The Highest Prevalence of Diabetes Recorded in Mainland ...Article Type: Research BMJ Journal: BMJ...

Confidential: For Review OnlyThe Highest Prevalence of Diabetes Recorded in Mainland

China: a National Epidemiologic Survey

Journal: BMJ

Manuscript ID BMJ-2019-051468

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the Author: 06-Jul-2019

Complete List of Authors: Li, Yongze; The First Hospital of China Medical UniversityTeng, Di; The First Hospital of China Medical UniversityShi, Xiaoguang; The First Hospital of China Medical UniversityQin, Guijun; University of Zhengzhou School of Medicine, China, Qin, Yingfen; The First Affiliated Hospital of Guangxi Medical UniversityQuan, Huibiao; Hainan General HospitalShi, Bingyin; The First Affiliated Hospital of Xi'an Jiaotong UniversitySun, Hui; Huazhong University of Science and TechnologyBa, Jianming; Chinese PLA General HospitalChen, Bing; Third Military Medical UniversityDu, Jianling; The First Affiliated Hospital of Dalian Medical UniversityHe, Lanjie; General Hospital of Ningxia Medical UniversityLai, Xiaoyang; Nanchang University Second Affiliated HospitalLi, Yanbo; The First Affiliated Hospital of Harbin Medical UniversityChi, Haiyi; Hohhot First HospitalLiao, Eryuan; The Second Xiangya Hospital, Central South UniversityLiu, Chao; Nanjing University of Chinese MedicineLiu, Libin; Fujian Medical University Union HospitalTang, Xulei; The First Hospital of Lanzhou University, Department of EndocrinologyTong, Nanwei; Sichuan UniversityWang, Guixia; The First Hospital of Jilin UniversityZhang, Jin-an; Jinshan Hospital of Fudan University, Department of EndocrinologyWang, Youmin; The First Affiliated Hospital of Anhui Medical UniversityXue, Yuanming; The First People's Hospital of Yunnan ProvinceYan, Li; ⑥ Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Department of Endocrinology and MetabolismYang, Jing; The First Hospital of Shanxi Medical UniversityYang, Lihui; People's Hospital of Tibet Autonomous RegionYao, Yongli; Qinghai Provincial People's HospitalYe, Zhen; Zhejiang Center for Disease Control and Prevention, China, Zhang, Qiao; Affiliated Hospital of Guiyang Medical UniversityZhang, Lihui; Second Hospital of Hebei Medical UniversityZhu, Jun; the First Affiliated Hospital of Xinjiang Medical UniversityZhu, Mei; Tianjin Medical University General HospitalNing, Guang; Shanghai Jiaotong University School of Medicine

https://mc.manuscriptcentral.com/bmj

BMJ

Confidential: For Review OnlyMu, Yiming; People’s Liberation Army General Hospital, China, Zhao, Jiajun; Shandong Provincial Hospital affiliated with Shandong UniversityTeng, Weiping; The Endocrine Institute and The Liaoning Provincial Key Laboratory of Endocrine Diseases, Department of Endocrinology and Metabolism, The First Hospital of China Medical University, Shan, Zhongyan; First Affiliated Hospital, Chinese Medical University,

Keywords: Diabetes, Prediabetes, China, Prevalence, Risk factors

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Confidential: For Review Only

The Highest Prevalence of Diabetes Recorded in Mainland China: a National Epidemiologic Survey

Running title: Prevalence of Diabetes in China

Yongze Li, Ph.D.1#, Di Teng, Ph.D1#, Xiaoguang Shi, M.D.1#, Guijun Qin, M.D.2#, Yingfen Qin, M.D.3#, Huibiao Quan,

M.D.4#, Bingyin Shi, M.D.5#, Hui Sun, M.D.6#, Jianming Ba, M.D.7, Bing Chen, M.D.8, Jianling Du, M.D9., Lanjie He,

M.D.10, Xiaoyang Lai, M.D.11, Yanbo Li, M.D.12, Haiyi Chi, M.D.13, Eryuan Liao, M.D.14, Chao Liu, M.D.15, Libin Liu,

M.D.16, Xulei Tang, M.D.17, Nanwei Tong, M.D.18, Guixia Wang, M.D.19, Jin-an Zhang, M.D.20, Youmin Wang, M.D.21,

Yuanming Xue, M.D.22, Li Yan, M.D.23, Jing Yang, M.D.24, Lihui Yang, M.D.25, Yongli Yao, M.D.26, Zhen Ye, M.D.27,

Qiao Zhang, M.D.28, Lihui Zhang, M.D.29, Jun Zhu, M.D.30, Mei Zhu, M.D.31, Guang Ning, M.D.32, Yiming Mu, M.D.7,

Jiajun Zhao, M.D.33, Weiping Teng, M.D.1* and Zhongyan Shan, M.D.1*

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Author Affiliations

1. Department of Endocrinology and Metabolism and the institute of Endocrinology, The First Hospital of China Medical

University, Shenyang, Liaoning, P.R. China, 110001;

2. Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital, Zhengzhou University,

Zhengzhou, Henan, P.R. China, 450052;

3. Department of Endocrine, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, P.R. China,

530021;

4. Department of Endocrinology, Hainan General Hospital, Haikou, Hainan, P.R. China, 570311;

5. Department of Endocrinology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi, P.R. China,

710061;

6. Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology,

Wuhan, Hubei, P.R. China, 430022;

7. Department of Endocrinology, Chinese PLA General Hospital, Beijing, P.R. China, 100853;

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8. Department of Endocrinology, Southwest Hospital, Third Military Medical University, Chongqing, P.R. China, 400038;

9. Department of Endocrinology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, P.R. China,

116011;

10. Department of Endocrinology, Cardiovascular and Cerebrovascular Disease Hospital of Ningxia Medical University,

Yinchuan, Ningxia, P.R. China, 750004;

11. Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang,

Jiangxi, P.R. China, 330006;

12. Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, P.R.

China, 150001;

13. Department of Endocrinology, Hohhot First Hospital, Hohhot, Inner Mongolia, P.R. China, 010000;

14. Department of Endocrinology and Metabolism, The Second Xiangya Hospital, Central South University, Changsha,

Hunan, P.R. China, 410011;

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15. Research center of Endocrine and Metabolic Diseases, Affiliated Hospital of Integrated Traditional Chinese and Western

Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, P.R. China, 210028;

16. Department of Endocrinology and Metabolism, Fujian Institute of Endocrinology, Fujian Medical University Union

Hospital, Fuzhou, Fujian, P.R. China, 350001;

17. Department of Endocrinology, the First Hospital of Lanzhou University, Lanzhou, Gansu, P.R. China, 730000;

18. Department of Endocrinology and Metabolism, State Key Laboratory of Biotherapy, West China Hospital, Sichuan

University, Chengdu, Sichuan, P.R. China, 610041;

19. Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, Jilin, P.R. China,

130021;

20. Department of Endocrinology, Shanghai University of Medicine & Health Science Affiliated Zhoupu Hosipital, Shanghai,

P.R. China, 201318;

21. Department of Endocrinology, The First Hospital of An Hui Medical University, Hefei, Anhui, P.R. China, 230000;

22. Department of Endocrinology, The First People's Hospital of Yunnan Province, Kunming, Yunnan, P.R. China, 650032;

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23. Department of Endocrinology and Metabolism, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou,

Guangdong, P.R. China, 510120;

24. Department of Endocrinology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, P.R. China, 030001;

25. Department of Endocrinology and Metabolism, People's Hospital of Tibet Autonomous Region, Lhasa, Tibet, P.R. China,

850000;

26. Department of Endocrinology, Qinghai Provincial People's Hospital, Xining, Qinghai, P.R. China, 810000;

27. Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, P.R. China, 310051;

28. Department of Endocrinology and Metabolism, Affiliated Hospital of Guiyang Medical University, Guiyang, Guizhou,

P.R. China, 550004;

29. Department of Endocrinology, Second hospital of Hebei Medical University, Shijiazhuang, Hebei, P.R. China, 050000;

30. Department of Endocrinology, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, P.R.

China, 830054;

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31. Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, P.R. China,

300052.

32. Department of Endocrinology and Metabolism and the institute of Endocrinology, Rui-Jin Hospital affiliated with

Shanghai Jiao-Tong University School of Medicine, Shanghai, P.R. China, 200025;

33. Department of Endocrinology, Shandong Provincial Hospital affiliated with Shandong University, Jinan, Shandong, P.R.

China, 250000;

#These authors contributed equally to this work.

*Corresponding author:

Zhongyan Shan, M.D, Ph.D., Department of Endocrinology and Metabolism, The First Hospital of China Medical

University, No. 155, Nanjing Bei street, Shenyang, P.R. China, 110001. E-mail address: [email protected]

Weiping Teng, M.D., The institute of Endocrinology ,The First Hospital of China Medical University, No. 155, Nanjing

Bei street, Shenyang, P.R. China, 110001. E-mail address: [email protected]

Word counts: 3412

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mailto:[email protected]


ABSTRACT

OBJECTIVE

To assess the current prevalence of diabetes and risk factors in mainland China, as well as the national trend in diabetes

prevalence.

DESIGN

Population-based cross-sectional study

SETTING

31 provinces in mainland China with nationally representative cross sectional data from 2015 to 2017

PARTICIPANTS

75,880 participants aged 18 years or older, as a nationally representative sample of mainland Chinese population

MAIN OUTCOME MEASURES

The participants were given a questionnaire and an anthropometric and clinical assessment. Serum concentrations of fasting

plasma glucose, 2-hour plasma glucose and HbA1c were measured.

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RESULTS

The weighted prevalence of total diabetes, self-reported diabetes, newly diagnosed diabetes and prediabetes was 12.75%

(95% CI, 11.97% to 13.56%), 6.01% (95% CI, 5.40% to 6.68%), 6.74% (95% CI, 6.14% to 7.40%) and 35.22% (95% CI,

33.51% to 36.97%), respectively, among the general Chinese population aged 18 years or older. The annual percentage

change in diabetes prevalence was 1.5% (95% CI, 0.2% to 3.0%, p<0.0001) from 2007 to 2017. Men had a higher

prevalence of diabetes (13.71% vs. 11.76%, p<0.0001) than did women. The prevalence of diabetes was shown to increase

sharply after 50 years of age which born around 1960’s. Diabetes prevalence ranged from 6.20% in Guizhou (95% CI,

2.89% to 12.83%) to 19.85% in Inner Mongolia (95% CI, 17.55% to 22.36%) in 31 provinces. Han ethnicity had the highest

prevalence of diabetes (12.82%, 95% CI, 12.03% to 13.66%), and Hui was the lowest (6.26%, 95% CI, 3.90% to 9.91%)

among five investigated ethnicities.

