Error bars indicate 95% confidence intervals.
eTable 1. Number of participants, replacement rate and crude prevalence of diabetes and pre-diabetes in each province
eTable 2. Weighted percentages (95% confidence intervals) of diabetes and pre-diabetes diagnosed by different glycemic measurements
eTable 3. Numbers of participants and unweighted percentages of diabetes among Chinese adults aged =18 years, 2010
eTable 4. Numbers of participants and unweighted percentages of prediabetes among Chinese adults aged =18 years, 2010
eTable 5. Numbers of participants and unweighted percentages of awareness, treatment and control of diabetes among Chinese adults aged =18 years, 2010
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Xu Y, Wang L, He J, et al. Prevalence and Control of Diabetes in Chinese Adults. JAMA. 2013;310(9):948–959. doi:10.1001/jama.2013.168118
Noncommunicable chronic diseases have become the leading causes of mortality and disease burden worldwide.
To investigate the prevalence of diabetes and glycemic control in the Chinese adult population.
Design, Setting, and Participants
Using a complex, multistage, probability sampling design, we conducted a cross-sectional survey in a nationally representative sample of 98 658 Chinese adults in 2010.
Main Outcomes and Measures
Plasma glucose and hemoglobin A1c levels were measured after at least a 10-hour overnight fast among all study participants, and a 2-hour oral glucose tolerance test was conducted among participants without a self-reported history of diagnosed diabetes. Diabetes and prediabetes were defined according to the 2010 American Diabetes Association criteria; whereas, a hemoglobin A1c level of <7.0% was considered adequate glycemic control.
The overall prevalence of diabetes was estimated to be 11.6% (95% CI, 11.3%-11.8%) in the Chinese adult population. The prevalence among men was 12.1% (95% CI, 11.7%-12.5%) and among women was 11.0% (95% CI, 10.7%-11.4%). The prevalence of previously diagnosed diabetes was estimated to be 3.5% (95% CI, 3.4%-3.6%) in the Chinese population: 3.6% (95% CI, 3.4%-3.8%) in men and 3.4% (95% CI, 3.2%-3.5%) in women. The prevalence of undiagnosed diabetes was 8.1% (95% CI, 7.9%-8.3%) in the Chinese population: 8.5% (95% CI, 8.2%-8.8%) in men and 7.7% (95% CI, 7.4%-8.0%) in women. In addition, the prevalence of prediabetes was estimated to be 50.1% (95% CI, 49.7%-50.6%) in Chinese adults: 52.1% (95% CI, 51.5%-52.7%) in men and 48.1% (95% CI, 47.6%-48.7%) in women. The prevalence of diabetes was higher in older age groups, in urban residents, and in persons living in economically developed regions. Among patients with diabetes, only 25.8% (95% CI, 24.9%-26.8%) received treatment for diabetes, and only 39.7% (95% CI, 37.6%-41.8%) of those treated had adequate glycemic control.
Conclusions and Relevance
The estimated prevalence of diabetes among a representative sample of Chinese adults was 11.6% and the prevalence of prediabetes was 50.1%. Projections based on sample weighting suggest this may represent up to 113.9 million Chinese adults with diabetes and 493.4 million with prediabetes. These findings indicate the importance of diabetes as a public health problem in China.
Noncommunicable chronic diseases have become the leading causes of mortality and disease burden worldwide. It was estimated that 34.5 million deaths globally were due to noncommunicable diseases in 2010, which reflected a significant increase from 1990.1,2 Mortality from diabetes doubled during this period and increased to 1.3 million deaths worldwide in 2010.1 In addition, diabetes is a major risk factor for ischemic heart disease and stroke, which collectively killed an estimated 12.9 million people globally in 2010.1,2 As the most populous country, the rapid increase in morbidity and mortality from noncommunicable diseases in China contributed to this pandemic.3,4 According to national data, noncommunicable diseases accounted for an estimated 80% of deaths and 70% of total disease burden in China in 2005.4
The prevalence of diabetes has increased significantly in recent decades and is now reaching epidemic proportions in China.5-8 The prevalence of diabetes was less than 1% in the Chinese population in 1980.6 In subsequent national surveys conducted in 1994 and 2000-2001, the prevalence of diabetes was 2.5% and 5.5%, respectively.7,8 The most recent national survey in 2007 reported that the prevalence of diabetes was 9.7%, representing an estimated 92.4 million adults in China with diabetes.5 Although different sampling methods, screening procedures, and diagnostic criteria were used, these data document a rapid increase in diabetes in the Chinese population.
