Sex-specific association of plasma vitamin E with homocysteine levels in Chinese middle-aged and older men and women: evidence from four large population based studies

Sex-specific association of plasma vitamin E with homocysteine levels in Chinese middle-aged and older men and women: evidence from four large population based studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sex-specific association of plasma vitamin E with homocysteine levels in Chinese middle-aged and older men and women: evidence from four large population based studies Fang-Fei You, Yi-Ning Gao, Qiang-Qiang He, Ze-Na Huang, Jian Gao, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8483180/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Blood homocysteine (Hcy) levels have become a sensitive predictor of the development of cardiovascular disease. Few studies have reported the relationship between plasma vitamin E and Hcy. We aim to conduct an age- and sex-stratified investigation of the association between vitamin E status and Hcy levels in a large nationwide sample in China. Methods We conducted a cross-sectional study including 15,842 Chinese adults. The exposure variable was plasma vitamin E. The outcome variables included homocysteine level and hyperhomocysteinemia. Multiple linear models and multivariable logistic regression were performed to evaluate the relation between plasma vitamin E and homocysteine. Restricted cubic spline was conducted to examine the non-linear relationship. Results In men, the association between plasma vitamin E and homocysteine level followed a U-shape ( p for nonlinearity < 0.001). Compared with plasma vitamin E value of 8.5 ~ 15.9 ug/ml, the risk of hyperhomocysteinemia increased for values lower than 8.5 ug/ml (OR: 1.33 (1.10,1.60), p = 0.002) or higher than 15.9 ug/ml (OR: 1.77 (1.25, 2.50), p = 0.001) in < 65 year-old adults. In men ≥ 65 years old, participants with plasma vitamin E less than 8.3 ug/ml had no significantly associated with hyperhomocysteinemia (OR: 1.22 (1.04,1.43), p = 0.015). Among women, however, no nonlinear relationship was found regardless of age. ( p for nonlinearity > 0.05), the dose-response relationship between vitamin E and homocysteine showed an L-shape. Conclusions Sex-specific associations between plasma vitamin E and homocysteine levels or hyperhomocysteinemia were found. The relationship was U-shaped in men and L-shaped in women. In contrast to the differences observed between sexes, the association between vitamin Eand homocysteine remained consistent across age groups. Plasma Vitamin E Homocysteine Level Hyperhomocysteinemia prevention Figures Figure 1 Figure 2 Highlights We used a large national database of Chinese middle-aged and older men and women. In men, the association between plasma vitamin E and homocysteine level followed a U-shape while a L-shape in women. Sex-specific associations between plasma vitamin E and homocysteine levels, as well as hyperhomocysteinemia, were found regardless of age. What is already known on this topic Vitamin E is a fat-soluble antioxidant that inhibits enzymes associated with inflammatory responses and has been reported to be beneficial in the treatment of cardiovascular disease. Previous studies have shown that supplementation with folic acid and vitamin E in patients with acute myocardial infarction and high plasma homocysteine concentrations significantly improved plasma antioxidant capacity and endothelial function. However, the association between vitamin E on homocysteine levels remains unclear, underscoring the need for age- and sex-specific thresholds. What this study adds In this large population-based study among middle-aged and elder adults in China, we revealed a sex-specific association between plasma vitamin E cand homocysteine levels or hyperhomocysteinemia. In men, plasma vitamin E showed a U-shaped association with both homocysteine levels and hyperhomocysteinemia. In women, plasma vitamin E showed a L shape. In contrast to the sex difference, the association between vitamin E and homocysteine was consistent across the age groups. Our findings warrant further investigation in longitudinal study. If further confirmed, this implies that optimizing plasma vitamin E levels may provide a sex-specific approach to lowering homocysteine levels.. Introduction Homocysteine (Hcy) is an important intermediate in the methionine cycle and cysteine metabolism [ 1 ]. When the homocysteine concentration in the blood exceeds 15 µmol/L, it is known as hyperhomocysteinemia[ 2 ]. Over the past decade, elevated homocysteine has been regarded as a marker for cardiovascular disease and a risk factor for stroke and heart disease [ 3 ]. In addition, elevated plasma homocysteine has a significant synergistic effect on hypertension. A study including more than 10,000 Americans showed that hypertension combined with elevated Hcy significantly increased the risk of stroke [ 4 ]. These may be related to the fact that Hcy exacerbates vascular oxidative stress [ 5 ] and impairs vasodilatory function [ 6 ]. Therefore, a comprehensive understanding of the factors influencing Hcy is of great significance in reducing the incidence of cardiovascular disease. Homocysteine, an important intermediate in the methionine cycle and cysteine metabolism, is a sulfur-containing, nonessential amino acid.[ 1 ]. The most common cause of hyperhomocysteinemia is defective enzymes related to homocysteine metabolism, with the more common enzyme being cystathionine-beta-synthase (CBS). When CBS fails, homocysteine cannot be converted to cystathionine, resulting in elevated homocysteine levels [ 7 ]. Dietary factors affecting Hcy levels include inadequate intake of cofactors involved in homocysteine metabolism such as vitamins B6 and B 12 [ 8 ]. Also, a high methionine diet induces homocysteine formation [ 9 ]. Unhealthy lifestyles, such as prolonged alcohol consumption, smoking, drinking strong tea, lack of exercise, and sedentary behavior, may also lead to elevated plasma Hcy levels [ 10 ]. In addition, chronic renal failure [ 11 ], hypothyroidism, [ 12 ] genetic polymorphism[ 13 ] and malignant tumors [ 14 ] can lead to hyperhomocysteinemia. Vitamin E is a fat-soluble antioxidant, which reduces levels of oxidative stress markers and inhibits enzymes associated with inflammatory responses [ 15 ], and has been reported to be beneficial in the treatment of cardiovascular disease, cancer, and Alzheimer's disease [ 16 ]. A previous study showed that hyperhomocysteinemia increases cardiovascular risk and impairs endothelial function through oxidative stress, which can be blocked by pretreatment with antioxidant vitamins [ 17 ]. Related research indicated that supplementation of folic acid and vitamin E to patients with acute myocardial infarction and high plasma homocysteine concentrations significantly improved plasma antioxidant capacity and endothelial function. This suggests that vitamin E may be accompanied by a synergistic homocysteine-lowering effect. However, the assosiation between vitamin E and homocysteine levels remains unclear [ 18 ] and the need for age- and sex-specific thresholds is emphasized. Herein, this study aims to examine the assosiation between plasma vitamin E and homocysteine levels, and further assess the relationship in subgroups defined by age and sex in a large sample of Chinese middle-aged and older adults. Methods Study Population Data were analyzed from 4 sources: the 2017 Nationwide nutrition and hypertension survey(2016YFC0903100), Nested case-control study on nutrition and stroke (NCT00794885), China Stroke Primary Prevention Trial (CSPPT; NCT00794885), and the China Precision Nutrition and Health KAP Real World Study (CPNAS; ChiCTR2100051983). Details concerning these datasets can be found elsewhere[ 19 – 24 ]. Written informed consent was obtained from all participants. This study was conducted following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. For this study, we excluded participants if they 1) had missing measurements of plasma vitamin E; 2) had missing measurements of homocysteine; 3) had missing key covariates or with implausible data. 4) The intervened population during the trial. Therefore, the final analysis included 15,843 participants. A flowchart showing the process of study population inclusion is shown in Figure S1 . Laboratory Assays Overnight fasting venous blood samples were obtained from each study participant at baseline. Serum folate and vitamin B 12 were measured by a commercial laboratory using a chemiluminescent immunoassay (New Industrial). Homocysteine (Hcy), fasting lipids, and fasting glucose were measured using automatic clinical analyzers (Beckman Coulter) at the core laboratory of the National Clinical Research Center for Kidney Disease, Nanfang Hospital, Guangzhou, China. Plasma vitamin E (alphatocopherol) was measured by liquid chromatography with tandem quadrupole mass spectrometers (LC-MS/MS) in a commercial lab (Beijing DIAN Medical Laboratory, China)[ 25 , 26 ]. Outcomes The study outcome was the homocysteine level, and hyperhomocysteinemia, defined as homocysteine ≥ 15 umol/L[ 2 ]. Covariates Sociodemographic characteristics included age (years), sex (male or female), marital status (never married; married; divorced or widowed), occupation (farmer or non-farmer), and education ( high school). The health behaviors included smoking (nonsmoker, former smoker, and current smoker), and alcohol consumption (nondrinker, former drinker, and current drinker). Other potential confounders were body mass index (BMI, kg/m 2 ; continuous), serum folate (ng/mL) and vitamin B 12 (pg/mL), Hypertension was defined as a physician-confirmed diagnosis or mean SBP/DBP ≥ 140/ 90 mmHg or the use of antihypertensive medications. Diabetes was defined as a physician-confirmed diagnosis or fasting plasma glucose ≥ 7.0 mmol/L or insulin injection. Hyperlipidemia was defined as a physician-confirmed diagnosis or a TC ≥ 6.2 mmol/L/, or TG ≥ 2.3mmol/L/, or LDL-C ≥ 4.1mmol/L or regular use of lipid-lowering medications. Coronary heart disease (CHD), stroke, cancer, and chronic kidney disease were identified based on self-reports from the participants . Statistical analysis For descriptive statistics, continuous variables were presented as mean (SD), and were compared using the Wilcoxon Rank tests or the Kruskal-Wallis tests. Categorical variables were presented as frequency (percentage) and were compared using the chi-squared tests or the t-tests. To evaluate the association between vitamin E and homocysteine levels, multiple linear models and multivariable logistic regression were performed. Model 1 represented the unadjusted model. Model 2 were adjusted for age, sex, occupation, education level, body mass index, smoking status, alcohol status, hypertension, diabetes, hyperlipidemia, coronary