CONCLUSION

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The highest recorded prevalence of diabetes was reported, which indicated that the diabetic epidemic in mainland China is

still increasing in severity. The increase in prevalence was not mainly attributed to aging and obesity but might be related to

genetic susceptibility, prenatal nutrition, urbanization and regional variations.

KEY WORDS: Diabetes; Prediabetes; China; Prevalence; Risk factors

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WHAT IS ALREADY KNOW ON THIS TOPIC

The most recent national survey of diabetes in China was conducted in 2013 and revealed a diabetes prevalence of 10.9%

and a prediabetes prevalence of 35.7%. Along with rapid socioeconomic development in China, the diabetes epidemic in

China might be in a state of transition. In 2015, China implemented a significant health care reform, which is setting up a

hierarchical medical system to solve the problems of biased resource allocation and high patient flows to large hospitals.

Therefore, ongoing reliable estimations are needed to evaluate prevention and treatment programs for diabetes management.

WHAT THIS STUDY ADDS

Our nationally representative epidemiological survey provided data regarding the latest and reliable prevalence of diabetes

and prediabetes in mainland China using a strict quality assurance and control protocol. We estimated the prevalence by not

only using statistical methods to weigh the results but also recruiting individuals according to the age and sex composition

of each community and an urban-rural ratio, referring to the latest national census data that avoided oversampling of certain

subpopulations. In addition, similar study design and statistical methods make our findings more comparable to historical

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data. In the context of lacking a high-quality national cohort to estimate diabetes incidence, our findings might add value to

evaluating the diabetes epidemic in mainland China. In addition, we also provide the first-ever diabetic profile at provincial

and geographical region levels using the latest diabetes diagnostic criteria, and the results showed a disproportionate burden

between them.

The estimated prevalence of diabetes in China might be increasing to a higher level than ever before. The elevation in the

current prevalence appears to not only attributed to adiposity and aging. The gap in the diabetes profile seems to be

shrinking between urban and rural areas. The pool of prediabetes aged over 50 years or living in rural areas seems to be

translated into a substantial increase in the population attributable and preventable fraction of diabetes in the near future.

Ongoing consecutive surveillance and proven effective control measures are needed to reduce the burden of diabetes.

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Introduction

Diabetes is a metabolic disorder caused by genetic and environmental factors that results in insulin insensitivity, insulin

deficiency and impaired biological effects, and diabetes has become a critical health issue worldwide due to its high

prevalence and related disability and mortality.1,2 China is one of the countries with a high prevalence of diabetes.3-8 In

recent years, despite the successive introduction of national policies for the prevention and treatment of chronic

noncommunicable diseases (NCDs) and great efforts to strengthen the efforts to prevent and treat diabetes, the prevalence of

diabetes has continued to rise from 0.67% in 1980 to 10.90% in 2013.3,8 However, in the United States, nationally

representative data from 1980 to 2012 showed that the annual percentage change (APC) of diabetes prevalence was 4.5%

between 1990 and 2008 and 0.6% between 2008 and 2012, which indicated that a plateauing and decreasing prevalence

appeared in the diabetic epidemic in the United States.9 The reasons for the stubbornly high prevalence of diabetes in China

are of concern. Ongoing reliable estimations are needed to evaluate whether an inflection point appeared in diabetes

prevalence or new risk factors of diabetes peeped.

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Recently, we finished an epidemiological study, Thyroid disorders, Iodine status and Diabetes Epidemiological survey

(TIDE study), which included all 31 provinces of mainland China with a sample of 75,880 individuals. The study was

conducted from Jan 2015 to Dec 2017 and was a nationally representative cross-sectional study designed to evaluate the

current and reliable prevalence of diabetes and prediabetes in mainland China, as well as the awareness, treatment and

control of diabetes by geographical location and subpopulation.

Methods

Sampling and study population

The entire study was conducted through four stages of random sampling in urban and rural locations in parallel (Supplement

Figure 1). At the first stage, thirty-one cities were selected and divided into 10 developed, 13 developing and 8

underdeveloped cities, based on population size and economic levels. At the second stage, one district was randomly

selected from each city. At the third stage, two residential communities were randomly selected from the district. At the

final stage, eligible individuals who met the inclusion criteria were randomly selected and stratified by age and sex. The age

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and sex composition of each community and urban-rural ratio were decided based on China’s 2010 national census data.

Parallel random sampling was performed in rural locations. The inclusion criteria of the adult respondents were as follows:

was aged 18 years or older, lived in the selected community for at least 5 years, and were not pregnant. The research

protocols were approved by the Medical Ethics Committee of China Medical University. All subjects provided written

informed consent following a thorough explanation of the research procedures.

Demographic and behavioral assessment

For each individual, a trained interviewer administered a detailed questionnaire to collect information about demographic

parameters, behavioral factors, and personal and family medical history. Cigarette smoking was defined as having smoked

at least 100 cigarettes in one’s life. Occasional smokers were defined as having smoked fewer than 20 cigarettes per day.

Regular smokers were defined as smoking more than 20 cigarettes per day.

Anthropometric and clinical assessment

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We measured bodyweight, height, waist circumference, and blood pressure according to standard protocols, and body mass

index (BMI) was calculated by dividing bodyweight in kg by the square of height in meters. We diagnosed hypertension if

individuals had a systolic blood pressure of 140 mm Hg or higher, a diastolic blood pressure of 90 mm Hg or higher, or both.

We defined central obesity as a waist circumference of 90 cm or greater for men and 80 cm or greater for women, with or

without generalized obesity. We defined generalized overweight as a BMI of 25.0 to 29.9, and obesity was defined as a

BMI of 30.0 or higher for both men and women.10

Biochemical assessment

Blood samples were collected for all participants after an overnight fast of at least 10 hours. Serum samples and

measurements of fasting plasma glucose (FPG) levels and 2-hour plasma glucose (2hPG) levels after oral 75 g glucose

tolerant test (OGTT) were performed. HbA1c was measured from venous blood samples using a high-performance liquid

chromatography method (Bio-Rad VARIANT II Hemoglobin Analyzer). In individuals with self-reported diabetes, we

measured only fasting glucose and HbA1c. Fasting plasma glucose, 2-hour plasma glucose, serum total cholesterol,

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low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides were

measured using an automatic biochemical analyzer (Mindray BS-180 Analyzer).

Outcome assessment

Self-reported diabetes was defined as a self-reported diagnosis that was determined previously by a health care professional.

Newly diagnosed diabetes and prediabetes were defined according to the 2018 American Diabetes Association criteria

(Supplementary Table 1). Total diabetes was the sum of the number of patients who received a diagnosis of diabetes and the

number of patients with newly diagnosed diabetes. Individuals with isolated impaired fasting glucose (IFG) and isolated

impaired glucose tolerance (IGT) were defined according to the 1999 World Health Organization diagnostic criteria

(Supplementary Table 1). Awareness was defined as the proportion of individuals with 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 taking medication.

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Statistical analysis

All calculations were weighted to represent the overall Chinese adult population aged 18 years or older. Weighting

coefficients were derived from the 2010 Chinese population census data and the sampling scheme of the current survey to

obtain national estimates. Standard errors were calculated with appropriate statistical techniques with data from the complex

survey design. Categorical data are presented as percentages and 95% confidence intervals (95% CIs) and were analyzed

with the chi-square test and Fisher’s exact test, as appropriate. Continuous data are described with means and 95% CIs. A

multinomial logit regression was used to examine the association of risk factors with the odds of diabetes and prediabetes. A

P value less than 0.05 was considered statistically significant. All statistical analyses were conducted using the SAS system,

version 9.3 (SAS Institute Inc), SUDAAN software, version 10.0 (Research Triangle Institute) and Joinpoint Regression

software (National Cancer Institute), version 4.6.0.0.

Role of the funding source

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The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or the writing of

the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision

to submit for publication.

Results

With an overall response rate of 92.08%, 80,937 participants completed the study. Among the participants, 5,057 were

excluded due to missing information on sex, age, plasma glucose or HbA1c, and 75,880 participants remained eligible for

analysis (Supplementary Figure 1).

The general characteristics and associated factors of the study population are presented in Table 1 by sex, urbanization and

age group. The mean age at baseline was 42.80 years (95% CI, 41.94-43.67), the mean BMI was 24.00 (95% CI,

23.86-24.14), and 51.48% were women. The overall standardized prevalence of overweight and obesity was 30.87% (95%

CI, 29.76%-32.00%) and 6.26% (95% CI, 5.94%-6.59%), respectively, in the general population. The mean FPG level was

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5.42 mmol/L (95% CI, 5.35-5.48), the mean OGTT2hPG level was 6.50 mmol/L (95% CI, 6.40-6.59) and the mean HbA1c

level was 5.55% (95% CI, 5.44%-5.65%).

As shown in Table 2, the overall standardized prevalence of total diabetes, self-reported diabetes and newly diagnosed

diabetes was 12.75% (95% CI, 11.97%-13.56%), 6.01% (95% CI, 5.40%-6.68%) and 6.74% (95% CI, 6.14%-7.40%),

respectively, among the general Chinese population aged 18 years or older. Men had a higher prevalence of diabetes

(13.71% vs. 11.76%, p<0.0001) than did women. Furthermore, diabetes prevalence increased with age in both men and

women (p <0.0001 for trend) (Figure 1).

The annual percentage change (APC) for the prevalence of diabetes was 1.5% (95% CI, 0.1% to 3.0%, p<0.0001) among

Chinese adults from 2007 to 2017. Diabetes prevalence exhibited a significantly increasing trend for women (APC, 1.6%,

95% CI, 1.2% to 2.0%, p<0.0001); however, a destabilizing increase with no significant change was observed in men (APC,

1.5%, 95% CI, -1.1% to 4.2%, p=0.1) (Figure 2).

