id":447526004,"identity":"4df96920-4f5d-4f04-8c20-ade8d88f3713","order_by":3,"name":"Jinho Lee","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jinho","middleName":"","lastName":"Lee","suffix":""},{"id":447526005,"identity":"0885c28b-7189-4fa6-ba54-53661199b63d","order_by":4,"name":"Baek Lok Oh","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Baek","middleName":"Lok","lastName":"Oh","suffix":""},{"id":447526006,"identity":"83e8f573-60e8-4236-9357-330dca733197","order_by":5,"name":"Ahnul Ha","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ahnul","middleName":"","lastName":"Ha","suffix":""},{"id":447526007,"identity":"a1fb6d0f-5af7-4c4a-a67e-98af0c1e2dac","order_by":6,"name":"Hyuk Jin Choi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDCCAwwMzAwMEnIGYJ6BBfFajKFaJBjAfCK0MCRugHCJ0MJ3vPnh54IKi/Tt7GePbvhRIMFgzt5/AK8WyTPHjKVnnJHI3dmTl3azB+gwy57D+G0xuJHDxszbJpG74UCO2Q0eoBaDG8nEaUk3OP/G7OYfkJb7j4nTkgBkmN2G2ELA+2C/8JyRMNxw443ZbRkDCR6DM8kGeLWAQ4ynok7e4HyO2c03f2zkDI4ffIDfGnTAQ5ryUTAKRsEoGAVYAQCx0kOuF9wXCAAAAABJRU5ErkJggg==","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Hyuk","middleName":"Jin","lastName":"Choi","suffix":""}],"badges":[],"createdAt":"2024-12-17 11:38:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5661349/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5661349/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-03939-z","type":"published","date":"2025-07-17T16:05:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82065593,"identity":"ac4ec3d0-a66d-4af5-b03c-66fe58aeb78f","added_by":"auto","created_at":"2025-05-06 12:34:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":216466,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the study population\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5661349/v1/aea9a90c26241b168a0f6d2c.png"},{"id":88506029,"identity":"fad3eed9-6ba8-4423-9a2d-cf31b4370e75","added_by":"auto","created_at":"2025-08-07 07:29:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1618771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5661349/v1/3a89a5d1-4898-48b4-8f0a-e47e98035171.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiology and risk factors of glaucoma in a comprehensive health screening baseline report from the Gangnam Eye Cohort Study ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlaucoma is the leading cause of irreversible blindness and affects over 70\u0026nbsp;million individuals worldwide.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Previous large-scale epidemiology studies have revealed the prevalence of glaucoma; primary open-angle glaucoma and primary angle-closure glaucoma, to be 0.5\u0026ndash;8.8%.\u003csup\u003e3\u0026ndash;5\u003c/sup\u003e The prevalence of glaucoma in the Republic of Korea has been documented in a few population-based studies. The Namil study estimated the prevalence of glaucoma to be 3.5%,\u003csup\u003e6\u003c/sup\u003e and it was 4.7% in the Korea National Health and Nutrition Examination Survey (KNHANES).\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eResearchers have also attempted to identify risk factors for glaucoma.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Identified risk factors include older age,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e non-white race,\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e family history of glaucoma,\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e elevated intraocular pressure (IOP),\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and several systemic risk factors, such as diabetes mellitus (DM),\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e low blood pressure,\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e metabolic syndrome,\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e arterial stiffness,\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e and chronic kidney disease (CKD).\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Unlike Western countries, most Asian nations have reported a higher prevalence of glaucoma with an IOP of 21 mmHg or lower.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Therefore, this population provides a good opportunity to investigate risk factors for glaucoma besides IOP. Consistently, the Namil study revealed age and history of thyroid disease as glaucoma risk factors,\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e while the KNHANES identified older age, male sex, myopia, hypertension (HTN), and non-overweight status as glaucoma risk factors.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRecently, health screening centers that provide comprehensive health check-up programs have become popular. They reflect the paradigm shift of medical care toward disease prevention and early diagnosis, which plays a significant role in national healthcare system. In fact, early detection of glaucoma has increased in the Republic of Korea since health check-up programs with screening fundus photography became commonplace. In parallel, participants undergo health interview surveys, anthropometry, physical examinations, various blood tests, and imaging studies. Therefore, in addition to population-based studies, large-scale health screening center-based scientific data could provide physicians with new insights for diagnosing and analyzing the risk factors of major ocular diseases, such as glaucoma. In the same context, we established a large healthcare center-based retrospective ophthalmic cohort, the Gangnam Eye Cohort, composed of consecutive subjects who visited Seoul National University Hospital (SNUH) Healthcare System Gangnam Center (HSGC) from the opening in October 2003. The primary goal of this ongoing cohort study is to investigate incidences and risk factors of major ophthalmic diseases causing visual loss such as age-related macular degeneration, glaucoma, and diabetic retinopathy based on minimum 10-year follow-up examinations. Meanwhile, it is meaningful to share baseline characteristics and statistical analysis data to understand the cohort and verify the feasibility of follow-up studies.\u003c/p\u003e \u003cp\u003eAccordingly, the purpose of this study was to investigate glaucoma epidemiology and risk factors using baseline data of the Gangnam Eye Cohort, a health screening center-based cohort. To the best of our knowledge, this is the first study to report such data with comprehensive biometric screening in the Korean population 18 years of age or older using 8 years of data.