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Background: The creation of highly muscled and strong fighters is a recurring theme in human performance enhancement concepts. Physical readiness standards, intended to prevent obesity in the military, produce contradictory objectives, hounding large individuals to lose weight because of confusion between body size and body composition. Through selection, specialised training and policy exceptions the US Marine Corps has successfully developed a unique group of large (body mass index (BMI) >30 kg/m 2 ) and strong individuals, the body bearers (BB) who carry coffins of Marines to their final resting place., Methods: We examined the relationship between adiposity and body size from nine male BB (age 25.0±2.1, height: 1.84±0.04 (1.80-1.92) m, BMI: 33.0±2.1 (30-37) kg/m 2 ). Body composition was assessed by dual-energy X-ray absorptiometry (DXA), bioelectrical impedance (BIA) and tape measured abdominal circumference (AC)-based equations and from three-dimensional scanning (3DS)., Results: Measures were made of fat-free mass (FFM): 90.5±7.0 (82.0-106.7) kg, where FFM included total body water: 62.8±5.0 (55.8-71.8) L, representing 69±2 (67-73) % of FFM, along with calculated FFM index: 26.8±2.4 (24.4-32.9) kg/m 2 ). DXA measures were made for bone mineral content 4.1±0.4 (3.5-4.9) kg, bone mineral density (BMD) 1.56±0.10 (1.37-1.76) g/cm 2 and %BF 19.5±6.6 (9.0-27.8). Additional measures of percent body fat (%BF) were made by AC: 20.3±2.9 (15.2-24.6), BIA: 23.7±6.4 (9.8-29.2) and 3DS: 25.5±4.7 (18.9-32.2). AC %BF reasonably matched DXA %BF, with expected overprediction and underprediction at low and high DXA %BF. BIA %BF was affected by deviations from assumed FFM hydration (72%-73%)., Conclusion: These men are classified as obese by BMI but carried massive amounts of muscle and bone on their large frames, while presenting a range of %BF irrelevant to strength performance. BMI did not predict obesity and adiposity had no association with muscle mass and strength performance., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: The US Army Load Carriage Decision Aid (LCDA) metabolic model is used by militaries across the globe and is intended to predict physiological responses, specifically metabolic costs, in a wide range of dismounted warfighter operations. However, the LCDA has yet to be adapted for vest-borne load carriage, which is commonplace in tactical populations, and differs in energetic costs to backpacking and other forms of load carriage., Purpose: The purpose of this study is to develop and validate a metabolic model term that accurately estimates the effect of weighted vest loads on standing and walking metabolic rate for military mission-planning and general applications., Methods: Twenty healthy, physically active military-age adults (4 women, 16 men; age, 26 ± 8 yr old; height, 1.74 ± 0.09 m; body mass, 81 ± 16 kg) walked for 6 to 21 min with four levels of weighted vest loading (0 to 66% body mass) at up to 11 treadmill speeds (0.45 to 1.97 m·s -1 ). Using indirect calorimetry measurements, we derived a new model term for estimating metabolic rate when carrying vest-borne loads. Model estimates were evaluated internally by k -fold cross-validation and externally against 12 reference datasets (264 total participants). We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured walking metabolic rate. Estimation accuracy, precision, and level of agreement were also evaluated by the bias, standard deviation of paired differences, and concordance correlation coefficient (CCC), respectively., Results: Metabolic rate estimates using the new weighted vest term were statistically equivalent ( P < 0.01) to measured values in the current study (bias, -0.01 ± 0.54 W·kg -1 ; CCC, 0.973) as well as from the 12 reference datasets (bias, -0.16 ± 0.59 W·kg -1 ; CCC, 0.963)., Conclusions: The updated LCDA metabolic model calculates accurate predictions of metabolic rate when carrying heavy backpack and vest-borne loads. Tactical populations and recreational athletes that train with weighted vests can confidently use the simplified LCDA metabolic calculator provided as Supplemental Digital Content to estimate metabolic rates for work/rest guidance, training periodization, and nutritional interventions., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)

