Association between cardiometabolic index and myocardial Infarction: based on NHANES database.

Abstract

Background: The cardiometabolic index (CMI) combines abdominal obesity and abnormal blood lipid indices, representing a good predictive indicator of risk in cardiovascular diseases (CVDs). However, the association between CMI and myocardial infarction (MI) is not clear.

Objective: The present project was designed to explore the linkage between CMI and MI.

Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 were employed in this project, with CMI as the independent variable and MI as the dependent variable. Weighted logistic regression was applied in the association analysis between CMI and MI. Restricted cubic spline (RCS), subgroup analysis, and interaction tests were employed to elucidate the non-linear relationship and stability of CMI and MI's link. Moreover, to verify the robustness of the results, sensitivity analysis was conducted, with the MI status of subjects taking lipid-lowering drugs as the outcome variable.

Results: A total of 13,923 participants were gathered in this project, with 605 cases of MI, accounting for 3.5%. In the weighted logistic regression model, a positive linkage was observed between CMI and the risk of MI (OR: 1.41, 95% CI: 1.18-1.68, p < 0.001). The RCS curves indicated a linear relationship between CMI and MI (P-non-linear = 0.146). Subgroup analysis manifested that CMI was positively linked with MI risk in males, individuals with BMI > 30kg/m², and alcohol drinkers (p < 0.05). In addition, the interaction results demonstrated that there was no heterogeneity in the association between CMI and MI risk in the subgroups (p > 0.05). The sensitivity analysis showed that after adjusting for all confounding factors in the model, there was still a significant positive correlation (p < 0.01) between CMI and MI in the population taking lipid-lowering drugs.

Conclusion: There is a significant positive linkage of CMI with MI risk, which is particularly significant in males, those with a BMI greater than 30 kg/m², and those who have drinking habits. Even after considering the impact of lipid-lowering drug therapy, the positive correlation between CMI and MI remains robust, supporting CMI as a promising tool for assessing MI risk and guiding clinical prevention. Further research is required to probe into the application of CMI in different populations and its role in the prevention of CVDs.