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The estimated prevalence of prediabetes was 35.22% (95% CI, 33.51%-36.97%) in Chinese adults, 37.03% (95% CI,

35.16%-38.93%) in men and 33.38% (95% CI, 31.56%-35.25%) in women (Table 2). Rural residents had a slightly higher

prevalence of prediabetes than urban residents (35.81% vs. 34.58%, p=0.29 for difference). Similar to the trend for diabetes,

an increasing trend between age groups and prediabetes prevalence among men and women is shown in Figure 1 (p <0.0001

for trend); however, the prevalence plateaued after an age older than 50 years. In addition, the prevalence of IFG was

10.95% (95% CI, 9.42%-12.71%), which was higher than that of IGT (7.15%, 95% CI, 6.19%-8.25%).

The overall proportion of patients who were aware of their diabetes condition was 43.25% (95% CI, 39.15%-47.45%)

(Table 2). The proportion of men who were aware of their diabetes condition was 42.03% (95% CI, 35.61%-48.73%), and

that of women was 44.50% (95% CI, 41.47%-47.57%); 48.95% (95% CI, 44.49%-53.44%) of all patients with diabetes

were taking antidiabetic medication. Among patients treated, 49.41% (95% CI, 39.43%-59.44%) had HbA1c levels

controlled to less than 7.0%.

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The proportion of patients who were aware of their diabetes and treated for it was higher in the older population (both

p<0.01 for trend), and the rate of awareness of diabetes was significantly higher in urban residents than in rural residents

(47.45% vs. 38.03%, p=0.02) (Table 2, Figure 1). The rate of patients who controlled their HbA1c levels well was higher in

younger patients (p=0.03 for trend) and in urban residents (p=0.003 for difference).

Regional variations in diabetes prevalence were found, with the highest prevalence in the northern region (14.23%, 95% CI,

12.45%-16.22%), followed by the southwestern (13.30%, 95% CI, 10.78%-16.31%), northeastern (12.94%, 95% CI,

10.51%-15.82%), southern (12.76%, 95% CI, 9.54%-16.87%), central (12.25%, 95% CI, 11.69%-12.82%), eastern (12.15%,

95% CI, 10.93%-13.48%), and northwestern regions (12.14%, 95% CI, 10.85%-13.56%) (Table 2). A significant difference

in prediabetes prevalence was found between regions (p=0.04 for difference). Supplementary Figure 2 illustrates the

geographical variation in the prevalence of diabetes and prediabetes at the provincial level, stratified into quintiles. The

prevalence of diabetes varied from 6.20% in Guizhou (95% CI, 2.89%-12.83%) to 19.85% in Inner Mongolia (95% CI,

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17.55%-22.36) (Supplementary Table 2). Additionally, prediabetes prevalence varied from 17.20% in Anhui (95% CI,

13.13%-22.20%) to 54.47% in Yunnan (95% CI, 46.12%-62.57%).

Regarding ethnic variations, Han ethnic participants had the highest prevalence of diabetes (12.82%, 95% CI,

12.03%-13.66%), followed by Uyghur (11.46%, 95% CI, 9.64%-13.57%), Zhuang (11.36%, 95% CI, 7.70%-16.45%),

Tibetan (6.48%, 95% CI, 6.08%-6.91%) and Hui participants (6.26%, 95% CI, 3.90%-9.91%) (Table 2). For prediabetes,

Hui (36.20%, 95% CI, 31.34%-41.36%), Zhuang (35.49%, 95% CI, 34.57%-36.42%), Han (35.43%, 95% CI,

33.63%-37.26%), and Tibetan individuals (34.43%, 95% CI, 26.29%-43.60%) had a similar prevalence that was

significantly higher than that of Uyghur individuals (20.19%, 95% CI, 12.63%-30.68%).

In the multivariable, multinomial, logit models, male sex, older age, Uyghur and Hui ethnicities, family history of diabetes,

less than high school education, income less than 30,000 Chinese Yuan per year, overweight and obesity, central obesity,

hypertension, hypercholesterolemia, hypertriglyceridemia, high LDL-C and low HDL-C were all significantly associated

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with diabetes (Table 3). In addition, male sex, older age, Uyghur ethnicity, living in the central China region, family history

of diabetes, overweight and obesity, central obesity, hypertension, hypercholesterolemia, hypertriglyceridemia, high LDL-C

and low HDL-C were all significantly associated with prediabetes.

Discussion

Prevalence of diabetes in China

The prevalence of diabetes continues to increase worldwide. As the NCD Risk Factor Collaboration（NCD risk）reported,

the age-standardized prevalence of adult diabetes was 10% in men and 8.8% in women.11 In addition, 85% to 95% of

diabetic adults had type 2 diabetes.12,13 Comparing 1980 to 2014, the global diabetes prevalence increased from 4.3% to

9.0% in men and from 5.0% to 7.9% in women. The reasons for the increase in prevalence were analyzed: 28.5% was

attributed to increased prevalence, 39.7% to population growth and aging and 31.8% to both.11 Two million people with

diabetes die each year from macrovascular and microvascular complications.14

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The diabetes prevalence trend in China is the same as the worldwide trend. Four national surveys have shown that the

prevalence gradually increased from 0.67% in 1980 to 2.5% in 1994, to 9.7% in 2007, and to 10.9% in 2013.3,4,6,8 In the

present study, a diabetes prevalence of 12.75% was reported, which is the highest level recorded in China and higher than

that reported by the United States (9.7% in the same period).15 The current study and the first three surveys were conducted

with similar study protocols, designs and statistical methods. 6-8 Therefore, an increasing prevalence of diabetes was noted

among Chinese adults in previous consecutive studies using the WHO criteria (Supplementary Table 3, Figure 2). The

prevalence of prediabetes was 35.22%, which was similar to the 35.7% reported in 2013.7,8 In this study, venous blood was

used to test for HbA1c, and this method was accepted by most laboratories. These findings suggested that the prevalence of

diabetes in China still maintained a trend of continuing growth without any plateau or inflection point.

Awareness, treatment and control of diabetes

Although an ongoing increase in self-reported diabetes was found, declines were noted in the prevalence of newly

diagnosed diabetes (Supplementary Table 3), suggesting better awareness of diabetes compared with that found in previous

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studies.6-8 This improved awareness and diagnosis is possibly attributed to the concerted effort by the government (through

programs such as China National Plan for Non-Communicable Disease Prevention and Treatment in 2012-2015) and the

Chinese Diabetes Society (launched Bluelight Action that aimed to prevent, provide care and cure diabetes through health

education).16 However, the control of diabetes is still similar to the results of a survey conducted in 2013, which indicates

that the health care system needs further strengthening and improvement.

The aged and malnourished

Diabetes prevalence was extremely high and the prevalence of prediabetes plateaued in individuals over 50 years old. These

data are all consistent with those of previous studies.7,8 Compared with previous data, the prevalence of diabetes in the

young population was relatively low and decreasing, which is inconsistent with the concept that diabetes has a

youth-oriented tendency in Asia.17 However, increases in diabetes prevalence have resulted from the increased prevalence in

the 40 years or older population, especially the population older than 50 years of age (Supplementary Table 4,

Supplementary Figure 3).6-8 The latest research revealed that prenatal exposure to famine markedly increases hyperglycemia

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risk in 2 consecutive generations of Chinese adults.18 Another famine study in Sub-Saharan Africa also indicated that fetal

and infant undernutrition were associated with increased risk of diabetes in middle aged population. 19 Gestational and

postnatal windows of famine exposure had variable effects on phenotype.20 DNA methylation differences were replicated at

previously identified metastable epialleles sensitive to periconceptual famine exposure.20 Given that the Chinese famine of

1959–1961 was among the most severe on record, the affected population showed a higher prevalence of diabetes and

prediabetes in those with a current age of 50 years or older.21 This reason might partially explain the phenomenon, which

supported the notion that prenatal nutrition plays an important role in the development of diabetes across consecutive

generations of Chinese adults.

Overweight and obesity

Obesity and overweight are significantly associated with the prevalence of diabetes, which might be one of the reasons for

the increased prevalence.22 However, compared with the results of the survey conducted in 2013, no increase in mean BMI

(24.00 Kg/m2 in 2013 vs. 24.00 Kg/m2 in 2017) or obesity rate [6.4% (95% CI, 6.0% to 6.7%) in 2013 vs. 6.26% (95% CI,

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5.94% to 6.59%) in 2017] was found in the current study considering the increasing diabetes prevalence.8 Additionally, the

prevalence of obesity among older age groups in this study was similar to that reported in 2013 (Supplementary Table 5).

Nevertheless, obesity is still an important risk factor for diabetes.

Genetic background and geography

It is generally accepted that genetic factors significantly influence the prevalence of diabetes. A recent study of

first-generation Asian-Americans confirmed that the prevalence of diabetes and prediabetes among Asian-Americans

increased from 6.8% in 2003 to 12.4% in 2013, while that among Caucasians increased from 5.5% to 6.9%.23 The present

study found that the prevalence of diabetes and prediabetes in the four ethic groups was significantly different from that in

the Han ethic group. Compared with the Han ethnic group, the Tibetan ethnic group had a significantly lower prevalence of

diabetes, which is consistent with the findings of a previous study.8 The difference might be attributed to dietary patterns,

altitude, economic development and genetic factors.24,25 However, a wide variation in diabetes and prediabetes prevalence

between the Hui and Uyghur ethnic groups was found in this study. The difference might be explained by factors such as

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genetic variation, although the two minority groups in northwestern China that were admixed were Muslim and shared

similar lifestyles.26,27

Among the 31 provinces in mainland China, there was large variation in province-specific diabetes and prediabetes

prevalence. The prevalence of diabetes in Inner Mongolia is three times higher than that in Guizhou Province. For

prediabetes, Yunnan Province had the highest prevalence, which was 3-times greater than the lowest prevalence in Anhui

Province. This difference is related to genetic factors, environmental factors, lifestyle and economic development levels.

Therefore, reasonable medical resource allocation should be a key priority for policymakers.

Urban-rural disparity

Urbanization variations were found in the prevalence of diabetes and prediabetes, awareness, treatment and control.

