Fat mass and vascular health in overweight/obese children

Licenziati, Maria Rosaria; Iannuzzo, Gabriella; Morlino, D.; Campana, G; Renis, Maurizio; Valerio, Giuliana

doi:10.1016/j.numecd.2020.12.017

Cited by 7 publications

(10 citation statements)

References 35 publications

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“…The eFM has been recently associated with increased intima media thickness and hypertrophy of the carotid wall, demonstrating the significant and independent role played by fat mass in the development of vascular abnormalities and highlighting the importance of treating this condition to preserve vascular health [22]. A high percentage of FM in obese children has also been associated with elevated BP levels [60,61], in particular systolic BP [61], especially in girls and older-aged (16-17 years old) children [61,62], and with cardiometabolic risk factors, such as IR, LDL, TG, and total cholesterol levels [63].…”

Section: Discussionmentioning

confidence: 99%

“…The eFM was calculated using the following formula: FM = weight − exp(0.3073 × height 2 −10.0155 × d-growth-standards/standards/body-mass-index-for-age-bmi-for-age weight−1 +0.004571 × weight − 0.9180 × ln(age) + 0.6488 × age 0.5 + 0.04723 × male + 2.8055) [22] (exp = exponential function, ln = natural logarithmic transformation, score 1 if child was of black (BA), south Asian (SA), other Asian (AO), or other (other) ethnic origin and score 0 if not, ln = natural logarithmic transformation, male = 1, female = 0).…”

Section: Clinical Evaluationmentioning

confidence: 99%

“…More recently, a new prediction model based on height, weight, age, sex, and ethnicity has been proposed to predict FM in children, and has obtained a high accuracy compared with BMI [21,22]. It is a simple method based on auxological parameters that does not require instruments to assess body composition [21].…”

Section: Introductionmentioning

confidence: 99%

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Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity

et al. 2021

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Body mass index (BMI), usually used as a body fatness marker, does not accurately discriminate between amounts of lean and fat mass, crucial factors in determining metabolic syndrome (MS) risk. We assessed the predictive ability of the estimate of FM (eFM) calculated using the following formula: FM = weight − exp(0.3073 × height2 − 10.0155 ×d-growth-standards/standards/body-mass-index-for-age-bmi-for-age weight− 1 + 0.004571 × weight − 0.9180 × ln(age) + 0.6488 × age0.5 + 0.04723×male + 2.8055) (exp = exponential function, score 1 if child was of black (BA), south Asian (SA), other Asian (AO), or other (other) ethnic origin and score 0 if not, ln = natural logarithmic transformation, male = 1, female = 0), to detect MS in 185 prepubertal obese children compared to other adiposity parameters. The eFM, BMI, waist circumference (WC), body shape index (ABSI), tri-ponderal mass index, and conicity index (C-Index) were calculated. Patients were classified as having MS if they met ≥ 3/5 of the following criteria: WC ≥ 95th percentile; triglycerides ≥ 95th percentile; HDL-cholesterol ≤ 5th percentile; blood pressure ≥ 95th percentile; fasting blood glucose ≥ 100 mg/dL; and/or HOMA-IR ≥ 97.5th percentile. MS occurred in 18.9% of obese subjects (p < 0.001), with a higher prevalence in females vs. males (p = 0.005). The eFM was correlated with BMI, WC, ABSI, and Con-I (p < 0.001). Higher eFM values were present in the MS vs. non-MS group (p < 0.001); the eFM was higher in patients with hypertension and insulin resistance (p < 0.01). The eFM shows a good predictive ability for MS. Additional to BMI, the identification of new parameters determinable with simple anthropometric measures and with a good ability for the early detection of MS, such as the eFM, may be useful in clinical practice, particularly when instrumentation to estimate the body composition is not available.

