Literature DB >> 18208433

Comparison of equations for predicting energy expenditure from accelerometer counts in children.

A Nilsson1, S Brage, C Riddoch, S A Anderssen, L B Sardinha, N Wedderkopp, L B Andersen, U Ekelund.   

Abstract

Several prediction equations developed to convert body movement measured by accelerometry into energy expenditure have been published. The aim of this study was to examine the degree of agreement between three different prediction equations, when applied to data on physical activity in a large sample of children. We examined 1321 children (663 boys, 658 girls; mean age 9.6+/-0.4 years) from four different countries. Physical activity was measured by the MTI accelerometer. One equation, derived from doubly labeled water (DLW) measurements, was compared with one treadmill-based (TM) and one room calorimeter-based (CAL) equation (mixture of activities). Predicted physical activity energy expenditure (PAEE) was the main outcome variable. In comparison with DLW-predicted PAEE, both laboratory-derived equations significantly (P<0.001) overestimated PAEE by 17% and 83%, respectively, when based on a 24-h prediction, while the TM equation significantly (P<0.001) underestimated PAEE by 46%, when based on awake time only. In contrast, the CAL equation agreed better with the DLW equation under the awake time assumption. Predicted PAEE differ substantially between equations, depending on time-frame assumptions, and interpretations of average levels of PAEE in children from available equations should be made with caution. Further development of equations applicable to free-living scenarios is needed.

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Year:  2008        PMID: 18208433     DOI: 10.1111/j.1600-0838.2007.00694.x

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  8 in total

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4.  Distributed lag and spline modeling for predicting energy expenditure from accelerometry in youth.

Authors:  Leena Choi; Kong Y Chen; Sari A Acra; Maciej S Buchowski
Journal:  J Appl Physiol (1985)       Date:  2009-12-03

5.  Review of prediction models to estimate activity-related energy expenditure in children and adolescents.

Authors:  Suzanne M de Graauw; Janke F de Groot; Marco van Brussel; Marjolein F Streur; Tim Takken
Journal:  Int J Pediatr       Date:  2010-06-29

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7.  Comparison of estimated energy intake using Web-based Dietary Assessment Software with accelerometer-determined energy expenditure in children.

Authors:  Anja Biltoft-Jensen; Mads F Hjorth; Ellen Trolle; Tue Christensen; Per B Brockhoff; Lene F Andersen; Inge Tetens; Jeppe Matthiessen
Journal:  Food Nutr Res       Date:  2013-12-17       Impact factor: 3.894

8.  Use of a Web-Based Dietary Assessment Tool (RiksmatenFlex) in Swedish Adolescents: Comparison and Validation Study.

Authors:  Anna Karin Lindroos; Jessica Petrelius Sipinen; Cecilia Axelsson; Gisela Nyberg; Rikard Landberg; Per Leanderson; Marianne Arnemo; Eva Warensjö Lemming
Journal:  J Med Internet Res       Date:  2019-10-04       Impact factor: 5.428

  8 in total

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