Obesity, hyperhomocysteinaemia and risk of chronic kidney disease: a population-based study

Obesity, hyperhomocysteinaemia and risk of chronic kidney disease: a population-based study Abstract Background Obesity is associated with increased risk of cardiovascular disease and chronic kidney disease (CKD). Hyperhomocysteinaemia refers to increased oxidative stress and has been associated with the risk of CKD. Objectives We investigated the association among body mass index (BMI), homocysteine level and impaired renal function in a Taiwanese adult population. Methods This was a retrospective cross-sectional study involving 24826 subjects who underwent a health check-up from January 2013 to December 2015. A multivariate linear regression model was developed to analyse the relationship among BMI, serum homocysteine and estimated glomerular filtration rate (eGFR). A multivariate logistic regression model was used to assess the relationship among weight categories, hyperhomocysteinaemia and CKD. Results The prevalence of CKD in the quartile groups of homocysteine were 2.5%, 2.7%, 3.4% and 5.2% (P < 0.01). For every one-unit increase in BMI (kg/m2), the eGFR decreased by 0.50 ml/min/1.73 m2. Overweight/obese subjects with high homocysteine levels had a higher odds ratio (OR) for CKD, as compared with normal weight subjects (1.84 versus 1.38, respectively; P < 0.01 versus P = 0.02, respectively). Overweight/obese female subjects with hyperhomocysteinaemia had an OR of 3.40 [P < 0.01; 95% confidence interval (CI): 2.06–5.61] for CKD; in males, the OR was 1.66 (P < 0.01; 95% CI: 1.38–1.99). Conclusions Patients who are overweight/obese with higher homocysteine levels have an increased risk of CKD, especially females. Additional studies exploring whether the effect of weight loss or homocysteine-lowering therapies such as folic acid, vitamin B12 supplements that may prevent or slow the progression of declining renal function, is warranted. Body mass index, chronic, glomerular filtration rate, homocysteine, inflammation, obesity, renal insufficiency Introduction Chronic kidney disease (CKD) poses a significant challenge in 21st century global health policy because of its emerging health and economic burden (1). Primary health care is important for CKD because of high global prevalence (11–13%) of stage 3 underdiagnosed and undertreated patients with CKD (2). In Taiwan, the prevalence of CKD is as high as 11.93%, reaching about 2.74 million patients, potentially resulting in a significant mortality rate because of cardiovascular diseases (CVD), and accounting for tremendous health care expenditures (3). Therefore, early identification of the risk factors for CKD is critical for preventing the development of kidney damage and adverse outcomes. At present, >2.1 billion people are overweight or obese worldwide. As overweight and obesity are the fifth leading cause of death worldwide, accounting for nearly 3.4 million deaths annually (4), the increasing prevalence should be considered in primary care setting. Obesity is strongly associated with diabetes and hypertension and was demonstrated as a risk factor for the development of CKD (5). The crucial pathogenic role of obesity-induced chronic renal disease may be related to excess nutrients in metabolic cells, leading to the activation of several bioactive mediators (6) and an increase in the endogenous production of proinflammatory cytokines (7). Homocysteine is an amino acid formed by the conversion of methionine to cysteine, and an elevated plasma homocysteine level has been recognized as an independent factor for CVD (8). Homocysteine is believed to impair implantation by interfering with oxidative injury to vascular endothelial cells, and their vascular integrity may contribute to intrarenal arteriosclerosis, along with a subsequent reduction in renal perfusion pressure (9) and eventually reduced estimated glomerular filtration rate (eGFR). Preliminary investigations suggest that elevated homocysteine levels may be a risk factor or risk marker of future CKD (10,11). However, the association between weight status and different plasma homocysteine levels in CKD is not yet well established. The purpose of this study was to determine the relationship between body mass index (BMI) and serum homocysteine levels in CKD and to evaluate other associated risk factors. Methods Subjects This cross-sectional study involved subjects aged ≥18 years who underwent annual heath check-ups at the Linkou (northern Taiwan) and Chiayi (southern Taiwan) branches of Chang Gung Memorial Hospital from January 2013 to December 2015. All subjects enrolled were factory workers from northern and southern Taiwan who participated in the annual health check-ups at Chang Gung Memorial Hospital Linkou or Chiayi branch. The general characteristics of the population were age ranging from 30 to 55 years and being predominantly male. Each subject was invited to answer the questionnaires regarding his or her personal and past medical history. Trained nurses provided assistance while the participants were answering the questionnaire during the health examination. The original number of participants was 29728, and 3828 of them were excluded because of incomplete answers to the questionnaire. Among the remaining participants, 152 pregnant women and 922 participants who reported with underlying chronic diseases that might alter the metabolic state or kidney function tests, such as thyroid or hypothalamic diseases, adrenal disease, renal cancer, glomerulonephritis, renal failure on haemodialysis or peritoneal dialysis, liver cirrhosis, or use of diuretic renal replacement therapy were also excluded. The remaining 24826 participants were enrolled in this study. Informed consent was obtained from all participants. The Institutional Review Board of Chang Gung Memorial Hospital approved this study. Data collection Trained nurses took the anthropometric measurements for all participants in accordance with standard operating procedures. The questionnaires consisted of two main parts: the survey of personal and past medical history. Questions on personal history included smoking habits, alcohol drinking history, betel nut chewing history and pregnancy status (if female). Questions on past medical history included chronic diseases, medication and operation history. Blood pressure (BP) was measured with an automatic sphygmomanometer and repeated two to three times after at least 10 min of rest when subjects had BP measurements higher than 120/80 mmHg (Welch Allyn, Skaneateles Falls, NY, USA; based on yearly calibrations). Height and weight were measured using an automatic scale with a sensitivity of 0.1 kg and a resolution of 0.1 cm. BMI was calculated as a ratio between weight and height in metre squared (kg/m2). Waist circumference was measured by two trained examiners using a measuring tape placed horizontally around the subjects’ abdomen at the midpoint between the lower border of the rib cage and the upper iliac crest. Biochemical measurements Venous blood samples were collected in vacuum tubes by venipuncture in the morning after a 12-h fast; the samples were stored at 4°C in a refrigerator before analysis by the hospital laboratory department. All blood analyses were done in the Clinical Laboratory Department of Linkuo or Chiayi Chang Gung Memorial Hospital; both laboratories are certified by the College of American Pathologists. Urine specimens were obtained in the morning and scheduled to avoid menstrual periods. Laboratory measurements included high-sensitivity C reactive protein (hsCRP), fasting plasma glucose (FPG), total cholesterol (TChol), triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels. Creatinine (Cr) and hsCRP levels were measured with a Hitachi 7600 Modular Chemistry Analyzer (Hitachi, Tokyo, Japan). FPG was measured using the hexokinase method. TChol and TG levels were measured using an enzymatic colorimetric test. HDL-C was measured using a selective-inhibition method. Definition of measurement cut-offs and calculations BMI