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Differences Between Responders and Non-responders for Endurance Performance During Combined Training in Military Operation

METHODS: Twenty-six (14 male, 12 female) Officer Cadets (OC, mean ± SD: age 23 ± 2 years, height 1.73 ± 0.09 m, body mass 77.2 ± 9.4 kg) wore a PAM (GENEActiv, Cambridge, UK) continuously on the dominant wrist over three 10-day blocks of military training on base and field exercises. Immediately prior to each 10-day block, OCs consumed a bolus of DLW and provided daily urine samples, which were analysed by mass spectrometry to determine TEEDLW. The PAM recorded continuously at 50 Hz throughout each 10-day block and the manufacturer’s software was used to estimate TEE for each OC using an equation developed in a civilian population (TEECIV). Each OC in each 10-day block was treated as a separate ‘observation’ (n=53). A random sample of 30 observations were entered into a linear regression to produce a model to estimate TEE for military populations (TEEMIL). The TEEMILequation was applied to the remaining 23 observations to quantify the mean bias ± 95% Limits of Agreement (LoA) between TEEDLW and TEECIV or TEEMIL. RESULTS: The TEEMIL equation [TEEMIL= 563.116 + (0.886 x TEECIV)] exhibited a strong correlation (r=0.826) and a Standard Error of the Estimate of 475 kcal·day . Applying the equation reduced mean bias ± 95% LoA against TEEDLW from -194 ± 1055 kcal·day for TEECIV to 0.79 ± 996 kcal·day for TEEMIL. CONCLUSIONS: The TEEMIL equation developed in this study improves the estimation of TEEDLW from a PAM in military populations compared to an existing TEECIV equation. Future research should explore data processing techniques to identify different physical activity types from wrist-worn PAM in military settings to further improve TEE estimation and validate these equations in different military cohorts.