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Prediction equation for estimating total daily energy requirements of special operations personnel
BACKGROUND: Special Operations Forces (SOF) engage in a variety of military tasks with many producing high energy expenditures, leading to undesired energy deficits and loss of body mass. Therefore, the ability to accurately estimate daily energy requirements would be useful for accurate logistical...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885383/ https://www.ncbi.nlm.nih.gov/pubmed/29632452 http://dx.doi.org/10.1186/s12970-018-0219-x |
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author | Barringer, N. D. Pasiakos, S. M. McClung, H. L. Crombie, A. P. Margolis, L. M. |
author_facet | Barringer, N. D. Pasiakos, S. M. McClung, H. L. Crombie, A. P. Margolis, L. M. |
author_sort | Barringer, N. D. |
collection | PubMed |
description | BACKGROUND: Special Operations Forces (SOF) engage in a variety of military tasks with many producing high energy expenditures, leading to undesired energy deficits and loss of body mass. Therefore, the ability to accurately estimate daily energy requirements would be useful for accurate logistical planning. PURPOSE: Generate a predictive equation estimating energy requirements of SOF. METHODS: Retrospective analysis of data collected from SOF personnel engaged in 12 different SOF training scenarios. Energy expenditure and total body water were determined using the doubly-labeled water technique. Physical activity level was determined as daily energy expenditure divided by resting metabolic rate. Physical activity level was broken into quartiles (0 = mission prep, 1 = common warrior tasks, 2 = battle drills, 3 = specialized intense activity) to generate a physical activity factor (PAF). Regression analysis was used to construct two predictive equations (Model A; body mass and PAF, Model B; fat-free mass and PAF) estimating daily energy expenditures. RESULTS: Average measured energy expenditure during SOF training was 4468 (range: 3700 to 6300) Kcal·d-(1). Regression analysis revealed that physical activity level (r = 0.91; P < 0.05) and body mass (r = 0.28; P < 0.05; Model A), or fat-free mass (FFM; r = 0.32; P < 0.05; Model B) were the factors that most highly predicted energy expenditures. Predictive equations coupling PAF with body mass (Model A) and FFM (Model B), were correlated (r = 0.74 and r = 0.76, respectively) and did not differ [mean ± SEM: Model A; 4463 ± 65 Kcal·d(− 1), Model B; 4462 ± 61 Kcal·d(− 1)] from DLW measured energy expenditures. CONCLUSION: By quantifying and grouping SOF training exercises into activity factors, SOF energy requirements can be predicted with reasonable accuracy and these equations used by dietetic/logistical personnel to plan appropriate feeding regimens to meet SOF nutritional requirements across their mission profile. |
format | Online Article Text |
id | pubmed-5885383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58853832018-04-09 Prediction equation for estimating total daily energy requirements of special operations personnel Barringer, N. D. Pasiakos, S. M. McClung, H. L. Crombie, A. P. Margolis, L. M. J Int Soc Sports Nutr Research Article BACKGROUND: Special Operations Forces (SOF) engage in a variety of military tasks with many producing high energy expenditures, leading to undesired energy deficits and loss of body mass. Therefore, the ability to accurately estimate daily energy requirements would be useful for accurate logistical planning. PURPOSE: Generate a predictive equation estimating energy requirements of SOF. METHODS: Retrospective analysis of data collected from SOF personnel engaged in 12 different SOF training scenarios. Energy expenditure and total body water were determined using the doubly-labeled water technique. Physical activity level was determined as daily energy expenditure divided by resting metabolic rate. Physical activity level was broken into quartiles (0 = mission prep, 1 = common warrior tasks, 2 = battle drills, 3 = specialized intense activity) to generate a physical activity factor (PAF). Regression analysis was used to construct two predictive equations (Model A; body mass and PAF, Model B; fat-free mass and PAF) estimating daily energy expenditures. RESULTS: Average measured energy expenditure during SOF training was 4468 (range: 3700 to 6300) Kcal·d-(1). Regression analysis revealed that physical activity level (r = 0.91; P < 0.05) and body mass (r = 0.28; P < 0.05; Model A), or fat-free mass (FFM; r = 0.32; P < 0.05; Model B) were the factors that most highly predicted energy expenditures. Predictive equations coupling PAF with body mass (Model A) and FFM (Model B), were correlated (r = 0.74 and r = 0.76, respectively) and did not differ [mean ± SEM: Model A; 4463 ± 65 Kcal·d(− 1), Model B; 4462 ± 61 Kcal·d(− 1)] from DLW measured energy expenditures. CONCLUSION: By quantifying and grouping SOF training exercises into activity factors, SOF energy requirements can be predicted with reasonable accuracy and these equations used by dietetic/logistical personnel to plan appropriate feeding regimens to meet SOF nutritional requirements across their mission profile. BioMed Central 2018-04-05 /pmc/articles/PMC5885383/ /pubmed/29632452 http://dx.doi.org/10.1186/s12970-018-0219-x Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Barringer, N. D. Pasiakos, S. M. McClung, H. L. Crombie, A. P. Margolis, L. M. Prediction equation for estimating total daily energy requirements of special operations personnel |
title | Prediction equation for estimating total daily energy requirements of special operations personnel |
title_full | Prediction equation for estimating total daily energy requirements of special operations personnel |
title_fullStr | Prediction equation for estimating total daily energy requirements of special operations personnel |
title_full_unstemmed | Prediction equation for estimating total daily energy requirements of special operations personnel |
title_short | Prediction equation for estimating total daily energy requirements of special operations personnel |
title_sort | prediction equation for estimating total daily energy requirements of special operations personnel |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885383/ https://www.ncbi.nlm.nih.gov/pubmed/29632452 http://dx.doi.org/10.1186/s12970-018-0219-x |
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