The study is aimed to investigate the pathogenesis underlying the increased prevalence of thyroid nodule (TN) in different levels of metabolic syndrome (MetS) components and analyze the relationships between TN and MetS components. A total of 6,798 subjects, including 2201 patients with TN, were enrolled in this study. Anthropometric, biochemical, thyroid ultrasonographic, and other metabolic parameters were all measured. There was obviously sexual difference in the prevalence of TN (males 26.0%, females 38.5%, resp.). The prevalence of TN in hyperuricemia (45.7% versus 37.4%,
Thyroid nodule (TN), one of the most common clinical thyroid diseases, has been becoming increasingly prevalent all over the world in the last decades and its associated risk factors have received much attention [
Previous studies have showed that impaired glucose metabolism is an independent risk factor for increased thyroid volume and nodule prevalence [
Based on this issue, the main purpose of this study was to investigate the prevalence of TN among a population aged over 45 years with different glucose metabolic status and to comprehensively investigate the association between TN diagnosed on ultrasonography and the MetS components in the SHDC-CDPC Community-based Study (Shenkang Hospital Development Center for Chronic Disease Prevention and Control project, Shanghai, China). A total of 7,920 individuals with age above 45 years were enrolled in the epidemiological investigation in a rural Chinese population. The different levels of metabolic indices between the TN group and control group were measured and compared. Our study would strengthen the associations between TN and the components of MetS and increase knowledge in gender disparity on the prevalence of TN.
From October 2014 to July 2015, a total of 7,920 local inhabitants aged 45 years or older who had been living in Sijing, Shanghai, for 1 year or longer before the enrollment and represented ten rural communities, were enrolled in this cross-section survey. A comprehensive survey was administered by the trained research staff to obtain a detailed questionnaire, anthropometry index, medical history, family histories of chronic diseases, and current medication use. Meanwhile, smoking and drinking status were also recorded. Through multiple screenings, 476 individuals were excluded from the study with missing data on questionnaire, anthropometry index, demographic variables, physical examination data, or the glucose metabolic indexes. Furthermore, subjects who met the exclusion criteria, including illnesses, such as hypothyroidism, hyperthyroidism, chronic renal failure, excessive drinking (an alcohol intake > 140 g/week for men or >70 g/week for women), or current medication use affecting body composition, thyroid function, lipid profile, serum UA level, and glucose metabolic status, were excluded in the data analysis. In the end, a total of 6798 subjects and 2201 of them with TN were included in the final data analysis. The study protocol has been approved by the Committee on Human Research at Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine. Written informed consent was obtained from each participant.
All subjects had a physical examination in a fasting state. Blood pressure was measured in the all participants seated quietly for at least five minutes thrice consecutively and the average of three measurements was recorded. Waist circumference (WC) was measured in standing subjects, midway between the lower edge of the costal arch and the top of the iliac crest. Hip circumference (HC) was measured in standing subjects, around the widest portion of the buttocks. Body mass index (BMI) was calculated as body weight/height2 in kg/m2. Waist-to-hip ratio (WHR) was calculated as WC divided by HC. In a supine position and the hyperextended neck of all participants, ultrasound examination of the thyroid nodules, including the TN number and location, was performed and evaluated independently by the two senior experts using a B-mode high-resolution tomographic ultrasound system (Toshiba, Tokyo, Japan).
Venous blood samples were collected from all participants in the morning after an overnight fasting for at least 10 hours. The subjects without diagnosis of diabetes underwent the oral standard 75 g glucose tolerance test (OGTT) and the previously diagnosed diabetes underwent the steamed bread meal test. Biochemical measurements, including plasma glucose concentrations, uric acid (UA), serum lipid profile containing levels of total cholesterol (TCH), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG), were measured enzymatically using an automatic biochemistry analyzer (HITACHI 7600). Fasting plasma insulin (FINS) concentration, serum level of thyroid-stimulating hormone (TSH), free triiodothyronine (FT3) concentration, free tetraiodothyronine (FT4) concentration, and thyroid peroxidase antibody (TPOAB) concentration were measured by electrochemiluminescence analyzer (Roche Diagnostics, Basel, Switzerland). The homoeostasis model assessment for insulin resistance index (HOMA-IR) was calculated by multiplying fasting plasma insulin (mIU/l) and fasting plasma glucose (FPG) (mM) and dividing the result by 22.5. Beta cell function (HOMA-beta) was calculated as 20x fasting plasma insulin (mIU/l)/(FPG (mM) −3.5) ×100%. Glycosylated hemoglobin (HbA1c) was measured by high-performance liquid chromatography (D10; Bio-Rad Laboratories, Inc., CA).
