Association of blood glucose levels with ocular diseases in the middle-aged and elderly population: results from the NHANES 2005-2008

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Methods The National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2008 were used for this study. The correlation between blood glucose and risk of ocular disease was examined using weighted multivariate logistic regression analysis, restricted cubic spline curve (RCS) plots, and subgroup analysis. The XGBoost algorithm was further used to rank the importance of the influencing factors. Results In the unadjusted model, higher blood glucose levels were significantly associated with an increased risk of DR (OR = 8.189, 95% CI: 2.687–24.96, p = 0.001), cataracts (OR = 2.134, 95% CI: 1.304–3.492, p = 0.005), and glaucoma (OR = 2.734, 95% CI: 1.588–4.708, p = 0.001). RCS analysis further revealed that the risk of DR and glaucoma increased when blood glucose levels exceeded 104.63 mg/dL, while the risk of cataracts began to increase significantly when blood glucose levels surpassed 163.92 mg/dL. The XGBoost algorithm indicated that blood glucose was a prominent predictor in the development of ocular diseases. Conclusions Higher blood glucose levels are associated with an increased risk of ocular diseases, suggesting that early glycemic control may be an effective measure for preventing the onset of ocular diseases in middle-aged and elderly populations. Ocular disorder glucose NHANES Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Diabetes, a major global public health challenge, has become one of the leading causes of adult blindness. Data from the International Diabetes Federation (IDF) in 2021 indicates that approximately 537 million adults worldwide have diabetes, with about one-third of these patients developing varying degrees of diabetic retinopathy (DR)[ 1 , 2 ]. Other ocular complications resulting from chronic hyperglycemia significantly impair patients' visual function and quality of life, including diabetic macular edema, cataracts, glaucoma, and dry eye[ 3 , 4 ]. Notably, middle-aged and elderly individuals are at high risk for diabetes and its ocular complications[ 5 ]. The prevalence of diabetes mellitus increases significantly with advancing age. Additionally, age-related changes in ocular tissues and structures, such as lens sclerosis and the deterioration of retinal microvascular function, further exacerbate the risk of ocular damage due to hyperglycemia[ 6 – 8 ]. Numerous studies have shown that poor glycemic control is associated with the development of DR and other related ocular diseases[ 9 – 11 ]. With the aging population and the rising prevalence of diabetes, early detection and management based on blood glucose levels could become a critical area for the prevention of ocular diseases in middle-aged and elderly populations. However, current studies on the relationship between blood glucose levels and ocular diseases in this demographic still suffer from limitations such as insufficient sample sizes, lack of long-term follow-up data, and inadequate control of confounding factors. There is an urgent need for systematic analyses based on large-scale, multi-dimensional databases. Therefore, this study utilizes the National Health and Nutrition Examination Survey (NHANES) database in the United States to systematically evaluate the association between blood glucose levels and common ocular diseases in middle-aged and elderly populations through large-sample analysis, providing scientific evidence for optimizing the prevention and treatment strategies for diabetic ocular diseases. Methods Study population This study used data from 2005–2008 from the NHANES database, a national health survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). These surveys collect comprehensive data on a variety of health-related topics, including demographic, socioeconomic factors, dietary patterns, and health-related information, all of which are accessible directly through an online website ( https://wwwn.cdc.gov/nchs/nhanes/search/ ). From the total sample of 27,034 participants, 15,928 participants under the age of 40 were excluded, 689 participants with missing BMI data, 3,419 participants were excluded due to missing information on hypertension as well as alcohol consumption, and 632 participants were excluded due to missing poverty-to-income ratio (PIR) information. Furthermore, 3,362 participants were excluded due to missing blood glucose information. Ultimately, a total of 3,004 participants were included in the study (Fig. 1 ). All participants provided written informed consent. Assessment of ocular disorders Ocular diseases were ascertained via two methodologies: self-reporting and retinal imaging. Retinal imaging was performed using a Canon EOS 10D digital camera (Canon, Tokyo, Japan) coupled with the Canon CR6-45NM ophthalmic digital imaging system. This examination was restricted to participants aged 40 years or older. Participants were seated in a darkened room during the imaging process, with their pupils pharmacologically dilated. Two digital images were captured for each participant: one centered on the macula and the other on the optic nerve. These images were subsequently analyzed by the Fundus Reading Center at the University of Wisconsin-Madison. Ocular disease status was defined based on the worse-seeing eye of the two[ 12 ]. DR was diagnosed according to the Early Treatment Diabetic Retinopathy Study (ETDRS) grading scale. Age-related macular degeneration (AMD) was defined using the modified Wisconsin Age-Related Maculopathy Grading Classification Scheme, supplemented by self-report[ 13 ]. Cataracts were identified based on the self-reported history of cataract surgery[ 14 ]. For glaucoma, a two-pronged approach was employed. First, to identify glaucoma defined by optic disc characteristics, fundus photographs were graded by experts on a four-point scale: none, possible, probable, or definite. Second, glaucoma was also defined based on a self-report question: “Has an ophthalmologist ever told you that you have glaucoma, sometimes called high eye pressure?”[ 15 ]. Assessment of blood glucose levels To measure morning fasting blood glucose, participants should fast for at least 9 hours before collection[ 16 ]. Fasting blood glucose levels are tested in the Mobile Examination Center (MEC). A fasting blood glucose level ≥ 126 mg/dL is defined as diabetes mellitus (DM), a fasting blood glucose level between 100–125 mg/dL is defined as prediabetes diabetes mellitus (Pre-DM), and a fasting blood glucose level < 100 mg/dL is defined as normal glucose regulation (NGR)[ 17 , 18 ]. Covariates Baseline data of participants were meticulously collected by trained interviewers using structured questionnaires. (1) Demographic and lifestyle data included age, sex (Female, Male), marital status (Married, unmarried), educational level (below high school, senior high school, above high school), drinking status (yes, no), and the PIR categorized as ( 2). (2) Physical measurements included body mass index (BMI). (3) Medical history included hypertension (yes, no) and depression (yes, no). Hypertension was defined based on self-report as to whether a healthcare professional had ever told the participant that they had hypertension[ 19 ]. Statistical analysis For baseline characteristic information, continuous variables following a normal distribution are presented as weighted means and standard deviations, and group differences are assessed using weighted Student’s t -tests. For quantitative variables not conforming to a normal distribution, we provide medians and interquartile ranges, and group differences are evaluated using Kruskal-Walli’s test. Categorical variables are expressed as weighted percentages, and statistical assessment is performed using weighted chi-square tests. Weighted multivariable logistic regression models were employed to investigate the association between different blood glucose levels and the risk of ocular diseases. Model 1 was unadjusted. Model 2 was adjusted only for age, sex, and marital status. Model 3, built upon Model 2, further adjusted for educational level, BMI, drinking status, depression, the PIR, and hypertension. Odds ratios (OR) and their 95% confidence intervals (CI) for the association between blood glucose levels and the risk of ocular diseases were calculated for each model. Subgroup analyses were conducted to assess whether the effect of blood glucose levels on ocular diseases varied by different demographic groups, stratifying by sex, marital status, educational level, PIR, drinking, depression, and hypertension. Additionally, a fully adjusted restricted cubic spline (RCS) analysis was performed to explore the dose-response relationship between blood glucose levels and various ocular diseases. Furthermore, to assess the relative importance of factors associated with ocular diseases, an XGBoost model was constructed using the “xgboost” package to rank the contribution of each variable. Data analysis for this study was performed using version 4.4.3 of the statistical software R. P < 0.05 was considered statistically significant. Results Participants’ characteristics stratified by blood glucose level Among the 3,004 participants, the mean age was 60.28 ± 12.16 years, including 1,522 females (50.7%) and 1,482 males (49.3%). The average BMI was 28.87 ± 5.97 kg/m². Compared to participants with NGR, those with DM were more likely to be male, have an educational level below high school, be drinkers, and have comorbid hypertension ( p < 0.05). In terms of ocular diseases, the prevalence of cataracts, glaucoma, and DR increased gradually with the elevation of blood glucose levels ( p 0.05) (Table 1 ). Table 1 Characteristics of participants stratified by blood glucose level. level Overall NGR Pre-DM DM p n 3004 982 1482 540 Age (years) 60.28 (12.16) 57.42 (12.45) 61.38 (12.04) 62.48 (10.99) < 0.001 Gender (%) Female 1522 (50.7) 604 (61.5) 690 (46.6) 228 (42.2) < 0.001 Male 1482 (49.3) 378 (38.5) 792 (53.4) 312 (57.8) Marital (%) Married 2134 (71.0) 678 (69.0) 1064 (71.8) 392 (72.6) 0.229 unmarried 870 (29.0) 304 (31.0) 418 (28.2) 148 (27.4) Educational level (n, %) Above high school 1290 (42.9) 466 (47.5) 668 (45.1) 156 (28.9) < 0.001 Below high school 962 (32.0) 268 (27.3) 462 (31.2) 232 (43.0) Senior high school 752 (25.0) 248 (25.3) 352 (23.8) 152 (28.1) PIR (%) 2 1672 (55.7) 548 (55.8) 848 (57.2) 276 (51.1) 1–2 820 (27.3) 268 (27.3) 390 (26.3) 162 (30.0) BMI (kg/m 2 ) 28.87 (5.97) 27.12 (5.52) 29.09 (5.59) 31.42 (6.71) < 0.001 Drinking status (n, %) No 978 (32.6) 340 (34.6) 440 (29.7) 198 (36.7) 0.003 Yes 2026 (67.4) 642 (65.4) 1042 (70.3) 342 (63.3) Depressed (n, %) No 2722 (90.6) 890 (90.6) 1356 (91.5) 476 (88.1) 0.073 Yes 282 (9.4) 92 (9.4) 126 (8.5) 64 (11.9) Hypertension (%) No 1546 (51.5) 626 (63.7) 742 (50.1) 178 (33.0) < 0.001 Yes 1458 (48.5) 356 (36.3) 740 (49.9) 362 (67.0) Cataracts (n, %) No 2590 (86.2) 876 (89.2) 1258 (84.9) 456 (84.4) 0.004 Yes 414 (13.8) 106 (10.8) 224 (15.1) 84 (15.6) Glaucoma (n, %) No 2836 (94.4) 938 (95.5) 1416 (95.5) 482 (89.3) < 0.001 Yes 168 (5.6) 44 (4.5) 66 (4.5) 58 (10.7) AMD (%) No 2894 (96.3) 938 (95.5) 1430 (96.5) 526 (97.4) 0.156 Yes 110 (3.7) 44 (4.5) 52 (3.5) 14 (2.6) DR (%) No 2876 (95.7) 965 (98.3) 1453 (98.0) 458 (84.8) < 0.001 Yes 128 (4.3) 17 (1.7) 29 (2.0) 82 (15.2) NGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; PIR: poverty-to-income ratio; BMI: body mass index; AMD: age-related macular degeneration; DR: diabetic retinopathy. Participants’ characteristics stratified by ocular disease Among the 3,004 participants, 128 were diagnosed with DR, 414 with cataracts, 168 with glaucoma, and 110 with AMD. First, patients with DR were generally older and had a significantly higher BMI ( p < 0.05). Additionally, DR patients were more inclined to consume alcohol and generally had an educational level below high school, with a higher proportion of the higher income group. Hypertension and DM were similarly more prevalent in DR patients ( p < 0.05), further suggesting that these chronic diseases might be independent risk factors for DR. Cataract patients were significantly older and more likely to be married. These patients generally had a lower BMI but a higher proportion of alcohol consumption. Compared to those without the disease, cataract patients also showed notable differences in income levels, prevalence of depression, and rates of hypertension and diabetes ( p < 0.05). Glaucoma patients were older and had a significantly higher prevalence of hypertension and diabetes ( p < 0.05). For AMD, patients were significantly older, generally had a lower BMI, and had relatively higher proportions of married individuals and alcohol drinkers. Hypertension was also more common among AMD patients ( p < 0.05) (Table 2 ). Table 2 Characteristics of participants stratified by ocular disease. DR Cataracts Glaucoma AMD level Overall No Yes p No Yes p No Yes p No Yes p n 3004 2876 128 2590 414 2836 168 2894 110 Age (mean (SD)) 60.28 (12.16) 60.18 (12.20) 62.58 (11.06) 0.029 58.00 (11.23) 74.57 (6.86) < 0.001 59.81 (12.14) 68.21 (9.59) < 0.001 59.71 (11.93) 75.22 (7.83) < 0.001 Gender (%) Female 1522 (50.7) 1467 (51.0) 55 (43.0) 0.091 1284 (49.6) 238 (57.5) 0.003 1440 (50.8) 82 (48.8) 0.678 1460 (50.4) 62 (56.4) 0.262 Male 1482 (49.3) 1409 (49.0) 73 (57.0) 1306 (50.4) 176 (42.5) 1396 (49.2) 86 (51.2) 1434 (49.6) 48 (43.6) Marital (%) Married 2134 (71.0) 2046 (71.1) 88 (68.8) 0.629 1798 (69.4) 336 (81.2) < 0.001 2022 (71.3) 112 (66.7) 0.231 2034 (70.3) 100 (90.9) < 0.001 unmarried 870 (29.0) 830 (28.9) 40 (31.2) 792 (30.6) 78 (18.8) 814 (28.7) 56 (33.3) 860 (29.7) 10 (9.1) BMI (mean (SD)) 28.87 (5.97) 28.72 (5.91) 32.10 (6.49) < 0.001 29.00 (6.02) 28.00 (5.54) 0.001 28.84 (5.93) 29.29 (6.68) 0.343 28.96 (6.01) 26.52 (4.23) < 0.001 Drinking status (%) No 978 (32.6) 920 (32.0) 58 (45.3) 0.002 796 (30.7) 182 (44.0) < 0.001 922 (32.5) 56 (33.3) 0.892 930 (32.1) 48 (43.6) 0.015 Yes 2026 (67.4) 1956 (68.0) 70 (54.7) 1794 (69.3) 232 (56.0) 1914 (67.5) 112 (66.7) 1964 (67.9) 62 (56.4) Depressed (%) No 2722 (90.6) 2609 (90.7) 113 (88.3) 0.442 2334 (90.1) 388 (93.7) 0.025 2568 (90.6) 154 (91.7) 0.729 2618 (90.5) 104 (94.5) 0.203 Yes 282 (9.4) 267 (9.3) 15 (11.7) 256 (9.9) 26 (6.3) 268 (9.4) 14 (8.3) 276 (9.5) 6 (5.5) Educational level (%) Above high school 1290 (42.9) 1244 (43.3) 46 (35.9) 0.008 1146 (44.2) 144 (34.8) < 0.001 1232 (43.4) 58 (34.5) 0.068 1242 (42.9) 48 (43.6) 0.456 Below high school 962 (32.0) 905 (31.5) 57 (44.5) 826 (31.9) 136 (32.9) 898 (31.7) 64 (38.1) 932 (32.2) 30 (27.3) Senior high school 752 (25.0) 727 (25.3) 25 (19.5) 618 (23.9) 134 (32.4) 706 (24.9) 46 (27.4) 720 (24.9) 32 (29.1) PIR (%) < 1 512 (17.0) 496 (17.2) 16 (12.5) < 0.001 460 (17.8) 52 (12.6) 2 1672 (55.7) 1615 (56.2) 57 (44.5) 1476 (57.0) 196 (47.3) 1590 (56.1) 82 (48.8) 1610 (55.6) 62 (56.4) 1_2 820 (27.3) 765 (26.6) 55 (43.0) 654 (25.3) 166 (40.1) 764 (26.9) 56 (33.3) 784 (27.1) 36 (32.7) Hypertension (%) No 1546 (51.5) 1523 (53.0) 23 (18.0) < 0.001 1396 (53.9) 150 (36.2) < 0.001 1490 (52.5) 56 (33.3) < 0.001 1504 (52.0) 42 (38.2) 0.006 Yes 1458 (48.5) 1353 (47.0) 105 (82.0) 1194 (46.1) 264 (63.8) 1346 (47.5) 112 (66.7) 1390 (48.0) 68 (61.8) GLU (%) Normal 982 (32.7) 965 (33.6) 17 (13.3) 876 (33.8) 106 (25.6) 938 (33.1) 44 (26.2) 938 (32.4) 44 (40.0) Prediabetes 1482 (49.3) 1453 (50.5) 29 (22.7) 1258 (48.6) 224 (54.1) 1416 (49.9) 66 (39.3) 1430 (49.4) 52 (47.3) Diabetes 540 (18.0) 458 (15.9) 82 (64.1) < 0.001 456 (17.6) 84 (20.3) 0.004 482 (17.0) 58 (34.5) < 0.001 526 (18.2) 14 (12.7) 0.156 NGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; PIR: poverty-to-income ratio; BMI: body mass index; AMD: age-related macular degeneration; DR: diabetic retinopathy. Association between blood glucose and ocular diseases According to the results presented in Table 3 , in the unadjusted model 1, compared to the NGR group, patients with DM exhibited a significantly increased risk of ocular diseases. The risk of DR was eight times higher in the DM group than in the NGR group (OR = 8.189, 95%CI: 2.687–24.96), and cataracts (OR = 2.134, 95%CI: 1.304–3.492) and glaucoma (OR = 2.734, 95%CI: 1.588–4.708) were also significantly elevated. Although the risk of AMD tended to increase with elevated blood glucose levels, no statistically significant difference was observed ( p > 0.05). In model 2, adjusted for age, sex, and marital status, only the risk of DR remained significantly increased in the DM group compared to the NGR group (OR = 6.655, 95%CI: 1.976–22.420, p = 0.006), while changes in the risks of other ocular diseases were not significant. In model 3, although the risks of various ocular diseases showed an increasing trend with elevated blood glucose levels, none reached statistical significance ( p > 0.05). Furthermore, RCS analysis further revealed a nonlinear relationship between blood glucose levels and DR, cataracts, and glaucoma ( p -non-linear < 0.001). Specifically, the risk of DR increased sharply when blood glucose levels exceeded 104.63 mg/dL ( Fig. 2 A ) , while the risk of cataracts began to increase significantly when blood glucose levels surpassed163.92 mg/dL (Fig. 2 B ) . The risk of glaucoma showed a gradual increasing trend after blood glucose levels exceeded 104.63 mg/dL (Fig. 2 C). For AMD, elevated blood glucose levels had almost no significant impact on the risk of the disease (Fig. 2 D). Table 3 Association between blood glucose and ocular diseases. exposure Model 1 OR (95% CI) p Model 2 OR (95% CI) p Model 3 OR (95% CI) p DR NGR reference Pre-DM 0.644(0.190–2.177) 0.451 0.562(0.154–2.054) 0.341 0.392(0.040–3.820) 0.282 DM 8.189(2.687–24.96) 0.001 6.655(1.976–22.420) 0.006 3.038(0.369-25.000) 0.192 Cataracts NGR reference Pre-DM 1.530(0.757–3.092) 0.220 1.189(0.604–2.339) 0.586 1.116(0.409–3.042) 0.751 DM 2.134(1.304–3.492) 0.005 1.405(0.872–2.263) 0.145 1.329(0.635–2.779) 0.308 Glaucoma NGR reference Pre-DM 0.888(0.464-1.700) 0.702 0.655(0.337–1.278) 0.192 0.595(0.231–1.532) 0.179 DM 2.734(1.588–4.708) 0.001 1.710(0.909–3.215) 0.09 1.333(0.567–3.129) 0.363 AMD NGR reference Pre-DM 1.271(0.645–2.508) 0.461 1.952(0.969–3.930) 0.06 1.889(0.704–5.072) 0.133 DM 1.230(0.468–3.232) 0.653 2.257(0.955–5.332) 0.06 1.965(0.561–6.883) 0.185 NGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; AMD: age-related macular degeneration; DR: diabetic retinopathy. Subgroup analysis A subgroup analysis was performed to gain insight into the relationship between blood glucose levels and the risk of different ocular diseases. The results indicated that among patients with DR, there were significant interactions between marital status, drinking status, hypertension, and PIR with blood glucose levels ( p for interaction < 0.05) (Fig. 3 A). Additionally, in the context of cataracts, the interaction between blood glucose and hypertension was also significant ( p for interaction = 0.013) (Fig. 3 B). In the glaucoma group, factors such as sex, alcohol consumption status, hypertension, and educational level significantly influenced the relationship between blood glucose levels and the risk of glaucoma ( p for interaction < 0.05) (Fig. 3 C). However, for AMD, the association between blood glucose levels and the risk of AMD remained consistent across different subgroups, with no significant interactions observed ( p for interaction > 0.05) (Fig. 3 D). Ranking the importance of risk factors for ocular diseases In this study, XGBoost algorithm was employed to rank the importance of multiple variables including gender, education level, marital status, drinking status, BMI, PIR, hypertension, depression and blood glucose level. The results indicated that blood glucose level had a significant impact on predictions among different ocular diseases. Specifically, it was ranked first among DR, third among cataracts, second among Glaucoma, and third among AMD, all of which are top positions (Fig. 4 ). Discussion This study is the first large-scale investigation to explore the association between blood glucose levels and ocular diseases based on the NHANES database. Our findings reveal that higher blood glucose levels are significantly associated with an increased risk of DR, cataracts, and glaucoma. However, no such association was observed between blood glucose levels and AMD. RCS analysis demonstrated nonlinear relationships between blood glucose levels and the risk of DR, cataracts, and glaucoma. Subgroup analyses indicated that the interaction between hypertension and blood glucose levels in influencing the risk of DR, cataracts, and glaucoma warrants special attention. Additionally, the XGBoost algorithm revealed that blood glucose levels are the most important predictor for DR risk and have good predictive power for cataracts, glaucoma, and AMD. These findings have important clinical implications and provide new evidence for the role of blood glucose control in the prevention of ocular diseases. DR is one of the most common ocular complications of diabetes, and its incidence is closely related to poor glycemic control[ 20 ]. A systematic analysis involving 16,259 patients with type 2 diabetes (T2D) showed that a high triglyceride glucose (TyG) index is associated with an increased risk of DR in T2D patients[ 21 ]. Another cross-sectional study based on the Chinese population demonstrated that among patients with T2D, those in the higher quartiles of TyG-WHR had an increased risk of DR (OR = 1.223, 95%CI: 1.078–1.387, p < 0.05), emphasizing that TyG-WHR could potentially serve as a valuable and reliable biomarker for DR[ 22 ]. This study further revealed a significant correlation between higher blood glucose levels and an increased risk of DR. Chronic hyperglycemia can induce the breakdown of the blood-retinal barrier, increase the production of reactive oxygen species within retinal cells, and trigger autophagy and aging of retinal ganglion cells[ 23 ]. Moreover, hyperglycemia can also initiate chronic low-grade inflammation in the retina, which subsequently impairs retinal function[ 24 ]. This suggests that glycemic management may be essential in the prevention of DR. A multi-cohort prospective study has shown that long-term use of metformin and sulfonylureas can effectively reduce the risk of DR in diabetic patients[ 25 ]. The RCS analysis in this study showed that the risk of DR increases sharply when blood glucose levels exceed 104.63 mg/dL. This result emphasizes that the risk of DR significantly increases even before reaching the diagnostic threshold for diabetes. It is evident that middle-aged and elderly people need to monitor their blood glucose levels more carefully, and their target values should be lower than those of younger people. Also strengthening lifestyle interventions in the middle-aged and elderly population, such as dietary control, exercise and regular fundus screening, may be a key strategy to reduce the incidence of DR[ 26 ]. In addition to DR, cataracts are also ocular disease closely related to blood glucose levels. Cataracts are a common age-related eye problem, however, the impact of high blood