heart disease, stroke, cancer and chronic kidney disease. The results from the logistic regression analysis are presented as odds ratios (ORs) and 95% confidence intervals (CIs). We further used a restricted cubic spline to explore the potential dose-response pattern, selecting 3 knots (10th, 50th, and 90th percentiles of vitamin E) to smooth the curve. If the relationship was nonlinear, a threshold effect analysis was performed, which implies that we utilized logistic regression analysis on both sides of the inflection point to investigate the association between vitamin E and homocysteine levels. All analyses were stratified based on sex (male or female) and age (< 65 or ≥ 65 years). All statistical analyses were conducted using R version 4.2.0 (R Foundation for Statistical Computing), with a 2-tailed alpha value of 0.05 considered statistically significant. Results Participant Characteristics The final sample for analysis comprised 15,842 participants. The baseline characteristics of participants stratified by age and sex are shown in Table 1 . Compared to male participants younger than 65 years, male participants older than 65 years were more likely farmers, former smokers or drinkers, less people with higher education levels. These individuals were also more likely to have lower levels of BMI, and have a higher prevalence of stroke and CHD. Compared with female participants younger than 65 years, the participants who are 65 years or older were more likely farmers, less current drinkers, and more people with lower education levels and BMI. These individuals were also more likely to have a higher prevalence of hypertension, hyperglycemia, hyperlipidemia, stroke, and CHD. Table 1 Characteristics of study participants by age group and sex Variables Overall (N = 15842) Male(N = 7139) p Female(N = 8704) p < 65 year-old (N = 3468) ≥ 65 year-old (N = 3671) < 65 year-old (N = 4818) ≥ 65 year-old (N = 3885) Education(%) < High school 13079(82.6) 2518(72.6) 3165(86.2) < 0.001 3877(80.5) 3519(90.6) High school 668(4.2) 315(9.1) 96(2.6) 224(4.6) 33(0.8) Occupation(%) Farmer 11155(70.4) 1989(57.4) 2708(73.8) < 0.001 3482(72.3) 2976(76.6) < 0.001 Non-farmer 4687(29.6) 1479(42.6) 963(26.2) 1336(27.7) 909(23.4) Married status(%) Never married 159(1.0) 73(2.1) 33(0.9) < 0.001 43(0.9) 10(0.3) < 0.001 Married 13940(88.0) 3269(94.3) 3243(88.3) 4488(93.2) 2940(75.7) Divorced 116(0.7) 45(1.3) 15(0.4) 39(0.8) 17(0.4) Widowed 1611(10.2) 78(2.2) 374(10.2) 244(5.1) 915(23.6) BMI (mean (SD)) 25.52(3.78) 25.75(3.54) 24.45(3.54) < 0.001 26.02(3.90) 25.70(3.84) < 0.001 Smoking status(%) Non-smoker 11318(71.4) 1289(37.2) 1518(41.4) < 0.001 4737(98.3) 3774(97.1) < 0.001 Former smoker 1318(8.3) 515(14.9) 756(20.6) 15(0.3) 32(0.8) Current smoker 3206(20.2) 1664(48.0) 1397(38.1) 66(1.4) 79(2.0) Alcohol consumption(%) Non-drinker 11281(71.2) 1329(38.3) 1673(45.6) < 0.001 4527(94.0) 3752(96.6) < 0.001 Former drinker 715(4.5) 269(7.8) 371(10.1) 49(1.0) 26(0.7) Current drinker 3846(24.3) 1870(53.9) 1627(44.3) 242(5.0) 107(2.8) Hypertension (%) No 5725(36.1) 1170(33.7) 1295(35.3) 0.179 2177(45.2) 1083(27.9) < 0.001 Yes 10117(63.9) 2298(66.3) 2376(64.7) 2641(54.8) 2802(72.1) Hyperglycaemia (%) No 13298(83.9) 2903(83.7) 3044(82.9) 0.390 4244(88.1) 3107(80.0) < 0.001 Yes 2544(16.1) 565(16.3) 627(17.1) 574(11.9) 778(20.0) Hyperlipidemia (%) No 9870(62.3) 2167(62.5) 2676(72.9) < 0.001 2905(60.3) 2122(54.6) < 0.001 Yes 5972(37.7) 1301(37.5) 995(27.1) 1913(39.7) 1763(45.4) Stroke (%) No 15251(96.3) 3339(96.3) 3493(95.2) 0.022 4716(97.9) 3703(95.3) < 0.001 Yes 591(3.7) 129(3.7) 178(4.8) 102(2.1) 182(4.7) CHD (%) No 14700(92.8) 3276(94.5) 3344(91.1) < 0.001 4648(96.5) 3432(88.3) < 0.001 Yes 1142(7.2) 192(5.5) 327(8.9) 170(3.5) 453(11.7) Cancer (%) No 15785(99.6) 3464(99.9) 3663(99.8) 0.442 4789(99.4) 3869(99.6) 0.281 Yes 57(0.4) 4(0.1) 8(0.2) 29(0.6) 16(0.4) CKD (%) No 15574(98.3) 3390(97.8) 3607(98.3) 0.149 4752(98.6) 3825(98.5) 0.557 Yes 268(1.7) 78(2.2) 64(1.7) 66(1.4) 60(1.5) Folate, ng/mL (mean (SD)) 8.01(5.12) 7.78(5.42) 7.09(5.04) < 0.001 8.62(4.84) 8.32(5.10) 0.005 VB 12 , pg/mL (mean (SD)) 441.36(191.91) 429.21(191.05) 426.34(197.67) 0.534 457.42(186.63) 446.49(191.87) 0.007 VE, ug/ml (mean (SD)) 10.62(3.28) 10.28(3.27) 9.67(2.84) < 0.001 11.07(3.37) 11.26(3.31) 0.008 Hcy, umol/L (mean (SD)) 13.22(4.35) 13.91(4.78) 14.73(4.64) < 0.001 11.58(3.59) 13.23(3.83) < 0.001 CHD, coronary heart disease; CKD, chronic kidney disease; HCY, Homocysteine Association between plasma vitamin E and homocysteine levels Table 2 shows the association between plasma vitamin E and homocysteine levels among men and women, and sex differences were found. Compared with the reference quartile, Q1 group was associated with higher homocysteine levels in men (adjusted beta coefficient 0.73, 95%CI: 0.40 to 1.07, p < 0.001), but not in men (0.19, 95%CI: -0.04 to 0.42, p = 0.112). Figure 1 shows that the relationship of plasma vitamin E to homocysteine showed a U-shaped pattern in males and a gradual decrease in homocysteine with increasing vitamin E levels in females, this finding was consistent across age groups (Table S1 ) . Table 2 Association between plasma vitamin E and homocysteine level among male and female N Crude model Adjusted model beta(95%CI) a p beta(95%CI) a p Male Per 1 SD 7139 -0.19(-0.31,-0.08) 0.001 -0.04(-0.16,0.08) 0.494 Q1 (< 7.7 ug/ml) 1428 1.24(0.89,1.59) < 0.001 0.73(0.40,1.07) < 0.001 Q2 (7.7 ~ 9.0 ug/ml) 1428 0.07(-0.27,0.42) 0.674 0.05(-0.27,0.38) 0.750 Q3 (9.0 ~ 10.2 ug/ml) 1410 Ref. Ref. Q4 (10.2 ~ 11.9 ug/ml) 1421 0.11(-0.23,0.46) 0.516 0.11(-0.22,0.44) 0.504 Q5 (≥ 11.9 ug/ml) 1452 0.27(-0.08,0.61) 0.129 0.28(-0.06,0.62) 0.108 P for trend b 0.129 0.969 Female Per 1 SD 8703 0.01(-0.06,0.09) 0.742 0.19(-0.04,0.42) 0.112 Q1 (< 8.7 ug/ml) 1741 0.29(0.04,0.55) 0.022 0.07(-0.16,0.31) 0.556 Q2 (8.7 ~ 10.1 ug/ml) 1646 0.03(-0.23,0.28) 0.846 0.06(-0.17,0.30) 0.596 Q3 (10.1 ~ 11.4 ug/ml) 1745 Ref. Ref. Q4 (11.4 ~ 13.2 ug/ml) 1803 0.20(-0.05,0.45) 0.114 0.09(-0.14,0.32) 0.442 Q5 (≥ 13.2 ug/ml) 1768 0.31(0.06,0.56) 0.016 0.03(-0.21,0.26) 0.835 P for trend b 0.065 0.950 a Beta coefficients were estimated using a general linear model. b Performed by treating vitamin E quartiles as a numeric variable. Crude model: unadjusted. Adjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB 12 Association between plasma vitamin E and hyperhomocysteinemia As is shown in Table 3 , compared with the reference quartile, adjusted ORs were 1.36(1.15,1.60), 0.94(0.79,1.12), 0.99(0.83,1.17), and 1.03(0.87,1.23) respectively in Q1, Q2, Q4 and Q5 group ( p for trend = 0.205) among males. In female participants, compared with Q3 group, the participants in Q1 had a OR of 1.27(1.04,1.55), while those in Q2-Q5 had no significantly higher risk of hyperhomocysteinemia. This result showed similar results when grouped by age(< 65 years old; ≥ 65 years old) (Table S2) . Table 3 Association between plasma vitamin E and hyperhomocysteinemia among male and female Events(%) Crude model Adjusted model OR(95%CI) a p OR(95%CI) a p Male Per 1 SD 2195(30.7) 0.90(0.85,0.95) < 0.001 0.97(0.92,1.04) 0.411 Q1 (< 7.7 ug/ml) 565(39.6) 1.62(1.39,1.90) < 0.001 1.36(1.15,1.60) < 0.001 Q2 (7.7 ~ 9.0 ug/ml) 403(28.2) 0.98(0.83,1.15) 0.767 0.94(0.79,1.12) 0.491 Q3 (9.0 ~ 10.2 ug/ml) 405(28.7) Ref. Ref. Q4 (10.2 ~ 11.9 ug/ml) 404(28.4) 0.99(0.84,1.16) 0.863 0.99(0.83,1.17) 0.883 Q5 (≥ 11.9 ug/ml) 418(28.8) 1.00(0.85,1.18) 0.970 1.03(0.87,1.23) 0.726 P for trend b 0.004 0.205 Female Per 1 SD 1294(14.9) 0.90(0.85,0.96) 0.001 0.91(0.85,0.97) 0.003 Q1 (< 8.7 ug/ml) 309(17.7) 1.41(1.17,1.69) < 0.001 1.27(1.04,1.55) 0.017 Q2 (8.7 ~ 10.1 ug/ml) 242(14.7) 1.12(0.93,1.36) 0.238 1.12(0.91,1.37) 0.285 Q3 (10.1 ~ 11.4 ug/ml) 232(13.3) Ref. Ref. Q4 (11.4 ~ 13.2 ug/ml) 261(14.5) 1.10(0.91,1.34) 0.313 1.11(0.91,1.36) 0.316 Q5 (≥ 13.2 ug/ml) 250(14.1) 1.07(0.89,1.30) 0.467 1.01(0.82,1.24) 0.945 P for trend b 0.552 0.658 a ORs were estimated using a logistic regression model. b Performed by treating vitamin E quartiles as a numeric variable. Crude model: unadjusted. Adjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB 12 Nonlinear associations between vitamin E and hyperhomocysteinemia To better explain the observed nonlinear association, we further analyzed vitamin E as a continuous variable using cubic spline regression adjusting for all covariates mentioned in the Methods section. As shown in Fig. 2 , there are significant nonlinear dose-response patterns between vitamin E and hyperhomocysteinemia in males and both age groups ( p for non-linear <0.001). Building upon these findings, a threshold effect analysis was conducted to further validate this U-shaped association. Compared with plasma vitamin E value of 8.5 ~ 15.9 ug/ml, the risk of hyperhomocysteinemia increased for values lower than 8.5 ug/ml (OR: 1.33(1.11,1.60), p = 0.002) or higher than 15.9 ug/ml (OR: 1.77(1.25,2.50), p = 0.001) in < 65-year-old adults. In men ≥ 65 years old, participants with plasma vitamin E less than 8.4 ug/ml had no significant relationship with hyperhomocysteinemia (OR: 1.06(0.86,1.30), p = 0.589) ( Table 4 ) . Among women ≥ 65 years old, participants with plasma vitamin E less than 8.5 ug/ml had risk of hyperhomocysteinemia (OR: 1.30(1.04,1.63), p = 0.024), however, no nonlinear relationship was found regardless of age. ( p for nonlinearity > 0.05). The dose-response relationship between vitamin E and homocysteine showed a L-shape. Table 4 Hyperhomocysteinemia versus different levels of plasma vitamin E Events(%) Crude model Adjusted model OR(95%CI) a p OR(95%CI) a p Male < 65 year-old Lower(< 8.5ug/ml) 316(30.2) 1.44(1.23,1.70) < 0.001 1.33(1.11,1.60) 0.002 Middle(8.9 ~ 15.9 ug/ml) 516(23.1) Ref. Ref. Higher(≥ 15.9 ug/ml) 64(34.8) 1.78(1.29,2.45) < 0.001 1.77(1.25,2.50) 0.001 ≥ 65 year-old Lower(< 8.4 ug/ml) 466(40.2) 1.09(0.91,1.32) 0.356 1.06(0.86,1.30) 0.589 Higher(≥ 8.4 ug/ml) 833(33.2) Ref. Ref. Female < 65 year-old Lower(< 10.7 ug/ml) 256(10.6) 1.35(1.17,1.56) < 0.001 1.17(1.00,1.37) 0.054 Higher(≥ 10.7 ug/ml) 237(9.8) Ref. Ref. ≥ 65 year-old Lower(< 8.5 ug/ml) 145(28.1) 1.62(1.31,1.99) < 0.001 1.30(1.04,1.63) 0.024 Higher(≥ 8.5 ug/ml) 656(19.5) Ref. Ref. a ORs were estimated using a logistic regression model. b Performed by treating vitamin E quartiles as a numeric variable. Crude model: unadjusted. Adjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB 12 Subgroup analyses We further performed exploratory subgroup analyses to assess the association between plasma vitamin E and the primary outcome in two groups of participants separated by the turning point of plasma vitamin E (Figure S2) . There were significant interactions BMI (< 24 vs. ≥24 kg/m 2 ) and Folic acid (< 6vs. ≥6 ng/mL) in women.