Recently, the American Diabetes Association (ADA) integrated glycated hemoglobin A1c (HbA1c) into the diagnostic criteria for diabetes in its updated 2010 guidelines.9 Just as there is less than 100% concordance between fasting plasma glucose and 2-hour plasma glucose tests, there is not full concordance between HbA1c and either glucose-based test. Therefore, the prevalence of diabetes could be underestimated in the previous national surveys based on the ADA 2010 criteria. Furthermore, the previous national surveys could not assess diabetes control in the Chinese population because HbA1c was not measured. To estimate the prevalence and control of diabetes in the general Chinese population, we measured HbA1c, fasting plasma glucose, and 2-hour plasma glucose in a large and nationally representative sample of 98 658 adults who were 18 years or older in 2010.
China Noncommunicable Disease Surveillance 2010 included all 162 study sites from the Chinese Center for Disease Control and Prevention’s (CDC’s) National Disease Surveillance Point System, which was designed to select a nationally representative sample of the general population, covering major geographic areas of all 31 provinces, autonomous regions, and municipalities in mainland China.10 The first level of sampling was stratified by 7 geographic regions (Northeast, North, East, South, Southwest, Northwest and Central areas) and 3 municipalities (Beijing, Tianjin, and Shanghai). The second level of sampling was stratified by urban and rural locations. The third level of sampling was stratified by 4 socioeconomic strata in rural areas and 3 population size strata in urban areas. The Surveillance Point System includes approximately 1% of the total Chinese population.10
At each site, a complex, multistage, probability sampling design was used to select participants who were representative of civilian, noninstitutionalized Chinese adults. Only persons who had been living in their current residence for at least 6 months were eligible to participate. In the first stage, 4 subdistricts in urban areas or townships in rural areas were selected from each site with probability proportional to size. In the second stage, 3 neighborhood communities or administrative villages were selected with probability proportional to size. In the third stage, households within each neighborhood community or administrative village were listed, and 50 households were randomly selected. In the final stage, 1 person who was at least 18 years old was selected randomly from each household using a Kish selection table.11 When the selected individual refused or was unavailable, a replacement household was selected from all households of similar composition in the same neighborhood or village after excluding the already selected households using the simple random sampling method. The replacements were used to ensure an adequate sample size within each selected neighborhood community or administrative village and to maximize the national representativeness of the surveyed samples with regard to geographic distribution, economic development, and urbanization. The households in our study were categorized into single-person households, families of couples who were married or cohabiting adults with or without children, single-parent families, or households with 3 or more cohabiting generations. The household composition information was obtained from the government household registration system, which includes personal identifiers such as name, parents, spouse, and date of birth for each member within a household who is a local permanent resident. If the second household did not participate, a third household was selected. All replacements were successfully recruited by the third sampling. If no available replacement was found in the same neighborhood or village, the nearest neighborhood or village was used. A total of 109 023 people were selected and 98 658 participated in the survey. The overall response rate was 90.5% (replacement rate, 9.25%, eTable 1 in the Supplement).
The study protocol was approved by the ethical review committee of the China CDC and other participating institutes. Written informed consent was obtained from all study participants.
