October – December 2013 

Perspectives 1 

MG Steve Jones; COL Mustapha Debboun; Richard Burton 

A System for Health: Essential Element of National Security 4 

LTG Patricia D. Horoho 

Strategies for Optimizing Military Physical Readiness and 5 

Preventing Musculoskeletal Injuries in the 21st Century 

Bradley C. Nindl, PhD; Thomas J Williams, PhD; Patricia A. Deuster, PhD; et al 

Physical Fitness: A Pathway to Health and Resilience 24 

Patricia A. Deuster, PhD; Marni N. Silverman, PhD 

Extreme Conditioning Programs and Injury Risk 36 

in a US Army Brigade Combat Team 

Tyson Grier, MS; Michelle Canham-Chervak, PhD; et al 

Measuring Physical Activity During US Army Basic Combat Training: 48 

A Comparison of 3 Methods 

Jan E. Redmond, PhD; Bruce S. Cohen, PhD; Kathleen Simpson, MS; et al

Quantification of Physical Activity Performed During 55 

US Army Basic Combat Training 

Kathleen Simpson, MS; Jan E. Redmond, PhD; Bruce S. Cohen, PhD; et al 

Nutrition as a Component of the Performance Triad: How Healthy Eating 66 

Behaviors Contribute to Soldier Performance and Military Readiness 

Dianna L. Purvis, PhD; Cynthia V. Lentino, MS; Theresa K. Jackson, PhD; et al 

The Importance of Leadership in Soldiers' Nutritional Behaviors: 79 

Results from the Soldier Fueling Initiative Program Evaluation 

Theresa K. Jackson, PhD; COL Sonya J. Cable; Wana K. Jin, MPH; et al 

Assessment of Dietary Intake Using the Healthy Eating Index 91

During Military Training 

Laura J. Lutz, MS; Erin Gaffney-Stomberg, PhD; Jenna L. Scisco, PhD; et al 

Sleep as a Component of the Performance Triad: 98 

The Importance of Sleep in a Military Population 

Cynthia V. Lentino, MS; Dianna L. Purvis, PhD; et al 

The Challenge of Sleep Management In Military Operations 109 

Nancy J. Wesensten, PhD; Thomas J. Balkin, PhD 

The foundation of a system for health: 

army medicine’s Performance Triad 
October – December 2013 The Army Medical Department Center & School PB 8-13-10/11/12 

By Order of the Secretary of the Army: 

Official: 

1325501 

RAYMOND T. ODIERNO 

General, United States Army 

Chief of Staff

DISTRIBUTION: Special 

Administrative Assistant to the 

Secretary of the Army 

JOYCE E. MORROW 

Online issues of the AMEDD Journal are available at http://www.cs.amedd.army.mil/amedd_journal.aspx 

A Professional Publication 

of the AMEDD Community 

The Army Medical Department Journal [ISSN 1524-0436] is published quarterly for 

The Surgeon General by the US Army Medical Dept Center & School, Journal Office, 

AHS CDD Bldg 4011, 2377 Greeley RD STE T, Fort Sam Houston, TX 78234-7584. 

Articles published in The Army Medical Department Journal are listed and 

indexed in MEDLINE, the National Library of Medicine’s premier bibliographic 

database of life sciences and biomedical information. As such, the Journal’s articles 

are readily accessible to researchers and scholars throughout the global scientific 

and academic communities. 

CORRESPONDENCE: Manuscripts, photographs, official unit requests to 

receive copies, and unit address changes or deletions should be sent to the 

Journal at the above address., or amedd.journal@amedd.army.mil. Telephone: 

(210) 221-6301, DSN 471-6301 

DISCLAIMER: The AMEDD Journal presents clinical and nonclinical 

professional information to expand knowledge of domestic & international 

military medical issues and technological advances; promote collaborative 

partnerships among Services, components, Corps, and specialties; convey 

clinical and health service support information; and provide a peer-reviewed, high 

quality, print medium to encourage dialogue concerning healthcare initiatives. 

Appearance or use of a commercial product name in an article published in 

the AMEDD Journal does not imply endorsement by the US Government. 

Views expressed are those of the author(s) and do not necessarily reflect 

official policies or positions of the Department of the Army, Department of the 

Navy, Department of the Air Force, Department of Defense, nor any other agency 

of the US Government. The content does not change or supersede information in 

other US Army Publications. The AMEDD Journal reserves the right to edit all 

material submitted for publication (see inside back cover). 

CONTENT: Content of this publication is not copyright protected. Reprinted 

material must contain acknowledgement to the original author(s) and the 

AMEDD Journal. 

OFFICIAL DISTRIBUTION: This publication is targeted to US Army 

Medical Department units and organizations, other US military medical 

organizations, and members of the worldwide professional medical community. 

LTG Patricia D. Horoho 

The Surgeon General 

Commander, US Army Medical Command 

MG Steve Jones 

Commanding General 

US Army Medical Department Center & School 
 October – December 2013 1

EDITOR’S PERSPECTIVE

In her introduction to the contents of this issue, The 

Surgeon General outlines the genesis and concept of the 

Performance Triad foundation to the System of Health 

initiative for Army Medicine. Dr Bradley Nindl of the 

US Army Public Health Command organized and led 

the effort to collect articles for this issue which present a 

sample of the professional skill and knowledge resources 

of Army medicine which are dedicated to realizing this 

transition. Each pillar of the Performance Triad is represented by articles describing completed studies and 

ongoing research to allow implementation of policies 

and doctrine from a perspective of solid, science-based 

knowledge.

Military service demands a strong, fi t body. Obviously, 

strength and fi tness cannot be achieved nor maintained 

without exercise. However, as Dr Nindl and his coauthors discuss in their article, both physical training and 

Perspectives

COMMANDER’S INTRODUCTION

MG Steve Jones

Instilling fi tness and resilience in our Soldiers, Families, and Army Civilians is as important today as it was 

during the long winter at Valley Forge. These qualities 

are critical as the Army continues to fi ght our nation’s 

longest war with an all-volunteer force. The Ready and 

Resilient Campaign seeks to institute a cultural change 

in the Army by directly linking personal resilience to 

readiness, and emphasizing the responsibility of each 

individual to build and maintain resilience. Taking a deliberate approach to strengthening physical, psychological, and emotional resilience will increase unit readiness 

and the ability of Soldiers, Families and Civilians to deal 

with the signifi cant challenges of the Army Profession. 

The Army Medical Department’s Performance Triad 

supports the Ready and Resilient Campaign and is a key 

component of our transition from a healthcare system to 

a System for Health. Patients spend an average of 100 

minutes each year in our healthcare system. Their decisions during the other 525,500 minutes of the year, the 

Lifespace, have a great impact on their health and their 

lives. Sound decisions concerning the basics of Activity, Nutrition, and Sleep are key to optimizing health, 

performance and resilience. The Performance Triad will 

lead to sound decisions, more healthy behaviors, and 

more optimal performance.

We know that individual resilience can be built, maintained, and strengthened with an appropriate training 

regimen. By taking a systematic approach we can better include activities into our schedule, follow a healthy 

diet that supports our training, and ensure we get the 

rest we need. A thoughtful plan will make our training 

more effective, help prevent injuries and overtraining. 

Start by setting challenging but realistic goals. Include 

both short and long term goals that are specifi c and 

measurable. Pick a physical activity that you enjoy and 

make it a regular part of your daily schedule. There’s no 

single best way to train, the best activity for you is one 

you will consistently stick with. Remember that it is just 

as important to train your mind and include mind-body 

activities as well. Meditation not only reduces stress but 

can also increase your ability to concentrate. Yoga increases fl exibility while reducing stress. Other mental 

training activities can improve your cognitive function.

Diet has a major infl uence on overall physical and psychological fi tness. Quality nutrition means eating the 

right foods in the right quantities to improve performance and maintain a healthy weight. Plan your meals 

in advance and follow your plan. Sleep, the fi nal element 

of the Performance Triad, is as important as the other 

two. Training overloads the body and a recovery period allows the adaptation which increases physical and 

psychological fi tness. Proper recovery includes cooling 

down, refueling, rehydrating, and sleep. And once again, 

make a point to include adequate time in your schedule.

Soldier athletes following a more advanced training program can achieve even greater goals. Their training plan 

should incorporate a strategy to improve endurance, 

speed, strength, power, fl exibility, and the technical/

mental skills required in their job. They should specifi -

cally tailor their training to accomplish their goals, and 

incorporate advanced techniques including training cycles and periodization. Rest may include active recovery 

activities such as walking, light biking, or swimming. 

With more intense and higher volume training, it’s even 

more important to follow a careful plan to avoid overtraining and overuse injuries. Finally, keep a training 

log—it helps you stay motivated, track your progress, 

and accomplish your goals.
2 http://www.cs.amedd.army.mil/amedd_journal.aspx

sports are essential, but are also the main cause of musculoskeletal injuries among military service members. 

Such injuries often render the service member medically 

not ready to deploy, or cause evacuation from theaters 

of operation. Their article presents a scholarly, wellresearched, carefully developed plan for achieving the 

necessary levels of fi tness and strength among Soldiers 

while signifi cantly reducing the number of musculoskeletal injuries incurred during training and individual fi tness activities. This article should be the starting point 

for anyone charged with the development and implementation of physical training plans, programs, and doctrine 

for military service members.

In their article, Dr Patricia Deuster and Dr Marni Silverman look at another benefi t of physical fi tness beyond 

its necessity in the strength and endurance required to 

perform physically-demanding tasks. They explore resilience as an indispensable characteristic for military 

service, sometimes being the difference between life 

and death. Using their extensive research, they carefully 

develop the position that physical fi tness is essential for 

a person to grow and maintain the resilience necessary 

to deal with the stresses and uncertainties of constantly 

changing demands. Further, their article presents the 

demonstrated relationship of resilience and good health 

in general, adding yet another contribution of physical 

fi tness to the goals of the Performance Triad.

The combat experiences of the past decade have emphasized the utmost importance of physical conditioning for 

the mission-specifi c tasks faced in the environment of 

nonlinear warfare. Combat units throughout the Army 

are looking at ways to tailor physical training to specifi -

cally address the demands presented by those tasks in 

order to improve immediate and long-term combat effectiveness. Tyson Grier and his team of coauthors looked 

at such new programs to determine if more intense and 

focused physical training had an effect on injury rates or 

physical fi tness beyond that experienced by units with 

standard Army fi tness training programs. They conducted detailed research in the literature, and collected and 

analyzed extensive amounts of data from battalions in 

training to discover any defi nitive trends and/or relationships among focused training, regular training, fi tness 

levels, and injuries incurred by those involved in physical training. Their comprehensive analysis demonstrates 

various relationships depending on various physiological parameters of individuals involved, and provides a 

wealth of data on which planners can base their programs 

and policies for physical fi tness training and standards.

Those involved in the transformation of raw recruits 

into combat Soldiers have many challenges, whether 

researching, designing, implementing, or conducting the 

training. This is particularly true for the physical fi tness 

requirements and programs in that they are charged with 

the training and physical development of people presenting a cross-section of physical, fi tness, capabilities, 

motivations, and dedication. They must do this while 

minimizing injury, but meeting the time limitations of 

the training schedule. Therefore, those who design the 

training regimen must have an understanding of the demands of the physical activity mandated by the training. 

To do that, those demands must be measured and quantifi ed. In their study, Dr Jan Redmond and her team evaluated 3 measurement instruments used with Soldiers in 

the basic combat training environment to determine the 

agreement among them. Each instrument had its respective use limitations, overhead requirements, and other 

considerations which must be factored into any decisions concerning use in the training environment. Their 

article clearly describes the carefully designed and conducted study, the data analysis, and the results, conclusions, and recommendations which should be of great 

assistance for future training planners and evaluators.

Accurate measurement of physical activity during training is valuable for many purposes, including to verify 

the level of standardization at different training sites. 

Kathleen Simpson and her team used the information 

concerning measurement instruments discussed in the 

above paragraph to design and conduct a study measuring the amount of physical activity involved in basic 

combat training at 2 different training locations. Their 

excellent article clearly describes the careful, extensive 

data collection and the detailed statistical analyses of 

the various data groups. The conclusions based on their 

solid research demonstrate that the physical activity in 

the training conducted at the 2 study sites closely match 

each other, indicating a good level of standardization in 

implementation of the prescribed training regimen.

The prosperity of this nation, and to a lesser degree a 

large part of the world, since World War II has changed 

the perspective of nutrition from one of insuffi ciency 

to that of abundance. However, that seemingly positive 

trend is not without its negative aspects. The prosperity 

has also given us the ability to exhaustively and seemingly endlessly evaluate the nutritive properties of the 

many substances classifi ed as food, and publicize those 

fi ndings to the population. Even with the availability of 

that information, most food choices are not made from a 

nutritive aspect, but rather from convenience, advertising hype, habit, and other lifestyle factors. This trend 

has long been refl ected in an inexorable increase in obesity and other unhealthy, nutrition-related manifestations such as cardio and digestive conditions. Since the 

PERSPECTIVES
 October – December 2013 3

THE ARMY MEDICAL DEPARTMENT JOURNAL

military is a snapshot, albeit a generally healthier one, 

of the population as a whole, the nutrition choices and 

habits of military members are of concern to health professionals. Since nutrition and good health—and therefore military readiness—are absolutely interdependent, 

nutrition is another of the designated foundation pillars 

of good health in The Surgeon General’s Performance 

Triad. This issue of the AMEDD Journal contains 3 articles presenting studies by Army health professionals addressing different aspects of nutrition within the Army, 

and which undoubtedly refl ect the situation throughout 

all the US military services. Dr Dianna Purvis and her 

coauthors lead off with their article describing Soldier 

dietary behaviors and the relationship of healthy eating 

behaviors and demographic, lifestyle, and psychosocial 

factors. They collected a considerable amount of data 

from a relatively large study population, and methodically reduced, parsed, and analyzed that data, and correlated the results with extensive literature research 

refl ected in the references cited throughout the article. 

The results of their efforts should be of great interest for 

everyone involved in organizational nutrition planning 

and management, whether civilian or military.

Since many, perhaps most, military recruits are not well 

versed in good dietary behaviors when they enter the 

service, one of the efforts made by the Army to improve 

nutritional behaviors is called the Soldier Fueling Initiative. It provides nutrition education and improved dining 

facility menus to Soldiers at basic combat training and 

advanced individual training locations in an effort to instill good dietary habits in trainees as an inherent part of 

their military lifestyle. However, no program or policy 

will be successfully implemented without positive, effective leadership, especially in the early phases of the 

military experience. Dr Theresa Jackson and her research team conducted a study to examine the infl uence 

and effectiveness of troop leaders at 2 training locations 

with regard to eating behavior of their Soldiers. Their 

study examined the activities and attitudes of Soldiers 

within the framework of the Soldier Fueling Initiative, 

and how it was or was not supported by their leadership 

during training. Their fi ndings clearly indicate the relationship of Soldier nutrition practices and the leadership 

they experienced in this area. This article is important to 

those designing and planning training for troop leaders 

working in these environments, as well as for Soldiers 

training under the Soldier Fueling Initiative.

Laura Lutz and her coauthors examined the actual (selfreported) eating behaviors of Soldiers in basic combat 

training to quantify any changes in dietary quality between their start and completion of that training cycle. 

Their investigation focused on the types and quantities 

of food consumed during training, and demographic data 

and tobacco use were factored into the data analysis as 

well. The study was carefully designed with a solid background of research, and the data collection was detailed. 

The results of their analysis, clearly presented in the article, indicate that the efforts of initiatives to improve 

the dietary habits of Soldiers from the beginning of their 

Army experience are showing measureable success.

The fact that adequate sleep, the third pillar of the Performance Triad, is essential to good health has been widely 

recognized for many years, not only by scientists and 

medical professionals, but by most people, usually based 

on personal experience. Unfortunately, similar to both 

healthy activity and good nutrition, adequate sleep loses 

against the time demands of our multitasked lifestyle 

of unlimited entertainment, universal contact, and 24 

hour availability. Lack of sleep begins early as teenagers cannot prioritize their activities, and continues into 

the working life with too many commitments (and/or 

jobs) and the demands of parenthood. Cynthia Lentino 

and her coauthors looked at sleep habits in the military 

population to examine the relationship of sleep quality 

to physical performance, nutritional habits, measures 

of obesity, and lifestyle behaviors, among other things. 

Their excellent, thoroughly referenced article clearly 

presents the details of their data collection, its analysis, 

and the conclusions developed from that analysis. The 

results of their study reinforce the fi ndings of other research in this area, and unquestionably demonstrate that 

the 3 elements of the Performance Triad are highly interdependent in both positive and negative relationships.

Dr Nancy Wesensten and Dr Thomas Balkin conducted 

an extensive, thorough literature review for research 

which could be used to address the adverse effect of 

insuffi cient sleep on military readiness. Their primary 

goal was to identify data and research fi ndings for use 

in developing an optimally effective sleep health education program which could be taught to military personnel and their families, since good sleep habits are just as 

important in garrison as in a deployed environment. Just 

as importantly, such a program must be understood and 

supported by military leadership at all levels, so that the 

sleep of combat troops would be a major consideration 

in maintaining the combat effectiveness of the fi ghting 

force. Their article is a logically organized, easily understood presentation of their research fi ndings, which 

further undergird The Surgeon General’s concept of the 

Performance Triad as the foundation in the development 

and maintenance of a fi ghting force at the highest level 

of readiness and combat capability.
4 http://www.cs.amedd.army.mil/amedd_journal.aspx

Army Medicine is transitioning from a healthcare system to a System for Health. This means shifting the focus to prevention of disease, injury, and disability. More 

importantly, it means advocating a culture shift to Soldiers and benefi ciaries by encouraging them to develop 

a mindset that drives them to optimize their own health. 

The Performance Triad is the enabler of our transition to 

a System for Health, as well as the framework for helping to change the mindsets of those for whom we are 

professionally and personally responsible. If we can improve the health literacy of the Army community, our 

Army family will make better decisions about Activity, Nutrition, and Sleep, which form the 3 pillars of the 

Triad. The depth of science and professional knowledge 

represented by the articles in this issue is essential to the 

evidence-based foundation we are using to encourage 

and assist Army benefi ciaries to choose good health.

The successful transition to a System for Health is vitally important. Not only is it important to the survival 

of Army medicine as an affordable, viable entity, but also—I am convinced—to the security of our nation. We 

spend more than any other nation on healthcare, yet we 

are becoming less and less healthy. Obesity is increasing and tobacco use and substance abuse are on the rise 

among both children and adults, chronic diseases lead 

our nation in causes of death, and the cost of our healthcare system is simply not sustainable.

The declining health status of our Soldiers, their Families and our nation as a whole are common concerns 

shared across and beyond Army Medicine. Additionally, 

we face the challenges of the drawdown, sequestration, 

budget cuts, and furloughs. These challenges fi ll our 

inboxes, consume our days, and negatively affect morale and our sense of value to the organization. Together, 

health issues and fi nancial pressures present a signifi -

cant threat to our security and to our Army’s most basic 

mission: to fi ght and win our nation’s wars. However, we 

cannot—I repeat, cannot—allow the challenges we face 

to drive us to despair. We are part of an organization that 

has faced equal and greater challenges over the past 238 

years. We have seized the opportunities that those challenges presented, and we emerged stronger and more resilient. Today is no different. 

Everyone in Army Medicine has an active role in changing not only the way Army Medicine is organized and 

operates, but how we interact with our benefi ciaries, and 

how we infl uence health. Whether in leadership positions at the headquarters, the regional medical commands, the major subordinate commands, or closer to 

the point of health care delivery in our medical treatment facilities or line units, each of us has a critical part 

in shaping the future of Army Medicine. What we do 

and how we do it will be our legacy. I believe that legacy 

will be the transformation of health care, not only across 

the Army, but across the nation.

ARMY STRONG!

A System for Health:

Essential Element of National Security

LTG Patricia D. Horoho

The Surgeon General of the United States Army
 October – December 2013 5

The United States military is being transformed as deployments in Iraq and Afghanistan come to an end and 

the Department of Defense (DoD) cuts budgets and 

personnel. The Chairman of the Joint Chiefs of Staff, 

General Martin Dempsey, has stated that strategies 

and capabilities are key factors in cutting $450 billion 

from DoD’s budget over the next 10 years.1

 Further, on 

January 26, 2012, the strategic guidance from the Pentagon, presented from then Secretary of Defense, Leon 

Panetta and GEN Martin Dempsey, included the recommendation for Army personnel strength reductions 

from 570,000 to 490,000 over the next 5 years.2

 Secondorder effects from this decline in troop strength superimposed upon the persistent and signifi cant percentage 

of Soldiers considered medically not ready (MNR) to 

deploy could potentially have signifi cant consequences 

if the manned force structure is not able to meet military operational requirements for protecting our nation’s 

vital and important interests. As a consequence of these 

austere changes/decrements in resources, protection of 

force health and performance optimization of Soldiers 

and other service members will be more important than 

ever.

Musculoskeletal injuries (MSIs) are the cause of a large 

percentage of service members deemed to be MNR and 

placed on limited duty.3

 These MSIs are a major threat 

to the health and fi tness of our Soldiers and other service 

members placing our nation’s war-fi ghting capability at 

risk.3,4 The costs imposed by this threat are both fi nancial (such as the economic burden from medical, healthcare and disability costs) and human. The injuries exacerbate human manpower losses as Soldiers are medically 

unable to perform their duties for deployment.3,5-8 The 

majority of the injuries encountered in military populations are training-related, overuse injuries.8,9

 Strategies for Optimizing Military Physical

 Readiness and Preventing Musculoskeletal

 Injuries in the 21st Century

Bradley C. Nindl, PhD

Thomas J. Williams, PhD

Patricia A. Deuster, PhD

COL Nikki L. Butler, SP, USA

Bruce H. Jones, MD, MPH

ABSTRACT

With downsizing of the military services and signifi cant budget cuts, it will be more important than ever to optimize 

the health and performance of individual service members. Musculoskeletal injuries (MSIs) represent a major threat 

to the health and fi tness of Soldiers and other service members that degrade our nation’s ability to project military 

power. This affects both fi nancial (such as the economic burden from medical, healthcare, and disability costs) and 

human manpower resources (Soldiers medically unable to optimally perform their duties and to deploy). For example, in 2012, MSIs represented the leading cause of medical care visits across the military services resulting in 

almost 2,200,000 medical encounters. They also result in more disability discharges than any other health condition. 