Biomathematical models quantitatively describe human physiological responses to environmental and operational stressors and have been used for planning and real-time prevention of cold injury. These same models can be applied from a military tactical perspective to gain valuable insights into the health status of opponent soldiers. This paper describes a use case for predicting physiological status of Russian soldiers invading Ukraine using open-source information. In March 2022, media outlets reported Russian soldiers in a stalled convoy invading Ukraine were at serious risk of hypothermia and predicted these soldiers would be "freezing to death" within days because of declining temperatures (down to -20°C). Using existing Army models, clothing data and open-source intelligence, modelling and analyses were conducted within hours to quantitatively assess the conditions and provide science-based predictions. These predictions projected a significant increase in risks of frostbite for exposed skin and toes and feet, with a very low (negligible) risk of hypothermia. Several days later, media outlets confirmed these predictions, reporting a steep rise in evacuations for foot frostbite injuries in these Russian forces. This demonstrated what can be done today with the existing mathematical physiology and how models traditionally focused on health risk can be used for tactical intelligence.

Global climate change has resulted in an increase in the number and intensity of environmental heat waves, both in areas traditionally associated with hot temperatures and in areas where heat waves did not previously occur. For military communities around the world, these changes pose progressively increasing risks of heat-related illnesses and interference with training sessions. This is a significant and persistent "noncombat threat" to both training and operational activities of military personnel. In addition to these important health and safety concerns, there are broader implications in terms of the ability of worldwide security forces to effectively do their job (particularly in areas that historically already have high ambient temperatures). In the present review, we attempt to quantify the impact of climate change on various aspects of military training and performance. We also summarize ongoing research efforts designed to minimize and/or prevent heat injuries and illness. In terms of future approaches, we propose the need to "think outside the box" for a more effective training/schedule paradigm. One approach may be to investigate potential impacts of a reversal of sleep-wake cycles during basic training during the hot months of the year, to minimize the usual increase in heat-related injuries, and to enhance the capacity for physical training and combat performance. Regardless of which approaches are taken, a central feature of successful present and future interventions will be that they are rigorously tested using integrative physiological approaches.

Introduction: Physiological limits imposed by vest-borne loads must be defined for optimal performance monitoring of the modern dismounted warfighter., Purpose: To evaluate how weighted vests affect locomotion economy and relative cardiometabolic strain during military load carriage while identifying key physiological predictors of exhaustion limits., Methods: Fifteen US Army soldiers (4 women, 11 men; age, 26 ± 8 years; height, 173 ± 10 cm; body mass (BM), 79 ± 16 kg) performed four incremental walking tests with different vest loads (0, 22, 44, or 66% BM). We examined the effects of vest-borne loading on peak walking speed, the physiological costs of transport, and relative work intensity. We then sought to determine which of the cardiometabolic indicators (oxygen uptake, heart rate, respiration rate) was most predictive of task failure., Results: Peak walking speed significantly decreased with successively heavier vest loads (p < 0.01). Physiological costs per kilometer walked were significantly higher with added vest loads for each measure (p < 0.05). Relative oxygen uptake and heart rate were significantly higher during the loaded trials than the 0% BM trial (p < 0.01) yet not different from one another (p > 0.07). Conversely, respiration rate was significantly higher with the heavier load in every comparison (p < 0.01). Probability modeling revealed heart rate as the best predictor of task failure (marginal R 2 , 0.587, conditional R 2 , 0.791)., Conclusion: Heavy vest-borne loads cause exceptional losses in performance capabilities and increased physiological strain during walking. Heart rate provides a useful non-invasive indicator of relative intensity and task failure during military load carriage., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Objective: The aim of this study was to model the effect of body armor coverage on body core temperature elevation and wet-bulb globe temperature (WBGT) offset., Background: Heat stress is a critical factor influencing the health and safety of military populations. Work duration limits can be imposed to mitigate the risk of exertional heat illness and are derived based on the environmental conditions (WBGT). Traditionally a 3°C offset to WBGT is recommended when wearing body armor; however, modern body armor systems provide a range of coverage options, which may influence thermal strain imposed on the wearer., Method: The biophysical properties of four military clothing ensembles of increasing ballistic protection coverage were measured on a heated sweating manikin in accordance with standard international criteria. Body core temperature elevation during light, moderate, and heavy work was modeled in environmental conditions from 16°C to 34°C WBGT using the heat strain decision aid., Results: Increasing ballistic protection resulted in shorter work durations to reach a critical core temperature limit of 38.5°C. Environmental conditions, armor coverage, and work intensity had a significant influence on WBGT offset., Conclusion: Contrary to the traditional recommendation, the required WBGT offset was &gt;3°C in temperate conditions (&lt;27°C WBGT), particularly for moderate and heavy work. In contrast, a lower WBGT offset could be applied during light work and moderate work in low levels of coverage., Application: Correct WBGT offsets are important for enabling adequate risk management strategies for mitigating risks of exertional heat illness.

