Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.
Horner, Fleur Bilzon, James L Rayson, Mark Blacker, Sam Richmond, Victoria Carter, James Wright, Anthony
Horner, Fleur
Bilzon, James L
Rayson, Mark
Blacker, Sam
Richmond, Victoria
Carter, James
Wright, Anthony
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2013
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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
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PubMed ID
23121502
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Journal article
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en
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1466-447X