Nonbattle injuries (NBIs) have caused more medical evacuations (34%) from recent theaters of operation than any 

other cause including combat injuries. Physical training and sports are the main cause of these NBIs. The majority (56%) of these injuries are the direct result of physical training. Higher levels of physical fi tness protect against 

such injuries; however, more physical training to improve fi tness also causes higher injury rates. Thus, military 

physical training programs must balance the need for fi tness with the risks of injuries. The Army has launched several initiatives that may potentially improve military physical readiness and reduce injuries. These include the US 

Army Training and Doctrine Command’s Baseline Soldier Physical Readiness Requirements and Gender Neutral 

Physical Performance Standards studies, as well as the reimplementation of the Master Fitness Trainer program and 

the Army Medical Command’s Soldier Medical Readiness and Performance Triad Campaigns. It is imperative for 

military leaders to understand that military physical readiness can be enhanced at the same time that MSIs are prevented. A strategic paradigm shift in the military’s approach to physical readiness policies is needed to avoid further 

degradation of warfi ghting capability in an era of austerity. We believe this can be best accomplished through leveraging scientifi c, evidence-based best practices by Army senior leadership which supports, prioritizes, and implements innovative, synchronized, and integrated human performance optimization/injury prevention policy changes.
6 http://www.cs.amedd.army.mil/amedd_journal.aspx

Controlling MSIs among military personnel and continuing to reduce injury rates depend on institutionalizing 

existing best practices for injury prevention and physical training, plus prioritizing relevant research in the future. Accomplishing this requires establishing stronger 

linkages across commands, operational personnel, researchers, medical providers, public health, and safety 

offi cials.10 With the emphasis of the 2010 Quadrennial 

Defense Review Report11 on the health and fi tness of the 

total force, and the 2007 Joint Force Health Protection 

Concept of Operations12 encompassing a healthy, enhanced, and protected force, now is the time to critically 

review military physical readiness practices—both human performance optimization (HPO) and injury prevention (IP)—with the Army and other services. The 

promotion and sustainment of military physical readiness requires an energized sense of urgency from senior 

military leadership responsible for the implementation 

of policies and strategies that promote and sustain military physical readiness. Such actions will contribute 

to force readiness and align the DoD and the Military 

Healthcare System with a fundamental premise that the 

Soldier is the center of our Warfi ghter capability. The 

human service member is the prime resource and key 

enabler of all Warfi ghting systems.12(ES-2)

This article proposes that the military approach to military physical readiness requires a new strategic paradigm that recognizes that physical training, physical fi tness, and injury prevention are interrelated and can be 

optimized simultaneously. For the purposes of this article, the term military physical readiness is an umbrella 

term referring to both HPO and IP efforts. This article 

describes (1) the scope and impact of the MSI problem 

on readiness; (2) the implications for the associations 

among physical training, fi tness, and injuries for readiness; (3) an assessment of current Army Physical Readiness Training Doctrine; (4) an overview of injury risk 

mitigation strategies and efforts; (5) current HPO/IP efforts in the Army targeting military physical readiness; 

(6) recommendations as to the implementation of organizational, communication, scientifi c, and operational 

changes through strategic planning; and (7) alternative 

scenarios for HPO/IP.

SCOPE AND IMPACT OF THE MUSCULOSKELETAL 

INJURY PROBLEM ON MILITARY READINESS

Former Army Surgeon General LTG Eric Schoomaker 

identifi ed that the Army’s deployment readiness was at 

just 85% for active duty and only 70% for Guard and Reserve forces.13 BG Brian Lein, former command surgeon 

at US Forces Command, warned that it would be diffi cult 

for the Army to maintain unit manning levels in the future if nondeployable status remained at the current level: 

If we don’t get our arms around the nondeployable population, and the biggest population is the MNR population, we’re going to have a signifi cant problem manning 

our units to get them to go downrange.... The Soldier is 

the center of our formations, so if the Soldier is not ready 

to go, then the unit is not ready to go.13

Across the military services, injuries represent the biggest medical threat to readiness.8,14,15 In 2012, MSIs 

resulted in over 2.2 million medical encounters annually across the military.16 These injuries affect more 

than 600,000 individual service members each year.17

In comparison, the second leading cause of medical encounters, mental disorders, results in approximately 2.1 

million encounters annually, affecting approximately 

250,000 service members.17 The biggest share of the injury problem (over 40%) belongs to the Army.8

 Across 

the services, overuse injuries can be estimated to cause 

more than 55% of all injury encounters by active duty 

service members.8

Published research demonstrates that the physical training-related injury risk is the highest for basic combat 

training in the Army and Marine Corps.9

 The incidence 

during US Army basic combat training ranges from 19% 

to 40% for men and 40% to 67% for women.18,19(pp6-7) For 

advanced individual training with training cycles from 

9 to 16 weeks duration, the literature reports trainingrelated injury incidences ranging from 24% to 40% for 

men and 30% to 60% for women.19(pp6-7) For operational 

units including infantry, armor, and military police, injury incidence has been reported to range from 5% to 

13% per month (equivalent to annualized rates of 60 

to 150 injuries per 100 soldiers per month) depending 

on the type of unit.19(pp6-7) Soldiers report that physical 

training and sports activities caused the largest proportion of these injuries. Army research shows that physical training and sports cause 53% to 63% for ordnance 

Soldiers in advanced individual training, 40% for armor 

Soldiers, 38% for garrison Soldiers, 42% for senior offi -

cers at the US Army War College, 58% for light infantry 

Soldiers, 53% for military police, and 34% for wheeled 

vehicle mechanics.19(pp6-7)

Downstream effects from the MSI epidemic in the military profoundly impact hospitalizations and outpatient 

visits, lost/limited duty time, and disabilities. Acute 

MSIs and chronic musculoskeletal conditions arising 

from injuries are consistently the leading cause of hospitalizations and outpatient visits in the military. Of the 

over 20 million ambulatory visits to military medical 

treatment facilities reported in 2012, over 4 million 

(20%) were acute injuries and other injury-related musculoskeletal/connective conditions.16

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
 October – December 2013 7

THE ARMY MEDICAL DEPARTMENT JOURNAL

It has been estimated that across all the services more 

than 25 million limited duty days annually result from 

injuries, an equivalent of 68,000 service members a 

year on limited duty.3,18(p11) If limited duty is prescribed 

in proportion to the percent of injuries reported by the 

services, the Army owns the largest share (slightly over 

40%) of those limited duty days or about 10 million limited duty days (about 27,000 man-years on limited duty 

each year). The healthcare costs alone ascribed to those 

68,000 DoD service members are over $700 million a 

year. The cost of salaries of Soldiers who cannot deploy 

is just over $3 billion annually. The costs to the Army 

for medical care and salaries of Soldiers on limited duty 

can be conservatively estimated to be about $1.5 billion 

per year. The time lost to commanders and organizations is incalculable.

The long-term effects in terms of disability discharges 

are just as sobering. Disabilities from MSIs have increased over time disproportionately to medical treatment rates.6,20 From 1982 to 2002, the disability discharge rates specifi cally for MSIs increased from less 

than 15 for both men and women to 140 per 10,000 for 

females (a 9-fold increase) and to 81 per 10,000 for males 

(a 5-fold increase).18(pp6-7) These disproportionate disability discharge rates between men and women imply that 

MSI risk mitigation strategies are essential for optimal 

performance among military women. Such injury risk 

mitigation strategies will be particularly critical as more 

women enter combat-centric occupations resulting from 

the elimination of the 1994 direct combat defi nition and 

assignment rule on January 9, 2013. In addition to the 

manpower losses incurred by the Army and other services due to disabilities, the Department of Veterans Affairs (VA) costs for compensation have historically been 

high.6

 The VA reported in 2001 that the annual compensation paid to disabled service members totaled over $21 

billion, with over $5.5 billion to service members with 

musculoskeletal disabilities.18(p10) Although it is understood that soldiering is a physically demanding occupation,21-26 the Army as an enterprise organization should 

not accept these high injury incidence rates and medical 

costs associated with them, especially since the risk factors for these injuries are largely understood and many 

methods for reducing injuries are available.

IMPLICATIONS FOR THE ASSOCIATION OF 

PHYSICAL TRAINING, FITNESS, AND 

INJURIES FOR READINESS

The rigor of physical training, particularly preparing for 

physically demanding military occupations, places great 

demands on the musculoskeletal system. The many benefi cial outcomes of effective physical training are well 

documented.18,27-30(pp6-7) Conversely, adverse outcomes 

also occur from physical training, the most common of 

which are MSIs. For example, many of the injury-related 

musculoskeletal conditions are due to the cumulative 

effects of repetitive microtrauma forces: overreaching/

training, overuse, overexertion, and repetitive movements experienced during both occupational duties and 

physical training.7

 Overuse injuries are an indicator that 

a unit is overtraining. As a consequence, one can expect 

that units with increasing overuse injury rates can also 

expect decreases in physical fi tness. Thus, injury rates 

can be reduced and physical fi tness enhanced by judicious modifi cations of training that can be calculated to 

optimize fi tness and minimize injury risks. Of the almost 750,000 MSIs reported in 2006 in military medical 

surveillance data on active duty, nondeployed service 

members, 82% were classifi ed as overuse.18(p16) As stated 

previously, typically 30% to 50% of these injuries are 

specifi cally attributable to physical training and sports 

activities.18(pp6-7)

The physical training MSI epidemic in the military training/garrison environment, arguably under-recognized 

by military leaders and policy makers, has been well 

documented in the scientifi c literature. Senior leaders 

should understand that the major cause of the more than 

30,000 medical evacuations between 2001–2006 from 

Operations Iraqi Freedom and Enduring Freedom were 

not battle injuries but rather nonbattle injuries (NBIs) 

from participation in sports and physical training activities. Hauret et al reported that medical evacuations for 

NBIs (36%) were twofold greater than for battle related 

injuries (18%).4

 The major causes for these nonbattle related medical evacuations were from physical training 

and sports (about 20% of the total). Further, Cohen et al 

reported that medical evacuations from Iraqi Freedom 

and Enduring Freedom were greater for musculoskeletal related injures (24%) than combat injuries (14%).31

Hence, effective physical training injury mitigation 

strategies are needed to keep more people “in the fi ght” 

and to decrease the number needed to be sent “to the 

fi ght” to replace those injured.

Numerous extrinsic and intrinsic risk factors for MSIs 

have been identifi ed. Extrinsic risk factors include high 

running mileage, age of running shoes, and seasonal 

variations, such as higher overall rates in summer.18(p23)

Intrinsic risk factors include female gender, low aerobic 

fi tness, low levels of physical activity prior to military 

entrance, cigarette smoking prior to military entrance, 

past ankle sprains, low muscular endurance, and older 

age.18(p18)

The most important modifi able risk factor for trainingrelated injuries is the physical training program itself. 
8 http://www.cs.amedd.army.mil/amedd_journal.aspx

Without physical training, these type of injuries do not 

occur. The scientifi c literature documents that greater 

volumes of training, especially weight-bearing physical 

training such as running or marching, are associated 

with higher risks of injuries.19,32-34 Among the intrinsic 

risk factors for training-related injuries, low levels of 

physical fi tness, in particular low levels of aerobic fi tness or slow run times, have been consistently shown to 

be associated with higher risks of such injuries.18,19,35-37

Ironically, this means that the Army and other services 

must expose service members to the risk of injury resulting from physical training in order to develop mission essential physical fi tness and accrue the benefi ts of 

higher levels of fi tness.

Interestingly, it has been shown that there are thresholds of physical training above which injury risks increase but physical fi tness plateaus or decreases.19,34,38

Increased injury risks and decreased physical performance are 2 of the cardinal signs of overtraining. If the 

thresholds of training indicative of overtraining can be 

identifi ed, scientists and commanders should be able to 

design programs that simultaneously minimize injury 

rates for units and enhance physical fi tness of Soldiers 

and other service members.

With the exception of considering aerobic fi tness levels in assigning basic trainees into groups for ability 

group runs,39 no systemic Army-wide policy exists for 

using known intrinsic risk factors to stratify Soldiers 

based upon injury risk potential and tailor their physical readiness training accordingly. More research is 

needed to identify modifi able risk factors for injury and 

the effectiveness of prevention strategies employing that 

knowledge.

ASSESSMENT OF CURRENT ARMY PHYSICAL 

READINESS TRAINING DOCTRINE

The Army continually tries to improve its physical 

training curriculum by inserting new evidence-based 

physical training information into policy and doctrine 

in an effort to balance HPO/IP. In October 2012, the 

Army Training and Doctrine Command’s (TRADOC) 

Army Physical Fitness School published an authoritative 

doctrine in the form of Field Manual 7-22, Army Physical Readiness Training.

39 Beginning in the early 2000s, 

the US Army Physical Fitness School initiated efforts 

to redesign Army physical training. In consultation 

with subject matter experts from the Army Institute of 

Public Health at the US Army Public Health Command 

(USAPHC) and the US Army Research Institute of Environmental Medicine, a program was designed to improve Warfi ghter’s physical capability for military operations and reduce musculoskeletal injuries. This was 

achieved by examining the standard list of warrior tasks 

and determining: (1) physical requirements of military 

tasks; (2) fi tness components involved; and (3) training 

activities most likely to improve performance of military tasks. Injury prevention features included reduced 

running mileage, exercise variety (cross-training), and 

gradual, progressive training.40 This program was subsequently validated in fi eld and laboratory studies41-43

which demonstrated that the overall adjusted injury risk 

was 1.5 to 1.8 times higher in groups of Soldiers performing traditional military physical training compared 

to groups participating in the new physical readiness 

training (PRT). Scores on the Army Physical Fitness 

Test (APFT) and physical performance metrics were 

similar or higher in groups using the PRT programs.40,44

The Army adopted the new PRT as offi cial doctrine as a 

result of these studies.

Despite the advantages and benefi ts of the current evidence-based Army PRT, several areas of concern and 

limitations with the current doctrine must be acknowledged. First, the PRT program was only assessed over 

a relatively short time period (approximately 8 weeks). 

Kraemer et al have shown that the incorporation of resistance training provides superior gains in strength, 

power, muscle hypertrophy, and military task performance over a 6-month training period when compared 

to conventional military fi eld training.45 Recently, Grier 

et al have shown that more weekly resistance training 

imparts a protective effect for injuries in infantry Soldiers.46 Fortunately, TRADOC is examining ways to encourage and monitor other test components of physical 

fi tness rather than relying solely on aerobic fi tness and 

muscle endurance.

Although there are a number of short-term studies available in the literature, a paucity of research has considered 

physical performance adaptations over the “life-cycle 

spectrum” of the Warfi ghter, particularly among operational units. Important considerations for physical training optimization among our Soldiers, in terms of incorporating resistance training, must be acknowledged. For 

relatively untrained Soldiers, improvements in strength 

at the onset of training are primarily due to neural factors (eg, increased agonist activation, improved motor 

unit coordination, and synchronization). Therefore, previously untrained Soldiers/recruits should participate 

fi rst in relatively low-load, low-volume resistance exercise protocols to induce substantial improvements in 

strength and minimize the likelihood of injury due to 

relatively modest loads and volume. Following 2 to 3 

months of training, the initial period of rapid neural adaptations has elapsed and most additional strength gains 

are due to muscular factors (ie, hypertrophy). After the 

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
 October – December 2013 9

THE ARMY MEDICAL DEPARTMENT JOURNAL

initial few months of resistance training, heavier loads 

and greater volumes of lifting appear to be required for 

further performance enhancement.19 It would be diffi -

cult to identify the optimal physical training programs 

without additional validation studies.

Second, the majority of fi eld validations utilized the 

APFT as the performance outcome measure. Debate is 

ongoing among military physical training subject matter 

experts with regard to the appropriateness of the APFT 

to assess the capability of a Warfi ghter to perform occupational and/or combat duties.47 However, no other 

established and accepted metrics of “combat or functional performance” is yet available. In 2012, the Army 

evaluated 2 different tests for consideration as doctrine: 

(1) an APRT consisting of a 60-yard shuttle run, 1-minute rower, standing long jump, 1-minute push-up, and 

2-mile run to replace the APFT; and (2) an Army Combat Readiness Test.

Currently, a Baseline Soldier Physical Readiness Requirements study is being conducted by the TRADOC 

Initial Military Training Center with support from leading subject matter experts from the USAPHC, the US 

Army Research Institute of Environmental Medicine, 

the US Military Academy, the C onsortium for Health 

and Military Performance (CHAMP) at the Uniformed 

Services University of the Health Sciences (USUHS), 

and the TRADOC Physical Readiness Division. The intent of this study is to systematically quantify, evaluate, 

and summarize the physical demands of warrior tasks 

and battle drills to determine, validate, and implement 

appropriate physical testing that would be used to assess a Soldier’s ability to successfully execute warrior 

tasks and battle drills. This study is projected to result 

in implementation of a new physical readiness testing 

paradigm in May 2015. It is clear that continued efforts 

are required to identify and establish the most valid 

metrics for military physical performance assessment. 

These TRADOC efforts indicate a paradigm change for 

physical training and testing.

INJURY RISK MITIGATION STRATEGIES AND EFFORTS

In a 2003 policy memorandum, Secretary of Defense 

Donald Rumsfeld challenged the DoD to reduce the incidence of preventable accidents. The memo stated:

World-class organizations do not tolerate preventable 

accidents. Our accident rates have increased recently, 

and we need to turn this situation around. I challenge 

all of you to reduce the number of mishaps and accident 

rates by at least 50% in the next two years. These goals 

are achievable and will directly increase our operational 

readiness. We owe no less to the men and women who 

defend our nation.48

In response to that memorandum, the Defense Safety 

Oversight Council (DSOC), chaired by the Under Secretary of Defense for Personnel and Readiness, was 

formed to provide governance on DoD-wide efforts to 

reduce preventable injuries. The Military Training Task 

Force (MTTF), comprised of civilian and military injury 

experts from Johns Hopkins Center for Injury Research 

and Policy and the Army Center for Health Promotion 

and Preventive Medicine (now the USAPHC), was chartered to support this accident and injury prevention directive with a focus on interventions that relate to all 

aspects of military training.49 The Joint services Physical Training Injury Prevention Working Group (JSPTIPWG) was created under the MTTF in September 2004 

to evaluate military physical training injury prevention 

programs, policies, and research for recommendations 

to reduce physical training-related injuries.49 An expedited systematic review process was used by the working group to: (1) establish the evidence base for making 

recommendations to prevent physical training-related 

injuries; (2) prioritize the recommendations for prevention programs and policies; and (3) prioritize further 

research and evaluation efforts that could likely reduce 

physical training-related injuries.49

Of the 40 promising injury prevention strategies systematically reviewed, only 6 intervention strategies to 

reduce physical training-related injuries had the requisite evidence-based scientifi c support to recommend for 

implementation across the military. These interventions 

in order of priority were: (1) prevent overtraining (ie, excessive running mileage); (2) perform multiaxial, neuromuscular, proprioceptive, and agility training; (3) wear 

mouthguards during high-risk activities; (4) wear semirigid ankle braces for high risk activities; (5) consume 

nutrients to restore energy balance within one hour following high-intensity activity; and (6) wear syntheticblend socks to prevent blisters.49 It is important to note 

that not all of these evidence-based interventions have 

been implemented as doctrine. Of equal interest, 23 intervention strategies with some theoretical basis for effi cacy were identifi ed as lacking suffi cient evidence to 

recommend at that time.49 The JSPTIPWG recommended that upon determination by systematic reviews that 

scientifi c information is scant and gaps exist in knowledge about prevention, more research is needed before 

the implementation of policies and programs.50 The efforts of the DSOC and the MTTF work group indicated 

that the DoD and the services are no longer willing to 

accept injuries as a given cost of conducting training 

and operations.
10 http://www.cs.amedd.army.mil/amedd_journal.aspx

CURRENT HPO/IP EFFORTS IN THE ARMY 

TARGETING MILITARY PHYSICAL READINESS

The Army published Technical Bulletin MED 592, Prevention and Control of Musculoskeletal Injuries Associated with Physical Training19 in May 2010. It is an important comprehensive document that translates stateof-the-art guidance into principles that military and civilian healthcare providers and allied medical personnel 

can understand and implement. Such evidence-based 

preventive principles can protect Army personnel from 

musculoskeletal injuries associated with physical training. The document serves as an authoritative source on 

HPO/IP and helps military care providers and leaders:

 understand physiologic and pathophysiologic responses to exercise,

 know risk factors associated with training-related 

musculoskeletal injuries,

 understand interventions with varying levels of 

evidence for effectiveness in preventing trainingrelated injuries,

 recognize the presentation and acute treatment of 

Soldiers with training-related MSIs,

 evaluate and appropriately treat Soldiers with acute 

training-related MSIs, and

 advise commanders on planning, implementing, and 

evaluating any proposed comprehensive program 

designed to reduce physical training-related MSIs.