categories were defined as follows: obesity, ≥27 kg/m2; overweight, 24–26.9 kg/m2; and normal weight, <23.9 kg/m2, according to the ranges established for Asian populations by the Ministry of Health and Welfare of Taiwan (12). The cut-off for waist circumference for abdominal obesity was ≥90 cm for men and ≥80 cm for women, using the Asian-specific cut-off points established by the International Diabetes Federation (13). The eGFR was calculated using equations for the Modification of Diet in Renal Disease for Chinese patients, with CKD (14) measured in the following manner: 175 × (Scr)–1.234 × (Age)–0.179 × 0.79 (if female). CKD was defined as an eGFR of <60 ml/min per 1.73 m2 of body surface (ml/min/1.73 m2), according to the definition from the Kidney Disease Outcomes Quality Initiative (K/DOQI) (15) for CKD ≥ stage 3. A high homocysteine level was defined using the upper quartile for the serum homocysteine level. The upper homocysteine quartile in our study population was 11.81 µmol/l. Diagnostic criteria for metabolic syndrome (MetS) were established according to the 2004 Taiwan Ministry of Health criteria that were adapted from the Asian modification of the US National Cholesterol Education Program criteria (16). A diagnosis of MetS required three or more of the following criteria: (a) high BP (systolic BP ≥130 mmHg, diastolic BP ≥85 mmHg); (b) high serum TG (TG ≥ 150 mg/dl); (c) increased HDL-C (<40 mg/dl for males and <50 mg/dl for females); (d) hyperglycaemia (FPG ≥ 100 mg/dl); and (e) abdominal obesity (using modified waist circumference cut-offs for Asian populations). Statistical analysis Continuous variables are presented as median (interquartile range). Categorical variables are shown as count and percentage. Differences for categorical variables between normal weight and overweight/obese groups were examined using the chi-square test. Participants were classified into quartiles according to their serum homocysteine levels. The four independent homocysteine groups were statistically analysed using a Kruskal–Wallis test with a post hoc Bonferroni correction for repeated comparisons. A multivariate linear regression model was established to study the association of renal function (eGFR), BMI and serum homocysteine levels with age, gender, hypertension and diabetes. Finally, we established two multivariate logistic regression models: one was developed to evaluate associations between different combined weight groups and serum homocysteine levels with the risk of CKD after adjusting for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. The other was developed to investigate the presence of hyperhomocysteinaemia and the risk of CKD among different weight groups based on the total population and sex with completely separate analyses. SPSS software package, version 20.0 (IBM Corporation, Chicago, USA), was used for statistical analysis. All statistic assessments were evaluated using a two-sided α level of 0.05. Results Baseline characteristics among different weight groups A total of 24826 subjects were enrolled in this study. All participants were divided into two groups based on their BMI: one with normal weight subjects (BMI <24 kg/m2; n = 12093, 48.71%) and the other with overweight/obese subjects (BMI ≥24 kg/m2; n = 12733, 51.29%). Among all participants, the medium age was 37 (33, 41) years and 44 (38, 51) years in the normal weight and overweight/obese groups, respectively. There were 19076 (76.8%) males and 5750 (23.2%) females in this study. Among the males, 77% were overweight or obese, and 23% of the females were overweight or obese. There were significant differences in demographic and cardiometabolic risk factors between the two groups (Table 1). Compared with the normal weight group, the overweight/obese group was older and had higher body fat percentages (%BF), waist circumferences, systolic/diastolic BP, TChol, LDL, TG, Chol-T/HDL, FPG, uric acid, Cr, hsCRP and homocysteine levels. In addition, the prevalence of smoking, proteinuria, hypertension, diabetes mellitus, hyperlipidaemia and CKD (eGFR ≥ 60 ml/min/1.73 m2 and/or proteinuria of ≥1+) was higher in the overweight/obese group than in the normal weight group. The percentages of CKD were 2.1% and 4.8% [odds ratio (OR): 2.38; 95% CI: 2.05–2.76; P < 0.01] in the normal weight and overweight/obese groups, respectively. Table 1. Baseline characteristics of study subjects aged ≥18 years who underwent annual health check-ups during 2013–2015 based on BMI groups (N = 24826) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Mann–Whitney U test of non-parametric analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a significant difference between BMI < 24 kg/m2 and BMI ≥ 24 kg/m2. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. View Large Table 1. Baseline characteristics of study subjects aged ≥18 years who underwent annual health check-ups during 2013–2015 based on BMI groups (N = 24826) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Mann–Whitney U test of non-parametric analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a significant difference between BMI < 24 kg/m2 and BMI ≥ 24 kg/m2. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. View Large Different characteristics among homocysteine subgroup quartiles Table 2 shows the different characteristics according to the quartiles of serum homocysteine levels. Significant differences were observed in most characteristics among low-to-high homocysteine subgroups, except for diabetes mellitus (0.9%, 1.1%, 1.4% and 1.6%, the first to fourth quartiles, respectively). Subjects with higher plasma homocysteine levels were more likely to have a lower eGFR. The eGFRs in the first, second, third and fourth quartiles were 124.4, 109.9, 105.1 and 99.1 ml/min/1.73 m2, respectively. The prevalence of smoking, hypertension, hyperlipidaemia, proteinuria and CKD (2.5%, 2.7%, 3.4% and 5.2% for the respective quartiles) increased with increasing plasma homocysteine levels. The medians for BMI, %BF, waist circumference, systolic BP, diastolic BP, TG, Chol/HDL, Cr and uric acid levels all significantly increased with increasing homocysteine levels (all P values <0.01); however, the HDL levels decreased with increasing homocysteine levels, and all post hoc analyses with a Bonferroni correction reached significance between the two groups (all P values <0.01). However, no significant difference was identified in TChol, LDL, FPG and hsCRP between the third and fourth quartiles. Table 2. Characteristics represented across quartiles of homocysteine (N = 24826) by participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Kruskal–Wallis test for post hoc analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a statistical significance among the quartiles of homocysteine. Group 1 indicated as homocysteine level lower than 8.50 µmol/l; Group 2 indicated as homocysteine level between 8.50 and 10.00 µmol/l; Group 3 indicated as homocysteine level between 10.01 and 11.80 µmol/l; Group 4 indicated as homocysteine level higher than 11.81 µmol/l. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. aSignificant differences between G1 and G2. bSignificant differences between G1 and G3. cSignificant differences between G1 and G4. dSignificant differences between G2 and G3. eSignificant differences between G2 and G4. fSignificant differences between G3 and G4. View Large Table 2. Characteristics represented across quartiles of homocysteine (N = 24826) by participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Kruskal–Wallis test for post hoc analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a statistical significance among the quartiles of homocysteine. Group 1 indicated as homocysteine level lower than 8.50 µmol/l; Group 2 indicated as homocysteine level between 8.50 and 10.00 µmol/l; Group 3 indicated as homocysteine level between 10.01 and 11.80 µmol/l; Group 4 indicated as homocysteine level higher than 11.81 µmol/l. