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Physical activity patterns and chronic kidney disease risk: a 5-year study in stage 1 cardiovascular-kidney-metabolic syndrome - 04/01/26

Doi : 10.1016/j.rehab.2026.102098 
Shiyue Wang a, #, Pingping Liu b, #, Tingting Li c, Liping Duan b, Ting Hu a, Tianlu Yin d, Wen Ma e, Kaijuan Wang a, f, g,
a School of Public Health, Zhengzhou University, 100 Science Avenue, Zhengzhou 450001, Henan, China 
b Department of Nephrology, Handan Central Hospital, 35 South Zhonghua Street, Hanshan District, Handan 056001, Hebei, China 
c School of Public Health, North China University of Science and Technology, 21 Bohai Avenue, Caofeidian District, Tangshan 063210, Hebei, China 
d Department of Health Management, Aerospace Center Hospital, 15 Yuquan Road, Haidian District, Beijing 100049, China 
e First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, 41 Linyin Road, Kundu District, Baotou 014040, Inner Mongolia Autonomous Region, China 
f Henan Key Laboratory of Tumor Epidemiology and International Joint Laboratory of Tumor Biomarker and Molecular Imaging, Zhengzhou University, 40 Daxue North Road, Erqi District, Zhengzhou 450052, Henan, China 
g State Key Laboratory for Esophageal Cancer Prevention & Treatment and Metabolic Disorders, Zhengzhou University, 40 Daxue North Road, Erqi District, Zhengzhou 450052, Henan, China 

Corresponding author.
In corso di stampa. Manoscritto Accettato. Disponibile online dal Sunday 04 January 2026

Highlights

Two activity patterns identified in people with stage 1 cardiovascular-kidney-metabolic
High parabolic pattern reduces kidney disease risk by 82% vs declining pattern
Physical activity shows nonlinear associations with kidney disease risk over time

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Abstract

Background

Cardiovascular-kidney-metabolic syndrome (CKM) and chronic kidney disease (CKD) exhibit bidirectional associations. Limited research has explored the relationship between physical activity patterns and CKD risk among middle-aged and older adult participants with stage 1 CKM.

Methods

This longitudinal analysis used China Health and Retirement Longitudinal Study (CHARLS) data from 2015, 2018, and 2020, including 2569 participants with stage 1 CKM. Physical activity was assessed using the International Physical Activity Questionnaire with Metabolic Equivalent of Task (MET) calculations. A Latent Class Growth Model was constructed to examine patterns in physical activity across follow-up points. Restricted Cubic Spline analysis examined nonlinear associations between MET and CKD risk, while a Generalized Linear Model evaluated associations between physical activity patterns and CKD incidence.

Results

The CKM stage 1 participants’ mean [SD] age was 59 [ 8 ] years, 69% (1766/2569) were female, and 59% (1518/2569) had low educational attainment. During the 5-year follow-up, 55% (1415/2569) of participants progressed to CKD. Two physical activity patterns were identified: a high-level parabolic physical activity pattern (HPPA; n = 428) and a low-level continuously decreasing physical activity pattern (LCDPA; n = 2,167). Significant nonlinear associations existed between physical activity levels and CKD risk. CKD risk was significantly reduced when weekly physical activity reached 2613 MET at baseline, 3066 MET at 3 years, and 5907 MET at 5 years (all P < 0.001). Compared with LCDPA, HPPA significantly reduced CKD risk (OR = 0.18; 95% CI, 0.13-0.24; P < 0.001), with consistent protective effects across all subgroups.

Conclusion

Physical activity in stage 1 CKM participants is nonlinearly associated with CKD risk. Maintaining specific MET thresholds at diagnosis, 3 years, and 5 years post-diagnosis significantly reduced CKD incidence. HPPA significantly reduced CKD risk compared to LCDPA, and suggests that encouraging higher sustained physical activity could be valuable for CKD prevention in this population.

Data Registration

This study used data from the China Health and Retirement Longitudinal Study (CHARLS), publicly available at charls.pku.edu.cn (registration required). The processed datasets and analysis code are openly available in the Zenodo repository: 17840857 (10.5281/zenodo.17840857).

Il testo completo di questo articolo è disponibile in PDF.

Graphical Abstract




Image, graphical abstract

Il testo completo di questo articolo è disponibile in PDF.

Keywords : Cardiovascular-kidney-metabolic syndrome, Chronic kidney disease, Physical activity patterns, China Health and Retirement Longitudinal Study, Prospective cohort study

Abbreviations : AHA, BMI, CHARLS, CKD, CKM, CVD, DBP, eGFR, FBG, HbA1c, HPPA, IPAQ, LCDPA, LCGM, MET, MVPA, SBP, SO, TG


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