Evidence map›Paper›PMID 39882253›Full record

ArticleThe Lancet regional health. Western Pacific2025

Prevalence of chronic kidney disease among Chinese adults with diabetes: a nationwide population-based cross-sectional study.

Weiping Jia, Rong Yu, Limin Wang, Dalong Zhu, Lixin Guo, Jianping Weng, Hong Li, Mei Zhang, Xiaoqi Ye, Zhiguang Zhou and 9 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. miRNA in the Progression of Diabetic Kidney Disease: New Insight.International journal of molecular sciences · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Weiping JiaDepartment of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
Rong YuDepartment of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
Limin WangNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dalong ZhuDepartment of Endocrinology, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, Jiangsu Province, China.
Lixin GuoDepartment of Endocrinology, Beijing Hospital, Beijing, China.
Jianping WengDepartment of Endocrinology, Institute of Endocrine and Metabolic Diseases, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences, University of Science and Technology of China, Hefei, Anhui Province, China.
Hong LiDepartment of Endocrinology, The Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Mei ZhangNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoqi YeDepartment of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
Zhiguang ZhouInstitute of Metabolism and Endocrinology, Key Laboratory of Diabetes Immunology, Ministry of Education, National Clinical Research Center for Metabolic Diseases, The Second Xiangya Hospital and the Diabetes Center, Central South University, Changsha, Hunan Province, China.
Dajin ZouDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Qiuhe JiDepartment of Endocrinology, Xijing Hospital, Xi'an, Shaanxi Province, China.
Xiaohui GuoDepartment of Endocrinology, Peking University First Hospital, Beijing, China.
Yinan ZhangCenter for Translational Medicine, The Metabolic Diseases Biobank, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Dong LangDepartment of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
Jiarui WuKey Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang Province, China.
Jing WuNational Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xuhong HouDepartment of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai, China.
China National Diabetic Chronic Complications (DiaChronic) Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To date, comprehensive data on the distribution of chronic kidney disease (CKD), the most prevalent comorbidity in diabetes, among Chinese adults with diabetes is lacking. Additionally, research gaps exist in understanding the association between CKD and cardiovascular health (CVH), an integrated indicator of lifestyle and metabolic control, within a nationwide sample of Chinese adults with diabetes. Methods: A nationally community-based cross-sectional survey was conducted in 2018-2020. 58,560 residents diagnosed with diabetes aged 18-74 years nationwide were invited to participate, and 52,000 participants with complete CKD data were included in this study. CKD was identified by the presence of albuminuria (urine albumin-to-creatinine ratio ≥30 mg/g) and/or decreased estimated glomerular filtration rate (eGFR, <60 mL/min/1.73 m Findings: The weighted prevalence rates (95% CI) of CKD, albuminuria, and decreased eGFR were 32.6% (31.3%-33.8%), 30.8% (29.6%-32.1%), and 5.5% (5.1%-5.9%), respectively. Among those with CKD, 25.7% had diabetic retinopathy (DR) and 22.3% had cardiovascular disease (CVD). The weighted prevalence rates of albuminuria and decreased eGFR were consistently higher among southern residents, rural residents, and individuals with more severe DR and a history of CVD than their counterparts (all p < 0.05). After adjustment for age, sex, sub-regional division, setting, educational level, annual household income, family history of diabetes, diabetes duration, glucose-lowering treatment, any DR, CVD, and drinking status, the logistic models showed that the odds ratios (ORs) (95% CI) for albuminuria and decreased eGFR were 0.46 (0.42-0.51) and 0.61 (0.55-0.67) for the participants with moderate scores, and 0.14 (0.10-0.21) and 0.28 (0.19-0.41) for those with high scores, compared with those with low total LE8 scores. Furthermore, the restricted cubic spline curves depicted that the disparities in the odds of having albuminuria or decreased eGFR among subpopulations grouped by sex, age, setting, and geographical region, significantly decreased and even disappeared in some cases as the LE8 scores increased. Interpretation: Chinese adults with diabetes are heavily burdened by CKD. Optimized CVH is central to reducing CKD risk across different subpopulations. Funding: National Key Clinical Specialty, the Chinese Academy of Engineering.

Indexed as

Cardiovascular healthChronic kidney diseaseDiabetesPrevalence

Identifiers

PMID39882253
PMCPMC11773038

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.