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: This 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., Methods: Thirty 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., 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 W·kg-1; CCC, 0.965) and from the seven independent data sets (bias, -0.08 ± 0.59 W·kg-1; CCC, 0.926)., Conclusions: 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., (Copyright © 2022 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Abstract: 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., (Copyright © 2022 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Introduction: Military leaders must understand how modern military equipment loads affect trade-offs between movement speed and physiological strain to optimize pacing strategies., Purpose: To evaluate the effects of load carried in a recently developed military backpack on the walking speed and cardiometabolic responses of dismounted warfighters., Methods: Fifteen soldiers (1 woman, 14 men; age, 22 ± 2 years; height, 173 ± 7 cm; body mass (BM), 73 ± 10 kg) completed incremental walking tests with four external load conditions (0, 22, 44, or 66% BM) using the US Army's newest backpack: the Modular Lightweight Load-Carrying Equipment 4000 (MOLLE 4000). Oxygen uptake (V̇O 2 ) and heart rate (HR) were evaluated relative to maximal values (V̇O 2max and HR max respectively). Testing ceased when participants completed the highest tested speed (1.97 m s -1 ), exceeded a respiratory exchange ratio (RER) of 1.00, or reached volitional exhaustion., Results: Peak speed significantly decreased (p < 0.03) with successively heavier loads (0% BM, 1.95 ± 0.06 m s -1 ; 22% BM, 1.87 ± 0.10 m s -1 ; 44% BM, 1.69 ± 0.13 m s -1 ; 66% BM, 1.48 ± 0.13 m s -1 ). Peak V̇O 2 was significantly lower (p < 0.01) with 0% BM (47 ± 5% V̇O 2max ) than each load (22% BM, 58 ± 8% V̇O 2max ; 44% BM, 63 ± 10% V̇O 2max ; 66% BM, 61 ± 11% V̇O 2max ). Peak HR was significantly lower (p < 0.01) with 0% BM (71 ± 5% HR max ) versus each load (22% BM, 83 ± 6% HR max ; 44% BM, 87 ± 6% HR max ; 66% BM, 88 ± 6% HR max )., Conclusion: Overburdened warfighters suffer severe impairments in walking speed even when carrying recently developed military load carriage equipment. Our results suggest that the relative work intensity of heavy load carriage may be better described when expressed relative to HR max versus V̇O 2max ., (Published by Elsevier Ltd.)