Although the prevalence of diabetes continues to be higher in urban areas than in rural areas without a significant difference,

the gap showed a decreasing trend compared with previous data.6-8 Compared with the national study conducted in 2013, the

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current diabetes prevalence in urban areas increased by 1%; however, the prevalence of diabetes increased by 2.5% in rural

areas. China has a large rural population base, and sanitation is lacking; thus, an increased prevalence of diabetes in rural

areas will lead to increased diabetic complications. Given the higher prediabetes prevalence and lower awareness, treatment

and control of diabetes in rural populations, there continues to be a very large pool of individuals at risk of developing

diabetes in rural areas without the implementation of effective preventative measures.

Strengths

The present study has several strengths. First, this nationally representative epidemiological survey provided data on the

latest and reliable prevalence of diabetes and prediabetes in mainland China by following a strict quality assurance and

control protocol. We estimated the prevalence not only by using statistical methods to weigh the results but also by

recruiting individuals according to age and sex composition of each community and the urban-rural ratio, referring to the

latest national census data, which prevented oversampling of certain subpopulations. Second, a similar study design and

statistical methods make our findings more comparable to historical data. In the context of lacking a high-quality national

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cohort to estimate diabetes incidence, our findings might add value in the context of evaluating diabetes epidemics in

mainland China. In addition, we also provide the first ever-diabetic profile at the provincial and geographical region levels

using the latest diabetes diagnostic criteria, which showed a disproportionate burden between the regions.

Limitations

However, our study also has some limitations. First, as a cross-sectional survey, this study was not able to unveil the

mechanisms involved in the observed phenomena. Second, we did not obtain information about individuals' physical

activity, dietary patterns or alcohol consumption, which reduced our ability to explore some risk factors for diabetes. Third,

using HbA1c levels of 6.4% to diagnose diabetes might be controversial since that figure was set for the United States

population. Although geographic disparities might exist in HbA1c levels, for comparison purposes, a consistent threshold

was preferred across the study. Last, we could not distinguish between type 1 and type 2 diabetes in this study; however,

type 2 diabetes was previously reported to be the predominant form of diabetes in the Chinese population.

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Conclusion

In conclusion, the estimated prevalence of diabetes and prediabetes was 12.75% and 35.22%, respectively, among the

Chinese population over 18 years old from 2015 to 2017. The diabetic epidemic in mainland China is still increasing. The

increase in current prevalence was not mainly attributed to aging and obesity but might be related to genetic susceptibility,

prenatal nutrition, urbanization and regional variations. Ongoing consecutive surveillance and effective control are needed

to reduce the burden of diabetes.

Contributors

ZYS, WPT, YZL, GJQ, YFQ, HBQ, BYS, HS, DT and XGS conceived and designed the study. ZYS and WPT supervised

the study. ZYS, WPT and YZL did the statistical analysis. All authors contributed to acquisition, analysis, or interpretation

of data. ZYS, WPT and YZL drafted the manuscript. All authors revised the report and approved the final version before

submission.

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Declaration of interests

All authors declare no competing interests.

Acknowledgments

We thank the participants of this study. For continuous support, assistance, and cooperation, we thank Jiang He and

Chung-Shiuan Chen (Tulane University); Wei Gong, Chenling Fan, Hong Wang, Hongmei Zhang, Shuangning Ding,

Xiaochen Xie and Tingting Liu (The First Hospital of China Medical University); Caiping Li and Jian Huangfu (The

Affiliated Hospital of Inner Mongolia University); Nan Jin(Chinese PLA General Hospital); Wuquan Deng, Fang Deng

(Third Military Medical University); Haicheng Zhou (The First Affiliated Hospital of Dalian Medical University); Qingling

Lu (Cardiovascular and Cerebrovascular Disease Hospital of Ningxia Medical University); Yunfeng Shen (The Second

Affiliated Hospital of Nanchang University); Guodong Liu (The First Affiliated Hospital of Harbin Medical University);

Junxiu Hou and Zhiqiang Zhang (The Affiliated Hospital of Inner Mongolia Medical University); Hong Zhang (The Second

Xiangya Hospital); Xiaodong Mao, Qifeng Wang and Kun Wang (Nanjing University of Chinese Medicine); Yanping

Wang (Fujian Medical University Union Hospital); Xiaojun Ma (The First Affiliated Hospital of Zhengzhou University);

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Liheng Meng (First Affiliated Hospital of Guangxi Medical University); Weihua Linle and Tuanyu Fang (Hainan General

Hospital); Xingjun Liu and Yanru Zhao (The First Affiliated Hospital of Xi'an Jiaotong University); Lulu Chen, Jiaoyue

Zhang and Hanyu Wang (Huazhong University of Science and Technology); Jingfang Liu and Songbo Fu (The First

Hospital of Lanzhou University); Qingguo Lv (West China Hospital); Chenglin Sun (The First Hospital of Jilin University);

Qiuming Yao and Ronghua Song (Shanghai University of Medicine & Health Science Affiliated Zhoupu Hosipital);

Tingting Chen (The First Hospital of An Hui Medical University); Ben Niu (The First People's Hospital of Yunnan

Province); Mingtong Xu and Feng Li (Sun Yat-sen Memorial Hospital); Lizhen Lan (The First Hospital of Shanxi Medical

University); Jun Yue and Jia Song (People's Hospital of Tibet Autonomous Region); Yanan Li and Wei Luo (Qinghai

Provincial People's Hospital); Xiaoming Lou and Zhe Mo (Zhejiang Provincial Center for Disease Control and Prevention);

Nianchun Peng and Lixin Shi (Affiliated Hospital of Guiyang Medical University); Mian Wang, Qiuxiao Zhu and Lingling

Yuan (Second hospital of Hebei Medical University); Haiqing Zhang (Shandong Provincial Hospital affiliated with

Shandong University); Yong Fan (The First Affiliated Hospital of Xinjiang Medical University); Hongyan Wei(Tianjin

Medical University General Hospital).

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Financial Support: This work is supported by the Clinical Research Fund of Chinese Medical Association (Grant No.

15010010589).

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Figure Legends

Figure 1. Prevalence, awareness, treatment, and control of diabetes among study participants.

Figure 2. Trends in diabetes prevalence according to the WHO criteria among Chinese men and women from 2007

to 2017.

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Table 1. General characteristics of the Chinese adult populationSex Urbanization

Overall Men Women Urban Rural(N=75880) (n=36819) (n=39061) (n=40560) (n=35320)

Age at survey, mean (95% CI), y 42.80 (41.94-43.67) 42.63 (41.77-43.49) 42.98 (42.10-43.86) 41.43 (40.49-42.37) 44.29 (43.53-45.06)Ethnicity,% (95% CI) Han 95.43 (93.52-96.80) 95.29 (93.42-96.65) 95.57 (93.61-96.95) 96.71 (86.89-99.24) 94.03 (78.67-98.54) Tibetan 0.18 (0.06-0.52) 0.18 (0.06-0.54) 0.18 (0.06-0.51) 0.08 (0.01-0.67) 0.29 (0.04-2.26) Uyghur 1.33 (1.10-1.60) 1.40 (1.12-1.74) 1.26 (1.08-1.47) 1.17 (0.15-8.71) 1.50 (0.19-10.88) Hui 0.25 (0.05-1.32) 0.25 (0.04-1.39) 0.25 (0.05-1.26) 0.04 (0.01-0.34) 0.47 (0.06-3.68) Zhuang 2.81 (1.64-4.78) 2.88 (1.72-4.77) 2.74 (1.55-4.80) 1.99 (0.25-13.92) 3.71 (0.47-23.71)Income per year,% (95% CI) ≤ 3000 Chinese Yuan 44.84 (38.19-51.68) 41.32 (35.08-47.85) 48.40 (41.27-55.60) 30.95 (26.41-35.89) 59.74 (53.91-65.31) > 3000 Chinese Yuan 55.16 (48.32-61.81) 58.68 (52.15-64.92) 51.60 (44.40-58.73) 69.05 (64.11-73.59) 40.26 (34.69-46.09)Education,% (95% CI) Less than high school 43.71 (36.47-51.24) 40.41 (33.61-47.61) 47.06 (39.30-54.95) 28.19 (23.20-33.79) 60.51 (56.18-64.67) High school and above 56.29 (48.76-63.53) 59.59 (52.39-66.39) 52.94 (45.05-60.70) 71.81 (66.21-76.80) 39.49 (35.33-43.82)Cigarette smoking,% (95% CI) Never smoker 73.58 (72.29-74.82) 49.96 (47.46-52.46) 97.51 (96.83-98.05) 75.45 (73.66-77.16) 71.54 (69.34-73.64) Occasional smoker 3.96 (3.56-4.40) 6.96 (6.32-7.66) 0.92 (0.72-1.16) 4.29 (3.58-5.14) 3.59 (3.02-4.27) Regular smoker 22.47 (21.16-23.83) 43.08 (40.44-45.76) 1.57 (1.14-2.16) 20.26 (18.46-22.18) 24.87 (22.52-27.38)Family history of diabetes,% (95% CI) 16.42 (13.89-19.31) 15.49 (13.17-18.13) 17.37 (14.58-20.55) 21.95 (19.10-25.09) 10.40 (8.75-12.32)Physical examination Body mass index, mean (95% CI),kg/m2 24.00 (23.86-24.14) 24.59 (24.42-24.76) 23.40 (23.22-23.58) 23.91 (23.57-24.25) 24.09 (23.79-24.39) Body mass index,% (95% CI)

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<25 62.87 (61.50-64.23) 56.10 (54.18-58.01) 69.73 (67.81-71.59) 63.85 (60.20-67.34) 61.82 (58.48-65.04) 25-<30 30.87 (29.76-32.00) 36.32 (34.79-37.88) 25.34 (23.74-27.01) 30.01 (27.55-32.60) 31.80 (29.46-34.23) ≥30 6.26 (5.94-6.59) 7.57 (7.03-8.16) 4.92 (4.60-5.27) 6.14 (5.05-7.44) 6.39 (5.42-7.51) Waist circumference, mean (95%CI), cm 83.20 (82.41-83.98) 86.62 (85.80-87.45) 79.72 (78.81-80.63) 82.70 (81.62-83.78) 83.74 (82.14-85.33) Heart rate, mean (95% CI), CPM 79.83 (79.17-80.49) 78.89 (78.18-79.59) 80.79 (80.05-81.53) 80.01 (78.66-81.35) 79.64 (78.45-80.82) Systolic blood pressure, mean (95%CI), mmHg

