Chronic kidney disease (CKD) has significantly increased the global disease burden. Its prevalence and mortality are increasing year by year and are closely related to visceral fat accumulation. The cardiometabolic index (CMI) is a novel indicator for comprehensively evaluating visceral obesity. Several cross-sectional studies suggest a connection between CMI and CKD risk. However, this relationship has not been sufficiently examined through longitudinal cohort studies, especially in the general Chinese population.

The primary objective of this study was to investigate the relationship between CMI and CKD risk in the general Chinese population.

A prospective cohort study was conducted. Based on the established inclusion and exclusion criteria, a total of 78 115 employees who participated in the health examination organized by Kailuan Group during the years 2006—2007 were selected as research subjects. The participants were categorized into four groups according to the quartiles of CMI, Q1 group (CMI≤0.27, n=19 545), Q2 group (0.27<CMI ≤0.44, n=19 907), Q3 group (0.44<CMI≤0.72, n=19 227), and Q4 group (CMI>0.72, n=19 436). The follow-up period commenced upon completion of the 2006 annual physical examination, with subsequent follow-ups conducted biennially. The endpoint event was the occurrence of CKD or death during follow-up, with the date of either event marking the end of follow-up. For participants without incident CKD, the last physical examination date served as the follow-up endpoint, and the follow-up time concluded on December 31, 2021. The Kaplan-Meier method was used to calculate the cumulative incidence of CKD in different CMI groups, and Log-rank test was used for inter-group comparison. Cox proportional hazards regression models were used to assess the association between CMI and CKD incidence. Restricted cubic splines (at the 10th, 50th, and 90th percentiles) were used to evaluate the non-linear relationship between CMI and CKD. Subgroup analyses were performed using Cox proportional hazards regression models, and multiplicative interactions were assessed.

During the median follow-up period of 14.89 years, 20 639 participants occurred CKD events. The number of CKD patients in the first quartile group of CMI was 4 137, the second quartile group was 5 090, the third quartile group was 5 289, and the fourth quartile group was 6 123. The corresponding incidence densities were 16.61, 20.82, 22.70, and 26.83 per thousand person-years, respectively. As the level of CMI exposure rose, the cumulative incidence of CKD showed a progressive increase, and the overall discrepancy was statistically significant by the Log-Rank test (P<0.01). Cox proportional hazard regression analysis showed that elevated CMI levels significantly increased the risk of CKD. Compared with the first quartile of CMI (Q1 group), the HR (95%CI) of the second (Q2 group), third (Q3 group), and fourth quartile (Q4 group) were 1.12 (1.07-1.17), 1.16 (1.11-1.21), and 1.34 (1.28-1.40), respectively. Restricted cubic spline analysis showed that there was an inverted L-shaped curve relationship between baseline CMI level and CKD. The results of stratified analysis showed that there was only a multiplicative interaction between smoking, drinking, and CMI.

In the general Chinese population, elevated levels of CMI were significantly associated with CKD, and this association was especially strong in smokers and drinkers.