Association of cardiometabolic index with prevalence of stroke, all-cause and cardiovascular mortality: a prospective cohort study

BACKGROUND: The association of the Cardiometabolic Index for stroke risk remains insufficiently explored. This study aimed to examine the associations of the CMI with the prevalence of stroke, as well as all-cause and cardiovascular mortality. METHODS: This prospective cohort study employed a multistage, stratified, and cluster random sampling method to recruit 147,897 participants aged 40 years or older from 2017 to 2023. Multivariable logistic regression, Cox regression analysis and restricted cubic splines (RCS) were utilized to examine the associations of CMI with prevalence of stroke, all-cause mortality, and CVD mortality. RESULTS: The prevalence of stroke was 5.4%, with ischemic stroke at 4.8% and hemorrhagic stroke at 0.7%. Over a median follow-up of 4.75 years, 7,150 all-cause deaths, 3,701 cardiovascular deaths, and 1,598 stroke-related deaths were recorded. Multivariable logistic regression analysis demonstrated that, compared to the lowest quartile (Q1), individuals in the highest CMI quartile (Q4) had significantly higher odds of overall stroke (OR 1.54, 95% CI 1.44-1.65), ischemic stroke (OR 1.59, 95% CI 1.47-1.71), and hemorrhagic stroke (OR 1.25, 95% CI 1.04-1.51). Similarly, multivariable Cox regression analysis showed that individuals in Q4, relative to those in Q1, had a 13% increased risk of all-cause mortality (HR 1.13, 95% CI 1.05-1.21), a 21% increased risk of CVD mortality (HR 1.21, 95% CI 1.10-1.34), and a 32% increased risk of stroke mortality (HR 1.32, 95% CI 1.14-1.53).Restricted cubic spline analyses confirmed significant overall and non-linear associations between CMI and both stroke prevalence and mortality (P-overall < 0.05, P-non-linear < 0.05). CONCLUSIONS: CMI was significantly associated with stroke prevalence, all-cause mortality, and cardiovascular as well as stroke-specific mortality. These findings indicate that CMI could serve as a useful tool for identifying high-risk individuals, potentially informing targeted preventive strategies.