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.

The normal relationship between fat and lean mass for mature (21-30 year old) physically fit men and women

OBJECTIVE

Determine if relative body fat (%BF) remains a biological norm in physically active, non-obese American men and women and determine reference values for other components of body composition.

METHODS

Participants (n = 174 men, 70 women) were physically fit U.S. Marine 2nd Lieutenants, in their third decade of physical maturity (age 21-30). Body composition was assessed by dual-energy x-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA); and body images were obtained by 3D body scans.

RESULTS

For men and women, respectively, %BF averaged 16.2 ± 4.1 (median 15.3), 24.3 ± 4.5 (median 23.8); fat-free mass (FFM): 67.7 ± 7.2, 49.4 ± 5.3 kg; FFM index: 21.5 ± 1.8, 18.3 ± 1.6 kg/m2 ; and body mass index (BMI): 25.5 ± 1.9, 24.1 ± 2.2 kg/m2 . Bone mineral content (BMC) was 5% of FFM; total body water (TBW) was 70%-72% of FFM. Physique remained similar between median and higher percentiles of %BF. Only small changes in key measures were noted across the six-month training program.

CONCLUSIONS

Mean %BF of healthy active men and women in 2021 remains very similar to the 15% and 25% posited in 1980, suggesting that relative body fat has a normal fat-lean relationship in physically mature humans. These data may bring new attention to sex-appropriate %BF.

Human performance and medical treatment during cold weather operations - synthesis of a symposium

In October 2022, the Human Factors and Medicine (HFM) panel of the NATO Science and Technology Organization convened a review of progress in military biomedical research for cold weather operations. This paper represents a summary of the research presentations and future directions. The importance of realistic training was an overarching theme. Many reported studies took advantage of cold weather training exercises to monitor soldiers' health and performance; these are valuable data, using winter exercises as a platform to gain further knowledge regarding human performance in the cold and represent an excellent extension of controlled laboratory studies. Topics also included prevention of Cold Weather Injuries (CWI); effects of cold weather stressors on cognitive function; field treatment of freezing cold injuries (FCI); and new consideration to injury and trauma care in the cold. Future work programmes re-emphasise development of cold weather training and establishment of consensus diagnostic criteria and treatments for FCI and non-FCI. CWI prevention should take advantage of biomathematical models that predict risk of CWI and provide guidance regarding optimal clothing and equipment and move from group averages to personalised predictions. The publication of selected presentations from the symposium in this special issue increases attention to military cold weather research.

The classification of freezing cold injuries - a NATO research task group position paper

INTRODUCTION

Freezing cold injuries (FCI) are a common risk in extreme cold weather operations. Although the risks have long been recognised, injury occurrences tend to be sparse and geographically distributed, with relatively few cases to study in a systematic way. The first challenge to improve FCI medical management is to develop a common nomenclature for FCI classification. This is critical for the development of meaningful epidemiological reports on the magnitude and severity of FCI, for the standardisation of patient inclusion criteria for treatment studies, and for the development of clinical diagnosis and treatment algorithms.

METHODOLOGY

A scoping review of the literature using PubMed and cross-checked with Google Scholar, using search terms related to freezing cold injury and frostbite, highlighted a paucity of published clinical papers and little agreement on classification schemes.

RESULTS

A total of 74 papers were identified, and 28 were included in the review. Published reports and studies can be generally grouped into four different classification schemes that are based on (1) injury morphology; (2) signs and symptoms; (3) pathophysiology; and (4) clinical outcome. The nomenclature in the different classification systems is not coherent and the discrete classification limits are not evidence based.

CONCLUSIONS

All the classification systems are necessary and relevant to FCI medical management for sustainment of soldier health and performance in cold weather operations and winter warfare. Future FCI reports should clearly characterise the nature of the FCI into existing classification schemes for surveillance (morphology, symptoms, and appearance), identifying risk-factors, clinical guidelines, and agreed inclusion/exclusion criteria for a future treatment trial.

Use case for predictive physiological models: tactical insights about frozen Russian soldiers in Ukraine

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.

Introduction: Training is more important than technology (for performance in the cold)

After more than 50 years of studying soldiers in the cold, we are well past the phase of defining the unique problems; the research requirements are known but the solutions have been slow in coming. This requires iterative testing of proposed lab-based solutions with soldiers in the real environment. Representing a renewed effort to produce and implement solutions to human biomedical challenges in Arctic operations, this journal supplement highlights presentations from a three-day NATO Human Factors and Medicine panel-sponsored symposium in Washington DC in October 2022. While technology can certainly aid soldiers in extreme environments, it is ultimately training that is the most important factor for ensuring optimal performance and survival. By investing in the development of specialized Arctic forces training and implementing new solutions to protect their health and performance, we can ensure success in the coldest and harshest of environments.

Physical performance and body composition reference values for modern US Marine Corps women

Women's roles in the US military have progressively changed over the past several decades. Previously women were barred from combat roles. Recent change in policy allow women into combat roles in the Marine Corps, and this has led to women being trained for combat specialties.

