Literature DB >> 26375253

Wear Compliance and Activity in Children Wearing Wrist- and Hip-Mounted Accelerometers.

Stuart J Fairclough1, Robert Noonan, Alex V Rowlands, Vincent Van Hees, Zoe Knowles, Lynne M Boddy.   

Abstract

PURPOSE: This study aimed to 1) explore children's compliance to wearing wrist- and hip-mounted accelerometers, 2) compare children's physical activity (PA) derived from raw accelerations of wrist and hip, and 3) examine differences in raw and counts PA measured by hip-worn accelerometry.
METHODS: One hundred and twenty-nine 9- to 10-yr-old children wore a wrist-mounted GENEActiv accelerometer (GAwrist) and a hip-mounted ActiGraph GT3X+ accelerometer (AGhip) for 7 d. Both devices measured raw accelerations, and the AGhip also provided count-based data.
RESULTS: More children wore the GAwrist than those from the AGhip regardless of wear time criteria applied (P < 0.001-0.035). Raw data signal vector magnitude (r = 0.68), moderate PA (MPA) (r = 0.81), vigorous PA (VPA) (r = 0.85), and moderate-to-vigorous PA (MVPA) (r = 0.83) were strongly associated between devices (P < 0.001). GAwrist signal vector magnitude (P = 0.001), MPA (P = 0.037), VPA (P = 0.002), and MVPA (P = 0.016) were significantly greater than those from the AGhip. According to GAwrist raw data, 86.9% of children engaged in at least 60 min · d(-1) of MVPA, compared with 19% for AGhip. ActiGraph MPA (raw) was 42.00 ± 1.61 min · d(-1) compared with 35.05 ± 0.99 min · d(-1) (counts) (P = 0.02). ActiGraph VPA was 7.59 ± 0.46 min · d(-1) (raw) and 37.06 ± 1.85 min · d(-1) (counts; P = 0.19).
CONCLUSIONS: In children, accelerometer wrist placement promotes superior compliance than the hip. Raw accelerations were significantly higher for GAwrist compared with those for AGhip possibly because of placement location and technical differences between devices. AGhip PA calculated from raw accelerations and counts differed substantially, demonstrating that PA outcomes derived from cut points for raw output and counts cannot be directly compared.

Entities:  

Mesh:

Year:  2016        PMID: 26375253     DOI: 10.1249/MSS.0000000000000771

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


  72 in total

1.  Accelerometry data in health research: challenges and opportunities.

Authors:  Marta Karas; Jiawei Bai; Marcin Strączkiewicz; Jaroslaw Harezlak; Nancy W Glynn; Tamara Harris; Vadim Zipunnikov; Ciprian Crainiceanu; Jacek K Urbanek
Journal:  Stat Biosci       Date:  2019-01-12

2.  Physical Activity and Sedentary Behavior among US Hispanic/Latino Youth: The SOL Youth Study.

Authors:  Kelly R Evenson; Elva M Arredondo; Mercedes R Carnethon; Alan M Delamater; Linda C Gallo; Carmen R Isasi; Krista M Perreira; Samantha A Foti; Linda VAN Horn; Denise C Vidot; Daniela Sotres-Alvarez
Journal:  Med Sci Sports Exerc       Date:  2019-05       Impact factor: 5.411

3.  Surveillance of Youth Physical Activity and Sedentary Behavior With Wrist Accelerometry.

Authors:  Youngwon Kim; Paul Hibbing; Pedro F Saint-Maurice; Laura D Ellingson; Erin Hennessy; Dana L Wolff-Hughes; Frank M Perna; Gregory J Welk
Journal:  Am J Prev Med       Date:  2017-06       Impact factor: 5.043

4.  Seasonal and weather variation of sleep and physical activity in 12-14-year-old children.

Authors:  Mirja Quante; Rui Wang; Jia Weng; Emily R Kaplan; Michael Rueschman; Elsie M Taveras; Sheryl L Rifas-Shiman; Matthew W Gillman; Susan Redline
Journal:  Behav Sleep Med       Date:  2017-10-09       Impact factor: 2.964

5.  Evaluation of the wrist-worn ActiGraph wGT3x-BT for estimating activity energy expenditure in preschool children.

Authors:  C Delisle Nyström; J Pomeroy; P Henriksson; E Forsum; F B Ortega; R Maddison; J H Migueles; M Löf
Journal:  Eur J Clin Nutr       Date:  2017-07-26       Impact factor: 4.016

6.  Estimated Physical Activity in Adolescents by Wrist-Worn GENEActiv Accelerometers.

Authors:  Sarah G Sanders; Elizabeth Yakes Jimenez; Natalie H Cole; Alena Kuhlemeier; Grace L McCauley; M Lee Van Horn; Alberta S Kong
Journal:  J Phys Act Health       Date:  2019-07-17

7.  Comparison of Accelerometry Methods for Estimating Physical Activity.

Authors:  Jacqueline Kerr; Catherine R Marinac; Katherine Ellis; Suneeta Godbole; Aaron Hipp; Karen Glanz; Jonathan Mitchell; Francine Laden; Peter James; David Berrigan
Journal:  Med Sci Sports Exerc       Date:  2017-03       Impact factor: 5.411

8.  Wrist Accelerometer Cut Points for Classifying Sedentary Behavior in Children.

Authors:  Christiana M T VAN Loo; Anthony D Okely; Marijka J Batterham; Trina Hinkley; Ulf Ekelund; Søren Brage; John J Reilly; Stewart G Trost; Rachel A Jones; Xanne Janssen; Dylan P Cliff
Journal:  Med Sci Sports Exerc       Date:  2017-04       Impact factor: 5.411

Review 9.  Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations.

Authors:  Jairo H Migueles; Cristina Cadenas-Sanchez; Ulf Ekelund; Christine Delisle Nyström; Jose Mora-Gonzalez; Marie Löf; Idoia Labayen; Jonatan R Ruiz; Francisco B Ortega
Journal:  Sports Med       Date:  2017-09       Impact factor: 11.136

10.  Wrist Acceleration Cut Points for Moderate-to-Vigorous Physical Activity in Youth.

Authors:  Christiana Maria Theodora VAN Loo; Anthony D Okely; Marijka J Batterham; Trina Hinkley; Ulf Ekelund; Søren Brage; John J Reilly; Stewart G Trost; Rachel A Jones; Xanne Janssen; Dylan P Cliff
Journal:  Med Sci Sports Exerc       Date:  2018-03       Impact factor: 5.411

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