A common trend among Warfi ghters is extreme conditioning programs (ECPs) (for example, CrossFit (CrossFit Inc, Washington, DC), Insanity (Beachbody LLC, 

Santa Monica, CA), Gym Jones (Gym Jones LLC, Salt 

Lake City, UT), and others) characterized by high-volume, intense training workouts. These well-marketed 

and popularized conditioning programs continue to 

generate interest and support among military and civilian fi tness communities. Acceptance of ECPs is reinforced by anecdotal reports of marked gains in physical 

performance. However, physicians and other primary 

care and rehabilitation providers have identifi ed a potential emerging problem of disproportionate MSI risk, 

particularly for novice participants. Muscle strains, torn 

ligaments, stress fractures, and mild to severe cases of 

potentially life-threatening exertional rhabdomyolysis 

have been anecdotally reported in increasing numbers 

as the popularity of ECPs has grown.51 Unfortunately, 

the short- and long-term physiological, functional, and 

readiness outcomes or safety of ECPs have not been 

carefully studied. Only one study to date has reported 

fi tness outcomes in the peer-reviewed literature using a 

CrossFit-based program. Smith et al reported increases 

in maximal aerobic fi tness and body composition after 

10 weeks of training. However, limitations for this study 

were that a control group was not included in the study 

and injury data were not reported.52

On September 13 and 14, 2010, a workshop on ECPs, 

composed of the CHAMP, other members of the DoD, 

and representatives of the American College of Sports 

Medicine, was convened at the USUHS in Bethesda, 

Maryland, to begin a critical dialog on this important 

issue.53 From this workshop, the consensus was that 

further research was needed to confi rm or negate the 

purported increase in injury risk from participating in 

ECPs and clarify other modifi able contributing factors.53

Former US Army Surgeon General LTG Eric Schoomaker initiated an ongoing effort germane to HPO/

IP in the military. LTG Schoomaker identifi ed Soldier 

Medical Readiness as his number one priority.54 The 

US Army Medical Command (MEDCOM) has partnered with the Headquarters, Department of the Army 

(HQDA); US Army Forces Command (FORSCOM); 

TRADOC; Installation Management Command; US 

Army Reserve Command; US Army Special Operations 

Command; Director, Army National Guard; US Army 

Human Resource Command; HQDA G-1; and HQDA 

G3/5/7 to execute a coordinated campaign to increase 

medical readiness in the Army. Through execution of 

this campaign, MEDCOM expects support to: (1) deploy healthy, resilient, and fi t Warfi ghters; (2) increase 

the medical readiness of the Army; and (3) effectively 

manage the medically not ready (MNR) population to 

return the maximum number of Warfi ghters possible 

to deployable status. These goals will be accomplished 

through 3 primary lines of effort:

1.0 MNR Soldier Identifi cation

2.0 MNR Management Programs

3.0 Evidence-Based Health Promotion,

HPO/IP Programs

Line of Effort (LOE) 3.0 of the Soldier Medical Readiness Campaign Plan54 (SMR-CP) embodies the key task 

to coordinate, synchronize, and integrate health promotion, injury prevention, and human performance optimization programs across the Army with key objectives to 

improve physical fi tness and reduce injury rates. Figure 

1 lists the SMR-CP LOE 3.0 strategic objectives, objective statements, quantifi able measures, target goals, and 

initiatives. The main objectives of this LOE are to: (1) 

provide evidence-based health promotion services to enable healthy lifestyle choices and eliminate preventable 

health issues that contribute to MNR Soldiers; (2) implement, support, and evaluate promising injury prevention 

and performance optimization best practices/programs; 

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
 October – December 2013 11

THE ARMY MEDICAL DEPARTMENT JOURNAL

(3) assess existing best practices and their evidence base 

and evaluate the feasibility of incorporating them into 

standardized best practices to improve management of 

injuries and optimize Soldier Medical Readiness; and 

(4) identify research programs within Army Medicine 

that contribute to HPO/IP, and communicate evidencebased lessons learned from these studies.

The Army MEDCOM is championing the initiatives 

of the Performance Triad Campaign conceived by The 

Surgeon General, LTG Patricia Horoho, which focuses 

on sustaining and enhancing Soldier stamina by implementing educational programs, motivational strategies, and revised policies to optimize aspects of Soldier 

health—activity, nutrition, and sleep—among the force. 

Operational implementation of this strategic initiative 

with an institutional, proactive system for health (as opposed to a reactive healthcare system) should maintain, 

restore, and improve health by improving fi tness and 

mitigating MSIs.55 A specifi c area of emphasis related 

to physical readiness involves providing greater educational awareness for Army Physical Readiness Training 

Strategic Objective: Synchronize Medical Readiness Related Research

Objective Statement: communicate commanders’ and public health research needs; collaborate with Army 

partners on HPO/IP projects; and enhance communication of evidence-based lessons learned to commanders, 

policy makers, and the health promotion community; ultimately contributing to the reduction in MNR Soldiers.

Measures: (1) number of scientifi c publications on MSI; (2) number of scientifi c presentations on MSI; (3) 

number of current agreements that leverage Army partners.

Target: (1) >50% manuscripts on MSI in peer-reviewed journals per fi scal year; (2) 5 talks/presentations 

per fi scal year specifi cally on MSI research; (3) one agreement with and Army partner to disseminate MSI 

research lessons learned not later than September 30, 2011.

Initiatives: (1) complete research inventory; (2) complete list of suggested future HPO/IP research; (3) develop 

communication/coordination strategy

Strategic Objective: Improve Integration of Musculoskeletal Injuries Rehabilitation Programs

Objective Statement: synchronize, coordinate, and improve unit-based and MTF-based musculoskeletal 

injury rehabilitation programs to enable Soldier medical readiness.

Measures: number of Soldier profi le days due to musculoskeletal injury in FORSCOM units evaluated.

Target: 15% decrease in profi le days due to MSI in FORSCOM units evaluated.

Initiatives: (1) unit-based medical management; (2) unit-based rehabilitation program; (3) musculoskeletal 

action plan; (4) aquatic rehabilitation pilot program; (5) aquatic warrior exercise program standardization.

Strategic Objective: Improve Soldier Injury Prevention/Human Performance

Objective Statement: coordinate and synchronize evidence-based HPO/IP policies and programs that support 

Army Force Generation in each of its phases in order to improve the medical readiness of the Army.

Measures: (1) percentage that pass APFT in FORSCOM units evaluated; (2) percentage of Soldier injury 

rate in FORSCOM units evaluated; (3) recommendations for injury prevention provided to FORSCOM units 

evaluated.

Target: (1) >85% pass rate on current APFT in FORSCOM units evaluated; (2) 15% decrease in injury rate in 

FORSCOM units evaluated; (3) recommendations for injury prevention targets provided to FORSCOM units 

evaluated (25th ID, 4th ID).

Initiatives: (1) conduct inventory of ongoing Army HPO/IP programs and initiatives; (2) conduct review of 

evidence-based support for HPO/IP initiatives and infantry division best practices and gaps; (3) implement, 

support, review and evaluate promising Army HPO/IP initiatives; (4) Initial Entry Training Soldier Athlete 

initiative; (5) 101st Eagle Tactical Athlete Program Research study; (6) 4th ID Iron Horse Performance 

Optimization US Army Medical Command/FORSCOM; (7) US Army Special Operations Command 

(USASOC) Tactical Human Optimization Rapid Rehabilitation Reconditioning initiative; (8) USASOC Ranger 

Athlete Warrior Program; (9) 25th ID Advanced Tactical Athlete Conditioning initiative; (10) implement policy, 

guidance, education, and training and incorporate them into HPO/IP initiatives.

Note: Detailed descriptions of HOP/IP initiatives are presented in Figure 3.

Figure 1. Soldier Medical Readiness Campaign Plan (SMR-CP) LOE 3.0: Evidence-Based Health Promotion, 

Injury Prevention, and Human Performance Optimization Programs Balanced Scorecard.54
12 http://www.cs.amedd.army.mil/amedd_journal.aspx

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

Figure 2. Performance Triad Activity Concept of Operations. The presentation of this Concept of Operations was part of a Performance Triad decision brief to The US Army Surgeon General on October 16, 2012.

LOE 1: Education – Inculcating a paradigm shift with the manner in which the Army views health should must start with the training 

base with appropriate programs of instruction. Evidence-based activity-centric research conducted by the US Army Research Institute of Environmental Medicine and others and published in peer-reviewed journals will serve as the cornerstone for establishing 

valid and effective best practices. Growing subject matter expertise within the Army can also be facilitated by partnering with relevant 

nonprofi t health organizations such as the American College of Sports Medicine and the National Strength and Conditioning Association. These organizations offer industry-accepted certifi cations for health and fi tness practitioners. Information dissemination of 

evidence-based scientifi c information from credible sources, such as the USAPHC and the Human Performance Resource Center, will 

be critical in providing the military with accurate and timely information.

LOE 2: Programs – There are many existing and emerging programs both within and outside of the Army that can be leveraged to foster greater awareness for activity among Soldiers and their families, such as Army Wellness Centers and Comprehensive Soldier and 

Family Fitness. Training and embedding master fi tness trainers and master resiliency trainers across the Army will provide subject 

matter experts to educate Soldiers in physical and mental activities, such as mindfulness. Programs outside the military, such as the 

American College of Sports Medicine’s Exercise Is Medicine, that promote activity as a vital sign could be useful for integrating physicians, as well as allied health and fi tness professionals prescribing exercise programs. The Army Morale, Welfare, and Recreation 

program serves as a platform to reach military families with activity-centric programs and initiatives.

LOE 3: Policy – Enforcing physical readiness training and requiring Army Wellness Center orientations will ensure fi tness and exercise 

principles are practiced and disseminated. Active engagement by Army senior leaders in modeling and support via policy directives, 

as well as physical and mental activity efforts will resonate among Soldiers. Policies for families, civilians, and other special populations (pregnant Soldiers, etc) will ensure the Army family is engaged with improving their activity. Physical readiness assessment 

changes underway in the military have the potential to change the way Soldiers train. Environmental/infrastructure policy changes 

can also change the manner in which activity is fostered. Integrating and synchronizing the Activity lines of effort for education, 

programs, and policies should all summate to change the mindset of the Army family so that stamina is maintained, restored and 

improved.
 October – December 2013 13

THE ARMY MEDICAL DEPARTMENT JOURNAL

doctrine, functional fi tness, ECPs, minimalist running 

shoes, dangers of prolonged sitting, preventing injuries, 

safe running, preparing to perform physical activity, and 

resistance training. The Activity LOE within the Performance Triad (Figure 2) could be particularly successful if implementation of the TRADOC MFT program 

is adopted. Embedding MFTs within operational units 

down to the lowest level feasible could serve the dual 

role of providing and sustaining legacy subject matter 

experts on HPO/IP practices, as well as role modeling 

“what right looks like” to promote the desired behavior 

modifi cation. Figure 2 illustrates a concept of operations for activity using education, program, and policy 

lines of effort.

Figure 3 provides more detailed descriptions for the current HPO/IP initiatives listed under the SMR-CP strategic objective: improve soldier injury prevention/human 

performance. Although a number of innovative HPO/

IP initiatives are currently ongoing, most of these initiatives are largely unknown beyond where they are being 

locally conducted; they are not part of a larger synchronized, integrated, and coordinated HPO/IP effort. An 

opportunity exists to use these examples and adopt lessons learned so we can move forward with a more global, 

unifi ed, and focused approach. This could lead to published research fi ndings providing militarily feasible, acceptable, and suitable HPO/IP interventions and performance outcome measures. Until such efforts have been 

fully validated as scientifi cally credible and shown to be 

effective, caution should be exercised before widespread 

implementation. The 2 MEDCOM initiatives, the Soldier Medical Readiness and the Performance Triad campaigns, demonstrate that the Army medical community 

intends to transform their paradigm from one of reactive 

health care to one of proactive promotion of health.

An analysis of the strengths, weaknesses, opportunities, 

and threats of current HPO/IP initiatives in the Army is 

provided in Figure 4. Clear strengths of the current state 

of military HPO/IP programs which could be exploited 

to facilitate further progress are indicated. However, to 

capitalize on current momentum, action by senior Army 

leaders is required to review HPO/IP policies and direct 

the development of strategic initiatives to improve upon 

weaknesses and neutralize growing threats.

RECOMMENDATIONS FOR THE WAY AHEAD: 

IMPLEMENTING ORGANIZATIONAL, 

COMMUNICATION, SCIENTIFIC, AND OPERATIONAL 

CHANGE THROUGH STRATEGIC PLANNING

A paradigm shift is beginning in the Army and DoD 

approaches to physical readiness policies, training, and 

doctrine. The Army initiatives described above testify 

to this need. In January 2004, the Deputy Secretary of 

Defense directed the Joint Staff to “develop the next 

generation of...programs designed to optimize human 

performance and maximize fi ghting strength.”58 Subsequently, a new joint human performance enhancement 

capabilities document addressed human-performance 

standards, metrics, capabilities, and gaps.58 The joint 

human performance enhancement capabilities outlined 

in the Joint Force Health Protection Concept of Operations12 include: (1) manage Warfi ghter fatigue; (2) optimize human-systems integration; (3) enhance Warfighter sensory, cognitive, and motor capabilities; (4) 

enhance Warfi ghter learning, communications, and decision making; (5) enhance physiological capability; (6) 

provide/maintain ability to operate across the full range 

of environments; and (7) provide a healthy and fi t force.

In 2005, the DoD Offi ce of Net Assessment published 

Human Performance Optimization and Military Missions.

59 This report spawned a request from the Assistant Secretary of Defense, Health Affairs (ASD/HA) to 

the military services to convene a conference that was 

held June 7-9, 2006. The goal of the conference was to 

initiate development of a strategic plan for HPO within 

the military. The conference was titled “Human Performance Optimization in DoD: Charting a Course for the 

Future.”60

The conference included subject matter experts from 

over 56 different DoD stakeholder groups: senior leaders (ADM Michael Mullen, Chairman of the Joint 

Chiefs of Staff was the keynote speaker),61 Warfi ghters/

operators, unit commanders, allied health professionals, 

scientists and researchers, and safety offi cers. Recommendations from the workshop were published in a report forwarded to ASD/HA and a special supplement 

issue of Military Medicine.

62 In response to this report, 

the ASD/HA convened a HPO Integrated Product Team 

to review the USUHS report, collect relevant data from 

the services, and make recommendations for a novel 

comprehensive HPO program. Among these was a directive to The Army Surgeon General to incorporate 

key HPO requirements into a Joint Medical Research 

Command (under the US Unifi ed Medical Command) 

as a key focus area. The plan for a US Unifi ed Medical 

Command was later rejected in December 2006 primarily due to resistance from Air Force senior leadership.63

With current federal budgetary constraints and the potential to reduce redundancies, conserve resources, and 

implement interoperability and collaboration among the 

services, the concept of a unifi ed medical command is 

again worth consideration.64,65 Currently, it appears the 

establishment off a Defense Health Agency in October 

2013 is an effort toward developing a set of strategies 
14 http://www.cs.amedd.army.mil/amedd_journal.aspx

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

Initiative Title: Ranger, Athlete, Warrior (RAW) Program

Proponent: 75th Ranger Regiment

Description/Comments: Uses Army physical therapist-led train-the-trainer course and is a conglomeration of 

several physical performance techniques focusing on body mechanics, strength, speed, agility, and military 

task performance. Includes a RAW physical performance assessment as a metric.

Initiative Title: Eagle Tactical Athlete Program

Proponent: 101st Airborne/Air Assault Division and the University of Pittsburgh

Description/Comments: Extramural funded (via the Army Medical Research and Material Command 

Telemedicine and Advanced Technology Research Center) research effort comprehensively evaluating aspects 

of HPO/IP: injury surveillance, task and demand analysis, predictors of injury and optimal performance, 

design and validation of interventions, program integration and implementation, and monitoring to determine 

effectiveness of program.56

Initiative Title: Mountain Athlete Program

Proponent: 4th ID/FORSCOM

Description/Comments: HPO program team consists of an Army physical therapist, CrossFit certifi ed 

trainers, and power lifting coaches who focus on muscular strength, muscular and cardiovascular endurance, 

speed, agility, and fl exibility. The goal is to reduce nondeployable injury rates and increase unit readiness.

Initiative Title: Iron Horse Performance Optimization Program

Proponent: 4th ID/FORSCOM

Description/Comments: Uses an embedded musculoskeletal action team (MAT) in a Brigade Combat Team 

through a full Army Force Generation cycle focusing on optimizing performance, minimizing injuries, 

identifying/treating injuries early, reconditioning rehabilitated Soldiers.

Initiative Title: Soldier Athlete Initiative

Proponent: TRADOC/MEDCOM

Description/Comments: Uses an MAT concept at TRADOC initial entry sites to address injury incidence 

rates.

Initiative Title: Tactical Human Optimization Rapid Rehabilitation & Reconditioning Program

Proponent: US Army Special Operations Command (USASOC)

Description/Comments: Program incorporates a team consisting of physical therapists, strength and 

conditioning coaches, and a dietician to reduce injury, improve functional performance, and optimize proper 

fueling. Each team sets program priorities and performance metrics.

Initiative Title: Advanced Tactical Athlete Conditioning

Proponent: MEDCOM/25th ID

Description/Comments: Provides tools (train-the-trainer) and information necessary to lead Soldiers through 

a tactical, battle-focused approach to PT. Includes high-intensity aquatic training, tactical agility physical 

training, combat core conditioning, interval speed training, and running form analysis. The USAPHC is 

conducting program evaluation.

Initiative Title: Military Power, Performance and Prevention

Proponent: MEDCOM/US Army Medical Department Center and School

Description/Comments: This program measures multiple performance metrics such as mobility, power, and 

balance and injury surveillance in 2/75th Ranger Battalion, 1st Special Forces, a Stryker brigade and a support 

brigade from the 2nd ID. The goal is to identify those performance metrics that are predictive of injury. A 

special and unique feature of the initiative is the use of technology as a leveraging tool for the assessment and 

data collection.

Figure 3. Human performance optimization and injury prevention initiatives tracked by the Offi ce of The Surgeon General.57
 October – December 2013 15

THE ARMY MEDICAL DEPARTMENT JOURNAL

Strengths

1. Current doctrine provided in Field Manual 7-2239 to guidelines established by the American College of 

Sports Medicine and the National Strength and Conditioning Association and has been validated by peerreviewed, published research.

2. Numerous intrinsic injury risk factors have been identifi ed via evidence-based and peer-reviewed research 

fi ndings.

3. Innovative research efforts and public health practices occur with the US Army Medical Command (Medical Research and Material Command and USAPHC) that prioritizes HPO/IP research, surveillance, and 

evaluation.

4. Many examples of human performance optimization and injury prevention initiatives currently ongoing 

across the Army.

5. Increasing senior leader awareness with regard to the impact of musculoskeletal injuries on military readiness and national security.

6. Current and future science and technology advances hold great promise with regard to human performance 

optimization and injury prevention research.

Weaknesses

1. The incidence rate for musculoskeletal injuries remains unacceptably high.

2. Lack of physical training/injury prevention subject matter experts organic to the military personnel system. 

3. The main proponent for physical readiness training (US Army Physical Fitness School) is not resourced 

adequately, particularly with personnel.

4. Poor synchronization, integration, and communication of human performance optimization/injury prevention efforts across Army commands and operators, health practitioners, researchers, and leaders.

5. Implementation of physical training doctrine is unevenly applied across the Army.

6. Validated and accepted performance metrics do not exist with regard to human performance optimization/

injury prevention.

7. HPO/IP initiatives have not been systematically applied or researched across the Warfi ghter’s entire lifecycle or within Army Reserve or National Guard units.

Opportunities

1. Soldier Medical Readiness Campaign.

2. Performance Triad Campaign.

3. Establishment of a Defense Health Agency.

4. Master fi tness trainers.

5. Current and future science and technology advances hold great promise with regard to human performance 

optimization and injury prevention research.

6. Increasing senior leader awareness with regard to the impact of musculoskeletal injuries on military readiness and national security.

7. Military health and fi tness outreach to society’s youth.

8. Revise manner in which HPO/IP is assessed. Establish metrics of performance and effectiveness.

Threats

1. Commercialized HPO/IP entities (CrossFit, etc) are becoming increasingly popular among Soldiers and 

have not been supported by evidence-based research.

2. Shrinking budgets can negatively impact research and development budgets and HPO/IP resource allocation.

3. Excessive and increasing external loads (load carriage).

4. Increasing societal trends for declining activity levels and fi tness. Increased obesity. 

5. Lack of Unifi ed Joint Medical/Research Command.

Figure 4. Strengths, weaknesses, opportunities and threats analysis for current Army HPO/IP initiatives.
16 http://www.cs.amedd.army.mil/amedd_journal.aspx

on governance to achieve certain effi ciencies on “shared 

services” across the DoD.

The workshop categorized the major issues/challenges 

to achieving HPO as (1) organizational, (2) communication, (3) scientifi c, and (4) operational, based upon 

the type of strategic action required to resolve identifi ed obstacles within DoD.60 With regard to organizational issues, existing policies should be reviewed with 

guidance to ensure consistency of HPO approaches in 

response to new research and technological developments.60 Another important related issue involves operational translation and dissemination of knowledge and 

research results to commanders and Warfi ghters.60 The 

workshop recommended the establishment of a joint 

center for HPO to translate knowledge and research 

into the DoD standard of Doctrine, Organization, Training, Material, Leadership, Personnel, and Facilities.60

The Human Performance Resource Center at CHAMP 

is an online (http://hprc-online.org/about-us/about-hprc)

clearinghouse and information repository that serves to 

translate and disseminate timely, accurate, scientifi cally 

based HPO information to commanders, Warfi ghters, 

medical personnel, and researchers, some key examples 

of which are shown in Figure 5.