Objectives

This observational cross-sectional study describes body composition and performance values for modern Marine Corps women.

Methods

Volunteers were 736 Marine women who were assessed for body composition and physical performance; (age 29.5±7.3 (18-56) years; height 163.6±6.8 (131.0-186.1) cm; body mass 68.3±9.2 (42.0-105.3) kg; years in the military 8.9±6.8 (0.5-37) years-in-service). Body composition measures were obtained using dual-energy X-ray absorptiometry and single-frequency bioelectrical impedance analyses. Performance measures were obtained from official physical and combat fitness test scores (PFT; CFT) as well as from data on measured countermovement jumps (CMJ) on a calibrated force platform.

Results

Mean body composition metrics for Marine women were: 47.5±5.7 fat free mass (FFM) (kg), 30.1%±6.4% body fat (%BF), 2.6±0.3 bone mineral content (kg), and 25.5±2.8 body mass index (kg/m2); performance metrics included 43.4±3.2 maximal oxygen uptake (VO2max; mL.kg.min), 22.4±7.1 CMJ height (cm) and 2575±565.2 CMJ peak power (W). Data showed strong correlations (r) (≥0.70) between PFT and VO2max scores (0.75), and moderate correlations (≥0.50) between CFT and VO2max scores (0.57), CFT and PFT scores (0.60), FFM and CMJ peak power (W) (0.68), and %BF to VO2max (-0.52), PFT (-0.54), CMJ-Ht (-0.52) and CMJ relative power (W/kg) (-0.54).

Conclusion

Modern Marine women are both lean and physically high performing. Body composition is a poor predictor of general physical performance.

US Army basic combat training alters the relationship between body mass index and per cent body fat

INTRODUCTION/BACKGROUND

As a proxy for adiposity, body mass index (BMI) provides a practical public health metric to counter obesity-related disease trends. On an individual basis, BMI cannot distinguish fat and lean components of body composition. Further, the relationship between BMI and body composition may be altered in response to physical training. We investigated this dynamic relationship by examining the effect of US Army basic combat training (BCT) on the association between BMI and per cent body fat (%BF).

METHODS

BMI and %BF were measured at the beginning (week 1) and end (week 9) of BCT in female (n=504) and male (n=965) trainees. Height and weight were obtained for BMI, and body composition was obtained by dual X-ray absorptiometry. Sensitivity and specificity of BMI-based classification were determined at two BMI thresholds (25 kg/m2 and 27.5 kg/m2).

RESULTS

A progressive age-related increase in fat-free mass index (FFMI) was observed, with an inflection point at age 21 years. In soldiers aged 21+, BMI of 25.0 kg/m2 predicted 33% and 29% BF in women and 23% and 20% BF in men and BMI of 27.5 kg/m2 predicted 35% and 31% BF in women and 26% and 22% BF in men, at the start and end of BCT, respectively. Sensitivity and specificity of BMI-based classification of %BF were poor. Soldiers below BMI of 20 kg/m2 had normal instead of markedly reduced %BF, reflecting especially low FFMI.

CONCLUSIONS

BCT alters the BMI-%BF relationship, with lower %BF at a given BMI by the end of BCT compared with the beginning, highlighting the unreliability of BMI to try to estimate body composition. The specific BMI threshold of 25.0 kg/m2, defined as 'overweight', is an out-of-date metric for health and performance outcomes. To the extent that %BF reflects physical readiness, these data provide evidence of a fit and capable military force at BMI greater than 25.0 kg/m2.

Physiology of Health and Performance: Enabling Success of Women in Combat Arms Roles

INTRODUCTION

The modern female soldier has yet to be fully characterized as she steps up to fill new combat roles that have only recently been opened to women. Both U.S. and U.K. military operational research efforts are supporting a science-based evolution of physical training and standards for female warfighters. The increasing representation of women in all military occupations makes it possible to discover and document the limits of female physiological performance.

METHOD

An informal Delphi process was used to synthesize an integrated concept of current military female physiological research priorities and emerging findings using a panel of subject matter experts who presented their research and perspectives during the second Women in Combat Summit hosted by the TriService Nursing Research Program in February 2021.

RESULTS

The physical characteristics of the modern soldier are changing as women train for nontraditional military roles, and they are emerging as stronger and leaner. Capabilities and physique will likely continue to evolve in response to new Army standards and training programs designed around science-based sex-neutral requirements. Strong bones may be a feature of the female pioneers who successfully complete training and secure roles traditionally reserved for men. Injury risk can be reduced by smarter, targeted training and with attention directed to female-specific hormonal status, biomechanics, and musculoskeletal architecture. An "estrogen advantage" appears to metabolically support enhanced mental endurance in physically demanding high-stress field conditions; a healthy estrogen environment is also essential for musculoskeletal health. The performance of female soldiers can be further enhanced by attention to equipment that serves their needs with seemingly simple solutions such as a suitable sports bra and personal protective equipment that accommodates the female anatomy.

