The Impact of Cardiometabolic Index on Cardiovascular Disease Risk Among Diabetic Patients: Evidence From Two National Cohorts
Changxing Liu, Zhirui Zhang, Tianwei Meng, Boyu Wang, Chengjia Li, Ximing Yu, Xulong Zhang
Abstract
BACKGROUND: This study investigates the relationship between the Cardiometabolic Index (CMI) and cardiovascular disease (CVD) risk in diabetic populations using data from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS). Understanding the predictive role of CMI in assessing CVD risk is essential for enhancing preventive strategies in diabetic patients. METHODS: A cross-sectional analysis was conducted on diabetic participants from NHANES (2005-2018) and CHARLS (2011). CMI was calculated based on the waist-to-height ratio and the triglyceride-to-HDL-C ratio. Multivariable logistic regression models and restricted cubic spline analyses were utilised to evaluate the associations between CMI and CVD risk, adjusting for demographic and clinical covariates. RESULTS: In the NHANES cohort (n = 2044), a higher CMI was significantly associated with an increased risk of CVD after adjusting for confounding factors (OR = 2.01, p = 0.0074). Similarly, in the CHARLS cohort (n = 3964), a higher CMI was linked to an elevated CVD risk (OR = 1.45, p = 0.009). Subgroup analyses demonstrated consistent results across various age, gender and health status subgroups. The restricted cubic spline analysis revealed significant non-linear trends between CMI and CVD risk in both cohorts (p < 0.05). CONCLUSION: CMI is a robust and independent predictor of CVD risk among diabetic individuals across different populations. These findings highlight the potential clinical value of incorporating CMI into routine assessments to identify high-risk diabetic patients. Future longitudinal studies are needed to further validate these findings and explore the underlying mechanisms.