Association between dynamic trajectory patterns of cardiometabolic indicators and renal insufficiency: a large-scale prospective cohort study among Chinese health examination population_Chinese Journal of Evidence-Based Medicine

Authors：

SU Xiaoyi ^1,2 , SU Shiqi ^2,3 , ZHANG Yixiao ^1,3 , MAO Ruolan ^1,3 , XIANG Nanyan ^1,3 , FU Tingting ^1,3 , WANG Le ^1,3 , LIAO Banghua ³ ,  LIN Yifei ³ ,  HUANG Jin ³

1. Department of Urology, Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Department of Urology, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
3. Department of Urology, Lab of Health Data Science, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;

Corresponding?author：

LIN Yifei, Email: ylin@wchscu.edu.cn; HUANG Jin, Email: michael_huangjin@163.com

Keywords：

Health check-up; Longitudinal study; Renal insufficiency; Cardiometabolic; Trajectory analysis

DOI：

10.7507/1672-2531.202602058

Video：

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Objective To investigate the association between cardiometabolic indicators and the risk of incident renal insufficiency using a longitudinal physical examination cohort. Methods Based on a large-scale, multi-center, repeated-measurement physical examination cohort in China, this study evaluated the impact of baseline cardiovascular metabolic indicators on incident renal insufficiency using logistic regression, Cox proportional hazards models, Poisson regression, and generalized linear mixed-effects models. Furthermore, latent class mixed models (LCMM) were employed to identify the longitudinal trajectories of these indicators, and the associations between distinct trajectory patterns and the risk of renal insufficiency were analyzed using Cox and logistic regression models. Results Derived from a massive longitudinal cohort of 680 000 individuals across a multi-center healthcare network, a total of 264 379 participants were ultimately included, among whom 82 849 developed renal insufficiency during the follow-up period. Baseline analyses revealed that elevated levels of triglycerides (TG) and fasting glucose (FG) consistently increased the risk of renal insufficiency across multiple statistical models (all P_FDR<0.001). Trajectory analyses demonstrated that high-level longitudinal trajectories of FG (HR=1.274, 95%CI 1.230 to 1.320) and diastolic blood pressure (DBP) (HR=1.042, 95%CI 1.023 to 1.061) were significant independent risk factors for the disease. Notably, the evolutionary trajectory of systolic blood pressure (SBP) exhibited opposite association directions between the Cox and logistic models, whereas the TG trajectory lost its statistical significance after fully adjusting for smoking and alcohol consumption. Conclusion Both baseline characteristics and longitudinal variations of cardiovascular metabolic indicators are significantly associated with the incidence of renal insufficiency. Abnormal levels and high-level evolutionary trajectories of fasting glucose and triglycerides serve as robust risk factors for the disease. Regular monitoring and longitudinal tracking of these metabolic profiles are of profound clinical value for the prevention and early identification of renal insufficiency.

Citation： SU Xiaoyi, SU Shiqi, ZHANG Yixiao, MAO Ruolan, XIANG Nanyan, FU Tingting, WANG Le, LIAO Banghua, LIN Yifei, HUANG Jin. Association between dynamic trajectory patterns of cardiometabolic indicators and renal insufficiency: a large-scale prospective cohort study among Chinese health examination population. Chinese Journal of Evidence-Based Medicine, 2026, 26(6): 661-668. doi: 10.7507/1672-2531.202602058 Copy

