Med Sci Sports Exerc. 2021 Nov 29. doi: 10.1249/MSS.0000000000002833. Online ahead of print.
ABSTRACT
INTRODUCTION: Existing 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.
PURPOSE: 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.
METHODS: Thirty healthy, active military-age adults (3 women, 27 men; age, 25 ± 7 years old; 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 Model estimation performance was evaluated internally by k-fold cross-validation and externally against seven historical reference datasets. 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.
RESULTS: Estimates from the LCDA backpacking equation were statistically equivalent (p < 0.01) to metabolic rates measured in the current study (Bias, -0.01 ± 0.62; CCC, 0.965) as well as from the seven independent datasets (Bias, -0.08 ± 0.59 W·kg-1; CCC, 0.926).
CONCLUSION: The 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.
PMID:34856578 | DOI:10.1249/MSS.0000000000002833