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eThe present study was based on the Gangnam Eye Cohort Study, an ongoing health screening center-based retrospective ophthalmic cohort survey conducted at SNUH HSGC which is one of the largest and leading health screening facilities in the Republic of Korea. The SNUH HSGC health screening system is an active follow-up mass screening system that allows participants to voluntarily visit the center, usually at a one-year follow-up interval, for repeated measurement and assessment of their overall health status. Other detailed information about the general cohort recruited through SNUH HSGC has been published elsewhere.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study, we used baseline data of the Gangnam Eye Cohort. The study population comprises Korean subjects aged 18 years or older who participated in a health screening program at SNUH HSGC between October 2003 and December 2010.\u003c/p\u003e \u003cp\u003eThis study was approved by the SNUH Institutional Review Board (IRB No. H-1906-141-1043). All of the procedures adhered to the tenets of the Declaration of Helsinki. Written informed consent to participate was obtained from all of the participants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComprehensive Health Screening Examinations and Definition of Variables\u003c/h3\u003e\n\u003cp\u003eThe health screening examination consisted of 2 parts: (1) the health interview survey and (2) the health examination survey, including a comprehensive ophthalmologic examination. The details of these examinations have been described elsewhere.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe health interview survey included standardized questionnaires on demographic variables and current and past medical conditions (e.g., DM, HTN, dyslipidemia, coronary heart disease, cerebral stroke, cancer), health-influencing behaviors (e.g., smoking status, drinking status), and socioeconomic status (e.g., household income, education). Regarding age, participants were divided into 6 age groups: younger than 40, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 years or older. Smoking status was categorized as never smoker, former smoker, and current smoker. Drinking status was categorized as never drinker, former drinker, and current drinker. Household income status was categorized as more than 50% of the household income and 50% of the household income or less of the average household income of Koreans. Regarding education status, participants were divided on the basis of whether they had at least a college degree and or had not graduated from college or lower-level schooling.\u003c/p\u003e \u003cp\u003eThe health examination survey included anthropometric measurements. Height, weight, waist circumference (WC), and blood pressure were measured by trained nurses. body mass index (BMI) was calculated as the ratio of weight (in kilograms) divided by square height (in meters). Subjects were categorized into 2 groups according to BMI: BMI less than 25 kg/m\u003csup\u003e2\u003c/sup\u003e and BMI of 25 kg/m\u003csup\u003e2\u003c/sup\u003e or more. Participants were divided into 2 groups by WC: WC\u0026thinsp;\u0026lt;\u0026thinsp;90 cm for men and \u0026lt;\u0026thinsp;85 cm for women and WC\u0026thinsp;\u0026ge;\u0026thinsp;90 cm for men and \u0026ge;\u0026thinsp;85 cm for women. Metabolic syndrome was defined based on criteria described elsewhere.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe ophthalmologic screening examination included measurement of visual acuity by Snellen chart, IOP measurement by noncontact tonometer (CT-80; Topcon Inc., Tokyo, Japan), and nonmydriatic fundus photography with a 45\u0026deg; field angle digital fundus camera (CR6-45NW; Canon Inc., Tokyo, Japan) in a dark room. Retinal arteriosclerosis grade (from 0 to 4) was determined using Scheie\u0026rsquo;s classification system with a slight modification to infer the ischemic status of the retina. Positive signs included diffuse arteriolar narrowing, arteriovenous compression, focal constriction or copper/silver-wire appearance.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e In the present study, grades 0 and 1 were defined as normal, and grade 2 or more was considered to indicate significant arteriosclerosis. Individuals were excluded if they had poor-quality photo interference with visualization of the fundus, pathologic myopia obscuring visualization of the retinal nerve fiber layer (RNFL),\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e or non-glaucomatous abnormal optic disc.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe blood tests included total calcium, inorganic phosphorus, blood urea nitrogen (BUN), creatinine, aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), total bilirubin, direct bilirubin, uric acid, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglyceride (TG), total protein, albumin, high-sensitivity C reactive protein (Hs-CRP), complete blood cell count (red blood cell, white blood cell, hematocrit[Hct]), fasting blood glucose, glycated hemoglobin (hemoglobin[Hb] A1c), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), hepatitis B surface antigen (HBsAg), hepatitis C antibody (Anti-HCV) and Helicobacter pylori antibody (Anti-HP). The laboratory medicine department at the SNUH is certified by the Korean Society of Laboratory Medicine and participated in the College of American Pathologist\u0026rsquo;s Survey/Proficiency Testing program.\u003c/p\u003e\n\u003ch3\u003eDiagnosis of Glaucoma\u003c/h3\u003e\n\u003cp\u003eThree discrete glaucoma reading committees were established, each comprising glaucoma specialists from different institutes to whom other information on the eyes was not revealed, and these specialists evaluated the fundus photographs. The vertical cup-to-disc ratio and rim width were measured on the disc photographs by a glaucoma specialist (EB). Each photograph was evaluated independently by the other 3 examiners to confirm the measurements by the glaucoma specialist (EB) and to detect RNFL defects. A RNFL defect was considered suggestive of glaucoma when its width at the disc edge was larger than a major retinal vessel, diverging in an arcuate or wedge shape.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e If the decisions of all 3 examiners did not agree, a consensus was obtained by discussion, referring to the fundus color photographs.