Literature DB >> 27327029

Moving Forward with Backward Compatibility: Translating Wrist Accelerometer Data.

Alex V Rowlands1, Dylan P Cliff, Stuart J Fairclough, Lynne M Boddy, Tim S Olds, Gaynor Parfitt, Rob J Noonan, Samantha J Downs, Zoe R Knowles, Michael W Beets.   

Abstract

PURPOSE: This study aimed to provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children's moderate-to-vigorous physical activity (MVPA) from a range of cut points applied to hip-worn ActiGraph data.
METHODS: This is a secondary analysis of three studies with concurrent 7-d accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children age 9-12 yr. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350, and 400 mg from wrist acceleration data (≤5-s epoch) was calculated for comparison with MVPA estimated from widely used children's hip-worn ActiGraph MVPA cut points (Freedson/Trost, 1100 counts per minute; Pate, 1680 counts per minute; Evenson, 2296 counts per minute; Puyau, 3200 counts per minute) with epochs of ≤5, 15, and 60 s.
RESULTS: The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut points determined from 70% of the sample and cross validated with the remaining 30% were as follows: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (intraclass correlation [ICC] ≥ 0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC ≥ 0.67); Evenson = ENMO 250+ mg for ≤5- and 15-s epochs (ICC ≥ 0.69) and ENMO 300+ mg for 60-s epochs (ICC = 0.73); Puyau = ENMO 300+ mg for ≤5-s epochs (ICC = 0.73), ENMO 350+ mg for 15-s epochs (ICC = 0.73), and ENMO 400+ mg for 60-s epochs (ICC = 0.65). Agreement was robust with cross-validation ICC = 0.62-0.71 and means within ∣7.8∣% ± 4.9% of MVPA estimates from ActiGraph cut points, except Puyau 60-s epochs (ICC = 0.42).
CONCLUSION: Incremental ENMO thresholds enable children's acceleration data measured at the wrist to be simply and directly compared, at a group level, with past estimates of MVPA from hip-worn ActiGraphs across a range of cut points.

Entities:  

Mesh:

Year:  2016        PMID: 27327029     DOI: 10.1249/MSS.0000000000001015

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


  12 in total

1.  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
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2.  Association between sleep quality and physical activity in postpartum women.

Authors:  Jiqiang Wu; Brett Einerson; Janet M Shaw; Ingrid E Nygaard; Xiaoming Sheng; Ali Wolpern; Marlene J Egger
Journal:  Sleep Health       Date:  2019-09-12

3.  The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.

Authors:  Sunku Kwon; Neng Wan; Ryan D Burns; Timothy A Brusseau; Youngwon Kim; Santosh Kumar; Emre Ertin; David W Wetter; Cho Y Lam; Ming Wen; Wonwoo Byun
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4.  Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community.

Authors:  Sarah L Taylor; Whitney B Curry; Zoe R Knowles; Robert J Noonan; Bronagh McGrane; Stuart J Fairclough
Journal:  Int J Environ Res Public Health       Date:  2017-05-16       Impact factor: 3.390

5.  Using open source accelerometer analysis to assess physical activity and sedentary behaviour in overweight and obese adults.

Authors:  Paul Innerd; Rory Harrison; Morc Coulson
Journal:  BMC Public Health       Date:  2018-04-23       Impact factor: 3.295

6.  The Feasibility of a Novel School Peer-Led Mentoring Model to Improve the Physical Activity Levels and Sedentary Time of Adolescent Girls: The Girls Peer Activity (G-PACT) Project.

Authors:  Michael B Owen; Charlotte Kerner; Sarah L Taylor; Robert J Noonan; Lisa Newson; Maria-Christina Kosteli; Whitney B Curry; Stuart J Fairclough
Journal:  Children (Basel)       Date:  2018-05-31

7.  Identification of earlier predictors of pregnancy complications through wearable technologies in a Brazilian multicentre cohort: Maternal Actigraphy Exploratory Study I (MAES-I) study protocol.

Authors:  Renato T Souza; Jose Guilherme Cecatti; Jussara Mayrink; Rafael Bessa Galvão; Maria Laura Costa; Francisco Feitosa; Edilberto Rocha Filho; Debora F Leite; Janete Vettorazzi; Ricardo P Tedesco; Danielly S Santana; Joao Paulo Souza
Journal:  BMJ Open       Date:  2019-04-20       Impact factor: 2.692

8.  Evaluation of a Pilot School-Based Physical Activity Clustered Randomised Controlled Trial-Active Schools: Skelmersdale.

Authors:  Sarah L Taylor; Robert J Noonan; Zoe R Knowles; Michael B Owen; Bronagh McGrane; Whitney B Curry; Stuart J Fairclough
Journal:  Int J Environ Res Public Health       Date:  2018-05-17       Impact factor: 3.390

9.  Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults.

Authors:  Jairo H Migueles; Cristina Cadenas-Sanchez; Alex V Rowlands; Pontus Henriksson; Eric J Shiroma; Francisco M Acosta; Maria Rodriguez-Ayllon; Irene Esteban-Cornejo; Abel Plaza-Florido; Jose J Gil-Cosano; Ulf Ekelund; Vincent T van Hees; Francisco B Ortega
Journal:  Sci Rep       Date:  2019-12-03       Impact factor: 4.379

10.  Early postpartum physical activity and pelvic floor support and symptoms 1 year postpartum.

Authors:  Ingrid E Nygaard; Ali Wolpern; Tyler Bardsley; Marlene J Egger; Janet M Shaw
Journal:  Am J Obstet Gynecol       Date:  2020-08-14       Impact factor: 8.661

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