ArticleLipids in health and disease2025
The association between the cardiac metabolic index and rapid kidney function decline and CKD in individuals with different glucose metabolism statuses: results from the China health and retirement longitudinal study.
Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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6 citing papers in PubMed.
- Machine learning prediction of CKD progression in hyperglycemic elderly adults: a prospective community cohort study.Renal failure · 2026Article
- Cardiometabolic index (CMI) and sarcopenia as predictors of all-cause and cardiovascular mortality in chronic kidney disease: a NHANES-based cohort study.Renal failure · 2026Article
- Article
- Correction: The association between the cardiac metabolic index and rapid kidney function decline and CKD in individuals with different glucose metabolism statuses: results from the China health and retirement longitudinal study.Lipids in health and disease · 2026Article
- Glycaemic Status Modifies the Association Between Cardiometabolic Index and Cardio-Kidney Outcomes: A Multi-Cohort Analysis.Diabetes/metabolism research and reviews · 2026Article
- The trajectory of frailty index and its association with rapid decline in kidney function and the incidence of chronic kidney disease: evidence from the China health and retirement longitudinal study.Aging clinical and experimental research · 2025Article
Corrections and comments
- Erratum issued
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10 authors.
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Abstract
backgroundThe Cardiometabolic Index (CMI) is a new measure that combines fat distribution and lipid profiles. However, its relationship with rapid decline in renal function and the chronic kidney disease (CKD), especially in individuals with varying glucose metabolism, is still unclear.
methodThis study included 3,485 participants aged 45 and above from the China Longitudinal Study on Health and Retirement (CHARLS), with baseline assessments in 2011-2012 and follow-ups in 2015 and 2018. Participants were grouped into four categories (Q1-Q4) based on baseline CMI levels. The primary outcome was rapid decline in renal function, with CKD events also observed. Multivariable logistic models and restricted cubic spline (RCS) analysis were used to explore the relationship between baseline CMI levels and the risk of kidney disease in individuals with different glucose metabolism statuses. Nine machine learning models were developed using baseline CMI to validate its predictive ability for kidney disease risk. Finally, mediation causal analysis was conducted to examine whether the development of diabetes in the non-diabetic population serves as an important mediator in the relationship between CMI and kidney disease.
resultsDuring the follow-up period, a total of 173 participants (4.96%) experienced rapid decline in renal function, and 87 participants (2.50%) developed CKD. With increasing baseline CMI levels, the risk of rapid decline in renal function and CKD significantly increased. Among the various machine learning models for predicting kidney disease, logistic regression performed excellently, with AUCs exceeding 0.6, indicating the strong predictive ability of baseline CMI. For the primary outcome, multivariable logistic regression analysis showed that, in all participants, as well as in the normal glucose regulation (NGR) group and the prediabetes (Pre-DM) group, the incidence of rapid decline in renal function significantly increased across different CMI groups (P < 0.05), with trend RR values of 1.285(1.076,1.536), 1.308 (1.015, 1.685) and 1.566 (1.207, 2.031), respectively. However, this association was not observed in patients with diabetes (P for trend > 0.05). RCS analysis further indicated that higher baseline CMI levels were associated with a greater risk of rapid decline in renal function in all participants and in the non-diabetic population. A similar trend was observed for CKD. Finally, mediation causal analysis showed that the development of new-onset diabetes in the non-diabetic population may not be an important mediator in the relationship between CMI and kidney disease.
conclusionHigher baseline CMI levels were significantly linked to rapid decline in renal function and CKD in middle-aged and elderly individuals, with the relationship varying by glucose metabolism status. CMI may serve as a useful indicator for predicting kidney disease risk, especially in non-diabetic population.
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