Metabolic Costs of Walking with Weighted Vests.

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.

Peak performance and cardiometabolic responses of modern US army soldiers during heavy, fatiguing vest-borne load carriage.

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 R2, 0.587, conditional R2, 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.

Changes in Immune Function during Initial Military Training.

PURPOSE: Initial military training (IMT) is a transitionary period wherein immune function may be suppressed and infection risk heightened due to physical and psychological stress, communal living, and sleep deprivation. This study characterized changes in biomarkers of innate and adaptive immune function, and potential modulators of those changes, in military recruits during IMT. METHODS: Peripheral leukocyte distribution and mitogen-stimulated cytokine profiles were measured in fasted blood samples, Epstein-Barr (EBV), varicella zoster (VZV), and herpes simplex 1 (HSV1) DNA was measured in saliva by quantitative polymerase chain reaction as an indicator of latent herpesvirus reactivation, and diet quality was determined using the healthy eating index measured by food frequency questionnaire in 61 US Army recruits (97% male) at the beginning (PRE) and end (POST) of 22-wk IMT. RESULTS: Lymphocytes and terminally differentiated cluster of differentiation (CD)4+ and CD8+ T cells increased PRE to POST, whereas granulocytes, monocytes, effector memory CD4+ and CD8+ T cells, and central memory CD8+ T cells decreased ( P ≤ 0.02). Cytokine responses to anti-CD3/CD28 stimulation were higher POST compared with PRE, whereas cytokine responses to lipopolysaccharide stimulation were generally blunted ( P < 0.05). Prevalence of EBV reactivation was higher at POST ( P = 0.04), but neither VZV nor HSV1 reactivation was observed. Diet quality improvements were correlated with CD8+ cell maturation and blunted proinflammatory cytokine responses to anti-CD3/CD28 stimulation. CONCLUSIONS: Lymphocytosis, maturation of T-cell subsets, and increased T-cell reactivity were evident POST compared with PRE IMT. Although EBV reactivation was more prevalent at POST, no evidence of VZV or HSV1 reactivation, which are more common during severe stress, was observed. Findings suggest increases in the incidence of EBV reactivation were likely appropriately controlled by recruits and immune-competence was not compromised at the end of IMT.

Initial military training modulates serum fatty acid and amino acid metabolites.

Initial military training (IMT) results in increased fat-free mass (FFM) and decreased fat mass (FM). The underlying metabolic adaptations facilitating changes in body composition during IMT are unknown. The objective of this study was to assess changes in body composition and the serum metabolome during 22-week US Army IMT. Fifty-four volunteers (mean ± SD; 22 ± 3 year; 24.6 ± 3.7 kg/m2 ) completed this longitudinal study. Body composition measurements (InBody 770) and blood samples were collected under fasting, rested conditions PRE and POST IMT. Global metabolite profiling was performed to identify metabolites involved in energy, carbohydrate, lipid, and protein metabolism (Metabolon, Inc.). There was no change in body mass (POST-PRE; 0.4 ± 5.1 kg, p = 0.59), while FM decreased (-1.7 ± 3.5 kg, p < 0.01), and FFM increased (2.1 ± 2.8 kg, p < 0.01) POST compared to PRE IMT. Of 677 identified metabolites, 340 differed at POST compared to PRE (p < 0.05, Q < 0.10). The majority of these metabolites were related to fatty acid (73%) and amino acid (26%) metabolism. Increases were detected in 41% of branched-chain amino acid metabolites, 53% of histidine metabolites, and 35% of urea cycle metabolites. Decreases were detected in 93% of long-chain fatty acid metabolites, while 58% of primary bile acid metabolites increased. Increases in amino acid metabolites suggest higher rates of protein turnover, while changes in fatty acid metabolites indicate increased fat oxidation, which likely contribute changes in body composition during IMT. Overall, changes in metabolomics profiles provide insight into metabolic adaptions underlying changes in body composition during IMT.

A digital tool for prevention and management of cold weather injuries-Cold Weather Ensemble Decision Aid (CoWEDA).