Objectives: We aimed to determine the agreement between actual and predicted core body temperature, using the Heat Strain Decision Aid (HSDA), in non-Ground Close Combat (GCC) personnel wearing multi terrain pattern clothing during two stages of load carriage in temperate conditions., Design: Cross-sectional., Methods: Sixty participants (men = 49, women = 11, age 31 ± 8 years; height 171.1 ± 9.0 cm; body mass 78.1 ± 11.5 kg) completed two stages of load carriage, of increasing metabolic rate, as part of the development of new British Army physical employment standards (PES). An ingestible gastrointestinal sensor was used to measure core temperature. Testing was completed in wet bulb globe temperature conditions; 1.2-12.6 °C. Predictive accuracy and precision were analysed using individual and group mean inputs. Assessments were evaluated by bias, limits of agreement (LoA), mean absolute error (MAE), and root mean square error (RMSE). Accuracy was evaluated using a prediction bias of ±0.27 °C and by comparing predictions to the standard deviation of the actual core temperature., Results: Modelling individual predictions provided an acceptable level of accuracy based on bias criterion; where the total of all trials bias ± LoA was 0.08 ± 0.82 °C. Predicted values were in close agreement with the actual data: MAE 0.37 °C and RMSE 0.46 °C for the collective data. Modelling using group mean inputs were less accurate than using individual inputs, but within the mean observed., Conclusion: The HSDA acceptably predicts core temperature during load carriage to the new British Army non-GCC PES, in temperate conditions., (Copyright © 2021. Published by Elsevier Ltd.)

Introduction: The Load Carriage Decision Aid (LCDA) is a U.S. Army planning tool that predicts physiological responses of soldiers during different dismounted troop scenarios. We aimed to develop an equation that calculates standing and walking metabolic rates in healthy military-age adults for the LCDA using a meta-regression., Methods: We searched for studies that measured the energetic cost of standing and treadmill walking in healthy men and women via indirect calorimetry. We used mixed effects meta-regression to determine an optimal equation to calculate standing and walking metabolic rates as a function of walking speed (S, m·s). The optimal equation was used to determine the economical speed at which the metabolic cost per distance walked is minimized. The estimation precision of the new LCDA walking equation was compared with that of seven reference predictive equations., Results: The meta-regression included 48 studies. The optimal equation for calculating normal standing and walking metabolic rates (W·kg) was 1.44 + 1.94S + 0.24S. The economical speed for level walking was 1.39 m·s (~ 3.1 mph). The LCDA walking equation was more precise across all walking speeds (bias ± SD, 0.01 ± 0.33 W·kg) than the reference predictive equations., Conclusion: Practitioners can use the new LCDA walking equation to calculate energy expenditure during standing and walking at speeds <2 m·s in healthy, military-age adults. The LCDA walking equation avoids the errors estimated by other equations at lower and higher walking speeds.

This study examined complex terrain march performance and cardiorespiratory responses when carrying different Soldier loads. Nine active duty military personnel (age, 21 ± 3 yr; height, 1.72 ± 0.07 m; body mass (BM), 83.4 ± 12.9 kg) attended two test visits during which they completed consecutive laps around a 2.5-km mixed terrain course with either a fighting load (30% BM) or an approach load (45% BM). Respiratory rate and heart rate data were collected using physiological status monitors. Training impulse (TRIMP) scores were calculated using Banister's formula to provide an integrated measure of both time and cardiorespiratory demands. Completion times were not significantly different between the fighting and approach loads for either Lap 1 (p = 0.38) or Lap 2 (p = 0.09). Respiration rate was not significantly higher with the approach load than the fighting load during Lap 1 (p = 0.17) but was significantly higher for Lap 2 (p = 0.04). However, heart rate was significantly higher with the approach load versus the fighting load during both Lap 1 (p = 0.03) and Lap 2 (p = 0.04). Furthermore, TRIMP was significantly greater with the approach load versus the fighting load during both Lap 1 (p = 0.02) and Lap 2 (p = 0.02). Trained military personnel can maintain similar pacing while carrying either fighting or approach loads during short mixed terrain marches. However, cardiorespiratory demands are greatly elevated with the approach load and will likely continue to rise during longer distance marches., (Copyright © 2018. Published by Elsevier Ltd.)

