Associations between Cardiometabolic Index and heart failure in adults aged ≥ 20 years: Evidence from the NHANES 1999–2018

Abstract

Background: Heart failure (HF) is a prevalent global health issue with increasing incidence due to aging populations and advancements in treatment. The Cardiometabolic Index (CMI), a new marker combining waist-to-height ratio and the triglycerides-to-HDL cholesterol ratio, has shown promise in predicting cardiovascular risks. However, the relationship between CMI and HF remains unclear, warranting further investigation. This study aims to examine the association between CMI and HF to better understand and potentially identify HF risks. Methods: This study included 101,316 participants, of whom 22,042 met the selection criteria to investigate the correlation between the CMI and heart failure. The CMI is calculated as the product of the waist-to-height ratio (WHtR) and the triglycerides-to-HDL cholesterol ratio (TG/HDL-C). Data collection involved personal interviews to gather heart failure information, with HF diagnosis based on specific questionnaire responses. Clinical and biochemical data encompassed a wide range of variables, including demographic details, health status, and biochemical markers. Statistical analyses leveraged complex survey design from the National Health and Nutrition Examination Survey (NHANES), using weighted regression and chi-square tests to compare groups and multivariate logistic regression to examine the CMI-HF relationship across adjusted models. An analysis of the threshold effect elucidated the nonlinear dynamics present between CMI and HF, incorporating subgroup analyses to investigate the interactions among variables and the Receiver Operating Characteristic (ROC) curve was employed to evaluate the diagnostic utility of CMI in comparison to Body Mass Index (BMI) for the detection of HF. Results: In this study, based on specific inclusion and exclusion criteria, 706 individuals were diagnosed with HF, representing 3.2% of the total population. The findings indicated a significant association between elevated CMI levels and an increased risk of HF (OR = 1.13; 95% CI, 1.07–1.17, p < 0.001), with each unit increment in CMI level being associated with a 13% increase in HF risk. Subgroup analyses revealed the stability of the CMI-HF relationship across various subgroups, identifying race, history of heart disease, and hypertension status as key modulators of the strength and direction of the CMI-HF association. Moreover, smooth curve fitting and threshold effect analysis demonstrated a non-linear relationship between CMI and HF, with an inflection point at a CMI level of 6.49. Below this threshold, the incidence of HF increased with rising CMI levels. Additionally, the diagnostic capabilities of CMI and Body Mass Index (BMI) in identifying HF were compared, with the area under the curve (AUC) values for CMI surpassing those for BMI, indicating a superior ability of CMI in identifying HF. Conclusion: Our research indicates that the level of CMI bears a substantial positive correlation with the incidence risk of HF, with the relationship between CMI and HF being non-linear. Additionally, the CMI is a better predictor of HF than the BMI.