This paper describes a Cold Weather Ensemble Decision Aid (CoWEDA) that provides guidance for cold weather injury prevention, mission planning, and clothing selection. CoWEDA incorporates current science from the disciplines of physiology, meteorology, clothing, and computer modeling. The thermal performance of a cold weather ensemble is defined by endurance times, which are the time intervals from initial exposure until the safety limits are reached. These safety limits correspond to conservative temperature thresholds that provide a warning of the approaching onset of frostbite and/or hypothermia. A validated six-cylinder thermoregulatory model is used to predict human thermal responses to cold while wearing different ensembles. The performance metrics, model, and a database of clothing properties were integrated into a user-friendly software application. CoWEDA is the first tool that allows users to build their own ensembles from the clothing menu (i.e., jackets, footwear, and accessories) for each body region (i.e., head, torso, lower body, hands, feet) and view their selections in the context of physiological strain and the operational consequences. Comparison of predicted values to skin and core temperatures, measured during 17 cold exposures ranging from 0 to -40°C, indicated that the accuracy of CoWEDA prediction is acceptable, and most predictions are within measured mean ± SD. CoWEDA predicts the risk of frostbite and hypothermia and ensures that a selected clothing ensemble is appropriate for expected weather conditions and activities. CoWEDA represents a significant enhancement of required clothing insulation (IREQ, ISO 11079) and wind chill index-based guidance for cold weather safety and survival.

Predicting military working dog core temperature during exertional heat strain: Validation of a Canine Thermal Model.

Military working dogs (MWDs) operate under a wide range of conditions, including hot environments. Predicting how long a MWD can safely work without overheating is important for both health and performance. A Canine Thermal Model (CTM) was developed to predict core temperature (Tc) of MWDs. The CTM calculates heat storage from the balance of heat production from metabolism and heat exchange with the environment. Inputs to the CTM are: meteorological conditions (ambient temperature, relative humidity, solar radiation and wind speed), physical characteristics of the dog (mass, length), and metabolic activity (MET level, estimated from accelerometer data). The CTM was validated against Tc measured in 23 MWDs during training sessions (11.6 ± 5.0 min (mean ± standard deviation), range 4-26 min) in October (24 °C, 52% RH), March (14 °C, 74% RH), or August (28 °C, 64% RH), and 24 kennel MWDs during a standard exercise walk (11.4 ± 3.3 min, range 5.6-18 min) in July (26 °C, 77% RH). The CTM was considered acceptable if predicted Tc was within ±0.5 °C of measured Tc at the end of exercise. Compared to Tc at the end of training sessions (39.8 ± 0.6 °C, range 38.4-41.1 °C) and exercise walks (40.0 ± 0.7 °C, range 38.9-41.4 °C), the CTM-predicted Tc was within ±0.5 °C for 71 of 84 cases (85%) and 19 of 24 cases (79%), respectively. The mean difference between CTM-predicted and measured final Tc during training was -0.04 ± 0.43 °C, with 80 of 84 cases (95%) within the range of ±2 SD (Bland Altman comparison). During exercise walks the mean difference was -0.15 °C ± 0.57, with 23 of 24 cases (96%) within ±2 SD. These results support the use of the CTM to predict Tc of MWDs for the types of physical activities described above.

Cardiorespiratory responses to heavy military load carriage over complex terrain.

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.

Complex Terrain Load Carriage Energy Expenditure Estimation Using Global Positioning System Devices.

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.

Metabolic Costs of Military Load Carriage over Complex Terrain.

INTRODUCTION: Dismounted military operations often involve prolonged load carriage over complex terrain, which can result in excessive metabolic costs that can directly impair soldiers' performance. Although estimating these demands is a critical interest for mission planning purposes, it is unclear whether existing estimation equations developed from controlled laboratory- and field-based studies accurately account for energy costs of traveling over complex terrain. This study investigated the accuracy of the following equations for military populations when applied to data collected over complex terrain with two different levels of load carriage: American College of Sports Medicine (2002), Givoni and Goldman (1971), Jobe and White (2009), Minetti et al (2002), Pandolf et al (1977), and Santee et al (2003). MATERIALS AND METHODS: Nine active duty military personnel (age 21 ± 3 yr; height 1.72 ± 0.07 m; body mass 83.4 ± 12.9 kg; VO2 max 47.8 ± 3.9 mL/kg/min) were monitored during load carriage (with loads equal to 30% and 45% of body mass) over a 10-km mixed terrain course on two separate test days. The course was divided into four 2.5-km laps of 40 segments based on distance, grade, and/or surface factors. Timing gates and radio-frequency identification cards (SportIdent; Scarborough Orienteering, Huntington Beach, CA) were used to record completion times for each course segment. Breath-by-breath measures of energy expenditure were collected using portable oxygen exchange devices (COSMED Sri., Rome, Italy) and compared model estimates. RESULTS: The Santee et al equation performed best, demonstrating the smallest estimation bias (-13 ± 87 W) and lowest root mean square error (99 W). CONCLUSION: Current predictive equations underestimate the metabolic cost of load carriage by military personnel over complex terrain. Applying the Santee et al correction factor to the Pandolf et al equation may be the most suitable approach for estimating metabolic demands in these circumstances. However, this work also outlines the need for improvements to these methods, new method development and validation, or the use of a multi-model approach to account for mixed terrain.