( p for interactions < 0.05) Discussion To our knowledge, this is the first study to investigate the relationships between plasma vitamin E and homocysteine in a large Chinese population. In this cross-sectional study of 15,842 individuals, Sex-specific associations between plasma vitamin E concentration and homocysteine level or hyperhomocysteinemia were found. The relationship exhibited a U-shaped pattern in men and an L-shaped pattern in women . Vitamin E is an antioxidant that protects the body from oxidative damage caused by oxygen-derived free radicals [ 27 ]. Previous studies have shown that antioxidant vitamins can reverse the damage to vessels caused by hyperhomocysteinemia [ 28 ] and may also reduce homocysteine levels. A study by Can et al. showed that Hcy levels in the serum of arthritic rats declined after treatment with vitamin E [ 29 ]. In a trial of young patients with myocardial infarction, supplementation with folic acid and vitamin E significantly reduced homocysteine concentrations and improved vasodilatation [ 18 ]. Another study found that in male smokers, plasma Hcy levels were negatively correlated with vegetable intake, which includes vitamins C and E [ 30 ]. Our results are consistent with these studies, in current study, we found Hcy levels decreased with increasing plasma vitamin E in women. However, there have also been some indications that vitamin E does not affect Hcy levels [ 31 ]. For example, a study in athletes showed that after 2 months of vitamin E supplementation, Hcy concentrations were not affected, although plasma antioxidant capacity increased [ 32 ]. Therefore, more studies are needed to prove our findings. The underlying mechanism is related to the metabolism of Hcy, which is converted by the remethylation pathway and the transsulfuration pathway [ 33 ]. Among them, folate and vitamins are necessary for homocysteine remethylation [ 34 ]. Oxidative stress reduces the concentration of antioxidant vitamins and folic acid, preventing the conversion of Hcy to methionine, which ultimately leads to elevated Hcy [ 29 ]. Vitamin E may indirectly affect these pathways by reducing oxidative stress and preventing the oxidative destruction of folate[ 35 ]. In our study, vitamin E was associated with hyperhomocysteinemia regardless of gender. However, the results of subgroup analyses showed that in men, there was a U-shaped relationship between vitamin E and hyperhomocysteinemia, implying that either too high or too low a level of vitamin E increased the risk of hyperhomocysteinemia; whereas in women, we observed an L-shaped relationship between. A related study reported that higher serum vitamin E levels were associated with the progression of depressive symptoms in older men but not in older women [ 36 ]. However, Jeong et al. found that the relationship between vitamin E and depressive symptoms was only observed in young women and older men [ 37 ]. These findings suggest that the physiological functions of Vitamin E may vary across different sexes and ages. Similarly, High levels of vitamin E may have negative effects. A clinical trial suggests that long-term vitamin E supplementation does not prevent major cardiovascular events in patients with vascular disease or diabetes but may increase the risk of heart failure [ 38 ]. A meta-analysis of vitamin E supplements showed that high doses of vitamin E increased mortality [ 39 ]. The possible reason for this is that high concentrations of vitamin E lose their antioxidant effects and may lead to increased oxidative stress [ 40 ]. High doses of vitamin E may displace other fat-soluble antioxidants, such as gamma- and delta-tocopherols [ 41 ], lowering high-density lipoprotein (HDL 2 ) cholesterol [ 42 ], disrupting the balance of the antioxidant system, and increasing oxidative damage. Also, vitamin E may be associated with the production of alpha-tocopherol radicals [ 40 ], making it a pro-oxidant [ 43 ]. High concentrations of vitamin E may also inhibit glutathione S-transferase, a substance that helps detoxify endogenous toxins [ 44 ]. This may explain the finding of elevated homocysteine levels associated with Vitamin E exceeding a certain threshold. The possible reason for the gender difference is related to sex hormones. It should also be noted that both androgens and estrogens have antioxidant capacity [ 45 ]. Studies have shown a positive correlation between estrogen levels and serum vitamin E levels in women [ 46 ], whereas serum androgen levels are negatively correlated with serum vitamin E levels in men [ 47 ]. Therefore, when serum vitamin E levels are elevated, estrogen in women may counteract the oxidative damage caused by this high concentration of vitamin E. Strengths and limitations The current study has some distinct advantages. Firstly, we considered numerous covariates to adjust the model, and the results have a certain credibility. Meanwhile, all blood samples were tested in the same cycle using standardized protocols, which greatly reduced potential bias. Plasma vitamin E is more accurate as an internal exposure compared to dietary estimates of vitamin E levels. Finally, the large sample size based on the whole country gives the possibility of stratified and subgroup analysis. However, some limitations of the study should be noted. First, this is a cross-sectional study and could not demonstrate a causal relationship between plasma vitamin E and Hcy levels or HHcy prevalence. Second, although we have adjusted for several confounders, some potential confounding factors were not measured, such as environmental factors. Perspectives and clinical applications Hcy has been confirmed as an independent risk factor for cardiovascular and cerebrovascular diseases, and regulating Hcy is considered helpful for the primary prevention of CVD. The nutritional factors influencing Hcy mainly focus on B vitamins and folic acid, while the mechanisms by which vitamin E regulates Hcy and its oxidative stress response remain unclear, with limited basic and clinical evidence. This study reveals sex differences and nonlinear associations between vitamin E and Hcy in the population, suggesting that vitamin E status is highly likely to influence cardiovascular health by modulating Hcy, thereby expanding the target spectrum of “precision nutrition intervention [ 48 ]”. Large longitudinal studies or randomized controlled trials are needed to verify this relationship in the future. Conclusion In this large population-based study among middle-aged and elder adults in China, we revealed a sex-specific association between plasma vitamin E and homocysteine level or hyperhomocysteinemia. In males, plasma vitamin E showed a U-shaped association with both homocysteine level and hyperhomocysteinemia. But in females, plasma vitamin E showed an L shape. In contrast to the sex difference, the vitamin E- homocysteine association was consistent across the age groups. Our findings warrant further investigation in the longitudinal study. If further confirmed, it implies that optimizing plasma vitamin E levels maybe another way to lower homocysteine levels, which is sex-specific. Declarations Acknowledgements: We thank all the participants in the study and members of the survey teams in all the study centers. Members of the CPNAS collaborative group: a) China Nutrition and Health Food Association: Zhenjia Bian, Liangqiu Li, Ningling Sun, Xiaoshu Cheng, Hanping Shi, Jianping Li, Wenhua Ling, Jingang Yang, Guifan Sun, Binyan Wang, Huihui Bao, Chen Mao, Xianhui Qin. b) Steering committee: Gangqiang Ding, Junsheng Huo, Yong Huo, Dafang Chen, Yan Zhang, Ping Li, Guangyun Mao, Zengning Li, Xiaoliang Shu, Xiang Gao, Ming Liu, Pinning Feng, Xinzheng Lu, Yong Duan, Yu Fu, Jianlong Wu, Jiaman Ou, Xuli Wu, Xiao Huang, Ziyi Zhou, Shufang Xu, Mingli He, Hai Ma, Qing Dong. c) Project coordination group: Houxun Xing, Genfu Tang, Zhiping Li, Yun Song, Lishun Liu, Qiangqiang He, Ping Chen, Jiafeng Xu, Changrui Ou, Hehao Zhu, Jiaping Huan. Author Contributions: FF-Y and YN-G are joint first authors and had primary responsibility for writing the manuscript and performing the statistical analyses. FF-Y and YN-G contributed equally to this article. CM and H-PS directed the study. Q-QH, Z-NH, JG, and DL contributed to the data cleaning. J-FX, C-RO, X-SC, J-GY, N-LS, X-HQ, and J-PL contributed to the analysis or interpretation of the data. CM ( [email protected] ) and H-PS ( [email protected] ) should be considered corresponding authors. All authors critically reviewed the manuscript for important intellectual content. CM and H-PS are the study guarantors. The corresponding authors (CM and H-PS) attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All authors approved the final version to be published. Conflict of Interest Disclosures: The authors have reported that they have no relationships relevant to the contents of this paper to disclose. Funding/Support: This work was supported by the National Natural Science Foundation of China (82425052), and the Development and Reform Commission of Shenzhen Municipality [XMHT20220104055], [XMHT20240104002]. 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Cancer Causes Control 22(6):827–836. 10.1007/s10552-011-9753-4 Shi∗ BPXH (2022) Precision nutrition: concept, evolution, and future vision Precision Nutr 1(1), e00002 Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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04:32:31","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":204904,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8483180/v1/5803d66c5a8c97d88419cf7f.html"},{"id":100750431,"identity":"42a62d0e-ed44-42b6-8da5-b3db9b9bb206","added_by":"auto","created_at":"2026-01-21 04:32:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":414671,"visible":true,"origin":"","legend":"\u003cp\u003eDose response curves of vitamin E and homocysteine decline\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8483180/v1/f91b9ba0bebfbb5915bb04f2.png"},{"id":100750434,"identity":"93614257-7b27-41e9-999b-c050961a2794","added_by":"auto","created_at":"2026-01-21 04:32:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":296015,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDose response curves of vitamin E and hyperhomocysteinemia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA restricted cubic spline was fitted to model each curve, with 3 knots fixed at the 10th, 50th, and 90th percentiles for all smooth curves. Solid lines represent the point estimates of ORs for prevalence hyperhomocysteinemia, while shadows represent corresponding 95% CIs. \u003cem\u003ep\u003c/em\u003e values were calculated using the Anova test.