126.30 (124.93-127.68)

129.89 (128.79-130.99)

122.67 (120.89-124.44)

124.12 (122.75-125.49)

128.68 (126.85-130.51)

Diastolic blood pressure, mean (95%CI), mmHg

78.33 (77.16-79.50) 80.67 (79.29-82.05) 75.97 (74.91-77.03) 77.30 (76.00-78.61) 79.46 (77.41-81.50)

Laboratory tests, mean (95% CI) Cholesterol, mmol/L 4.77 (4.73-4.82) 4.80 (4.75-4.85) 4.75 (4.70-4.80) 4.80 (4.70-4.90) 4.74 (4.63-4.86) Low-density lipoprotein, mmol/L 2.83 (2.77-2.89) 2.90 (2.83-2.96) 2.76 (2.70-2.81) 2.83 (2.74-2.92) 2.82 (2.68-2.97) High-density lipoprotein, mmol/L 1.47 (1.45-1.48) 1.37 (1.35-1.39) 1.56 (1.54-1.59) 1.46 (1.40-1.52) 1.47 (1.40-1.54) Triglycerides, mmol/L 1.57 (1.52-1.62) 1.78 (1.73-1.83) 1.35 (1.29-1.42) 1.52 (1.47-1.57) 1.62 (1.53-1.71) Fasting plasma glucose, mmol/L 5.42 (5.35-5.48) 5.50 (5.43-5.57) 5.33 (5.27-5.39) 5.39 (5.28-5.49) 5.45 (5.32-5.58) 2-hour plasma glucose, mmol/L 6.50 (6.40-6.59) 6.50 (6.40-6.60) 6.49 (6.40-6.59) 6.51 (6.35-6.67) 6.49 (6.29-6.68) Hemoglobin A1c,% 5.55 (5.44-5.65) 5.59 (5.49-5.69) 5.50 (5.40-5.60) 5.49 (5.30-5.67) 5.61 (5.55-5.67)

(Continued)Age group, in years18-29 30-39 40-49 50-59 60-69 ≥70(n=17873) (n=15082) (n=16686) (n=12736) (n=8205) (n=5298)

Age at survey, mean (95% CI),y23.52 (23.43-23.61)

34.80 (34.73-34.87) 44.35 (44.29-44.40) 54.59 (54.53-54.64) 63.90 (63.85-63.94) 74.51 (74.21-74.81)

Ethnicity,% (95% CI) Han 95.14 94.89 (93.49-96.01) 95.45 (93.72-96.73) 96.12 (93.72-97.63) 95.95 (92.17-97.94) 95.73 (91.40-97.93)

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(93.67-96.27) Tibetan 0.26 (0.08-0.84) 0.20 (0.09-0.46) 0.16 (0.06-0.38) 0.12 (0.04-0.38) 0.13 (0.03-0.55) 0.10 (0.02-0.45) Uyghur 1.32 (1.14-1.54) 1.70 (1.50-1.93) 1.48 (1.30-1.69) 1.02 (0.64-1.62) 1.05 (0.61-1.80) 0.86 (0.53-1.40) Hui 0.26 (0.04-1.58) 0.27 (0.05-1.57) 0.25 (0.05-1.27) 0.23 (0.05-1.03) 0.24 (0.05-1.09) 0.19 (0.04-0.95) Zhuang 3.01 (2.13-4.24) 2.93 (2.06-4.16) 2.66 (1.57-4.47) 2.50 (1.22-5.09) 2.64 (0.96-7.03) 3.12 (1.17-8.04)Income per year,% (95% CI)

≤ 3000 Chinese Yuan40.31 (35.77-45.02)

31.20 (26.28-36.58) 41.98 (34.95-49.34) 52.71 (43.85-61.41) 62.93 (52.45-72.31) 66.93 (57.21-75.38)

> 3000 Chinese Yuan59.69 (54.98-64.23)

68.80 (63.42-73.72) 58.02 (50.66-65.05) 47.29 (38.59-56.15) 37.07 (27.69-47.55) 33.07 (24.62-42.79)

Education,% (95% CI)

Less than high school14.80 (11.11-19.44)

32.15 (25.07-40.15) 52.20 (43.15-61.10) 57.04 (49.60-64.18) 77.45 (70.64-83.05) 78.24 (69.89-84.78)

High school and above85.20 (80.56-88.89)

67.85 (59.85-74.93) 47.80 (38.90-56.85) 42.96 (35.82-50.40) 22.55 (16.95-29.36) 21.76 (15.22-30.11)

Cigarette smoking,% (95% CI)

Never smoker78.15 (75.93-80.21)

73.25 (71.77-74.68) 71.14 (69.78-72.47) 68.86 (67.83-69.87) 71.79 (69.78-73.71) 78.38 (75.89-80.67)

Occasional smoker 4.94 (4.14-5.88) 4.42 (3.93-4.96) 3.53 (3.01-4.14) 3.61 (3.24-4.02) 2.63 (2.27-3.03) 3.06 (2.37-3.94)

Regular smoker16.92 (14.73-19.36)

22.33 (20.95-23.77) 25.32 (24.11-26.57) 27.53 (26.53-28.56) 25.59 (23.87-27.39) 18.56 (16.50-20.82)

Family history of diabetes,% (95% CI)

17.92 (15.44-20.70)

19.28 (17.22-21.51) 17.60 (14.82-20.77) 15.27 (12.08-19.12) 11.05 (8.45-14.32) 9.18 (6.99-11.96)

Physical examination Body mass index, mean (95% CI),kg/m2

22.27 (22.03-22.52)

24.14 (24.00-24.28) 24.75 (24.62-24.87) 25.00 (24.84-25.15) 24.77 (24.60-24.94) 24.17 (23.87-24.46)

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Body mass index,% (95% CI)

<2579.18 (76.76-81.40)

62.25 (60.84-63.65) 55.94 (54.30-57.57) 52.57 (50.44-54.68) 55.28 (53.14-57.41) 61.01 (57.81-64.11)

25-<3016.60 (14.75-18.64)

30.20 (29.17-31.25) 36.99 (35.68-38.33) 39.97 (38.28-41.68) 38.68 (36.54-40.87) 34.00 (31.59-36.50)

≥30 4.22 (3.55-5.01) 7.54 (6.86-8.29) 7.06 (6.46-7.72) 7.47 (6.76-8.24) 6.04 (5.38-6.77) 4.99 (4.02-6.18) Waist circumference, mean (95%CI), cm

77.66 (76.48-78.83)

82.83 (82.35-83.32) 84.67 (83.91-85.44) 86.88 (86.02-87.74) 86.80 (85.99-87.61) 86.36 (85.50-87.21)

Heart rate, mean (95% CI),CPM81.86 (80.75-82.96)

80.19 (79.43-80.95) 79.14 (78.46-79.82) 78.21 (77.49-78.92) 78.23 (77.58-78.87) 79.44 (78.66-80.22)

Systolic blood pressure, mean (95%CI), mmHg

117.97 (117.22-118.72)

120.57 (119.72-121.41)

126.13 (124.93-127.32)

132.54 (130.88-134.21)

138.41 (136.52-140.30)

142.60 (140.71-144.49)

Diastolic blood pressure, mean (95%CI), mmHg

73.96 (72.40-75.52)

77.26 (75.80-78.72) 80.26 (79.41-81.12) 81.73 (80.82-82.65) 81.35 (80.17-82.53) 79.48 (77.71-81.25)

Laboratory tests, mean (95% CI) Cholesterol, mmol/L 4.29 (4.19-4.38) 4.67 (4.59-4.74) 4.91 (4.86-4.96) 5.15 (5.09-5.20) 5.12 (5.05-5.19) 5.10 (5.02-5.18) Low-density lipoprotein, mmol/L 2.47 (2.39-2.54) 2.78 (2.72-2.85) 2.92 (2.85-2.98) 3.10 (3.03-3.16) 3.08 (3.00-3.17) 3.03 (2.94-3.11) High-density lipoprotein, mmol/L 1.48 (1.46-1.51) 1.44 (1.42-1.46) 1.45 (1.43-1.47) 1.46 (1.44-1.48) 1.49 (1.46-1.52) 1.52 (1.50-1.55) Triglycerides, mmol/L 1.21 (1.14-1.28) 1.58 (1.53-1.63) 1.78 (1.71-1.84) 1.78 (1.72-1.83) 1.67 (1.61-1.74) 1.57 (1.50-1.64) Fasting plasma glucose, mmol/L 4.91 (4.86-4.97) 5.18 (5.13-5.23) 5.49 (5.42-5.55) 5.85 (5.75-5.94) 5.98 (5.88-6.09) 5.95 (5.85-6.05) 2-hour plasma glucose, mmol/L 5.42 (5.30-5.54) 6.06 (5.94-6.19) 6.66 (6.54-6.78) 7.29 (7.16-7.43) 7.74 (7.54-7.94) 8.14 (7.95-8.34) Hemoglobin A1c,% 5.20 (5.09-5.31) 5.35 (5.22-5.47) 5.56 (5.48-5.65) 5.83 (5.68-5.98) 6.01 (5.92-6.10) 6.02 (5.93-6.10)

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Table 2. Age- and sex-standardized prevalence of diabetes, prediabetes, awareness, treatment, and control of

diabetes and risk factors in the Chinese adult population

% (95% CI)

No. of

participantsTotal diabetes

Self-reported

diabetes

Newly diagnosed

diabetes

Diabetes based on

information of diagnosed

diabetes, FPG, and PG

IFG IGT

Overall 75880 12.75 (11.97-13.56) 6.01 (5.40-6.68) 6.74 (6.14-7.40) 11.20 (10.50-11.94) 2.38 (1.97-2.87) 11.53 (10.47-12.67)

Sex

Men 36819 13.71 (12.78-14.70) 6.37 (5.60-7.23) 7.35 (6.62-8.14) 12.13 (11.32-12.98) 2.98 (2.46-3.60) 11.16 (10.07-12.35)