\u003c/p\u003e \u003cp\u003eThe criteria for glaucoma diagnosis, which was classified into normal, glaucoma suspect, and glaucoma, were based on the criteria outlined in the previous studies, including the International Society of Geographical and Epidemiological Ophthalmology criteria and other well-designed studies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003csup\u003e\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Only eyes classified as (1) normal and (2) glaucoma were included for further analysis; glaucoma suspect cases were excluded from the present study. If there were any signs of glaucoma in one eye, the patient was classified in the glaucoma group.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Glaucoma Diagnostic Criteria of this Study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) nonglaucomatous optic disc appearance\u003c/p\u003e \u003cp\u003eand (2) absence of optic disc hemorrhage or RNFL defect\u003c/p\u003e \u003cp\u003eand (3) optic disc not violating the neuroretinal rim thickness order\u003c/p\u003e \u003cp\u003eof inferior\u0026thinsp;\u0026gt;\u0026thinsp;superior\u0026thinsp;\u0026gt;\u0026thinsp;nasal\u0026thinsp;\u0026gt;\u0026thinsp;temporal rule\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlaucoma suspect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) vertical cup-to-disc ratio\u0026thinsp;\u0026ge;\u0026thinsp;0.7 without RNFL defect\u003c/p\u003e \u003cp\u003eor (2) rim width\u0026thinsp;\u0026le;\u0026thinsp;0.1 of the disc diameter without RNFL defect\u003c/p\u003e \u003cp\u003eor (3) presence of optic disc hemorrhage without RNFL defect\u003c/p\u003e \u003cp\u003eor (4) a RNFL defect without glaucomatous optic disc change\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlaucoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1) vertical cup-to-disc ratio\u0026thinsp;\u0026ge;\u0026thinsp;0.9\u003c/p\u003e \u003cp\u003eor (2) rim width\u0026thinsp;\u0026le;\u0026thinsp;0.05 of the disc diameter\u003c/p\u003e \u003cp\u003eor (3) presence of RNFL defect compatible with optic disc appearance\u003c/p\u003e \u003cp\u003eor (4) presence of optic disc hemorrhage corresponding to RNFL defect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eRNFL\u0026thinsp;=\u0026thinsp;retinal nerve fiber layer\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed with the Statistical Package for Social Sciences (SPSS) version 23.0 for Windows (SPSS, Inc., Chicago, IL) and SAS software version 9.4 (SAS Inc, Cary, NC). A \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. In cases where both eyes were eligible, one eye was chosen at random using the random sample option in SPSS, and the ophthalmic examination test of that eye was used for further analysis. The demographic characteristics were compared using Student\u0026rsquo;s t test for continuous variables and the chi-square test for categorical variables. The risk factors for glaucoma were investigated by univariate logistic regression analysis. Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.10 were selected as candidates for the subsequent multivariate analysis by the stepwise selection method. Multivariable regression analyses were performed after correction for multiple testing using Benjamini\u0026ndash;Hochberg procedure. Multicollinearity was detected by using the variance inflation factor (VIF) in a regression model. VIF above 10 which indicate variable correlation were evaluated. Variables correlated significantly with each other were not analyzed simultaneously to avoid multicollinearity. Instead, the variable with the highest significance among correlated variables was chosen. Odds ratios with 95% CI values were calculated in all the regression analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and Clinical Characteristics\u003c/h2\u003e \u003cp\u003eA total of 76,030 subjects (40,463 males) visited SNUH HSBC and underwent comprehensive health screening examinations from October 2003 to December 2010. After the exclusion of 496 non-Korean subjects, 75,534 Korean subjects (40,132 males) were enrolled in the Gangnam Eye Cohort Study. Among them, 380 subjects were excluded for reasons including poor photographic image quality (n\u0026thinsp;=\u0026thinsp;79), concomitant pathological myopia (n\u0026thinsp;=\u0026thinsp;204), and concomitant binocular disc morphological abnormalities (n\u0026thinsp;=\u0026thinsp;97).\u003c/p\u003e \u003cp\u003eOf the 75,154 eligible subjects with a qualifying fundus photograph for at least 1 eye, 67,683 were normal subjects (control group), 5,378 were glaucoma suspect, and 2,093 were glaucoma (unilateral 1,455 and bilateral 638) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age was 48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4 years (range, 18\u0026ndash;93 years), and mean IOP was 13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 mmHg (range, 6\u0026ndash;35 mmHg). Patients with glaucoma were significantly older (52.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 years) and had a significantly higher IOP (14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mmHg) than the individuals in the control group (48.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3 years and 13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 mmHg, respectively; all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrevalence of Glaucoma\u003c/h3\u003e\n\u003cp\u003eThe overall prevalence of glaucoma was estimated to be 2.8% (n\u0026thinsp;=\u0026thinsp;2093, 95% CI, 2.6\u0026ndash;3.2), and that of glaucoma with an IOP of 21 mmHg or less was 2.7% (n\u0026thinsp;=\u0026thinsp;2046, 95% CI, 2.5\u0026ndash;3.1). Unilateral glaucoma was observed in 1,464 of 2,093 subjects (69.9%). The prevalence of glaucoma in men (3.4%) was higher than that in women (2.1%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The glaucoma prevalence for the different age groups, younger than 40, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 years or older, was 1.5%, 2.3%, 3.2%, 4.5%, 6.2%, and 13.2%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e); thus, glaucoma prevalence increased significantly with age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Meanwhile, the prevalence of glaucoma suspect was estimated to be 7.2% (n\u0026thinsp;=\u0026thinsp;5,378, 95% CI, 6.9\u0026ndash;7.6). Eyes in the (1) normal group and (2) glaucoma group were included for further analysis, and glaucoma suspects were excluded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAge-specific Prevalence of Glaucoma\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group, y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMale Subjects\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eFemale Subjects\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCohort population\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eGlaucoma cases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCohort population\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eGlaucoma cases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCohort population\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eGlaucoma cases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eRisk Factors for Glaucoma\u003c/h3\u003e\n\u003cp\u003eThe characteristics compared between participants with and without glaucoma and associated risk factors with univariate analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Variables with VIF above 10 were total cholesterol (VIF 43.003) and LDL cholesterol (VIF 31.768). The variables with a \u003cem\u003eP\u003c/em\u003e value less than 0.10 were subsequently included in the multivariate analysis. In the multivariate analysis, the prevalence of glaucoma was positively associated with older age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), male sex (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher household income (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045), higher education (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), overweight status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), higher IOP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of retinal arteriosclerosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher serum creatinine (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013) and uric acid (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Characteristics between Participants with and without Glaucoma and Associated Risk Factors Using Univariate Logistic Regression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;67,683)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGlaucoma\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,093)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eUnivariable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;40 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15726 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e254 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23232 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e576 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.323\u0026ndash;1.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18674 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e684 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.961\u0026ndash;2.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8293 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e436 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.782\u0026ndash;3.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1617 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.676\u0026ndash;5.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.389\u0026ndash;15.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32420 (47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e724 (34.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35263 (52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1369 (65.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.587\u0026ndash;1.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical condition, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6362 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e311 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.489\u0026ndash;1.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16116 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e763 (36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.680\u0026ndash;2.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15777 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e491 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.911\u0026ndash;1.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2273 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.367\u0026ndash;2.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15086 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e602 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.280\u0026ndash;1.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebral stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e289 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.084\u0026ndash;2.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1168 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u0026ndash;1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35294 (52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e949 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15803 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e638 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.356\u0026ndash;1.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14186 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e431 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.007\u0026ndash;1.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinking status, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18869 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e528 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2019 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.023\u0026ndash;1.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.033*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43985 (65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1401 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.028\u0026ndash;1.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Income, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23590 (34.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e683 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38310 (56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1243 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.019\u0026ndash;1.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.018*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; College (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21781 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e627 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44498 (65.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1416 (67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.005\u0026ndash;1.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.039*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometric\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m2), n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48145 (71.