Data collection was conducted in examination centers at local health stations or community clinics in the participants’ residential area by trained staff according to a standard protocol. A questionnaire including information on demographic characteristics, medical history, and lifestyle factors was administered by trained interviewers. Current smoking was defined as having smoked 100 cigarettes in one’s lifetime and currently smoking cigarettes. Current drinking was defined as alcohol intake more than once per month during the past 12 months. The Global Physical Activity Questionnaire was used to assess physical activity.12 Body weight and height were measured according to a standard protocol and body mass index (BMI), which is calculated as weight in kilograms divided by height in meters squared. Waist circumference was measured on standing participants midway between the lower edge of the costal arch and the upper edge of the iliac crest. Overweight was defined as a BMI of 25.0 to 29.9, and obesity was defined as a BMI of 30.0 or higher.13 Central obesity was defined as waist circumference 90 cm or more in men and 80 cm or more in women.14 Blood pressure was measured at the nondominant arm 3 times consecutively with a 1-minute interval between the measurements with the participant in a seated position after 5 minutes of rest using an automated device (OMRON Model HEM-7071, Omron Co).
Blood samples were collected in all participants after an overnight fast of at least 10 hours. Participants without a self-reported history of diabetes were given a standard 75-g glucose solution, and plasma glucose was measured at 0 and 2 hours after administration during the oral glucose tolerance test. Blood specimens for the glucose test were collected using vacuum blood–collection tubes containing anticoagulant sodium fluoride and were centrifuged on site within 2 hours of collection. Plasma glucose was measured locally using glucose oxidase or hexokinase methods within 24 hours. All study laboratories successfully completed a standardization and certification program.
The Hemoglobin Capillary Collection System (Bio-Rad Laboratories) was used to collect capillary blood samples strictly according to the manufacturer’s instructions. Blood specimens prepared using this procedure were stable for up to 4 weeks at 2°C to 8°C. The capillary blood specimens were shipped and stored at 2°C to 8°C until HbA1c was measured within 4 weeks after collection by high-performance liquid chromatography using the VARIANT II Hemoglobin Testing System (Bio-Rad Laboratories) at the central laboratory in the Shanghai Institute of Endocrine and Metabolic Diseases, which was certificated by the National Glycohemoglobin Standardization Program. Capillary HbA1c was converted to venous values using a validated formula. In addition, we performed an internal validation study with paired samples from 6648 adults that showed high agreement in HbA1c values from capillary whole blood samples prepared with the Hemoglobin Capillary Collection System vs the venous whole blood samples collected using EDTA tubes (capillary HbA1c = 0.0143 + 0.9983 × [venous HbA1c]).
Serum samples were aliquoted and frozen at −80°C within 2 hours of collection and shipped by air in dry ice to the central laboratory, which was certificated by the College of American Pathologists. Serum total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides were measured using an autoanalyser (Abbott Laboratories).
A stringent quality assurance and quality control program was implemented to ensure the validity and reliability of study data. All investigators and research staff underwent a weeklong training session on the use of standardized protocols and instruments for data collection. Only certified staff were allowed to collect data. All laboratory equipment was calibrated and blinded duplicate samples were used. All data were double entered in a database and then compared and corrected for errors.
According to the ADA 2010 criteria, diabetes was defined as (1) a self-reported previous diagnosis by health care professionals, (2) fasting plasma glucose level of 126 mg/dL or higher (to convert to millimoles per liter, multiply by 0.0555), (3) 2-hour plasma glucose level of 200 mg/dL or higher, or (4) HbA1c concentration of 6.5% or more. Prediabetes or categories of increased risk of diabetes were defined as (1) fasting plasma glucose levels between 100 mg/dL and 125 mg/dL, (2) 2-hour plasma glucose levels between 140 mg/dL and 199 mg/dL, or (3) HbA1c concentrations between 5.7% and 6.4% in participants without a prior diabetes diagnosis. Awareness was defined as the proportion of individuals who reported a history of physician-diagnosed diabetes among all patients with diabetes. Treatment was defined as the proportion of individuals taking diabetes medications among all patients with diabetes. Control was defined as the proportion of individuals with an HbA1c concentration of less than 7.0% among patients with diabetes who were treated.
