The Impact of Critical Speed and Lean Body Mass on Load Carriage Performance for Army Reserve Officers' Training Corps Cadets.

Introduction: Load carriage is an inherent part of tactical operations. Critical speed (CS) has been associated with technical and combat-specific performance measures (e.g., loaded running). The 3-min all-out exercise test provides estimates of CS and the maximal capacity to displace the body (D') at speeds above CS. The current study investigated the contributions of CS, D', lean body mass (LBM), thigh lean mass (TLM), and lower body isokinetic strength and endurance parameters related to load carriage time trials (LCTTs).

Methods: Twenty-two Reserve Officers' Training Corps cadets (6 = females, age = 20.82 ± 1.59 years) underwent various assessments that included a running 3-minute all-out test to determine CS and D', isokinetic knee extension (KE) muscle strength and endurance, body composition assessed by dual-energy X-ray absorption, and two 21-kg LCTTs of 400 and 3,200 m, respectively. Pearson's product-moment correlations investigated relationships between selected predictor variables. Stepwise multiple linear regression analyses were used to determine the relationship between variables that predicted LCTT performance.

Results: Significant correlations were as follows: LBM and CS (r = 0.651, P < .001), KE endurance work and CS (r = 0.645, P < .001), TLM and CS (r = 0.593, P < .05), and KE peak torque and CS (r = 0.529, P < .05). The stepwise regression analyses indicated that CS and LBM contributed significantly to predicting 3,200-m LCTT (F [2,19] = 81.85, R2 = 0.90, P < .001) with standardized β coefficients (-0.723 and -0.301, respectively). Thigh lean mass contributed significantly to predicting the 400-m LCTT (F [1,20] = 46.586, R2 = 0.70, P < .001) with a standardized β coefficient (-0.836).

Conclusion: The results of this study highlight that CS and LBM were the best predictors of the 3,200-m LCTT, and TLM was the best predictor of the 400-m LCTT. The findings of this study support that CS and LBM, including TLM, are important in predicting load carriage task completion in the time trial tasks.