the highest prevalence of diabetes recorded in mainland ...article type: research bmj journal: bmj...
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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
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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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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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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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References
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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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