glucose on the lens makes diabetic patients significantly more susceptible to cataracts[ 27 ]. Wei et al., using the NHANES database, found that higher TyG index and its related indicators were significantly positively correlated with the presence of cataracts ( p < 0.05)[ 14 ]. Our study indicates that high blood glucose is an important risk factor for the development of cataracts, especially when blood glucose levels reach above 163.92 mg/dL, significantly increasing the risk of cataracts. Cataracts caused by high blood glucose may be related to the elevation of inflammation and oxidative stress levels in lens epithelial cells[ 28 , 29 ]. Elevated blood glucose leads to the conversion of glucose to sorbitol in the lens, and the accumulation of sorbitol causes an increase in osmotic pressure, resulting in swelling of lens epithelial cells, ultimately making the lens opaque[ 30 ]. Additionally, our findings reveal that long-term uncontrolled blood glucose levels increase the risk of cataracts. Therefore, it is crucial to reduce blood glucose levels through dietary adjustments, regular exercise, and anti-diabetic medications to slow down or prevent the development of cataracts. Glaucoma is another ocular disease associated with high blood glucose levels, characterized mainly by increased intraocular pressure, which subsequently damages the optic nerve[ 31 , 32 ]. Our study found that higher blood glucose levels are closely related to the occurrence of glaucoma. However, a Mendelian randomization study based on European and East Asian populations showed no causal relationship between fasting blood glucose and the risk of primary open-angle glaucoma, which contrasts with our findings[ 33 ]. Another cohort study based on the Korean national population demonstrated that high fasting blood glucose is associated with an increased risk of open-angle glaucoma (HR = 2.189, 95%CI: 1.779–2.695)[ 34 ]. A Mendelian randomization study based on the Japanese population also observed a significant correlation between fasting blood glucose and primary open-angle glaucoma (OR = 1.48, 95% CI: 1.10–1.79)[ 35 ]. The discrepancy in these results could be due to differences in population sources and disease types, and therefore, the causal relationship between them still requires further prospective studies. Additionally, our study found that the risk of glaucoma shows an upward trend in the pre-diabetic stage. This is consistent with the results of Zhao et al., where participants without diabetes but with higher fasting blood glucose were more likely to develop glaucoma[ 36 ]. This suggests that in pre-diabetic patients, glaucoma screening should be strengthened in clinical practice. This not only aids in the early detection of glaucoma to prevent vision loss but also provides a new perspective for the treatment of glaucoma. AMD is one of the leading causes of irreversible vision loss in the elderly population[ 37 ]. Our study found that although there is an increasing trend in the risk of AMD with elevated blood glucose levels, no statistically significant difference was observed ( p > 0.05). The relationship between blood glucose levels and AMD remains controversial. A Mendelian randomization study indicated that genetically predicted glycemic traits were not significantly associated with late-stage AMD[ 38 ]. However, another systematic review found a significant correlation between diabetes and an increased risk of AMD (OR, 1.05; 95% CI, 1.00-1.14)[ 39 ]. Additionally, research has shown that treatment of diabetes with metformin can significantly reduce the risk of AMD[ 40 ]. The lack of statistically significant findings in our study may be attributed to an insufficient sample size, which failed to adequately capture the subtle effects of elevated blood glucose on AMD risk. Furthermore, previous studies often only adjusted for age and sex, failing to effectively exclude other potential confounding factors, which may have affected the accuracy of their conclusions. The subgroup analyses of this study were based on sex, marital status, educational level, PIR, drinking status, depression, and hypertension to explore the potential influences and interactions between blood glucose and ocular diseases. Differences in sex lead to varying hormone levels, which subsequently affect inflammation and disease susceptibility[ 41 , 42 ]. Additionally, social determinants of health based on education and economics may be associated with ocular diseases such as DR, and identifying these determinants can aid in early screening and the development of more comprehensive prevention and treatment plans[ 43 ]. Hypertension and depression were included as they are known as risk factors for several ocular diseases and may interact with blood glucose levels[ 44 , 45 ]. Therefore, by analyzing different subgroups and their interactions, this study provides a more nuanced understanding of the relationship between blood glucose and ocular diseases in various populations, offering important bases for formulating precise prevention and intervention strategies. This study has its strengths and limitations. Firstly, this study is the first to use a large, nationally representative sample to investigate the relationship between blood glucose levels and ocular diseases. However, as a cross-sectional study, it cannot establish a causal relationship between blood glucose and ocular diseases. Large-scale prospective studies are needed to further demonstrate the relationship. Secondly, the study relied on self-reported diagnoses of ocular diseases, which may lead to classification bias and an underestimation of prevalence, as some severe cases may not have participated in the survey. Finally, although this study employed weighted multivariate logistic regression analysis to adjust for multiple confounding factors, other potential confounders such as genetic susceptibility or medication use may still influence the relationship between blood glucose and ocular diseases. Conclusion In conclusion, higher blood glucose levels are associated with an increased risk of DR, cataracts, and glaucoma, but no statistically significant difference was found with the increased risk of AMD. Thresholds of blood glucose were observed, where the risk of DR, cataracts, and glaucoma increased when blood glucose levels exceeded 104.63 mg/dL or 163.92 mg/dL. Controlling blood glucose levels in both pre-diabetic and diabetic phases may be an effective measure for preventing the onset of ocular diseases. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable Availability of data and materials The datasets analyzed in this study are available at the NHANES database (https://wwwn.cdc.gov/nchs/nhanes/search/). Competing interests The authors declare that there are no potential competing interests to declare. Funding None. Authors' contributions XW and LW conceptualized and collected and interpreted the data. XW wrote the original draft. LW reviewed and edited the draft. Acknowledgements None. 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Current eye research. 2018; 43:1233-1238; doi:10.1080/02713683.2018.1485953 Li H, Xu L, Song H: MiR-29a Alleviates High Glucose-induced Inflammation and Mitochondrial Dysfunction via Modulation of IL-6/STAT3 in Diabetic Cataracts. Current eye research. 2021; 46:1325-1332; doi:10.1080/02713683.2021.1887272 Lian L, Le Z, Wang Z, Chen YA, Jiao X, Qi H, Hejtmancik JF, Ma X, Zheng Q, Ren Y: SIRT1 Inhibits High Glucose-Induced TXNIP/NLRP3 Inflammasome Activation and Cataract Formation. Investigative ophthalmology & visual science. 2023; 64:16; doi:10.1167/iovs.64.3.16 Bai J, Jiang G, Zhao M, Wang S: Ghrelin Mitigates High-Glucose-Induced Oxidative Damage and Apoptosis in Lens Epithelial Cells. Journal of diabetes research. 2022; 2022:1373533; doi:10.1155/2022/1373533 Zhao D, Cho J, Kim MH, Friedman DS, Guallar E: Diabetes, fasting glucose, and the risk of glaucoma: a meta-analysis. Ophthalmology. 2015; 122:72-78; doi:10.1016/j.ophtha.2014.07.051 AlDarrab A, Al Jarallah OJ, Al Balawi HB: Association of diabetes, fasting glucose, and the risk of glaucoma: a systematic review and meta-analysis. European review for medical and pharmacological sciences. 2023; 27:2419-2427; doi:10.26355/eurrev_202303_31776 Hu Z, Zhou F, Kaminga AC, Xu H: Type 2 Diabetes, Fasting Glucose, Hemoglobin A1c Levels and Risk of Primary Open-Angle Glaucoma: A Mendelian Randomization Study. Investigative ophthalmology & visual science. 2022; 63:37; doi:10.1167/iovs.63.5.37 Choi JA, Park YM, Han K, Lee J, Yun JS, Ko SH: Fasting plasma glucose level and the risk of open angle glaucoma: Nationwide population-based cohort study in Korea. PloS one. 2020; 15:e0239529; doi:10.1371/journal.pone.0239529 Hanyuda A, Goto A, Nakatochi M, Sutoh Y, Narita A, Nakano S, Katagiri R, Wakai K, Takashima N, Koyama T et al : Association Between Glycemic Traits and Primary Open-Angle Glaucoma: A Mendelian Randomization Study in the Japanese Population. American journal of ophthalmology. 2023; 245:193-201; doi:10.1016/j.ajo.2022.09.004 Zhao D, Cho J, Kim MH, Friedman D, Guallar E: Diabetes, glucose metabolism, and glaucoma: the 2005-2008 National Health and Nutrition Examination Survey. PloS one. 2014; 9:e112460; doi:10.1371/journal.pone.0112460 Guymer RH, Campbell TG: Age-related macular degeneration. Lancet (London, England). 2023; 401:1459-1472; doi:10.1016/s0140-6736(22)02609-5 Kuan V, Warwick A, Hingorani A, Tufail A, Cipriani V, Burgess S, Sofat R: Association of Smoking, Alcohol Consumption, Blood Pressure, Body Mass Index, and Glycemic Risk Factors With Age-Related Macular Degeneration: A Mendelian Randomization Study. JAMA ophthalmology. 2021; 139:1299-1306; doi:10.1001/jamaophthalmol.2021.4601 Chen X, Rong SS, Xu Q, Tang FY, Liu Y, Gu H, Tam PO, Chen LJ, Brelén ME, Pang CP et al : Diabetes mellitus and risk of age-related macular degeneration: a systematic review and meta-analysis. PloS one. 2014; 9:e108196; doi:10.1371/journal.pone.0108196 Liang KH, Chen CH, Tsai HR, Chang CY, Chen TL, Hsu WC: Association Between Oral Metformin Use and the Development of Age-Related Macular Degeneration in Diabetic Patients: A Systematic Review and Meta-Analysis. Investigative ophthalmology & visual science. 2022; 63:10; doi:10.1167/iovs.63.13.10 Sen HN, Davis J, Ucar D, Fox A, Chan CC, Goldstein DA: Gender disparities in ocular inflammatory disorders. Current eye research. 2015; 40:146-161; doi:10.3109/02713683.2014.932388 Korpole NR, Kurada P, Korpole MR: Gender Difference in Ocular Diseases, Risk Factors and Management with Specific Reference to Role of Sex Steroid Hormones. Journal of mid-life health. 2022; 13:20-25; doi:10.4103/jmh.jmh_28_22 Silverberg EL, Sterling TW, Williams TH, Castro G, Rodriguez de la Vega P, Barengo NC: The Association between Social Determinants of Health and Self-Reported Diabetic Retinopathy: An Exploratory Analysis. International journal of environmental research and public health. 2021; 18; doi:10.3390/ijerph18020792 Wang XF, Zhang XW, Liu YJ, Zheng XY, Su MR, Sun XH, Jiang F, Liu ZN: The causal effect of hypertension, intraocular pressure, and diabetic retinopathy: a Mendelian randomization study. Frontiers in endocrinology. 2024; 15:1304512; doi:10.3389/fendo.2024.1304512 Ang MJ, Afshari NA: Cataract and systemic disease: A review. Clinical & experimental ophthalmology. 