1.	Stevens PE, Ahmed SB, Carrero JJ, et al. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int, 2024, 105(4S): S117-S314.
2.	Foreman KJ, Marquez N, Dolgert A, et al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories. Lancet, 2018, 392(10159): 2052-2090.
3.	Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet, 2012, 379(9818): 815-822.
4.	Kushner P, Khunti K, Cebrián A, et al. Early identification and management of chronic kidney disease: a narrative review of the crucial role of primary care practitioners. Adv Ther, 2024, 41(10): 3757-3770.
5.	Sebastian SA, Padda I, Johal G. Cardiovascular-kidney-metabolic (CKM) syndrome: a state-of-the-art review. Curr Probl Cardiol, 2024, 49(2): 102344.
6.	Wang J, Wang F, Liu S, et al. Reduced kidney function, albuminuria, and risks for all-cause and cardiovascular mortality in China: a population-based cohort study. BMC Nephrol, 2017, 18(1): 188.
7.	Sullivan MK, Lees JS, Rosales BM, et al. Sex and the relationship between cardiometabolic risk factors and estimated GFR decline: a population-based cohort study. Am J Kidney Dis, 2024, 84(6): 731-741. e1.
8.	Tang R, Wang X, Li X, et al. Adherence to life’s essential 8 and incident chronic kidney disease: a prospective study of 147, 988 UK Biobank participants. Am J Clin Nutr, 2023, 118(4): 804-811.
9.	Wang L, Lin Y, Fu T, et al. Blood cell biomarker trajectories and depression risk in a sex-stratified 10-year longitudinal cohort analysis. Nat Ment Health, 2025, 3(11): 1438-1451.
10.	Lin Y, Yang Y, Xiang N, et al. Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up. BMC Med, 2024, 22(1): 105.
11.	Lin Y, Yang Y, Li Z, et al. Cohort profile: the West-China hospital alliance longitudinal epidemiology wellness (WHALE) study. Eur J Epidemiol, 2025, 40(9): 1143-1159.
12.	Wang L, Fu T, Yang Y, et al. Longitudinal trajectories of adiposity indicators and cancer risk over 14 years: evidence from repeated health check-ups of 10 times or more - China, 2010-2023. China CDC Wkly, 2025, 7(35): 1138-1143.
13.	Awdishu L, Maxson R, Gratt C, et al. KDIGO 2024 clinical practice guideline on evaluation and management of chronic kidney disease: a primer on what pharmacists need to know. Am J Health Syst Pharm, 2025, 82(12): 660-671.
14.	Wang H, Naghavi M, Allen C, et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet, 2016, 388(10053): 1459-1544.
15.	Xia J, Wang L, Ma Z, et al. Cigarette smoking and chronic kidney disease in the general population: a systematic review and meta-analysis of prospective cohort studies. Nephrol Dial Transplant, 2017, 32(3): 475-487.
16.	上海市腎內科臨床質量控制中心專家組. 慢性腎臟病早期篩查、診斷及防治指南(2022年版). 中華腎臟病雜志, 2022, 38(5): 453-464.
17.	Liu J, Ma Y, Yu G, et al. Trajectories of fasting plasma glucose and risks of chronic kidney disease in a general chinese population: a retrospective study. Int J Gen Med, 2023, 16: 5695-5702.
18.	Rooney MR, Wallace AS, Echouffo Tcheugui JB, et al. Prediabetes is associated with elevated risk of clinical outcomes even without progression to diabetes. Diabetologia, 2025, 68(2): 357-366.
19.	Wang Z, do Carmo JM, Aberdein N, et al. Synergistic interaction of hypertension and diabetes in promoting kidney injury and the role of endoplasmic reticulum stress. Hypertension, 2017, 69(5): 879-891.
20.	Xu W, Zhu Y, Wang S, et al. From adipose to ailing kidneys: the role of lipid metabolism in obesity-related chronic kidney disease. Antioxidants (Basel), 2024, 13(12): 1540.
21.	Barbagallo CM, Cefalù AB, Giammanco A, et al. Lipoprotein abnormalities in chronic kidney disease and renal transplantation. Life (Basel), 2021, 11(4): 315.
22.	Delrue C, Speeckaert MM. Beyond blood pressure: emerging pathways and precision approaches in hypertension-induced kidney damage. Int J Mol Sci, 2025, 26(15): 7606.
23.	Kalantar-Zadeh K, Block G, Horwich T, et al. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol, 2004, 43(8): 1439-1444.
24.	Rocha H, Gouveia R, Elias C, et al. Systolic blood pressure increase in chronic heart failure associates with survival advantage. Porto Biomed J, 2025, 10(2): e284.
25.	Watanabe Y, Kubota Y, Asai K. Worsening renal function in acute heart failure: not always harmful. Curr Heart Fail Rep, 2025, 22(1): 25.
26.	van der Tol A, Van Biesen W, Van Laecke S, et al. Statin use and the presence of microalbuminuria. results from the ERICABEL trial: a non-interventional epidemiological cohort study. PLoS ONE, 2012, 7(2): e31639.
27.	Rahman M, Yang W, Akkina S, et al. Relation of serum lipids and lipoproteins with progression of CKD: the CRIC study. Clin J Am Soc Nephrol, 2014, 9(7): 1190-1198.
28.	Yen CL, Fan PC, Lee CC, et al. The role of maintaining lower LDL-C level during statin treatment for advanced CKD patients. Atherosclerosis, 2024, 399: 119042.
29.	Bergman BC, Perreault L, Hunerdosse D, et al. Novel and reversible mechanisms of smoking-induced insulin resistance in humans. Diabetes, 2012, 61(12): 3156-3166.
30.	Jeon S, Carr R. Alcohol effects on hepatic lipid metabolism. J Lipid Res, 2020, 61(4): 470-479.
31.	Kunutsor SK, Seidu S, Kurl S, et al. Baseline and usual triglyceride-glucose index and the risk of chronic kidney disease: a prospective cohort study. GeroScience, 2024, 46(3): 3035-3046.
32.	Hwang W, Lee EJ, Park JH, et al. Effect of long-term blood pressure trajectory on the future development of chronic kidney disease: an analysis of data from the Korean national insurance health checkup study. Epidemiol Health, 2024, 46: e2024090.
33.	Joo YS, Kim HW, Nam KH, et al. Association between longitudinal blood pressure trajectory and the progression of chronic kidney disease: results from the KNOW-CKD. Hypertension, 2021, 78(5): 1355-1364.

