Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.

2.50
Hdl Handle:
http://hdl.handle.net/2436/298059
Title:
Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.
Authors:
Horner, Fleur; Bilzon, James L; Rayson, Mark; Blacker, Sam; Richmond, Victoria; Carter, James; Wright, Anthony; Nevill, Alan M.
Abstract:
This study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r (2) = 0.65, SE = 462 kcal · d(-1) (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r (2) = 0.41, SE = 490 kcal · d(-1) (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.
Citation:
Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort. 2013, 31 (4):354-60 J Sports Sci
Journal:
Journal of sports sciences
Issue Date:
2013
URI:
http://hdl.handle.net/2436/298059
DOI:
10.1080/02640414.2012.734632
PubMed ID:
23121502
Type:
Article
Language:
en
ISSN:
1466-447X
Appears in Collections:
Sport, Exercise and Health Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorHorner, Fleuren_GB
dc.contributor.authorBilzon, James Len_GB
dc.contributor.authorRayson, Marken_GB
dc.contributor.authorBlacker, Samen_GB
dc.contributor.authorRichmond, Victoriaen_GB
dc.contributor.authorCarter, Jamesen_GB
dc.contributor.authorWright, Anthonyen_GB
dc.contributor.authorNevill, Alan M.en_GB
dc.date.accessioned2013-08-13T09:17:37Z-
dc.date.available2013-08-13T09:17:37Z-
dc.date.issued2013-
dc.identifier.citationDevelopment of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort. 2013, 31 (4):354-60 J Sports Scien_GB
dc.identifier.issn1466-447X-
dc.identifier.pmid23121502-
dc.identifier.doi10.1080/02640414.2012.734632-
dc.identifier.urihttp://hdl.handle.net/2436/298059-
dc.description.abstractThis study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r (2) = 0.65, SE = 462 kcal · d(-1) (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r (2) = 0.41, SE = 490 kcal · d(-1) (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.en_GB
dc.language.isoenen
dc.rightsArchived with thanks to Journal of sports sciencesen_GB
dc.subject.meshActigraphyen_GB
dc.subject.meshAdolescenten_GB
dc.subject.meshAdulten_GB
dc.subject.meshAnalysis of Varianceen_GB
dc.subject.meshBody Heighten_GB
dc.subject.meshBody Weighten_GB
dc.subject.meshCohort Studiesen_GB
dc.subject.meshEnergy Metabolismen_GB
dc.subject.meshExerciseen_GB
dc.subject.meshFemaleen_GB
dc.subject.meshHumansen_GB
dc.subject.meshLinear Modelsen_GB
dc.subject.meshMaleen_GB
dc.subject.meshMilitary Personnelen_GB
dc.subject.meshModels, Biologicalen_GB
dc.subject.meshMotor Activityen_GB
dc.subject.meshReproducibility of Resultsen_GB
dc.subject.meshSex Factorsen_GB
dc.subject.meshYoung Adulten_GB
dc.titleDevelopment of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.en
dc.typeArticleen
dc.identifier.journalJournal of sports sciencesen_GB

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