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

F. Horner, J.L. Bilzon, M. Rayson, S. Blacker, V. Richmond, J. Carter, A. Wright, A. Nevill

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)354-360
Number of pages7
JournalJournal of Sports Sciences
Volume31
Issue number4
Early online date5 Nov 2012
DOIs
Publication statusPublished - Apr 2013

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