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Background: Normal weight obesity (NWO), which is defined by the excess of body fat in normal weight individuals, has been neglected among adolescents, due to their normal weight and young age. Few studies were carried out on the topic with adolescents., Objective: To analyze whether the NWO is associated with cardiometabolic risk factors in adolescents., Subjects/methods: Cross-sectional study, with 506 normal weight adolescents aged 10-19 years, selected in schools in Brazil. Weight, height, waist circumference (WC) and neck circumference were obtained and the body mass index (BMI) and waist/height ratio (WHR) were calculated. Body composition analysis was performed using dual-energy X-ray absorptiometry. The clinical evaluation included lipid and glycid profile, platelets, leukocytes, lymphocytes, monocytes, uric acid and blood pressure, as well as the presence of metabolic syndrome (MS) and its components. NWO was defined by the presence of normal weight, according to BMI for age, and excess body fat (≥25% and ≥30% in males and females, respectively). Logistic regression models were used to analyze associations between normal weight adolescents with and without the NWO phenotype., Results: NWO associated positively with abdominal obesity, analyzed through WC (OR = 1.36;95%CI = 1.27-1.47), WHR (OR = 25.89;95%CI = 10.43-64.26) and android fat (OR = 1.49;95%CI = 1.36-1.63); insulin resistance (OR = 4.09;95%CI = 1.72-9.70), hyperinsulinemia (OR = 3.83;95%CI = 1.50-9.76) and the highest values of the triglycerides-glycemia index (OR = 4.28;95%CI = 1.21-15.08); uric acid (OR = 1.81;95%CI = 1.29-2.55), as well as the changes in LDL (OR = 3.39;95%CI = 1.47-7.81), total cholesterol (OR = 2.77;95%CI = 1.22-6.29), and in at least one (OR = 1.87;95%CI = 1.04-3.37) or two (OR = 6.61;95%CI = 1.45-30.19) components of MS., Conclusion: NWO is associated with the presence of cardiometabolic risk factors in adolescents., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Background and Aim: Hyperuricemia in adults is associated with cardiovascular risk factors. However, there is less data regarding this association in children and adolescents. Our purpose was to determine association between serum uric acid (SUA) and cardiovascular risk., Methods and Results: A fasting blood sample was collected from 1750 participants aged 6-17 years enrolled in a social project and public schools in Espírito Santo, Brazil. Internal cut-offs were generated to define high SUA (≥90th percentile of SUA concentration for sex and age group). Body mass index percentile (pBMI), body fat percentage (BFP) and muscle mass were determined by bioimpedance. Data are given as mean ± standard deviation. High SUA was associated with overweight/obesity (OR 3.7 CI 95% 2.7-5.0), high waist circumference (WC) (OR 3.9 CI 95% 2.9-5.4), low HDL (OR 2.0 CI 95% 1.5-2.8), high blood pressure (BP) (OR 1.8 CI 95% 1.1-3.2), high BFP (OR 4.1 CI 95% 2.7-6.4), metabolic syndrome (MetS) (OR 3.6 CI 95% 1.8-7.1) and insulin resistance (OR 1.7 CI 95% 1.1-2.7). Individuals in the fourth quartile of SUA, compared to those in the first quartile, showed higher age, pBMI, WC, BFP and muscle mass. Using a reference value of 5.5 mg/dL, the prevalence of hyperuricemia in the sample was 10.3% (CI 95% 8.9-11.7%)., Conclusion: Higher SUA values are associated with higher cardiovascular risk in childhood and adolescence. The main cardiovascular risk factors associated with hyperuricemia were overweight/obesity, high WC, dyslipidemia, high BFP, high BP, insulin resistance and MetS., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Objective: Given the importance of incorporating simple and low-cost tools into the pediatric clinical setting to provide screening for insulin resistance, the present study sought to investigate whether waist-to-height ratio is comparable to biochemical markers for the discrimination of insulin resistance in children and adolescents., Methods: This cross-sectional study involved students from nine public schools. In total, 296 children and adolescents of both sexes, aged 8-14 years, composed the sample. Waist-to-height ratio, triglycerides/glucose index, and triglycerides-to-HDL-C ratio were determined according to standard protocols. Insulin resistance was defined as homeostatic model assessment for insulin resistance with cut-off point ≥ 3.16., Results: Age, body mass index, frequency of overweight, waist circumference, waist-to-height ratio, insulin, glucose, homeostatic model assessment for insulin resistance, triglycerides, triglycerides/glucose index, and triglycerides-to-HDL-C were higher among insulin resistant boys and girls. Moderate correlation of all indicators (waist-to-height ratio, triglycerides/glucose index, and triglycerides-to-HDL-C ratio) with homeostatic model assessment for insulin resistance was observed for both sexes. The areas under the receiver operational characteristic curves ware similar between waist-to-height ratio and biochemical markers., Conclusion: The indicators provided similar discriminatory power for insulin resistance. However, taking into account the cost-benefit ratio, we suggest that waist-to-height ratio may be a useful tool to provide screening for insulin resistance in pediatric populations., (Copyright © 2018 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.)

