IntroductionExisting predictive equations underestimate the metabolic costs of heavy military load carriage. Metabolic costs are specific to each type of military equipment, and backpack loads often impose the most sustained burden on the dismounted warfighter.PurposeThis study aimed to develop and validate an equation for estimating metabolic rates during heavy backpacking for the US Army Load Carriage Decision Aid (LCDA), an integrated software mission planning tool.MethodsThirty healthy, active military-age adults (3 women, 27 men; age, 25 ± 7 yr; height, 1.74 ± 0.07 m; body mass, 77 ± 15 kg) walked for 6–21 min while carrying backpacks loaded up to 66% body mass at speeds between 0.45 and 1.97 m·s−1. A new predictive model, the LCDA backpacking equation, was developed on metabolic rate data calculated from indirect calorimetry. Model estimation performance was evaluated internally by k-fold cross-validation and externally against seven historical reference data sets. We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured metabolic rate. Estimation accuracy and level of agreement were also evaluated by the bias and concordance correlation coefficient (CCC), respectively.ResultsEstimates from the LCDA backpacking equation were statistically equivalent (P < 0.01) to metabolic rates measured in the current study (bias, −0.01 ± 0.62 W·kg−1; CCC, 0.965) and from the seven independent data sets (bias, −0.08 ± 0.59 W·kg−1; CCC, 0.926).ConclusionsThe newly derived LCDA backpacking equation provides close estimates of steady-state metabolic energy expenditure during heavy load carriage. These advances enable further optimization of thermal-work strain monitoring, sports nutrition, and hydration strategies.

The impact of acute mountain sickness (AMS) and sleep disturbances on mood and cognition at two altitudes relevant to the working and tourist population is unknown. Twenty unacclimatized lowlanders were exposed to either 3000 m (n = 10; 526 mmHg) or 4050 m (n = 10; 460 mmHg) for 20 h in a hypobaric chamber. AMS prevalence and severity was assessed using the Environmental Symptoms Questionnaire (ESQ) and an AMS‐C score ≥ 0.7 indicated sickness. While sleeping for one night both at sea level (SL) and high altitude (HA), a wrist motion detector was used to measure awakenings (Awak, events/h) and sleep efficiency (Eff, %). If Eff was ≥85%, individuals were considered a good sleeper (Sleep+). Mood and cognition were assessed using the Automated Neuropsychological Assessment Metric and Mood Scale (ANAM‐MS). The ESQ and ANAM‐MS were administered in the morning both at SL and after 20 h at HA. AMS severity (mean ± SE; 1.82 ± 0.27 vs. 0.20 ± 0.27), AMS prevalence (90% vs. 10%), depression (0.63 ± 0.23 vs. 0.00 ± 0.24) Awak (15.6 ± 1.6 vs. 10.1 ± 1.6 events/h), and DeSHr (38.5 ± 6.3 vs. 13.3 ± 6.3 events/h) were greater (p < 0.05) and Eff was lower (69.9 ± 5.3% vs. 87.0 ± 5.3%) at 4050 m compared to 3000 m, respectively. AMS presence did not impact cognition but fatigue (2.17 ± 0.37 vs. 0.58 ± 0.39), anger (0.65 ± 0.25 vs. 0.02 ± 0.26), depression (0.63 ± 0.23 vs. 0.00 ± 0.24) and sleepiness (4.8 ± 0.4 vs. 2.7 ± 0.5) were greater (p < 0.05) in the AMS+ group. The Sleep− group, compared to the Sleep+ group, had lower (p < 0.05) working memory scores (50 ± 7 vs. 78 ± 9) assessed by the Sternberg 6‐letter memory task, and lower reaction time fatigue scores (157 ± 17 vs. 221 ± 22), assessed by the repeated reaction time test. Overall, AMS, depression, DeSHr, and Awak were increased (p < 0.05) at 4050 m compared to 3000 m. In addition, AMS presence impacted mood while poor sleep impacted cognition which may deteriorate teamwork and/or increase errors in judgement at HA.

Figueiredo, PS, Looney, DP, Pryor, JL, Doughty, EM, McClung, HL, Vangala, SV, Santee, WR, Beidleman, BA, and Potter, AW. Verification of maximal oxygen uptake in active military personnel during treadmill running. J Strength Cond Res 36(4): 1053–1058, 2022—It is unclear whether verification tests are required to confirm “true” maximal oxygen uptake (V̇o2max) in modern warfighter populations. Our study investigated the prevalence of V̇o2max attainment in U.S. Army soldiers performing a traditional incremental running test. In addition, we examined the utility of supramaximal verification testing as well as repeated trials for familiarization for accurate V̇o2max assessment. Sixteen U.S. Army soldiers (1 woman, 15 men; age, 21 ± 2 years; height, 1.73 ± 0.06 m; body mass, 71.6 ± 10.1 kg) completed 2 laboratory visits, each with an incremental running test (modified Astrand protocol) and a verification test (110% maximal incremental test speed) on a motorized treadmill. We evaluated V̇o2max attainment during incremental testing by testing for the definitive V̇O2 plateau using a linear least-squares regression approach. Peak oxygen uptake (V̇o2peak) was considered statistically equivalent between tests if the 90% confidence interval around the mean difference was within ±2.1 ml·kg−1·min−1. Oxygen uptake plateaus were identified in 14 of 16 volunteers for visit 1 (87.5%) and all 16 volunteers for visit 2 (100%). Peak oxygen uptake was not statistically equivalent, apparent from the mean difference in V̇o2peak measures between the incremental test and verification test on visit 1 (2.3 ml·kg−1·min−1, [1.3–3.2]) or visit 2 (1.1 ml·kg−1·min−1 [0.2–2.1]). Interestingly, V̇o2peak was equivalent, apparent from the mean difference in V̇o2peak measures between visits for the incremental tests (0.0 ml·kg−1·min−1 [−0.8 to 0.9]) but not the verification tests (−1.2 ml·kg−1·min−1 [−2.2 to −0.2]). Modern U.S. Army soldiers can attain V̇o2max by performing a modified Astrand treadmill running test. Additional familiarization and verification tests for confirming V̇o2max in healthy active military personnel may be unnecessary.