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1438 (68.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19273 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e643 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.016\u0026ndash;1.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWC (cm), n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49250 (72.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1462 (69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18144 (26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e618 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.043\u0026ndash;1.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood Pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e117.1\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.013\u0026ndash;1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.014\u0026ndash;1.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOcular characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIOP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.191\u0026ndash;1.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRetinal arteriosclerosis, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65231 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1730(82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2452 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e363 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.950\u0026ndash;6.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood tests\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.633\u0026ndash;2.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.849\u0026ndash;1.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.632\u0026ndash;1.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.198\u0026ndash;5.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.066\u0026ndash;1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.043\u0026ndash;1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;22.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.623\u0026ndash;0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.2\u0026thinsp;\u0026plusmn;\u0026thinsp;41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.071\u0026ndash;1.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.955\u0026ndash;1.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect bilirubin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.044\u0026ndash;3.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.287\u0026ndash;1.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195.3\u0026thinsp;\u0026plusmn;\u0026thinsp;34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e196.3\u0026thinsp;\u0026plusmn;\u0026thinsp;34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.975\u0026ndash;1.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119.7\u0026thinsp;\u0026plusmn;\u0026thinsp;32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121.3\u0026thinsp;\u0026plusmn;\u0026thinsp;32.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.038\u0026ndash;1.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.123\u0026ndash;1.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114.0\u0026thinsp;\u0026plusmn;\u0026thinsp;77.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e119.7\u0026thinsp;\u0026plusmn;\u0026thinsp;69.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.098\u0026ndash;1.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.748\u0026ndash;1.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.379-3.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.990\u0026ndash;1.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.867\u0026ndash;1.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.755\u0026ndash;1.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.735\u0026ndash;0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting blood glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98.0\u0026thinsp;\u0026plusmn;\u0026thinsp;19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101.8\u0026thinsp;\u0026plusmn;\u0026thinsp;24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.262\u0026ndash;1.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.198\u0026ndash;1.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApoA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123.2\u0026thinsp;\u0026plusmn;\u0026thinsp;22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.988\u0026ndash;1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApoB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95.3\u0026thinsp;\u0026plusmn;\u0026thinsp;22.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.6\u0026thinsp;\u0026plusmn;\u0026thinsp;22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.979\u0026ndash;1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBsAg, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3032 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.794\u0026ndash;1.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-HCV, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e721 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.937\u0026ndash;1.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-HP, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33919 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1045 (0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.893\u0026ndash;1.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eData are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Significant values with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are indicated by asterisk.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCI\u0026thinsp;=\u0026thinsp;confidence interval; DM\u0026thinsp;=\u0026thinsp;diabetes mellitus; HTN\u0026thinsp;=\u0026thinsp;hypertension; BMI\u0026thinsp;=\u0026thinsp;Body mass index; WC\u0026thinsp;=\u0026thinsp;waist circumference; IOP\u0026thinsp;=\u0026thinsp;intraocular pressure; Ca\u0026thinsp;=\u0026thinsp;calcium; P\u0026thinsp;=\u0026thinsp;phosphorus; BUN\u0026thinsp;=\u0026thinsp;blood urea nitrogen; AST\u0026thinsp;=\u0026thinsp;aspartate transaminase; ALT\u0026thinsp;=\u0026thinsp;alanine transaminase; ALP\u0026thinsp;=\u0026thinsp;alkaline phosphatase; GGT\u0026thinsp;=\u0026thinsp;gamma-glutamyl transferase; LDL\u0026thinsp;=\u0026thinsp;low-density lipoprotein; HDL\u0026thinsp;=\u0026thinsp;high-density lipoprotein; TG\u0026thinsp;=\u0026thinsp;triglyceride; Hs-CRP\u0026thinsp;=\u0026thinsp;high-sensitivity C reactive protein; RBC\u0026thinsp;=\u0026thinsp;red blood cell; WBC\u0026thinsp;=\u0026thinsp;white blood cell; Hct\u0026thinsp;=\u0026thinsp;hematocrit; HbA1c\u0026thinsp;=\u0026thinsp;hemoglobin A1c; ApoA1\u0026thinsp;=\u0026thinsp;apolipoprotein A1; ApoB\u0026thinsp;=\u0026thinsp;apolipoprotein B; HBsAg\u0026thinsp;=\u0026thinsp;hepatitis B surface antigen; Anti-HCV\u0026thinsp;=\u0026thinsp;hepatitis C antibody; Anti-HP\u0026thinsp;=\u0026thinsp;Helicobacter pylori antibody\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificant Risk Factors Associated with Glaucoma by Multivariate Logistic Regression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;40 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.177\u0026ndash;1.