The Relationship Between Cardiometabolic Index and New-Onset Diabetes in Adults Aged Over 45: A Longitudinal Analysis
Xiaoqin Chen1,2, Zhitong Li1, Tao Liu1,3
1Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Tongji Shanxi Hospital, Shanxi Academy of Medical Sciences, Taiyuan, Shanxi, China.
Abstract:
Objective: The cardiometabolic index (CMI) serves as a comprehensive indicator of metabolic risk. Recent findings indicate a potential association between CMI and the likelihood of diabetes onset. The objective of this research is to explore the correlation between initial CMI values and the occurrence of newly diagnosed diabetes mellitus in individuals aged 45 years and above in China. Methods: In this research, data were sourced from the China Health and Retirement Longitudinal Study (CHARLS). To evaluate the association between baseline CMI and the incidence of newly diagnosed diabetes, multivariate logistic regression models were employed, with adjustments made for various potential confounding factors. Additionally, stratified analyses evaluated subgroup variations, and mediation analysis explored pathways through which CMI influences diabetes risk. Results: A cohort of 4,944 participants was followed, with 786 diagnosed with new-onset diabetes. The occurrence of diabetes escalated with increasing CMI quartiles, with Q4 showing a 141% increased risk (OR 2.41, 95% CI, 1.94-3.02) in unadjusted models. This association remained significant after adjustment. Stratified analyses found that dyslipidemia modified the CMI-diabetes association. CMI, age, BMI, HbA1c, and hypertension were identified as independent predictors of new-onset diabetes. Mediation analysis revealed that HbA1c mediated 9.70% of the CMI-diabetes relationship. Conclusion: In summary, our research establishes a connection between increased levels of CMI and the onset of diabetes, suggesting its potential as a predictive tool. The findings highlight CMI's role in assessing diabetes risk and call for targeted interventions. Future research should validate these associations and explore underlying mechanisms for better prevention strategies.
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