Core temperature responses of military working dogs during training activities and exercise walks.

Heat strain is common in military working dogs (MWDs), but can be mitigated by limiting duration of activity to avoid overheating and allowing sufficient time for recovery. To determine work/rest times for MWDs, temperature responses during training must be characterized. This study measured body core temperature of 48 MWDs at Lackland Air Force Base, San Antonio, TX. Twenty-four MWDs in training for patrol and detection activities participated under a range of ambient temperatures in August (27°C-32°C), October (22°C-26°C) and March (approximately 13°C). These MWDs swallowed a telemetric thermometer pill to measure continuous gastrointestinal tract temperature (Tgi). Twenty-four kennel MWDs participated in July (25°C-29°C). In these dogs rectal temperature (Tre) was measured manually during a standard exercise walk. For the MWDs in training, Tgi before the first activity was 38.5±0.5°C (mean±SD) and final Tgi was 39.8±0.6°C after sessions that lasted 13.1±4.9 minutes (5.4 to 26.3 minutes). Peak Tgi, 0.4±0.4°C above final Tgi, occurred 8 to 12 minutes into recovery. Before beginning a second activity 40 to 165 minutes later, Tgi was within 0.5°C of initial values for 80% of dogs. For the kennel MWDs, Tre was 39.0±0.8°C (37.7°C to 40.7°C) at the start and 40.1±0.6°C at the end of the 21.3±2.8 minute walk. The continuous increase in core temperature during activity of both groups of MWDs indicates that limiting exercise duration is important for minimizing risk of overheating in MWDs. The observation of continued increase in Tgi to a peak after exercise ends suggests that for MWDs suspected of overheating temperature should be monitored for at least 15 minutes postexercise to ensure recovery.

Cardiovascular and thermal strain during 3-4 days of a metabolically demanding cold-weather military operation.

BACKGROUND: Cardiovascular (CV) and thermal responses to metabolically demanding multi-day military operations in extreme cold-weather environments are not well described. Characterization of these operations will provide greater insights into possible performance capabilities and cold injury risk. METHODS: Soldiers from two cold-weather field training exercises (FTX) were studied during 3-day (study 1, n = 18, age: 20 ± 1 year, height: 182 ± 7 cm, mass: 82 ± 9 kg) and 4-day (study 2, n = 10, age: 20 ± 1 year, height: 182 ± 6 cm, mass: 80.7 ± 8.3 kg) ski marches in the Arctic. Ambient temperature ranged from -18 to -4 °C during both studies. Total daily energy expenditure (TDEE, from doubly labeled water), heart rate (HR), deep body (Tpill), and torso (Ttorso) skin temperature (obtained in studies 1 and 2) as well as finger (Tfing), toe (Ttoe), wrist, and calf temperatures (study 2) were measured. RESULTS: TDEE was 6821 ± 578 kcal day-1 and 6394 ± 544 for study 1 and study 2, respectively. Mean HR ranged from 120 to 140 bpm and mean Tpill ranged between 37.5 and 38.0 °C during skiing in both studies. At rest, mean Tpill ranged from 36.0 to 36.5 °C, (lowest value recorded was 35.5 °C). Mean Tfing ranged from 32 to 35 °C during exercise and dropped to 15 °C during rest, with some Tfing values as low as 6-10 °C. Ttoe was above 30 °C during skiing but dropped to 15-20 °C during rest. CONCLUSIONS: Daily energy expenditures were among the highest observed for a military training exercise, with moderate exercise intensity levels (~65% age-predicted maximal HR) observed. The short-term cold-weather training did not elicit high CV and Tpill strain. Tfing and Ttoe were also well maintained while skiing, but decreased to values associated with thermal discomfort at rest.

Biophysical Assessment and Predicted Thermophysiologic Effects of Body Armor.

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.

Effect of WBGT Index Measurement Location on Heat Stress Category Classification.

