The cross-sectional association between cardiometabolic index and abdominal aortic calcification in U.S. adults: evidence from NHANES 2013–2014 - Peng, Jiawei; Wu, Jijun; Luo, Xitu; Yang, Chengyu; Wu, Shian; Liu, Wenjun; Feng, Yuanhao (Frontiers in Nutrition, 2025)
BackgroundThe cardiometabolic index (CMI) is a novel composite measure that integrates assessments of abdominal adiposity and lipid profiles. While abdominal aortic calcification (AAC) is a well-established marker of subclinical atherosclerosis and systemic metabolic dysregulation, the association between CMI and AAC remains underexplored. This cross-sectional study aimed to investigate the association between CMI and AAC.MethodsA cross-sectional study was conducted using data from the 2013 to 2014 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between CMI and AAC. A weighted multivariate logistic regression model was employed to assess the associations between triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), waist-to-height ratio (WHtR), CMI, and AAC. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the statistical association strength of each variable with AAC presence. Non-linear relationships were examined through restricted cubic spline (RCS) curve analysis. Potential influencing factors were investigated through subgroup analysis.ResultsThe average CMI of 2,675 participants was 0.98 ± 1.36. Multivariable regression showed that each one-unit increase in lnCMI was associated with a 0.19-point increase in the AAC score (β = 0.19, 95% CI: 0.03–0.35). Individuals in the highest CMI group had a 34% higher likelihood of severe AAC than those in the lowest (OR = 1.34; 95% CI, 1.09–1.66, P < 0.05). The ROC analysis showed CMI had an AUC of 0.548, comparable to TG (0.545), HDL-C (0.526), and WHtR (0.525). Although differences were not statistically significant (all P > 0.05), CMI may reflect underlying metabolic characteristics associated with AAC. A significant trend (P < 0.05) indicated a non-linear CMI-AAC relationship with gender-based interactions.ConclusionThis study demonstrated a positive correlation between CMI and AAC. However, given the cross-sectional nature of the study, causality cannot be directly inferred. These cross-sectional findings indicate a statistical association between CMI and AAC burden, suggesting potential epidemiological relevance. However, no causal inference can be drawn, but further longitudinal cohort studies are needed to confirm its potential value.