Literature DB >> 30303935

Accelerometer Data Processing and Energy Expenditure Estimation in Preschoolers.

Jairo H Migueles1, Christine Delisle Nyström2, Pontus Henriksson1,2, Cristina Cadenas-Sanchez1, Francisco B Ortega1,2, Marie Löf2,3.   

Abstract

PURPOSE: To assess the capacity of different acceleration metrics from wrist accelerations to estimate total energy expenditure (TEE) and activity energy expenditure (AEE) using doubly labeled water in preschool children.
METHODS: Thirty-nine preschoolers (5.5 ± 0.1 yr) were included. Total energy expenditure was measured using doubly labeled water during 14 d, and AEE was then calculated using a predicted basal metabolic rate. Participants wore a wGT3X-BT accelerometer on their nondominant wrist for ≥5 d. We derived the following metrics from raw accelerations: raw ActiGraph activity counts using the normal filter and the low-frequency extension; and alternate summary metrics, such as the Euclidian norm minus 1g (ENMO), Euclidian norm of the high-pass-filtered accelerations (HFEN), the bandpass-filtered accelerations, the HFEN plus Euclidean norm of low-pass filtered accelerations minus 1g (HFEN+) and the mean amplitude deviation.
RESULTS: Alternate summary metrics explained a larger proportion of the variance in TEE and AEE than ActiGraph's activity counts (counts, 7-8 and 25% of TEE and AEE; alternate summary metrics, 13%-16% and 35%-39% of TEE and AEE). Adjustments for body weight and height resulted in an explanation of 51% of AEE by ENMO. All of the metrics adjusted for fat mass and fat-free mass explained up to 84% and 67% of TEE and AEE, respectively.
CONCLUSIONS: ENMO and the other alternate summary metrics explained more of the variance in TEE and AEE than the ActiGraph's activity counts in 5-yr-old children, suggesting further exploration of these variables in studies on physical activity and energy expenditure in preschoolers. Our results need confirmation in other populations with wider age groups and varying body compositions.

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Year:  2019        PMID: 30303935     DOI: 10.1249/MSS.0000000000001797

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  3 in total

1.  Assessment of 24-hour physical behaviour in children and adolescents via wearables: a systematic review of free-living validation studies.

Authors:  Marco Giurgiu; Simon Kolb; Carina Nigg; Alexander Burchartz; Irina Timm; Marlissa Becker; Ellen Rulf; Ann-Kathrin Doster; Elena Koch; Johannes B J Bussmann; Claudio Nigg; Ulrich W Ebner-Priemer; Alexander Woll
Journal:  BMJ Open Sport Exerc Med       Date:  2022-05-12

2.  Unsupervised IMU-based evaluation of at-home exercise programmes: a feasibility study.

Authors:  Dimitrios-Sokratis Komaris; Georgia Tarfali; Brendan O'Flynn; Salvatore Tedesco
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-02-19

3.  Determining total energy expenditure in 3-6-year-old Japanese pre-school children using the doubly labeled water method.

Authors:  Keisuke Teramoto; Kodo Otoki; Erina Muramatsu; Chika Oya; Yui Kataoka; Shoji Igawa
Journal:  J Physiol Anthropol       Date:  2022-08-05       Impact factor: 2.509

  3 in total

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