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8483180/v1/15e65058437dbb280aebcb69.png"},{"id":100859862,"identity":"1902af1b-2772-4418-beaf-10732de77e82","added_by":"auto","created_at":"2026-01-22 07:33:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2256713,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8483180/v1/aef2b9ae-dfaf-4494-b9b3-6081a5747336.pdf"},{"id":100804073,"identity":"5f342d8a-d9f2-4009-8e80-1bebd288a2b0","added_by":"auto","created_at":"2026-01-21 14:36:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1290647,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8483180/v1/e36fdf676f9770680c54c304.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sex-specific association of plasma vitamin E with homocysteine levels in Chinese middle-aged and older men and women: evidence from four large population based studies","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eWe used a large national database of Chinese middle-aged and older men and women.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;In men, the association between plasma vitamin E and homocysteine level followed a U-shape while a L-shape in women.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;Sex-specific associations between plasma vitamin E and homocysteine levels, as well as hyperhomocysteinemia, were found regardless of age.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"What is already known on this topic","content":"\u003cp\u003eVitamin E is a fat-soluble antioxidant that inhibits enzymes associated with inflammatory responses and has been reported to be beneficial in the treatment of cardiovascular disease. Previous studies have shown that supplementation with folic acid and vitamin E in patients with acute myocardial infarction and high plasma homocysteine concentrations significantly improved plasma antioxidant capacity and endothelial function. However, the association \u0026nbsp;between vitamin E on homocysteine levels remains unclear, underscoring \u0026nbsp;the need for age- and sex-specific thresholds.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this large population-based study among middle-aged and elder adults in China, we revealed a sex-specific association between plasma vitamin E cand homocysteine levels or hyperhomocysteinemia. In men, plasma vitamin E showed a U-shaped association with both homocysteine levels and hyperhomocysteinemia. In women, plasma vitamin E showed a L shape. In contrast to the sex difference, the association between vitamin E and homocysteine was consistent across the age groups. Our findings warrant further investigation in longitudinal study. If further confirmed, this implies that optimizing plasma vitamin E levels may provide a sex-specific approach to lowering homocysteine levels..\u003c/p\u003e\n"},{"header":"Introduction","content":"\u003cp\u003eHomocysteine (Hcy) is an important intermediate in the methionine cycle and cysteine metabolism [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. When the homocysteine concentration in the blood exceeds 15 \u0026micro;mol/L, it is known as hyperhomocysteinemia[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Over the past decade, elevated homocysteine has been regarded as a marker for cardiovascular disease and a risk factor for stroke and heart disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, elevated plasma homocysteine has a significant synergistic effect on hypertension. A study including more than 10,000 Americans showed that hypertension combined with elevated Hcy significantly increased the risk of stroke [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These may be related to the fact that Hcy exacerbates vascular oxidative stress [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and impairs vasodilatory function [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, a comprehensive understanding of the factors influencing Hcy is of great significance in reducing the incidence of cardiovascular disease.\u003c/p\u003e \u003cp\u003eHomocysteine, an important intermediate in the methionine cycle and cysteine metabolism, is a sulfur-containing, nonessential amino acid.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The most common cause of hyperhomocysteinemia is defective enzymes related to homocysteine metabolism, with the more common enzyme being cystathionine-beta-synthase (CBS). When CBS fails, homocysteine cannot be converted to cystathionine, resulting in elevated homocysteine levels [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Dietary factors affecting Hcy levels include inadequate intake of cofactors involved in homocysteine metabolism such as vitamins B6 and B\u003csub\u003e12\u003c/sub\u003e [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Also, a high methionine diet induces homocysteine formation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Unhealthy lifestyles, such as prolonged alcohol consumption, smoking, drinking strong tea, lack of exercise, and sedentary behavior, may also lead to elevated plasma Hcy levels [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, chronic renal failure [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], hypothyroidism, [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] genetic polymorphism[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and malignant tumors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] can lead to hyperhomocysteinemia.\u003c/p\u003e \u003cp\u003eVitamin E is a fat-soluble antioxidant, which reduces levels of oxidative stress markers and inhibits enzymes associated with inflammatory responses [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and has been reported to be beneficial in the treatment of cardiovascular disease, cancer, and Alzheimer's disease [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A previous study showed that hyperhomocysteinemia increases cardiovascular risk and impairs endothelial function through oxidative stress, which can be blocked by pretreatment with antioxidant vitamins [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Related research indicated that supplementation of folic acid and vitamin E to patients with acute myocardial infarction and high plasma homocysteine concentrations significantly improved plasma antioxidant capacity and endothelial function. This suggests that vitamin E may be accompanied by a synergistic homocysteine-lowering effect. However, the assosiation between vitamin E and homocysteine levels remains unclear [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and the need for age- and sex-specific thresholds is emphasized.\u003c/p\u003e \u003cp\u003eHerein, this study aims to examine the assosiation between plasma vitamin E and homocysteine levels, and further assess the relationship in subgroups defined by age and sex in a large sample of Chinese middle-aged and older adults.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eData were analyzed from 4 sources: the 2017 Nationwide nutrition and hypertension survey(2016YFC0903100), Nested case-control study on nutrition and stroke (NCT00794885), China Stroke Primary Prevention Trial (CSPPT; NCT00794885), and the China Precision Nutrition and Health KAP Real World Study (CPNAS; ChiCTR2100051983). Details concerning these datasets can be found elsewhere[\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Written informed consent was obtained from all participants. This study was conducted following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. For this study, we excluded participants if they 1) had missing measurements of plasma vitamin E; 2) had missing measurements of homocysteine; 3) had missing key covariates or with implausible data. 4) The intervened population during the trial. Therefore, the final analysis included 15,843 participants. A flowchart showing the process of study population inclusion is shown in \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLaboratory Assays\u003c/h3\u003e\n\u003cp\u003eOvernight fasting venous blood samples were obtained from each study participant at baseline. Serum folate and vitamin B\u003csub\u003e12\u003c/sub\u003e were measured by a commercial laboratory using a chemiluminescent immunoassay (New Industrial). Homocysteine (Hcy), fasting lipids, and fasting glucose were measured using automatic clinical analyzers (Beckman Coulter) at the core laboratory of the National Clinical Research Center for Kidney Disease, Nanfang Hospital, Guangzhou, China. Plasma vitamin E (alphatocopherol) was measured by liquid chromatography with tandem quadrupole mass spectrometers (LC-MS/MS) in a commercial lab (Beijing DIAN Medical Laboratory, China)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe study outcome was the homocysteine level, and hyperhomocysteinemia, defined as homocysteine\u0026thinsp;\u0026ge;\u0026thinsp;15 umol/L[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eSociodemographic characteristics included age (years), sex (male or female), marital status (never married; married; divorced or widowed), occupation (farmer or non-farmer), and education (\u0026lt;\u0026thinsp;high school; high school or \u0026gt;\u0026thinsp;high school). The health behaviors included smoking (nonsmoker, former smoker, and current smoker), and alcohol consumption (nondrinker, former drinker, and current drinker). Other potential confounders were body mass index (BMI, kg/m\u003csup\u003e2\u003c/sup\u003e; continuous), serum folate (ng/mL) and vitamin B\u003csub\u003e12\u003c/sub\u003e (pg/mL), Hypertension was defined as a physician-confirmed diagnosis or mean SBP/DBP\u0026thinsp;\u0026ge;\u0026thinsp;140/ 90 mmHg or the use of antihypertensive medications. Diabetes was defined as a physician-confirmed diagnosis or fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L or insulin injection. Hyperlipidemia was defined as a physician-confirmed diagnosis or a TC\u0026thinsp;\u0026ge;\u0026thinsp;6.2 mmol/L/, or TG\u0026thinsp;\u0026ge;\u0026thinsp;2.3mmol/L/, or LDL-C\u0026thinsp;\u0026ge;\u0026thinsp;4.1mmol/L or regular use of lipid-lowering medications. Coronary heart disease (CHD), stroke, cancer, and chronic kidney disease were identified based on self-reports from the participants .\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor descriptive statistics, continuous variables were presented as mean (SD), and were compared using the Wilcoxon Rank tests or the Kruskal-Wallis tests. Categorical variables were presented as frequency (percentage) and were compared using the chi-squared tests or the t-tests. To evaluate the association between vitamin E and homocysteine levels, multiple linear models and multivariable logistic regression were performed. Model 1 represented the unadjusted model. Model 2 were adjusted for age, sex, occupation, education level, body mass index, smoking status, alcohol status, hypertension, diabetes, hyperlipidemia, coronary heart disease, stroke, cancer and chronic kidney disease. The results from the logistic regression analysis are presented as odds ratios (ORs) and 95% confidence intervals (CIs). We further used a restricted cubic spline to explore the potential dose-response pattern, selecting 3 knots (10th, 50th, and 90th percentiles of vitamin E) to smooth the curve. If the relationship was nonlinear, a threshold effect analysis was performed, which implies that we utilized logistic regression analysis on both sides of the inflection point to investigate the association between vitamin E and homocysteine levels. All analyses were stratified based on sex (male or female) and age (\u0026lt;\u0026thinsp;65 or \u0026ge;\u0026thinsp;65 years).