Objective: To determine the prevalence of metabolic syndrome (MS) and the hypertriglyceridemic waist phenotype (HW) in a representative adolescent sample; as well as to establish which anthropometric indicator better identifies MS and HW, according to gender and adolescent age., Methods: This cross sectional study had the participation of 800 adolescents (414 girls) from 10-19 years old. Anthropometric indicators (body mass index, waist perimeter, waist/stature ratio, waist/hip ratio, and central/peripheral skinfolds) were determined by standard protocols. For diagnosis of MS, the criteria proposed by de Ferranti et al. (2004) were used. HW was defined by the simultaneous presence of increased waist perimeter (>75th percentile for age and sex) and high triglycerides (>100mg/dL). The ability of anthropometric indicators was evaluated by Receiver Operating Characteristic curve., Results: The prevalence of MS was identical to HW (6.4%), without differences between genders and the adolescence phases. The waist perimeter showed higher area under the curve for the diagnosis of MS, except for boys with 17-19 years old, for whom the waist/stature ratio exhibited better performance. For diagnosing HW, waist perimeter also showed higher area under the curve, except for boys in initial and final phases, in which the waist/stature ratio obtained larger area under the curve. The central/peripheral skinfolds had the lowest area under the curve for the presence of both MS and HW phenotype., Conclusions: The waist perimeter and the waist/stature showed a better performance to identify MS and HW in both genders and in all three phases of adolescence., (Copyright © 2015 Associação de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.)

Objective: To analyze the influence of metabolic syndrome components in insulin resistance, by gender and adolescence phase., Subjects and Methods: We evaluated biochemical, clinical, lifestyle and body composition data of 800 adolescents from 10 to 19 years old, from both genders, from Viçosa, MG/Brasil, and there was the division by stage: early (10 to 13 years), intermediate (14 to 16 years) and late (17 to 19 years)., Results: 10.3 and 3.4% had, respectively, insulin resistance and metabolic syndrome. In the initial phase there was a higher prevalence of dyslipidemia and intermediate hyperuricemia and excess body fat. Females had a higher prevalence of dyslipidemia, excess body fat and insulin resistance and higher male prevalence of low HDL, hyperuricemia and blood pressure changes. Those from the initial phase had higher levels of total cholesterol, LDL, HDL, triglycerides, fasting glucose and waist/hip ratio, stayed less time sitting and had more meals (p < 0.05) in relation to other phases. The final model, adjusted for gender, was different for each phase of adolescence., Conclusions: Insulin resistance is associated with inadequate body composition, in biochemical levels and lifestyle, being the factors associated different in each phase of adolescence.

Objective: To study anthropometrical and body composition variables as predictors of risk for metabolic alterations and metabolic syndrome in female adolescents., Methods: Biochemical, clinical and corporal composition data of 100 adolescents from 14 to 17 years old, who attended public schools in Viçosa, Southeastern Brazil, were collected., Results: Regarding nutritional status, 83, 11 and 6% showed eutrophia, overweight/obesity and low weight, respectively, and 61% presented high body fat percent. Total cholesterol presented the highest percentage of inadequacy (57%), followed by high-density lipoprotein (HDL - 50%), low-density lipoprotein (LDL - 47%) and triacylglycerol (22%). Inadequacy was observed in 11, 9, 3 and 4% in relation to insulin resistance, fasting insulin, blood pressure and glycemia, respectively. The highest values of the fasting insulin and the Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) were verified at the highest quartiles of body mass index (BMI), waist perimeter, waist-to-height ratio and body fat percent. Body mass index, waist perimeter, and waist-to-height ratio were the better predictors for high levels of HOMA-IR, blood glucose and fasting insulin. Waist-to-hip ratio was associated to arterial hypertension diagnosis. All body composition variables were effective in metabolic syndrome diagnosis., Conclusions: Waist perimeter, BMI and waist-to-height ratio showed to be good predictors for metabolic alterations in female adolescents and then should be used together for the nutritional assessment in this age range.