2021; 49:118-127; doi:10.1111/ceo.13892 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-6981822","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494607257,"identity":"b892bba8-7649-420b-8906-36a4eeefb35d","order_by":0,"name":"Xinru Wang","email":"","orcid":"","institution":"No. 905 Hospital of PLA Navy","correspondingAuthor":false,"prefix":"","firstName":"Xinru","middleName":"","lastName":"Wang","suffix":""},{"id":494607259,"identity":"5d4efc03-601c-4153-b2eb-084de329d72f","order_by":1,"name":"Lin Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYHACxgeJf2x4+NkbiNfCbPCxIU1GsucA8VrYJGc2HLYxuOFApHp+ieRj0rw7zvMw3GBg/PAxhwgtkjPSkq15z9zmYZzdwCw5cxsRWgxu5Bje5mG7zcMsc4CNmZcYLfY38j9I87Cd42GTSCBSi4FEDpPkzLYDPDxEa5E488zY4MOZZB4JnoPNxPmFvz354YOECjt7++PNBz98JEYLg0ACjMXYQIx6kDUHiFQ4CkbBKBgFIxcAAPdlNiHb80w6AAAAAElFTkSuQmCC","orcid":"","institution":"No. 905 Hospital of PLA Navy","correspondingAuthor":true,"prefix":"","firstName":"Lin","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-06-26 09:23:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6981822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6981822/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88248363,"identity":"21293016-f7dd-4452-8a74-e19f6b06e6e5","added_by":"auto","created_at":"2025-08-04 12:57:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69619,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of study participants.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6981822/v1/fed361df2c3f4192cf4d4adf.jpg"},{"id":88247383,"identity":"3a702cd7-5d06-45cc-a9ed-368feb42474c","added_by":"auto","created_at":"2025-08-04 12:49:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86848,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline (RCS) analysis associations between blood glucose and ocular disorders.\u003cstrong\u003e A\u003c/strong\u003e Presents the connection between blood glucose and the risk of diabetic retinopathy (DR). \u003cstrong\u003eB\u003c/strong\u003ePresents the connection between blood glucose and the risk of cataract. \u003cstrong\u003eC\u003c/strong\u003ePresents the connection between blood glucose and the risk of glaucoma.\u003cstrong\u003e D\u003c/strong\u003ePresents the connection between blood glucose and the risk of age-related macular degeneration (AMD).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6981822/v1/840bbc33dff3a4fe0c3b5679.jpg"},{"id":88247384,"identity":"bfa1c5da-3dca-4adf-b2a4-36f086eef1f2","added_by":"auto","created_at":"2025-08-04 12:49:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217089,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup and interaction analyses of the association between blood glucose and ocular disorders risk.\u003cstrong\u003eA \u003c/strong\u003ediabetic retinopathy (DR).\u003cstrong\u003e B \u003c/strong\u003ecataract. \u003cstrong\u003eC\u003c/strong\u003e glaucoma. \u003cstrong\u003eD\u003c/strong\u003eage-related macular degeneration (AMD). Adjusted for sex, marital status, educational level, PIR, drinking status, depression, and hypertension.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6981822/v1/3f8db4f72e6abd74fcb71869.jpg"},{"id":88247381,"identity":"24c8db18-87a2-403d-af8f-eb7a330bc4a7","added_by":"auto","created_at":"2025-08-04 12:49:07","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":81606,"visible":true,"origin":"","legend":"\u003cp\u003eThe importance of the influencing factors by XGBoost algorithm. \u003cstrong\u003eA \u003c/strong\u003ediabetic retinopathy (DR).\u003cstrong\u003eB \u003c/strong\u003ecataract. \u003cstrong\u003eC\u003c/strong\u003e glaucoma. \u003cstrong\u003eD\u003c/strong\u003e age-related macular degeneration (AMD).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6981822/v1/ace78f6e14bc8f9b220d41ae.jpg"},{"id":101296692,"identity":"37023053-ad27-4a6a-974c-1c2fe599e53e","added_by":"auto","created_at":"2026-01-28 09:18:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1548954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6981822/v1/0df2fb27-b893-412c-a6b4-cc68b4ae3433.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of blood glucose levels with ocular diseases in the middle-aged and elderly population: results from the NHANES 2005-2008","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes, a major global public health challenge, has become one of the leading causes of adult blindness. Data from the International Diabetes Federation (IDF) in 2021 indicates that approximately 537\u0026nbsp;million adults worldwide have diabetes, with about one-third of these patients developing varying degrees of diabetic retinopathy (DR)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Other ocular complications resulting from chronic hyperglycemia significantly impair patients' visual function and quality of life, including diabetic macular edema, cataracts, glaucoma, and dry eye[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Notably, middle-aged and elderly individuals are at high risk for diabetes and its ocular complications[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The prevalence of diabetes mellitus increases significantly with advancing age. Additionally, age-related changes in ocular tissues and structures, such as lens sclerosis and the deterioration of retinal microvascular function, further exacerbate the risk of ocular damage due to hyperglycemia[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Numerous studies have shown that poor glycemic control is associated with the development of DR and other related ocular diseases[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. With the aging population and the rising prevalence of diabetes, early detection and management based on blood glucose levels could become a critical area for the prevention of ocular diseases in middle-aged and elderly populations. However, current studies on the relationship between blood glucose levels and ocular diseases in this demographic still suffer from limitations such as insufficient sample sizes, lack of long-term follow-up data, and inadequate control of confounding factors. There is an urgent need for systematic analyses based on large-scale, multi-dimensional databases. Therefore, this study utilizes the National Health and Nutrition Examination Survey (NHANES) database in the United States to systematically evaluate the association between blood glucose levels and common ocular diseases in middle-aged and elderly populations through large-sample analysis, providing scientific evidence for optimizing the prevention and treatment strategies for diabetic ocular diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eThis study used data from 2005\u0026ndash;2008 from the NHANES database, a national health survey conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). These surveys collect comprehensive data on a variety of health-related topics, including demographic, socioeconomic factors, dietary patterns, and health-related information, all of which are accessible directly through an online website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wwwn.cdc.gov/nchs/nhanes/search/\u003c/span\u003e\u003cspan address=\"https://wwwn.cdc.gov/nchs/nhanes/search/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). From the total sample of 27,034 participants, 15,928 participants under the age of 40 were excluded, 689 participants with missing BMI data, 3,419 participants were excluded due to missing information on hypertension as well as alcohol consumption, and 632 participants were excluded due to missing poverty-to-income ratio (PIR) information. Furthermore, 3,362 participants were excluded due to missing blood glucose information. Ultimately, a total of 3,004 participants were included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All participants provided written informed consent.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssessment of ocular disorders\u003c/h3\u003e\n\u003cp\u003eOcular diseases were ascertained via two methodologies: self-reporting and retinal imaging. Retinal imaging was performed using a Canon EOS 10D digital camera (Canon, Tokyo, Japan) coupled with the Canon CR6-45NM ophthalmic digital imaging system. This examination was restricted to participants aged 40 years or older. Participants were seated in a darkened room during the imaging process, with their pupils pharmacologically dilated. Two digital images were captured for each participant: one centered on the macula and the other on the optic nerve.\u003c/p\u003e\u003cp\u003eThese images were subsequently analyzed by the Fundus Reading Center at the University of Wisconsin-Madison. Ocular disease status was defined based on the worse-seeing eye of the two[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. DR was diagnosed according to the Early Treatment Diabetic Retinopathy Study (ETDRS) grading scale. Age-related macular degeneration (AMD) was defined using the modified Wisconsin Age-Related Maculopathy Grading Classification Scheme, supplemented by self-report[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Cataracts were identified based on the self-reported history of cataract surgery[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor glaucoma, a two-pronged approach was employed. First, to identify glaucoma defined by optic disc characteristics, fundus photographs were graded by experts on a four-point scale: none, possible, probable, or definite. Second, glaucoma was also defined based on a self-report question: \u0026ldquo;Has an ophthalmologist ever told you that you have glaucoma, sometimes called high eye pressure?\u0026rdquo;[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eAssessment of blood glucose levels\u003c/h3\u003e\n\u003cp\u003eTo measure morning fasting blood glucose, participants should fast for at least 9 hours before collection[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Fasting blood glucose levels are tested in the Mobile Examination Center (MEC). A fasting blood glucose level\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL is defined as diabetes mellitus (DM), a fasting blood glucose level between 100\u0026ndash;125 mg/dL is defined as prediabetes diabetes mellitus (Pre-DM), and a fasting blood glucose level\u0026thinsp;\u0026lt;\u0026thinsp;100 mg/dL is defined as normal glucose regulation (NGR)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eBaseline data of participants were meticulously collected by trained interviewers using structured questionnaires. (1) Demographic and lifestyle data included age, sex (Female, Male), marital status (Married, unmarried), educational level (below high school, senior high school, above high school), drinking status (yes, no), and the PIR categorized as (\u0026lt;\u0026thinsp;1, 1\u0026ndash;2, \u0026gt;\u0026thinsp;2). (2) Physical measurements included body mass index (BMI). (3) Medical history included hypertension (yes, no) and depression (yes, no). Hypertension was defined based on self-report as to whether a healthcare professional had ever told the participant that they had hypertension[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFor baseline characteristic information, continuous variables following a normal distribution are presented as weighted means and standard deviations, and group differences are assessed using weighted Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-tests. For quantitative variables not conforming to a normal distribution, we provide medians and interquartile ranges, and group differences are evaluated using Kruskal-Walli\u0026rsquo;s test. Categorical variables are expressed as weighted percentages, and statistical assessment is performed using weighted chi-square tests. Weighted multivariable logistic regression models were employed to investigate the association between different blood glucose levels and the risk of ocular diseases. Model 1 was unadjusted. Model 2 was adjusted only for age, sex, and marital status. Model 3, built upon Model 2, further adjusted for educational level, BMI, drinking status, depression, the PIR, and hypertension. Odds ratios (OR) and their 95% confidence intervals (CI) for the association between blood glucose levels and the risk of ocular diseases were calculated for each model. Subgroup analyses were conducted to assess whether the effect of blood glucose levels on ocular diseases varied by different demographic groups, stratifying by sex, marital status, educational level, PIR, drinking, depression, and hypertension. Additionally, a fully adjusted restricted cubic spline (RCS) analysis was performed to explore the dose-response relationship between blood glucose levels and various ocular diseases. Furthermore, to assess the relative importance of factors associated with ocular diseases, an XGBoost model was constructed using the \u0026ldquo;xgboost\u0026rdquo; package to rank the contribution of each variable. Data analysis for this study was performed using version 4.4.3 of the statistical software R. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u0026rsquo; characteristics stratified by blood glucose level\u003c/h2\u003e\u003cp\u003eAmong the 3,004 participants, the mean age was 60.28\u0026thinsp;\u0026plusmn;\u0026thinsp;12.16 years, including 1,522 females (50.7%) and 1,482 males (49.3%). The average BMI was 28.87\u0026thinsp;\u0026plusmn;\u0026thinsp;5.97 kg/m\u0026sup2;. Compared to participants with NGR, those with DM were more likely to be male, have an educational level below high school, be drinkers, and have comorbid hypertension (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In terms of ocular diseases, the prevalence of cataracts, glaucoma, and DR increased gradually with the elevation of blood glucose levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, the prevalence of AMD did not show significant changes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eCharacteristics of participants stratified by blood glucose level.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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=\"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\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNGR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePre-DM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3004\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e982\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1482\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e540\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e60.28 (12.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.42 (12.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e61.38 (12.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e62.48 (10.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\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\u003eGender (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1522 (50.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e604 (61.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e690 (46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e228 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1482 (49.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e378 (38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e792 (53.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e312 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2134 (71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e678 (69.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1064 (71.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e392 (72.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eunmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e870 (29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e304 (31.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e418 (28.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e148 (27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1290 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e466 (47.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e668 (45.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e156 (28.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e962 (32.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e268 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e462 (31.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e232 (43.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSenior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e752 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e248 (25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e352 (23.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e152 (28.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIR (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e512 (17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e166 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e244 (16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e102 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1672 (55.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e548 (55.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e848 (57.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e276 (51.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e820 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e268 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e390 (26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e162 (30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.87 (5.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.12 (5.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.09 (5.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e31.42 (6.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\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\u003eDrinking status (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e978 (32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e340 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e440 (29.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e198 (36.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2026 (67.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e642 (65.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1042 (70.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e342 (63.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepressed (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2722 (90.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e890 (90.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1356 (91.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e476 (88.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e282 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e92 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e126 (8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e64 (11.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1546 (51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e626 (63.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e742 (50.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e178 (33.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1458 (48.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e356 (36.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e740 (49.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e362 (67.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCataracts (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2590 (86.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e876 (89.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1258 (84.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e456 (84.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e414 (13.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e106 (10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e224 (15.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e84 (15.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlaucoma (n, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2836 (94.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e938 (95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1416 (95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e482 (89.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e168 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e66 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e58 (10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAMD (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2894 (96.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e938 (95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1430 (96.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e526 (97.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e110 (3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e52 (3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14 (2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDR (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2876 (95.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e965 (98.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1453 (98.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e458 (84.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e128 (4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17 (1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e82 (15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; PIR: poverty-to-income ratio; BMI: body mass index; AMD: age-related macular degeneration; DR: diabetic retinopathy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants’ characteristics stratified by ocular disease\u003c/h3\u003e\n\u003cp\u003eAmong the 3,004 participants, 128 were diagnosed with DR, 414 with cataracts, 168 with glaucoma, and 110 with AMD. First, patients with DR were generally older and had a significantly higher BMI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, DR patients were more inclined to consume alcohol and generally had an educational level below high school, with a higher proportion of the higher income group. Hypertension and DM were similarly more prevalent in DR patients (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), further suggesting that these chronic diseases might be independent risk factors for DR. Cataract patients were significantly older and more likely to be married. These patients generally had a lower BMI but a higher proportion of alcohol consumption. Compared to those without the disease, cataract patients also showed notable differences in income levels, prevalence of depression, and rates of hypertension and diabetes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Glaucoma patients were older and had a significantly higher prevalence of hypertension and diabetes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For AMD, patients were significantly older, generally had a lower BMI, and had relatively higher proportions of married individuals and alcohol drinkers. Hypertension was also more common among AMD patients (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003eCharacteristics of participants stratified by ocular disease.