[Skip to Content]
[Skip to Content Landing]

Prevalence and Treatment of Diabetes in China, 2013-2018

Educational Objective
To learn the changes in diabetes and prediabetes prevalence in China from 2013 to 2018.
1 Credit CME
Key Points

Question  What is the prevalence of diabetes and prediabetes and diabetes treatment in China?

Findings  In this nationally representative cross-sectional study conducted in mainland China with 173 642 participants in 2018, the estimated overall prevalence of diabetes was 12.4% and of prediabetes was 38.1%, with awareness of diabetes in 36.7%, treatment in 32.9%, and adequate control in 50.1%. Among the 170 287 participants enrolled in 2013, the estimated prevalence of diabetes was 10.9% and of prediabetes was 35.7%.

Meaning  Estimated diabetes prevalence in China increased significantly from 2013 to 2018, with a low estimated prevalence of adequate treatment.


Importance  Recent data on prevalence, awareness, treatment, and risk factors of diabetes in China is necessary for interventional efforts.

Objective  To estimate trends in prevalence, awareness, treatment, and risk factors of diabetes in China based on national data.

Design, Setting, and Participants  Cross-sectional nationally representative survey data collected in adults aged 18 years or older in mainland China from 170 287 participants in the 2013-2014 years and 173 642 participants in the 2018-2019 years.

Exposures  Fasting plasma glucose and hemoglobin A1c levels were measured for all participants. A 2-hour oral glucose tolerance test was conducted for all participants without diagnosed diabetes.

Main Outcomes and Measures  Primary outcomes were diabetes and prediabetes defined according to American Diabetes Association criteria. Secondary outcomes were awareness, treatment, and control of diabetes and prevalence of risk factors. A hemoglobin A1c level of less than 7.0% (53 mmol/mol) among treated patients with diabetes was considered adequate glycemic control.

Results  In 2013, the median age was 55.8 years (IQR, 46.4-65.2 years) and the weighted proportion of women was 50.0%; in 2018, the median age was 51.3 years (IQR, 42.1-61.6 years), and the weighted proportion of women was 49.5%. The estimated prevalence of diabetes increased from 10.9% (95% CI, 10.4%-11.5%) in 2013 to 12.4% (95% CI, 11.8%-13.0%) in 2018 (P < .001). The estimated prevalence of prediabetes was 35.7% (95% CI, 34.2%-37.3%) in 2013 and 38.1% (95% CI, 36.4%-39.7%) in 2018 (P = .07). In 2018, among adults with diabetes, 36.7% (95% CI, 34.7%-38.6%) reported being aware of their condition, and 32.9% (95% CI, 30.9%-34.8%) reported being treated; 50.1% (95% CI, 47.5%-52.6%) of patients receiving treatment were controlled adequately. These rates did not change significantly from 2013. From 2013 to 2018, low physical activity, high intake of red meat, overweight, and obesity significantly increased in prevalence.

Conclusions and Relevance  In this survey study, the estimated diabetes prevalence was high and increased from 2013 to 2018. There was no significant improvement in the estimated prevalence of adequate treatment.

Sign in to take quiz and track your certificates

Buy This Activity

JN Learning™ is the home for CME and MOC from the JAMA Network. Search by specialty or US state and earn AMA PRA Category 1 Credit(s)™ from articles, audio, Clinical Challenges and more. Learn more about CME/MOC

CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Corresponding Authors: Jing Wu, PhD, National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Rd, Xicheng District, 100050 Beijing, China (wujing@chinacdc.cn); Youfa Wang, MD, PhD, Global Health Institute, Xi’an Jiaotong University Health Science Center, Room 3104, No. 21 Hongren Building, West China Science and Technology Innovation Harbour (iHarbour), 710061 Xi’an, Shaanxi, China (youfawang@gmail.com).

Accepted for Publication: November 23, 2021.

Correction: This article was corrected on March 15, 2022, to fix the symbol in the overweight and obesity row of Table 5 and to show the ranges of the overweight and obesity rows as subcategories.

Author Contributions: Drs Limin Wang and Y. Wang had full access to all of the data in the study and take responsibility for the integrity of the study and the accuracy of the data analysis. Drs Limin, Wang, Peng, and Zhao contributed equally.

Concept and design: Y. Wang, Limin Wang, Wu, Peng.

Acquisition of data or filed quality control: Limin Wang, Zhao, M. Zhang, X. Zhang, C. Li, Huang, Linhong Wang, Zhou, Wu.

