Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 961

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Prevalence and Treatment of Diabetes in China, 2013-2018

Open access
Wang, Limin, Peng, Wen, Zhao, Zhenping, Zhang, Mei, Shi, Zumin, Song, Ziwei, Zhang, Xiao, Li, Chun, Huang, Zhengjing, Sun, Xiaomin, Wang, Linhong, Zhou, Maigeng, Wu, Jing, Wang, Youfa·2021·JAMA

Abstract

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/jama.2021.22208

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 27 references

Cited by

See all 961

Metadata

Authors
Wang, L., Peng, W., Zhao, Z., Zhang, M., Shi, Z., Song, Z., Zhang, X., Li, C., Huang, Z., Sun, X., Wang, L., Zhou, M., Wu, J., & Wang, Y.
Venue
JAMA
Published
2021-12-28
Volume
326
Issue
24
Pages
2498
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W4200230313
Cited by
961
References
27
FWCI
86.61
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Prevalence and Treatment of Diabetes in China, 2013-2018. https://app.cochat.ai/papers/10.1001/jama.2021.22208
The paper
Wang, L., Peng, W., Zhao, Z., Zhang, M., Shi, Z., Song, Z., Zhang, X., Li, C., Huang, Z., Sun, X., Wang, L., Zhou, M., Wu, J., & Wang, Y. (2021). Prevalence and Treatment of Diabetes in China, 2013-2018. JAMA. https://doi.org/10.1001/jama.2021.22208

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.