Introduction: Military personnel are often required to wear ballistic protection in order to defend against enemies. However, this added protection increases mass carried and imposes additional thermal burden on the individual. Body armor (BA) is known to reduce combat casualties, but the effects of BA mass and insulation on the physical performance of soldiers are less well documented. Until recently, the emphasis has been increasing personal protection, with little consideration of the adverse impacts on human performance. Objective: The purpose of this work was to use sweating thermal manikin and mathematical modeling techniques to quantify the tradeoff between increased BA protection, the accompanying mass, and thermal effects on human performance. Methods: Using a sweating thermal manikin, total insulation (IT, clo) and vapor permeability indexes (im) were measured for a baseline clothing ensemble with and without one of seven increasingly protective U.S. Army BA configurations. Using mathematical modeling, predictions were made of thermal impact on humans wearing each configuration while working in hot/dry (desert), hot/humid (jungle), and temperate environmental conditions. Results: In nearly still air (0.4 m/s), IT ranged from 1.57 to 1.63 clo and im from 0.35 to 0.42 for the seven BA conditions, compared to IT and im values of 1.37 clo and 0.45 respectively, for the baseline condition (no BA). Conclusion: Biophysical assessments and predictive modeling show a quantifiable relationship exists among increased protection and increased thermal burden and decreased work capacity. This approach enables quantitative analysis of the tradeoffs between ballistic protection, thermal-work strain, and physical work performance. [ABSTRACT FROM AUTHOR]

Introduction: The load carriage decision aid (LCDA) walking equation was developed from literature-aggregated group mean data to calculate standing and level walking energy expenditures in healthy, military-age adults. The LCDA walking equation has not been validated for use in individuals or graded walking. Purpose: We aimed to validate the LCDA walking equation as a predictor of standing and level walking energy expenditure in individuals and expand to a new graded walking equation for uphill and downhill walking. Methods: We compiled standing, level walking, and graded walking energy expenditures measured in 95 participants from 11 studies. Walking speeds reached up to 1.96 m·s−1 with grades ranging between −40% and 45%. The LCDA walking equation was validated against the aggregated standing and level walking data. The new LCDA graded walking equation was developed and cross-validated on the graded walking trials. We compared each equation against four reference predictive equations with the standard error of estimation (SEE) as the primary criterion. Results: The LCDA walking equation accurately estimated standing and level walking energy expenditure (bias, −0.02 ± 0.20 W·kg−1; SEE, 0.20 W·kg−1). Addition of the novel grade term resulted in precise estimates of uphill and downhill walking energy expenditure (bias, 0.09 ± 0.40 W·kg−1; SEE, 0.42 W·kg−1). Conclusions: The LCDA walking equation is a valid predictor of standing and walking energy expenditure in healthy, military-age individuals. We developed a novel grade term for estimating both uphill and downhill walking energy expenditure with a single equation. Practitioners can use the new LCDA graded walking equation to calculate energy expenditure during standing as well as walking on level, uphill, and downhill slopes. [ABSTRACT FROM AUTHOR]

Introduction: Military load carriage can cause extreme energy expenditure (EE) that is difficult to estimate due to complex terrain grades and surfaces. Global Positioning System (GPS) devices capture rapid changes in walking speed and terrain but the delayed respiratory response to movement is problematic. We investigated the accuracy using GPS data in three different equations to estimate EE during complex terrain load carriage. Methods: Twelve active duty military personnel (age, 20 ± 3 yr; height, 174 ± 8 cm; body mass, 85 ± 13 kg) hiked a complex terrain trail on multiple visits under different external load conditions. Energy expenditure was estimated by inputting GPS data into three different equations: the Pandolf–Santee equation, a recent GPS-based equation from de Müllenheim et al.; and the Minimum Mechanics model. Minute-by-minute EE estimates were exponentially smoothed using smoothing factors between 0.05 and 0.95 and compared with mobile metabolic sensor EE measurements. Results: The Pandolf–Santee equation had no significant estimation bias (−2 ± 12 W; P = 0.89). Significant biases were detected for the de Müllenheim equation (38 ± 13 W; P = 0.004) and the Minimum Mechanics model (−101 ± 7 W; P < 0.001). Conclusions: Energy expenditure can be accurately estimated from GPS data using the Pandolf–Santee equation. Applying a basic exponential smoothing factor of 0.5 to GPS data enables more precise tracking of EE during non–steady-state exercise. [ABSTRACT FROM AUTHOR]