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. aSignificant differences between G1 and G2. bSignificant differences between G1 and G3. cSignificant differences between G1 and G4. dSignificant differences between G2 and G3. eSignificant differences between G2 and G4. fSignificant differences between G3 and G4. View Large Association analysis among BMI, homocysteine and eGFR As shown in Table 3, both the BMI and plasma homocysteine levels were negatively associated with eGFR. A significant difference was detected in the multiple linear regression model for evaluating the association among BMI, homocysteine and eGFR after adjusting for gender, age, smoking, hypertension, diabetes and hyperlipidaemia. For a one-unit (kg/m2) increase in BMI, there was a 0.50 ml/min/1.73 m2 decline in eGFR. For every unit (µmol/l) increase in homocysteine, the eGFR decreased by 1.10 ml/min/1.73 m2. Table 3. Multivariate linear regression model estimating the association among BMI, homocysteine and eGFR (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate linear regression analysis; constant = 185.78; F = 2000.15; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 3. Multivariate linear regression model estimating the association among BMI, homocysteine and eGFR (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate linear regression analysis; constant = 185.78; F = 2000.15; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 4 shows that both the BMI and plasma homocysteine levels were significantly related to an increased risk of CKD after adjusting for gender, age, smoking, hypertension, diabetes and hyperlipidaemia. As for overweight/obese (BMI ≥24 kg/m2), the OR for risk of CKD was 1.94 (95% CI: 1.66–2.27, P < 0.01). The OR for hyperhomocysteinaemia (>11.81 µmol/l) for CKD was 1.70 (95% CI: 1.47–1.97, P < 0.01). Table 4. Multivariate linear regression model estimating the association among BMI, homocysteine and CKD (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate logistic regression analysis; constant = 185.78; F = 2000.154; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 4. Multivariate linear regression model estimating the association among BMI, homocysteine and CKD (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate logistic regression analysis; constant = 185.78; F = 2000.154; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Hyperhomocysteinaemia and risk of CKD among different weight groups Table 5 shows the association of hyperhomocysteinaemia and risk of CKD based on different weights and gender. For the total population, the OR for CKD in hyperhomocysteinaemia for the normal weight group was 1.38 (95% CI: 1.05–1.83, P = 0.02) and 1.84 for the overweight/obesity group (95% CI: 1.56–2.19, P < 0.01). Similar patterns and trends were observed in both genders. For males, the OR for CKD with hyperhomocysteinaemia for the normal weight and overweight/obese groups was 1.44 (95% CI: 1.06–1.95, P = 0.02) and 1.66 (95% CI: 1.38–1.99, P < 0.01), respectively; for females, the OR for CKD with hyperhomocysteinaemia for the normal weight and overweight/obese groups was 1.95 (95% CI: 0.77–4.94, P = 0.16) and 3.40 (95% CI: 2.06–5.61, P < 0.01), respectively. Table 5. Hyperhomocysteinaemia and risk of chronic kidney disease among different weight groups by multivariate logistic regression analysis in total population and in stratification of gender (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Asterisk indicates significant statistical difference. In normal weight groups, omnibus test for total, male and female model = 0.01, 0.01, 0.00; in overweight/obesity groups, omnibus test for total, male and female model = 0.00, 0.00, 0.00; chi-square test = 43.37; P = 0.00. All models are adjusted for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. BMI, body mass index. View Large Table 5. Hyperhomocysteinaemia and risk of chronic kidney disease among different weight groups by multivariate logistic regression analysis in total population and in stratification of gender (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Asterisk indicates significant statistical difference. In normal weight groups, omnibus test for total, male and female model = 0.01, 0.01, 0.00; in overweight/obesity groups, omnibus test for total, male and female model = 0.00, 0.00, 0.00; chi-square test = 43.37; P = 0.00. All models are adjusted for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. BMI, body mass index. View Large Discussion To our knowledge, this is the first study to identify the association of weight and serum homocysteine levels with risk of CKD in a Taiwanese adult population. Hyperhomocysteinaemia has been recognized as an independent factor for CVD, deep vein thrombosis and CKD development (8). Elevated homocysteine levels were associated with oxidative injury to vascular endothelial cells and the inhibition of endothelial mediators such as nitric oxide; generation of superoxide radicals that inhibit the relaxation of vessels (17); increased proliferation of vascular smooth muscle cells (9); and decreased production of adenosine, which is thought to be associated with vasodilation and vessel remodelling (18). Meanwhile, in hyperhomocysteinaemic conditions, homocysteine burden leads to the expression of an endoplasmic reticulum stress gene that causes cellular injury in cultured podocytes suggesting a link to kidney damage (19) and eventually leading to focal or global glomerulosclerosis, tubular atrophy, interstitial fibrosis and reduced GFRs (20). Recent evidence has suggested that hormones and cytokines secreted from adipose tissue also contribute to CKD (21). Visceral fats, along with other risk factors in the pathogenesis of MetS, are strongly correlated with insulin resistance. As a result, proatherogenic and inflammatory cytokine production increases; interferes with insulin signalling; and contributes to the development of insulin resistance (22), vascular wall inflammation and CKD (23). Hyperinsulinemia and hyperhomocysteinaemia are now well-accepted risk factors for atherosclerosis. The mechanism of homocysteine angiotoxicity–related kidney injury seems to involve the nitric oxide system by inducing oxidative stress (24). Oxidative stress has been suggested to cause insulin resistance (IR) and may be linked to atherosclerosis. The association between IR and elevated homocysteine levels in healthy, non-obese patients has been proposed, suggesting that IR may contribute to the development of hyperhomocysteinaemia and therefore have implications to premature vascular disease. However, previous study by De Pergola et al. (25) indicated that plasma homocysteine levels are independently associated with IR in apparently healthy normal weight, overweight and obese premenopausal women, thus suggesting a possible role in IR, hyperinsulinemia, or both in increasing plasma homocysteine levels. Consistent estimated high prevalence of CKD and obesity was observed globally. Therefore, identifying patients with CKD at an earlier stage in the primary care setting is vital, so that treatment can be initiated to delay progression and prevent renal failure complications. Our findings indicated that inflammation-related glomerulopathy may be one of the potential causal pathways for IR caused by obesity and hyperhomocysteinaemia (26), and surrogate markers such as BMI and homocysteine may be useful for predicting CKD. Gender differences were also identified by combining BMI and hyperhomocysteinaemia to estimate the risk of CKD among different weight groups based on the multivariate logistic regression analysis of the total population and in different sexes with completely separate analyses (Table 5). For females, the OR for risk of CKD in overweight/obese groups with hyperhomocysteinaemia was greater than that of males (3.40 versus 1.66, respectively), implying that BMI and homocysteine levels may be more influential in females than males. This may be because of different body compositions and fat mass deposition in each gender. With the same BMI level, females usually have greater body fat composition, whereas males have more