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eDR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003eCataracts\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e\u003cp\u003eGlaucoma\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e\u003cp\u003eAMD\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\u003elevel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2876\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2590\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e2894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (mean (SD))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.28 (12.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.18 (12.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62.58 (11.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e58.00 (11.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e74.57 (6.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e59.81 (12.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e68.21 (9.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e59.71 (11.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e75.22 (7.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\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\u003eGender (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1522 (50.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1467 (51.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55 (43.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1284 (49.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e238 (57.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1440 (50.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e82 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.678\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1460 (50.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e62 (56.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1482 (49.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1409 (49.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e73 (57.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1306 (50.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e176 (42.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1396 (49.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e86 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1434 (49.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e48 (43.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2134 (71.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2046 (71.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e88 (68.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1798 (69.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e336 (81.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2022 (71.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e112 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e2034 (70.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e100 (90.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eunmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e870 (29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e830 (28.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40 (31.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e792 (30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e78 (18.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e814 (28.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e56 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e860 (29.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e10 (9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (mean (SD))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.87 (5.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.72 (5.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32.10 (6.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.00 (6.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e28.00 (5.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e28.84 (5.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e29.29 (6.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e28.96 (6.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e26.52 (4.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\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\u003eDrinking status (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e978 (32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e920 (32.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e796 (30.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e182 (44.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e922 (32.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e56 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e930 (32.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e48 (43.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2026 (67.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1956 (68.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1794 (69.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e232 (56.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1914 (67.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e112 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1964 (67.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e62 (56.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepressed (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2722 (90.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2609 (90.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e113 (88.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2334 (90.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e388 (93.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2568 (90.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e154 (91.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e2618 (90.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e104 (94.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e267 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e256 (9.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e268 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e14 (8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e276 (9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e6 (5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbove high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1290 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1244 (43.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 (35.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1146 (44.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e144 (34.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1232 (43.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e58 (34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1242 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e48 (43.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBelow high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e962 (32.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e905 (31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e57 (44.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e826 (31.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e136 (32.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e898 (31.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e64 (38.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e932 (32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e30 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSenior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e752 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e727 (25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25 (19.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e618 (23.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e134 (32.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e706 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e46 (27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e720 (24.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e32 (29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePIR (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e512 (17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e496 (17.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 (12.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e460 (17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e52 (12.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e482 (17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e30 (17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e500 (17.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12 (10.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.152\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1672 (55.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1615 (56.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e57 (44.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1476 (57.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e196 (47.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1590 (56.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e82 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1610 (55.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e62 (56.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e820 (27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e765 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55 (43.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e654 (25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e166 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e764 (26.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e56 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e784 (27.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e36 (32.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1546 (51.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1523 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23 (18.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1396 (53.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e150 (36.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1490 (52.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e56 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1504 (52.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e42 (38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1458 (48.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1353 (47.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e105 (82.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1194 (46.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e264 (63.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1346 (47.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e112 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1390 (48.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e68 (61.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLU (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e982 (32.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e965 (33.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e876 (33.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e106 (25.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e938 (33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e44 (26.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e938 (32.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e44 (40.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrediabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1482 (49.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1453 (50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1258 (48.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e224 (54.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1416 (49.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e66 (39.