1. Stevens PE, Ahmed SB, Carrero JJ, et al. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int, 2024, 105(4S): S117-S314.
2. Foreman KJ, Marquez N, Dolgert A, et al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories. Lancet, 2018, 392(10159): 2052-2090.
3. Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet, 2012, 379(9818): 815-822.
4. Kushner P, Khunti K, Cebrián A, et al. Early identification and management of chronic kidney disease: a narrative review of the crucial role of primary care practitioners. Adv Ther, 2024, 41(10): 3757-3770.
5. Sebastian SA, Padda I, Johal G. Cardiovascular-kidney-metabolic (CKM) syndrome: a state-of-the-art review. Curr Probl Cardiol, 2024, 49(2): 102344.
6. Wang J, Wang F, Liu S, et al. Reduced kidney function, albuminuria, and risks for all-cause and cardiovascular mortality in China: a population-based cohort study. BMC Nephrol, 2017, 18(1): 188.
7. Sullivan MK, Lees JS, Rosales BM, et al. Sex and the relationship between cardiometabolic risk factors and estimated GFR decline: a population-based cohort study. Am J Kidney Dis, 2024, 84(6): 731-741. e1.
8. Tang R, Wang X, Li X, et al. Adherence to life’s essential 8 and incident chronic kidney disease: a prospective study of 147, 988 UK Biobank participants. Am J Clin Nutr, 2023, 118(4): 804-811.
9. Wang L, Lin Y, Fu T, et al. Blood cell biomarker trajectories and depression risk in a sex-stratified 10-year longitudinal cohort analysis. Nat Ment Health, 2025, 3(11): 1438-1451.
10. Lin Y, Yang Y, Xiang N, et al. Characterization and trajectories of hematological parameters prior to severe COVID-19 based on a large-scale prospective health checkup cohort in western China: a longitudinal study of 13-year follow-up. BMC Med, 2024, 22(1): 105.
11. Lin Y, Yang Y, Li Z, et al. Cohort profile: the West-China hospital alliance longitudinal epidemiology wellness (WHALE) study. Eur J Epidemiol, 2025, 40(9): 1143-1159.
12. Wang L, Fu T, Yang Y, et al. Longitudinal trajectories of adiposity indicators and cancer risk over 14 years: evidence from repeated health check-ups of 10 times or more - China, 2010-2023. China CDC Wkly, 2025, 7(35): 1138-1143.
13. Awdishu L, Maxson R, Gratt C, et al. KDIGO 2024 clinical practice guideline on evaluation and management of chronic kidney disease: a primer on what pharmacists need to know. Am J Health Syst Pharm, 2025, 82(12): 660-671.
14. Wang H, Naghavi M, Allen C, et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet, 2016, 388(10053): 1459-1544.
15. Xia J, Wang L, Ma Z, et al. Cigarette smoking and chronic kidney disease in the general population: a systematic review and meta-analysis of prospective cohort studies. Nephrol Dial Transplant, 2017, 32(3): 475-487.
16. 上海市腎內科臨床質量控制中心專家組. 慢性腎臟病早期篩查、診斷及防治指南(2022年版). 中華腎臟病雜志, 2022, 38(5): 453-464.
17. Liu J, Ma Y, Yu G, et al. Trajectories of fasting plasma glucose and risks of chronic kidney disease in a general chinese population: a retrospective study. Int J Gen Med, 2023, 16: 5695-5702.