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

Source Comments

Field Manual 7-22: Army Physical Readiness 

Training39 (October 2012)

Supersedes discontinued Training Circular 3-22.20: 

Army Physical Readiness Training (August 2010)

Technical Bulletin Med 592: Prevention and Control of Musculoskeletal Injuries Associated with 

Physical Training18 (May 2011)

First medical technical bulletin dedicated to disseminating evidence-based guidance for controlling MSIs.

Consortium for Health and Military Performance and American College of Sports Medicine Consensus Paper on Extreme Conditioning 

Programs in Military Personnel53

This peer-reviewed scientifi c manuscript is the product of a joint workshop addressing extreme conditioning programs held September 13-14, 2010, at USUHS, 

Bethesda, MD.

American Journal of Preventive Medicine, January 2010, Volume 38 (Supplement 1)

This supplement contains 25 peer-reviewed articles 

from the Joint Services Physical Training Injury Prevention Working Group which include systematic 

reviews.3,4,7,8,10,49,50

Military Medicine (Supplement: Total Force Fitness for the 21st Century: A New Paradigm), 

August 2010, Volume 175(8)60

This supplement contains 15 peer-reviewed articles 

from the 2006 joint service workshop “Human Performance Optimization in DoD: Charting a Course for 

the Future” hosted by USUHS, Bethesda, MD.

Warfi ghter Nutrition: Current Opportunities and 

Advanced Technologies Report From a Department of Defense Workshop55

This peer-reviewed article is the product of a joint DoD 

conference which concluded that nutritional optimization represents an integral and proactive approach to 

prevent illness, injury, and performance degradation 

throughout all phases of military service.

Physiological Employment Standards III: 

Physiological Challenges and Consequences 

Encountered During International Military 

Deployments23

This peer-reviewed article was the result of an Invited 

Keynote Presentation at the 1st Australian Conference 

on Physiological and Physical Employment Standards, 

28 November 28, 2012 in Canberra, Australia. It provides a comprehensive overview of the physiological 

effects of deployment with a particular focus on physical fi tness and injuries.

Human Performance Resource Center: A DoD 

initiative under the Force Health Protection and 

Readiness Program

(http://hprc-online.org/about-us/about-hprc)

A website sponsored by the CHAMP at USUHS that 

translates and disseminates accurate, scientifi callybased HPO information to commanders, Warfi ghters, 

medical personnel, and researchers.

Figure 5. Key authoritative military physical readiness sources for Army senior leaders.
 October – December 2013 17

THE ARMY MEDICAL DEPARTMENT JOURNAL

Communication remains a large barrier to the achievement of HPO. A common concern is that commanders 

and clinicians in the fi eld are typically unaware of current HPO information and research efforts. Operators at 

the highest levels often do not have adequate visibility of 

research results and existing biomedical solutions. There 

are also concerns about valid and reliable information 

from military research reaching the Warfi ghter, but rather 

the Warfi ghter gathers his information from unsubstantial commercial venues.60 Consequently, opportunities 

for military scientists to regularly interact with operators 

about evidence and development of scientifi c fi ndings 

should be encouraged. Future communication efforts 

should focus on coordination within and across services. 

Ideally, organizations that conduct HPO research need to 

be teamed with representatives from acquisition, medical 

personnel, and operational units from the fi eld to discuss 

current research, to identify opportunities for cooperation, and to determine future HPO needs.60

The scientifi c issues raised by the workshop centered on 

the need to develop operationally relevant and standardized metrics to meet joint military requirements.53 The 

development of these metrics was considered the single 

most important issue for research and application of 

HPO.60 Accepted, reliable, and valid metrics that relate 

to combat effectiveness for all of the above capabilities 

are limited and remain an area for which joint consensus is needed, particularly for measures of performance 

and measures of effectiveness. Ideally, research efforts 

should consider the Warfi ghter through his/her entire life cycle as an integrated program of preparation, 

training, and monitoring from accession to retirement/

separation.60

From an operational perspective, collaboration between 

operators and medical researchers is essential for developing and fi elding feasible, acceptable, and suitable 

HPO approaches.60 Options for maintaining functional 

fi tness, performance nutrition, cognitive and psychological readiness throughout predeployment, deployment/

engagement, and postdeployment/ redeployment timelines are desired and critically needed.60 The HPO programming should preserve human capital by addressing 

service member weaknesses, injury and disease prevention, physical readiness training, maximizing sleep 

quality, and other factors affecting performance.60

The vision moving forward is to have HPO conceived as 

a joint, interagency, combined and coalition effort that 

creates an interdisciplinary center for investigating HPO 

in operational settings as well as establishing translational research and education agendas that address barriers and approaches to optimal performance. Developing 

effective communication netrworks that cross research, 

medical and operational boundaries is critical to the success of this effort.60 The recommended course of action 

is to provide HPO functionality by establishing a unifi ed 

Joint Medical Research Program with a core HPO function. The specifi c objectives of such an option would be 

to: (1) advocate for HPO within DoD; (2) coordinate and 

integrate DoD extramural and intramural HPO medical 

research; (3) align HPO initiatives to DoD priorities; (4) 

collaborate with line HPO research functions to ensure 

synergy toward common endpoints; (5) establish HPO 

standards, (6) establish a clearinghouse function; (7) 

continue to leverage the Health Affairs HPO IPT as a 

community of interest; 8) recommend HPO policy and 

doctrine to Assistant Secretary of the Army (Health Affairs).60 A concerted and integrated strategic HPO effort 

will serve to: (1) enhance the mental and physical resilience of the Warfi ghter; (2) reduce injury and illness 

or facilitate more rapid recovery if injury does occur; 

(3) provide seamless information and knowledge transfer from the laboratory to line; (4) improve the human 

weapon system’s ability to accomplish the mission; and 

(5) allow the United States to remain at the leading/cutting edge in this area.60 With the sanctioning of CHAMP 

and their educational arm, the Human Performance Resource Center at the USUHS as a Defense Center of Excellence (Figure 5), and the establishment of the Health 

Affairs Human Performance Optimization Health Sciences Advisory Committee, many of the recommendations are being realized.

ALTERNATIVE SCENARIOS FOR HPO/IP

On February 19, 2013, the Strategy Innovation Offi ce 

of USAPHC conducted an alternative exercise considering possible future scenarios with over 20 subject matter 

experts from the USAPHC Epidemiology and Disease 

Surveillance and the Health Promotion and Wellness 

Portfolios, and CHAMP. The purpose of this exercise 

was to brainstorm and develop narratives for different 

future HPO/IP scenarios based upon alternative political, economic, organizational, operational, environmental, scientifi c, technological, and social assumptions. 

Figure 6 depicts 2 key variables that would potentially 

infl uence future HPO/IP scenarios: (1) the use of scientifi c, evidence-based best practices; and (2) the extent to 

which senior leadership supports, prioritizes, and implements scientifi c innovative, synchronized, and integrated HPO/IP policy changes. Of the 4 possible alternative 

scenarios represented in Figure 6, two were chosen to 

script narratives for the best case, most desired scenario 

(Resilient, Dominant Warfi ghter) and the worst case 

(Injured, Nondeployable Warfi ghter), projected to occur 

unless appropriate strategies are implemented. These 

scenarios are discussed below.
18 http://www.cs.amedd.army.mil/amedd_journal.aspx

Scenario 1: Resilient, Dominant Warfighter

As the military becomes smaller, senior leadership will 

prioritize and place a greater emphasis on preservation 

of the force by focusing on proven preventive and public 

health practices. A more selective screening process will 

be used to recruit new military trainees based on established baseline physical and cognitive requirements to 

perform military occupations and duties. Better predictive models and analytics will yield better placement of 

Soldiers in military occupational specialties.

The military prioritizes investment in research and development. Technological advances in materiel science 

and further refi nement of exoskeletons result in lighter 

external loads. Biosensor technologies provide great insight for training physiology and recovery and are used 

as important adjuncts to planning physical training. A 

detailed cost-benefi t analysis indicates that signifi cant 

cost savings can result from embedding medical, physical fi tness, and nutritional subject matter experts into 

operational units. Deliberate and detailed physiological studies on women in the military will identify risk 

mitigation and HPO/IP strategies to protect against increased MSI risk. When data systems are integrated and 

able to communicate with one another, the information 

gathered is used to refi ne models predicting risk; new 

models are applied to pre-identify injuries and negative 

outcomes before they occur.

The HPO/IP and human systems are given the same attention as weapons systems. The military strategically 

partners with leading nonprofi t HPO/IP organizations 

(eg, the American College of Sports Medicine, National 

Strength and Conditioning Association) to assist in disseminating credible and validated HPO/IP information. 

Logically extending from the MFT course, additional 

occupational specialties or additional skill identifi er 

dedicated toward HPO/IP are implemented. Identifi ers 

exist for units and Soldiers to engage in healthy behaviors, which lead to improved HPO/IP efforts. The HPO/

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

Anecdotal and/or historical precendence 

drives HOP/IP doctrine and policy

“Science-Light”

Senior leadership fails to prioritize

HPO/IP programs.

“Strategic Complacency”

Desired Status Current Status

Current Status Projected Status

Senior leadership implements innovative 

HOP/IP policy changes.

“Strategic Action”

3. “Warfi ghter Cannot Carry His 

Load.”

HPO/IP efforts in the military are 

not supported by evidence-based 

science.

2. “Walking Wounded Warfi ghter”

Status quo: MSIs continue to 

degrade the military’s human capital.

4. “Injured, Nondeployable 

Warfi ghter”

Severe MSI epidemic degrades the 

US military as national instrument 

of power.

1. “Resilient, Dominant Warfi ghter”

Integrated and synchronized

HPO/IP efforts establish

strategic dominance.

Scientifi c, evidence-based best practices 

drive HPO/IP doctrine and policy.

“Science-Plus”

Figure 6. Conceptual alternative future scenario framework portrays 2 major variables: the vertical axis depicts the extent 

to which HPO/IP practices in the Army are supported by scientifi c evidence-based best practices (Science Plus vs Science 

Light). The horizontal axis depicts the extent to which senior leadership supports, prioritizes, and implements innovative, 

synchronized, and integrated HPO/IP policy changes (Strategic Action vs Strategic Complacency). Each quadrant uses a 

pairing of these 4 states to frame a scenario, examine possible strategic intervention measures, and explore potential strategic outcomes: 1. Resilient, Dominant Warfi ghter; 2. Walking Wounded Warfi ghter; 3. Warfi ghter Cannot Carry His Load; 

and 4. Injured, Nondeployable Warfi ghter. The narratives for the best case (Resilient, Dominant Warfi ghter) and worst case 

(Injured, Nondeployable Warfi ghter) scenarios are presented in the text.
 October – December 2013 19

THE ARMY MEDICAL DEPARTMENT JOURNAL

IP efforts are individualized and exploit the latest scientifi c and technological breakthroughs. Additionally, 

military environments are redesigned and organized to 

take advantage of the latest HPO/IP scientifi c and technological breakthroughs. Dining facility administration centers employ dietary specialists to ensure quality 

throughout all food venues on bases.

Science is embraced by senior Army leadership, and 

HPO/IP science advisors are embedded in major Army 

commands to facilitate policy decisions governing the 

health and fi tness of Soldiers. A joint DoD HPO/IP center is created to ensure a rapid process for systemic reviews and increased research funding for HPO/IP translational research. Research is communicated effectively 

and in a timely fashion to the operational force. The military becomes the worldwide leader in HPO/IP, resulting with the emergence of resilient and dominant Warfi ghters who effectively project our military power and 

act as deterrents to hostile action from our adversaries.

Scenario 2: Injured, Nondeployable Warfighter

With the downsizing of the military and further budget cuts, a danger exists that preventive medicine, public health, and HPO/IP research initiatives will be forsaken. Fewer medical assets, allied health professionals, 

and other HPO/IP enablers (MFTs, health promotion 

offi cers, resiliency and wellness centers, and so forth) 

will be available in the personnel inventory. Fewer resources result in the military experiencing a technology lag, which leads to a decline in personal protective 

equipment development and, consequently, a continued 

increase in external loads Soldiers are required to carry. 

A moderate “brain drain” occurs in the military research 

and development community as research budgets shrink 

further to marginalize HPO/IP research efforts. As scientifi c conference attendance restrictions are sustained, 

military scientists lose relevance and expertise resulting 

in more scientists leaving government service.

Increased use of drones and alternate technologies 

changes the dynamics of the fi ghting force. Commanders become less interested in maintaining military physical readiness as the nature of warfare becomes more 

technological, while there is a focus shift from physical 

to cognitive performance. The associated increase in 

physical health problems and degradation of individual 

health lead to more injuries and chronic disease; this 

amplifi es behavioral health concerns as a result of increased cognitive trauma and stress. Long-term health 

care and long-term disability costs rise, which overwhelms the federal budget and results in diminished 

quality of care. The societal trends for decreased fi tness 

continue. The implosion of obesity and the medically 

unfi t results in even higher injury rates halting progress 

toward a system for health.

Implementation of validated science-based best-practices is lost in a cacophony of messages, marketing, and 

voices, many driven by non-DoD “pseudo” HPO/IP 

subject matter experts motivated primarily by fi nancial 

profi t and/or personal gain. Confused and demoralized 

Soldiers obtain their HPO/IP information from unvetted 

sources available through the internet and companies 

catering to the military for profi t.

The end result is a military characterized as injured and 

nondeployable. The military has compromised stamina 

and ceases to be an effective instrument of national political power. Seeking to exploit this vulnerability, other 

hostile nation states and nonstate actors provoke aggression to create internal and external confl icts and “small 

wars.”

CONCLUSION

It is imperative for military leaders to understand that 

physical training-related MSIs are preventable when 

composite risk management principles are closely followed and pragmatic strategy and policy changes are 

considered. Figure 5 provides a list of some authoritative HPO/IP sources for military leaders reference as 

needed. The following recommendations are offered to 

establish a comprehensive, evidence-based approach to 

military HPO/IP60:

 Increase HPO/IP knowledge and expertise across 

the military. Implementation of additional occupational specialties or additional skill identifi ers dedicated toward HPO/IP (ie, MFTs) could be productive.

 Implement/adapt evidence-based, proven physical 

training and injury prevention strategies based on 

preestablished priorities.

 Evaluate effectiveness of all implemented policies, 

procedures, and interventions/countermeasures on 

a continuous basis.

 Identify gaps in knowledge of human physical performance optimization and injury prevention, and 

target these gaps for research.

 Establish routine channels for disseminating information based on each public health and evidencebased decision-making process to ensure key stakeholders receive the information and training necessary to effectively reduce the impact of injuries on 

the health and readiness of military personnel.

 Use readily available military surveillance databases to identify the largest, most serious military 

injury problems.
20 http://www.cs.amedd.army.mil/amedd_journal.aspx

 Commission systematic reviews of prevention and 

safety literature to determine what works for the 

largest, most serious military injury problems.

 Establish committees of medical and safety subject 

matter experts to routinely assess and prioritize 

both injury prevention research and program/policy 

implementation.

As our military transforms and responds to current and 

emerging threats, it is increasingly clear that we must 

ensure optimal human performance of our military. 

By taking advantage of the science and applications of 

physical fi tness and injury prevention, we can leverage 

our increased understanding to reduce the risk of injuries with the optimal application of our physical and 

mental readiness processes, ensuring that we maintain 

our Soldiers as Army Strong.

RELEVANCE TO PERFORMANCE TRIAD

The Army Surgeon General has provided visionary guidance for Army Medicine to transform from a healthcare 

system to a system for health. The foundation for this is 

the Performance Triad of activity, nutrition, and sleep.

LTG Horoho is particularly timely and insightful in her 

vision for Army Medicine following 12 years of war. 

The time is ripe for a paradigm shift, and this article 

highlights the many ongoing efforts within the DoD and 

Army that are indicative of a climate of change. In this 

article we provide a strategic vision for Army leadership and policy makers on a path for enhanced military 

physical readiness, which directly supports the Activity 

Line of Effort for the Performance Triad. By identifying, 

prioritizing, resourcing, and assigning proponency for 

HPO/IP solutions, we believe success can be realized. 

A continued dialogue and forging of partnerships with 

all relevant stakeholders will be critical for altering the 

mindset for behavior change to drive HPO/IP solutions 

and develop healthy and resilient Warfi ghters.

ACKNOWLEDGEMENTS

This article is based on a paper that was completed 

as part of a Strategic Research Project and in partial 

fulfi llment for the Masters Degree in Strategic Studies 

while Dr Nindl was a Department of the Army civilian 

in residence from 2011-2012 at the Army War College, 

Carlisle, PA. Particular recognition and appreciation for 

their support goes to Dr Thomas Williams (COL (Ret), 

USA), who served as the Strategic Research Project 

advisor, Professor Edward Filiberti (COL (Ret), USA), his 

academic advisor and Seminar 3 lead instructor, and Ms 

Julie Manta (COL (Ret), USA), civilian student advisor.

REFERENCES

1. Garamone J, Parrish K. Military strategy drives 

budget decisions, Dempsey says [internet]. American Forces Press Service. December 9, 2011. 

Available at: http://www.defense.gov/News/News

Article.aspx?ID=66419. Accessed August 29, 2013.

2. Garamone J. Panetta announces fi scal 2013 budget 

priorities [internet]. American Forces Press Service. January 26, 2012. Available at: http://www.

defense.gov/News/NewsArticle.aspx?ID=66940. 

Accessed August 29, 2013.

3. Ruscio BA, Jones BH, Bullock SH, et al. A process 

to identify military injury prevention priorities 

based on injury type and limited duty days. Am J 

Prev Med. 2010;38(suppl 1):S19-S33.

4. Hauret KG, Taylor BJ, Clemmons NS, Block SR, 

Jones BH. Frequency and causes of nonbattle injuries air evacuated from operations Iraqi Freedom 

and Enduring Freedom, U.S. Army, 2001-2006. Am 

J Prev Med. 2010;38(suppl 1):S94-S107.

5. Feuerstein M, Berkowitz SM, Peck CA Jr. Musculoskeletal-related disability in US Army personnel: 

prevalence, gender, and military occupational specialties. J Occup Environ Med. 1997;39(1):68-78.

6. Amoroso PJ, Canham ML. Chapter 4. Disabilities 

related to the musculoskeletal system: Physical 

Evaluation Board Data. Mil Med. 1999;164(suppl 

8):1-73.

7. Hauret KG, Jones BH, Bullock SH, Canham-Chervak M, Canada S. Musculoskeletal injuries description of an under-recognized injury problem among 

military personnel. Am J Prev Med. 2010;38(suppl 

1):S61-S70.

8. Jones BH, Canham-Chervak M, Canada S, Mitchener TA, Moore S. Medical surveillance of injuries 

in the U.S. Military: descriptive epidemiology and 

recommendations for improvement. Am J Prev 

Med. 2010;38(suppl 1):S42-S60.

9. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and 

injury prevention in military populations. Sports 

Med. 1999;27(2):111-125.

10. Schoomaker LE. The U.S. Army Medical Department commitment to injury reduction. Am J Prev 

Med. 2010;38(suppl 1):S217.

11. Quadrennial Defense Review. Washington, DC: 

US Dept of Defense; February 2010. Available 

at: http://www.defense.gov/qdr/images/QDR_as_

of_12Feb10_1000.pdf. Accessed August 29, 2013.

12. Joint Force Health Protection Concept of Operations. Ver 1.0. Washington, DC: US Dept of Defense; July 2007. Available at: http://pre.docdat.com/

docs/index-21211.html. Accessed August 29, 2013.

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
 October – December 2013 21

THE ARMY MEDICAL DEPARTMENT JOURNAL

13. Sample D. Army wants more Soldiers back on deployable status [internet]. Army News Service. October 11, 2011. Available at: http://www.army.mil/

article/67037/. Accessed August 29, 2013.

14. Jones BH, Perrotta DM, Canham-Chervak ML, 

Nee MA, Brundage JF. Injuries in the military: a 

review and commentary focused on prevention. 

Am J Prev Med. 2000;18(suppl 3):71-84.

15. Atlas of injuries in the United States Armed Forces. 

Mil Med. 1999;164(suppl 8).

16. Army Medical Surveillance Activity. Absolute and 

relative morbidity burdens attributable to various 

illnesses and injuries, U.S. Armed Forces, 2012. 

MSMR. 2013;20(4):5-10.

17. Army Medical Surveillance Activity. Estimates of 

absolute and relative health care burdens attributable to various illnesses and injuries, U.S. Armed 

Forces, 2005. MSMR. 2006;12(3):16-22. Available 

at: http://www.afhsc.mil/viewMSMR?fi le=2006/

v12_n03.pdf#Article3. Accessed August 29, 2013.

18. Gilchrist J, Jones BH, Sleet DA, Kimsey CD. Exercise-related injuries among women: strategies 

for prevention from civilian and military studies. 

MMWR Recomm Rep. 2000;49(RR-2):15-33.

19. Technical Bulletin Med 592: Prevention and Control of Musculoskeletal Injuries Associated with 

Physical Training. Washington, DC: US Dept of 

the Army; May 2011. Available at: http://armypubs.

army.mil/med/dr_pubs/dr_a/pdf/tbmed592.pdf. 

Accessed August 29, 2013.

20. Bell NS, Schwartz CE, Harford T, Hollander 

IE, Amoroso PJ. The changing profi le of disability in the U.S. Army: 1981-2005. Disabil Health J. 

2008;1(1):14-24.

21. Nindl BC, Alemany JA, Kellogg MD, et al. Utility of circulating IGF-I as a biomarker for assessing body composition changes in men during 

periods of high physical activity superimposed 

upon energy and sleep restriction. J Appl Physiol. 

2007;103(1):340-346.

