Association between cardiometabolic index and stroke risk: insights from the CHARLS cohort study

Tian Liu1, Chen Xu1, Hangjun Chen1

  • 1Department of Ultrasound, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, China.

Frontiers in Neurology
|August 18, 2025
PubMed

Insights

The Cardiometabolic Index (CMI) is linked to higher stroke risk. Elevated CMI, a measure of metabolic health, independently predicts stroke, suggesting its use in early risk assessment.

Area of Science:

  • Cardiology
  • Metabolic Health
  • Public Health

Background:

  • Stroke represents a significant global health burden.
  • The Cardiometabolic Index (CMI), integrating triglycerides, HDL cholesterol, and waist-to-height ratio, is a novel metric for metabolic disease prediction.
  • The association between CMI and stroke risk remains underexplored.

Purpose of the Study:

  • To investigate the relationship between the Cardiometabolic Index (CMI) and the risk of stroke.
  • To determine if CMI can serve as an independent predictor of stroke incidence.

Main Methods:

  • Analysis of data from 9,079 participants in the China Health and Retirement Longitudinal Study (CHARLS).
  • Stratification of participants into CMI quintiles for risk assessment.
  • Utilized Cox proportional hazard models and restricted cubic spline regression over a 7.8-year follow-up period.
  • Adjusted for potential confounding factors in the analysis.

Main Results:

  • A significant association was found between higher CMI levels and increased stroke risk.
  • A 21% increased stroke risk was observed per 1-unit increase in CMI after adjustments (HR: 1.21, 95% CI: 1.11-1.32).
  • A dose-response relationship between CMI and stroke incidence was evident, particularly above a CMI threshold of 1.6.

Conclusions:

  • Elevated CMI is a robust, independent predictor of stroke risk.
  • CMI shows potential as a valuable clinical tool for early stroke risk stratification and prevention strategies.
  • Further large-scale research is recommended to validate the clinical utility of CMI in stroke prediction.
Abstract

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