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1430 (49.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e52 (47.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e540 (18.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e458 (15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82 (64.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e456 (17.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e84 (20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e482 (17.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e58 (34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e526 (18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e14 (12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"15\"\u003eNGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; PIR: poverty-to-income ratio; BMI: body mass index; AMD: age-related macular degeneration; DR: diabetic retinopathy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAssociation between blood glucose and ocular diseases\u003c/h2\u003e\u003cp\u003eAccording to the results presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, in the unadjusted model 1, compared to the NGR group, patients with DM exhibited a significantly increased risk of ocular diseases. The risk of DR was eight times higher in the DM group than in the NGR group (OR\u0026thinsp;=\u0026thinsp;8.189, 95%CI: 2.687\u0026ndash;24.96), and cataracts (OR\u0026thinsp;=\u0026thinsp;2.134, 95%CI: 1.304\u0026ndash;3.492) and glaucoma (OR\u0026thinsp;=\u0026thinsp;2.734, 95%CI: 1.588\u0026ndash;4.708) were also significantly elevated. Although the risk of AMD tended to increase with elevated blood glucose levels, no statistically significant difference was observed (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In model 2, adjusted for age, sex, and marital status, only the risk of DR remained significantly increased in the DM group compared to the NGR group (OR\u0026thinsp;=\u0026thinsp;6.655, 95%CI: 1.976\u0026ndash;22.420, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), while changes in the risks of other ocular diseases were not significant. In model 3, although the risks of various ocular diseases showed an increasing trend with elevated blood glucose levels, none reached statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, RCS analysis further revealed a nonlinear relationship between blood glucose levels and DR, cataracts, and glaucoma (\u003cem\u003ep\u003c/em\u003e-non-linear\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, the risk of DR increased sharply when blood glucose levels exceeded 104.63 mg/dL \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e, while the risk of cataracts began to increase significantly when blood glucose levels surpassed163.92 mg/dL (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. The risk of glaucoma showed a gradual increasing trend after blood glucose levels exceeded 104.63 mg/dL (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). For AMD, elevated blood glucose levels had almost no significant impact on the risk of the disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\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\u003eAssociation between blood glucose and ocular diseases.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eexposure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1 OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 2 OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eModel 3 OR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ereference\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\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.644(0.190\u0026ndash;2.177)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.562(0.154\u0026ndash;2.054)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.392(0.040\u0026ndash;3.820)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.282\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.189(2.687\u0026ndash;24.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.655(1.976\u0026ndash;22.420)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.038(0.369-25.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCataracts\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ereference\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\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.530(0.757\u0026ndash;3.092)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.189(0.604\u0026ndash;2.339)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.116(0.409\u0026ndash;3.042)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.751\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.134(1.304\u0026ndash;3.492)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.405(0.872\u0026ndash;2.263)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.329(0.635\u0026ndash;2.779)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.308\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGlaucoma\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ereference\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\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.888(0.464-1.700)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.655(0.337\u0026ndash;1.278)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.595(0.231\u0026ndash;1.532)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.179\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.734(1.588\u0026ndash;4.708)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.710(0.909\u0026ndash;3.215)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.333(0.567\u0026ndash;3.129)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAMD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ereference\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\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.271(0.645\u0026ndash;2.508)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.952(0.969\u0026ndash;3.930)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.889(0.704\u0026ndash;5.072)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.230(0.468\u0026ndash;3.232)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.257(0.955\u0026ndash;5.332)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.965(0.561\u0026ndash;6.883)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.185\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNGR: normal glucose regulation; Pre-DM: prediabetes diabetes mellitus; DM: diabetes mellitus; AMD: age-related macular degeneration; DR: diabetic retinopathy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup analysis\u003c/h2\u003e\u003cp\u003eA subgroup analysis was performed to gain insight into the relationship between blood glucose levels and the risk of different ocular diseases. The results indicated that among patients with DR, there were significant interactions between marital status, drinking status, hypertension, and PIR with blood glucose levels (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Additionally, in the context of cataracts, the interaction between blood glucose and hypertension was also significant (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.013) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In the glaucoma group, factors such as sex, alcohol consumption status, hypertension, and educational level significantly influenced the relationship between blood glucose levels and the risk of glaucoma (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). However, for AMD, the association between blood glucose levels and the risk of AMD remained consistent across different subgroups, with no significant interactions observed (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eRanking the importance of risk factors for ocular diseases\u003c/h2\u003e\u003cp\u003eIn this study, XGBoost algorithm was employed to rank the importance of multiple variables including gender, education level, marital status, drinking status, BMI, PIR, hypertension, depression and blood glucose level. The results indicated that blood glucose level had a significant impact on predictions among different ocular diseases. Specifically, it was ranked first among DR, third among cataracts, second among Glaucoma, and third among AMD, all of which are top positions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is the first large-scale investigation to explore the association between blood glucose levels and ocular diseases based on the NHANES database. Our findings reveal that higher blood glucose levels are significantly associated with an increased risk of DR, cataracts, and glaucoma. However, no such association was observed between blood glucose levels and AMD. RCS analysis demonstrated nonlinear relationships between blood glucose levels and the risk of DR, cataracts, and glaucoma. Subgroup analyses indicated that the interaction between hypertension and blood glucose levels in influencing the risk of DR, cataracts, and glaucoma warrants special attention. Additionally, the XGBoost algorithm revealed that blood glucose levels are the most important predictor for DR risk and have good predictive power for cataracts, glaucoma, and AMD. These findings have important clinical implications and provide new evidence for the role of blood glucose control in the prevention of ocular diseases.\u003c/p\u003e\u003cp\u003eDR is one of the most common ocular complications of diabetes, and its incidence is closely related to poor glycemic control[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A systematic analysis involving 16,259 patients with type 2 diabetes (T2D) showed that a high triglyceride glucose (TyG) index is associated with an increased risk of DR in T2D patients[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another cross-sectional study based on the Chinese population demonstrated that among patients with T2D, those in the higher quartiles of TyG-WHR had an increased risk of DR (OR\u0026thinsp;=\u0026thinsp;1.223, 95%CI: 1.078\u0026ndash;1.387, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), emphasizing that TyG-WHR could potentially serve as a valuable and reliable biomarker for DR[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This study further revealed a significant correlation between higher blood glucose levels and an increased risk of DR. Chronic hyperglycemia can induce the breakdown of the blood-retinal barrier, increase the production of reactive oxygen species within retinal cells, and trigger autophagy and aging of retinal ganglion cells[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, hyperglycemia can also initiate chronic low-grade inflammation in the retina, which subsequently impairs retinal function[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This suggests that glycemic management may be essential in the prevention of DR. A multi-cohort prospective study has shown that long-term use of metformin and sulfonylureas can effectively reduce the risk of DR in diabetic patients[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The RCS analysis in this study showed that the risk of DR increases sharply when blood glucose levels exceed 104.63 mg/dL. This result emphasizes that the risk of DR significantly increases even before reaching the diagnostic threshold for diabetes. It is evident that middle-aged and elderly people need to monitor their blood glucose levels more carefully, and their target values should be lower than those of younger people. Also strengthening lifestyle interventions in the middle-aged and elderly population, such as dietary control, exercise and regular fundus screening, may be a key strategy to reduce the incidence of DR[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to DR, cataracts are also ocular disease closely related to blood glucose levels. Cataracts are a common age-related eye problem, however, the impact of high blood glucose on the lens makes diabetic patients significantly more susceptible to cataracts[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Wei et al., using the NHANES database, found that higher TyG index and its related indicators were significantly positively correlated with the presence of cataracts (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our study indicates that high blood glucose is an important risk factor for the development of cataracts, especially when blood glucose levels reach above 163.92 mg/dL, significantly increasing the risk of cataracts. Cataracts caused by high blood glucose may be related to the elevation of inflammation and oxidative stress levels in lens epithelial cells[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Elevated blood glucose leads to the conversion of glucose to sorbitol in the lens, and the accumulation of sorbitol causes an increase in osmotic pressure, resulting in swelling of lens epithelial cells, ultimately making the lens opaque[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Additionally, our findings reveal that long-term uncontrolled blood glucose levels increase the risk of cataracts. Therefore, it is crucial to reduce blood glucose levels through dietary adjustments, regular exercise, and anti-diabetic medications to slow down or prevent the development of cataracts.