Demographic and metabolic characteristics of study participants were described in means (95% CIs) for continuous variables and percentages (95% CIs) for categorical variables in the overall population and in subgroups of sex, location (urban/rural), age, stages of economic development, and categories of BMI and waist circumference. Prevalence and 95% CIs of diabetes, prediabetes, and subtypes by various criteria were estimated by subgroups and overall. Each of the 162 study sites was categorized into underdeveloped, intermediately developed, or developed according to their region’s gross domestic product per capita in 2009. Age-standardized prevalences of Chinese adults with diabetes and prediabetes were also estimated in the overall population and among subgroups based on China 2010 census data.
All calculations were weighted to represent the overall Chinese adult population aged 18 years or older. Weight coefficients were derived from 2010 China population census data and the sampling scheme of the current survey to obtain national estimates. Standard errors were calculated using the Taylor-linearization method appropriate for the complex survey design. A multivariable multinomial logit analysis was used to examine the association of demographic, lifestyle, and metabolic factors with the odds of diabetes and prediabetes. All P values are 2-tailed and have not been adjusted for multiple testing. A P value <.05 was considered statistically significant. All statistical analyses were conducted using the SAS system, version 9.3 (SAS Institute Inc) and SUDAAN software, version 10.0 (Research Triangle Institute).
The general characteristics and metabolic risk factors of the study population are presented in Table 1 and Table 2.
The prevalence of diabetes was estimated to be 11.6% (95% CI, 11.3%-11.8%) in Chinese adults, 12.1% (95% CI, 11.7%-12.5%) in men, and 11.0% (95% CI, 10.7%-11.4%) in women (Table 3), with an estimated prevalence of 8.1% (95% CI, 7.9%-8.3%) for newly detected diabetes: 8.5% (95% CI, 8.2%-8.8%) in men and 7.7% (95% CI, 7.4%-8.0%) in women and was 3.5% (95% CI, 3.4%-3.6%) for those with previously diagnosed diabetes: 3.6% (95% CI, 3.4%-3.8%) in men and 3.4% (95% CI, 3.2%-3.5%) in women. Among the 3 glycemic parameters, a 2-hour plasma glucose concentration of 200 mg/dL or higher was less frequent (3.5%; 95% CI, 3.4%-3.7%) than fasting plasma glucose concentration of 126 mg/dL or higher (4.5%; 95% CI, 4.4%-4.7%) or an HbA1c concentration of 6.5% or more (4.6%; 95% CI, 4.4%-4.7%) among individuals without a history of diabetes (Table 3 and eTables 2 and 3 in the Supplement). The prevalence of diabetes was higher in urban than in rural residents in both men and women (Table 3 and Figure). Furthermore, diabetes prevalence increased with age in both men and women (P value for trend <.001), and men younger than 50 years had a higher prevalence, whereas women older than 60 years had a higher prevalence (Figure). In addition, the prevalence of diabetes increased with economic development, as well as in overweight and obese persons (Table 3, Figure).
The estimated prevalence of prediabetes was 50.1% (95% CI, 49.7%-50.6%) in Chinese adults: 52.1% (95% CI, 51.5%-52.7%) in men and 48.1% (95% CI, 47.6%-48.7%) in women (Table 4). The prevalence estimated by 2-hour plasma glucose alone was much lower than by either fasting plasma glucose or HbA1c alone (eTables 2 and 4 in the Supplement). Rural residents had slightly higher prevalence of prediabetes than did urban residents, especially in men (Figure). The prevalence of prediabetes increased with age (P value for trend <.001), and was higher in men younger than 50 years (Figure). Additionally, prediabetes was more prevalent in economically underdeveloped regions, as well as in overweight and obese persons (Table 4, Figure).
