Accelerometer Data Treatment for Adolescents: Fitting a Piece of the Puzzle

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aut.relation.endpage231
aut.relation.journalPreventive Medicine Reportsen_NZ
aut.relation.startpage228
aut.relation.volume5en_NZ
aut.researcherRush, Elaine
dc.contributor.authorSmith, Men_NZ
dc.contributor.authorTaylor, Sen_NZ
dc.contributor.authorIusitini, Len_NZ
dc.contributor.authorStewart, Ten_NZ
dc.contributor.authorSavila, Fen_NZ
dc.contributor.authorTautolo, ESen_NZ
dc.contributor.authorPlank, Len_NZ
dc.contributor.authorJalili-Moghaddam, Sen_NZ
dc.contributor.authorPaterson, Jen_NZ
dc.contributor.authorRush, Een_NZ
dc.date.accessioned2017-03-24T02:16:37Z
dc.date.available2017-03-24T02:16:37Z
dc.date.copyright2017-03en_NZ
dc.date.issued2017-03en_NZ
dc.description.abstractThis study aimed to assess the differences in participant retention and associations between physical activity and key variables when a range of accelerometer data inclusion criteria are employed. Data were drawn from 204 adolescents of Pacific Island heritage (survey, body composition, 7-day accelerometry) and their parents (date of birth, socioeconomic status) between October 2014 and February 2016 in Auckland, New Zealand. Data wear time criteria for inclusion were as follows: A) > = 10 h/weekday or > = 8 h weekend day, > = 5 days (at least one weekend day); B) > = 10 h/weekday or > = 8 h weekend day, > = 4 days; C) > = 7 h/day, > = 3 days; D) > = 10 h/day, > = 1 day. Overall, 49%, 62%, 88%, and 96% of participants met the criteria, respectively. Adjusted odds of meeting each criterion were examined using a multivariable logistic regression model. Almost 50% of participants were excluded by the most stringent inclusion criteria. Increased body fat percentage and proportion of time in moderate-to-vigorous activity were associated with decreased odds of meeting Criterions A and B. This research contributes to a growing understanding of the impact of differing accelerometer reduction approaches to sample retention and bias in adolescent physical activity research.en_NZ
dc.identifier.citationPreventive Medicine Reports. Volume 5, March 2017, Pages 228–231
dc.identifier.doi10.1016/j.pmedr.2016.12.010en_NZ
dc.identifier.issn2211-3355en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/10404
dc.languageengen_NZ
dc.publisherElsevier
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S2211335516301619
dc.rights© 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectAccelerometryen_NZ
dc.subjectAdolescentsen_NZ
dc.subjectMeasureen_NZ
dc.subjectPacific healthen_NZ
dc.subjectPhysical activityen_NZ
dc.titleAccelerometer Data Treatment for Adolescents: Fitting a Piece of the Puzzleen_NZ
dc.typeJournal Article
pubs.elements-id219012
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Health & Environmental Science
pubs.organisational-data/AUT/Health & Environmental Science/Public Health & Psych Studies
pubs.organisational-data/AUT/Health & Environmental Science/Sports & Recreation
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