Drafting of the manuscript: Peng, Limin Wang, Zhao, Y. Wang.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Zhao, M. Zhang, Song, Shi, Peng, Limin Wang, Y. Wang.

Interpretation of data: All authors

Administrative, technical, or material support: Y. Wang, Limin Wang, Wu.

Supervision: Y. Wang, Limin Wang, Wu.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported in part by research grants 2018YFC1311706, 2017YFC0907200, and 2017YFC0907201 from the National Key Research and Development Program of China, the Chinese central government (key project of public health program 2013 and 2018), and grant 821603846 from the National Scientific Foundation of China.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank the Chinese Center for Disease Control and Prevention staff and those in the 31 provincial level administrative areas in China and the local investigators in the 298 Disease Surveillance Sites for their efforts in data collection. We also thank Ke Li, BA, from Xi’an Jiaotong University for her assistance in editing the manuscript. She did not receive compensation for her role in the study.

Malik  VS , Willet  WC , Hu  FB .  Nearly a decade on—trends, risk factors and policy implications in global obesity.   Nat Rev Endocrinol. 2020;16(11):615-616. doi:10.1038/s41574-020-00411-yPubMedGoogle ScholarCrossref
Magliano  DJ , Islam  RM , Barr  ELM ,  et al.  Trends in incidence of total or type 2 diabetes: systematic review.   BMJ. 2019;366:l5003. doi:10.1136/bmj.l5003PubMedGoogle Scholar
Wang  L , Li  X , Wang  Z ,  et al.  Trends in prevalence of diabetes and control of risk factors in diabetes among US adults, 1999-2018.   JAMA. 2021. doi:10.1001/jama.2021.9883PubMedGoogle Scholar
Chandrupatla  SG , Khalid  I , Muthuluri  T , Dantala  S , Tavares  M .  Diabetes and prediabetes prevalence among young and middle-aged adults in India, with an analysis of geographic differences: findings from the National Family Health Survey.   Epidemiol Health. 2020;42:e2020065. doi:10.4178/epih.e2020065PubMedGoogle Scholar
Pan  XR , Yang  WY , Li  GW , Liu  J ; National Diabetes Prevention and Control Cooperative Group.  Prevalence of diabetes and its risk factors in China, 1994.   Diabetes Care. 1997;20(11):1664-1669. doi:10.2337/diacare.20.11.1664PubMedGoogle ScholarCrossref
Yang  W , Lu  J , Weng  J ,  et al; China National Diabetes and Metabolic Disorders Study Group.  Prevalence of diabetes among men and women in China.   N Engl J Med. 2010;362(12):1090-1101. doi:10.1056/NEJMoa0908292PubMedGoogle ScholarCrossref
Xu  Y , Wang  L , He  J ,  et al; 2010 China Noncommunicable Disease Surveillance Group.  Prevalence and control of diabetes in Chinese adults.   JAMA. 2013;310(9):948-959. doi:10.1001/jama.2013.168118PubMedGoogle ScholarCrossref
Wang  L , Gao  P , Zhang  M ,  et al.  Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013.   JAMA. 2017;317(24):2515-2523. doi:10.1001/jama.2017.7596PubMedGoogle ScholarCrossref
Li  LM , Rao  KQ , Kong  LZ ,  et al; Technical Working Group of China National Nutrition and Health Survey.  A description on the Chinese national nutrition and health survey in 2002. 中国居民2002年营养与健康状况调查.   Zhonghua Liu Xing Bing Xue Za Zhi. 2005;26(7):478-484.PubMedGoogle Scholar
International Diabetes Federation.  IDF Diabetes Atlas. 9th ed. International Diabetes Federation; 2019.
Centers for Disease Control and Prevention. National diabetes statistics report 2020: estimates of diabetes and its burden in the United States. Accessed October 24, 2021. https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf
Fang  M , Wang  D , Coresh  J , Selvin  E .  Trends in diabetes treatment and control in US adults, 1999-2018.   N Engl J Med. 2021;384(23):2219-2228. doi:10.1056/NEJMsa2032271PubMedGoogle ScholarCrossref
Li  Y , Teng  D , Shi  X ,  et al.  Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study.   BMJ. 2020;369:m997. doi:10.1136/bmj.m997PubMedGoogle Scholar