The proportion of diabetes patients who were aware of their condition was 30.1% (95% CI, 29.1%-31.1%) among the Chinese general population: 29.7% (95% CI, 28.3%-31.2%) in men and 30.5% (95% CI, 29.1%-31.9%) in women. Only 25.8% (95% CI, 24.9%-26.8%) of overall patients with diabetes were treated for this condition: 25.5% (95% CI, 24.2%-26.9%) in men and 26.2% (95% CI, 24.9%-27.5%) in women. Among those treated, 39.7% (95% CI, 37.6%-41.8%) had their HbA1c controlled to a concentration of less than 7.0%: 40.7% (95% CI, 37.6%-43.7%) in men and 38.6% (95% CI, 35.9%-41.3%) in women (Table 5, eTable 5 in the Supplement). The proportions of those who were aware of, treated for, and managed their glucose levels were higher in urban than in rural residents and higher in economically developed and intermediately developed regions than in underdeveloped regions. Women living in rural areas had a substantially lower proportion of controlled diabetes than did their male counterparts or than did women living in urban areas (Table 5). Similarly, women living in underdeveloped regions had a much lower control rate than men living in the same regions or women living in intermediately developed or developed regions.
In the multivariable, multinomial, logit models, male sex; older age; urban residency; parental history of diabetes; overweight; obesity; central obesity; elevated systolic blood pressure; and elevated serum total cholesterol, LDL-cholesterol, and triglyceride levels were all significantly associated with a higher risk of diabetes (Table 6). Current cigarette smoking, alcohol consumption, higher serum HDL-cholesterol level, and living in intermediately developed regions were associated with a lower risk of diabetes. In addition, male sex, older age, parental history of diabetes, overweight, obesity, central obesity, physical activity, elevated systolic blood pressure, and elevated serum total cholesterol were positively associated with a higher risk of prediabetes. Higher education, higher serum HDL-cholesterol and triglycerides levels, and living in intermediately developed and developed regions were inversely associated with prediabetes (Table 6).
This large national survey documents that diabetes has become a major public health problem in the general population of China. Our study estimated that approximately 11.6% of Chinese adults 18 years or older may have had diabetes in 2010. In addition, the weighted results suggest that half of the entire Chinese adult population (50.1%) may have had prediabetes, which is an important risk factor for the development of overt diabetes and cardiovascular disease.15,16 Furthermore, among patients with diabetes, it is estimated that less than one-third (30.1%) were aware of their condition and only one-quarter (25.8%) reported receiving treatment for diabetes. Moreover, only little more than one-third of patients (39.7%) treated for diabetes had adequate glycemic control. These data suggest that diabetes may have reached an alert level in the Chinese general population, with the potential for a major epidemic of diabetes-related complications, including cardiovascular disease, stroke, and chronic kidney disease in China in the near future without an effective national intervention.
The prevalence of diabetes was estimated to be 8.3% worldwide in 2012, representing a total of 371 million people living with diabetes.17 The prevalence of diabetes in Asian populations has increased rapidly in recent decades with a disproportionate burden among young and middle-aged individuals.18 It was estimated that the national prevalence of diabetes was 9.0% in India.17 Our study and a previous study by Yang et al5 indicate that China is now among the countries with the highest diabetes prevalence in Asia and has the largest absolute disease burden of diabetes in the world. Projections from our study estimate that 113.9 million Chinese adults 18 years or older (60.5 million men and 53.4 million women) may have had diabetes and 493.4 million (260.1 million men and 233.3 million women) may have had prediabetes in 2010. The estimated prevalence of diabetes in the Chinese population is very similar to the US population (11.3%) even though overweight and obesity are much more common in the United States.19,20 The mean BMI was 23.7 in our study vs 28.7 in the US population.20 In addition, it has been suggested that poor nutrition in utero and early life combined with overnutrition in later life may contribute to the accelerated epidemic of diabetes in China.21
Diabetes is a major risk factor for morbidity and mortality worldwide.22 High blood glucose levels accounted for 21% of all deaths from ischemic heart disease and 13% of all deaths from stroke worldwide with 84% of these cardiovascular deaths in low- and middle-income countries.23 Diabetes is the most common underlying cause for chronic kidney disease.24 Diabetic retinopathy is the leading cause of blindness in working-age adults in many countries.25,26 Furthermore, recent studies have reported that diabetes is a risk factor for cancer.27-30 Improvement in glycemic control is the key for preventing diabetes-related complications.31 Our study indicates that the awareness, treatment, and control rates of diabetes in the general Chinese population may be disproportionately low, raising concern for future high rates of diabetes-related morbidity and mortality.
