Evidence map›Paper›PMID 37532222›Full record

ArticleJournal of sport and health science2024

Association of physical activity with risk of chronic kidney disease in China: A population-based cohort study.

Kexiang Shi, Yunqing Zhu, Jun Lv, Dianjianyi Sun, Pei Pei, Huaidong Du, Yiping Chen, Ling Yang, Bing Han, Rebecca Stevens and 5 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of sport and health science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

15 citing papers in PubMed, 17 citations in OpenAlex.

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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

15 authors at 5 institutions in 2 countries.

Kexiang ShiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Yunqing ZhuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Jun LvDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
Dianjianyi SunDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
Pei PeiPeking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China.
Huaidong DuClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK.
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK; Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK.
Bing HanNCDs Prevention and Control Department, Henan Center for Disease Control and Prevention, Zhengzhou 450016, China.
Rebecca StevensClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing 100022, China.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Liming LiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
Canqing YuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China. Electronic address: yucanqing@pku.edu.cn.
China Kadoorie Biobank collaborative group
Peking University · CNUniversity of Oxford · GBChina National Center for Food Safety Risk Assessment · CNHenan Provincial Center for Disease Control and Prevention · CNMedical Research Council · GB

Funding

Cancer Research UK 29186Medical Research Council MC_UU_00017/1Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundInformation on the association between physical activity (PA) and the risk of chronic kidney disease (CKD) is limited. We aimed to explore the associations of total, domain-specific, and intensity-specific PA with CKD and its subtypes in China.

methodsThe study included 475,376 adults from the China Kadoorie Biobank aged 30-79 years during 2004-2008 at baseline. An interviewer-administered questionnaire was used to collect the information about PA, which was quantified as metabolic equivalent of task hours per day (MET-h/day) and categorized into 4 groups based on quartiles. Cox regression was used to analyze the association between PA and CKD risk.

resultsDuring a median follow-up of 12.1 years, 5415 incident CKD cases were documented, including 1159 incident diabetic kidney disease (DKD) cases and 362 incident hypertensive nephropathy (HTN) cases. Total PA was inversely associated with CKD risk, with an adjusted hazard ratio (HR, 95% confidence interval (95%CI)) of 0.83 (0.75-0.92) for incident CKD in the highest quartile of total PA as compared with participants in the lowest quartile. Similar results were observed for risk of DKD and HTN, and the corresponding HRs (95%CIs) were 0.75 (0.58-0.97) for DKD risk and 0.56 (0.37-0.85) for HTN risk. Increased nonoccupational PA, low-intensity PA, and moderate-to-vigorous-intensity PA were significantly associated with a decreased risk of CKD, with HRs (95%CIs) of 0.80 (0.73-0.88), 0.85 (0.77-0.94), and 0.85 (0.76-0.95) in the highest quartile, respectively.

conclusionPA, including nonoccupational PA, low-intensity PA, and moderate-to-vigorous-intensity PA, was inversely associated with the risk of CKD, including DKD, HTN, and other CKD, and such associations were dose dependent.

Indexed as

Hypertension, RenalNephritisRenal Insufficiency, ChronicAdultCohort StudiesExerciseHumansIncidenceChronic kidney diseaseDomainIntensityPhysical activity

Identifiers

PMID37532222
PMCPMC10980896
OpenAlexW4385431658

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.