22. Nindl BC, Barnes BR, Alemany JA, Frykman PN, 

Shippee RL, Friedl KE. Physiological consequences of U.S. Army Ranger training. Med Sci Sports 

Exerc. 2007;39(8):1380-1387.

23. Nindl BC, Castellani JW, Warr BJ, et al. Physiological employment standards III: physiological challenges and consequences encountered during international military deployments. Eur J Appl Physiol. 

February 2013 [epub].

24. Nindl BC, Castellani JW, Young AJ, et al. Differential responses of IGF-I molecular complexes to 

military operational fi eld training. J Appl Physiol. 

2003;95(3):1083-1089.

25. Nindl BC, Leone CD, Tharion WJ, et al. Physical performance responses during 72 h of military operational stress. Med Sci Sports Exerc. 

2002;34(11):1814-1822.

26. Nindl BC, Rarick KR, Castellani JW, et al. Altered 

secretion of growth hormone and luteinizing hormone after 84 h of sustained physical exertion superimposed on caloric and sleep restriction. J Appl 

Physiol. 2006;100(1):120-128.

27. Nindl BC. Insulin-like growth factor-I, physical 

activity, and control of cellular anabolism. Med Sci 

Sports Exerc. 2010;42(1):35-38.

28. Nindl BC, Pierce JR. Insulin-like growth factor I 

as a biomarker of health, fi tness, and training status. Med Sci Sports Exerc. 2010;42(1):39-49.

29. Kraemer WJ, Adams K, Cafarelli E, et al. American College of Sports Medicine position stand. Progression models in resistance training for healthy 

adults. Med Sci Sports Exerc. 2002;34(2):364-380.

30. Nindl BC, Scofi eld DE, Strohbach CA, et al. IGFI, IGFBPs, and infl ammatory cytokine responses 

during gender-integrated Israeli Army basic combat training. J Strength Cond Res. 2012;26 (suppl 

2):S73-S81.

31. Cohen SP, Brown C, Kurihara C, Plunkett A, 

Nguyen C, Strassels SA. Diagnoses and factors associated with medical evacuation and return to duty for service members participating 

in Operation Iraqi Freedom or Operation Enduring Freedom: a prospective cohort study. Lancet. 

2010;375(9711):301-309.

32. Koplan JP, Powell KE, Sikes RK, Shirley RW, Campbell CC. An epidemiologic study of the benefi ts and 

risks of running. JAMA. 1982;248(23):3118-3121.

33. Knapik JJ, Hauret KG, Canada S, Marin R, Jones B. 

Association between ambulatory physical activity 

and injuries during United States Army Basic Combat Training. J Phys Act Health. 2011;8(4):496-502.

34. Jones BH, Cowan DN, Knapik JJ. Exercise, training and injuries. Sports Med. 1994;18(3):202-214.

35. Knapik JJ, Sharp MA, Canham-Chervak M, 

Hauret K, Patton JF, Jones BH. Risk factors for 

training-related injuries among men and women 

in basic combat training. Med Sci Sports Exerc. 

2001;33(6):946-954.

36. Jones BH, Cowan DN, Tomlinson JP, Robinson 

JR, Polly DW, Frykman PN. Epidemiology of injuries associated with physical training among 

young men in the army. Med Sci Sports Exerc. 

1993;25(2):197-203.

37. Jones BH, Bovee MW, Harris JM III, Cowan DN. 

Intrinsic risk factors for exercise-related injuries 

among male and female army trainees. Am J Sports 

Med. 1993;21(5):705-710.
22 http://www.cs.amedd.army.mil/amedd_journal.aspx

38. Pollock ML, Gettman LR, Milesis CA, Bah MD, 

Durstine L, Johnson RB. Effects of frequency and 

duration of training on attrition and incidence of 

injury. Med Sci Sports. Spring 1977;9(1):31-36.

39. Field Manual 7-22: Army Physical Readiness 

Training. Washington, DC: US Dept of the Army; 

October 2012. Available at: http://armypubs.army.

mil/doctrine/DR_pubs/dr_a/pdf/fm7_22.pdf. Accessed August 29, 2013.

40. Knapik JJ, Rieger W, Palkoska F, Van Camp S, 

Darakjy S. United States Army physical readiness training: rationale and evaluation of the 

physical training doctrine. J Strength Cond Res. 

2009;23(4):1353-1362.

41. Knapik JJ, Hauret KG, Arnold S, et al. Injury 

and fi tness outcomes during implementation of 

physical readiness training. Int J Sports Med. 

2003;24(5):372-381.

42. Knapik JJ, Bullock SH, Canada S, et al. Infl uence of an injury reduction program on injury 

and fi tness outcomes among soldiers. Inj Prev. 

2004;10(1):37-42.

43. Knapik J, Darakjy S, Scott SJ, et al. Evaluation 

of a standardized physical training program for 

basic combat training. J Strength Cond Res. May 

2005;19(2):246-253.

44. Harman EA, Gutekunst DJ, Frykman PN, et al. Effects of two different eight-week training programs 

on military physical performance. J Strength Cond 

Res. March 2008;22(2):524-534.

45. Kraemer WJ, Mazzetti SA, Nindl BC, et al. Effect 

of resistance training on women’s strength/power 

and occupational performances. Med Sci Sports 

Exerc. Jun 2001;33(6):1011-1025.

46. Grier T, Canham-Chervak M, McNulty V, Jones B. 

Extreme conditioning programs and injury risk in 

a U.S. Army brigade combat team. US Army Med 

Dep J. October–December 2013:36-47.

47. National Strength and Conditioning Association 

Blue Ribbon Panel on Military Physical Readiness; 

13-14 January, 2011; Key West, FL.

48. US Secretary of Defense. Memorandum: Reducing 

Preventable Accidents. Washington, DC: US Dept 

of Defense; May 19, 2003. Available at: http://www.

defense.gov/news/May2003/U06916-03.pdf. Accessed August 29, 2013.

49. Bullock SH, Jones BH, Gilchrist J, Marshall SW. 

Prevention of physical training-related injuries 

recommendations for the military and other active 

populations based on expedited systematic reviews. 

Am J Prev Med. 2010;38(suppl 1):S156-S181.

50. Jones BH, Canham-Chervak M, Sleet DA. An evidence-based public health approach to injury priorities and prevention recommendations for the U.S. 

military. Am J Prev Med. 2010;38(suppl 1):S1-S10.

51. Hadeed M, Kuehl K, Elliot D, Sleigh A. Exertional 

rhadbomyolysis after crossfi t exercise program. 

Med Sci Sports Exerc. 2011;43(suppl 5):S152.

52. Smith MM, Sommer AJ, Starkoff BE, Devor ST. 

Crossfi t-based high intensity power training improves maximal aerobic fi tness and body composition. J Strength Cond Res. February 22, 2013 

[epub].

53. Bergeron MF, Nindl BC, Deuster PA, et al. Consortium for Health and Military Performance 

and American College of Sports Medicine consensus paper on extreme conditioning programs 

in military personnel. Curr Sports Med Rep. 

2011;10(6):383-389.

54. Soldier Medical Readiness Campaign Plan 

2011-2016. Washington, DC: US Army Medical 

Command; May 2011. Available at: http://www.

armymedicine.army.mil/news/docs/SMR_CP_

Version_1.2.pdf. Accessed August 29, 2013.

55. Deuster PA, Weinstein AA, Sobel A, Young AJ. 

Warfi ghter nutrition: current opportunities and advanced technologies report from a Department of 

Defense workshop. Mil Med. 2009;174(7):671-677.

56. Sell TC, Abt JP, Crawford K, et al. Warrior model 

for human performance and injury prevention: Eagle Tactical Athlete Program (ETAP) Part I. J Spec 

Oper Med. 2010;10(4):2-21.

57. Pendergrass T. Injury Prevention and Human Performance Optimization Initiatives. Washington, 

DC: Offi ce of The Army Surgeon General; 12 July 

2011.

58. Performance Optimization (HPO) within DoD. 

Paper presented at: 2007 Military Health System 

Conference; January 29 – February 1, 2007; Washington, DC.

59. Russell A, Bulkley B, Grafton C. Human Performance Optimization and Military Missions: Final 

Report, GS-10F-0297K. Washington, DC: Offi ce of 

Net Assessment, US Dept of Defense; May 2005.

60. Deuster PA, O’Connor FG, Henry KA, et al. Human performance optimization: an evolving 

charge to the Department of Defense. Mil Med. 

2007;172(11):1133-1137.

61. Mullen M. On total force fi tness in war and peace. 

Mil Med. 2010;175:1-2.

62. Jonas WB, Deuster PA, O’Connor FG, Macedonia 

C, eds. Total Force Fitness for the 21st Century: A 

New Paradigm. Alexandria, VA: Samueli Institute; 

August 2010 [featured in special supplement to Mil 

Med August 2010;175(8)]. Available at: http://www.

dtic.mil/cgi-bin/GetTRDoc?AD=ADA528391. Accessed August 29, 2013. 

 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING

MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
 October – December 2013 23

THE ARMY MEDICAL DEPARTMENT JOURNAL

63. Philpott T. Three-branch plan for unifi ed medical 

command rejected info [serial online]. Newport 

News Daily Press; December 17, 2006. Available 

at: http://www.military-quotes.com/forum/threebranch-plan-unifi ed-medical-t30131.html. 

Accessed August 29, 2013.

64. Kumpula D. Joint Medical Command – Do it now

[master’s thesis]. Carlisle Barracks, PA: US Army 

War College; 2005. Available at: http://www.dtic.mil/

cgi-bin/GetTRDoc?AD=ADA434405. 

Accessed August 29, 2013.

65. Smith AM, Lane DA, Zimble JA. Purple medicine: 

the case for a joint medical command. Naval War 

College Review. 2007;60(1):1-11. Available at: http://

www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA519521. 

Accessed August 29, 2013.

AUTHORS

Dr Nindl is the Science Advisor for the US Army Institute 

of Public Health, US Army Public Health Command, 

Aberdeen Proving Ground, Maryland.

Dr Williams is the Director of the Strategic Leader 

Resiliency Program at the Army War College, Carlisle, 

Pennsylvania.

Dr Deuster is the Director for the Consortium for Health 

and Military Performance Defense Center of Excellence 

at the Uniformed Services University of the Health 

Sciences, Bethesda, Maryland.

COL Butler is the Chief, Army Medical Specialist 

Corps and Specialist Corps Branch Chief (LTC/COL 

Assignments Offi cer) at the Human Resources Command, 

Fort Knox, Kentucky.

Dr Jones is the Manager of the Injury Program, 

Epidemiology and Disease Surveillance Portfolio, US 

Army Institute of Public Health, US Army Public Health 

Command, Aberdeen Proving Ground, Maryland.
24 http://www.cs.amedd.army.mil/amedd_journal.aspx

...physical fi tness is not only one of the most important keys to a healthy body; it is the basis of dynamic 

and creative intellectual activity.

President-Elect John F. Kennedy1

Various groups representing a number of different perspectives (for example, operational, architectural, community, institutional, and individual resilience) have 

defi ned the term resilience. For the purposes of this 

article, we defi ne resilience as the ability to withstand, 

recover, and grow in the face of stressors and changing 

demands.2

In recent reviews and papers on resilience, one factor 

that continues to appear as promoting and/or conferring 

resilience is physical fi tness3,4 and regular physical activity.5-7 Thus, we focus on the role of physical fi tness 

in overall individual resilience. The benefi t of physical 

fi tness on resilience is in part based on the recognition 

that physical fi tness, achieved through physical activity 

and/or regular exercise, can induce positive physiologic 

and psychological benefi ts, protect against the potential consequences of stressful events, and prevent many 

chronic diseases.8-11 After a brief historical overview of 

the health-promoting effects of exercise and physical activity, the following topics are discussed: the concept of 

hardiness and mental toughness and how they relate to 

resilience and physical fi tness; how physical fi tness promotes resilience; the clinical implications of a sedentary 

lifestyle; and the relevance of physical fi tness and resilience to Army Medicine’s Performance Triad. Throughout this article, the terms physical activity and exercise 

are used interchangeably, depending on the literature, 

recognizing that exercise represents a planned, structured, and regular form of physical activity.

HISTORICAL OVERVIEW

The quest for physical fi tness has been unremitting, however, its importance and application have changed and/

or transitioned over time with both high and low points. 

Hunting and gathering for survival were the initial impetus for fi tness, which was later followed by the recognition that selected physical movements and activities 

were important for developing the body and preventing 

and curing diseases.12-14 In fact, the importance of regular exercise and physical activity has been touted for 

over 7,000 years.12,13 In China, the philosophical teachings of Confucius encouraged participation in regular 

physical activity, as physical inactivity was recognized 

as associated with certain diseases.12 The Chinese developed many perspectives on how to achieve and maintain 

health, and they deemed exercise essential for increasing 

strength, prolonging life, preventing and curing diseases, and minimizing the accumulation of fat.12 Quigong, 

Cong fou (later Kung Fu), and Tai-Chi were some of the 

gymnastic/movement forms developed in China sometime around 3,000 BC.

12 Among the Greeks, Herodicus 

(circa 450 BC) was the fi rst to promote physical activity, and he even considered exercise a form of medicine. 

Nonetheless, Hippocrates is usually considered the father of exercise and medicine.13 These 2 Greeks were followed by Galen (129-210 AD)15 who was perhaps the most 

advanced, as he wrote not only about when to exercise, 

but he also described various types of exercises, identifi ed qualities of exercise, specifi c places to exercise, and 

factors to think about prior to exercise.13 Although the 

Physical Fitness:

 A Pathway to Health and Resilience

Patricia A. Deuster, PhD, MPH

Marni N. Silverman, PhD

ABSTRACT

Various groups representing a number of different perspectives (for example, operational, architectural, community, institutional, and individual resilience) use the term resilience. We defi ne resilience as the ability to 

withstand, recover, and grow in the face of stressors and changing demands. Physical fi tness is one pathway 

toward resilience because it is associated with many traits and attributes required for resilience. In addition, 

physical fi tness confers resilience because regular exercise and/or physical activity induces positive physiologic 

and psychological benefi ts, protects against the potential consequences of stressful events, and prevents many 

chronic diseases. This article presents a brief historical overview of the health-promoting effects of exercise 

and physical activity, followed by a discussion on the concept of hardiness and mental toughness and how they 

relate to resilience and physical fi tness; how physical fi tness promotes resilience; the clinical implications of a 

sedentary lifestyle; and the relevance of physical fi tness and resilience to Army Medicine’s Performance Triad.
 October – December 2013 25

importance of exercise and physical fi tness diminished 

during various periods of time, such as after the fall of 

the Roman empire when the church became the dominant infl uence,16 during the period of industrialization,12

and notably during the 1920s (often called the Roaring 

Twenties) when relaxation and enjoyment were key.12

However, the importance of exercise remains widely 

recognized. It is interesting to refl ect on the comment of 

Edward Stanley, the 15th Earl of Derby, who stated in an 

address at Liverpool College on December 20, 1873 that:

Those who think they have not time for bodily exercise 

will sooner or later have to fi nd time for illness.14

It is discouraging to realize we have made little progress 

over the centuries.

PERSONALITY TRAITS/ATTRIBUTES ASSOCIATED 

WITH RESILIENCE

Although the term resilience, as it is used today, emerged 

from work on children living under conditions of deprivation,17-20 it is now applied to diverse disciplines5-7 and 

populations.21-24 Identifying how and why some individuals are seemingly able to bear up, and sometimes 

thrive, under adverse conditions with no observable negative physical or psychological outcomes, is a continuous quest.5-7,25-33 Personality traits associated with resilience include hardiness and mental toughness.9,34-46 The 

term hardiness, as considered by Kobasa et al,34,37-43 was 

typifi ed by “interrelated orientations of commitment (vs 

alienation), control (vs powerlessness), and challenge 

(vs threat).”41 This original characterization was later 

refi ned by Maddi,11 who proposed that hardiness is an 

attitude (or set of attitudes) and personality trait that 

helps an individual restructure stressors into growth opportunities rather than allowing them to be or become 

catastrophes.

Bartone et al47,48 developed the dispositional hardiness 

scale to assess hardiness, and this scale has been used in 

a number of studies to relate hardiness characteristics in 

persons exposed to challenging occupations and experiences.45,49-52 Bonanno53 noted that hardiness is one of the 

pathways to resilience. Crust et al36 developed the model 

of mental toughness by applying the traits of hardiness 

to refl ect the unique demands of sports and exercise; the 

trait of confi dence was added to control, commitment, 

and challenge.35,36,44,46,54,55 As noted by Crust et al36:

Mentally tough individuals are considered to be competitive, resilient to errors or stress, and have high selfconfi dence and low anxiety.

The literature clearly shows that both hardiness and 

mental toughness are highly related to resilience.28,56-58 

In addition to the personality traits of hardiness and 

mental toughness, other psychological attributes and 

social-cognitive variables have been associated with 

resilience, including self-esteem, self-effi cacy and motivation.20,21,59-62 How do these closely associated traits or 

attributes relate to physical fi tness and physical activity?

PERSONALITY TRAITS/ATTRIBUTES ASSOCIATED 

WITH PHYSICAL FITNESS

Interestingly, regular physical activity and aerobic fi tness have been shown to be associated with specifi c 

personality traits and psychological attributes63-72 associated with resilience. For example, anxiety and depression are inversely related to maximal aerobic capacity, a 

primary indicator of physical fi tness.73,74 Moreover, our 

unpublished data show a signifi cant positive association 

between aerobic capacity and hardiness (r=0.24), and an 

inverse relation with perceived stress (r=-0.26) and trait 

anxiety (r=-0.17). Of note, Skirka et al10 reported signifi cantly higher hardiness scores, less perceived stress, 

and fewer psychological symptoms in varsity college 

athletes than college nonathletes, which further supports 

a strong association between regular exercise, aerobic 

fi tness, and hardiness. Furthermore, mental toughness, 

the personality trait associated with athletes and athletic 

competition, has been shown to mitigate the relationship 

between high stress and depressive symptoms.57

Two determinants of physical activity, self-esteem and 

self-effi cacy, be they enduring traits or modifi able attributes, are essential for resilience.65,66,75 Self-effi cacy generally refl ects how self-confi dent a person is with regard 

to undertaking a particular action under challenging 

situations,67,72,76,77 and self-esteem signifi es ones sense 

of self-worth or personal value.68 Multiple studies have 

shown that children and young adults who participate in 

regular exercise score higher on measures of self-esteem 

and self-effi cacy67,70-72,76,78-80 and competitiveness81 compared to sedentary, untrained controls. Moreover, these 

two attributes are improved through regular physical 

activity.69,72 Netz et al72 conducted a meta-analysis of 36 

studies examining how physical activity interventions 

affected well-being in healthy adults. Moderate intensity aerobic exercise was shown to be most benefi cial and 

had a strong effect on self-effi cacy, in addition to conferring improvements in aerobic capacity and strength. 

Ekeland et al69 likewise conducted a systematic review 

of 12 studies to assess how exercise affected self-esteem 

in children and young people. They concluded that exercise has positive short-term effects on self-esteem and 

that it might be an important strategy for improving selfesteem. Interestingly, one hypothesis as to how physical 

activity enhances self-effi cacy and self-esteem is that it 

requires the application of self-management strategies 

(eg, thoughts, goals, plans, and acts) to achieve a goal.76
26 http://www.cs.amedd.army.mil/amedd_journal.aspx

Self-management strategies require commitment, control, and motivation, and although each strategy is important, motivation appears to be key in terms of regular 

physical activity.70,78,82-85 Research has shown that motivation is very important with regard to commencing 

and maintaining participation in regular physical exercise.76,84 According to the literature, motivation is some 

force or stimulus that leads an individual to undertake 

a particular task or activity in which they have a specifi c objective or derive personal meaning.78,82,83 Overall, these studies strongly suggest that personality traits 

(hardiness and mental toughness) and other attributes 

(self-esteem, self-effi cacy, motivation, self-management strategies) may contribute to the buffering effect 

of physical fi tness and how fi tness confers resilience. 

Further, one must be motivated to be committed, and 

possess self-effi cacy and self-esteem to accept a challenge. Clearly, strong relationships exist between and 

among hardiness or mental toughness, self-effi cacy, 

self-esteem, and motivation; all essential resources for 

resilience, and all associated with physical fi tness.

PHYSICAL FITNESS AND STRESS RESILIENCE

That physical fi tness is essential for health and well-being 

is not in question, as noted in the earlier historical overview. However, scientifi c data documenting the essentiality of physical activity for health did not emerge until 

the late 1800s and early 1900s when epidemiological 

studies demonstrated that sedentary persons were more 

likely to have coronary heart disease than those who led 

active lifestyles.16,86-90 Since those fi rst studies, the literature has become replete with evidence that physical fi tness and regular exercise confer resilience and serve as a 

resistance resource in a variety of ways, including blunting stress reactivity in response to both physical and psychosocial stressors, conferring multiple physiologic and 

psychological benefi ts, serving as a buffer against stress, 

and protecting against stress-related disorders and many 

chronic illnesses.57,74,78,91-95 A conceptual model of the 

personality traits and attributes associated with physical 

fi tness and resilience is presented in the Figure.