Our study used the most current 2010 ADA criteria, which include an HbA1c concentration of 6.5% or higher for the diagnosis of diabetes and may have partly contributed to the increased prevalence. When the 1999 World Health Organization criteria were used, both our study and the one in 20075 found similar prevalence estimates (9.7%). Nevertheless, with rapid economic growth and associated industrialization, urbanization, and lifestyle changes (increased high-calorie, high-fat, high-sugar, and high-sodium diets and decreased physical activity), prediabetes and diabetes have reached epidemic proportions in the Chinese population. Moreover, the prevalence of prediabetes was high in the younger age groups, which may translate into a greater epidemic of diabetes in the near future. A diabetes epidemic would further burden an already overloaded health care system in China. The health care costs for diabetes would likely become a huge financial burden to patients, their families, and society as whole.32 To avoid this societal burden, the primary prevention of diabetes should be a national priority for China.
Our study found that the prevalence of diabetes was lower but prediabetes was higher in underdeveloped regions. The reason for this is unclear but suggests that preventive interventions for diabetes should be used at all levels of economic development.
The present study has several strengths. First, it was conducted in a large nationally representative sample of the general population in China. Second, all 3 glycemic indexes for the diagnosis of diabetes—fasting plasma glucose, 2-hour plasma glucose, and HbA1c concentrations—were obtained, which provide a comprehensive estimation of diabetes prevalence and control in the Chinese population. In addition, a strict quality assurance and quality control program was implemented at every phase of the study to ensure data validity and reliability.
There are also several study limitations. First, the capillary blood sample, instead of venous blood, was used for HbA1c measurement. Because venous blood could be preserved in EDTA tubes for fewer than 7 days prior to HbA1c measurement, the Hemoglobin Capillary Collection System was the best method for collecting blood samples in remote areas for centralized analysis. Excellent agreement between capillary and venous HbA1c values (R2 = 0.987) has been documented,33 and a validated formula was available to convert capillary HbA1c into venous values. Second, we did not distinguish between type 1 and type 2 diabetes in this study. Nevertheless, type 2 diabetes is the predominant form of diabetes in adults.34 In addition, due to the cross-sectional nature of our study and potential reverse causation bias, associations between some risk factors and diabetes or prediabetes were in unexpected directions. Finally, participation after the initial invitation varied by province, with lower initial acceptance in urban than in rural provinces. These differences could have differentially affected prevalence estimates in urban and rural environments.
The estimated prevalence of diabetes and prediabetes in a representative sample of Chinese adults was 11.6% and 50.1%, respectively. Projections based on sample weighting suggest this may represent up to 113.9 million and 493.4 million adults, respectively. These findings indicate the importance of diabetes as a public health problem in China.
The Corresponding Authors: Guang Ning, MD, PhD, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, 197 Rui-Jin 2nd Rd, Shanghai, 200025, China (firstname.lastname@example.org); Wenhua Zhao, PhD (email@example.com); and Weiqing Wang, MD, PhD (firstname.lastname@example.org).
Author Contributions: Drs Ning and W. Zhao had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Y. Xu, Limin Wang, He, and Bi contributed equally to this work. Drs Weiqing Wang, Wenhua Zhao, and Ning jointly directed this work.
Study concept and design: Y. Xu, L. Wang, Bi, Y. Jiang, Dai, Y. Li, Hu, Mi, G. Li, Mu, J. Zhao, Kong, J. Chen, Wang, W. Zhao, Ning.