The MetS was defined according to the IDF criteria [
All statistical analyses were performed using the SAS version 9.2 (SAS Institute Inc., Cary, NC, USA). Demographic, metabolic features and other clinical parameters were described by sex using frequency (percentage) for categorical variables and median (interquartile range) for continuous variables, respectively. Additionally, we divided the participants into different subgroups with and without thyroid nodules according to the different levels of MetS components and clinical characteristics. Differences on metabolic characteristics in subjects with or without TN were evaluated using
Clinical characteristics of the total of 6,798 participants including 3289 males and 3509 females, with a median age of 58.8 years (52.5–66.0), stratified by gender with and without thyroid nodules, were presented in Table
Clinical characteristics of the participants according to the presence or absence of thyroid nodules stratified by gender.
Parameters | Total subjects ( |
Statistic |
|
Male ( |
Statistic |
|
Female ( |
Statistic |
| |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Thyroid nodules | Nonthyroid nodules | Thyroid nodules | Nonthyroid nodules | Thyroid nodules | Nonthyroid nodules | |||||||
Participants | 2201 (32.4) | 4597 (67.6) | 854 (26.0) | 2435 (74.0) | 1352 (38.5) | 2157 (61.5) | ||||||
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Age (years) | 60.8 (55.1,67.9) | 57.9 (51.4,64.9) | 11.911 | <0.001 | 61.1 (55.6,67.7) | 58.1 (52,65) | 8.12 | <0.001 | 60.6 (54.8,68) | 57.6 (50.7,64.8) | 9.09 | <0.001 |
Smoking, |
470 (22.1) | 1342 (30.2) | 48.20 | <0.001 | 465 (55.4) | 1332 (56.2) | 0.170 | 0.680 | 5 (0.4) | 10 (0.5) | 0.17 | 0.684 |
Drinking, |
226 (10.7) | 802 (18.2) | 60.32 | <0.001 | 216 (26.3) | 785 (33.6) | 14.97 | <0.001 | 10 (0.8) | 17 (0.8) | 0.02 | 0.883 |
SBP (mmHg) | 136.0 (124.7,149.0) | 134.0 (122.7,146.3) | 4.43 | <0.001 | 135.3 (123.7,148.3) | 134.0 (123.3,146.3) | 1.71 | 0.088 | 136.7 (125.3,149) | 133.7 (122.3,146.3) | 4.29 | <0.001 |
DBP (mmHg) | 77.0 (70.7,83.3) | 77.7 (71.0,84.3) | −2.82 | 0.005 | 78.0 (71.3,84.3) | 79 (72,86) | −2.81 | 0.005 | 76.7 (70.3,82.7) | 76.3 (70,82.7) | 0.257 | 0.797 |
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BMI (kg/m2) | 24.2 (22.1,26.5) | 24.3 (22.1,26.5) | −0.66 | 0.512 | 24.4 (22.4,26.5) | 24.6 (22.3,26.6) | −0.42 | 0.672 | 24.1 (21.9,26.5) | 24 (21.9,26.3) | 0.23 | 0.822 |
WC (cm) | 86 (80,92) | 86 (80,93) | −0.58 | 0.564 | 88 (82,93) | 87 (81,94) | 0.93 | 0.354 | 84 (78,91) | 84 (78,91) | 0.66 | 0.506 |
