Assessment of Epicardial Fat in Children: Its Role as a Cardiovascular Risk Factor and How It Is Influenced by Lifestyle Habits
Abstract
:1. Introduction
2. Methods
3. Assessment of Epicardial Adipose Tissue
3.1. Transthoracic Echocardiography
3.2. Magnetic Resonance Imaging (MRI)
3.3. Computed Tomography
4. Epicardial Fat Tissue as a Marker for Cardiovascular Risk in Pediatric Age
4.1. Children with Obesity
4.2. Children with Undernutrition
5. The Impact of Lifestyle Habits and Lifestyle Intervention on Epicardial Adipose Tissue
5.1. Unhealthy Eating Habits
5.2. Sedentary Life and Exercise
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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First Author, Year of Publication | Study Type | Population | Main Result | References |
---|---|---|---|---|
Ozdemir et al. (2010) | Cross-sectional study | 106 obese and 62 lean children (aged 11–14 years) | Increased thickness of EAT in obese children (6.99 ± 1.45 mm vs. 3.93 ± 0.68 mm in lean subjects). Positive correlation between EAT thickness and BMI, left atrial diameter and left ventricular mass. | [9] |
Schusterova et al. (2014) | Observational study | 25 overweight and obese subjects and 24 lean controls (aged 10–16 years) | In obese children, EAT thickness is correlated with an unfavorable cardiometabolic profile; it is positively with blood pressure, triglycerides, uric acid, apoprotein B, and hepatic enzymes and negatively correlated with HDL levels. EAT is a more accurate metabolic predictor than waist circumference but is not a stronger indicator than BMI. | [22] |
Mazur et al. (2010) | Cross-sectional observational study | 52 obese children and 54 controls (aged 11–15 years) | No statistically significant correlation was found between EAT thickness and the HOMA index. Similarly, there was no significant difference in EATT between obese children with or without metabolic syndrome. | [27] |
Barbaro et al. (2016) | Longitudinal pilot study | 73 prepuberal children (average age of 8.22 years) | For patients with a weight >90th percentile and a family history of metabolic syndrome risk factors, EAT values correlate positively with anthropometric parameters and metabolic markers (triglycerides, insulin, HOMA index) and negatively with HDL levels. | [28] |
Abaci et al. (2009) | Cross-sectional study | 46 obese children and 30 lean controls (10.2 ± 2.5 years of age) | No significant correlation was observed between EAT and insulin resistance (r = 0.170, p = 0.253), but there was a significant correlation between EAT and BMI, age, and IMT. | [31] |
Güneş et al. (2020) | Prospective and cross-sectional study | 94 obese patients (aged 8–18 year) | A significant association was established between EAT and insulin resistance (IR). The identified optimal cut-off value for EAT to predict IR was >3.85 mm (92.5% specificity and 68.5% sensitivity) | [30] |
Schweighofer et al. (2023) | Prospective case–control study | 72 children and adolescents with normal BMI (aged 12–19 years) | Hypertensive patients have a higher volume (16.5 ± 1.9 cm3 and 10.9 ± 1.5 cm3) and thickness (0.8 ± 0.3 cm and 0.4 ± 0.1 cm) of EAT compared to their healthy peers. The volume of EAT might be a potential predictor of arterial hypertension in children. | [35] |
Elshorbagy et al. (2016) | Prospective cohort study | 60 obese adolescents and 25 controls (aged 8–16 years) | EAT increased in MS patients compared to the control group. EATT emerged as a predictor for carotid IMT. | [33] |
Bedir et al. (2013) | Cross-sectional study | 138 obese adolescents and 63 lean subjects (aged 9–18 years) | Close association between EAT and carotid IMT, along with early cardiac dysfunction, in obese adolescents with MS. Echocardiographic EAT appears to be a more effective indicator of premature atherosclerosis than waist circumference in MS patients. | [36] |
Calcaterra et al. (2018) | Cross-sectional study | 32 disabled patients (12.4 ± 6.3 years) | EAT values in neurologically impaired children were higher than those in the control group (p = 0.02). EAT showed correlations with gender, age, pubertal stage, and WHtR. Significantcorrelations were found between EAT levels and abnormal triglycerides and HOMA-IR. | [38] |
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Calcaterra, V.; Cena, H.; Garella, V.; Loperfido, F.; Chillemi, C.; Manuelli, M.; Mannarino, S.; Zuccotti, G. Assessment of Epicardial Fat in Children: Its Role as a Cardiovascular Risk Factor and How It Is Influenced by Lifestyle Habits. Nutrients 2024, 16, 420. https://doi.org/10.3390/nu16030420
Calcaterra V, Cena H, Garella V, Loperfido F, Chillemi C, Manuelli M, Mannarino S, Zuccotti G. Assessment of Epicardial Fat in Children: Its Role as a Cardiovascular Risk Factor and How It Is Influenced by Lifestyle Habits. Nutrients. 2024; 16(3):420. https://doi.org/10.3390/nu16030420
Chicago/Turabian StyleCalcaterra, Valeria, Hellas Cena, Vittoria Garella, Federica Loperfido, Claudia Chillemi, Matteo Manuelli, Savina Mannarino, and Gianvincenzo Zuccotti. 2024. "Assessment of Epicardial Fat in Children: Its Role as a Cardiovascular Risk Factor and How It Is Influenced by Lifestyle Habits" Nutrients 16, no. 3: 420. https://doi.org/10.3390/nu16030420
APA StyleCalcaterra, V., Cena, H., Garella, V., Loperfido, F., Chillemi, C., Manuelli, M., Mannarino, S., & Zuccotti, G. (2024). Assessment of Epicardial Fat in Children: Its Role as a Cardiovascular Risk Factor and How It Is Influenced by Lifestyle Habits. Nutrients, 16(3), 420. https://doi.org/10.3390/nu16030420