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.772\u0026ndash;2.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.322\u0026ndash;3.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.277\u0026ndash;5.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.758\u0026ndash;18.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.325\u0026ndash;1.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Income (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.188\u0026ndash;1.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; College (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.131\u0026ndash;1.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometric\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25 (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.120\u0026ndash;1.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOcular characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRetinal arteriosclerosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent (reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.904\u0026ndash;5.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIOP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.188\u0026ndash;1.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood tests\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.157\u0026ndash;3.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUric acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.068\u0026ndash;1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCI\u0026thinsp;=\u0026thinsp;confidence interval; BMI\u0026thinsp;=\u0026thinsp;Body mass index; IOP\u0026thinsp;=\u0026thinsp;intraocular pressure\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Significant after Benjamini-Hochberg procedure.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this health screening center-based Gangnam Eye Cohort Study, the prevalence of glaucoma was 2.8% which was higher in men and in those of older age. More importantly, the present study revealed that older age, male sex, higher IOP, presence of retinal arteriosclerosis, higher household income, higher education, overweight status, higher serum creatinine and uric acid were independent risk factors for glaucoma.\u003c/p\u003e \u003cp\u003eOlder age and high IOP are reported as risk factors for glaucoma worldwide and in population-based studies of Asians.\u003csup\u003e\u003cspan additionalcitationids=\"CR36 CR37 CR38 CR39\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e This study also identified age-related increases in glaucoma prevalence and IOP as risk factors for glaucoma. Approximately 98% of our glaucoma patients had an IOP of 21 mmHg or less (14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 mmHg; range, 6\u0026ndash;21 mmHg). However, the mean IOP of the glaucoma patients (14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mmHg; range, 6\u0026ndash;35 mmHg) was significantly higher than that of the control group (13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 mmHg; range, 6\u0026ndash;21 mmHg). Baseline elevated IOP increased the risk for incident glaucoma by 1.12 for each 1-mmHg increase in the present study. These results indicate that high IOP can play an important role even in patients with an IOP in the normal range.\u003c/p\u003e \u003cp\u003eThe association between glaucoma and gender has generated inconsistent results across studies. Several studies have reported contradictory findings, while numerous epidemiologic studies worldwide have reported that men are more likely to have glaucoma than women.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Likewise, we found that the prevalence of glaucoma was 3.4% in men vs. 2.1% in women, and the risk was 1.5 times higher in men than in women. Interestingly, the odds ratio was almost the same as that of the KNHANES, the largest population-based study involving the same ethnic group.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The low prevalence of glaucoma in women has been explained by the protective roles of endogenous estrogen,\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e exogenous hormone use after menopause,\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and genetic variability.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHigher levels of education and income were associated with glaucoma in the current study. While previous studies have revealed that lower socioeconomic status is associated with a higher risk of glaucoma,\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e others have indicated that those with higher socioeconomic status are more aware of their own diseases and are more likely to have access to healthcare providers.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e The accessibility of medical services affects the detection of glaucoma, which is influenced by socioeconomic status.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eArteriosclerosis is a systemic condition affecting arteries of all sizes, including small ocular arteries.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e It may result in alteration in circulatory hemodynamics and disruption of ocular autoregulation, thus relating glaucoma development or aggravation. Population-based studies reported retinal arteriolar narrowing associated with glaucoma, while population-based data on the relationship between arteriosclerosis and glaucoma are scarce and inconclusive.\u003csup\u003e\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e More than retinal arteriolar narrowing, the Gangnam Eye Cohort Study is the first health screening center-based study to investigate the association between glaucoma and retinal arteriosclerosis ; which includes retinal arteriolar narrowing, arteriovenous compression, focal constriction, and copper/silver-wire appearance. Retinal arteriosclerosis was present in 17.3% of glaucoma patients vs. 3.5% of normal control patients, and it increased the risk of glaucoma by approximately 4.5-fold. This adds further information to previous population-based studies and supports the \u0026ldquo;vascular theory\u0026rdquo; of glaucoma.