\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using R version 4.2.0 (R Foundation for Statistical Computing), with a 2-tailed alpha value of 0.05 considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eThe final sample for analysis comprised 15,842 participants. The baseline characteristics of participants stratified by age and sex are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared to male participants younger than 65 years, male participants older than 65 years were more likely farmers, former smokers or drinkers, less people with higher education levels. These individuals were also more likely to have lower levels of BMI, and have a higher prevalence of stroke and CHD. Compared with female participants younger than 65 years, the participants who are 65 years or older were more likely farmers, less current drinkers, and more people with lower education levels and BMI. These individuals were also more likely to have a higher prevalence of hypertension, hyperglycemia, hyperlipidemia, stroke, and CHD.\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 study participants by age group and sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;15842)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMale(N\u0026thinsp;=\u0026thinsp;7139)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eFemale(N\u0026thinsp;=\u0026thinsp;8704)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" 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=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65 year-old\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;3468)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65 year-old\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;3671)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65 year-old\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;4818)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65 year-old\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;3885)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \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 \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13079(82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2518(72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3165(86.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3877(80.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3519(90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2095(13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e635(18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e410(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e717(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e333(8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e668(4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e315(9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96(2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e224(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11155(70.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1989(57.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2708(73.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3482(72.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2976(76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eNon-farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4687(29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1479(42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e963(26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1336(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e909(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarried status(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159(1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43(0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13940(88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3269(94.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3243(88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4488(93.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2940(75.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45(1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1611(10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78(2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e374(10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e244(5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e915(23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (mean (SD))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.52(3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.75(3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.45(3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.02(3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.70(3.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11318(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1289(37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1518(41.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4737(98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3774(97.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eFormer smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1318(8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e515(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e756(20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3206(20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1664(48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1397(38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79(2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol consumption(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11281(71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1329(38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1673(45.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4527(94.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3752(96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eFormer drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e715(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e269(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e371(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49(1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3846(24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1870(53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1627(44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e242(5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e107(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5725(36.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1170(33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1295(35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2177(45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1083(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10117(63.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2298(66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2376(64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2641(54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2802(72.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyperglycaemia (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13298(83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2903(83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3044(82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4244(88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3107(80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2544(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e565(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e627(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e574(11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e778(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyperlipidemia (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9870(62.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2167(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2676(72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2905(60.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2122(54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5972(37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1301(37.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e995(27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1913(39.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1763(45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStroke (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15251(96.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3339(96.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3493(95.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4716(97.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3703(95.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e591(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e178(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e102(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e182(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCHD (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14700(92.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3276(94.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3344(91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4648(96.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3432(88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1142(7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e192(5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e327(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e170(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e453(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15785(99.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3464(99.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3663(99.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4789(99.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3869(99.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4(0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCKD (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15574(98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3390(97.