Association of Cardiometabolic Index With Cardiometabolic Disease Prevalence and Mortality: Evidence From Two National Surveys.

Abstract

Background: The cardiometabolic index (CMI), a composite marker derived from the product of waist-to-height ratio and triglyceride-to- high-density lipoprotein cholesterol ratio, has emerged as a potential indicator of metabolic risk. However, the prognostic value of the CMI across diverse populations and the continuum from cardiometabolic disease prevalence to mortality remains poorly characterised.

Method: This study integrated data from two nationally representative datasets: 17,922 adults from the US National Health and Nutrition Examination Survey (NHANES; 1999-2018; longitudinal) and 9,313 adults from the China Health and Retirement Longitudinal Study (CHARLS; 2011; cross-sectional). Multivariate Cox regression models estimated hazard ratios (HRs) for mortality, whereas logistic regression models estimated odds ratios (ORs) for disease prevalence. Restricted cubic splines (RCSs) were used to evaluate dose-response relationships.

Results: In the NHANES cohort, elevated CMI was significantly associated with increased risks of all-cause mortality (HR 1.35; 95% confidence interval [CI] 1.26-1.44), cardiovascular disease (CVD) mortality (HR 1.30; 95% CI 1.17-1.45), and diabetes mortality (HR 1.91; 95% CI 1.56-2.34). Age significantly modified these associations (p for interaction <0.001), with stronger predictive power observed in adults aged <60 years. In the CHARLS cohort, CMI was strongly associated with prevalent CVD (OR 1.06; 95% CI 1.01-1.11) and diabetes (OR 1.66; 95% CI 1.56-1.77). RCS analyses revealed a nonlinear threshold effect for all-cause mortality in the US population and a steep linear increase in diabetes prevalence in the Chinese population.

Conclusions: CMI is a robust, low-cost indicator for predicting mortality in US adults and cardiometabolic disease burden in Chinese adults. Its greater predictive utility in younger populations supports its clinical implementation for early-onset risk stratification and targeted prevention globally.