CONCLUSIONS

Female physiological limits and performance have yet to be adequately defined as women move into new roles that were previously developed and reserved for men. Emerging evidence indicates much greater physical capacity and physiological resilience than previously postulated.

Body composition changes during 8 weeks of military training are not accurately captured by circumference-based assessments

In 1981, the US military adopted body fat standards to promote physical readiness and prevent obesity. Separate circumference-based equations were developed for women and men. Both predictive equations were known to underestimate %BF. However, it was not known how well these abdominal circumference-based methods tracked changes in %BF. This study examined the validity of the circumference-based %BF equations for assessing changes in %BF in young adult recruits during Army Basic Combat Training (BCT). Dual-energy X-ray absorptiometry (DXA) and circumference-based measures of %BF were obtained in women (n = 481) and men (n = 926) at the start (pre-BCT) and end (post-BCT) of 8 weeks of BCT. Repeated-measure ANOVAs were used to assess differences between DXA and circumference pre-BCT and for the change during BCT. Pre-BCT, circumferences underestimated %BF relative to DXA, with mean errors of -6.0% ± 4.4% for women and -6.0% ± 3.5% for men (both p < 0.01), and no difference between sexes was observed (p = 0.77). DXA detected a -4.0% ± 2.4% and -3.3% ± 2.8% change in %BF for women and men in response to BCT, respectively (both p < 0.01), whereas circumference estimates of %BF indicated a 0.0% ± 3.3% (p = 0.86) change in women and a -2.2% ± 3.3% (p < 0.01) change in men (sex difference by technique p < 0.01). In conclusion, circumference-based measures underestimated %BF at the start of BCT in both sexes as compared to DXA. Circumference measures underestimated changes in %BF during BCT in men and did not detect changes in women. These findings suggest that circumference-based %BF metrics may not be an appropriate tool to track changes in body composition during short duration training.

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.

With life there is motion. Activity biomarkers signal important health and performance outcomes

Measures of human motion provide a rich source of health and physiological status information. This paper provides examples of motion-based biomarkers in the form of patterns of movement, quantified physical activity, and characteristic gaits that can now be assessed with practical measurement technologies and rapidly evolving physiological models and algorithms, with research advances fed by the increasing access to motion data and associated contextual information. Quantification of physical activity has progressed from step counts to good estimates of energy expenditure, useful to weight management and to activity-based health outcomes. Activity types and intensity durations are important to health outcomes and can be accurately classified even from carried smart phone data. Specific gaits may predict injury risk, including some re-trainable injurious running or modifiable load carriage gaits. Mood status is reflected in specific types of human movement, with slumped posture and shuffling gait signaling depression. Increased variability in body sway combined with contextual information may signify heat strain, physical fatigue associated with heavy load carriage, or specific neuropsychological conditions. Movement disorders might be identified earlier and chronic diseases such as Parkinson's can be better medically managed with automatically quantified information from wearable systems. Increased path tortuosity suggests head injury and dementia. Rapidly emerging wear-and-forget systems involving global positioning system and inertial navigation, triaxial accelerometry, smart shoes, and functional fiber-based clothing are making it easier to make important health and performance outcome associations, and further refine predictive models and algorithms that will improve quality of life, protect health, and enhance performance.

Body surface area equations for physically active men and women

OBJECTIVES

To improve predictive formulae for estimating body surface area (BSA) in healthy men and women using a modern three-dimensional scanner technology.

METHODS

Body surface areas were obtained from a convenience sample of 1267 US Marines (464 women and 803 men) using a whole body surface scanner (Size Stream SS20). The reliability of SS20 measures of total and regional BSA within participants was compared across triplicate scans. We then derived a series of formulae to estimate SS20-measured BSA using various combinations of sex, height, and mass. We also assessed relationships between percent body fat measured by dual-energy x-ray absorptiometry and sex-specific formulae errors in Marines.

RESULTS

Body surface areas recorded by the SS20 were highly reliable whether measured for the total body or by region (ICC ≥ .962). Formulae estimates of BSA from sex, height, and mass were precise (root-mean-square deviation, 0.031 m² ). Errors from the Marine Corps formulae were positively associated with percent body fat for men (p = .001) but not women (p = .843).

CONCLUSIONS

Clinicians, military leaders, and researchers can use the newly developed BSA formulae for precise estimates in healthy physically active men and women. Users should be aware that height- and mass-based BSA estimates are less accurate for individuals with extremely low or high percent body fat.