WHR | 0.9 (0.9,1) | 0.9 (0.9,0.9) | −0.51 | 0.611 | 0.9 (0.9,1.0) | 0.9 (0.9,1.0) | 1.29 | 0.199 | 0.9 (0.9,0.9) | 0.9 (0.8,0.9) | 0.78 | 0.437 |
TCH (mmol/l) | 5.1 (4.5,5.8) | 5.1 (4.5,5.7) | 1.90 | 0.057 | 4.8 (4.3,5.4) | 4.9 (4.4,5.5) | −2.15 | 0.032 | 5.3 (4.7,5.9) | 5.2 (4.7,5.9) | 1.57 | 0.117 |
TG (mmol/l) | 1.4 (1.0,1.9) | 1.3 (0.9,2.0) | 0.67 | 0.500 | 1.4 (1.0,2.0) | 1.4 (0.9,2.1) | −0.12 | 0.902 | 1.4 (1,1.9) | 1.3 (0.9,1.9) | 1.64 | 0.102 |
HDL-C (mmol/l) | 1.5 (1.3,1.8) | 1.5 (1.3,1.8) | 0.75 | 0.451 | 1.4 (1.2,1.6) | 1.4 (1.2,1.7) | −2.95 | 0.003 | 1.6 (1.4,1.9) | 1.6 (1.4,1.9) | 0.03 | 0.973 |
LDL-C (mmol/l) | 2.9 (2.4,3.4) | 2.8 (2.4,3.3) | 1.65 | 0.099 | 2.7 (2.2,3.2) | 2.7 (2.3,3.2) | −1.510 | 0.131 | 3 (2.5,3.5) | 2.9 (2.5,3.5) | 1.24 | 0.215 |
UA ( |
306 (256,363) | 313 (261,369) | −2.73 | 0.006 | 353 (304,404) | 350 (302,404) | 0.09 | 0.930 | 280 (237,329) | 273 (235,318) | 3.20 | 0.001 |
FPG (mmol/l) | 5.7 (5.3,6.3) | 5.7 (5.3,6.2) | 2.48 | 0.013 | 5.7 (5.3,6.3) | 5.7 (5.3,6.3) | −0.08 | 0.938 | 5.7 (5.4,6.3) | 5.7 (5.3,6.1) | 4.01 | <0.001 |
PPG (mmol/l) | 7.6 (6.2,10.0) | 7.3 (6.0,9.4) | 5.07 | <0.001 | 7.3 (5.9,10.1) | 7.2 (5.8,9.6) | 1.49 | 0.135 | 7.8 (6.5,9.9) | 7.3 (6.1,9.2) | 4.96 | <0.001 |
HbA1c (%) | 5.6 (5.3,6.0) | 5.6 (5.3,5.9) | 4.76 | <0.001 | 5.6 (5.3,6) | 5.6 (5.3,5.9) | 2.26 | 0.024 | 5.6 (5.4,5.9) | 5.6 (5.3,5.8) | 4.71 | <0.001 |
FINS (mIU/l) | 7.2 (4.9,10.7) | 6.8 (4.6,9.9) | 4.10 | <0.001 | 6.4 (4.2,9.6) | 6.2 (4.1,9.2) | 1.21 | 0.225 | 7.7 (5.3,11) | 7.5 (5.2,10.6) | 2.15 | 0.032 |
HOMA-IR | 1.9 (1.2,2.9) | 1.8 (1.1,2.6) | 4.73 | <0.001 | 1.7 (1,2.7) | 1.7 (1,2.5) | 1.65 | 0.098 | 2 (1.3,3) | 1.9 (1.3,2.8) | 3.03 | 0.002 |
HOMA-beta | 61.6 (42.2,89.1) | 59.9 (40.6,85.2) | 2.18 | 0.029 | 54.3 (34.6,82.6) | 53.7 (35.4,79.2) | 0.61 | 0.545 | 65.5 (47.1,93) | 66.7 (47,90.9) | −0.27 | 0.789 |
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FT3 (pmol/l) | 4.9 (4.5,5.4) | 5.1 (4.7,5.5) | −8.79 | <0.001 | 5.2 (4.7,5.7) | 5.3 (4.9,5.7) | −3.70 | <0.001 | 4.8 (4.4,5.2) | 4.9 (4.5,5.3) | −4.01 | <0.001 |
FT4 (pmol/l) | 15.9 (14.7,17.4) | 15.8 (14.5,17.3) | 2.29 | 0.022 | 16.2 (14.8,18) | 16 (14.7,17.5) | 2.50 | 0.013 | 15.8 (14.5,17.1) | 15.6 (14.3,17) | 2.58 | 0.010 |
TSH (mIU/l) | 2.0 (1.5,2.7) | 2.1 (1.5,2.8) | −2.24 | 0.025 | 1.8 (1.4,2.5) | 1.9 (1.4,2.6) | −1.31 | 0.191 | 2.1 (1.6,2.8) | 2.3 (1.7,3) | −4.38 | <0.001 |
TPOAB (IU/ml) | 13.8 (8.7,22.8) | 12.5 (8.4,20.1) | 4.23 | <0.001 | 14.4 (9,23.5) | 12.4 (8.2,19.1) | 5.14 | <0.001 | 13.3 (8.4,22.4) | 12.7 (8.6,21.5) | 0.851 | 0.395 |
SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WC, waist circumference; WHR, waist-to-hip ratio; TCH, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, Low-density lipoprotein cholesterol; UA, uric acid; FPG, fasting plasma glucose; PPG, postprandial plasma glucose; HbA1c, Hemoglobin A1c; FINS, fasting plasma insulin; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; TPOAB, thyroid peroxidase antibody.
To explore the association of TN and related metabolic risk factors, the subjects were classified into different subgroups according to the different levels of MetS components and clinical characteristics (Table
Stratified analysis of prevalence of thyroid nodules according to the different levels of metabolic syndrome components.
Parameters |
Total subjects ( |
Males ( |
Females ( |
|||
---|---|---|---|---|---|---|
Thyroid nodules | Nonthyroid nodules | Thyroid nodules | Nonthyroid nodules | Thyroid nodules | Nonthyroid nodules | |
|
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<55 | 540 (24.1) | 1700 (75.9) | 194 (18.5) | 854 (81.5) | 346 (29.0) | 846 (71.0) |
55–65 | 912 (34.2) | 1756 (65.8) | 362 (27.2) | 967 (72.8) | 550 (41.1) | 789 (58.9) |
65–75 | 497 (39.4) | 765 (60.6) | 203 (32.3) | 426 (67.7) | 294 (46.5) | 339 (53.6) |
≥75 | 252 (41.0) | 362 (59.0) | 93 (34.1) | 180 (65.9) | 159 (46.6) | 182 (53.4) |
Chi-square | 123.139 | 53.725 | 75.329 | |||
|
<0.001 | <0.001 | <0.001 | |||
|
<0.001 | <0.001 | <0.001 | |||
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<25.0 | 1270 (32.8) | 2602 (67.2) | 465 (26.1) | 1319 (73.9) | 805 (38.6) | 1283 (61.5) |
25.0–30.0 | 755 (32.1) | 1601 (68.0) | 314 (25.3) | 929 (74.7) | 441 (39.6) | 672 (60.4) |
≥30.0 | 122 (32.5) | 254 (67.6) | 48 (28.9) | 118 (71.1) | 74 (35.2) | 136 (64.8) |
Chi-square | 0.380 | 1.076 | 1.479 | |||
|
0.827 | 0.584 | 0.477 | |||
|
0.618 | 0.888 | 0.806 | |||
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Q1 | 504 (31.1) | 1115 (68.9) | 187 (24.0) | 593 (76.0) | 317 (37.8) | 522 (62.2) |
Q2 | 515 (31.8) | 1105 (68.2) | 196 (24.7) | 597 (75.3) | 319 (38.6) | 508 (61.4) |
Q3 | 520 (32.1) | 1099 (67.9) | 203 (26.3) | 568 (73.7) | 317 (37.4) | 531 (62.6) |
Q4 | 544 (33.9) | 1062 (66.1) | 208 (26.8) | 567 (73.2) | 336 (40.4) | 495 (59.6) |
Chi-square | 3.034 | 2.222 | 1.941 | |||
|
0.386 | 0.528 | 0.585 | |||
|
0.101 | 0.144 | 0.372 | |||
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<90 in men | 812 (29.3) | 1964 (70.8) | 454 (25.1) | 1356 (74.9) | 358 (37.1) | 608 (62.9) |
<80 in women | ||||||
≥90 in men | 1281 (34.6) | 2425 (65.4) | 345 (26.2) | 973 (73.8) | 936 (39.2) | 1452 (60.8) |
≥80 in women | ||||||
Chi-square | 20.506 | 0.479 | 1.324 | |||
|
<0.001 | 0.489 | 0.250 | |||