\u003csup\u003e\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Additionally, obesity and high BMI are associated with an increased risk for both elevated IOP\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e and vascular dysregulation, such as arteriosclerosis.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e In our study, overweight participants had a higher risk for glaucoma. Newman-Casey et al. reported an increased glaucoma hazard associated with obesity, although its association with glaucoma remains under debate.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOne of the most distinct variables associated with glaucoma in this study was high serum uric acid. Uric acid plays an important role in the pathophysiology of CKD and is one of the main ocular antioxidative small molecules.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e While being a potent antioxidant in the extracellular environment, uric acid is a pro-oxidant inside the cell where it can induce mitochondrial dysfunction.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e An imbalance between oxidative stress and antioxidant defense contributes to the pathogenesis of various ocular diseases, including glaucoma.\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e In previous studies on serum uric acid levels and different subtypes of glaucoma, there was no consistent direction of the effect.\u003csup\u003e\u003cspan additionalcitationids=\"CR65 CR66 CR67\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e Opposite mechanisms could lead to variable outcomes. First, uric acid being a marker of CKD, a presumed harmful process. Second, low uric acid levels have been associated with neurodegenerative disease, possibly via the fact that uric acid has a strong antioxidant capacity. Other possible explanations for this inconsistency are differences in ethnicity or differences in confounding factors. Additionally, in this study, high creatinine was associated with glaucoma. Recent studies have shown that the serum uric acid to creatinine ratio is a good biomarker for detecting the pathogenesis of metabolic syndrome and CKD.\u003csup\u003e\u003cspan additionalcitationids=\"CR70 CR71\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e Therefore, these antioxidants may serve as biomarkers for predictive diagnostics and therapeutic targets for glaucoma.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, this study was based on a health screening center located in Seoul, the capital of the Republic of Korea. Selection bias may have contributed to data collection making it less representative of the Korean population. Second, approximately 98% of glaucoma participants had an IOP of 21 mmHg or lower; therefore, our findings may be more relevant to glaucoma patients with normal baseline IOP. However, previously diagnosed ocular disease, such as glaucoma, was not included in the initial health interview survey. Possible use of IOP lowering medications or previous surgery of glaucoma may affect IOP and should be interpreted cautiously. Third, we did not perform visual field testing on all subjects because the cohort was based on a healthcare screening program. The glaucoma grading scheme required a glaucomatous optic disc with a RNFL defect to be classified as glaucoma. This approach streamlined the logistics of examining the cohort, but it is possible that some subjects with subtle optic nerve changes were missed. Fourth, angle examination with gonioscopy was not performed; therefore, we could not disaggregate the subtype of glaucoma (i.e., primary open-angle vs. primary angle-closure). Despite this fact, previous reports suggest that the rate of primary angle-closure glaucoma is negligible (0.1%).\u003csup\u003e73\u003c/sup\u003e Further studies including gonioscopy should be conducted.\u003c/p\u003e \u003cp\u003eThis study has several strengths. First, to the best of our knowledge, this is the largest health screening center-based study that determined the prevalence of glaucoma and associated risk factors. Additionally, the present study is the first report to include young adults under age 40, with a glaucoma prevalence of 1.5%. This highlights the importance of health screening even in young adults, which leads to early detection required to cope with the growing burden of glaucoma. Additionally, we included comprehensive biometric screenings and revealed risk factors for glaucoma: high BMI, high serum uric acid and creatinine levels. Correction of antioxidant conditions may be recommended, taking into account the harmful associations of overweight status. Our findings also imply a possible different pathophysiologic course of glaucoma with normal IOP. Despite the potential limitations that the present study may have, we believe that this study may serve as a reference for public health policy and planning.\u003c/p\u003e \u003cp\u003eIn conclusion, the prevalence of glaucoma in the health screening center-based Gangnam Eye Cohort Study was 2.8%. Older age, male sex, high IOP, retinal arteriosclerosis, overweight status, and high serum uric acid and creatinine were independent risk factors for glaucoma. Considering the associations of glaucoma with retinal microvascular abnormalities, obesity, and serum uric acid, a common pathway such as arteriosclerosis or oxidative stress may be the vascular problem underlying glaucoma.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEB and HJC performed the study design.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEB and HJC helped in writing the article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData collection was done by EB, JSK, DJM, JL, BLO, AH, HJC.\u003c/p\u003e\n\u003cp\u003eAnalysis and interpretation of the data were done by EB and HJC.\u003c/p\u003e\n\u003cp\u003eEB, DJM, HJC helped in literature search.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEB and HJC helped in critical revision of the article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHJC gave the final approval of the article.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial Support:\u0026nbsp;\u003c/strong\u003eThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2024-00342696). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eQuigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. \u003cem\u003eBritish Journal of Ophthalmology\u003c/em\u003e 2006;90:262.