Military Body Composition Standards and Physical Performance: Historical Perspectives and Future Directions

ABSTRACT

Harty, PS, Friedl, KE, Nindl, BC, Harry, JR, Vellers, HL, and Tinsley, GM. Military body composition standards and physical performance: historical perspectives and future directions. J Strength Cond Res 36(12): 3551-3561, 2022-US military physique and body composition standards have been formally used for more than 100 years. These metrics promote appropriate physical fitness, trim appearance, and long-term health habits in soldiers, although many specific aspects of these standards have evolved as evidence-based changes have emerged. Body composition variables have been shown to be related to many physical performance outcomes including aerobic capacity, muscular endurance, strength and power production, and specialized occupational tasks involving heavy lifting and load carriage. Although all these attributes are relevant, individuals seeking to improve military performance should consider emphasizing strength, hypertrophy, and power production as primary training goals, as these traits appear vital to success in the new Army Combat Fitness Test introduced in 2020. This fundamental change in physical training may require an adjustment in body composition standards and methods of measurement as physique changes in modern male and female soldiers. Current research in the field of digital anthropometry (i.e., 3-D body scanning) has the potential to dramatically improve performance prediction algorithms and potentially could be used to inform training interventions. Similarly, height-adjusted body composition metrics such as fat-free mass index might serve to identify normal weight personnel with inadequate muscle mass, allowing for effective targeted nutritional and training interventions. This review provides an overview of the origin and evolution of current US military body composition standards in relation to military physical readiness, summarizes current evidence relating body composition parameters to aspects of physical performance, and discusses issues relevant to the emerging modern male and female warrior.

Body composition of extreme performers in the US Marine Corps

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/m2) 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/m2). 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/m2). 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/cm2 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.

High precision but systematic offset in a standing bioelectrical impedance analysis (BIA) compared with dual-energy X-ray absorptiometry (DXA)

Bioelectrical impedance analysis (BIA) provides a practical method of body composition estimation for field research and weight management programmes, with devices and algorithms that have improved in recent years. We compared suitability of a commercial BIA system that uses multi-frequency-based proprietary algorithms (InBody 770, Cerritos, California, USA) and a laboratory-based validated single-frequency system (Quantum IV, RJL Systems, Clinton Township, Michigan, USA) with dual-energy X-ray absorptiometry (DXA) (iDXA, GE Lunar, Madison, Wisconsin, USA). Volunteers included fit non-obese active duty US Marines (480 men; 315 women), assessed by DXA and the two BIA systems. Both RJL and InBody BIA devices predicted DXA-based fat-free mass (FFM) (mean absolute error (MAE) 2.8 and 3.1 kg, respectively) and per cent body fat (%BF) (MAE 3.4% and 3.9%, respectively), with higher correlations from the InBody device (r²=0.96 (%BF) and 0.84 (FFM)) versus the RJL (r²=0.92 (%BF) and 0.72 (FFM)). InBody overpredicted FFM (bias +2.7, MAE 3.1 kg) and underpredicted %BF (bias -3.4 and MAE 3.9%) versus the RJL. A 3% correction factor applied to the InBody device results provided values very close to the DXA measurements. These findings support the application of modern BIA systems to body composition goals of maximum %BF and minimum lean body mass for both men and women.

Circumference-Based Predictions of Body Fat Revisited: Preliminary Results From a US Marine Corps Body Composition Survey

Purpose: Body composition assessment methods are dependent on their underlying principles, and assumptions of each method may be affected by age and sex. This study compared an abdominal circumference-focused method of percent body fat estimation (AC %BF) to a criterion method of dual-energy x-ray absorptiometry (DXA), and a comparative assessment with bioelectrical impedance (BIA), in younger (≤30 years) and older (>age 30 years) physically fit (meeting/exceeding annual US Marine Corps fitness testing requirements) men and women.

Methods: Fit healthy US Marines (430 men, 179 women; 18–57 years) were assessed for body composition by DXA (iDXA, GE Lunar), anthropometry, and BIA (Quantum IV, RJL Systems).

Results: Compared to DXA %BF, male AC %BF underestimated for both ≤30 and >30 years age groups (bias, -2.6 ± 3.7 and -2.5 ± 3.7%); while female AC %BF overestimated for both ≤30 and >30 years age groups (2.3 ± 4.3 and 1.3 ± 4.8%). On an individual basis, lean men and women were overestimated and higher %BF individuals were underestimated. Predictions from BIA were more accurate and reflected less relationship to adiposity for each age and sex group (males: ≤30, 0.4 ± 3.2, >30 years, -0.5 ± 3.5; women: ≤30, 1.4 ± 3.1, >30 years, 0.0 ± 3.3). Total body water (hydration) and bone mineral content (BMC) as a proportion of fat-free mass (FFM) remained consistent across the age range; however, women had a higher proportion of %BMC/FFM than men. Older men and women (>age 30 years) were larger and carried more fat but had similar FFM compared to younger men and women.

Conclusion: The AC %BF provides a field expedient method for the US Marine Corps to classify individuals for obesity prevention, but does not provide research-grade quantitative body composition data.

Modeling the Metabolic Costs of Heavy Military Backpacking

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.

Human performance research for military operations in extreme cold environments

OBJECTIVES

Soldier performance in the Arctic depends on planning and training, protective equipment, and human physiological limits. The purpose of this review was to highlight the span of current research on enhancing soldier effectiveness in extreme cold and austere environments.