\u003c/p\u003e\u003cp\u003eGlaucoma is another ocular disease associated with high blood glucose levels, characterized mainly by increased intraocular pressure, which subsequently damages the optic nerve[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Our study found that higher blood glucose levels are closely related to the occurrence of glaucoma. However, a Mendelian randomization study based on European and East Asian populations showed no causal relationship between fasting blood glucose and the risk of primary open-angle glaucoma, which contrasts with our findings[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Another cohort study based on the Korean national population demonstrated that high fasting blood glucose is associated with an increased risk of open-angle glaucoma (HR\u0026thinsp;=\u0026thinsp;2.189, 95%CI: 1.779\u0026ndash;2.695)[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. A Mendelian randomization study based on the Japanese population also observed a significant correlation between fasting blood glucose and primary open-angle glaucoma (OR\u0026thinsp;=\u0026thinsp;1.48, 95% CI: 1.10\u0026ndash;1.79)[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The discrepancy in these results could be due to differences in population sources and disease types, and therefore, the causal relationship between them still requires further prospective studies. Additionally, our study found that the risk of glaucoma shows an upward trend in the pre-diabetic stage. This is consistent with the results of Zhao et al., where participants without diabetes but with higher fasting blood glucose were more likely to develop glaucoma[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This suggests that in pre-diabetic patients, glaucoma screening should be strengthened in clinical practice. This not only aids in the early detection of glaucoma to prevent vision loss but also provides a new perspective for the treatment of glaucoma.\u003c/p\u003e\u003cp\u003eAMD is one of the leading causes of irreversible vision loss in the elderly population[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Our study found that although there is an increasing trend in the risk of AMD with elevated blood glucose levels, no statistically significant difference was observed (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The relationship between blood glucose levels and AMD remains controversial. A Mendelian randomization study indicated that genetically predicted glycemic traits were not significantly associated with late-stage AMD[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. However, another systematic review found a significant correlation between diabetes and an increased risk of AMD (OR, 1.05; 95% CI, 1.00-1.14)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Additionally, research has shown that treatment of diabetes with metformin can significantly reduce the risk of AMD[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The lack of statistically significant findings in our study may be attributed to an insufficient sample size, which failed to adequately capture the subtle effects of elevated blood glucose on AMD risk. Furthermore, previous studies often only adjusted for age and sex, failing to effectively exclude other potential confounding factors, which may have affected the accuracy of their conclusions.\u003c/p\u003e\u003cp\u003eThe subgroup analyses of this study were based on sex, marital status, educational level, PIR, drinking status, depression, and hypertension to explore the potential influences and interactions between blood glucose and ocular diseases. Differences in sex lead to varying hormone levels, which subsequently affect inflammation and disease susceptibility[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additionally, social determinants of health based on education and economics may be associated with ocular diseases such as DR, and identifying these determinants can aid in early screening and the development of more comprehensive prevention and treatment plans[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Hypertension and depression were included as they are known as risk factors for several ocular diseases and may interact with blood glucose levels[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, by analyzing different subgroups and their interactions, this study provides a more nuanced understanding of the relationship between blood glucose and ocular diseases in various populations, offering important bases for formulating precise prevention and intervention strategies.\u003c/p\u003e\u003cp\u003eThis study has its strengths and limitations. Firstly, this study is the first to use a large, nationally representative sample to investigate the relationship between blood glucose levels and ocular diseases. However, as a cross-sectional study, it cannot establish a causal relationship between blood glucose and ocular diseases. Large-scale prospective studies are needed to further demonstrate the relationship. Secondly, the study relied on self-reported diagnoses of ocular diseases, which may lead to classification bias and an underestimation of prevalence, as some severe cases may not have participated in the survey. Finally, although this study employed weighted multivariate logistic regression analysis to adjust for multiple confounding factors, other potential confounders such as genetic susceptibility or medication use may still influence the relationship between blood glucose and ocular diseases.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, higher blood glucose levels are associated with an increased risk of DR, cataracts, and glaucoma, but no statistically significant difference was found with the increased risk of AMD. Thresholds of blood glucose were observed, where the risk of DR, cataracts, and glaucoma increased when blood glucose levels exceeded 104.63 mg/dL or 163.92 mg/dL. Controlling blood glucose levels in both pre-diabetic and diabetic phases may be an effective measure for preventing the onset of ocular diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed in this study are available at the NHANES database (https://wwwn.cdc.gov/nchs/nhanes/search/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no potential competing interests to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXW and LW conceptualized and collected and interpreted the data. XW wrote the original draft. LW reviewed and edited the draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, Stein C, Basit A, Chan JCN, Claude Mbanya J\u003cem\u003e et al\u003c/em\u003e: Erratum to \u0026quot;IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045\u0026quot; [Diabetes Res. Clin. Pract. 183 (2022) 109119]. Diabetes research and clinical practice.\u003cem\u003e \u003c/em\u003e2023; 204:110945; doi:10.1016/j.diabres.2023.110945\u003c/li\u003e\n\u003cli\u003eWong TY, Sabanayagam C: Strategies to Tackle the Global Burden of Diabetic Retinopathy: From Epidemiology to Artificial Intelligence. 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Clinical \u0026amp; experimental ophthalmology.\u003cem\u003e \u003c/em\u003e2021; 49:118-127; doi:10.1111/ceo.13892\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ocular disorder, glucose, NHANES","lastPublishedDoi":"10.21203/rs.3.rs-6981822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6981822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe aim of this study was to investigate the relationship between blood glucose levels and risk of ocular diseases, including diabetic retinopathy (DR), cataract, glaucoma, and age-related macular degeneration (AMD) in the middle-aged and elderly population.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2008 were used for this study. The correlation between blood glucose and risk of ocular disease was examined using weighted multivariate logistic regression analysis, restricted cubic spline curve (RCS) plots, and subgroup analysis. The XGBoost algorithm was further used to rank the importance of the influencing factors.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the unadjusted model, higher blood glucose levels were significantly associated with an increased risk of DR (OR\u0026thinsp;=\u0026thinsp;8.189, 95% CI: 2.687\u0026ndash;24.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), cataracts (OR\u0026thinsp;=\u0026thinsp;2.134, 95% CI: 1.304\u0026ndash;3.492, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), and glaucoma (OR\u0026thinsp;=\u0026thinsp;2.734, 95% CI: 1.588\u0026ndash;4.708, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). RCS analysis further revealed that the risk of DR and glaucoma increased when blood glucose levels exceeded 104.63 mg/dL, while the risk of cataracts began to increase significantly when blood glucose levels surpassed 163.92 mg/dL. The XGBoost algorithm indicated that blood glucose was a prominent predictor in the development of ocular diseases.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHigher blood glucose levels are associated with an increased risk of ocular diseases, suggesting that early glycemic control may be an effective measure for preventing the onset of ocular diseases in middle-aged and elderly populations.\u003c/p\u003e","manuscriptTitle":"Association of blood glucose levels with ocular diseases in the middle-aged and elderly population: results from the NHANES 2005-2008","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 12:49:02","doi":"10.21203/rs.3.rs-6981822/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a86529e8-8418-4aa4-9a01-e7c5679b2fdd","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-23T10:40:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-04 12:49:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6981822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6981822","identity":"rs-6981822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}