Evidence map›Paper›PMID 42112160›Full record

ArticleKidney international reports2026

Trends in 10th Revision of the International Classification of Diseases-Coded CKD Incidence Among Chinese Adults.

Zhiqing Zeng, Si Cheng, Yizhen Hu, Chao Yang, Canqing Yu, Dianjianyi Sun, Pei Pei, Ling Yang, Yiping Chen, Huaidong Du and 8 more

Abstract read
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Article in Kidney international reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

18 authors.

Zhiqing ZengDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Si ChengDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yizhen HuDepartment of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
Chao YangRenal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Pei PeiPeking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
Ling YangClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Yiping ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Huaidong DuClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Kaifei ZhuNCDs Prevention and Control Department, Wuzhong Center for Disease Control and Prevention, Suzhou, Jiangsu, China.
Dan SchmidtClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Luxia ZhangRenal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
China Kadoorie Biobank Collaborative Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chronic kidney disease (CKD) is a growing public health concern, yet evidence on its incidence is limited in China. Methods: Using data from the China Kadoorie Biobank (CKB), which recruited 512,723 participants aged 30 to 79 years from 10 areas across China, we analyzed 5 major CKD subtypes: diabetic kidney disease (DKD), hypertensive nephropathy (HTN), glomerulonephritis (GN), chronic tubulointerstitial nephritis (CTIN), and obstructive nephropathy (ON). Total CKD included the aforementioned subtypes, CKD due to other reasons, or chronic kidney failure. Outcomes were ascertained through linkages to local death and disease registries and health insurance databases until December 31, 2018. Poisson regression model was used to assess secular trends and population variations. Results: Over a mean of 9.5 years of follow-up, 5662 total CKD cases were identified. The crude incidence rate (per 100,000 person-years) of total CKD was 119.7 (95% confidence interval: 116.6-122.8) between 2009 and 2018, with an annual increase of 8.9% (7.9%-10.0%) after adjusting for age, sex, and study area. The crude incidence rates were highest in GN, whereas biggest increases were observed in ON, DKD, and HTN. Total CKD incidence rate was similar between urban and rural areas; however, those of different subtypes varied: DKD or CTIN were higher in urban areas, and ON was significantly higher in rural areas. Males, older adults, and participants with hypertension or diabetes mellitus were at higher risks. Conclusion: Despite the underestimation of CKD incidence because of outcome ascertainment methods, the incidence of total CKD and its subtypes increased in the CKB population during 2009 to 2018. Measures should be taken against major driving factors, such as diabetes mellitus, hypertension, and kidney stones.

Indexed as

adultChinesechronic kidney diseasedisease subtypeincidence ratesecular trend

Identifiers

PMID42112160
PMCPMC13156572

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