METHODS

The practices of seasoned soldiers who train in the Arctic and cold-dwelling natives inform performance strategies. We provide examples of research and technology that build on these concepts.

RESULTS

Examples of current performance research include evaluation of equipment and tactics such as the bioenergetics of load carriage over snow in Norwegian exercises; Canadian field monitoring of hand temperatures and freezing cold injuries for better protection of manual dexterity; and Dutch predictive modeling of cold-wet work tolerances. Healthy young men can respond to cold with a substantial thermogenic response based on US and Canadian studies on brown adipose tissue and other mechanisms of non-shivering thermogenesis; the potential advantage of greater fat insulation is offset in obese unfit subjects by a smaller thermogenic response. Current physiological studies are addressing previously unanswered problems of cold acclimation procedures, thermogenic enhancement and regulation, and modulation of sympathetic activation, all of which may further enhance cold survival and expand the performance envelope.

CONCLUSION

There is an inseparable behavioral component to soldier performance in the Arctic, and even the best equipment does not benefit soldiers who have not trained in the actual environment. Training inexperienced soldiers to performance limits may be helped with personal monitoring technologies and predictive models.

Validation of ambulatory monitoring devices to measure energy expenditure and heart rate in a military setting

Objectives.To investigate the validity of different devices and algorithms used in military organizations worldwide to assess physical activity energy expenditure (PAEE) and heart rate (HR) among soldiers.Design.Device validation study.Methods. Twenty-three male participants serving their mandatory military service accomplished, firstly, nine different military specific activities indoors, and secondly, a normal military routine outdoors. Participants wore simultaneously an ActiHeart, Everion, MetaMax 3B, Garmin Fenix 3, Hidalgo EQ02, and PADIS 2.0 system. The PAEE and HR data of each system were compared to the criterion measures MetaMax 3B and Hidalgo EQ02, respectively.Results. Overall, the recorded systematic errors in PAEE estimation ranged from 0.1 (±1.8) kcal.min^-1to -1.7 (±1.8) kcal.min^-1for the systems PADIS 2.0 and Hidalgo EQ02 running the Royal Dutch Army algorithm, respectively, and in the HR assessment ranged from -0.1 (±2.1) b.min^-1to 0.8 (±3.0) b.min^-1for the PADIS 2.0 and ActiHeart systems, respectively. The mean absolute percentage error (MAPE) in PAEE estimation ranged from 29.9% to 75.1%, with only the Everion system showing an overall MAPE <30%, but all investigated devices reported overall MAPE <1.4% in the HR assessment.Conclusions. The present study demonstrated poor to moderate validity in terms of PAEE estimation, but excellent validity in all investigated devices in terms of HR assessment. Overall, the Everion performed among the best in both parameters and with a device placement on the upper arm, the Everion system is particularly useful during military service, as it does not interfere with other relevant equipment.

Changes in energy balance, body composition, metabolic profile and physical performance in a 62-day Army Ranger training in a hot-humid environment

OBJECTIVES

To determine the physiological effects of multiple stressors including energy deficit during a 62-day Ranger course in a hot-humid environment.

DESIGN

Prospective cohort design.

METHODS

Food intake data were collected daily and energy expenditure at each of the three phases of the course was estimated by the doubly-labeled water method. Anthropometry, hydration status, stress and metabolic hormones, handgrip strength and lower explosive power were measured at the start and at the end of each phase.

RESULTS

Seventeen male participants (age: 24.5 ± 3.2 years, height: 173.9 ± 5.1 cm, body mass: 69.3 ± 3.2 kg, BMI: 22.9 ± 0.9 kg/m², percent body fat: 14 ± 5%) completed the study. Mean total daily energy expenditure was 4756 kcal/day and mean daily energy intake was 3882 kcal/day. An 18% energy deficit resulted in an average body mass loss of 4.6 kg, comprising mostly fat mass. Participants with higher baseline adiposity (>15% body fat) lost more fat mass and gained (rather than lost) muscle mass compared to those with lower baseline adiposity. Handgrip strength declined only at the end of Phase I, while lower body explosive power declined progressively throughout the course. Lean mass in arms and legs was correlated with initial grip strength and lower body explosive power, but only at the start of the course.

CONCLUSIONS

Physiologically demanding Ranger training in an equatorial environment is at least as metabolically demanding and stressful as other similar high-risk training courses, as demonstrated by the stress and metabolic endocrine responses, changes in body composition, and reduction in explosive power. Moreover, the smaller body size of Asian soldiers may confer an energetic advantage over larger sized Western counterparts.

