Longitudinal changes and cumulative exposure of cardiometabolic index predict cardiovascular disease risk in middle-aged and older adults: a national prospective cohort study.

Authors

Xiaoyun Liu, Lu Yin, Xiaohua Hao

Published in

BMC cardiovascular disorders. Jun 27, 2026. Epub Jun 27, 2026.

Abstract

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality among aging populations. Single-time-point risk assessments may not reflect dynamic cardiometabolic changes. The cardiometabolic index (CMI), integrating triglyceride-to-HDL cholesterol ratio and waist-to-height ratio, reflects both atherogenic dyslipidemia and central adiposity, but its longitudinal prognostic value remains unclear. Thus, this study aims to evaluate the associations of baseline CMI, longitudinal change patterns, cumulative exposure, and absolute change (ΔCMI) with incident CVD among Chinese adults aged ≥ 45 years.
Data from the China Health and Retirement Longitudinal Study (CHARLS). Baseline analyses included 9120 participants. Longitudinal analyses included 6164 participants. CVD (including heart diseases and stroke) was ascertained during follow-up. Multivariable Cox proportional hazard models were fitted with adjustment for confounding factors.
Higher baseline CMI was independently associated with increased CVD risk with a non-linear association and an inflection point at 0.42. Compared with stable low CMI, participants with persistently high CMI showed the highest CVD risk (HR = 1.31; 95%CI: 1.14, 1.50), followed by progression from low-to-high CMI (HR = 1.23; 95%CI: 1.04, 1.46), whereas improvement from high-to-low was not associated with excess risk. Among participants with low baseline CMI, higher cumulative CMI and less favorable ΔCMI were associated with increased CVD risk. Incorporating longitudinal CMI changes modestly but significantly improved risk discrimination and reclassification beyond baseline assessment.
CMI is a dynamic, threshold-dependent predictor of CVD, independent of LDL-C and hsCRP. Longitudinal monitoring enhances risk stratification beyond single measurements.

PMID:
42365234
Bibliographic data and abstract were imported from PubMed on 28 Jun 2026.

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