Quantifying the metabolic costs of carrying or wearing various military uniform components is essential for accurate assessment of the metabolic cost of warfighters performing military tasks under scenarios and environmental conditions. PURPOSE: Evaluate the metabolic demand of walking at incremental speeds in a controlled laboratory environment while wearing military-issued combat boots compared to athletic sneakers. METHODS: In this randomized, cross-over study, nineteen active military-age men (age, 24 ± 5 years; height, 177 ± 6 cm; body mass, 80 ± 13 kg) performed an incremental treadmill walking test in combat boots and athletic sneakers on separate visits. Treadmill speed started at 4.18 km/h for 3 min, then increased by 0.23 km/h every 2 min. Tests were terminated when volunteers either completed the highest treadmill speed (7.08 km/h), reached volitional fatigue, or exceeded a respiratory exchange ratio of 1.0. Volunteers exhaled into a laboratory metabolic cart that measured expired gases. Metabolic demand was quantified as the average oxygen uptake (...O2) over the final minute of each walking speed. RESULTS: Across all speeds, walking in combat boots resulted in significantly higher ...O2 than walking in athletic sneakers (0.63 ± 1.05 mL⋅kg-1⋅min-1; p = 0.01). Regression analysis determined a V O2 difference between footwear of 0.31 mL⋅kg-1⋅min-1 at 4.18 km/h that increased by 0.22 mL⋅kg-1⋅min-1 with each 1 km/h increase (R², 0.68). Regressing walking ...O2 when wearing combat boots on walking ...O2 while wearing athletic sneakers revealed both a positive offset and slope (Trendline, ...O2boots = 0.04 + 1.04- ...O2sneakers; R², 0.97). CONCLUSIONS: The metabolic demand of walking in military combat boots is greater and more pronounced at increased walking speeds than when wearing common athletic sneakers. The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of Army, Department of Defense, or the U.S. Government. [ABSTRACT FROM AUTHOR]

Body surface area (BSA) is an important measurement for many thermophysiological, pharmaceutical, toxicological, environmental, and military applications. Unfortunately, BSA is difficult to quantify, and existing prediction methods are not optimized for contemporary populations. The present study analyzed data body measurements from 5603 male and female participants of a US Army Anthropometric Survey to determine optimal methods for estimating BSA in modern US Army Soldiers. This data included 94 individual body measurements as well as three dimensional (3D) whole body scans for each participant. We used this data to assess and compared 15 existing equations to the measured data. We also derived best fitting nonlinear regression models for estimating BSA from different combinations of sex, height, and weight and iteratively included the remaining 91 measurements to determine which combinations resulted in the highest goodness-of-fit. We found that inclusion of armspan measurements as a third body dimension maximized the model goodness-of-fit. Some of the existing formulae provide reasonable estimates of 3D-scanner derived BSA; while our new formulae derived from this study allows for more accurate estimates of BSA using one or more common input variables. • Uses an extensive anthropometic database that includes 94 direct measures along with 3D body scans. • Compares accuracy of existing methods for estimating body surface area to a dataset of 5,603 male and females. • Provides an improved method for body surface area calculation. • Includes a supplemental Excel file with new formulae embedded for easy use. • Provides evidence to support the inclusion of an additional measure of armspan in body composition assessments. [ABSTRACT FROM AUTHOR]