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3607(98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4752(98.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3825(98.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.557\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e268(1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78(2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64(1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e60(1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFolate, ng/mL (mean (SD))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.01(5.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.78(5.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.09(5.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.62(4.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.32(5.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVB\u003c/b\u003e\u003csub\u003e\u003cb\u003e12\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003epg/mL (mean (SD))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e441.36(191.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e429.21(191.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e426.34(197.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e457.42(186.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e446.49(191.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVE, ug/ml (mean (SD))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.62(3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.28(3.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.67(2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.07(3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.26(3.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHcy, umol/L (mean (SD))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.22(4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.91(4.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.73(4.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.58(3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.23(3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eCHD, coronary heart disease; CKD, chronic kidney disease; HCY, Homocysteine\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssociation between plasma vitamin E and homocysteine levels\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the association between plasma vitamin E and homocysteine levels among men and women, and sex differences were found. Compared with the reference quartile, Q1 group was associated with higher homocysteine levels in men (adjusted beta coefficient 0.73, 95%CI: 0.40 to 1.07, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but not in men (0.19, 95%CI: -0.04 to 0.42, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.112). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the relationship of plasma vitamin E to homocysteine showed a U-shaped pattern in males and a gradual decrease in homocysteine with increasing vitamin E levels in females, this finding was consistent across age groups \u003cb\u003e(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\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\u003eAssociation between plasma vitamin E and homocysteine level among male and female\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAdjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ebeta(95%CI) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ebeta(95%CI) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePer 1 SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.19(-0.31,-0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.04(-0.16,0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (\u0026lt;\u0026thinsp;7.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24(0.89,1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73(0.40,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2 (7.7\u0026thinsp;~\u0026thinsp;9.0 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07(-0.27,0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05(-0.27,0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3 (9.0\u0026thinsp;~\u0026thinsp;10.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (10.2\u0026thinsp;~\u0026thinsp;11.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11(-0.23,0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11(-0.22,0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5 (\u0026ge;\u0026thinsp;11.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27(-0.08,0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28(-0.06,0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csub\u003efor trend\u003c/sub\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePer 1 SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01(-0.06,0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19(-0.04,0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (\u0026lt;\u0026thinsp;8.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29(0.04,0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07(-0.16,0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2 (8.7\u0026thinsp;~\u0026thinsp;10.1 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03(-0.23,0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06(-0.17,0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3 (10.1\u0026thinsp;~\u0026thinsp;11.4 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (11.4\u0026thinsp;~\u0026thinsp;13.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20(-0.05,0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09(-0.14,0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5 (\u0026ge;\u0026thinsp;13.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.31(0.06,0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03(-0.21,0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csub\u003efor trend\u003c/sub\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eBeta coefficients were estimated using a general linear model.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003eb\u003c/sup\u003ePerformed by treating vitamin E quartiles as a numeric variable.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCrude model: unadjusted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAdjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB\u003csub\u003e12\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between plasma vitamin E and hyperhomocysteinemia\u003c/h2\u003e \u003cp\u003eAs is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, compared with the reference quartile, adjusted ORs were 1.36(1.15,1.60), 0.94(0.79,1.12), 0.99(0.83,1.17), and 1.03(0.87,1.23) respectively in Q1, Q2, Q4 and Q5 group (\u003cem\u003ep\u003c/em\u003e for trend\u0026thinsp;=\u0026thinsp;0.205) among males. In female participants, compared with Q3 group, the participants in Q1 had a OR of 1.27(1.04,1.55), while those in Q2-Q5 had no significantly higher risk of hyperhomocysteinemia. This result showed similar results when grouped by age(\u0026lt;\u0026thinsp;65 years old; \u0026ge; 65 years old) \u003cb\u003e(Table S2)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between plasma vitamin E and hyperhomocysteinemia among male and female\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEvents(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAdjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR(95%CI) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR(95%CI) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePer 1 SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2195(30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90(0.85,0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97(0.92,1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (\u0026lt;\u0026thinsp;7.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e565(39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62(1.39,1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.36(1.15,1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2 (7.7\u0026thinsp;~\u0026thinsp;9.0 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e403(28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98(0.83,1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94(0.79,1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3 (9.0\u0026thinsp;~\u0026thinsp;10.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e405(28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (10.2\u0026thinsp;~\u0026thinsp;11.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e404(28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99(0.84,1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99(0.83,1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5 (\u0026ge;\u0026thinsp;11.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e418(28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00(0.85,1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03(0.87,1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csub\u003efor trend\u003c/sub\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePer 1 SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1294(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90(0.85,0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91(0.85,0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (\u0026lt;\u0026thinsp;8.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e309(17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41(1.17,1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27(1.04,1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2 (8.7\u0026thinsp;~\u0026thinsp;10.1 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e242(14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12(0.93,1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12(0.91,1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3 (10.1\u0026thinsp;~\u0026thinsp;11.4 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232(13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (11.4\u0026thinsp;~\u0026thinsp;13.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e261(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10(0.91,1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11(0.91,1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5 (\u0026ge;\u0026thinsp;13.2 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e250(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07(0.89,1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01(0.82,1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csub\u003efor trend\u003c/sub\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eORs were estimated using a logistic regression model.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003eb\u003c/sup\u003ePerformed by treating vitamin E quartiles as a numeric variable.