18. Rooney MR, Wallace AS, Echouffo Tcheugui JB, et al. Prediabetes is associated with elevated risk of clinical outcomes even without progression to diabetes. Diabetologia, 2025, 68(2): 357-366.
19. Wang Z, do Carmo JM, Aberdein N, et al. Synergistic interaction of hypertension and diabetes in promoting kidney injury and the role of endoplasmic reticulum stress. Hypertension, 2017, 69(5): 879-891.
20. Xu W, Zhu Y, Wang S, et al. From adipose to ailing kidneys: the role of lipid metabolism in obesity-related chronic kidney disease. Antioxidants (Basel), 2024, 13(12): 1540.
21. Barbagallo CM, Cefalù AB, Giammanco A, et al. Lipoprotein abnormalities in chronic kidney disease and renal transplantation. Life (Basel), 2021, 11(4): 315.
22. Delrue C, Speeckaert MM. Beyond blood pressure: emerging pathways and precision approaches in hypertension-induced kidney damage. Int J Mol Sci, 2025, 26(15): 7606.
23. Kalantar-Zadeh K, Block G, Horwich T, et al. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol, 2004, 43(8): 1439-1444.
24. Rocha H, Gouveia R, Elias C, et al. Systolic blood pressure increase in chronic heart failure associates with survival advantage. Porto Biomed J, 2025, 10(2): e284.
25. Watanabe Y, Kubota Y, Asai K. Worsening renal function in acute heart failure: not always harmful. Curr Heart Fail Rep, 2025, 22(1): 25.
26. van der Tol A, Van Biesen W, Van Laecke S, et al. Statin use and the presence of microalbuminuria. results from the ERICABEL trial: a non-interventional epidemiological cohort study. PLoS ONE, 2012, 7(2): e31639.
27. Rahman M, Yang W, Akkina S, et al. Relation of serum lipids and lipoproteins with progression of CKD: the CRIC study. Clin J Am Soc Nephrol, 2014, 9(7): 1190-1198.
28. Yen CL, Fan PC, Lee CC, et al. The role of maintaining lower LDL-C level during statin treatment for advanced CKD patients. Atherosclerosis, 2024, 399: 119042.
29. Bergman BC, Perreault L, Hunerdosse D, et al. Novel and reversible mechanisms of smoking-induced insulin resistance in humans. Diabetes, 2012, 61(12): 3156-3166.
30. Jeon S, Carr R. Alcohol effects on hepatic lipid metabolism. J Lipid Res, 2020, 61(4): 470-479.
31. Kunutsor SK, Seidu S, Kurl S, et al. Baseline and usual triglyceride-glucose index and the risk of chronic kidney disease: a prospective cohort study. GeroScience, 2024, 46(3): 3035-3046.
32. Hwang W, Lee EJ, Park JH, et al. Effect of long-term blood pressure trajectory on the future development of chronic kidney disease: an analysis of data from the Korean national insurance health checkup study. Epidemiol Health, 2024, 46: e2024090.
33. Joo YS, Kim HW, Nam KH, et al. Association between longitudinal blood pressure trajectory and the progression of chronic kidney disease: results from the KNOW-CKD. Hypertension, 2021, 78(5): 1355-1364.

Chinese Journal of Evidence-Based Medicine

Association between dynamic trajectory patterns of cardiometabolic indicators and renal insufficiency: a large-scale prospective cohort study among Chinese health examination population

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