Detecting Parkinson's Disease from Wrist-Worn Accelerometry in the U.K. Biobank

Parkinson's disease (PD) is a chronic movement disorder that produces a variety of characteristic movement abnormalities. The ubiquity of wrist-worn accelerometry suggests a possible sensor modality for early detection of PD symptoms and subsequent tracking of PD symptom severity. As an initial proof of concept for this technological approach, we analyzed the U.K. Biobank data set, consisting of one week of wrist-worn accelerometry from a population with a PD primary diagnosis and an age-matched healthy control population. Measures of movement dispersion were extracted from automatically segmented gait data, and measures of movement dimensionality were extracted from automatically segmented low-movement data. Using machine learning classifiers applied to one week of data, PD was detected with an area under the curve (AUC) of 0.69 on gait data, AUC = 0.84 on low-movement data, and AUC = 0.85 on a fusion of both activities. It was also found that classification accuracy steadily improved across the one-week data collection, suggesting that higher accuracy could be achievable from a longer data collection. These results suggest the viability of using a low-cost and easy-to-use activity sensor for detecting movement abnormalities due to PD and motivate further research on early PD detection and tracking of PD symptom severity.

Estimating Sedentary Breathing Rate from Chest-Worn Accelerometry From Free-Living Data

Breathing rate was estimated from chest-worn accelerometry collected from 1,522 servicemembers during training by a wearable physiological monitor. A total of 29,189 hours of training and sleep data were analyzed. The primary purpose of the monitor was to assess thermal-work strain and avoid heat injuries. The monitor design was thus not optimized to estimate breathing rate. Since breathing rate cannot be accurately estimated during periods of high activity, a qualifier was applied to identify sedentary time periods, totaling 8,867 hours. Breathing rate was estimated for a total of 4,179 hours, or 14% of the total collection and 47% of the sedentary total, primarily during periods of sleep. The breathing rate estimation method was compared to an FDA 510(K)-cleared criterion breathing rate sensor (Zephyr, Annapolis MD, USA) in a controlled laboratory experiment, which showed good agreement between the two techniques. Contributions of this paper are to: 1) provide the first analysis of accelerometry-derived breathing rate on free-living data including periods of high activity as well as sleep, along with a qualifier that effectively identifies sedentary periods appropriate for estimating breathing rate; 2) test breathing rate estimation on a data set with a total duration that is more than 60 times longer than that of the largest previously reported study, 3) test breathing rate estimation on data from a physiological monitor that has not been expressly designed for that purpose.

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing.

Divers risk accelerated fatigue and core temperature rise during fully-immersed exercise in warmer water temperature extremes

Physiological responses to work in cold water have been well studied but little is known about the effects of exercise in warm water; an overlooked but critical issue for certain military, scientific, recreational, and professional diving operations. This investigation examined core temperature responses to fatiguing, fully-immersed exercise in extremely warm waters. Twenty-one male U.S. Navy divers (body mass, 87.3 ± 12.3 kg) were monitored during rest and fatiguing exercise while fully-immersed in four different water temperatures (Tw): 34.4, 35.8, 37.2, and 38.6°C (Tw_34.4, Tw_35.8, Tw_37.2, and Tw_38.6 respectively). Participants exercised on an underwater cycle ergometer until volitional fatigue or core temperature limits were reached. Core body temperature and heart rate were monitored continuously. Trial performance time decreased significantly as water temperature increased (Tw_34.4, 174 ± 12 min; Tw_35.8, 115 ± 13 min; Tw_37.2, 50 ± 13 min; Tw_38.6, 34 ± 14 min). Peak core body temperature during work was significantly lower in Tw_34.4 water (38.31 ± 0.49°C) than in warmer temperatures (Tw_35.8, 38.60 ± 0.55°C; Tw_37.2, 38.82 ± 0.76°C; Tw_38.6, 38.97 ± 0.65°C). Core body temperature rate of change increased significantly with warmer water temperature (Tw_34.4, 0.39 ± 0.28°C·h⁻¹; Tw_35.8, 0.80 ± 0.19°C·h⁻¹; Tw_37.2, 2.02 ± 0.31°C·h⁻¹; Tw_38.6, 3.54 ± 0.41°C·h⁻¹). Physically active divers risk severe hyperthermia in warmer waters. Increases in water temperature drastically increase the rate of core body temperature rise during work in warm water. New predictive models for core temperature based on workload and duration of warm water exposure are needed to ensure warm water diving safety.

The association between obesity related health risk and fitness test results in the British Army personnel

OBJECTIVE

In the British Army, fitness is assessed by a load carriage test (Annual Fitness Test, AFT) and by a three event Personal Fitness Assessment (PFA). Body composition based on body mass index (BMI) and abdominal circumference (AC) is also part of a mandatory annual assessment. This study examined the influence of BMI and AC on fitness test results within a comprehensive sample of British Army personnel.

DESIGN

Secondary analyse were carried out on data obtained from the 2011 Defence Analytical Services and Advice (DASA) database for 50,635 soldiers (47,173 men and 3,462 women).

METHODS

Comparisons using loglinear analysis were made between groups of individuals classified by body mass index as obese (≥30kg/m2) and not obese (<30kg/m2), and further classified using combined BMI and AC for obesity-related health risks to compare "no risk" with "increased risk."

