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Association between cardiometabolic index and congestive heart failure among US adults: a cross-sectional study
1Department of Clinical Nutrition, Tongde Hospital of Zhejiang Province, Hangzhou, China.
Insights
Obesity increases congestive heart failure (CHF) risk. The cardiometabolic index (CMI) and CMI-age, a novel indicator, show significant correlations with CHF, with CMI-age demonstrating superior predictive ability for early detection.
Area of Science:
- Cardiology and Public Health
Background:
- Obesity is a known risk factor for congestive heart failure (CHF).
- Limited data exist on the association between visceral obesity and CHF risk.
- The cardiometabolic index (CMI) has been proposed as a marker for cardiometabolic risk.
Purpose of the Study:
- To explore the relationship between CHF and the cardiometabolic index (CMI).
- To investigate the association of CMI and a novel CMI-age index with CHF risk.
- To evaluate the predictive performance of CMI and CMI-age for CHF.
Main Methods:
- Cross-sectional study using NHANES data (2011-2018) with 9,008 participants.
- CMI calculated as triglyceride/HDL-C × weight-to-height ratio (WHtR).
- CMI-age calculated as CMI × age.
- Logistic regression and ROC curve analysis used to assess correlations and predictive ability.
Main Results:
- The overall prevalence of CHF was 3.31%.
- Both CMI and CMI-age showed positive correlations with CHF risk in crude and adjusted models.
- CMI-age demonstrated a significantly higher area under the ROC curve (0.697) compared to CMI (0.610) in predicting CHF.
Conclusions:
- CMI and CMI-age are independently correlated with CHF risk.
- CMI-age offers valuable insights for CHF prevention and management.
- CMI-age can be an effective tool for identifying CHF in primary care and resource-limited settings.
Background:
The risk of congestive heart failure (CHF) is significantly affected by obesity. However, data on the association between visceral obesity and the risk of CHF remain limited. We explored the relationship between CHF and cardiometabolic index (CMI).
Methods:
Drawing from the National Health and Nutrition Examination Survey (NHANES) for 2011-2018, we enrolled 9,008 participants in a cross-sectional study. We calculated the CMI as triglyceride (TG)/high density lipid-cholesterol (HDL-C) × weight-to-height ratio (WHtR), and CMI-age as CMI × age. Then, we analyzed CMI and CMI-age as categorical and continuous variables to assess its correlation with CHF. To assess the relationships of CMI and CMI-age with CHF, we used multiple logistic regression models and performed subgroup analysis. To examine the predictive ability of CMI and CMI-age on patients with CHF, we used receiver operating characteristic (ROC) curves.
Results:
The overall prevalence of CHF was 3.31%. The results revealed significant differences in demographic data, comorbidities, lifestyle variables, standing height, BMI, WC, WHtR, TG, and HDL-C among the four groups classified by CMI quartile and CMI-age quartile. When indicators were analyzed as continuous variables, CMI and CMI-age showed positive correlations with CHF in both the crude and adjusted models (all P < 0.05). When indicators were analyzed as categorical variables, it was found that in all four models, the ORs of group Q4 was significantly different compared to Q1 (all P < 0.05), suggesting the risk of CHF is significantly increased with higher CMI, and CMI-age. The associations of CMI and CMI-age with CHF were similar in all stratified populations (P for interaction > 0.05). The areas under the ROC curve (AUCs) of CMI and CMI-age in predicting CHF were 0.610 (95% CI, 0.578-0.642) and 0.697 (95% CI, 0.668-0.725) separately, suggesting that CMI-age was significantly better than the CMI in predicting CHF (P < 0.001).
Conclusions:
Both CMI and CMI-age were independently correlated with the risk for CHF. These results suggested that the CMI-age, which provides new insights into the prevention and management of CHF. CMI-age could serve as effective tools to identify CHF during primary care examinations and in medically resource-limited areas.
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