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Exploring the Relationship Between Visceral Fat and Coronary Artery Calcification Risk Using Metabolic Score for Visceral Fat (METS-VF)

Authors :
Jiun-Chi Huang
Ya-Chin Huang
Chia-Hsin Lu
Yun-Shiuan Chuang
Hsu-Han Chien
Chia-I Lin
Ming-Fang Chao
Hung-Yi Chuang
Chi-Kung Ho
Chao-Ling Wang
Chia-Yen Dai
Source :
Life, Vol 14, Iss 11, p 1399 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Background: Metabolic Score for Visceral Fat (METS-VF) is a novel indicator for estimating intra-abdominal fat, yet its connection with coronary artery calcification (CAC) remains uncharted. Our research aims to explore the novel METS-VF indicator’s link to CAC while comparing its performance against relevant anthropometric indices. Methods: This study enrolled participants who underwent health checkups and computed tomography scans for categorizing severity of CAC using the coronary artery calcium score. The METS-VF was calculated and compared with anthropometric indices in estimating the presence of CAC and different CAC severity using receiver operating characteristic curves. Results: Overall, 1217 participants (mean age 50.7 ± 9.9, 53.8% male) were included. METS-VF (odds ratio [OR], 1.506; 95% confidence interval [CI], 1.181–1.921; p = 0.001) was positively associated with the presence of CAC, even after accounting for cardiometabolic factors. Notably, METS-VF was positively associated with mild (OR, 1.450; 95% CI, 1.115–1.886; p = 0.006), moderate (OR, 1.865; 95% CI, 1.137–3.062; p = 0.014), and severe (OR, 2.316; 95% CI, 1.090–4.923; p = 0.029) CAC. Moreover, METS-VF yielded the highest area under curve (AUC) value in the estimation of the CAC presence (AUC = 0.710), mild (AUC = 0.682), moderate (AUC = 0.757), and severe (AUC = 0.807) CAC when compared with body mass index, waist circumference, visceral adiposity index, triglyceride–glucose index, and metabolic score for insulin resistance. The optimal METS-VF cut-off value was 6.4 for predicting CAC. Conclusions: METS-VF emerged as a strong independent marker for detecting CAC presence across mild, moderate, and severe CAC categories, outperforming major anthropometric indices in accurately estimating the presence of CAC and different severity of CAC.

Details

Language :
English
ISSN :
20751729
Volume :
14
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Life
Publication Type :
Academic Journal
Accession number :
edsdoj.598f11008e304663b709dd0567112ff4
Document Type :
article
Full Text :
https://doi.org/10.3390/life14111399