Physical Fitness Blunts Stress Reactivity in Response 

to Both Physical and Psychosocial Stressors: 

Physiologic and Psychological Benefits

The 2 main neuroendocrine/neural systems that mediate the stress response are the hypothalamic-pituitaryadrenal axis, with the resultant release of cortisol, and 

the sympathetic nervous system, which releases the catecholamines epinephrine (adrenaline) and norepinephrine. Activation of these stress systems mediates the 

fi ght or fl ight response, which entails the rapid mobilization of energy from storage sites to critical muscles 

and the brain (getting one ready for action, increasing 

alertness/arousal). Moreover, increased heart rate, blood 

pressure, and breathing rate facilitate the rapid transport 

of nutrients and oxygen to relevant parts of the body. Together, these stress systems orchestrate the physiologic 

and behavioral adaptations to stress. However, chronic 

activation can lead to dysregulation of multiple physiologic and behavioral systems, leading to maladaptive 

stress responses, including anxiety and depression.96,97

Physical fi tness and aerobic fi tness have been related to 

a reduction in stress reactivity, physiologically and psychologically, for both physical and mental/psychosocial 

stress.65,98-107

Interestingly, neuroendocrine and physiologic responses 

to exercise at the same absolute workload are signifi -

cantly lower in physically fi t than unfi t persons.108-111 Additionally, physically active people show reduced sympathoadrenal reactivity to physical stressors.109,110 When 

untrained persons are enrolled in a regular exercise program for 8-12 weeks, their response to the same physical 

stress prior to beginning exercise training is signifi cantly higher than after the training.112 Thus, when trained 

and untrained persons have to work at the same rate, 

the untrained person will experience signifi cantly more 

stress than someone who is physically fi t and aerobically 

trained.108-110 Therefore, the higher the level of aerobic 

fi tness, the greater the ability to tolerate high workloads 

and be minimally stressed by low ones.

Physical training also appears to confer protection 

against nonphysical stressors, mental and/or psychological.98,111,113,114 Rimelle et al115 documented signifi cantly 

lower cortisol and heart rate responses to psychosocial 

PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE

A conceptual model of the personality traits and attributes associated with physical fi tness and resilience and how physical 

fi tness confers resilience. Physical fi tness confers resilience because regular exercise/physical activity can protect against the 

potential consequences of stressful events and prevent many 

chronic and stress-related diseases/disorders. 

CVD indicates cardiovascular disease.

Sedentary

Low self-esteem

Low self-effi cacy

Anxious

Depressed

Lethargic

Unsure/uncertain

Timid

Physically Unfi t

(Aerobically unfi t/fat)

Vulnerable

Physically Fit

(Aerobically fi t/lean)

Resilient

Physically active

High self-esteem

High self-effi cacy

Motivated

Hardy/mentally

 tough

Committed

Confi dent

Chronic/Stress-related Disorders

anxiety, depression, cognitive 

dysfunction, pain and fatigue disorders, 

sleep disorders, obesity, CVD, metabolic 

syndrome, type 2 diabetes, osteoporosis, 

autoimmune disease, cancer

Physical/Mental

Resilience

(-)

(-)

(-)
 October – December 2013 27

THE ARMY MEDICAL DEPARTMENT JOURNAL

stress in trained men compared to untrained men. Moreover, signifi cantly greater calmness and better mood, 

and a trend toward lower state anxiety were noted in 

the trained relative to untrained men. In addition, others have noted blunted cortisol responses115 and reduced 

cardiovascular responses98,99,115 to psychological laboratory stressors in physically active as compared to less 

active persons. Webb et al111 administered a dual challenge of physical and mental stress and noted that lowfi t participants had greater cortisol responses compared 

to high-fi t individuals. Importantly, in a meta-review of 

34 studies, Crews et al99 reported that aerobically fi t individuals had reduced responses to psychosocial stress 

in comparison to controls. These fi ndings are consistent 

with those from the Aerobics Center Longitudinal Study, 

which found a signifi cant inverse dose-response relationship between aerobic fi tness and depressive symptomatology and a positive association between fi tness 

and emotional well-being.116

In addition to cross-sectional studies, longitudinal studies have demonstrated positive effects of exercise training and regular physical activity, and negative effects 

of exercise withdrawal on mood and depressive symptoms.68,117-121 Nabkasorn et al117 studied adolescent females with depressive symptoms and noted signifi cant 

decreases in total depressive score, as well as in 24-hour 

urinary cortisol and epinephrine excretion, following 8 

weeks of physical training (jogging). Importantly, studies by Berlin et al118 and Weinstein et al121 demonstrated 

that when someone who exercises regularly is forced 

to withdraw from exercise for 2 weeks, negative mood 

increases signifi cantly and correlates with decreases in 

fi tness.118,121 In addition, a reduction in parasympathetic 

nervous system activity, as measured by heart rate variability, predicted the development of negative mood after 

deprivation of exercise.121 These fi ndings are relevant to 

understanding both short-term exercise withdrawal and 

exercise initiation, and how they affect overall stress resilience and reactivity.

Despite the multiple positive fi ndings, not all are consistent,65,122,123 particularly with regard to catecholamine release, with both blunted and augmented responses noted 

in high- versus low-fi t persons.112,123 Along those same 

lines, de Geus et al65 were unable to detect changes in 

psychological make-up (for example, personality traits 

of neuroticism, introversion, hostility, anger expression) 

or acute neurophysiologic reactivity (for example, heart 

rate, blood pressure, urinary catecholamine excretion, 

or cardiac beta-adrenergic drive) after 4 and 8 months of 

training. Thus, although the majority of studies support 

positive effects of regular exercise and aerobic fi tness, 

not all studies are consistent.

Physical Fitness Serves as a Buffer against Stress and 

Stress-Related Disorders

Physical activity may provide a protective effect against 

stress-related disorders, as physically fi t persons appear 

to be less susceptible to life stressors, in particular with 

regard to illnesses: physical fi tness may serve as a buffer 

against stress,63,124,125 with stress being highly associated 

with various illnesses.20,34,73,124,126,127 A comprehensive review of the literature from 1982 to 2008 in which exercise was examined as a stress-buffer concluded that the 

majority of studies, both cross-sectional and prospective, 

found exercise to be an effective buffer, but the amount 

and type of exercise necessary for protection were not 

stated.93 The concept of stress buffering was fi rst proposed by Kobasa et al,34 and later by others9,11 who clearly 

showed that regular exercise and hardiness interact to decrease illness in the face of serious life stressors.34 Persons 

who scored high in hardiness and participated in regular 

exercise were usually more healthy than those high only 

in hardiness or exercise alone.34 Collectively, the data 

suggest that participation in leisure physical activity is 

important to the stress-buffering effect of exercise.128

Physical fi tness and regular exercise also appear to buffer against depression 63,68,125,129-134 and anxiety.100,125,134-136

In fact, the benefi cial effects of physical activity on positive mood are well recognized.83,137 Rethorst et al131 conducted a meta-analysis of all studies investigating the 

effects of exercise on depression, and 12 of 16 exercise 

treatment groups with clinically depressed patients were 

classifi ed as “recovered” or “improved” after the treatment. Similarly, a number of prospective studies have 

demonstrated reductions in state anxiety.129,138 Manger et al129 had persons diagnosed with posttraumatic 

stress disorder (PTSD) undergo a 12-session aerobic 

exercise program and showed signifi cant reductions in 

PTSD, anxiety, and depression following the intervention. Moreover, these positive results were stable over 1 

month of follow-up.129 Finally, Wipfl i et al135 conducted 

a meta-analysis (based on 49 randomized, controlled 

trials) examining the effects of exercise on anxiety, 

and demonstrated clear reductions in anxiety among 

those who exercised compared to the respective control 

groups. Of interest was their fi nding that exercise was 

more effective in reducing anxiety relative to other anxiety-reducing treatments.135

CLINICAL IMPLICATIONS OF A SEDENTARY LIFESTYLE

The short- and long-term consequences of low physical 

fi tness and a sedentary lifestyle are clear. Physical inactivity serves a major role in the rising prevalence of obesity, cardiovascular disease (CVD), hypertension, type II 

diabetes mellitus (T2DM), metabolic syndrome, insulin 

resistance, hyperlipidemia, and breast and colon cancers, 
28 http://www.cs.amedd.army.mil/amedd_journal.aspx

to name a few.91,94,95,116,139,140 Of course, excess energy intake also contributes to obesity,78,94,95, but lack of physical activity is the leading contributor91,94,95,116,139,140 and 

also the fourth leading cause of death worldwide.95 In 

contrast to a sedentary lifestyle, high aerobic fi tness is 

inversely related to obesity, metabolic syndrome, CVD, 

hypertension, and T2DM.74,141-145

In addition to the major chronic diseases mentioned 

above, low aerobic fi tness has been associated with fi bromyalgia (FM),146,147 chronic fatigue syndrome (CFS),148,149

osteoarthritis,150-152 rheumatoid arthritis,150,153,154 and infl ammatory muscle disorders.155,156 Low aerobic fi tness 

is also associated with elevations in serum C-reactive 

protein (CRP), a well-known marker of infl ammation. 

Many studies have shown that maximal aerobic capacity 

is inversely related to CRP,142,157 and that exercise interventions, both aerobic and resistance in nature, reduce 

levels of CRP.157-159 However, not all studies showed a 

signifi cant effect.160-162 A meta-analytic study by Kelley 

et al162 of 5 randomized controlled trials reported an approximately 3% reduction in CRP levels across the exercise groups, which was not signifi cant. However, the 

studies that were negative found other positive benefi ts 

of exercise, regardless of its effect on CRP.

With regard to FM, exercise as an intervention has been 

shown to be benefi cial, particularly in relation to pain 

management. Ellingson et al147 conducted a prospective 

study and emphasized how a sedentary lifestyle was likely deleterious for pain regulation in FM. Likewise, Curtis et al163 conducted a study wherein women with FM 

who engaged in a 75-minute yoga class twice weekly for 

8 weeks reported reduced pain and catastrophizing, and 

increased acceptance of pain. Chronic fatigue syndrome 

is another debilitating disorder characterized by minimal physical activity during daily life and lower muscle 

strength and aerobic capacity compared to healthy sedentary subjects.149,154 As with FM, when persons with 

CFS are entered into a regular exercise program, signifi -

cant benefi ts in terms of physical capacity, quality of life, 

fatigue severity, and depressive symptomatology are 

reported.164,165 Interestingly, Heins et al166 reported that 

physical activity is intentionally limited in CFS patients, 

possibly because they expect negative bodily symptoms 

and catastrophize in such a way as to negatively affect 

their performance. This underscores the importance of 

the exercise-derived resilience resources self-effi cacy, 

self-esteem, and motivation, which, unfortunately, were 

not measured in the above studies.

Overall, the clinical implications of a sedentary, physically inactive lifestyle are profound, and the literature 

clearly demonstrates that having a valid measure of 

physical fi tness, in particular aerobic fi tness, may be 

one of the best indicators of resilience, as well as longterm health and risk of chronic diseases. Most of the 

above mentioned chronic diseases/disorders are also associated with depression, anxiety, low self-effi cacy, and 

other barriers to critical resilience resources. Promoting 

regular physical activity in these populations has been 

shown to exert profound benefi cial changes, and should 

be the key intervention for all such populations who are 

able to engage in regular physical activity.

LIMITATIONS AND FUTURE DIRECTIONS

Limitations of studies examining how physical fi tness 

contributes to resilience must be acknowledged. First, 

many studies examining reactivity to both physical 

and psychosocial stress did not quantify aerobic fi tness 

or regular physical activity. This is essential for being 

able to accurately interpret the results, as they may be 

important confounders. Secondly, the intimate relation between hardiness/mental toughness, and aerobic 

capacity/physical activity must be further evaluated to 

document their interrelationship. Certainly, the mental 

toughness model was specifi cally developed for athletes 

who are physically fi t and have self-confi dence, so one 

would expect them to have many resilience resources. 

However, what happens when they become injured? In 

addition, many people with chronic diseases are able to 

cope and are physically unfi t (they may be unable to engage in regular exercise), so physical fi tness is important, 

but not an absolute.23,24

CONCLUSIONS

Physical fi tness is associated with many traits and attributes required for resilience. As such, it is one pathway 

toward resilience. Promoting physical fi tness as a pathway to resilience is based on solid, scientifi c evidence 

as noted in many ancient and current sources showing 

that physical fi tness blunts stress reactivity, confers 

physiologic and psychological benefi ts, serves as a buffer against stress, and can protect against stress-related 

disorders and chronic illness. Perhaps the role of physical 

fi tness as a pathway to resilience was most eloquently 

stated by then President-Elect John F. Kennedy in 1960 

when he said:

...physical fi tness is not only one of the most important 

keys to a healthy body; it is the basis of dynamic and 

creative intellectual activity. ...intelligence and skill can 

only function at the peak of their capacity when the body 

is healthy and strong; hardy spirits and tough minds usually inhabit sound bodies.1

RELEVANCE TO THE PERFORMANCE TRIAD 

Physical activity is a key component of the Performance 

Triad and is clearly essential to optimal performance. 

PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE
 October – December 2013 29

THE ARMY MEDICAL DEPARTMENT JOURNAL

However, physical activity in the absence of adequate 

fueling (ie, healthy dietary patterns, appropriate timing 

and types of nutrients) and an adequate quantity and 

quality of sleep and recovery is not the solution. Excessive activity can lead to overtraining, musculoskeletal injuries, and similar problems. Only when physical 

activity is balanced with a healthy diet and restorative 

sleep will the benefi ts described above be realized.

ACKNOWLEDGMENTS

This research was supported by a grant from 

Comprehensive Soldier and Family Fitness (CSF2; 

HT9404-12-1-0017; F191GJ).

We appreciate the support in preparation and review of 

this article by LTC Sharon A. McBride, MS, USA.

REFERENCES

1. Kennedy JF. The soft American. Sports Illustrated. 1960;13(26):14-17. Available at: http://

sportsillustrated.cnn.com/vault/article/magazine/

MAG1134750/2/. Accessed August 15, 2013.

2. CJCS Instruction 3405.01: Chairman’s Total Force 

Fitness Framework. Washington, DC: Offi ce of the 

Chairman, Joint Chiefs of Staff; 2011. Available at: 

http://www.dtic.mil/cjcs_directives/cdata/unlim

it/3405_01.pdf. Accessed July 24, 2013.

3. Baker DG, Nash WP, Litz BT, et al. Predictors of 

risk and resilience for posttraumatic stress disorder among ground combat Marines: methods of 

the Marine Resiliency Study. Prev Chronic Dis. 

2012;9:E97.

4. Meredith LS, Sherbourne CD, Gaillot S, et al. Psychological Resilience in the U.S. Military. Santa 

Monica, CA 90407-2138: Rand Corporation;2011.

5. Perna L, Mielck A, Lacruz ME, et al. Socioeconomic position, resilience, and health behaviour among elderly people. Int J Public Health. 

2012;57(2):341-349.

6. Skrove M, Romundstad P, Indredavik MS. Resilience, lifestyle and symptoms of anxiety and depression in adolescence: the Young-HUNT study. 

Soc Psychiatry and Psychiatr Epidemiol. 8 2012.

7. Wells M, Avers D, Brooks G. Resilience, physical 

performance measures, and self-perceived physical 

and mental health in older Catholic nuns. J Geriatr 

Physical Ther. Jul-2012;35(3):126-131.

8. Acevedo EO, Webb HE, Weldy ML, Fabianke 

EC, Orndorff GR, Starks MA. Cardiorespiratory 

responses of Hi Fit and Low Fit subjects to mental challenge during exercise. Int J Sports Med. 

2006;27(12):1013-1022.

9. Roth DL, Wiebe DJ, Fillingim RB, Shay KA. Life 

events, fi tness, hardiness, and health: a simultaneous analysis of proposed stress-resistance effects. J 

Pers Soc Psychol. 1989;57(1):136-142.

10. Skirka N. The relationship of hardiness, sense 

of coherence, sports participation, and gender 

to perceived stress and psychological symptoms 

among college students. J Sports Med Phys Fitness. 

2000;40(1):63-70.

11. Maddi SR. On hardiness and other pathways to resilience. Am Psychol. 2005;60(3):261-262; discussion 265-267.

12. Dalleck LC, Kravitz L. The history of fi tness. IDEA 

Health and Fitness Source. 2002;20(2):26-33.

13. Berryman JW. Exercise is medicine: a historical perspective. Curr Sports Med Reports. 

Jul-2010;9(4):195-201.

14. Fletcher GF. The history of exercise in the practice of 

medicine. J Med Assoc Georgia. 1983;72(1):35-40.

15. Berryman JW. The tradition of the “six things nonnatural”: exercise and medicine from Hippocrates 

through ante-bellum America. Exerc Sport Sci Rev. 

1989;17:515-559.

16. MacAuley D. A history of physical activity, health 

and medicine. J R Soc Med. 1994;87(1):32-35.

17. Herrman H, Stewart DE, Diaz-Granados N, Berger 

EL, Jackson B, Yuen T. What is resilience? Can 

J Psychiatry. Revue canadienne de psychiatrie. 

2011;56(5):258-265.

18. Seligman ME. Building resilience. Harv Bus Rev. 

2011;89(4):100-106, 138.

19. Ong AD, Bergeman CS, Boker SM. Resilience 

comes of age: defi ning features in later adulthood. 

J Pers. 2009;77(6):1777-1804.

20. Yi JP, Vitaliano PP, Smith RE, Yi JC, Weinger K. 

The role of resilience on psychological adjustment 

and physical health in patients with diabetes. Br J 

Health Psychol. 2008;13(Pt 2):311-325.

21. Howe A, Smajdor A, Stockl A. Towards an understanding of resilience and its relevance to medical 

training. Med Educ. 2012;46(4):349-356.

22. Mertens VC, Bosma H, Groffen DA, van Eijk JT. 

Good friends, high income or resilience? What 

matters most for elderly patients? Eur J Public 

Health. 2012;22(5):666-671.

23. Robottom BJ, Gruber-Baldini AL, Anderson KE, 

et al. What determines resilience in patients with 

Parkinson’s disease? Parkinsonism Relat Disord. 

2012;18(2):174-177.

24. West C, Stewart L, Foster K, Usher K. The meaning of resilience to persons living with chronic 

pain: an interpretive qualitative inquiry. J Clin 

Nurs. 2012;21(9-10):1284-1292.

25. Jeffcott SA, Ibrahim JE, Cameron PA. Resilience in 

healthcare and clinical handover. Qual Saf Health 

Care. 2009;18(4):256-260.
30 http://www.cs.amedd.army.mil/amedd_journal.aspx

26. Levine SZ, Laufer A, Stein E, Hamama-Raz Y, 

Solomon Z. Examining the relationship between 

resilience and posttraumatic growth. J Trauma 

Stress. 2009;22(4):282-286.

27. Mancini AD, Bonanno GA. Predictors and parameters of resilience to loss: toward an individual differences model. J Pers. 2009;77(6):1805-1832.

28. Pickering MA, Hammermeister J, Ohlson C, Holliday B, Ulmer G. An exploratory investigation of 

relationships among mental skills and resilience in 

Warrior Transition Unit cadre members. Mil Med. 

2010;175(4):213-219.

29. Pickering RP, Grant BF, Chou SP, Compton WM. 

Are overweight, obesity, and extreme obesity associated with psychopathology? Results from the national epidemiologic survey on alcohol and related 

conditions. J Clin Psychiatry. 2007;68(7):998-1009.

30. Pietrzak RH, Johnson DC, Goldstein MB, Malley JC, Southwick SM. Psychological resilience 

and postdeployment social support protect against 

traumatic stress and depressive symptoms in 

soldiers returning from Operations Enduring 

Freedom and Iraqi Freedom. Depress Anxiety. 

2009;26(8):745-751.

31. Ri-Li G, Chase PJ, Witkowski S, et al. Obesity: associations with acute mountain sickness. Ann Intern Med. 2003;139(4):253-257.

32. Sawka MN, Young AJ, Cadarette BS, Levine L, 

Pandolf KB. Infl uence of heat stress and acclimation on maximal aerobic power. Eur J Appl Physiol 

Occup Physiol. 1985;53(4):294-298.

33. Taliaz D, Loya A, Gersner R, Haramati S, Chen A, 

Zangen A. Resilience to chronic stress is mediated 

by hippocampal brain-derived neurotrophic factor. 

J Neurosci. 2011;31(12):4475-4483.

34. Kobasa SC, Maddi SR, Puccetti MC. Personality 

and exercise as buffers in the stress-illness relationship. J Behav Med. 1982;5(4):391-404.

35. Connaughton D, Wadey R, Hanton S, Jones G. The 

development and maintenance of mental toughness: perceptions of elite performers. J Sports Sci. 

2008;26(1):83-95.

36. Crust L, Clough PJ. Relationship between mental 

toughness and physical endurance. Percept Mot 

Skills. 2005;100(1):192-194.

37. Kobasa SC. Stressful life events, personality, and 

health: an inquiry into hardiness. J Pers Soc Psychol. 1979;37(1):1-11.

38. Kobasa SC. Personality and resistance to illness. 

Am J Community Psychol. 1979;7(4):413-423.

39. Kobasa SC, Maddi SR, Courington S. Personality 

and constitution as mediators in the stress-illness relationship. J Health Soc Behav. 1981;22(4):368-378.

40. Kobasa SC, Maddi SR, Kahn S. Hardiness and 

health: a prospective study. J Pers Soc Psychol. 

1982;42(1):168-177.

41. Kobasa SC, Maddi SR, Puccetti MC, Zola MA. Effectiveness of hardiness, exercise and social support as resources against illness. J Psychosom Res. 

1985;29(5):525-533.

42. Kobasa SC, Puccetti MC. Personality and social 

resources in stress resistance. J Pers Soc Psychol. 

1983;45(4):839-850.

43. Kobasa SC, Spinetta JJ, Cohen J, et al. Social environment and social support. Cancer. 1991;67(suppl 

3):788-793.

44. Mack MG, Ragan BG. Development of the mental, emotional, and bodily toughness inventory in 

collegiate athletes and nonathletes. J Athl Train. 

2008;43(2):125-132.

45. Ramanaiah NV, Sharpe JP, Byravan A. Hardiness and major personality factors. Psychol Rep. 

1999;84(2):497-500.

