Nutrition and Physical Activity During British Army Officer Cadet Training: Part 1-Energy Balance and Energy Availability.

Military training is characterized by high daily energy expenditures which are difficult to match with energy intake, potentially resulting in negative energy balance (EB) and low energy availability (EA). The aim of this study was to quantify EB and EA during British Army Officer Cadet training. Thirteen (seven women) Officer Cadets (mean ± SD: age 24 ± 3 years) volunteered to participate. EB and EA were estimated from energy intake (weighing of food and food diaries) and energy expenditure (doubly labeled water) measured in three periods of training: 9 days on-camp (CAMP), a 5-day field exercise (FEX), and a 9-day mixture of both CAMP and field-based training (MIX). Variables were compared by condition and gender with a repeated-measures analysis of variance. Negative EB was greatest during FEX (-2,197 ± 455 kcal/day) compared with CAMP (-692 ± 506 kcal/day; p < .001) and MIX (-1,280 ± 309 kcal/day; p < .001). EA was greatest in CAMP (23 ± 10 kcal·kg free-fat mass [FFM]-1·day-1) compared with FEX (1 ± 16 kcal·kg FFM-1·day-1; p = .002) and MIX (10 ± 7 kcal·kg FFM-1·day-1; p = .003), with no apparent difference between FEX and MIX (p = .071). Irrespective of condition, there were no apparent differences between gender in EB (p = .375) or EA (p = .385). These data can be used to inform evidenced-based strategies to manage EA and EB during military training, and enhance the health and performance of military personnel.

Validity of energy expenditure estimation methods during 10 days of military training.

Wearable physical activity (PA) monitors have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established research methods has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors and a PA log against doubly labeled water (DLW) during British Army Officer Cadet (OC) training. For 10 days of training, twenty (10 male and 10 female) OCs (mean ± SD: age 23 ± 2 years, height 1.74 ± 0.09 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK) on the dominant wrist, wore one commercially available monitor (Fitbit SURGE, USA) on the non-dominant wrist, and completed a self-report PA log. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analyzed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement (LoA) were employed to compare TEE from each estimation method to DLW. Average daily TEE from DLW was 4112 ± 652 kcal·day-1 against which the GENEActiv showed near identical average TEE (mean bias ± LoA: -15 ± 851 kcal. day-1 ) while Fitbit tended to underestimate (-656 ± 683 kcal·day-1 ) and the PA log substantially overestimate (+1946 ± 1637 kcal·day-1 ). Wearable physical activity monitors provide a cheaper and more practical method for estimating free-living TEE than DLW in military settings. The GENEActiv accelerometer demonstrated good validity for assessing daily TEE and would appear suitable for use in large-scale, longitudinal military studies.

Implications of the variation in biological 18 O natural abundance in body water to inform use of Bayesian methods for modelling total energy expenditure when using doubly labelled water.

RATIONALE: Variation in 18 O natural abundance can lead to errors in the calculation of total energy expenditure (TEE) when using the doubly labelled water (DLW) method. The use of Bayesian statistics allows a distribution to be assigned to 18 O natural abundance, thus allowing a best-fit value to be used in the calculation. The aim of this study was to calculate within-subject variation in 18 O natural abundance and apply this to our original working model for TEE calculation. METHODS: Urine samples from a cohort of 99 women, dosed with 50 g of 20% 2 H2 O, undertaking a 14-day breast milk intake protocol, were analysed for 18 O. The within-subject variance was calculated and applied to a Bayesian model for the calculation of TEE in a separate cohort of 36 women. This cohort of 36 women had taken part in a DLW study and had been dosed with 80 mg/kg body weight 2 H2 O and 150 mg/kg body weight H2 18 O. RESULTS: The average change in the δ18 O value from the 99 women was 1.14‰ (0.77) [0.99, 1.29], with the average within-subject 18 O natural abundance variance being 0.13‰2 (0.25) [0.08, 0.18]. There were no significant differences in TEE (9745 (1414), 9804 (1460) and 9789 (1455) kJ/day, non-Bayesian, Bluck Bayesian and modified Bayesian models, respectively) between methods. CONCLUSIONS: Our findings demonstrate that using a reduced natural variation in 18 O as calculated from a population does not impact significantly on the calculation of TEE in our model. It may therefore be more conservative to allow a larger variance to account for individual extremes.