A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data.

Détails

Ressource 1Télécharger: s12966-019-0801-x.pdf (692.26 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_6A3A5FA4103F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data.
Périodique
The international journal of behavioral nutrition and physical activity
Auteur(s)
Kwon S., Andersen L.B., Grøntved A., Kolle E., Cardon G., Davey R., Kriemler S., Northstone K., Page A.S., Puder J.J., Reilly J.J., Sardinha L.B., van Sluijs EMF, Janz K.F.
ISSN
1479-5868 (Electronic)
ISSN-L
1479-5868
Statut éditorial
Publié
Date de publication
29/04/2019
Peer-reviewed
Oui
Volume
16
Numéro
1
Pages
40
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Résumé
Accelerometers are widely used to assess child physical activity (PA) levels. Using the accelerometer data, several PA metrics can be estimated. Knowledge about the relationships between these different metrics can improve our understanding of children's PA behavioral patterns. It also has significant implications for comparing PA metrics across studies and fitting a statistical model to examine their health effects. The aim of this study was to examine the relationships among the metrics derived from accelerometers in children.
Accelerometer data from 24,316 children aged 5 to 18 years were extracted from the International Children's Accelerometer Database (ICAD) 2.0. Correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC) were calculated.
TAC was approximately 22X10 <sup>3</sup> counts higher (p < 0.01) with longer wear time (13 to 18 h/day) as compared to shorter wear time (8 to < 13 h/day), while MVPA was similar across the wear time categories. MVPA was very highly correlated with TAC (r = .91; 99% CI = .91 to .91). Wear time-adjusted correlation between SB and LPA was also very high (r = -.96; 99% CI = -.96, - 95). VPA was moderately correlated with MPA (r = .58; 99% CI = .57, .59).
TAC is mostly explained by MVPA, while it could be more dependent on wear time, compared to MVPA. MVPA appears to be comparable across different wear durations and studies when wear time is ≥8 h/day. Due to the moderate to high correlation between some PA metrics, potential collinearity should be addressed when including multiple PA metrics together in statistical modeling.
Mots-clé
Accelerometry, Adolescent, Child, Child, Preschool, Databases, Factual, Exercise/physiology, Fitness Trackers, Human Activities/statistics & numerical data, Humans, Models, Statistical, Sedentary Behavior, ActiGraph, Adolescents, Children, ICAD, Physical activity measurement, Sedentary, Total activity counts
Pubmed
Web of science
Open Access
Oui
Création de la notice
06/05/2019 16:17
Dernière modification de la notice
20/08/2019 14:25
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