\u003c/li\u003e\n\u003cli\u003eWeinreb RN, Aung T, Medeiros FA. The Pathophysiology and Treatment of Glaucoma: A Review. \u003cem\u003eJAMA\u003c/em\u003e 2014;311:1901-1911.\u003c/li\u003e\n\u003cli\u003eFoster PJ, Baasanhu J, Alsbirk PH, Munkhbayar D, Uranchimeg D, Johnson GJ. Glaucoma in Mongolia: A Population-Based Survey in H\u0026ouml;vsg\u0026ouml;l Province, Northern Mongolia. \u003cem\u003eArchives of Ophthalmology\u003c/em\u003e 1996;114:1235-1241.\u003c/li\u003e\n\u003cli\u003eMason RP, Kosoko O, Wilson MR, et al. 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Serum uric acid, alanine aminotransferase, hemoglobin and red blood cell count levels in pseudoexfoliation syndrome. \u003cem\u003eJournal of Ophthalmology\u003c/em\u003e 2015;2015.\u003c/li\u003e\n\u003cli\u003eLi S, Shao M, Tang B, Zhang A, Cao W, Sun X. The association between serum uric acid and glaucoma severity in primary angle closure glaucoma: a retrospective case-control study. \u003cem\u003eOncotarget\u003c/em\u003e 2017;8:2816-2824.\u003c/li\u003e\n\u003cli\u003eLi S, Shao M, Li D, Tang B, Cao W, Sun X. Association of serum uric acid levels with primary open-angle glaucoma: a 5-year case-control study. \u003cem\u003eActa Ophthalmol\u003c/em\u003e 2019;97:e356-e363.\u003c/li\u003e\n\u003cli\u003eAl-Daghri NM, Al-Attas OS, Wani K, Sabico S, Alokail MS. Serum Uric Acid to Creatinine Ratio and Risk of Metabolic Syndrome in Saudi Type 2 Diabetic Patients. \u003cem\u003eSci Rep\u003c/em\u003e 2017;7:12104.\u003c/li\u003e\n\u003cli\u003eTao J, Shen X, Li J, et al. Serum uric acid to creatinine ratio and metabolic syndrome in postmenopausal Chinese women. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e 2020;99:e19959.\u003c/li\u003e\n\u003cli\u003eGu L, Huang L, Wu H, Lou Q, Bian R. Serum uric acid to creatinine ratio: A predictor of incident chronic kidney disease in type 2 diabetes mellitus patients with preserved kidney function. \u003cem\u003eDiab Vasc Dis Res\u003c/em\u003e 2017;14:221-225.\u003c/li\u003e\n\u003cli\u003eSilva NR, Gon\u0026ccedil;alves CET, Gon\u0026ccedil;alves DLN, Cotta RMM, da Silva LS. Association of uric acid and uric acid to creatinine ratio with chronic kidney disease in hypertensive patients. \u003cem\u003eBMC Nephrology\u003c/em\u003e 2021;22:311.\u003c/li\u003e\n\u003cli\u003eWensor MD, McCarty CA, Stanislavsky YL, Livingston PM, Taylor HR. The prevalence of glaucoma in the Melbourne Visual Impairment Project. \u003cem\u003eOphthalmology\u003c/em\u003e 1998;105:733-739.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"comprehensive health screening, epidemiology, risk factor, glaucoma","lastPublishedDoi":"10.21203/rs.3.rs-5661349/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5661349/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe investigated the epidemiology and systemic risk factors of glaucoma in a health screening center-based cohort. The Gangnam Eye Cohort Study included 75,154 participants who completed initial comprehensive health check-up examinations in 2003\u0026ndash;2010. In this baseline report, the prevalence of glaucoma was estimated, ocular and systemic factors were compared between glaucoma and normal control groups, and risk factors were analyzed by logistic regression. The prevalence of glaucoma was 2.8%; 3.4% in men and 2.1% in women, and increased with age (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mean age of the glaucoma group (52.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 years) was older than that of the normal group (48.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3 years, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mean intraocular pressure (IOP) of the glaucoma group (14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 mmHg) was higher than that of the normal group (13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 mmHg, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Older age (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), male sex (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of retinal arteriosclerosis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher IOP (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher household income (P\u0026thinsp;=\u0026thinsp;0.045), higher education (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), overweight status (P\u0026thinsp;=\u0026thinsp;0.001), higher serum creatinine (P\u0026thinsp;=\u0026thinsp;0.013) and uric acid (P\u0026thinsp;=\u0026thinsp;0.008) were significantly associated with glaucoma. In this largest health screening center-based cohort study, considering the associations of glaucoma with retinal microvascular abnormality, obesity, and serum creatinine and uric acid, a common pathway such as arteriosclerosis or oxidative stress may be the vascular problem underlying glaucoma.\u003c/p\u003e","manuscriptTitle":"Epidemiology and risk factors of glaucoma in a comprehensive health screening baseline report from the Gangnam Eye Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 12:26:55","doi":"10.21203/rs.3.rs-5661349/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-02T07:06:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-01T08:58:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-26T16:41:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121669208113698060329951388272420674800","date":"2025-04-26T06:09:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258656926715383586792271693890083805370","date":"2025-04-24T14:03:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-24T09:37:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-23T05:44:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-21T03:50:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3064e4f8-87ee-4792-bccb-5ccb2a46723b","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47635419,"name":"Health sciences/Health care"},{"id":47635420,"name":"Health sciences/Medical research"},{"id":47635421,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-08-07T07:11:32+00:00","versionOfRecord":{"articleIdentity":"rs-5661349","link":"https://doi.org/10.1038/s41598-025-03939-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-17 16:05:10","publishedOnDateReadable":"July 17th, 2025"},"versionCreatedAt":"2025-05-06 12:26:55","video":"","vorDoi":"10.1038/s41598-025-03939-z","vorDoiUrl":"https://doi.org/10.1038/s41598-025-03939-z","workflowStages":[]},"version":"v1","identity":"rs-5661349","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5661349","identity":"rs-5661349","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}