46. Simpson RJ, Gray SC, Florida-James GD. Physiological variables and performance markers of 

serving soldiers from two “elite” units of the British Army. J Sports Sci. 2006;24(6):597-604.

47. Bartone PT. Test-retest reliability of the dispositional resilience scale-15, a brief hardiness scale. 

Psychol Rep. 2007;101(3 Pt 1):943-944.

48. Bartone PT, Ursano RJ, Wright KM, Ingraham LH. 

The impact of a military air disaster on the health 

of assistance workers. A prospective study. J Nerv 

Ment Dis. 1989;177(6):317-328.

49. Ford IW, Eklund RC, Gordon S. An examination 

of psychosocial variables moderating the relationship between life stress and injury time-loss 

among athletes of a high standard. J Sports Sci. 

2000;18(5):301-312.

50. Funk SC. Hardiness: a review of theory and research. Health Psychol. 1992;11(5):335-345.

51. Maddi SR, Harvey RH, Khoshaba DM, Lu JL, 

Persico M, Brow M. The personality construct of 

hardiness, III: Relationships with repression, innovativeness, authoritarianism, and performance. J 

Pers. 2006;74(2):575-597.

52. Britt TW, Adler AB, Bartone PT. Deriving benefi ts 

from stressful events: the role of engagement in 

meaningful work and hardiness. J Occup Health 

Psychol. 2001;6(1):53-63.

53. Bonanno GA. Loss, trauma, and human resilience: 

have we underestimated the human capacity to 

thrive after extremely aversive events? Am Psychol. 

2004;59(1):20-28.

54. Gucciardi DF. Measuring mental toughness in 

sport: a psychometric examination of the psychological performance inventory-a and its predecessor. J Pers Assess. 2012;94(4):393-403.

PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE
 October – December 2013 31

THE ARMY MEDICAL DEPARTMENT JOURNAL

55. Richardson M. Developing mental toughness. Nurs 

Times. 2011;107(45):inside back cover.

56. Gucciardi DF, Jones MI. Beyond optimal performance: mental toughness profi les and developmental success in adolescent cricketers. J Sport Exerc 

Psychol. 2012;34(1):16-36.

57. Gerber M, Kalak N, Lemola S, et al. Are adolescents 

with high mental toughness levels more resilient 

against stress. Stress Health. 2013;29(2):164-171.

58. Miller L. Stress and resilience in law enforcement 

training and practice. Int J Emerg Ment Health. 

2008;10(2):109-124.

59. Barrow FH, Armstrong MI, Vargo A, Boothroyd 

RA. Understanding the fi ndings of resilience-related research for fostering the development of African American adolescents. Child Adolesc Psychiatr Clin N Am. 2007;16(2):393-413, ix-x.

60. Richardson GE. The metatheory of resilience and 

resiliency. J Clin Psychol. 2002;58(3):307-321.

61. Richardson GE, Waite PJ. Mental health promotion 

through resilience and resiliency education. Int J 

Emerg Ment Health. 2002;4(1):65-75.

62. Rutter M. Psychosocial resilience and protective mechanisms. Am J Orthopsychiatry. 

1987;57(3):316-331.

63. Norris R, Carroll D, Cochrane R. The effects of 

physical activity and exercise training on psychological stress and well-being in an adolescent population. J Psychosom Res. 1992;36(1):55-65.

64. Rimmele U, Seiler R, Marti B, Wirtz PH, Ehlert 

U, Heinrichs M. The level of physical activity affects adrenal and cardiovascular reactivity to 

psychosocial stress. Psychoneuroendocrinology. 

2009;34(2):190-198.

65. de Geus EJ, van Doornen LJ, Orlebeke JF. Regular 

exercise and aerobic fi tness in relation to psychological make-up and physiological stress reactivity. 

Psychosom Med. 1993;55(4):347-363.

66. Delignières D, Marcellini A, Brisswalter J, Legros 

P. Self-perception of fi tness and personality traits. 

Percept Mot Skills. 1994;78(3 pt 1):843-851.

67. Dzewaltowski DA. Physical activity determinants: 

a social cognitive approach. Med Sci Sports Exerc. 

1994;26(11):1395-1399.

68. Scully D, Kremer J, Meade MM, Graham R, 

Dudgeon K. Physical exercise and psychological well being: a critical review. Br J Sports Med. 

1998;32(2):111-120.

69. Ekeland E, Heian F, Hagen KB, Abbott J, Nordheim L. Exercise to improve self-esteem in children and young people. Cochrane Database Syst 

Rev [serial online]. 2004(1):CD003683.

70. Kwan BM, Bryan AD. Affective response to exercise as a component of exercise motivation: Attitudes, norms, self-effi cacy, and temporal stability 

of intentions. Psychol Sport Exerc. 2010;11(1):71-79.

71. Craft LL, Perna FA, Freund KM, Culpepper L. Psychosocial correlates of exercise in women with selfreported depressive symptoms. J Phys Act Health. 

2008;5(3):469-480.

72. Netz Y, Wu MJ, Becker BJ, Tenenbaum G. Physical 

activity and psychological well-being in advanced 

age: a meta-analysis of intervention studies. Psychol Aging. 2005;20(2):272-284.

73. Taylor MK, Markham AE, Reis JP, et al. Physical 

fi tness infl uences stress reactions to extreme military training. Mil Med. 2008;173(8):738-742.

74. Deuster PA, Kim-Dorner SJ, Remaley AT, Poth 

M. Allostatic load and health status of African Americans and whites. Am J Health Behav. 

2011;35(6):641-653.

75. McMurray I, Connolly H, Preston-Shoot M, Wigley V. Constructing resilience: social workers’ understandings and practice. Health Soc Care Community. 2008;16(3):299–309.

76. Dishman RK, Motl RW, Sallis JF, et al. Self-management strategies mediate self-effi cacy and physical activity. Am J Prev Med. 2005;29(1):10-18.

77. Dishman RK, Saunders RP, Felton G, Ward 

DS, Dowda M, Pate RR. Goals and intentions 

mediate effi cacy beliefs and declining physical activity in high school girls. Am J Prev Med. 

2006;31(6):475-483.

78. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJ, 

Martin BW. Correlates of physical activity: why 

are some people physically active and others not? 

Lancet. 2012;380(9838):258-271.

79. Lee LL, Arthur A, Avis M. Using self-effi cacy 

theory to develop interventions that help older 

people overcome psychological barriers to physical activity: a discussion paper. Int J Nurs Stud. 

2008;45(11):1690-1699.

80. Magnan RE, Kwan BM, Bryan AD. Effects of current physical activity on affective response to exercise: physical and social-cognitive mechanisms. 

Psychol Health. 2013;28(4):418-433.

81. Frederick CM. Competitiveness: relations with 

GPA, locus of control, sex, and athletic status. Percept Mot Skills. 2000;90(2):413-414.

82. Andrè N, Dishman RK. Evidence for the construct 

validity of self-motivation as a correlate of exercise 

adherence in French older adults. J Aging Phys Act. 

2012;20(2):231-245.

83. Anthony J. Psychologic aspects of exercise. Clin 

Sports Med. 1991;10(1):171-180.

84. Dishman RK, Sallis JF, Orenstein DR. The determinants of physical activity and exercise. Public 

Health Rep. 1985;100(2):158-171.
32 http://www.cs.amedd.army.mil/amedd_journal.aspx

85. Motl RW, Dishman RK, Felton G, Pate RR. Selfmotivation and physical activity among black 

and white adolescent girls. Med Sci Sports Exerc. 

2003;35(1):128-136.

86. Morris JN, Chave SP, Adam C, Sirey C, Epstein L, 

Sheehan DJ. Vigorous exercise in leisure-time and 

the incidence of coronary heart-disease. Lancet. 

1973;1(7799):333-339.

87. Chave SP, Morris JN, Moss S, Semmence AM. 

Vigorous exercise in leisure time and the death rate: 

a study of male civil servants. J Epidemiol Community Health. 1978;32(4):239-243.

88. Morris JN, Everitt MG, Pollard R, Chave SP, Semmence AM. Vigorous exercise in leisure-time: 

protection against coronary heart disease. Lancet. 

1980;2(8206):1207-1210.

89. Paffenbarger RS, Jr., Hyde RT. Exercise in the 

prevention of coronary heart disease. Prev Med. 

1984;13(1):3-22.

90. Paffenbarger RS Jr, Hyde RT, Wing AL, Hsieh 

CC. Physical activity, all-cause mortality, and 

longevity of college alumni. N Engl J Med. 

1986;314(10):605-613.

91. Pratt M, Norris J, Lobelo F, Roux L, Wang G. The 

cost of physical inactivity: moving into the 21st 

century. Br J Sports Med. 2012; Nov 7 [epub].

92. Blair SN, LaMonte MJ, Nichaman MZ. The 

evolution of physical activity recommendations: how much is enough? Am J Clin Nutr. 

2004;79(5):913S-920S.

93. Gerber M, Puhse U. Review article: do exercise 

and fi tness protect against stress-induced health 

complaints? a review of the literature. Scand J Public Health. 2009;37(8):801-819.

94. Wen CP, Wu X. Stressing harms of physical inactivity to promote exercise. Lancet. 

2012;380(9838):192-193.

95. Kohl HW III, Craig CL, Lambert EV, et al. The 

pandemic of physical inactivity: global action for 

public health. Lancet. 2012;380(9838):294-305.

96. McEwen BS. Central effects of stress hormones in 

health and disease: understanding the protective 

and damaging effects of stress and stress mediators. 

Eur J Pharmacol. 2008;583(2-3):174-185.

97. Chrousos GP. Stress and disorders of the stress system. Nat Rev Endocrinol. 2009;5(7):374-381.

98. Claytor RP. Stress reactivity: hemodynamic adjustments in trained and untrained humans. Med Sci 

Sports Exerc. 1991;23(7):873-881.

99. Crews DJ, Landers DM. A meta-analytic review 

of aerobic fi tness and reactivity to psychosocial 

stressors. Med Sci Sports Exerc. 1987;19(suppl 

5):S114-S120.

100. Deboer LB, Tart CD, Presnell KE, Powers MB, 

Baldwin AS, Smits JA. Physical activity as a moderator of the association between anxiety sensitivity 

and binge eating. Eating Behav. 2012;13(3):194-201.

101. Deuster PA, Petrides JS, Singh A, Chrousos GP, 

Poth M. Endocrine response to high-intensity exercise: dose-dependent effects of dexamethasone. J 

Clin Endocrinol Metab. 2000;85(3):1066-1073.

102. Dienstbier RA. Behavioral correlates of sympathoadrenal reactivity: the toughness model. Med Sci 

Sports Exerc. 1991;23(7):846-852.

103. Horowitz M, Robinson SD. Heat shock proteins 

and the heat shock response during hyperthermia 

and its modulation by altered physiological conditions. Prog Brain Res. 2007;162:433-446.

104. Lambiase MJ, Dorn J, Chernega NJ, McCarthy TF, 

Roemmich JN. Excess heart rate and systolic blood 

pressure during psychological stress in relation to 

metabolic demand in adolescents. Biol Psychol. 

2012;91(1):42-47.

105. McEwen BS. The neurobiology and neuroendocrinology of stress. Implications for post-traumatic 

stress disorder from a basic science perspective. 

Psychiatr Clin North Am. 2002;25(2):469-494, ix.

106. Ribeiro F, Campbell CS, Mendes G, et al. Exercise 

lowers blood pressure in university professors during subsequent teaching and sleeping hours. Int J 

Gen Med. 2011;4:711-716.

107. Steptoe A, Kearsley N, Walters N. Cardiovascular 

activity during mental stress following vigorous 

exercise in sportsmen and inactive men. Psychophysiology. 1993;30(3):245-252.

108. Luger A, Watschinger B, Deuster P, Svoboda T, 

Clodi M, Chrousos GP. Plasma growth hormone 

and prolactin responses to graded levels of acute 

exercise and to a lactate infusion. Neuroendocrinology. 1992;56(1):112-117.

109. Luger A, Deuster PA, Kyle SB, et al. Acute hypothalamic-pituitary-adrenal responses to the stress of 

treadmill exercise. Physiologic adaptations to physical training. N Engl J Med. 1987;316(21):1309-1315.

110. Deuster PA, Chrousos GP, Luger A, et al. Hormonal and metabolic responses of untrained, moderately trained, and highly trained men to three exercise 

intensities. Metabolism. 1989;38(2):141-148.

111. Webb HE, Rosalky DS, Tangsilsat SE, McLeod 

KA, Acevedo EO, Wax B. Aerobic fi tness affects 

cortisol responses to concurrent challenges. Med 

Sci Sports Exerc. 2013;45(2):379-386.

112. Sothmann MS, Hart BA, Horn TS. Plasma catecholamine response to acute psychological stress 

in humans: relation to aerobic fi tness and exercise 

training. Med Sci Sports Exerc. 1991;23(7):860-867.

PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE
 October – December 2013 33

THE ARMY MEDICAL DEPARTMENT JOURNAL

113. Cox RH. Exercise training and response to stress: 

insights from an animal model. Med Sci Sports Exerc. 1991;23(7):853-859.

114. Sothmann MS, Buckworth J, Claytor RP, Cox RH, 

White-Welkley JE, Dishman RK. Exercise training 

and the cross-stressor adaptation hypothesis. Exerc 

Sport Sci Rev. 1996;24:267-287.

115. Rimmele U, Zellweger BC, Marti B, et al. Trained 

men show lower cortisol, heart rate and psychological responses to psychosocial stress compared 

with untrained men. Psychoneuroendocrinology. 

2007;32(6):627-635.

116. Galper DI, Trivedi MH, Barlow CE, Dunn AL, 

Kampert JB. Inverse association between physical 

inactivity and mental health in men and women. 

Med Sci Sports Exerc. 2006;38(1):173-178.

117. Nabkasorn C, Miyai N, Sootmongkol A, et al. Effects of physical exercise on depression, neuroendocrine stress hormones and physiological fi tness 

in adolescent females with depressive symptoms. 

Eur J Public Health. 2006;16(2):179-184.

118. Berlin AA, Kop WJ, Deuster PA. Depressive mood 

symptoms and fatigue after exercise withdrawal: 

the potential role of decreased fi tness. Psychosom 

Med. 2006;68(2):224-230.

119. van Gool CH, Kempen GI, Bosma H, van Boxtel 

MP, Jolles J, van Eijk JT. Associations between 

lifestyle and depressed mood: longitudinal results 

from the Maastricht Aging Study. Am J Public 

Health. 2007;97(5):887-894.

120. Hamer M, Endrighi R, Poole L. Physical activity, 

stress reduction, and mood: insight into immunological mechanisms. Methods Mol Biol (Clifton, 

N.J.). 2012;934:89-102.

121. Weinstein AA, Deuster PA, Kop WJ. Heart rate 

variability as a predictor of negative mood symptoms induced by exercise withdrawal. Med Sci 

Sports Exerc. 2007;39(4):735-741.

122. Jackson EM, Dishman RK. Cardiorespiratory fi tness and laboratory stress: a meta-regression analysis. Psychophysiology. 2006;43(1):57-72.

123. Moyna NM, Bodnar JD, Goldberg HR, Shurin MS, 

Robertson RJ, Rabin BS. Relation between aerobic 

fi tness level and stress induced alterations in neuroendocrine and immune function. Int J Sports Med. 

1999;20(2):136-141.

124. Li G, He H. Hormesis, allostatic buffering capacity and physiological mechanism of physical activity: a new theoretic framework. Med Hypotheses. 

2009;72(5):527-532.

125. Steptoe A, Edwards S, Moses J, Mathews A. The 

effects of exercise training on mood and perceived 

coping ability in anxious adults from the general 

population. J Psychosom Res. 1989;33(5):537-547.

126. Morgan CA III, Wang S, Southwick SM, et al. Plasma neuropeptide-Y concentrations in humans exposed to military survival training. Biol Psychiatry. 

2000;47(10):902-909.

127. O’Donnell K, Brydon L, Wright CE, Steptoe A. 

Self-esteem levels and cardiovascular and infl ammatory responses to acute stress. Brain Behav Immun. 2008;22(8):1241-1247.

128. Carmack CL, Boudreaux E, Amaral-Melendez M, 

Brantley PJ, de Moor C. Aerobic fi tness and leisure 

physical activity as moderators of the stress-illness 

relation. Ann Behav Med. 1999;21(3):251-257.

129. Manger TA, Motta RW. The impact of an exercise program on posttraumatic stress disorder, 

anxiety, and depression. Int J Emerg Ment Health. 

2005;7(1):49-57.

130. Southwick SM, Vythilingam M, Charney DS. The 

psychobiology of depression and resilience to 

stress: implications for prevention and treatment. 

Annu Rev Clin Psychol. 2005;1:255-291.

131. Rethorst CD, Wipfl i BM, Landers DM. The antidepressive effects of exercise: a meta-analysis of 

randomized trials. Sports Med. 2009;39(6):491-511.

132. Paluska SA, Schwenk TL. Physical activity and 

mental health: current concepts. Sports Med. 

2000;29(3):167-180.

133. Oman RF, Oman KK. A case-control study of 

psychosocial and aerobic exercise factors in 

women with symptoms of depression. J Psychol. 

2003;137(4):338-350.

134. Oeland AM, Laessoe U, Olesen AV, Munk-Jorgensen P. Impact of exercise on patients with 

depression and anxiety. Nordic J Psychiatry. 

2010;64(3):210-217.

135. Wipfl i BM, Rethorst CD, Landers DM. The anxiolytic effects of exercise: a meta-analysis of randomized trials and dose-response analysis. J Sport 

Exerc Psychol. 2008;30(4):392-410.

136. Fox KR. The infl uence of physical activity on mental 

well-being. Public Health Nutr. 1999;2(3A):411-418.

137. Moses J, Steptoe A, Mathews A, Edwards S. The 

effects of exercise training on mental well-being in 

the normal population: a controlled trial. J Psychosom Res. 1989;33(1):47-61.

138. DiLorenzo TM, Bargman EP, Stucky-Ropp R, 

Brassington GS, Frensch PA, LaFontaine T. Longterm effects of aerobic exercise on psychological 

outcomes. Prev Med. 1999;28(1):75-85.

139. Blair SN. Physical inactivity: the biggest public 

health problem of the 21st century. Br J Sports Med. 

2009;43(1):1-2.

140. Goetzel RZ, Pei X, Tabrizi MJ, et al. Ten modifi -

able health risk factors are linked to more than onefi fth of employer-employee health care spending. 

Health Aff (Milwood). 2012;31(11):2474-2484.
34 http://www.cs.amedd.army.mil/amedd_journal.aspx

141. Zeno SA, Deuster PA, Davis JL, Kim-Dorner SJ, 

Remaley AT, Poth M. Diagnostic criteria for metabolic syndrome: caucasians versus African-Americans. Metab Syndr Relat Disord. 2010;8(2):149-156.

142. Zeno SA, Kim-Dorner SJ, Deuster PA, Davis JL, 

Remaley AT, Poth M. Cardiovascular fi tness and 

risk factors of healthy African Americans and caucasians. J Natl Med Assoc. 2010;102(1):28-35.

143. Kuo LE, Abe K, Zukowska Z. Stress, NPY and 

vascular remodeling: implications for stress-related diseases. Peptides. 2007;28(2):435-440.

144. Kim-Dorner SJ, Simpson-McKenzie CO, Poth M, 

Deuster PA. Psychological and physiological correlates of insulin resistance at fasting and in response 

to a meal in African Americans and whites. Ethn 

Dis. 2009;19(2):104-110.

145. Kim-Dorner SJ, Deuster PA, Zeno SA, Remaley 

AT, Poth M. Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be 

used as surrogates for insulin resistance?. Metabolism. 2010;59(2):299-304.

146. McLoughlin MJ, Stegner AJ, Cook DB. The 

relationship between physical activity and 

brain responses to pain in fi bromyalgia. J Pain. 

2011;12(6):640-651.

147. Ellingson LD, Shields MR, Stegner AJ, Cook DB. 

Physical activity, sustained sedentary behavior, 

and pain modulation in women with fi bromyalgia. 

J Pain. 2012;13(2):195-206.

148. Puetz TW, Flowers SS, O’Connor PJ. A randomized controlled trial of the effect of aerobic exercise 

training on feelings of energy and fatigue in sedentary young adults with persistent fatigue. Psychother Psychosom. 2008;77(3):167-174.

149. Nijs J, Aelbrecht S, Meeus M, Van Oosterwijck J, 

Zinzen E, Clarys P. Tired of being inactive: a systematic literature review of physical activity, physiological exercise capacity and muscle strength in 

patients with chronic fatigue syndrome. Disabil 

Rehabil. 2011;33(17-18):1493-1500.

150. Gualano B, Pinto AL, Perondi MB, et al. Therapeutic effects of exercise training in patients with 

pediatric rheumatic diseases. Rev Bra Reumatol. 

2011;51(5):490-496.

151. Semanik PA, Chang RW, Dunlop DD. Aerobic activity in prevention and symptom control of osteoarthritis. PM R. 2012;4(suppl 5):S37-S44.

152. Stevenson JD, Roach R. The benefi ts and barriers 

to physical activity and lifestyle interventions for 

osteoarthritis affecting the adult knee. J Orthop 

Surg Res. 2012;7:15.

153. Baillet A, Zeboulon N, Gossec L, et al. Effi cacy 

of cardiorespiratory aerobic exercise in rheumatoid 

arthritis: meta-analysis of randomized controlled 

trials. Arthritis Care Res. 2010;62(7):984-992.

154. Weinstein AA, Drinkard BM, Diao G, et al. Exploratory analysis of the relationships between aerobic 

capacity and self-reported fatigue in patients with 

rheumatoid arthritis, polymyositis, and chronic fatigue syndrome. PM R. 2009;1(7):620-628.