lean muscle mass (27). Visceral fat contains greater amounts of inflammatory mediators than subcutaneous fat, and these mediators are thought to contribute to the development of IR (28). However, BMI measurements, particularly %BF, are the major determinants of IR in non-diabetic patients with stages 3 and 4 CKD (29). Inflammation-related IR and elevated homocysteine levels secondary to excess body fat at the same BMI levels may have a greater influence in females than males. Prospective studies are needed to define more clearly how different body compositions or fat mass deposition interferes with renal function changes and to determine whether interventions targeting IR or how homocysteine-lowering therapy in this patient population can decrease cardiovascular morbidity and mortality and progression to end-stage renal disease. Nevertheless, certain limitations should be mentioned. First, because of the cross-sectional design of this study, we cannot draw any causal inferences from the data. Continued longitudinal analyses will be aimed at exploring the pathophysiological relationship among overweight/obese, insulin resistance, chronic inflammation, accumulated homocysteine level and subsequent renal function deterioration. Second, it was not a national survey so the results are only representative of healthy adults aged 30–55 years in a Taiwanese population. More prospective data are needed to determine the predictive value of BMI and hyperhomocysteinaemia in CKD development in children as cardiometabolic risk factors begin early in life and continue to adulthood. Moreover, we used the same cut-off value for homocysteine levels for men and women, an assumption that may confound results if a gender difference exists. Further longitudinal research focusing on the relationship between inflammation-related IR and elevated homocysteine levels in CKD patients may help in elucidating the causal relationship and determining whether any interventions, such as vitamins supplementation, modified dietary habits and intensive exercise by changing the body composition or weight loss could prevent CKD progression by lowering the IR or homocysteine level. Conclusion Both BMI and homocysteine levels are independent risk factors for CKD. Our findings may provide the clinical physician a method for early detection of renal function impairment and thus help prevent CKD by identifying overweight or obese patients in the primary care. Moreover, elevated serum homocysteine levels were positively associated with the risk for CKD, and the association was more profound in overweight/obese females than overweight/obese males. Moreover, future clinical research on the effects of weight loss, intensive exercise, lifestyle modification, nutritional status or homocysteine-lowering therapy such as folic acid, vitamin B6, and B12 supplementation, with the aim of unravelling the role of adipose tissue and serum homocysteine levels in associated comorbidities, is highly warranted. Author contribution The authors’ contributions were as follows: SHL and YCC were responsible for data collection. SHL planned the research, analysed the data and prepared the draft of the manuscript. YWT and SSC designed the research, planned the data analysis, interpretation and reviewed the final draft. YWT and SSC were in equal contribution to this work. All authors read and approved the final version of the manuscript. Declaration Funding: None. Ethical approval: Chang Gung Memorial Hospital Institution Review Board (Ethical Review Committee). Ethical approval number: 201600399B0. Conflict of interest: none declared. Acknowledgements Y-WT and S-SC are in equal contribution to this work. The authors would like to thank the staff of the Health Examination Centers in the Keelung, Linkou, and Chiayi branches of Cheng Gung Memorial Hospital for assistance with data collection. References 1. Nugent RA , Fathima SF , Feigl AB et al. The burden of chronic kidney disease on developing nations: a 21st century challenge in global health . Nephron Clin Pract 2011 ; 118 : c269 – 77 . Google Scholar CrossRef Search ADS PubMed 2. Hill NR , Fatoba ST , Oke JL et al. Global prevalence of chronic kidney disease—a systematic review and meta-analysis . PLoS One 2016 ; 11 : e0158765 . Google Scholar CrossRef Search ADS PubMed 3. Wen CP , Cheng TY , Tsai MK et al. All-cause mortality attributable to chronic kidney disease: a prospective cohort study based on 462 293 adults in Taiwan . Lancet 2008 ; 371 : 2173 – 82 . Google Scholar CrossRef Search ADS PubMed 4. Smith KB , Smith MS . Obesity statistics . 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Endocrinology 2004 ; 145 : 2273 – 82 . Google Scholar CrossRef Search ADS PubMed 29. Trirogoff ML , Shintani A , Himmelfarb J et al. Body mass index and fat mass are the primary correlates of insulin resistance in nondiabetic stage 3-4 chronic kidney disease patients . Am J Clin Nutr 2007 ; 86 : 1642 – 8 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Family Practice Oxford University Press

Obesity, hyperhomocysteinaemia and risk of chronic kidney disease: a population-based study

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Abstract

Abstract Background Obesity is associated with increased risk of cardiovascular disease and chronic kidney disease (CKD). Hyperhomocysteinaemia refers to increased oxidative stress and has been associated with the risk of CKD. Objectives We investigated the association among body mass index (BMI), homocysteine level and impaired renal function in a Taiwanese adult population. Methods This was a retrospective cross-sectional study involving 24826 subjects who underwent a health check-up from January 2013 to December 2015. A multivariate linear regression model was developed to analyse the relationship among BMI, serum homocysteine and estimated glomerular filtration rate (eGFR). A multivariate logistic regression model was used to assess the relationship among weight categories, hyperhomocysteinaemia and CKD. Results The prevalence of CKD in the quartile groups of homocysteine were 2.5%, 2.7%, 3.4% and 5.2% (P < 0.01). For every one-unit increase in BMI (kg/m2), the eGFR decreased by 0.50 ml/min/1.73 m2. Overweight/obese subjects with high homocysteine levels had a higher odds ratio (OR) for CKD, as compared with normal weight subjects (1.84 versus 1.38, respectively; P < 0.01 versus P = 0.02, respectively). Overweight/obese female subjects with hyperhomocysteinaemia had an OR of 3.40 [P < 0.01; 95% confidence interval (CI): 2.06–5.61] for CKD; in males, the OR was 1.66 (P < 0.01; 95% CI: 1.38–1.99). Conclusions Patients who are overweight/obese with higher homocysteine levels have an increased risk of CKD, especially females. Additional studies exploring whether the effect of weight loss or homocysteine-lowering therapies such as folic acid, vitamin B12 supplements that may prevent or slow the progression of declining renal function, is warranted. Body mass index, chronic, glomerular filtration rate, homocysteine, inflammation, obesity, renal insufficiency Introduction Chronic kidney disease (CKD) poses a significant challenge in 21st century global health policy because of its emerging health and economic burden (1). Primary health care is important for CKD because of high global prevalence (11–13%) of stage 3 underdiagnosed and undertreated patients with CKD (2). In Taiwan, the prevalence of CKD is as high as 11.93%, reaching about 2.74 million patients, potentially resulting in a significant mortality rate because of cardiovascular diseases (CVD), and accounting for tremendous health care expenditures (3). Therefore, early identification of the risk factors for CKD is critical for preventing the development of kidney damage and adverse outcomes. At present, >2.1 billion people are overweight or obese worldwide. As overweight and obesity are the fifth leading cause of death worldwide, accounting for nearly 3.4 million deaths annually (4), the increasing prevalence should be considered in primary care setting. Obesity