Prediction of metabolic syndrome in children through anthropometric indicators

Because of the need to measure anthropometric, biochemical and hemodynamic variables for the diagnosis of metabolic syndrome, we realize how difficult it is to analyze large populations, especially children, due to the poor accessibility and the invasive character. There is an urgent need to develop...

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Published in:Arquivos brasileiros de cardiologia Vol. 96; no. 2; pp. 121 - 125
Main Authors: Ferreira, Aparecido Pimentel, Ferreira, Cristiane Batisti, Brito, Ciro José, Pitanga, Francisco José Gondim, Moraes, Clayton Franco, Naves, Luciana Ansaneli, Nóbrega, Otávio de Toledo, França, Nancí Maria de
Format: Journal Article
Language:English
Portuguese
Published: Brazil 01-02-2011
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Summary:Because of the need to measure anthropometric, biochemical and hemodynamic variables for the diagnosis of metabolic syndrome, we realize how difficult it is to analyze large populations, especially children, due to the poor accessibility and the invasive character. There is an urgent need to develop easy-to-use, accurate and low-cost diagnostic tools in order to predict metabolic syndrome at early ages. To verify the prevalence of metabolic syndrome in children and to test predictive anthropometric indicators. Cross-sectional study conducted among 109 children aged 7 to 11 years. The age-adjusted National Cholesterol Education Program definition was used for the diagnosis of metabolic syndrome. The following parameters were tested as possible predictors: body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), conicity index (C index), and body fat percentage. The prevalence of metabolic syndrome was 13.3% and 36% for boys and girls, respectively. The main anthropometric indicators were: BMI = 0.81 (0.69 - 0.94), WC = 0.79 (0.64 - 0.94), body fat = 0.79 (0.66 - 0.92) and WHR = 0.37 (0.21 - 0.54). WC higher than 78 cm, body fat higher than 41%, and BMI higher than 24.5 kg/m² were considered predictors of metabolic syndrome. The C index and WHR were not considered predictors.
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ISSN:1678-4170
DOI:10.1590/S0066-782X2011005000005