Zhou  M , Astell-Burt  T , Bi  Y ,  et al.  Geographical variation in diabetes prevalence and detection in China: multilevel spatial analysis of 98,058 adults.   Diabetes Care. 2015;38(1):72-81. doi:10.2337/dc14-1100PubMedGoogle ScholarCrossref
Wang  L , Zhou  B , Zhao  Z ,  et al.  Body-mass index and obesity in urban and rural China: findings from consecutive nationally representative surveys during 2004-18.   Lancet. 2021;398(10294):53-63. doi:10.1016/S0140-6736(21)00798-4PubMedGoogle ScholarCrossref
Liu  Y , Wang  L , Pang  R ,  et al.  Designing and implementation of a web-based quality monitoring system for plasma glucose measurement in a multicenter population study.  Article in Chinese.  Zhonghua Liu Xing Bing Xue Za Zhi. 2015;36(5):506-509.PubMedGoogle Scholar
Zhou  BF ; Cooperative Meta-Analysis Group of the Working Group on Obesity in China.  Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults.   Biomed Environ Sci. 2002;15(1):83-96.PubMedGoogle Scholar
World Health Organization. Waist circumference and waist-hip ratio: report of a WHO expert consultation; August 8-11, 2008; Geneva, Switzerland. Accessed July 15, 2021. http://apps.who.int/iris/bitstream/handle/10665/44583/9789241501491_eng.pdf
American Diabetes Association.  2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2021.   Diabetes Care. 2021;44(suppl 1):S15-S33. doi:10.2337/dc21-S002PubMedGoogle ScholarCrossref
Jung  CH , Son  JW , Kang  S ,  et al.  Diabetes fact sheets in Korea, 2020: an appraisal of current status.   Diabetes Metab J. 2021;45(1):1-10. doi:10.4093/dmj.2020.0254PubMedGoogle ScholarCrossref
Wang  Y , Zhao  L , Gao  L , Pan  A , Xue  H .  Health policy and public health implications of obesity in China.   Lancet Diabetes Endocrinol. 2021;9(7):446-461. doi:10.1016/S2213-8587(21)00118-2PubMedGoogle ScholarCrossref
Chan  JC , Zhang  Y , Ning  G .  Diabetes in China: a societal solution for a personal challenge.   Lancet Diabetes Endocrinol. 2014;2(12):969-979. doi:10.1016/S2213-8587(14)70144-5PubMedGoogle ScholarCrossref
Zhang  Y , Ning  G .  Diabetes: young-onset type 2 diabetes mellitus—a challenge for Asia.   Nat Rev Endocrinol. 2014;10(12):703-704. doi:10.1038/nrendo.2014.162PubMedGoogle ScholarCrossref
Wang  Y , Sun  M , Yang  Y .  China Blue Paper on Obesity Prevention and Control. Peking University Medical Press; 2019.
Bragg  F , Holmes  MV , Iona  A ,  et al; China Kadoorie Biobank Collaborative Group.  Association between diabetes and cause-specific mortality in rural and urban areas of China.   JAMA. 2017;317(3):280-289. doi:10.1001/jama.2016.19720PubMedGoogle ScholarCrossref
Powell  LM , Wada  R , Krauss  RC , Wang  Y .  Ethnic disparities in adolescent body mass index in the United States: the role of parental socioeconomic status and economic contextual factors.   Soc Sci Med. 2012;75(3):469-476. doi:10.1016/j.socscimed.2012.03.019PubMedGoogle ScholarCrossref
Di Cesare  M , Khang  YH , Asaria  P ,  et al; Lancet NCD Action Group.  Inequalities in non-communicable diseases and effective responses.   Lancet. 2013;381(9866):585-597. doi:10.1016/S0140-6736(12)61851-0PubMedGoogle ScholarCrossref
Zhao  Z , Li  M , Li  C ,  et al.  Dietary preferences and diabetic risk in China: a large-scale nationwide Internet data-based study.   J Diabetes. 2020;12(4):270-278. doi:10.1111/1753-0407.12967PubMedGoogle ScholarCrossref
Yip  W , Fu  H , Chen  AT ,  et al.  10 years of health-care reform in China: progress and gaps in Universal Health Coverage.   Lancet. 2019;394(10204):1192-1204. doi:10.1016/S0140-6736(19)32136-1PubMedGoogle ScholarCrossref
State of Council, China. Healthy China 2030 initiative. Released October 24, 2016. Accessed Nov 13,2021. http://www.gov.cn/xinwen/2016-10/25/content_5124174.htm
Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right

Name Your Search

Save Search
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience

Lookup An Activity


My Saved Searches

You currently have no searches saved.


My Saved Courses

You currently have no courses saved.