is strongly associated with diabetes and hypertension and was demonstrated as a risk factor for the development of CKD (5). The crucial pathogenic role of obesity-induced chronic renal disease may be related to excess nutrients in metabolic cells, leading to the activation of several bioactive mediators (6) and an increase in the endogenous production of proinflammatory cytokines (7). Homocysteine is an amino acid formed by the conversion of methionine to cysteine, and an elevated plasma homocysteine level has been recognized as an independent factor for CVD (8). Homocysteine is believed to impair implantation by interfering with oxidative injury to vascular endothelial cells, and their vascular integrity may contribute to intrarenal arteriosclerosis, along with a subsequent reduction in renal perfusion pressure (9) and eventually reduced estimated glomerular filtration rate (eGFR). Preliminary investigations suggest that elevated homocysteine levels may be a risk factor or risk marker of future CKD (10,11). However, the association between weight status and different plasma homocysteine levels in CKD is not yet well established. The purpose of this study was to determine the relationship between body mass index (BMI) and serum homocysteine levels in CKD and to evaluate other associated risk factors. Methods Subjects This cross-sectional study involved subjects aged ≥18 years who underwent annual heath check-ups at the Linkou (northern Taiwan) and Chiayi (southern Taiwan) branches of Chang Gung Memorial Hospital from January 2013 to December 2015. All subjects enrolled were factory workers from northern and southern Taiwan who participated in the annual health check-ups at Chang Gung Memorial Hospital Linkou or Chiayi branch. The general characteristics of the population were age ranging from 30 to 55 years and being predominantly male. Each subject was invited to answer the questionnaires regarding his or her personal and past medical history. Trained nurses provided assistance while the participants were answering the questionnaire during the health examination. The original number of participants was 29728, and 3828 of them were excluded because of incomplete answers to the questionnaire. Among the remaining participants, 152 pregnant women and 922 participants who reported with underlying chronic diseases that might alter the metabolic state or kidney function tests, such as thyroid or hypothalamic diseases, adrenal disease, renal cancer, glomerulonephritis, renal failure on haemodialysis or peritoneal dialysis, liver cirrhosis, or use of diuretic renal replacement therapy were also excluded. The remaining 24826 participants were enrolled in this study. Informed consent was obtained from all participants. The Institutional Review Board of Chang Gung Memorial Hospital approved this study. Data collection Trained nurses took the anthropometric measurements for all participants in accordance with standard operating procedures. The questionnaires consisted of two main parts: the survey of personal and past medical history. Questions on personal history included smoking habits, alcohol drinking history, betel nut chewing history and pregnancy status (if female). Questions on past medical history included chronic diseases, medication and operation history. Blood pressure (BP) was measured with an automatic sphygmomanometer and repeated two to three times after at least 10 min of rest when subjects had BP measurements higher than 120/80 mmHg (Welch Allyn, Skaneateles Falls, NY, USA; based on yearly calibrations). Height and weight were measured using an automatic scale with a sensitivity of 0.1 kg and a resolution of 0.1 cm. BMI was calculated as a ratio between weight and height in metre squared (kg/m2). Waist circumference was measured by two trained examiners using a measuring tape placed horizontally around the subjects’ abdomen at the midpoint between the lower border of the rib cage and the upper iliac crest. Biochemical measurements Venous blood samples were collected in vacuum tubes by venipuncture in the morning after a 12-h fast; the samples were stored at 4°C in a refrigerator before analysis by the hospital laboratory department. All blood analyses were done in the Clinical Laboratory Department of Linkuo or Chiayi Chang Gung Memorial Hospital; both laboratories are certified by the College of American Pathologists. Urine specimens were obtained in the morning and scheduled to avoid menstrual periods. Laboratory measurements included high-sensitivity C reactive protein (hsCRP), fasting plasma glucose (FPG), total cholesterol (TChol), triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels. Creatinine (Cr) and hsCRP levels were measured with a Hitachi 7600 Modular Chemistry Analyzer (Hitachi, Tokyo, Japan). FPG was measured using the hexokinase method. TChol and TG levels were measured using an enzymatic colorimetric test. HDL-C was measured using a selective-inhibition method. Definition of measurement cut-offs and calculations BMI categories were defined as follows: obesity, ≥27 kg/m2; overweight, 24–26.9 kg/m2; and normal weight, <23.9 kg/m2, according to the ranges established for Asian populations by the Ministry of Health and Welfare of Taiwan (12). The cut-off for waist circumference for abdominal obesity was ≥90 cm for men and ≥80 cm for women, using the Asian-specific cut-off points established by the International Diabetes Federation (13). The eGFR was calculated using equations for the Modification of Diet in Renal Disease for Chinese patients, with CKD (14) measured in the following manner: 175 × (Scr)–1.234 × (Age)–0.179 × 0.79 (if female). CKD was defined as an eGFR of <60 ml/min per 1.73 m2 of body surface (ml/min/1.73 m2), according to the definition from the Kidney Disease Outcomes Quality Initiative (K/DOQI) (15) for CKD ≥ stage 3. A high homocysteine level was defined using the upper quartile for the serum homocysteine level. The upper homocysteine quartile in our study population was 11.81 µmol/l. Diagnostic criteria for metabolic syndrome (MetS) were established according to the 2004 Taiwan Ministry of Health criteria that were adapted from the Asian modification of the US National Cholesterol Education Program criteria (16). A diagnosis of MetS required three or more of the following criteria: (a) high BP (systolic BP ≥130 mmHg, diastolic BP ≥85 mmHg); (b) high serum TG (TG ≥ 150 mg/dl); (c) increased HDL-C (<40 mg/dl for males and <50 mg/dl for females); (d) hyperglycaemia (FPG ≥ 100 mg/dl); and (e) abdominal obesity (using modified waist circumference cut-offs for Asian populations). Statistical analysis Continuous variables are presented as median (interquartile range). Categorical variables are shown as count and percentage. Differences for categorical variables between normal weight and overweight/obese groups were examined using the chi-square test. Participants were classified into quartiles according to their serum homocysteine levels. The four independent homocysteine groups were statistically analysed using a Kruskal–Wallis test with a post hoc Bonferroni correction for repeated comparisons. A multivariate linear regression model was established to study the association of renal function (eGFR), BMI and serum homocysteine levels with age, gender, hypertension and diabetes. Finally, we established two multivariate logistic regression models: one was developed to evaluate associations between different combined weight groups and serum homocysteine levels with the risk of CKD after adjusting for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. The other was developed to investigate the presence of hyperhomocysteinaemia and the risk of CKD among different weight groups based on the total population and sex with completely separate analyses. SPSS software package, version 20.0 (IBM Corporation, Chicago, USA), was used for statistical analysis. All statistic assessments were evaluated using a two-sided α level of 0.05. Results Baseline characteristics among different weight groups A total of 24826 