RESULTS

Not obese or "no risk" soldiers had a significant relationship with success in the AFT (p<0.01) and PFA (p<0.01). Of those soldiers who attempted the AFT, 99% of men and 92% of women passed; for the PFA, 92% of men and 91% of women passed. Obese or "at risk" soldiers were more likely to fail and far less likely to take both tests (p<0.05). Compared to older obese soldiers, young obese soldiers were more likely to attempt the tests.

CONCLUSIONS

We conclude that BMI and AC are useful indicators of fitness test outcome in the British Army.

Wearable physiological monitoring for human thermal-work strain optimization

Safe performance limits of soldiers and athletes have typically relied on predictive work-rest models of ambient conditions, average work intensity, and characteristics of the population. Bioengineering advances in noninvasive sensor technologies, including miniaturization, reduced cost, power requirements, and comfort, now make it possible to produce individual predictions of safe thermal-work limits. These precision medicine assessments depend on the development of thoughtful algorithms based on physics and physiology. Both physiological telemetry and thermal-strain indexes have been available for >50 years, but greater computing power and better wearable sensors now make it possible to provide actionable information at the individual level. Core temperature can be practically estimated from time series heart rate data and, using an adaptive physiological strain index, provides meaningful predictions of safe work limits that cannot be predicted from only core temperature or heart rate measurements. Early adopters of this technology include specialized occupations where individuals operate in complete encapsulation such as chemical protective suits. Emerging technologies that focus on heat flux measurements at the skin show even greater potential for estimating thermal-work strain using a parsimonious sensor set. Applications of these wearable technologies include many sports and military training venues where inexperienced individuals can learn effective work pacing strategies and train to safe personal limits. The same strategies can also provide a technologically based performance edge for experienced workers and athletes faced with novel and nonintuitive physiological challenges, such as health care providers in full protective clothing treating Ebola patients in West Africa in 2014.

NEW & NOTEWORTHY This mini-review details how the application of computational techniques borrowed from signal processing and control theory can provide meaningful advances for the applied physiological problem of real-time thermal-work strain monitoring. The work examines the development of practical core body temperature estimation techniques and how these can be used in combination with current and updated thermal-work strain indexes to provide objective state assessments and to optimize work rest schedules for a given task.

Talk to the Hand: U.S. Army Biophysical Testing

BACKGROUND

Many people are unaware of the science underlying the biophysical properties of Soldier clothing and personal protective equipment, yet there is a well-refined biomedical methodology initiated by Army physiologists in World War II. This involves a methodical progression of systematic material testing technologies, computer modeling, and human testing that enables more efficient development and rapid evaluation of new concepts for Soldier health and performance. Sophisticated manikins that sweat and move are a central part of this testing continuum. This report briefly summarizes the evolution and use of one specialized form of the manikin technologies, the thermal hand model, and its use in research on Soldier hand-wear items that sustain dexterity and protect the hand in extreme environments.

METHODS

Thermal manikin testing methodologies were developed to provide an efficient and consistent analytical tool for the rapid evaluation of new clothing concepts. These methods have been upgraded since the original World War II and Korean War eras to include articulation and sweating capabilities, as characterized and illustrated in this article. The earlier "retired" versions of thermal hand models have now been transferred to the National Museum of Health and Science.

FINDINGS

The biophysical values from manikin testing are critical inputs to the U.S. Army Research Institute of Environmental Medicine mathematical models that provide predictions of soldier comfort, duration of exposure before loss of manual dexterity, and time to significant risk of freezing (skin temperature <-1°C) and nonfreezing cold injuries (skin temperature <5°C). The greater thickness of better insulated handwear reduces dexterity and also increases surface area which makes added insulation increasingly less effective in retaining heat. Measurements of both thermal resistance (insulation) and evaporative resistance (permeability) collectively characterize the biophysical properties and enable mathematical modeling of the human thermophysiological responses. This information can help guide the hand-wear development and selection process which often requires trade-offs between factors such as material, cost, and sizing.

IMPACT

Soldier hands provide fine motor dexterity in tactical functions, ranging from pulling a trigger to pulling a parachute ripcord; thus, protecting hand function is critical to soldier readiness. Also, the importance of protection against nonbattle cold injuries was highlighted during World War II in northern Europe, in the Aleutian Islands, and later in Korea. The U.S. Army has been on the forefront of the biophysical analysis of clothing including gloves since environmental research was established at the Armored Medical Research Laboratory and Climatic Research Laboratory during World War II. U.S. Army Research Institute of Environmental Medicine does not make the equipment but works with their Natick Soldier Research, Development, and Engineering Center partners to make the equipment better.

