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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.

(1) Background. Visceral adiposity index (VAI) has been recently identified as a new cardiometabolic risk marker reflecting abdominal fat distribution and dyslipidaemia. The aim of the present paper was to evaluate the relationship between VAI, daily energy intake and metabolic syndrome (MetS) in a cohort of obese Caucasian children and adolescents, aged 8 to 15 years. (2) Methods. Consecutive Italian children and adolescents with obesity, according to World Health Organization were enrolled. Anthropometric parameters and blood pressure were measured. Fasting blood samples have been analyzed for lipids, insulin and glucose levels. MetS was diagnosed using identification and prevention of dietary- and lifestyle-induced health effects in children and infants (IDEFICS) or International Diabetes Federation (IDF) criteria according to age. Homeostatic model assessment index (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), A body shape index (ABSI) and VAI were calculated. Multivariable logistic regression analyses with sex, age and each anthropometric parameter (body mass index (BMI) z-score, ABSI, waist-to-height ratio (WHR)) or VAI was performed to predict MetS. Receiver operation curve (ROC) analysis was used to define the optimal VAI cut-off to identify MetS. Multiple regression was performed to predict the BMI z-score and VAI from daily energy intake after adjusting for age and sex. (3) Results. Six hundred and thirty-seven (313 boys and 324 girls) children and adolescents with obesity with median age 11 (interquartile range 10–13) years were included in the analysis. MetS was diagnosed in 79 patients. VAI correlated with BMI, WHR, ABSI, HOMA-IR, QUICKI, systolic blood pressure, low- and high-density lipoprotein cholesterol, triglycerides and triglycerides-to-HDL ratio (p < 0.050). Optimal VAI cut-off (AUC) values to identify MetS were 1.775 (0.774), 1.685 (0.776) and 1.875 (0.797) in the whole population, boys and girls, respectively. Energy intake was positively associated with BMI z-score but no association was found with VAI. (4) Conclusion. VAI is a promising tool to identify MetS in children and adolescents with obesity and should be used in the management of abdominal obesity together with dietary assessment.

Body shape index (ABSI) and triponderal mass index (TMI) have been recently associated with cardiovascular risk in adults. A cross-sectional study was conducted to evaluate the relationship between different anthropometric adiposity indexes and metabolic syndrome (MetS) in Caucasian obese children and adolescents. Consecutive obese children aged ≥7 years have been enrolled. Anthropometric parameters, body composition (by bioelectrical impedance), and systolic and diastolic blood pressure have been measured. Fasting blood samples have been analyzed for lipids, insulin, glucose. A multivariate logistic regression analyses, with body mass index z-score, waist to height ratio, ABSI z-score, TMI, conicity index as predictors for MetS (IDEFICS and IDF criteria according to age) has been performed. Four hundred and three (179 boys and 224 girls) obese children, aged 7–20 years, have been evaluated. When we explored the joint contribution of each anthropometric and adiposity index of interest and BMIz on the risk of MetS, we found that the inclusion of ABSIz improved the prediction of MetS compared to BMIz alone. ABSI-BMI can be a useful index for evaluating the relative contribution of central obesity to cardiometabolic risk in clinical management of obese children and adolescents.

(1) Background: Pediatric obesity is an emerging public health issue, mainly related to western diet. A cross-sectional study was conducted to explore the association between macronutrients intake and cardiometabolic risk factors in obese adolescents. (2) Methods: Ninety-three Italian obese adolescents were recruited; anthropometric parameters, body composition, glucose and lipid metabolism profiles were measured. Macronutrients intake was estimated by a software-assisted analysis of a 120-item frequency questionnaire. The association between macronutrients and cardiometabolic risk factors was assessed by bivariate correlation, and multiple regression analysis was used to adjust for confounders such as age and sex. (3) Results: By multiple regression analysis, we found that higher energy and lower carbohydrate intakes predicted higher body mass index (BMI) z-score, p = 0.005, and higher saturated fats intake and higher age predicted higher HOmeostasis Model Assessment of insulin resistance (HOMA-IR) and lower QUantitative Insulin-sensitivity ChecK (QUICK) index, p = 0.001. In addition, a saturated fats intake p = 0.011. (4) Conclusions: Higher energy intake and lower carbohydrate dietary intake predicted higher BMI z-score after adjustment for age and sex. Higher total and saturated fats dietary intakes predicted insulin resistance, even after adjustment for confounding factors. A dietary pattern including appropriate high-quality carbohydrate and reduced saturated fat intakes could result in reduced cardiometabolic risk in obese adolescents.