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Section: Discussionmentioning

confidence: 99%

Section: Clinical Evaluationmentioning

confidence: 99%

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Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity

et al. 2021

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“…Even though these parameters present serious limitations, particularly in children, because they do not accurately discriminate between lean and fat mass, they are considered good markers of metabolic and cardiovascular comorbidities [5,6]. Recently, new indexes of obesity, such as triponderal mass index (TMI) [7] and non-linear equations to estimate the fat mass [8], have been proposed as markers of cardiovascular risk. Additionally, ultrasonography may be used as a reliable method to measure subcutaneous and visceral fat for predicting health risk [9] related to obesity.…”

Section: Introductionmentioning

confidence: 99%

Interaction between Autonomic Regulation, Adiposity Indexes and Metabolic Profile in Children and Adolescents with Overweight and Obesity

et al. 2021

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Early obesity predicts initial modifications in cardiac and vascular autonomic regulation. The aim of this study was to assess the possible interaction between non-invasive measures of autonomic cardiovascular control and peripheral endothelium regulation in children with overweight and obesity. We involved 114 young subjects (77M/37F, 12.7 ± 2.2 years) with normal weight (NW, n = 46,) to overweight or obesity (OB, n = 68). Multivariate statistical techniques utilizing a collection of modern indices of autonomic regulation, adiposity indexes and metabolic profile were employed. Resting values show substantial equivalence of data. Conversely, blood pressure variance is greater in NW/OB groups. The correlation matrix between major autonomic and metabolic/hemodynamic variables shows a clustered significant correlation between homogeneous indices. A significant correlation between metabolic indices and endothelial and autonomic control, mostly in its vascular end, was recorded. Particularly, the alpha index is significantly correlated with triglycerides (r = −0.261) and endothelial indices (RHI, r = 0.276). Children with obesity show a link between indices of autonomic and endothelial function, fat distribution and metabolic profile. The optimization of autonomic control, for instance by exercise/nutrition interventions, could potentially prevent/delay the occurrence of structural vascular damage leading to reduced cardiovascular health.

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“…BMI is usually considered a good marker of the cardiometabolic risk [ 29 ]. Recently, Licenziati et al reported [ 42 ] that fat mass, assessed by using a new prediction model based on simple anthropometric measures, is associated with subclinical cardiovascular alterations. This model may result useful in preliminarily identifying the cardiovascular risk factors in the early developmental stages of the children, i.e., ahead adulthood, when these conditions become harshly reversible.…”

Section: Discussionmentioning

confidence: 99%

“Fitness and Fatness” in Children and Adolescents: An Italian Cross-Sectional Study

et al. 2021

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Children with obesity tend to have lower level of physical activity compared to non-obese peers. In fact, sedentary behaviors are prevalent in obese children causing difficulties to perform motor tasks and engaging in sport activities. This, in turn, has direct repercussions on adiposity and related comorbidities. The aim of the study was to investigate several components of fitness and their relationship with the degree of fatness in children. We considered 485 Italian schoolchildren (9.5 ± 1.12 years). BMI and prediction modelling outputs of fat mass were employed as markers of body fatness. Physical fitness (PF) was assessed by the 9-item test battery (explosive power, leg muscle power, arm muscle power, upper body power, coordination, agility, speed and endurance). Differences between groups in the PF tests (p < 0.05) were noted. A similar pattern was reflected in both genders. The relationship between anthropometrics’ characteristics and PF tests showed that weight and fat mass had a high level of correlation with different PF tests. Our findings highlight the importance of investigating the degree of fatness in relation with different components of fitness, in children and adolescents. This combination of proxies may cover an unexpectedly helpful screening of the youth population, for both health and performance.

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Fat mass and vascular health in overweight/obese children

Cited by 7 publications

References 35 publications

Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity

Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity

Interaction between Autonomic Regulation, Adiposity Indexes and Metabolic Profile in Children and Adolescents with Overweight and Obesity

“Fitness and Fatness” in Children and Adolescents: An Italian Cross-Sectional Study

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