What Engineering Technology Could Do for Quality of Life in Parkinson's Disease: A Review of Current Needs and Opportunities

Parkinson's disease (PD) involves well-known motor symptoms such as tremor, rigidity, bradykinesia, and altered gait, but there are also nonlocomotory motor symptoms (e.g., changes in handwriting and speech) and even nonmotor symptoms (e.g., disrupted sleep, depression) that can be measured, monitored, and possibly better managed through activity-based monitoring technologies. This will enhance quality of life (QoL) in PD through improved self-monitoring and also provide information that could be shared with a healthcare provider to help better manage treatment. Until recently, nonmotor symptoms ("soft signs") had been generally overlooked in clinical management, yet these are of primary importance to patients and their QoL. Day-to-day variability of the condition, the high variability in symptoms between patients, and the isolated snapshots of a patient in periodic clinic visits make better monitoring essential to the proper management of PD. Continuously monitored patterns of activity, social interactions, and daily activities could provide a rich source of information on status changes, guiding self-correction and clinical management. The same tools can be useful in earlier detection of PD and will improve clinical studies. Remote medical communications in the form of telemedicine, sophisticated tracking of medication use, and assistive technologies that directly compensate for disease-related challenges are examples of other near-term technology solutions to PD problems. Ultimately, a sensor technology is not good if it is not used. The Parkinson's community is a sophisticated early adopter of useful technologies and a group for which engineers can provide near-term gratifying benefits.

U.S. Army Research on Pharmacological Enhancement of Soldier Performance: Stimulants, Anabolic Hormones, and Blood Doping

The level playing field of competitive sports is an irrelevant concern in asymmetrical warfare. However, there is a common theme of pressure to use performance-enhancing drugs because athletic or military opponents may be using them to advantage. This interest is fueled by personal anecdotes, misconceptions, and myths, and decisions to use or not to use pharmacological interventions may ignore available scientific data. The U.S. Army has led research in this area, with an abundance of published data extending back to World War II. Behavioral effects have been a consistent concern. A key conclusion to be drawn from this research is that although there may be specialized applications for some of these interventions, the majority of soldiers will gain the greatest performance benefits from effective physical and mental training programs combined with good principles of rest and nutrition. Furthermore, the perceived need to improve human biology with drugs may be solving the wrong problem, trying to fit the human to the demands of poorly conceived tactics, tasks, and equipments instead of capitalizing on human capabilities.

Lifestyle and health-related risk factors and risk of cognitive aging among older veterans

Lifestyle and health-related factors are critical components of the risk for cognitive aging among veterans. Because dementia has a prolonged prodromal phase, understanding effects across the life course could help focus the timing and duration of prevention targets. This perspective may be especially relevant for veterans and health behaviors. Military service may promote development and maintenance of healthy lifestyle behaviors, but the period directly after active duty has ended could be an important transition stage and opportunity to address some important risk factors. Targeting multiple pathways in one intervention may maximize efficiency and benefits for veterans. A recent review of modifiable risk factors for Alzheimer's disease estimated that a 25% reduction of a combination of seven modifiable risk factors including diabetes, hypertension, obesity, depression, physical inactivity, smoking, and education/cognitive inactivity could prevent up to 3 million cases worldwide and 492,000 cases in the United States. Lifestyle interventions to address cardiovascular health in veterans may serve as useful models with both physical and cognitive activity components, dietary intervention, and vascular risk factor management. Although the evidence is accumulating for lifestyle and health-related risk factors as well as military risk factors, more studies are needed to characterize these factors in veterans and to examine the potential interactions between them.

Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer's disease in veterans, using the Alzheimer's Disease Neuroimaging Initiative

Both traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common problems resulting from military service, and both have been associated with increased risk of cognitive decline and dementia resulting from Alzheimer's disease (AD) or other causes. This study aims to use imaging techniques and biomarker analysis to determine whether traumatic brain injury (TBI) and/or PTSD resulting from combat or other traumas increase the risk for AD and decrease cognitive reserve in Veteran subjects, after accounting for age. Using military and Department of Veterans Affairs records, 65 Vietnam War veterans with a history of moderate or severe TBI with or without PTSD, 65 with ongoing PTSD without TBI, and 65 control subjects are being enrolled in this study at 19 sites. The study aims to select subject groups that are comparable in age, gender, ethnicity, and education. Subjects with mild cognitive impairment (MCI) or dementia are being excluded. However, a new study just beginning, and similar in size, will study subjects with TBI, subjects with PTSD, and control subjects with MCI. Baseline measurements of cognition, function, blood, and cerebrospinal fluid biomarkers; magnetic resonance images (structural, diffusion tensor, and resting state blood-level oxygen dependent (BOLD) functional magnetic resonance imaging); and amyloid positron emission tomographic (PET) images with florbetapir are being obtained. One-year follow-up measurements will be collected for most of the baseline procedures, with the exception of the lumbar puncture, the PET imaging, and apolipoprotein E genotyping. To date, 19 subjects with TBI only, 46 with PTSD only, and 15 with TBI and PTSD have been recruited and referred to 13 clinics to undergo the study protocol. It is expected that cohorts will be fully recruited by October 2014. This study is a first step toward the design and statistical powering of an AD prevention trial using at-risk veterans as subjects, and provides the basis for a larger, more comprehensive study of dementia risk factors in veterans.