subjects were enrolled in this study. All participants were divided into two groups based on their BMI: one with normal weight subjects (BMI <24 kg/m2; n = 12093, 48.71%) and the other with overweight/obese subjects (BMI ≥24 kg/m2; n = 12733, 51.29%). Among all participants, the medium age was 37 (33, 41) years and 44 (38, 51) years in the normal weight and overweight/obese groups, respectively. There were 19076 (76.8%) males and 5750 (23.2%) females in this study. Among the males, 77% were overweight or obese, and 23% of the females were overweight or obese. There were significant differences in demographic and cardiometabolic risk factors between the two groups (Table 1). Compared with the normal weight group, the overweight/obese group was older and had higher body fat percentages (%BF), waist circumferences, systolic/diastolic BP, TChol, LDL, TG, Chol-T/HDL, FPG, uric acid, Cr, hsCRP and homocysteine levels. In addition, the prevalence of smoking, proteinuria, hypertension, diabetes mellitus, hyperlipidaemia and CKD (eGFR ≥ 60 ml/min/1.73 m2 and/or proteinuria of ≥1+) was higher in the overweight/obese group than in the normal weight group. The percentages of CKD were 2.1% and 4.8% [odds ratio (OR): 2.38; 95% CI: 2.05–2.76; P < 0.01] in the normal weight and overweight/obese groups, respectively. Table 1. Baseline characteristics of study subjects aged ≥18 years who underwent annual health check-ups during 2013–2015 based on BMI groups (N = 24826) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Mann–Whitney U test of non-parametric analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a significant difference between BMI < 24 kg/m2 and BMI ≥ 24 kg/m2. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. View Large Table 1. Baseline characteristics of study subjects aged ≥18 years who underwent annual health check-ups during 2013–2015 based on BMI groups (N = 24826) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Characteristics Normal weight; BMI <24 (n = 12093) Overweight/obesity; BMI ≥24 (n = 12733) P value Age 37 (33, 41) 44 (38, 51) <0.01* Gender (n, %) 0.61  Male 9275 (76.7) 9801 (77.0)  Female 2818 (23.3) 2932 (23.0) Smoking (n, %) <0.01*  Non-smokers 9280 (76.7) 9093 (71.4)  Past smokers 730 (6.0) 1192 (9.4)  Current smokers 2083 (17.2) 2448 (19.2) BMI (kg/m2) 22.46 (20.78, 23.95) 26.77 (25.0, 28.82) <0.01* Body fat percentage (%) 30.18 (25.10, 32.31) 36.41 (34.34, 39.09) <0.01* Waist circumference (cm) (n, %) 77.5 (71.0, 82.0) 88.0 (82.0, 94.0) <0.01* Normal 11700 (96.8) 6454 (50.7) Abnormal (male ≥90, female ≥80) 393 (3.2) 6279 (49.3) SBP (mmHg) 117 (108, 126) 127 (118, 136) <0.01* DBP (mmHg) 73 (67, 79) 80 (73, 87) <0.01* Total cholesterol (mg/dl) 180 (161, 202) 193 (172, 214) <0.01* LDL cholesterol(mg/dl) 113 (95, 133) 125 (106, 145) <0.01* Triglycerides (mg/dl) 84 (62, 119) 120 (86, 173) <0.01* HDL cholesterol (mg/dl) 51 (44, 59) 46 (40, 53) <0.01* Chol-T/HDL 3.46 (2.90, 4.17) 4.19 (3.50, 4.97) <0.01* Fasting glucose (mg/dl) 85 (81, 90) 90 (85, 97) <0.01* Creatinine (mg/dl) 0.83 (0.71, 0.93) 0.86 (0.73, 0.98) <0.01* eGFR (ml/min/1.73 m2) 112.8 (98.93, 130.7) 104.8 (90.02, 121.93) <0.01* CKD (n, %) <0.01*  eGFR ≥60 11844 (97.9) 12127 (95.2)  eGFR <60 or proteinuria ≥1+ 249 (2.1) 606 (4.8) Proteinuria (n, %) <0.01*  Absent 11862 (98.1) 12219 (96)  Present 231 (1.9) 514 (4.0) Uric acid (mg/dl) 6.0 (5.1, 6.9) 6.6 (5.5, 7.5) <0.01* Homocysteine (µmol/l) 9.82 (8.30, 9.82) 10.1 (8.60, 11.98) <0.01* hsCRP (μg/ml) 0.76 (0.43, 1.47) 1.4 (0.77, 2.62) <0.01* Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 11984 (99.1) 11648 (91.5)  Present 109 (0.9) 1085 (8.5)  Diabetes mellitus (n, %) <0.01*  Absent 12062 (99.7) 12456 (97.8)  Present 31 (0.3) 277 (2.2)  Hyperlipidaemia (n, %) <0.01*  Absent 12058 (99.7) 12513 (98.3)  Present 35 (0.3) 220 (1.7) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Mann–Whitney U test of non-parametric analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a significant difference between BMI < 24 kg/m2 and BMI ≥ 24 kg/m2. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. View Large Different characteristics among homocysteine subgroup quartiles Table 2 shows the different characteristics according to the quartiles of serum homocysteine levels. Significant differences were observed in most characteristics among low-to-high homocysteine subgroups, except for diabetes mellitus (0.9%, 1.1%, 1.4% and 1.6%, the first to fourth quartiles, respectively). Subjects with higher plasma homocysteine levels were more likely to have a lower eGFR. The eGFRs in the first, second, third and fourth quartiles were 124.4, 109.9, 105.1 and 99.1 ml/min/1.73 m2, respectively. The prevalence of smoking, hypertension, hyperlipidaemia, proteinuria and CKD (2.5%, 2.7%, 3.4% and 5.2% for the respective quartiles) increased with increasing plasma homocysteine levels. The medians for BMI, %BF, waist circumference, systolic BP, diastolic BP, TG, Chol/HDL, Cr and uric acid levels all significantly increased with increasing homocysteine levels (all P values <0.01); however, the HDL levels decreased with increasing homocysteine levels, and all post hoc analyses with a Bonferroni correction reached significance between the two groups (all P values <0.01). However, no significant difference was identified in TChol, LDL, FPG and hsCRP between the third and fourth quartiles. Table 2. Characteristics represented across quartiles of homocysteine (N = 24826) by participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Kruskal–Wallis test for post hoc analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a statistical significance among the quartiles of homocysteine. Group 1 indicated as homocysteine level lower than 8.50 µmol/l; Group 2 indicated as homocysteine level between 8.50 and 10.00 µmol/l; Group 3 indicated as homocysteine level between 10.01 and 11.80 µmol/l; Group 4 indicated as homocysteine level higher than 11.81 µmol/l. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. aSignificant differences between G1 and G2. bSignificant differences between G1 and G3. cSignificant differences between G1 and G4. dSignificant differences between G2 and G3. eSignificant differences between G2 and G4. fSignificant differences between G3 and G4. View Large Table 2. Characteristics represented across quartiles of homocysteine (N = 24826) by participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Homocysteine quartiles Group 1; 0–8.50 µmol/l (n = 6485) Group 2; 8.51–10.00 µmol/l (n = 6140) Group 3; 10.01–11.80 µmol/l (n = 6189) Group 4; >11.81 µmol/l (n = 6012) P value Age 40 (35, 46) 40 (35, 46) 40 (35, 47) 40 (35, 47) <0.01*bc Gender (n, %) <0.01*  Male 3065 (47.3) 4830 (78.7) 5504 (88.9) 5677 (94.4)  Female 3420 (52.7) 1310 (21.3) 685 (11.1) 335 (5.6) BMI (kg/m2) 23.37 (21.0, 25.8) 24.4 (22.2, 26.7) 24.8 (22.8, 27.1) 25.1 (23.1, 27.5) <0.01*abcdef Normal weight (BMI <24) 3412 (52.6) 3062 (49.9) 2940 (47.5) 2679 (48.7) <0.01* Overweight/obese (BMI ≥24) 3073 (47.4) 3078 (50.1) 3249 (52.5) 3333 (55.4) Body fat percentage (%) 27.3 (18.9, 33.8) 32.6 (28.0, 36.3) 33.6 (30.2, 37.0) 34.4 (31.1, 37.7) <0.01*abcedf Waist circumference (cm) (n, %) 78.0 (70.0, 85.0) 82.0 (76, 89) 84 (78, 90) 85.0 (79.0, 91.5) <0.01*abcdef  Normal 5075 (78.3) 4587 (74.7) 4443 (71.8) 4049 (67.3)  Abnormal (male ≥90, female ≥80) 1410 (21.7) 1553 (25.3) 1746 (28.2) 1963 (32.7) <0.01* SBP (mmHg) 116 (106, 128) 122 (112, 131) 119 (111, 129) 126 (117, 135) <0.01*abcdef DBP (mmHg) 73 (66, 81) 76 (69, 83) 77 (71, 85) 79 (72, 86) <0.01*abcdef Total cholesterol (mg/dl) 182 (163, 204) 187 (166, 108) 189 (169, 211) 188 (168, 211) <0.01*abcde LDL cholesterol (mg/dl) 114 (95, 134) 119 (100, 139) 123 (103, 143) 122 (103, 143) <0.01*abcde Triglycerides (mg/dl) 88 (63, 128) 102 (71, 149) 106 (75, 154) 110 (78, 160) <0.01*abcdef HDL cholesterol (mg/dl) 52 (44, 60) 48 (42, 56) 47 (41, 55) 46 (40, 54) <0.01*abcdef Chol-T/HDL 3.47 (2.89, 4.23) 3.83 (3.16, 4.58) 4.0 (3.3, 4.7) 4.07 (3.37, 4.85) <0.01*abcdef Fasting glucose (mg/dl) 86 (81, 92) 87 (83, 94) 88 (83, 