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A composite score combining waist circumference and body mass index more accurately predicts body fat percentage in 6- to 13-year-old children


Aeberli, I; Gut-Knabenhans, M; Kusche-Ammann, R S; Molinari, L; Zimmermann, M B (2013). A composite score combining waist circumference and body mass index more accurately predicts body fat percentage in 6- to 13-year-old children. European Journal of Nutrition, 52(1):247-253.

Abstract

Purpose: Body mass index (BMI) and waist circumference (WC) are widely used to predict % body fat (BF) and classify degrees of pediatric adiposity. However, both measures have limitations. The aim of this study was to evaluate whether a combination of WC and BMI would more accurately predict %BF than either alone. Methods: In a nationally representative sample of 2,303 6- to 13-year-old Swiss children, weight, height, and WC were measured, and %BF was determined from multiple skinfold thicknesses. Regression and receiver operating characteristic (ROC) curves were used to evaluate the combination of WC and BMI in predicting %BF against WC or BMI alone. An optimized composite score (CS) was generated. Results: A quadratic polynomial combination of WC and BMI led to a better prediction of %BF (r 2=0.68) compared with the two measures alone (r 2=0.58-0.62). The areas under the ROC curve for the CS [0.6*WC-SDS+0.4*BMI-SDS] ranged from 0.962±0.0053 (overweight girls) to 0.982±0.0046 (obese boys) and were somewhat greater than the AUCs for either BMI or WC alone. At a given specificity, the sensitivity of the prediction of overweight and obesity based on the CS was higher than that based on either WC or BMI alone, although the improvement was small. Conclusion: Both BMI and WC are good predictors of %BF in primary school children. However, a composite score incorporating both measures increased sensitivity at a constant specificity as compared to the individual measures. It may therefore be a useful tool for clinical and epidemiological studies of pediatric adiposity

Abstract

Purpose: Body mass index (BMI) and waist circumference (WC) are widely used to predict % body fat (BF) and classify degrees of pediatric adiposity. However, both measures have limitations. The aim of this study was to evaluate whether a combination of WC and BMI would more accurately predict %BF than either alone. Methods: In a nationally representative sample of 2,303 6- to 13-year-old Swiss children, weight, height, and WC were measured, and %BF was determined from multiple skinfold thicknesses. Regression and receiver operating characteristic (ROC) curves were used to evaluate the combination of WC and BMI in predicting %BF against WC or BMI alone. An optimized composite score (CS) was generated. Results: A quadratic polynomial combination of WC and BMI led to a better prediction of %BF (r 2=0.68) compared with the two measures alone (r 2=0.58-0.62). The areas under the ROC curve for the CS [0.6*WC-SDS+0.4*BMI-SDS] ranged from 0.962±0.0053 (overweight girls) to 0.982±0.0046 (obese boys) and were somewhat greater than the AUCs for either BMI or WC alone. At a given specificity, the sensitivity of the prediction of overweight and obesity based on the CS was higher than that based on either WC or BMI alone, although the improvement was small. Conclusion: Both BMI and WC are good predictors of %BF in primary school children. However, a composite score incorporating both measures increased sensitivity at a constant specificity as compared to the individual measures. It may therefore be a useful tool for clinical and epidemiological studies of pediatric adiposity

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Item Type:Journal Article, refereed, original work
Communities & Collections:National licences > 142-005
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:1 February 2013
Deposited On:04 Jul 2019 15:14
Last Modified:05 Jul 2019 08:36
Publisher:Springer
ISSN:1436-6207
OA Status:Green
Publisher DOI:https://doi.org/10.1007/s00394-012-0317-5
Related URLs:https://www.swissbib.ch/Search/Results?lookfor=nationallicencespringer101007s0039401203175 (Library Catalogue)
PubMed ID:22322925

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