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCrude model: unadjusted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAdjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB\u003csub\u003e12\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eNonlinear associations between vitamin E and hyperhomocysteinemia\u003c/h2\u003e \u003cp\u003eTo better explain the observed nonlinear association, we further analyzed vitamin E as a continuous variable using cubic spline regression adjusting for all covariates mentioned in the Methods section. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, there are significant nonlinear dose-response patterns between vitamin E and hyperhomocysteinemia in males and both age groups (\u003cem\u003ep\u003c/em\u003e for non-linear \u0026lt;0.001). Building upon these findings, a threshold effect analysis was conducted to further validate this U-shaped association. Compared with plasma vitamin E value of 8.5\u0026thinsp;~\u0026thinsp;15.9 ug/ml, the risk of hyperhomocysteinemia increased for values lower than 8.5 ug/ml (OR: 1.33(1.11,1.60), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) or higher than 15.9 ug/ml (OR: 1.77(1.25,2.50), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) in \u0026lt;\u0026thinsp;65-year-old adults. In men\u0026thinsp;\u0026ge;\u0026thinsp;65 years old, participants with plasma vitamin E less than 8.4 ug/ml had no significant relationship with hyperhomocysteinemia (OR: 1.06(0.86,1.30), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.589) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among women\u0026thinsp;\u0026ge;\u0026thinsp;65 years old, participants with plasma vitamin E less than 8.5 ug/ml had risk of hyperhomocysteinemia (OR: 1.30(1.04,1.63), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), however, no nonlinear relationship was found regardless of age. (\u003cem\u003ep\u003c/em\u003e for nonlinearity\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The dose-response relationship between vitamin E and homocysteine showed a L-shape.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHyperhomocysteinemia versus different levels of plasma vitamin E\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\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e \u003cp\u003eEvents(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAdjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR(95%CI) \u003csup\u003ea\u003c/sup\u003e\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\u003eOR(95%CI) \u003csup\u003ea\u003c/sup\u003e\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\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\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\u003e\u003cb\u003e\u0026lt;\u0026thinsp;65 year-old\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\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\u003eLower(\u0026lt;\u0026thinsp;8.5ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e316(30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.44(1.23,1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.33(1.11,1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle(8.9\u0026thinsp;~\u0026thinsp;15.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e516(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\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\u003eHigher(\u0026ge;\u0026thinsp;15.9 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e64(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.78(1.29,2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.77(1.25,2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;65 year-old\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\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\u003eLower(\u0026lt;\u0026thinsp;8.4 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e466(40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09(0.91,1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.06(0.86,1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher(\u0026ge;\u0026thinsp;8.4 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e833(33.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\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\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\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\u003e\u003cb\u003e\u0026lt;\u0026thinsp;65 year-old\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\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\u003eLower(\u0026lt;\u0026thinsp;10.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e256(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.35(1.17,1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17(1.00,1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher(\u0026ge;\u0026thinsp;10.7 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237(9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\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\u003e\u003cb\u003e\u0026ge;\u0026thinsp;65 year-old\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\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\u003eLower(\u0026lt;\u0026thinsp;8.5 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145(28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.62(1.31,1.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.30(1.04,1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher(\u0026ge;\u0026thinsp;8.5 ug/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e656(19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\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\"\u003e\u003csup\u003ea\u003c/sup\u003eORs were estimated using a logistic regression model.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003ePerformed by treating vitamin E quartiles as a numeric variable.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCrude model: unadjusted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAdjusted model: adjusted for sex, age, education, occupation, marital status, smoking status, alcohol consumption, body mass index, hypertension, diabetes, hyperlipidemia, stroke, coronary heart disease, chronic kidney disease, folate, VB\u003csub\u003e12\u003c/sub\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analyses\u003c/h2\u003e \u003cp\u003eWe further performed exploratory subgroup analyses to assess the association between plasma vitamin E and the primary outcome in two groups of participants separated by the turning point of plasma vitamin E \u003cb\u003e(Figure S2)\u003c/b\u003e. There were significant interactions BMI (\u0026lt;\u0026thinsp;24 vs. \u0026ge;24 kg/m\u003csup\u003e2\u003c/sup\u003e) and Folic acid (\u0026lt;\u0026thinsp;6vs. \u0026ge;6 ng/mL) in women.( \u003cem\u003ep\u003c/em\u003e for interactions\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study to investigate the relationships between plasma vitamin E and homocysteine in a large Chinese population. In this cross-sectional study of 15,842 individuals, Sex-specific associations between plasma vitamin E concentration and homocysteine level or hyperhomocysteinemia were found. The relationship exhibited a U-shaped pattern in men and an L-shaped pattern in women .\u003c/p\u003e \u003cp\u003eVitamin E is an antioxidant that protects the body from oxidative damage caused by oxygen-derived free radicals [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Previous studies have shown that antioxidant vitamins can reverse the damage to vessels caused by hyperhomocysteinemia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and may also reduce homocysteine levels. A study by Can et al. showed that Hcy levels in the serum of arthritic rats declined after treatment with vitamin E [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In a trial of young patients with myocardial infarction, supplementation with folic acid and vitamin E significantly reduced homocysteine concentrations and improved vasodilatation [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Another study found that in male smokers, plasma Hcy levels were negatively correlated with vegetable intake, which includes vitamins C and E [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our results are consistent with these studies, in current study, we found Hcy levels decreased with increasing plasma vitamin E in women. However, there have also been some indications that vitamin E does not affect Hcy levels [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For example, a study in athletes showed that after 2 months of vitamin E supplementation, Hcy concentrations were not affected, although plasma antioxidant capacity increased [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, more studies are needed to prove our findings. The underlying mechanism is related to the metabolism of Hcy, which is converted by the remethylation pathway and the transsulfuration pathway [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Among them, folate and vitamins are necessary for homocysteine remethylation [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Oxidative stress reduces the concentration of antioxidant vitamins and folic acid, preventing the conversion of Hcy to methionine, which ultimately leads to elevated Hcy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Vitamin E may indirectly affect these pathways by reducing oxidative stress and preventing the oxidative destruction of folate[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, vitamin E was associated with hyperhomocysteinemia regardless of gender. However, the results of subgroup analyses showed that in men, there was a U-shaped relationship between vitamin E and hyperhomocysteinemia, implying that either too high or too low a level of vitamin E increased the risk of hyperhomocysteinemia; whereas in women, we observed an L-shaped relationship between. A related study reported that higher serum vitamin E levels were associated with the progression of depressive symptoms in older men but not in older women [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, Jeong et al. found that the relationship between vitamin E and depressive symptoms was only observed in young women and older men [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings suggest that the physiological functions of Vitamin E may vary across different sexes and ages. Similarly, High levels of vitamin E may have negative effects. A clinical trial suggests that long-term vitamin E supplementation does not prevent major cardiovascular events in patients with vascular disease or diabetes but may increase the risk of heart failure [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. A meta-analysis of vitamin E supplements showed that high doses of vitamin E increased mortality [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The possible reason for this is that high concentrations of vitamin E lose their antioxidant effects and may lead to increased oxidative stress [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. High doses of vitamin E may displace other fat-soluble antioxidants, such as gamma- and delta-tocopherols [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], lowering high-density lipoprotein (HDL\u003csub\u003e2\u003c/sub\u003e) cholesterol [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], disrupting the balance of the antioxidant system, and increasing oxidative damage. Also, vitamin E may be associated with the production of alpha-tocopherol radicals [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], making it a pro-oxidant [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. High concentrations of vitamin E may also inhibit glutathione S-transferase, a substance that helps detoxify endogenous toxins [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This may explain the finding of elevated homocysteine levels associated with Vitamin E exceeding a certain threshold. The possible reason for the gender difference is related to sex hormones. It should also be noted that both androgens and estrogens have antioxidant capacity [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Studies have shown a positive correlation between estrogen levels and serum vitamin E levels in women [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], whereas serum androgen levels are negatively correlated with serum vitamin E levels in men [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Therefore, when serum vitamin E levels are elevated, estrogen in women may counteract the oxidative damage caused by this high concentration of vitamin E.