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<2.8 | 1603 (31.0) | 3566 (69.0) | 649 (24.9) | 1954 (75.1) | 954 (37.2) | 1612 (62.8) |
≥2.8 | 597 (37.0) | 1016 (63.0) | 203 (30.1) | 472 (69.9) | 394 (42.0) | 544 (58.0) |
Chi-square | 20.194 | 7.366 | 6.758 | |||
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<0.001 | 0.001 | 0.009 | |||
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NGR, |
472 (29.9) | 1106 (70.1) | 195 (26.1) | 652 (73.9) | 277 (33.3) | 554 (66.7) |
Prediabetes, |
1094 (31.4) | 2390 (68.6) | 397 (24.1) | 1248 (75.9) | 697 (37.9) | 1142 (62.1) |
Diabetes, |
526 (37.2) | 889 (62.8) | 208 (28.8) | 515 (71.2) | 318 (46.0) | 374 (54.1) |
Chi-square | 20.773 | 5.746 | 25.896 | |||
|
<0.001 | 0.057 | <0.001 | |||
|
<0.001 | 0.253 | <0.001 | |||
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≤420 in men | 1856 (32.5) | 3862 (67.5) | 702 (26.6) | 1933 (73.4) | 1154 (37.4) | 1929 (62.6) |
≤360 in women | ||||||
>420 in men | 341 (32.2) | 719 (67.8) | 150 (23.4) | 492 (76.6) | 191 (45.7) | 227 (54.3) |
>360 in women | ||||||
Chi-square | 0.034 | 2.881 | 10.622 | |||
|
0.854 | 0.090 | 0.001 | |||
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Without NAFLD | 760 (32.2) | 1599 (67.8) | 254 (26.3) | 713 (73.7) | 506 (36.4) | 886 (63.7) |
NAFLD | 535 (33.4) | 1069 (66.7) | 214 (26.0) | 610 (74.0) | 321 (41.2) | 459 (58.9) |
Chi-square | 0.561 | 0.020 | 4.892 | |||
|
0.454 | 0.887 | 0.027 | |||
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Without MetS | 1168 (30.1) | 2716 (69.9) | 539 (25.6) | 1566 (64.3) | 629 (35.4) | 1150 (64.6) |
MetS | 876 (35.3) | 1605 (64.7) | 249 (25.8) | 716 (74.2) | 627 (41.4) | 889 (58.6) |
Chi-square | 19.041 | 0.014 | 12.500 | |||
|
<0.001 | 0.908 | <0.001 |
BMI, body mass index; WHR, waist-to-hip ratio; NGR, normal glucose regulation; UA, uric acid; NAFLD, nonalcoholic fatty liver disease; MetS, metabolic syndrome.
Finally, to explore whether the MetS and the associated other metabolic parameters were independently associated with TN. A multiple logistic regression analysis for the risk factors of TN involving all the significant different anthropometric and metabolic parameters, such as central obesity, HOMA-IR, HOMA-beta, FPG, PPG, FINS, hyperuricemia, NAFLD, and MetS, were applied in subjects with or without TN (Figure
Metabolic risk factors of thyroid nodules were analyzed using logistic regression in total, male and female subjects. Adjustment of age, drinking, smoking, and family history of thyroid disease; FINS, fasting plasma insulin; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; TPOAB, thyroid peroxidase antibody; NAFLD, nonalcoholic fatty liver disease.
