Objective: Evaluate accuracy of skinfold thicknesses and body mass index (BMI) for the prediction of fat mass percentage (FM%) in paediatric inflammatory bowel disease (IBD) and to develop population-specific formulae based on anthropometry for estimation of FM%. Methods: IBD children (n = 30) and healthy controls (HCs, n = 144) underwent anthropometric evaluation and dual-energy X-ray absorptiometry (DEXA) scan, as the clinical reference for measurement of body composition. Body FM% estimated with skinfolds thickness was compared with FM% measured with DEXA. By means of 4 prediction models, population specific formulae for estimation of FM% were developed. Results: No significant difference in terms of FM% measured by DEXA was found between IBD population and HCs (FM% 29.6% vs 32.2%, P = 0.108). Triceps skinfold thickness (TSF, Model 2) was better than BMI (Model 1) at predicting FM% (82% vs 68% of variance). The sum of 2 skinfolds (biceps + triceps; SF2, Model 3) showed an improvement in the prediction of FM% as compared with TSF, Model 2 (86% vs 82% of variance). The sum of 4 skinfolds (biceps + triceps + suprailiac + subscapular; Model 4) showed further improvement in the prediction of FM% as compared with SF2 (88% vs 86% of variance). Conclusions: The sum of 4 skinfolds is the most accurate in predicting FM% in paediatric IBD. The sum of 2 skinfolds is less accurate but more feasible and less prone to error. The newly developed population-specific formulae could be a valid tool for estimation of body composition in IBD population and an alternative to DEXA measurement.

Penagini, F., Leone, A., Borsani, B., Bosetti, A., Dilillo, D., Rendo, G., et al. (2021). Predictive Fat Mass Equations for Children With Inflammatory Bowel Disease. JOURNAL OF PEDIATRIC GASTROENTEROLOGY AND NUTRITION, 73(4), 98-104 [10.1097/MPG.0000000000003188].

Predictive Fat Mass Equations for Children With Inflammatory Bowel Disease

Bedogni, G;
2021

Abstract

Objective: Evaluate accuracy of skinfold thicknesses and body mass index (BMI) for the prediction of fat mass percentage (FM%) in paediatric inflammatory bowel disease (IBD) and to develop population-specific formulae based on anthropometry for estimation of FM%. Methods: IBD children (n = 30) and healthy controls (HCs, n = 144) underwent anthropometric evaluation and dual-energy X-ray absorptiometry (DEXA) scan, as the clinical reference for measurement of body composition. Body FM% estimated with skinfolds thickness was compared with FM% measured with DEXA. By means of 4 prediction models, population specific formulae for estimation of FM% were developed. Results: No significant difference in terms of FM% measured by DEXA was found between IBD population and HCs (FM% 29.6% vs 32.2%, P = 0.108). Triceps skinfold thickness (TSF, Model 2) was better than BMI (Model 1) at predicting FM% (82% vs 68% of variance). The sum of 2 skinfolds (biceps + triceps; SF2, Model 3) showed an improvement in the prediction of FM% as compared with TSF, Model 2 (86% vs 82% of variance). The sum of 4 skinfolds (biceps + triceps + suprailiac + subscapular; Model 4) showed further improvement in the prediction of FM% as compared with SF2 (88% vs 86% of variance). Conclusions: The sum of 4 skinfolds is the most accurate in predicting FM% in paediatric IBD. The sum of 2 skinfolds is less accurate but more feasible and less prone to error. The newly developed population-specific formulae could be a valid tool for estimation of body composition in IBD population and an alternative to DEXA measurement.
2021
Penagini, F., Leone, A., Borsani, B., Bosetti, A., Dilillo, D., Rendo, G., et al. (2021). Predictive Fat Mass Equations for Children With Inflammatory Bowel Disease. JOURNAL OF PEDIATRIC GASTROENTEROLOGY AND NUTRITION, 73(4), 98-104 [10.1097/MPG.0000000000003188].
Penagini, F; Leone, A; Borsani, B; Bosetti, A; Dilillo, D; Rendo, G; Calcaterra, V; Bertoli, S; Mora, S; Battezzati, A; Bedogni, G; Zuccotti, GV...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/959729
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