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe current study has some distinct advantages. Firstly, we considered numerous covariates to adjust the model, and the results have a certain credibility. Meanwhile, all blood samples were tested in the same cycle using standardized protocols, which greatly reduced potential bias. Plasma vitamin E is more accurate as an internal exposure compared to dietary estimates of vitamin E levels. Finally, the large sample size based on the whole country gives the possibility of stratified and subgroup analysis.\u003c/p\u003e \u003cp\u003eHowever, some limitations of the study should be noted. First, this is a cross-sectional study and could not demonstrate a causal relationship between plasma vitamin E and Hcy levels or HHcy prevalence. Second, although we have adjusted for several confounders, some potential confounding factors were not measured, such as environmental factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePerspectives and clinical applications\u003c/h2\u003e \u003cp\u003eHcy has been confirmed as an independent risk factor for cardiovascular and cerebrovascular diseases, and regulating Hcy is considered helpful for the primary prevention of CVD. The nutritional factors influencing Hcy mainly focus on B vitamins and folic acid, while the mechanisms by which vitamin E regulates Hcy and its oxidative stress response remain unclear, with limited basic and clinical evidence. This study reveals sex differences and nonlinear associations between vitamin E and Hcy in the population, suggesting that vitamin E status is highly likely to influence cardiovascular health by modulating Hcy, thereby expanding the target spectrum of \u0026ldquo;precision nutrition intervention [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u0026rdquo;. Large longitudinal studies or randomized controlled trials are needed to verify this relationship in the future.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this large population-based study among middle-aged and elder adults in China, we revealed a sex-specific association between plasma vitamin E and homocysteine level or hyperhomocysteinemia. In males, plasma vitamin E showed a U-shaped association with both homocysteine level and hyperhomocysteinemia. But in females, plasma vitamin E showed an L shape. In contrast to the sex difference, the vitamin E- homocysteine association was consistent across the age groups. Our findings warrant further investigation in the longitudinal study. If further confirmed, it implies that optimizing plasma vitamin E levels maybe another way to lower homocysteine levels, which is sex-specific.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe thank all the participants in the study and members of the survey teams in all the study centers. Members of the CPNAS collaborative group: a) China Nutrition and Health Food Association: Zhenjia Bian, Liangqiu Li, Ningling Sun, Xiaoshu Cheng, Hanping Shi, Jianping Li, Wenhua Ling, Jingang Yang, Guifan Sun, Binyan Wang, Huihui Bao, Chen Mao, Xianhui Qin. b) Steering committee: Gangqiang Ding, Junsheng Huo, Yong Huo, Dafang Chen, Yan Zhang, Ping Li, Guangyun Mao, Zengning Li, Xiaoliang Shu, Xiang Gao, Ming Liu, Pinning Feng, Xinzheng Lu, Yong Duan, Yu Fu, Jianlong Wu, Jiaman Ou, Xuli Wu, Xiao Huang, Ziyi Zhou, Shufang Xu, Mingli He, Hai Ma, Qing Dong. c) Project coordination group: Houxun Xing, Genfu Tang, Zhiping Li, Yun Song, Lishun Liu, Qiangqiang He, Ping Chen, Jiafeng Xu, Changrui Ou, Hehao Zhu, Jiaping Huan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eFF-Y and YN-G are joint first authors and had primary responsibility for writing the manuscript and performing the statistical analyses. FF-Y and YN-G contributed equally to this article. CM and H-PS directed the study. Q-QH, Z-NH, JG, and DL contributed to the data cleaning. J-FX, C-RO, X-SC, J-GY, N-LS, X-HQ, and J-PL contributed to the analysis or interpretation of the data. CM ([email protected]) and H-PS ([email protected]) should be considered corresponding authors. All authors critically reviewed the manuscript for important intellectual content. CM and H-PS are the study guarantors. The corresponding authors (CM and H-PS) attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All authors approved the final version to be published.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConflict of Interest Disclosures:\u0026nbsp;\u003c/strong\u003eThe authors have reported that they have no relationships relevant to the contents of this paper to disclose.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding/Support:\u0026nbsp;\u003c/strong\u003eThis work was supported by the National Natural Science Foundation of China (82425052), and the Development and Reform Commission of Shenzhen Municipality [XMHT20220104055], [XMHT20240104002].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eRole of the Funder/Sponsor:\u003c/strong\u003e The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAdditional Contributions:\u0026nbsp;\u003c/strong\u003eThe authors appreciate efforts made by the original data creators, depositors, copy right holders, and funders of the data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWu DF, Yin RX, Deng JL (2024) Homocysteine, hyperhomocysteinemia, and H-type hypertension. 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Cancer Causes Control 22(6):827\u0026ndash;836. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10552-011-9753-4\u003c/span\u003e\u003cspan address=\"10.1007/s10552-011-9753-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi\u0026lowast; BPXH (2022) Precision nutrition: concept, evolution, and future\u003c/span\u003e\u003cspan\u003e vision Precision Nutr 1(1), e00002\u003c/span\u003e\u003c/li\u003e\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":"Plasma Vitamin E, Homocysteine Level, Hyperhomocysteinemia prevention","lastPublishedDoi":"10.21203/rs.3.rs-8483180/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8483180/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eBlood homocysteine (Hcy) levels have become a sensitive predictor of the development of cardiovascular disease. Few studies have reported the relationship between plasma vitamin E and Hcy. We aim to conduct an age- and sex-stratified investigation of the association between vitamin E status and Hcy levels in a large nationwide sample in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study including 15,842 Chinese adults. The exposure variable was plasma vitamin E. The outcome variables included homocysteine level and hyperhomocysteinemia. Multiple linear models and multivariable logistic regression were performed to evaluate the relation between plasma vitamin E and homocysteine. Restricted cubic spline was conducted to examine the non-linear relationship.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn men, the association between plasma vitamin E and homocysteine level followed a U-shape (\u003cem\u003ep\u003c/em\u003e for nonlinearity\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared with plasma vitamin E value of 8.5\u0026thinsp;~\u0026thinsp;15.9 ug/ml, the risk of hyperhomocysteinemia increased for values lower than 8.5 ug/ml (OR: 1.33 (1.10,1.60), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) or higher than 15.9 ug/ml (OR: 1.77 (1.25, 2.50), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) in \u0026lt;\u0026thinsp;65 year-old adults. In men\u0026thinsp;\u0026ge;\u0026thinsp;65 years old, participants with plasma vitamin E less than 8.3 ug/ml had no significantly associated with hyperhomocysteinemia (OR: 1.22 (1.04,1.43), \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015). Among women, however, no nonlinear relationship was found regardless of age. (\u003cem\u003ep\u003c/em\u003e for nonlinearity\u0026thinsp;\u0026gt;\u0026thinsp;0.05), the dose-response relationship between vitamin E and homocysteine showed an L-shape.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSex-specific associations between plasma vitamin E and homocysteine levels or hyperhomocysteinemia were found. The relationship was U-shaped in men and L-shaped in women. In contrast to the differences observed between sexes, the association between vitamin Eand homocysteine remained consistent across age groups.\u003c/p\u003e","manuscriptTitle":"Sex-specific association of plasma vitamin E with homocysteine levels in Chinese middle-aged and older men and women: evidence from four large population based studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-21 04:32:26","doi":"10.21203/rs.3.rs-8483180/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":"7785e167-bdc2-4f98-9c97-fd6eeeadc706","owner":[],"postedDate":"January 21st, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-01T17:28:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T07:45:23+00:00","index":44,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-01T17:39:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-21 04:32:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8483180","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8483180","identity":"rs-8483180","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}