UNLABELLED: The location of the wet bulb globe temperature (WBGT) index measurement may affect heat stress flag category classification. PURPOSE: This study aimed to compare WBGT measurements at three locations along the Boston Marathon race course and compare WBGT estimates for meteorological stations and 72-h advanced WBGT forecasts. METHODS: WBGT was measured hourly from 1000 to 1400 h at approximately 7 km, approximately 18 km, and approximately 30 km on the Boston Marathon race course. Simultaneous WBGT estimates were made for two meteorological stations southeast of the course via a commercial online system, which also provided 72-h advanced forecasts. RESULTS: The measurement difference (mean ± SD) among course locations was 0.2°C ± 1.8°C WBGT (ANOVA, P > 0.05). The difference between course and stations was 1.9°C ± 2.4°C WBGT (t-test, P < 0.05). Station values underestimated (n = 98) or overestimated (n = 13) course values by >3°C WBGT (>0.5 flag category) in 111 of 245 paired comparisons (45%). Higher black globe and lower wet bulb temperatures explained over- and underestimates, respectively. Significant underestimates of WBGT resulted in misclassification of green (labeled white) and black (labeled red) course flag categories (χ2, P < 0.05). Forecast data significantly underestimated red (labeled amber) and black (labeled red) course flag categories. CONCLUSIONS: Differences in WBGT index along 23 km of the Boston Marathon race route can be small enough to warrant single measurements. However, significant misclassification of flag categories occurred using WBGT estimates for meteorological stations; thus, local measurements are preferred. If the relation between station WBGT forecasts and the race sites can be established, the forecast WBGT values could be corrected to give advanced warning of approximate flag conditions. Similar work is proposed for other venues to improve heat stress monitoring.

Relationship between core temperature, skin temperature, and heat flux during exercise in heat.

PURPOSE: This paper investigates the relationship between core temperature (T c), skin temperature (T s) and heat flux (HF) during exercise in hot conditions. METHOD: Nine test volunteers, wearing an Army Combat Uniform and body armor, participated in three sessions at 25 °C/50 % relative humidity (RH); 35 °C/70 % RH; and 42 °C/20 % RH. Each session consisted of two 1-h treadmill walks at ~350 W and ~540 W intensity. T s and HF from six sites on the forehead, sternum, pectoralis, left rib cage, left scapula, and left thigh, and T c (i.e., core temperature pill used as a suppository) were measured. Multiple linear regressions were conducted to derive algorithms that estimate T c from T s and HF at each site. A simple model was developed to simulate influences of thermal conductivity and thickness of the local body tissues on the relationship between T c, T s, and HF. RESULTS: Coefficient of determination (R (2)) ranged from 0.30 to 0.88, varying with locations and conditions. Good sites for T c measurement at surface were the sternum, and a combination of the sternum, scapula, and rib sites. The combination of T s and HF measured at the sternum explained ~75 % or more of variance in observed T c in hot environments. The forehead was found unsuitable for exercise in heat due to sweating and evaporative heat loss. The derived algorithms are likely applicable only for the same ensemble or ensembles with similar thermal and vapor resistances. CONCLUSION: Algorithms for T c measurement are location-specific and their accuracy is dependent, to a large degree, on sensor placement.

Applications of real-time thermoregulatory models to occupational heat stress: validation with military and civilian field studies.

A real-time thermoregulatory model using noninvasive measurements as inputs was developed for predicting physiological responses of individuals working long hours. The purpose of the model is to reduce heat-related injuries and illness by predicting the physiological effects of thermal stress on individuals while working. The model was originally validated mainly by using data from controlled laboratory studies. This study expands the validation of the model with field data from 26 test volunteers, including US Marines, Australian soldiers, and US wildland fire fighters (WLFF). These data encompass a range of environmental conditions (air temperature: 19-30° C; relative humidity: 25-63%) and clothing (i.e., battle dress uniform, chemical-biological protective garment, WLFF protective gear), while performing diverse activities (e.g., marksmanship, marching, extinguishing fires, and digging). The predicted core temperatures (Tc), calculated using environmental, anthropometric, clothing, and heart rate measures collected in the field as model inputs, were compared with subjects' Tc collected with ingested telemetry temperature pills. Root mean standard deviation (RMSD) values, used for goodness of fit comparisons, indicated that overall, the model predictions were in close agreement with the measured values (grand mean of RMSD: 0.15-0.38° C). Although the field data showed more individual variability in the physiological data relative to more controlled laboratory studies, this study showed that the performance of the model was adequate.