Childhood obesity represents an important public health issue worldwide and is strongly linked to metabolic alterations such as hypertension, insulin resistance, and dyslipidemia. The constellation of these conditions is commonly known as Metabolic Syndrome (MetS). Metabolic syndrome is not just a simple cluster of metabolic complications due to excess of adipose tissue, but is considered a risk factor for cardiovascular diseases. Evidence from several human and animal studies suggests that environmental and nutritional exposure during pregnancy may affect the newborn development and future health through epigenetic changes, playing a potential role in determining obesity and obesity-related complications. Understanding how nutritional epigenetic mechanisms contribute to the “transgenerational risk” for obesity and metabolic dysfunction is crucial in order to develop early prevention strategies for children’s health. Nutrigenetics is the science that studies the role of nutrients in gene expression. Long Chain Polyunsaturated Fatty Acids (LCPUFAs) are known for their health benefits, especially in relation to their ability to modulate inflammation and improve some obesity-associated comorbidities, mainly by decreasing plasma triglycerides. Recent nutrigenetic research is focusing on the potential role of LCPUFAs in influencing epigenetic markers. In this review, we present the most recent updates about the possible interaction between n-3 LCPUFAs and epigenetic pathways in metabolic syndrome. Literature from MEDLINE® and the Cochrane database between May 2005 and December 2018 has been scanned.

Background: Metabolic syndrome (MS) is closely linked to obesity; however, not all individuals with obesity will develop obesity-related complications and a metabolically healthy obesity (MHO) group is also described. Objective: To perform a multivariate analysis (MVA) of the anthropometric and biochemical data in pediatric patients with obesity to reveal a "phenotype" predictive for MS. Methods: We analyzed 528 children with obesity (OB) and 119 normal-weight pediatric patients (NW). Adiposity indices were recorded, and MS was detected. MVA was performed. Results: Analysis of the structure of correlation of the variables showed that the variables of waist circumference (WC), body mass index (BMI), and estimated fat mass (eFM) were positively correlated with each other as a whole. In addition, the variables of the triglycerides (TG), triglyceride–glucose (TyG) index, and visceral adiposity index were positively correlated with each other as a whole, although none were correlated with the variables of BMI z-score, waist-to-height ratio, WC, eFM, or weight. The variables that related to insulin resistance (IR) and dyslipidemia were crucial for the early stratification of patients at risk of MS. Conclusions: Independently of body weight, IR, dyslipidemia, hypertriglyceridemia, and fat distribution seem to be the strongest MS risk factors. The early detection of and intervention in these modifiable risk factors are useful to protect children's health. [ABSTRACT FROM AUTHOR]

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/bodymass-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. [ABSTRACT FROM AUTHOR]