The prevalence of TN and the accompanying thyroid tumors are the increasing public health problems [
Metabolic syndrome is a complex clinical disorder characterized by dyslipidemia, obesity, NAFLD, insulin resistance, hyperuricemia, and a disturbance of glucose metabolism. In our study, to further explore whether MetS components and the other metabolic risk parameters related to the pathogenesis of TN in subjects, all subjects were divided into different subgroups according to different metabolic status. Nearly 35.3% of subjects with MetS had TN. The results showed that the subjects with TN had significantly higher levels of FPG, PPG, HbA1c, FINS, HOMA-IR, HOMA-beta, and TPOAB than those without TN after adjusting for age. However, in addition to the above findings, after further stratified analysis of gender, there were still significant differences of FPG, PPG, FINS, HOMA-IR, and TSH between the groups with or without TN in females, but not in males. The females with hyperuricemia, NAFLD, or MetS had much higher prevalence of TN as compared with controls, whereas there were no such associations in males. Perhaps the most intriguing finding of our study was that the MetS were significantly associated with TN only in women. The one plausible explanation for this gender disparity in TN formation was the hormone testosterone, which might contribute to the protective roles against the harmful effects of MetS cluster in men compared to women. We concluded from our data that the prevalence of TN was more closely associated with the components of MetS in women than in men. Female subjects with MetS were at increased risk for TN. Few studies assessed gender disparity in the pathogenesis of TN formation [
Researchers have recently focused their interest on the pathogenesis of TN in subjects with abnormal glucose metabolism [
Recently, extensive studies have found the roles of NAFLD and hyperuricemia in IR. Up to now, we were unable to find any published studies to explore the role of NAFLD in pathogenesis of TN in a large population [
Ayturk et al. reported that higher serum TSH level was an independent risk factor for increased thyroid volume in MetS patients but failed to find the relationship between TSH and TN formation [
Although the components of metabolic syndrome lie among the risk factors for TN both in men and women, our results suggested that MetS components had the much stronger effects on the risk of TN in women than in men. In conclusion, age, gender, IR, MetS, and abnormal glucose metabolic status as well as hyperuricemia independently played the important roles in the pathological mechanisms of thyroid nodules. The prevalence of TN in female patients with MetS was significantly increased, which was significantly associated with the different levels of MetS components. The prevalence of TN in DM group was significantly higher than those in NGR and prediabetes groups only in females. The right managements of MetS aimed to adjust hyperuricemia, central obesity, abnormal glucose metabolism, and IR might be beneficial in the blocking of TN formation, especially in females. Our data supported the possible metabolic clues to the gender disparity of nodule formation. Hence, in the future, more cross-sectional and long-term cohort multicenter study on a large scale will be necessary to further verify and clarify the findings in this study.
Waist-to-hip ratio
Systolic blood pressure
Diastolic blood pressure
Body mass index
Waist circumference
Hip circumference
Nonalcoholic fatty liver disease
Total cholesterol
Triglyceride
High-density lipoprotein cholesterol
Low-density lipoprotein cholesterol
Uric acid
Fasting plasma glucose
Postprandial plasma glucose
Hemoglobin A1c
Fasting plasma insulin
Normal glucose regulation
Nonalcoholic fatty liver disease
Metabolic syndrome
Free triiodothyronine
Free thyroxine
Thyroid-stimulating hormone
Thyroid peroxidase antibody.
The authors declare that there are no conflicts of interest.
Xiaoying Ding, Ying Xu, and Yufan Wang contributed equally to this work.
The study was supported by grants from the Shanghai Shenkang Hospital Development Center for chronic disease prevention and control project (SHDC12015304), the Shanghai municipal health bureau key project fund (201440033), 2015 Wang Kuancheng medicine fund, 2015 Shanghai General Hospital Excellent physician project, the Songjiang district health bureau medical climbing project (0702N14003), and The science and technology committee project of Songjiang district (15SJGG54). The authors thank all the study participants and all the research staff for their participation and contribution.