Literature DB >> 23196764

Comparison of accelerometry cut points for physical activity and sedentary behavior in preschool children: a validation study.

Jane F Hislop1, Cathy Bulley, Tom H Mercer, John J Reilly.   

Abstract

This study compared accelerometry cut points for sedentary behavior, light and moderate to vigorous intensity activity (MVPA) against a criterion measure, the Children's Activity Rating Scale (CARS), in preschool children. Actigraph accelerometry data were collected from 31 children (4.4 ± 0.8 yrs) during one hour of free-play. Video data were coded using the CARS. Cut points by Pate et al., van Cauwenberghe et al., Sirard et al. and Puyau et al. were applied to calculate time spent in sedentary, light and MVPA. Repeated-measures ANOVA and paired t tests tested differences between the cut points and the CARS. Bland and Altman plots tested agreement between the cut points and the CARS. No significant difference was found between the CARS and the Puyau et al. cut points for sedentary, light and MVPA or between the CARS and the Sirard et al. cut point for MVPA. The present study suggests that the Sirard et al. and Puyau et al. cut points provide accurate group-level estimates of MVPA in preschool children.

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Year:  2012        PMID: 23196764     DOI: 10.1123/pes.24.4.563

Source DB:  PubMed          Journal:  Pediatr Exerc Sci        ISSN: 0899-8493            Impact factor:   2.333


  7 in total

1.  NET-Works: Linking families, communities and primary care to prevent obesity in preschool-age children.

Authors:  Nancy E Sherwood; Simone A French; Sara Veblen-Mortenson; A Lauren Crain; Jerica Berge; Alicia Kunin-Batson; Nathan Mitchell; Meghan Senso
Journal:  Contemp Clin Trials       Date:  2013-10-09       Impact factor: 2.226

2.  Tracking of accelerometer-measured physical activity in early childhood.

Authors:  Nicholas M Edwards; Philip R Khoury; Heidi J Kalkwarf; Jessica G Woo; Randal P Claytor; Stephen R Daniels
Journal:  Pediatr Exerc Sci       Date:  2013-07-12       Impact factor: 2.333

3.  Device-based measurement of physical activity in pre-schoolers: Comparison of machine learning and cut point methods.

Authors:  Matthew N Ahmadi; Stewart G Trost
Journal:  PLoS One       Date:  2022-04-13       Impact factor: 3.240

4.  Park use is associated with less sedentary time among low-income parents and their preschool child: The NET-Works study.

Authors:  Simone A French; Nancy E Sherwood; Nathan R Mitchell; Yingling Fan
Journal:  Prev Med Rep       Date:  2016-11-10

Review 5.  Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old).

Authors:  Annelinde Lettink; Teatske M Altenburg; Jelle Arts; Vincent T van Hees; Mai J M Chinapaw
Journal:  Int J Behav Nutr Phys Act       Date:  2022-09-08       Impact factor: 8.915

6.  Predictive validity and classification accuracy of ActiGraph energy expenditure equations and cut-points in young children.

Authors:  Xanne Janssen; Dylan P Cliff; John J Reilly; Trina Hinkley; Rachel A Jones; Marijka Batterham; Ulf Ekelund; Søren Brage; Anthony D Okely
Journal:  PLoS One       Date:  2013-11-11       Impact factor: 3.240

7.  Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children.

Authors:  Matthew N Ahmadi; Toby G Pavey; Stewart G Trost
Journal:  Sensors (Basel)       Date:  2020-08-05       Impact factor: 3.576

  7 in total

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