Acquisition of data: Y. Xu, Limin Wang, M. Li, T. Wang, Linhong Wang, Jiang, Dai, Lu, M. Xu, Y. Li, Hu, J. Li, Mi, G. Li.
Analysis and interpretation of data: Y. Xu, He, Bi, M. Li, T. Wang, Jiang, Lu, M. Xu, C-H. Chen, J. Zhao, Lai, Wang, Ning.
Drafting of the manuscript: Y. Xu, He, Bi, M. Li, J. Li.
Critical revision of the manuscript for important intellectual content: Limin Wang, He, Bi, T. Wang, Linhong Wang, Jiang, Dai, Lu, M. Xu, Y. Li, Hu, Mi, C. Chen, G. Li, Mu, J. Zhao, Kong, J. Chen, Lai, Wang, W. Zhao, Ning.
Statistical analysis: Y. Xu, He, Bi, M. Li, Y. Jiang, M. Xu, Hu, J. Li, C. Chen, Lai.
Administrative, technical, or material support: L. Wang, Bi, T. Wang, L. Wang, Jiang, Dai, Lu, M. Xu, Y. Li, Hu, Mi, Mu, J. Zhao, Kong, Wang, W. Zhao, Ning.
Study supervision: L. Wang, Bi, Jiang, G. Li, Mu, J. Zhao, Kong, J. Chen, Wang, W. Zhao, Ning.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Investigators for the 2010 China Noncommunicable Disease Surveillance Group
Advising group–Lingzhi Kong, Gonghuan Yang, Yude Chen, Guangwei Li, Keji Li, Dong Zhao, Jialun Chen, Changyu Pan, Zhengpei Zeng, Guang Ning, Yiming Mu, Weiping Teng, Eryuan Liao, Jiajun Zhao, Weiqing Wang, Xiaohui Guo, Tianpei Hong, Mingcai Qiu, Caiping Li, Zhongyan Shan, Zhimin Liu, Xin Gao, Chao Liu, Lulu Chen, Li Yan, Nanwei Tong, Bingyin Shi, Jiapu Ge, Xiaoping Xing, Jie Liu, Huacong Deng, Biao Chen, Chunming Chen, Junshi Chen, Hui Li, Lisheng Liu, Dantao Peng, Xiaoming Shi, Wenzhi Wang, Yongjun Wang, Zhenglai Wu.
Working Group–Guang Ning, Wenhua Zhao, Yufang Bi, Jianqiang Lai, Yong Jiang, Limin Wang, Meng Dai, Nan Hu, Zhengjing Huang, Jianhong Li, Xiaoyan Li, Yichong Li, Zhihui Wang, Mei Zhang, Peng Yin, Yu Xu, Wenzhong Zhou, Yamin Bai, Xiaoning Cai, Guoping Cao, Xiaorong Chen, Wenlan Dong, Leilei Duan, Yajing Feng, Yuan He, Yun Huang, Mian Li, Boren Li, Shengquan Mi, Xiaoqian Shi, Baohua Wang, Chunxiao Wang, Tiange Wang, Yilong Wang, Zhuoqun Wang, Hongxi Wu, Dan Xing, Jing Yang, Xingquan Zhao, Tao Zheng, Jingren Yang, Di Zhang, Yubei Wu.
Funding/Support: This work is supported by the Chinese Ministry of Finance grants 1994DP131044 from the Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health; 201002002 from the Sector Funds of Ministry of Health; 2012ZX09303006-001 from the National Key New Drug Creation and Manufacturing Program of Ministry of Science and Technology; 2011AA020107 from the National High Technology Research and Development Program of China (863 Program); and 81030011, 81222008, and 81130016 from the National Natural Science Foundation of China.
Role of the Sponsor: The funding agencies had no role in the design and conduct of the study, in the collection, management, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript or decision to submit for publication.
Additional Contributions: We thank all 3240 research staff from local Centers for Disease Control and Prevention for their collection of data and blood samples. We also thank all the study participants for their participation and contribution.
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