(1) Background. Visceral adiposity index (VAI) has been recently identified as a new cardiometabolic risk marker reflecting abdominal fat distribution and dyslipidaemia. The aim of the present paper was to evaluate the relationship between VAI, daily energy intake and metabolic syndrome (MetS) in a cohort of obese Caucasian children and adolescents, aged 8 to 15 years. (2) Methods. Consecutive Italian children and adolescents with obesity, according to World Health Organization were enrolled. Anthropometric parameters and blood pressure were measured. Fasting blood samples have been analyzed for lipids, insulin and glucose levels. MetS was diagnosed using identification and prevention of dietary- and lifestyle-induced health effects in children and infants (IDEFICS) or International Diabetes Federation (IDF) criteria according to age. Homeostatic model assessment index (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), A body shape index (ABSI) and VAI were calculated. Multivariable logistic regression analyses with sex, age and each anthropometric parameter (body mass index (BMI) z-score, ABSI, waist-to-height ratio (WHR)) or VAI was performed to predict MetS. Receiver operation curve (ROC) analysis was used to define the optimal VAI cut-off to identify MetS. Multiple regression was performed to predict the BMI z-score and VAI from daily energy intake after adjusting for age and sex. (3) Results. Six hundred and thirty-seven (313 boys and 324 girls) children and adolescents with obesity with median age 11 (interquartile range 10–13) years were included in the analysis. MetS was diagnosed in 79 patients. VAI correlated with BMI, WHR, ABSI, HOMA-IR, QUICKI, systolic blood pressure, low- and high-density lipoprotein cholesterol, triglycerides and triglycerides-to-HDL ratio (p < 0.050). Optimal VAI cut-off (AUC) values to identify MetS were 1.775 (0.774), 1.685 (0.776) and 1.875 (0.797) in the whole population, boys and girls, respectively. Energy intake was positively associated with BMI z-score but no association was found with VAI. (4) Conclusion. VAI is a promising tool to identify MetS in children and adolescents with obesity and should be used in the management of abdominal obesity together with dietary assessment. [ABSTRACT FROM AUTHOR]

(1) Background: Pediatric obesity is an emerging public health issue, mainly related to western diet. A cross-sectional study was conducted to explore the association between macronutrients intake and cardiometabolic risk factors in obese adolescents. (2) Methods: Ninety-three Italian obese adolescents were recruited; anthropometric parameters, body composition, glucose and lipid metabolism profiles were measured. Macronutrients intake was estimated by a software-assisted analysis of a 120-item frequency questionnaire. The association between macronutrients and cardiometabolic risk factors was assessed by bivariate correlation, and multiple regression analysis was used to adjust for confounders such as age and sex. (3) Results: By multiple regression analysis, we found that higher energy and lower carbohydrate intakes predicted higher body mass index (BMI) z-score, p = 0.005, and higher saturated fats intake and higher age predicted higher HOmeostasis Model Assessment of insulin resistance (HOMA-IR) and lower QUantitative Insulin-sensitivity ChecK (QUICK) index, p = 0.001. In addition, a saturated fats intake <7% was associated with normal HOMA-IR, and a higher total fats intake predicted a higher HOMA of percent β-cell function (HOMA-β), p = 0.011. (4) Conclusions: Higher energy intake and lower carbohydrate dietary intake predicted higher BMI z-score after adjustment for age and sex. Higher total and saturated fats dietary intakes predicted insulin resistance, even after adjustment for confounding factors. A dietary pattern including appropriate high-quality carbohydrate and reduced saturated fat intakes could result in reduced cardiometabolic risk in obese adolescents. [ABSTRACT FROM AUTHOR]

Childhood obesity represents an important public health issue worldwide and is strongly linked to metabolic alterations such as hypertension, insulin resistance, and dyslipidemia. The constellation of these conditions is commonly known as Metabolic Syndrome (MetS). Metabolic syndrome is not just a simple cluster of metabolic complications due to excess of adipose tissue, but is considered a risk factor for cardiovascular diseases. Evidence from several human and animal studies suggests that environmental and nutritional exposure during pregnancy may affect the newborn development and future health through epigenetic changes, playing a potential role in determining obesity and obesity-related complications. Understanding how nutritional epigenetic mechanisms contribute to the "transgenerational risk" for obesity and metabolic dysfunction is crucial in order to develop early prevention strategies for children's health. Nutrigenetics is the science that studies the role of nutrients in gene expression. Long Chain Polyunsaturated Fatty Acids (LCPUFAs) are known for their health benefits, especially in relation to their ability to modulate inflammation and improve some obesity-associated comorbidities, mainly by decreasing plasma triglycerides. Recent nutrigenetic research is focusing on the potential role of LCPUFAs in influencing epigenetic markers. In this review, we present the most recent updates about the possible interaction between n-3 LCPUFAs and epigenetic pathways in metabolic syndrome. Literature from MEDLINE® and the Cochrane database between May 2005 and December 2018 has been scanned. [ABSTRACT FROM AUTHOR]