Women 39061 11.76 (10.92-12.65) 5.64 (5.10-6.23) 6.12 (5.52-6.78) 10.25 (9.50-11.06) 1.77 (1.44-2.17) 11.90 (10.71-13.20)

p for difference <0.0001 0.01 0.0001 <0.0001 <0.0001 0.14

Urbanization

Urban 40560 13.68 (12.68-14.73) 7.11 (6.55-7.72) 6.57 (5.80-7.42) 12.24 (11.42-13.12) 2.05 (1.58-2.67) 12.18 (10.48-14.11)

Rural 35320 11.97 (10.72-13.34) 5.04 (4.29-5.92) 6.93 (5.93-8.07) 10.30 (9.18-11.55) 2.69 (1.93-3.72) 10.84 (9.38-12.49)

p for difference 0.92 0.08 0.13 0.76 0.18 0.8

Age group

18-29 17873 1.99 (1.49-2.67) 0.77 (0.48-1.22) 1.23 (0.95-1.59) 1.48 (1.02-2.13) 0.85 (0.63-1.14) 4.10 (3.17-5.28)

30-39 15082 6.31 (5.42-7.33) 2.58 (2.08-3.20) 3.72 (3.21-4.32) 5.37 (4.60-6.27) 1.74 (1.46-2.08) 8.67 (7.38-10.16)

40-49 16686 12.14 (11.10-13.26) 4.80 (4.06-5.66) 7.34 (6.48-8.31) 10.56 (9.62-11.57) 2.88 (2.33-3.56) 13.24 (11.77-14.86)

50-59 12736 21.14 (19.79-22.55) 10.58 (9.58-11.66) 10.56 (9.49-11.73) 18.94 (17.81-20.11) 3.88 (3.21-4.69) 15.91 (14.60-17.31)

60-69 8205 28.84 (26.52-31.28) 14.92 (12.81-17.30) 13.92 (11.99-16.11) 25.53 (23.29-27.91) 3.78 (2.81-5.07) 19.12 (17.40-20.96)

≥70 5298 31.84 (28.77-35.08) 16.46 (13.79-19.54) 15.38 (13.99-16.87) 28.77 (25.66-32.08) 3.11 (2.31-4.17) 21.45 (20.00-22.97)

p for trend <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0006

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Ethnicity

Han 68064 12.82 (12.03-13.66) 6.10 (5.49-6.78) 6.72 (6.09-7.41) 11.28 (10.57-12.04) 2.39 (1.97-2.90) 11.44 (10.35-12.62)

Tibetan 2034 6.48 (6.08-6.91) 1.45 (0.62-3.34) 5.03 (3.62-6.94) 4.20 (3.83-4.59) 0.58 (0.44-0.76) 8.46 (5.72-12.34)

Uyghur 2159 11.46 (9.64-13.57) 4.56 (4.15-5.00) 6.90 (5.51-8.61) 9.05 (7.41-11.01) 1.30 (0.68-2.50) 6.99 (5.82-8.36)

Hui 1661 6.26 (3.90-9.91) 1.82 (0.45-7.03) 4.44 (4.04-4.87) 5.41 (3.59-8.07) 3.07 (2.63-3.58) 5.92 (4.73-7.40)

Zhuang 1962 11.36 (7.70-16.45) 3.77 (1.52-9.08) 7.59 (6.71-8.57) 9.95 (6.60-14.73) 2.45 (1.68-3.55) 17.40 (14.05-21.37)

p for difference <0.0001 <0.0001 <0.0001 <0.0001 0.15 <0.0001

Region

South 6882 12.76 (9.54-16.87) 5.76 (3.03-10.70) 6.99 (6.92-7.07) 11.61 (8.23-16.13) 1.54 (0.79-2.99) 16.09 (11.78-21.58)

North 12112 14.23 (12.45-16.22) 6.64 (5.21-8.44) 7.58 (7.22-7.97) 11.40 (9.67-13.38) 2.68 (2.35-3.06) 9.92 (8.09-12.12)

East 17206 12.15 (10.93-13.48) 5.86 (5.10-6.72) 6.29 (5.17-7.63) 10.66 (9.92-11.45) 2.25 (1.54-3.29) 11.12 (9.58-12.88)

Central 7823 12.25 (11.69-12.82) 6.63 (5.53-7.92) 5.62 (4.41-7.13) 10.47 (9.77-11.21) 1.39 (0.91-2.12) 8.98 (7.95-10.12)

Southwest 11347 13.30 (10.78-16.31) 4.74 (3.68-6.07) 8.57 (6.22-11.68) 11.92 (9.95-14.22) 4.01 (2.52-6.30) 12.81 (10.87-15.04)

Northwest 13147 12.14 (10.85-13.56) 5.71 (4.35-7.44) 6.44 (5.71-7.26) 10.73 (9.56-12.01) 1.75 (0.87-3.51) 11.37 (10.00-12.91)

Northeast 7363 12.94 (10.51-15.82) 6.78 (4.76-9.57) 6.16 (5.32-7.11) 12.65 (10.19-15.61) 3.21 (2.50-4.11) 12.14 (10.16-14.45)

p for difference 0.1 0.25 0.01 0.33 0.009 0.02

Income per year

≤ 30000 Chinese Yuan 32339 12.92 (11.94-13.97) 5.90 (5.23-6.64) 7.02 (6.30-7.82) 11.29 (10.35-12.30) 2.59 (2.04-3.27) 11.63 (10.28-13.13)

＞30000 Chinese Yuan 42552 12.86 (12.00-13.77) 6.33 (5.72-6.99) 6.53 (5.87-7.25) 11.40 (10.71-12.14) 2.19 (1.80-2.67) 11.57 (10.63-12.57)

p for difference 0.0001 0.0004 0.0004 <0.0001 0.03 0.002

Education

Less than high school 34856 12.89 (11.78-14.09) 5.81 (5.05-6.68) 7.08 (6.34-7.90) 11.34 (10.30-12.47) 2.84 (2.23-3.61) 11.28 (10.30-12.33)

High school and above 40729 13.22 (12.50-13.97) 6.64 (6.06-7.28) 6.57 (5.92-7.30) 11.51 (10.82-12.23) 2.01 (1.61-2.51) 11.78 (10.58-13.09)

p for difference <0.0001 <0.0001 <0.0001 <0.0001 0.0001 <0.0001

Cigarette smoking

Never smoker 55958 12.87 (12.08-13.70) 6.16 (5.53-6.87) 6.70 (6.10-7.37) 11.35 (10.66-12.07) 2.31 (1.90-2.79) 11.65 (10.53-12.87)

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Occasional smoker 2626 13.46 (12.15-14.90) 6.21 (4.60-8.33) 7.25 (6.05-8.68) 12.04 (10.87-13.31) 2.20 (1.63-2.97) 9.80 (8.17-11.72)

Regular smoker 17246 13.57 (11.92-15.40) 6.69 (5.65-7.92) 6.88 (5.75-8.21) 11.89 (10.36-13.62) 2.44 (1.91-3.11) 9.94 (8.61-11.46)

p for trend 0.33 0.38 0.77 0.42 0.6 0.007

Family history of diabetes

Yes 12348 23.32 (21.75-24.96) 15.25 (14.08-16.50) 8.06 (7.09-9.16) 21.63 (20.15-23.19) 2.09 (1.71-2.54) 11.75 (10.56-13.04)

No 63503 10.98 (10.33-11.67) 4.53 (4.08-5.03) 6.45 (5.87-7.08) 9.48 (8.94-10.05) 2.41 (1.98-2.92) 11.41 (10.33-12.60)

p for difference <0.0001 <0.0001 0.04 <0.0001 0.03 0.45

Body mass index

<25 47749 9.99 (9.19-10.85) 4.96 (4.35-5.66) 5.03 (4.45-5.67) 8.77 (8.04-9.55) 2.10 (1.70-2.58) 9.76 (8.63-11.01)

25-<30 23178 15.64 (14.71-16.61) 7.38 (6.68-8.16) 8.25 (7.53-9.04) 13.83 (13.00-14.70) 2.84 (2.30-3.50) 13.94 (12.73-15.26)

≥30 4786 22.99 (21.79-24.23) 9.80 (8.78-10.92) 13.19 (12.03-14.43) 20.14 (18.85-21.49) 2.90 (2.34-3.59) 17.44 (15.25-19.87)

p for trend 0.03 <0.0001 0.02 <0.0001 0.002 <0.0001

Waist circumference

Men≥90 cm women≥80 cm 41736 16.15 (15.20-17.14) 7.44 (6.65-8.31) 8.71 (8.02-9.46) 14.22 (13.35-15.15) 2.68 (2.19-3.27) 14.00 (12.64-15.49)

Men<90 cm women<80 cm 33827 9.25 (8.30-10.29) 4.43 (3.83-5.12) 4.82 (4.18-5.54) 8.00 (7.17-8.92) 2.16 (1.74-2.68) 9.64 (8.47-10.95)

p for difference <0.0001 <0.0001 <0.0001 <0.0001 0.0003 <0.0001

(Continued)% (95% CI)

No. of participants

IFG+IGT PrediabetesAwareness of diabetes

Treatment of diabetes

Control of diabetes

Overall 75880 1.54 (1.31-1.80) 35.22 (33.51-36.97) 43.25 (39.15-47.45) 48.95 (44.49-53.44) 49.41 (39.43-59.44)Sex Men 36819 1.68 (1.43-1.98) 37.03 (35.16-38.93) 42.03 (35.61-48.73) 52.55 (47.50-57.54) 47.99 (37.13-59.05) Women 39061 1.39 (1.14-1.68) 33.38 (31.56-35.25) 44.50 (41.47-47.57) 45.29 (38.82-51.92) 50.86 (38.79-62.83) p for difference 0.02 <0.0001 0.25 0.1 0.36