94) 88 (83, 95) <0.01*abcde Smoking (n, %) <0.01*  Non-smokers 5357 (82.6) 4508 (73.4) 4340 (70.1) 4168 (69.3)  Past smokers 367 (5.7) 493 (8.0) 572 (9.2) 490 (8.2)  Current smokers 761 (11.7) 1139 (18.6) 1277 (20.6) 1354 (22.5) Creatinine (mg/dl) 0.70 (0.57, 0.85) 0.84 (0.72, 0.93) 0.88 (0.78, 0.98) 0.92 (0.83, 1.03) <0.01*abcdef eGFR (ml/min/1.73 m2) 124.4 (106.3, 146.3) 109.9 (96.9, 125.9) 105.1 (92.1, 119.6) 99.1 (86.2, 113.07) <0.01*abcdef CKD (n, %) <0.01*  eGFR ≥60 6321 (97.5) 5975 (97.3) 5977 (96.6) 5698 (94.8)  eGFR<60 or proteinuria ≥1+ 164 (2.5) 165 (2.7) 212 (3.4) 314 (5.2) Proteinuria (n, %) <0.01*  Absent 6326 (97.5) 5986 (97.5) 5992 (96.8) 5777 (96.1)  Present 159 (2.5) 154 (2.5) 197 (3.2) 235 (3.9) Uric acid (mg/dl) 5.4 (4.5, 6.4) 6.2 (5.3, 7.1) 6.6 (5.7, 7.5) 6.9 (6.0, 7.8) <0.01*abcdef Homocysteine (µmol/l) 7.5 (6.7, 8.1) 9.3 (8.9, 9.7) 10.83 (10.4, 11.3) 13.3 (12.5, 15.0) <0.01*abcdef hsCRP (μg/ml) 0.94 (0.49, 1.95) 1.03 (0.53,2.06) 1.09 (0.6, 2.08) 1.14 (0.62, 2.18) <0.01*abcde Past medical history of systemic diseases  Hypertension (n, %) <0.01*  Absent 6271 (96.7) 5895 (96) 5868 (94.8) 5598 (93.1)  Present 214 (3.3) 245 (4.0) 321 (5.2) 414 (6.9)  Diabetes mellitus (n, %) <0.01  Absent 6426 (99.1) 6074 (98.9) 6100 (98.6) 5918 (98.4)  Present 59 (0.9) 66 (1.1) 89 (1.4) 94 (1.6)  Hyperlipidaemia (n, %) <0.01*  Absent 6441 (99.3) 6090 (99.3) 6116 (98.8) 5918 (98.4)  Present 44 (0.7) 44 (0.7) 73 (1.2) 94 (1.6) Continuous data are reported as median (interquartile range) for non-normal distribution data and compared using the Kruskal–Wallis test for post hoc analysis; categorical data are shown as number (percentage) and compared using the chi-square test. Asterisk indicates a statistical significance among the quartiles of homocysteine. Group 1 indicated as homocysteine level lower than 8.50 µmol/l; Group 2 indicated as homocysteine level between 8.50 and 10.00 µmol/l; Group 3 indicated as homocysteine level between 10.01 and 11.80 µmol/l; Group 4 indicated as homocysteine level higher than 11.81 µmol/l. BMI, body mass index; SBP, systolic blood pressure; DPB, diastolic blood pressure; LDL, low-density lipoprotein lipase cholesterol; HDL, high-density lipoprotein lipase cholesterol; Chol-T, total cholesterol; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; hsCRP, high sensitivity C reactive protein. aSignificant differences between G1 and G2. bSignificant differences between G1 and G3. cSignificant differences between G1 and G4. dSignificant differences between G2 and G3. eSignificant differences between G2 and G4. fSignificant differences between G3 and G4. View Large Association analysis among BMI, homocysteine and eGFR As shown in Table 3, both the BMI and plasma homocysteine levels were negatively associated with eGFR. A significant difference was detected in the multiple linear regression model for evaluating the association among BMI, homocysteine and eGFR after adjusting for gender, age, smoking, hypertension, diabetes and hyperlipidaemia. For a one-unit (kg/m2) increase in BMI, there was a 0.50 ml/min/1.73 m2 decline in eGFR. For every unit (µmol/l) increase in homocysteine, the eGFR decreased by 1.10 ml/min/1.73 m2. Table 3. Multivariate linear regression model estimating the association among BMI, homocysteine and eGFR (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate linear regression analysis; constant = 185.78; F = 2000.15; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 3. Multivariate linear regression model estimating the association among BMI, homocysteine and eGFR (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 β (95% Confidence interval) P value Gender (male) –28.79 (–29.53, –28.06) <0.01 Age –0.65 (–0.68, –0.62) <0.01 Hypertension –2.56 (–3.97, –1.16) <0.01 Diabetes 6.16 (3.53, 8.78) <0.01 BMI –0.50 (–0.58, –0.42) <0.01 Homocysteine –1.10 (–1.18, –1.11) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate linear regression analysis; constant = 185.78; F = 2000.15; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 4 shows that both the BMI and plasma homocysteine levels were significantly related to an increased risk of CKD after adjusting for gender, age, smoking, hypertension, diabetes and hyperlipidaemia. As for overweight/obese (BMI ≥24 kg/m2), the OR for risk of CKD was 1.94 (95% CI: 1.66–2.27, P < 0.01). The OR for hyperhomocysteinaemia (>11.81 µmol/l) for CKD was 1.70 (95% CI: 1.47–1.97, P < 0.01). Table 4. Multivariate linear regression model estimating the association among BMI, homocysteine and CKD (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate logistic regression analysis; constant = 185.78; F = 2000.154; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Table 4. Multivariate linear regression model estimating the association among BMI, homocysteine and CKD (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 OR (95% confidence interval) P value Age 1.02 (1.01, 1.02) <0.01 Hypertension 2.42 (1.96, 3.00) <0.01 Diabetes 3.12 (2.25, 4.34) <0.01 BMI 1.11 (1.10, 1.11) <0.01 Homocysteine 1.05 (1.03, 1.06) <0.01 The model of association analysis among BMI, homocysteine and eGFR was adjusted by gender, age, smoking, hypertension (self-reported history of hypertension or taking anti-hypertensive medication), diabetes (self-reported history of diabetes or taking anti-diabetic drugs), hyperlipidaemia (self-reported history of hyperlipidaemia or taking lipid-lowering medication), body mass index and homocysteine using stepwise multivariate logistic regression analysis; constant = 185.78; F = 2000.154; r2 = 0.33; P = <0.01. BMI, body mass index; eGFR, estimated glomerular filtration rate. View Large Hyperhomocysteinaemia and risk of CKD among different weight groups Table 5 shows the association of hyperhomocysteinaemia and risk of CKD based on different weights and gender. For the total population, the OR for CKD in hyperhomocysteinaemia for the normal weight group was 1.38 (95% CI: 1.05–1.83, P = 0.02) and 1.84 for the overweight/obesity group (95% CI: 1.56–2.19, P < 0.01). Similar patterns and trends were observed in both genders. For males, the OR for CKD with hyperhomocysteinaemia for the normal weight and overweight/obese groups was 1.44 (95% CI: 1.06–1.95, P = 0.02) and 1.66 (95% CI: 1.38–1.99, P < 0.01), respectively; for females, the OR for CKD with hyperhomocysteinaemia for the normal weight and overweight/obese groups was 1.95 (95% CI: 0.77–4.94, P = 0.16) and 3.40 (95% CI: 2.06–5.61, P < 0.01), respectively. Table 5. Hyperhomocysteinaemia and risk of chronic kidney disease among different weight groups by multivariate logistic regression analysis in total population and in stratification of gender (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Asterisk indicates significant statistical difference. In normal weight groups, omnibus test for total, male and female model = 0.01, 0.01, 0.00; in overweight/obesity groups, omnibus test for total, male and female model = 0.00, 0.00, 0.00; chi-square test = 43.37; P = 0.00. All models are adjusted for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. BMI, body mass index. View Large Table 5. Hyperhomocysteinaemia and risk of chronic kidney disease among different weight groups by multivariate logistic regression analysis in total population and in stratification of gender (N = 24826) of participants aged ≥18 years who underwent annual health check-ups during 2013–2015 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Odds ratio P value 95% Confidence interval Total (N = 24826) Normal weight (BMI <24 kg/m2) 1.38* 0.02 1.05–1.83 Overweight/obesity (BMI ≥24 kg/m2) 1.84* <0.01 1.56–2.19 Male (n = 19,076) Normal weight (BMI <24 kg/m2) 1.44* 0.02 1.06–1.95 Overweight/obesity (BMI ≥24 kg/m2) 1.66* <0.01 1.38–1.99 Female (n = 5750) Normal weight (BMI <24 kg/m2) 1.95 0.16 0.77–4.94 Overweight/obesity (BMI ≥24 kg/m2) 3.40* <0.01 2.06–5.61 Asterisk indicates significant statistical difference. In normal weight groups, omnibus test for total, male and female model = 0.01, 0.01, 0.00; in overweight/obesity