Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort |
| |
Authors: | Fleur Horner Mark Rayson Sam Blacker Victoria Richmond James Carter |
| |
Affiliation: | 1. University of Bath, Department for Health , Bath , United Kingdom;2. Optimal Performance Ltd , Clifton , Bristol , United Kingdom;3. Optimal Performance Ltd , Clifton , Bristol , United Kingdom |
| |
Abstract: | 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. |
| |
Keywords: | accelerometry doubly labelled water military free-living |
|
|