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Urbanization Urban 40560 1.59 (1.26-2.00) 34.58 (31.62-37.66) 47.45 (42.92-52.02) 51.55 (46.92-56.15) 53.93 (41.89-65.53) Rural 35320 1.50 (1.12-2.01) 35.81 (32.18-39.62) 38.03 (33.09-43.24) 45.53 (38.56-52.68) 47.37 (42.55-52.23) p for difference 0.76 0.29 0.02 0.9 0.003Age group 18-29 17873 0.20 (0.13-0.30) 20.20 (18.16-22.40) 38.40 (28.73-49.08) 30.97 (20.48-43.86) 67.74 (32.30-90.23) 30-39 15082 0.85 (0.65-1.11) 29.87 (27.41-32.45) 41.64 (36.98-46.46) 38.06 (31.85-44.68) 52.20 (42.54-61.69) 40-49 16686 1.58 (1.35-1.85) 39.97 (38.03-41.93) 39.17 (34.18-44.41) 55.92 (49.05-62.56) 37.87 (31.23-45.00) 50-59 12736 3.02 (2.51-3.64) 47.14 (44.87-49.43) 50.05 (46.28-53.81) 65.48 (62.37-68.47) 39.24 (34.16-44.58) 60-69 8205 3.30 (2.66-4.07) 47.81 (45.02-50.61) 51.75 (45.52-57.93) 66.28 (60.56-71.56) 39.70 (36.12-43.40) ≥70 5298 2.62 (2.02-3.39) 47.62 (44.25-51.02) 51.77 (46.80-56.71) 64.85 (57.29-71.74) 45.50 (40.34-50.75) p for trend <0.0001 <0.0001 0.0004 0.0028 0.03Ethnicity Han 68064 1.54 (1.31-1.82) 35.43 (33.63-37.26) 43.95 (39.79-48.19) 49.11 (44.62-53.62) 49.50 (39.48-59.57) Tibetan 2034 0.26 (0.16-0.41) 34.43 (26.29-43.60) 28.30 (14.86-47.15) 43.41 (29.36-58.60) 24.32 (24.32-24.32) Uyghur 2159 1.13 (0.74-1.74) 20.19 (12.63-30.68) 34.19 (28.75-40.08) 32.50 (10.28-66.93) 36.91 (32.24-41.83) Hui 1661 2.03 (1.78-2.32) 36.20 (31.34-41.36) 36.67 (23.68-51.94) 66.67 (53.03-78.00) 43.91 (40.91-46.96) Zhuang 1962 1.52 (1.09-2.11) 35.49 (34.57-36.42) 27.05 (8.51-59.64) 60.60 (40.59-77.59) 40.76 (36.41-45.27) p for difference 0.003 0.005 0.047 0.86 0.12Region South 6882 1.20 (0.59-2.42) 35.07 (32.72-37.05) 45.40 (31.77-59.75) 46.93 (39.30-54.70) 67.03 (51.44-79.60) North 12112 1.36 (0.93-2.00) 37.37 (32.95-42.01) 39.04 (33.87-44.47) 50.71 (37.62-63.70) 51.28 (44.68-57.84) East 17206 1.63 (1.32-2.03) 33.70 (30.11-37.49) 41.77 (36.80-46.92) 39.79 (33.43-46.52) 42.96 (32.25-54.38) Central 7823 0.86 (0.45-1.63) 38.01 (35.37-40.72) 48.61 (42.17-55.09) 48.99 (40.31-57.74) 41.30 (40.66-41.94) Southwest 11347 2.34 (1.73-3.17) 37.74 (31.81-44.06) 33.21 (26.11-41.15) 46.84 (37.66-56.24) 53.32 (43.11-63.25) Northwest 13147 1.21 (0.84-1.73) 31.71 (28.32-35.31) 43.76 (35.60-52.28) 58.02 (50.41-65.27) 40.98 (31.69-50.97)

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Northeast 7363 2.07 (1.46-2.93) 31.26 (24.67-38.71) 47.90 (40.33-55.57) 61.35 (49.16-72.27) 40.79 (30.93-51.45) p for difference 0.01 0.04 0.42 0.29 0.02Income per year ≤ 30000 Chinese Yuan 32339 1.52 (1.24-1.86) 35.69 (33.75-37.67) 43.06 (38.40-47.85) 50.65 (42.21-59.06) 51.69 (47.58-55.77) ＞30000 Chinese Yuan 42552 1.57 (1.31-1.87) 34.97 (32.92-37.07) 43.06 (38.39-47.86) 49.63 (42.88-56.39) 45.50 (37.34-53.92) p for difference 0.0048 0.01 0.59 0.69 0.12Education Less than high school 34856 1.73 (1.43-2.08) 36.91 (34.17-39.74) 44.29 (39.40-49.29) 46.55 (41.96-51.20) 44.74 (37.02-52.72) High school and above 40729 1.41 (1.18-1.67) 34.58 (32.72-36.49) 43.91 (39.34-48.58) 50.90 (45.76-56.03) 54.63 (44.05-64.81) p for difference <0.0001 <0.0001 0.34 0.02 0.045Cigarette smoking Never smoker 55958 1.50 (1.28-1.77) 35.02 (33.18-36.90) 44.38 (39.59-49.29) 51.02 (45.36-56.65) 50.94 (39.80-61.99) Occasional smoker 2626 1.59 (0.72-3.46) 35.19 (31.53-39.03) 38.45 (30.84-46.67) 44.76 (37.68-52.07) 29.54 (20.49-40.54) Regular smoker 17246 1.69 (1.22-2.34) 34.19 (31.37-37.13) 44.50 (34.89-54.54) 40.35 (35.63-45.25) 42.94 (32.23-54.36) p for trend 0.46 0.5 0.98 0.0002 0.01Family history of diabetes Yes 12348 1.94 (1.62-2.32) 33.15 (30.94-35.44) 59.34 (55.76-62.83) 56.37 (47.90-64.48) 49.21 (38.09-60.41) No 63503 1.45 (1.22-1.72) 35.39 (33.63-37.19) 36.66 (32.57-40.96) 43.58 (38.66-48.63) 46.76 (39.58-54.07) p for difference 0.0047 0.009 <0.0001 0.23 0.9Body mass index <25 47749 1.14 (0.91-1.42) 33.03 (31.14-34.98) 43.08 (38.03-48.27) 51.57 (42.57-60.48) 57.44 (51.83-62.87) 25-<30 23178 2.03 (1.74-2.36) 38.94 (36.56-41.38) 45.84 (39.49-52.33) 46.93 (40.16-53.80) 39.67 (30.60-49.52) ≥30 4786 3.12 (2.46-3.96) 43.12 (40.27-46.01) 41.17 (36.82-45.67) 51.01 (43.88-58.10) 49.21 (39.65-58.82) p for trend <0.0001 <0.0001 0.4 0.93 0.004Waist circumference Men≥90 cm women≥80 cm 41736 2.05 (1.72-2.43) 38.89 (36.91-40.90) 44.11 (39.84-48.48) 48.75 (42.27-55.27) 42.29 (33.45-51.66)

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Men<90 cm women<80 cm 33827 1.15 (0.92-1.42) 33.11 (31.16-35.12) 42.27 (36.77-47.97) 49.95 (41.31-58.59) 57.37 (49.41-64.96) p for difference <0.0001 <0.0001 0.54 0.14 0.44

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Table 3. Risk factors for diabetes and prediabetes in Chinese AdultsDiabetes Prediabetes

Variable OR (95% CI) P Value OR (95% CI) P ValueMale sex 1.51 (1.35-1.70) <0.0001 1.24 (1.14-1.35) <0.0001Age, per 10 year increment 2.24 (2.08-2.40) <0.0001 1.56 (1.48-1.64) <0.0001Urban residence 1.15 (0.82-1.61) 0.42 1.00 (0.71-1.42) 0.99Han ethnicity 0.97 (0.91-1.04) 0.41 0.95 (0.90-1.00) 0.06Family history of diabetes 2.99 (2.67-3.35) <0.0001 1.25 (1.14-1.36) <0.0001Less than high school education 1.11 (1.00-1.23) 0.05 1.07 (0.96-1.18) 0.22Income ≤￥30000 RMB per year 1.15 (1.01-1.29) 0.03 1.04 (0.97-1.11) 0.26Current smoking 0.95 (0.85-1.05) 0.29 0.97 (0.90-1.05) 0.49Weight Overweight 1.45 (1.26-1.68) <0.0001 1.25 (1.13-1.39) 0.0002 Obesity 2.55 (2.25-2.88) <0.0001 1.76 (1.52-2.03) <0.0001Central obesity 1.54 (1.35-1.75) <0.0001 1.24 (1.13-1.36) <0.0001Hypertension 1.44 (1.29-1.61) <0.0001 1.13 (1.02-1.25) 0.03Hypercholesterolemia 1.44 (1.27-1.65) <0.0001 1.34 (1.21-1.48) <0.0001Hypertriglyceridemia 1.75 (1.60-1.91) <0.0001 1.23 (1.12-1.36) 0.0001High LDL-C 1.24 (1.07-1.43) 0.005 1.28 (1.10-1.50) 0.002Low HDL-C 1.44 (1.30-1.59) <0.0001 1.13 (1.05-1.22) 0.003Heart rate, per increase of 10 beats/min 1.21 (1.15-1.27) <0.0001 1.12 (1.09-1.16) <0.0001

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Figure 1. Prevalence, awareness, treatment, and control of diabetes among study participants.

222x158mm (96 x 96 DPI)

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Figure 2. Trends in diabetes prevalence according to the WHO criteria among Chinese men and women from 2007 to 2017.

317x238mm (96 x 96 DPI)

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Supplementary appendix

Figure 1. Flowchart depicting survey design.

Figure 2. Choropleth maps of diabetes and prediabetes prevalence in mainland China by province.

Figure 3. Prevalence of diabetes according to the WHO criteria among Chinese adults stratified by age group from 2008, 2013 and 2017

nationwide surveys.

Table 1. Diagnostic criteria for diabetes related disorders

Table 2. Crude and adjusted prevalence of diabetes and prediabetes by province.

Table 3. Prevalence of diabetes according to the WHO criteria among four large national representative surveys.

Table 4. Prevalence of diabetes, prediabetes and obesity among Chinese adults stratified by age group according to 2013 and 2017

nationwide surveys.

Table 5. Prevalence of diabetes and prediabetes among Chinese adults stratified by BMI groups according to 2013 and 2017 nationwide

surveys.

This supplementary material has been provided by the authors to provide readers additional information about their work.