groups, omnibus test for total, male and female model = 0.00, 0.00, 0.00; chi-square test = 43.37; P = 0.00. All models are adjusted for age, gender, smoking status, hypertension, diabetes mellitus and hyperlipidaemia. BMI, body mass index. View Large Discussion To our knowledge, this is the first study to identify the association of weight and serum homocysteine levels with risk of CKD in a Taiwanese adult population. Hyperhomocysteinaemia has been recognized as an independent factor for CVD, deep vein thrombosis and CKD development (8). Elevated homocysteine levels were associated with oxidative injury to vascular endothelial cells and the inhibition of endothelial mediators such as nitric oxide; generation of superoxide radicals that inhibit the relaxation of vessels (17); increased proliferation of vascular smooth muscle cells (9); and decreased production of adenosine, which is thought to be associated with vasodilation and vessel remodelling (18). Meanwhile, in hyperhomocysteinaemic conditions, homocysteine burden leads to the expression of an endoplasmic reticulum stress gene that causes cellular injury in cultured podocytes suggesting a link to kidney damage (19) and eventually leading to focal or global glomerulosclerosis, tubular atrophy, interstitial fibrosis and reduced GFRs (20). Recent evidence has suggested that hormones and cytokines secreted from adipose tissue also contribute to CKD (21). Visceral fats, along with other risk factors in the pathogenesis of MetS, are strongly correlated with insulin resistance. As a result, proatherogenic and inflammatory cytokine production increases; interferes with insulin signalling; and contributes to the development of insulin resistance (22), vascular wall inflammation and CKD (23). Hyperinsulinemia and hyperhomocysteinaemia are now well-accepted risk factors for atherosclerosis. The mechanism of homocysteine angiotoxicity–related kidney injury seems to involve the nitric oxide system by inducing oxidative stress (24). Oxidative stress has been suggested to cause insulin resistance (IR) and may be linked to atherosclerosis. The association between IR and elevated homocysteine levels in healthy, non-obese patients has been proposed, suggesting that IR may contribute to the development of hyperhomocysteinaemia and therefore have implications to premature vascular disease. However, previous study by De Pergola et al. (25) indicated that plasma homocysteine levels are independently associated with IR in apparently healthy normal weight, overweight and obese premenopausal women, thus suggesting a possible role in IR, hyperinsulinemia, or both in increasing plasma homocysteine levels. Consistent estimated high prevalence of CKD and obesity was observed globally. Therefore, identifying patients with CKD at an earlier stage in the primary care setting is vital, so that treatment can be initiated to delay progression and prevent renal failure complications. Our findings indicated that inflammation-related glomerulopathy may be one of the potential causal pathways for IR caused by obesity and hyperhomocysteinaemia (26), and surrogate markers such as BMI and homocysteine may be useful for predicting CKD. Gender differences were also identified by combining BMI and hyperhomocysteinaemia to estimate the risk of CKD among different weight groups based on the multivariate logistic regression analysis of the total population and in different sexes with completely separate analyses (Table 5). For females, the OR for risk of CKD in overweight/obese groups with hyperhomocysteinaemia was greater than that of males (3.40 versus 1.66, respectively), implying that BMI and homocysteine levels may be more influential in females than males. This may be because of different body compositions and fat mass deposition in each gender. With the same BMI level, females usually have greater body fat composition, whereas males have more lean muscle mass (27). Visceral fat contains greater amounts of inflammatory mediators than subcutaneous fat, and these mediators are thought to contribute to the development of IR (28). However, BMI measurements, particularly %BF, are the major determinants of IR in non-diabetic patients with stages 3 and 4 CKD (29). Inflammation-related IR and elevated homocysteine levels secondary to excess body fat at the same BMI levels may have a greater influence in females than males. Prospective studies are needed to define more clearly how different body compositions or fat mass deposition interferes with renal function changes and to determine whether interventions targeting IR or how homocysteine-lowering therapy in this patient population can decrease cardiovascular morbidity and mortality and progression to end-stage renal disease. Nevertheless, certain limitations should be mentioned. First, because of the cross-sectional design of this study, we cannot draw any causal inferences from the data. Continued longitudinal analyses will be aimed at exploring the pathophysiological relationship among overweight/obese, insulin resistance, chronic inflammation, accumulated homocysteine level and subsequent renal function deterioration. Second, it was not a national survey so the results are only representative of healthy adults aged 30–55 years in a Taiwanese population. More prospective data are needed to determine the predictive value of BMI and hyperhomocysteinaemia in CKD development in children as cardiometabolic risk factors begin early in life and continue to adulthood. Moreover, we used the same cut-off value for homocysteine levels for men and women, an assumption that may confound results if a gender difference exists. Further longitudinal research focusing on the relationship between inflammation-related IR and elevated homocysteine levels in CKD patients may help in elucidating the causal relationship and determining whether any interventions, such as vitamins supplementation, modified dietary habits and intensive exercise by changing the body composition or weight loss could prevent CKD progression by lowering the IR or homocysteine level. Conclusion Both BMI and homocysteine levels are independent risk factors for CKD. Our findings may provide the clinical physician a method for early detection of renal function impairment and thus help prevent CKD by identifying overweight or obese patients in the primary care. Moreover, elevated serum homocysteine levels were positively associated with the risk for CKD, and the association was more profound in overweight/obese females than overweight/obese males. Moreover, future clinical research on the effects of weight loss, intensive exercise, lifestyle modification, nutritional status or homocysteine-lowering therapy such as folic acid, vitamin B6, and B12 supplementation, with the aim of unravelling the role of adipose tissue and serum homocysteine levels in associated comorbidities, is highly warranted. Author contribution The authors’ contributions were as follows: SHL and YCC were responsible for data collection. SHL planned the research, analysed the data and prepared the draft of the manuscript. YWT and SSC designed the research, planned the data analysis, interpretation and reviewed the final draft. YWT and SSC were in equal contribution to this work. All authors read and approved the final version of the manuscript. Declaration Funding: None. Ethical approval: Chang Gung Memorial Hospital Institution Review Board (Ethical Review Committee). Ethical approval number: 201600399B0. Conflict of interest: none declared. 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Endocrinology 2004 ; 145 : 2273 – 82 . Google Scholar CrossRef Search ADS PubMed 29. Trirogoff ML , Shintani A , Himmelfarb J et al. Body mass index and fat mass are the primary correlates of insulin resistance in nondiabetic stage 3-4 chronic kidney disease patients . Am J Clin Nutr 2007 ; 86 : 1642 – 8 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Family PracticeOxford University Press

Published: Oct 28, 2017

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