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Figure 1. Flowchart depicting survey design

31 villages31 cities Random selection of a rural township from each village

Random selection of an urban district from each city

31 urban districts 31 rural townships

Random selection of two residential communities from each urban district

Random selection of two residential communities from each rural township

62 residential communities 62 residential communities

Random selection of individuals fulfilling the inclusion criteria and population stratification by sex and age

87900 adults were invited to participate in the survey

6963 subjects refused to participate in this survey

80937 subjects participated in this survey

167 subjects had incomplete information on sex or age

4890 subjects had incomplete information on plasma glucose or HbA1c

75880 subjects included in the final analysis

10 developed cities 13 developing cities 8 underdeveloped cities 9 developed cities 10 developing cities 12 underdeveloped cities

Sampling process for urban location Sampling process for rural location

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Confidential: For Review OnlyFigure 2. Choropleth maps of diabetes and prediabetes prevalence in mainland China by province.

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Figure 3. Prevalence of Diabetes according to the WHO criteria among Chinese adults stratified by age group from 2008, 2013 and 2017 nationwide surveys.

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Table 1. Diagnostic criteria for diabetes related disorders.

Disorders Diagnostic criteria

1. Self-reported diabetes A self-reported diagnosis that was determined previously by a health care professional.2. Newly diagnosed diabetes Fasting plasma glucose levels of 126 mg/dL (7 mmol/L) or greater, 2-hour plasma glucose

levels of 200 mg/dL (11·1 mmol/L) or greater (after 75 g glucose intake), or HbA1c levels of 6·5% or higher in individuals without self-reported diabetes.

3. Total diabetes The sum of the number of patients with self-reported diabetes and the number of patients with newly diagnosed diabetes.

4. Prediabetes Any participants who did not have diabetes but who had an HbA1c level of 5·7% to 6·4%, fasting plasma glucose level of 100 mg/dL (5·6 mmol/L) to less than 126 mg/dL (7 mmol/L), or 2-hour plasma glucose level of 140 mg/dL (7·8 mmol/L) to less than 200 mg/dL (11·1 mmol/L).

5. Isolated IFG Any participants who did not have diabetes but who had a fasting plasma glucose level of 110 mg/dL (6·1 mmol/L) to less than 126 mg/dL (7 mmol/L) and a 2-hour plasma glucose level less than 140 mg/dL (7·8 mmol/L).

6. Isolated IGT Any participants who did not have diabetes but who had a fasting plasma glucose level less than 126 mg/dL (7 mmol/L) and a 2-hour plasma glucose level of 140 mg/dL (7·8 mmol/L) to less than 200 mg/dL (11·1 mmol/L)

7. Combined IFG and IGT Any participants who did not have diabetes but who had a fasting plasma glucose level of 110 mg/dL (6·1 mmol/L) to less than 126 mg/dL (7 mmol/L) and a 2-hour plasma glucose level of 140 mg/dL (7·8 mmol/L) to less than 200 mg/dL (11·1 mmol/L).

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Table 2. Crude and adjusted prevalence of diabetes and prediabetes by province.

Crude, % (95% CI) Age- and sex-adjusted, % (95% CI)Province Total diabetes Prediabetes Total diabetes PrediabetesJilin 13.68 (12.20-15.16) 26.24 (24.35-28.14) 13.41 (7.95-21.73) 24.32 (20.12-29.08)Tianjin 13.44 (12.13-14.74) 32.06 (30.27-33.85) 14.38 (11.43-17.92) 31.58 (30.04-33.17)Hebei 14.80 (13.45-16.15) 42.05 (40.17-43.93) 14.35 (10.98-18.54) 40.84 (32.55-49.68)Shanxi 9.88 (8.74-11.02) 34.50 (32.68-36.31) 10.39 (6.86-15.44) 34.50 (29.07-40.36)Inner Mongolia 20.85 (19.29-22.41) 41.32 (39.43-43.20) 19.85 (17.55-22.36) 39.84 (24.06-58.05)Liaoning 12.76 (11.49-14.03) 27.66 (25.96-29.36) 12.68 (9.33-17.00) 27.16 (26.22-28.12)Beijing 16.96 (15.12-18.79) 38.15 (35.78-40.53) 13.56 (13.06-14.08) 31.74 (29.99-33.55)Heilongjiang 12.67 (11.40-13.94) 40.80 (38.93-42.68) 12.90 (9.10-17.96) 40.09 (21.98-61.39)Shanghai 14.04 (12.66-15.42) 32.91 (31.05-34.77) 13.73 (13.67-13.78) 29.88 (25.74-34.37)Jiangsu 11.31 (10.05-12.56) 31.31 (29.48-33.15) 11.50 (11.35-11.66) 30.77 (21.80-41.46)Zhejiang 11.82 (10.58-13.06) 32.79 (30.99-34.60) 11.21 (8.67-14.38) 32.70 (25.62-40.66)Anhui 8.99 (7.91-10.07) 18.80 (17.32-20.27) 8.47 (5.60-12.61) 17.20 (13.13-22.20)Fujian 17.58 (16.12-19.04) 48.02 (46.10-49.94) 17.25 (9.60-29.04) 49.75 (40.04-59.49)Jiangxi 12.60 (11.32-13.88) 48.26 (46.33-50.18) 12.07 (8.93-16.13) 46.64 (38.74-54.71)Shandong 14.38 (12.77-15.99) 36.25 (34.05-38.45) 13.36 (11.83-15.05) 34.86 (32.72-37.05)Henan 11.73 (10.50-12.97) 39.84 (37.96-41.72) 11.99 (10.89-13.18) 40.06 (36.73-43.49)Hubei 10.65 (9.48-11.82) 43.34 (41.46-45.23) 10.64 (9.46-11.94) 42.04 (41.52-42.57)Hunan 14.21 (12.85-15.56) 32.85 (31.03-34.67) 14.03 (13.77-14.30) 31.52 (25.25-38.55)Guangdong 13.45 (12.15-14.75) 37.60 (35.76-39.45) 12.67 (8.38-18.70) 34.94 (31.01-39.09)Guangxi 12.25 (10.89-13.61) 34.69 (32.72-36.66) 11.93 (7.84-17.74) 34.79 (32.73-36.91)Hainan 18.68 (16.97-20.40) 40.43 (38.28-42.59) 17.51 (17.24-17.78) 34.96 (31.44-38.67)Chongqing 17.04 (15.48-18.59) 30.42 (28.51-32.32) 16.01 (15.34-16.71) 29.77 (23.72-36.62)

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Sichuan 18.94 (17.11-20.76) 38.04 (35.78-40.31) 15.58 (12.14-19.78) 34.59 (26.94-43.13)Guizhou 7.38 (6.38-8.37) 30.38 (28.63-32.14) 6.20 (2.89-12.83) 27.61 (17.84-40.12)Yunnan 12.59 (11.33-13.85) 53.46 (51.56-55.36) 12.41 (10.84-14.16) 54.47 (46.12-62.57)Tibet 6.30 (5.25-7.35) 28.76 (26.80-30.72) 6.46 (6.00-6.95) 34.39 (26.18-43.67)Shaanxi 15.21 (13.73-16.69) 31.39 (29.48-33.30) 15.07 (13.69-16.56) 31.97 (25.79-38.87)Gansu 9.38 (8.28-10.49) 36.82 (34.99-38.65) 9.12 (6.69-12.31) 35.96 (33.38-38.62)Qinghai 12.18 (10.93-13.43) 38.87 (37.00-40.74) 11.80 (8.57-16.04) 38.47 (30.33-47.31)Ningxia 8.43 (7.45-9.41) 38.82 (37.10-40.55) 7.96 (4.00-15.20) 37.86 (37.35-38.38)Xinjiang 11.04 (9.82-12.26) 22.08 (20.46-23.70) 11.41 (10.55-12.32) 21.66 (15.91-28.78)

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Table 3. Prevalence of diabetes according to the WHO criteria from four large national representative surveys.

Year SexSelf-reported diabetes

Newly diagnosed diabetes

Total diabetes

Men 4.10% 6.50% 10.60%Women 3.50% 5.20% 8.80%

2007

All N/A N/A 9.70%Men 3.60% 6.60% 10.20%Women 3.40% 5.70% 9.10%

2010

All 3.50% 6.20% 9.70%Men 3.90% 7.20% 11.10%Women 4.10% 5.50% 9.60%

2013

All 4.00% 6.40% 10.40%Men 6.37% 5.76% 12.13%Women 5.64% 4.61% 10.25%

2017

All 6.01% 5.19% 11.20%

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Table 4. Prevalence of diabetes, prediabetes and obesity among Chinese adults stratified by age group according to 2013 and 2017 nationwide surveys.

Prevalence of diabetes, % (95% CI)

Prevalence of prediabetes, % (95% CI)

Prevalence of obesity, % (95% CI)Age group

2013 2017 2013 2017 2013 2017<40 Years old 5.9 (5.1-6.6) 3.9 (3.3-4.7) 28.8 (26.8-30.9) 24.5 (22.4-26.7) 6.0 (5.5-6.5) 5.7 (5.1-6.3)40-59 Years old 12.9 (12.3-13.5) 15.8 (14.8-16.9) 39.5 (37.8-41.2) 42.9 (41.0-44.9) 7.3 (6.9-7.6) 7.2 (6.7-7.9)60 Years or older 20.2 (19.1-21.2) 30.2 (27.9-32.6) 45.8 (44.3-47.2) 47.7 (45.0-50.5) 5.5 (5.0-6.0) 5.6 (5.0-6.2)

Table 5. Prevalence of diabetes and prediabetes among Chinese adults stratified by BMI groups according to 2013 and 2017 nationwide surveys.

Prevalence of diabetes, % (95% CI) Prevalence of prediabetes, % (95% CI)BMI group

2013 2017 2013 2017<25 7.8 (7.3-8.4) 9.99 (9.19-10.85) 32.6 (30.8-34.4) 33.03 (31.14-34.98)23-<25 15.4 (14.6-16.2) 15.64 (14.71-16.61) 40.7 (38.9-42.4) 38.94 (36.56-41.38)≥25 21.1 (19.5-22.7) 22.99 (21.79-24.23) 43.6 (41.5-45.6) 43.12 (40.27-46.01)

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The Highest Prevalence of Diabetes Recorded in Mainland ...Article Type: Research BMJ Journal: BMJ...

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