155. Lundberg IE, Nader GA. Molecular effects of 

exercise in patients with infl ammatory rheumatic disease. Nature Clin Pract Rheumatol. 

2008;4(11):597-604.

156. Nader GA, Lundberg IE. Exercise as an antiinfl ammatory intervention to combat infl ammatory diseases of muscle. Curr Opin Rheumatol. 

2009;21(6):599-603.

157. Thomson RL, Buckley JD, Moran LJ, et al. 

Comparison of aerobic exercise capacity and 

muscle strength in overweight women with 

and without polycystic ovary syndrome. BJOG. 

2009;116(9):1242-1250.

158. Arikawa AY, Thomas W, Schmitz KH, Kurzer MS. 

Sixteen weeks of exercise reduces C-reactive protein levels in young women. Med Sci Sports Exerc. 

2011;43(6):1002-1009.

159. Martins RA, Neves AP, Coelho-Silva MJ, Verissimo MT, Teixeira AM. The effect of aerobic versus strength-based training on high-sensitivity Creactive protein in older adults. Eur J Appl Physiol. 

2010;110(1):161-169.

160. Wong PC, Chia MY, Tsou IY, et al. Effects of a 

12-week exercise training programme on aerobic 

fi tness, body composition, blood lipids and C-reactive protein in adolescents with obesity. Ann Acad 

Med Singapore. 2008;37(4):286-293.

161. Stewart LK, Earnest CP, Blair SN, Church TS. Effects of different doses of physical activity on Creactive protein among women. Med Sci Sports 

Exerc. 2010;42(4):701-707.

162. Kelley GA, Kelley KS. Effects of aerobic exercise 

on C-reactive protein, body composition, and maximum oxygen consumption in adults: a meta-analysis of randomized controlled trials. Metabolism. 

2006;55(11):1500-1507.

163. Curtis K, Osadchuk A, Katz J. An eight-week yoga 

intervention is associated with improvements in 

pain, psychological functioning and mindfulness, 

and changes in cortisol levels in women with fi bromyalgia. J Pain Res. 2011;4:189-201.

164. Edmonds M, McGuire H, Price J. Exercise therapy 

for chronic fatigue syndrome. Cochrane Database 

Syst Rev [serial online]. 2004(3):CD003200.

165. Gordon BA, Knapman LM, Lubitz L. Graduated 

exercise training and progressive resistance training in adolescents with chronic fatigue syndrome: 

a randomized controlled pilot study. Clin Rehabil. 

2010;24(12):1072-1079.

PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE
 October – December 2013 35

THE ARMY MEDICAL DEPARTMENT JOURNAL

166. Heins M, Knoop H, Nijs J, et al. Infl uence of symptom expectancies on stair-climbing performance in chronic fatigue syndrome: effect of study context. Int J Behav Med. 2013;20(2):213-218.

AUTHORS

Dr Deuster is Director and Professor, Consortium for Health and Military Performance, Department of Military and 

Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

Dr Silverman is Senior Scientist, Human Performance Laboratory, Consortium for Health and Military Performance, 

Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, 

Maryland.
36 http://www.cs.amedd.army.mil/amedd_journal.aspx

Soldiers must maintain high levels of physical fi tness 

to endure demanding tasks, harsh deployment environments and military occupational specialty requirements. 

However, routine training required to maintain high 

levels of physical fi tness can result in musculoskeletal 

injuries, limited duty days, and signifi cant health care 

costs.1-3 Studies have shown that injuries related to physical training (PT) account for 30% to 50% of all injuries 

in US Army Soldiers.4-6 An investigation examining 

injury incidence in light infantry Soldiers found that 

physical training caused 50% of all injuries, and 30% 

of these injuries were associated with running.4

 Injuries 

caused approximately 10 times the number of limited 

duty days compared to illness. The investigators concluded that physical training is associated with a high 

number of injuries in infantry Soldiers.4

 It has also been 

Extreme Conditioning Programs and Injury

 Risk in a US Army Brigade Combat Team

Tyson Grier, MS

Michelle Canham-Chervak, PhD

Vancil McNulty, DPT

Bruce H. Jones, MD, MPH

ABSTRACT

Context: Brigades and battalions throughout the US Army are currently implementing a variety of exercise and conditioning programs with greater focus on preparation for mission-specifi c tasks. An Army physical therapy clinic 

working with a light infantry brigade developed the Advanced Tactical Athlete Conditioning (ATAC) program. The 

ATAC program is a unique physical training program consisting of high-intensity aquatic exercises, tactical agility 

circuits, combat core conditioning, and interval speed training. Along with ATAC, battalions have also incorporated 

components of fi tness programs such as the Ranger Athlete Warrior program and CrossFit (Crossfi t, Inc, Santa 

Monica, CA) an extreme conditioning program (ECP).

Objective: To determine if these new programs (ATAC, ECP) had an effect on injury rates and physical fi tness.

Design: Surveys were administered to collect personal characteristics, tobacco use, personal physical fi tness training, Army physical fi tness test results, and self-reported injuries. Medical record injury data were obtained 6 months 

before and 6 months after the implementation of the new program. Predictors of injury risk were assessed using 

multivariate logistic regression. Odds ratios (OR) and 95% confi dence intervals (CI) were reported.

Results: Injury incidence among Soldiers increased 12% for overall injuries and 16% for overuse injuries after the 

implementation of the ATAC/ECPs. However, injury incidence among Soldiers not participating in ATAC/ECPs 

also increased 14% for overall injuries and 10% for overuse injuries. Risk factors associated with higher injury risk 

for Soldiers participating in ATAC/ECPs included:

greater mileage run per week during unit physical training (OR (>16 miles per week÷≤7 miles per 

week)=2.24, 95% CI, 1.33-3.80)

higher body mass index (BMI) (OR (BMI 25-29.9÷BMI<25)=1.77, 95% CI, 1.29-2.44),

(OR (BMI ≥30÷BMI<25)=2.72, 95% CI, 1.67-4.43)

cigarette use (OR (smoker÷nonsmoker)=1.80, 95% CI, 1.34-2.42)

poor performance on the 2-mile run during the Army Physical Fitness Test (APFT)

(OR (≥15.51 minutes÷≤13.52 minutes)=1.76, 95% CI, 1.13-2.74)

Injury risk was lower for those reporting resistance training

(OR (<1 time per week÷none)=0.53, 95% CI, 0.31-0.92)

(OR (1-2 times per week÷none)=0.50, 95% CI, 0.29-0.84)

(OR (≥3 times per week÷none)=0.45, 95% CI, 0.24-0.85)

Conclusions: Given that Soldiers participating in ATAC/ECPs showed similar changes in injury rates compared to Soldiers not participating in ATAC/ECPs, no recommendation can be made for or against implementation of ATAC/ECPs.
 October – December 2013 37

shown that musculoskeletal injuries are a leading cause 

of hospitalization.7

 In a study investigating hospitalizations for sports and Army physical training injuries, 

11% of 120,430 hospital admissions over a 6-year period 

were attributed to sports or Army physical training injuries. This resulted in 29,435 total lost duty days, with 

an average of 13 days of limited duty per injury for male 

Soldiers and 11 days per injury for female Soldiers.3

These investigations indicate that physical training-related injuries have a considerable impact on the health 

and readiness of Soldiers.

Previous research has identifi ed a number of risk factors for injury in infantry Soldiers. In one study, higher 

risk of injury was associated with fewer sit-ups on the 

Army Physical Fitness Test (APFT) and slower 2-mile 

run times,8

 while another study showed higher risk of 

injury was associated with smoking and a body mass index (BMI) of 25 or more.9

 In an investigation of British 

infantry Soldiers, higher risk of injury was associated 

with younger age, previous lower limb injury, and previous back injury.10 More work to identify the most important risk factors among infantry Soldiers is needed.

Only a few investigations have explored injury risk during the implementation of a new military fi tness program.11-15 In 3 investigations, Knapik et al compared 

Soldiers performing Army Physical Readiness Training 

(PRT) to Soldiers performing traditional Army physical training. Physical readiness training consists of calisthenics, movement drills, climbing drills, dumbbell 

exercises, interval training, and ability group long-distance running whereas traditional Army physical training consists primarily of warm-up and stretching exercises followed by calisthenics, push-ups, sit-ups, some 

sprint training, and group long-distance running. For all 

3 studies, the adjusted risk of injury was 1.5 to 1.8 times 

higher in the groups performing traditional physical 

training compared to those performing PRT. It was also 

found that scores on the APFT were higher or similar 

for groups using the PRT program. Knapik et al concluded that the PRT program results in fewer injuries 

and equal or greater improvements in fi tness and military performance compared to traditional Army physical training.11-13,16

In a US Air Force study, a new PT program implemented 

within the combat controller training pipeline was evaluated. The goal of this new PT program was to reduce 

overuse and overtraining injuries and transition from 

a traditional PT program to a functional PT program. 

For the new PT program, running mileage decreased by 

50%, and long-distance runs were replaced with interval 

running and agility training. In addition, bodybuilding 

type resistance training (single joint) was replaced with 

functional strength training movements (multiple joint, 

standing exercises), and an athletic trainer was hired to 

visit the group twice per week. Investigators found that 

by replacing traditional training with the new functional training program, overall injuries decreased by 67%, 

and improvements were made in body composition, aerobic capacity, ventilatory threshold, upper body power, 

and graduation rates. The authors concluded that the 

new fi tness program decreased injury rates, increased 

fi tness performance and graduation rates, and suggested 

that other combat athletes would benefi t from adopting 

these practices.14

A variety of exercise and conditioning programs with 

greater focus on preparation for mission-specifi c tasks 

are currently being implemented by various brigades 

and battalions throughout the US Army. As a result, 

Soldiers are transitioning from traditional Army PT to 

a more intensive, combat-focused PT program. Injury 

rates and risk factors associated with these programs 

are not well known. The purpose of this project was to 

examine physical training, fi tness, and injury rates, and 

to identify injury risk factors in a light infantry brigade 

beginning a new PT program incorporating elements of 

extreme conditioning programs (ECPs).

METHOD

Population

The population consisted of Soldiers in a light infantry 

brigade combat team (N=1,393). The brigade combat 

team consisted of 2 infantry battalions, a cavalry battalion, a fi eld artillery battalion, a brigade support battalion 

(hereinafter referred to as Infantry A, Infantry B, Cavalry, Field Artillery, and Brigade Support), and a brigade 

special troops battalion. Rosters of unit members were 

requested and obtained through the brigade medical offi -

cer. Roster information included each Soldier’s battalion.

Surveys

A survey was used to collect information from Soldiers 

about personal characteristics, tobacco use, unit and 

personal physical fi tness training, Army physical fi tness 

test results, and injuries. The survey was administered 

in September 2010, approximately 4 months after the 

new physical fi tness and conditioning programs began.

Interviews

Battalion commanders were interviewed to obtain their 

views and opinions on physical training and fi tness. 

They were also asked about training equipment and injury prevention.
38 http://www.cs.amedd.army.mil/amedd_journal.aspx

Exercise Instructor Certification and Programs 

Conducted by the Brigade Combat Team

Selected Soldiers from every battalion in the brigade 

combat team attended a 1-week certifi cation class on the 

fundamentals of the Advanced Tactical Athlete Conditioning (ATAC) program. The ATAC Program consisted 

of workouts employing plyometrics, kettlebells, medicine balls, high-intensity water exercises, wrestling, ladder and cone agility drills, tire fl ipping, speed interval 

training, and cinderblock throwing. Some of the battalions also required their Soldiers to attend additional 

certifi cation classes in exercise and fi tness performance 

involving other exercise programs such as CrossFit 

(CrossFit Inc, Washington, DC) and the Ranger Athlete 

Warrior program (RAW), developed within the US Army’s 25th Infantry Division.

CrossFit is a core strength and conditioning program 

that aims to prepare athletes for any physical contingency. CrossFit consists of continuously varied, highintensity functional movements that generally fall into 

3 categories: gymnastics, Olympic weightlifting, and 

metabolic conditioning or “cardio.”* There are 4 components to the RAW program: functional fi tness, performance nutrition, sports medicine, and mental toughness. The functional fi tness component of RAW consists 

of movement drills (before each PT session), muscular 

endurance workouts, heavy resistance workouts, power and power endurance workouts, endurance training 

workouts, movement skills training, hybrid drills, and 

recovery exercises (at the end of each workout).†

CrossFit and RAW or parts of these exercise programs 

can also be classifi ed as ECPs,17 which are characterized by high-volume, aggressive exercise workouts with 

a variety of high-intensity exercise repetitions and short 

rest periods between sets. Popular ECPs include P90X 

and Insanity (Beachbody LLC, Santa Monica, CA), and 

Gym Jones (Gym Jones LLC, Salt Lake City, UT).

New Physical Training Program

Soldiers began a new physical training program that incorporated ATAC and components of fi tness programs 

such as the RAW program and CrossFit.

Army Physical Fitness Test Scores

The APFT was used as a measure of physical fi tness. 

Self-reported scores from each Soldier’s most recent 

APFT were obtained from the surveys. Close correlations have been found between actual APFT scores 

and self-reported APFT scores.18 The APFT consisted 

of 3 events: a 2-minute maximal effort push-up event, 

a 2-minute maximal effort sit-up event, and a 2-mile 

run performed for time. Events were performed in accordance with instructions contained in F ield Manual 

7-22: Army Physical Readiness Training.19 Performance 

metrics obtained included the number of push-ups and 

sit-ups successfully completed within separate 2-minute 

time periods. The performance measure for the run was 

the time taken to complete a 2-mile distance.

Demographics and Injury Outcome Measures

The Armed Forces Health Surveillance Center (AFHSC) provided demographic data obtained from the Defense Manpower Data Center (DMDC). Demographics 

included date of birth, education level, marital status, 

race, and gender.

Data on injuries treated in military treatment facilities 

or paid for by the Military Health System (purchased 

care) were obtained from the Defense Medical Surveillance System (DMSS). A brigade unit roster was provided to the AFHSC, which returned DMSS data containing visit dates and International Classifi cation of 

Disease 9th Revision (ICD-9)‡ diagnosis codes for all 

inpatient and outpatient medical encounters captured 

electronically by the DMSS occurring between November 1, 2009 and October 28, 2010. Injuries were categorized into 3 groups—overall injury, overuse injuries, 

and traumatic injuries—using the primary (fi rst) ICD-9 

diagnosis code in a manner consistent with prior studies 

of military training injuries.20,21

Overall injuries comprise all ICD-9 codes from the 800-

999 and 710-739 code series related to acute and chronic 

musculoskeletal injuries, including environmental injuries. Overuse injuries contain a subset of musculoskeletal injuries resulting from cumulative microtrauma 

due to repetitive motion, typically in the 710-739 ICD9 code series. This series indicates such diagnoses as 

stress fractures, stress reactions, tendonitis, bursitis, 

fasciitis, shin splints, and musculoskeletal pain (not otherwise specifi ed). Traumatic injuries contain a subset 

of musculoskeletal injuries resulting from a strong sudden force or forces being applied to the body, including 

events such as a fall from a ladder, an automobile crash, 

or being struck by a bullet. These injuries are contained 

in the 800-999 ICD-9 code series.

Data Analysis

The IBM SPSS Statistics (V 18.0) application (IBM 

Corp, Chicago, IL) was used for statistical analysis. *CrossFit Forging Elite Fitness – http://www.crossfi t.com/cf-info/

what-crossfi t.html

†RAW PT Program Manual – http://www.25idl.army.mil/pt/rawpt

guide_bp.pdf ‡http://www.cdc.gov/nchs/icd/icd9.htm

EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM
 October – December 2013 39

THE ARMY MEDICAL DEPARTMENT JOURNAL

Descriptive statistics (frequencies, distributions, means, 

SDs) were calculated for personal characteristics, physical training, and physical fi tness. Body mass index was 

calculated as weight in kilograms divided by height in 

meters squared (kg/m2). The BMI was categorized according to the Centers for Disease Control and Prevention (CDC) classifi cations for normal, overweight, and 

obese.22 Current cigarette smokers were identifi ed as 

smoking at least 1 cigarette within the last 30 days, and 

smoking 100 or more cigarettes in their lifetime.

To assess changes in injury rates pre- and postimplementation of the physical training programs, the McNemar test was used to compare injury incidence among 

Soldiers in the 6 months before the new programs were 

initiated (November 2009 to April 2010) with injury incidence in the 6 months following full implementation of the program (May 2010 to October 

2010) for the overall, overuse, and traumatic injury 

categories. For each of the 2 periods, injury risk 

(percentage) for each category was calculated as:

To investigate potential injury risk factors among 

Soldiers in the brigade, injury risk ratio and 95% 

CI, were calculated using the electronic medical 

record data on overall injuries occurring after the 

implementation of the new exercise programs. Potential injury risk factors included demographic 

characteristics obtained from AFHSC as well as 

health behavior, physical training, and physical fi tness data collected by survey.

A backward-stepping multivariate logistic regression and a forced multivariate logistic regression 

model were used to assess key factors for association with injury risk in this population. Odds ratios 

and 95% CIs were calculated for each potential 

risk factor (independent variables).

RESULTS

The average age of Soldiers in the brigade was 

26.8±5.9 years with a range of 18 to 52 years. A 

majority of the Soldiers were classifi ed as overweight or obese (61%), white (62%), rank of E4 to 

E6 (61%), high school graduates (82%), and married (55%). The descriptive statistics are presented 

in Table 1.

Due to the small number of Soldiers who participated in the ATAC program (n=87), the ATAC and 

ECP groups were combined in further analyses, 

comparing Soldiers who participated in ATAC/

ECPs with Soldiers who did not report participating in 

those programs. Using injuries recorded in the medical 

records, injury rates of Soldiers in units participating in 

ATAC/ECPs were compared to injury rates for Soldiers 

in units that did not participate. A total of 1,032 Soldiers 

reported that their units were participating in ATAC/

ECPs, while the other 340 Soldiers did not report participation. Soldiers were either exercising on their own 

time or were performing traditional PT. The baseline 

overall injury rates for Soldiers participating in ATAC/

ECPs and Soldiers who did not participate were 41% 

and 50%, respectively, as shown in Tables 2 and 3.

After full implementation of the ATAC/ECPs, injury incidence increased by 12% and 16% for overall injuries 

number of Soldiers with 1 or more injuries

total number of Soldiers 100%

Table 1. Descriptive Statistics for Men and Women in the Light Infantry Brigade.

Variable Subcategory of 

Variable

Men

M=1,248

Women

W=145

Men and

Women

N=1,393

n %M n %W n %N

Gender Men 1,248 90%

Women 145 10%

Age <23 374 30% 46 32% 420 30%

23-25 333 27% 40 28% 373 27%

26-29 258 21% 28 19% 286 21%

30+ 283 23% 31 21% 314 23%

Body mass 

index

≤25 (normal) 450 37% 85 60% 535 40%

25-29 (overweight) 593 49% 49 35% 642 48%

30+ (obese) 161 13% 7 5% 168 13%

Rank E1-E3 331 27% 44 30% 375 27%

E4-E6 769 62% 86 59% 855 61%

E7-E9 67 5% 5 3% 72 5%

W1-W2 5 0.4% 1 0.7% 6 0.4%

O1-O3 72 6% 9 6% 81 6%

O4-O6 4 0.3% 0 0% 4 0.3%

Race White 803 64% 61 42% 864 62%

Black 186 15% 53 37% 239 17%

Hispanic 138 11% 15 10% 153 11%

American Indian 9 1% 2 1% 11 1%

Asian 100 8% 13 9% 113 8%

Unknown 12 1% 1 1% 13 1%

Education 

Level

No High School 6 0.5% 0 0% 6 0.4%

High School 1,021 82% 114 79% 1,135 82%

Some College 88 7% 12 8% 100 7%

Bachelor’s 98 8% 16 11% 114 8%

Master’s 5 0.4% 2 1% 7 0.5%

Unknown 30 2% 1 1% 31 2%

Marital 

Status

Married 690 55% 76 52% 766 55%

Single 506 41% 53 37% 559 40%

Other 52 4% 16 11% 68 5%

Battalion Infantry A 445 36% 15 10% 460 33%

Infantry B 150 12% 0 0% 150 11%

Cavalry 185 15% 11 8% 196 14%

Field artillery 201 16% 11 8% 212 15%

Brigade support 

battalion 135 11% 72 50% 207 15%

Brigade special 

troops battalion 132 11% 36 25% 168 12%
40 http://www.cs.amedd.army.mil/amedd_journal.aspx

and overuse injuries, respectively, for Soldiers who participated (Table 2). Injury incidence for Soldiers who did 

not participate increased by 14% for overall injuries and 

10% for overuse injuries (Table 3). The absolute percentage change in overall injury incidence for the ATAC/

ECPs and no-ATAC/ECPs groups was an increase of 

5% and 7%, respectively (Tables 2 and 3).

Risk Factors for Men Participating in ATAC/ECPs

Tables 4 and 5 display the injury risk ratio variables for 

factors possibly associated with risk of injury. Since 

there were only 82 women participating in ATAC/

ECPs, the following analysis excluded women, except 

for initial comparisons of risk by gender. The number of 

responses may slightly vary between questions due to 

missing answers on some of the surveys. Higher risk of 

injury was associated with female gender; overweight 

or obese status; current smoking; and Infantry B, Cavalry, and Brigade Support battalions. An examination of 

physical training risk factors determined that injury risk 

was higher for Soldiers who participated in unit PT less than 5 times a week 

and ran more than 16 miles per week. 

Soldiers who performed resistance and 

agility training had a lower risk of injury. Analysis of APFT data indicated 

that those with lower performances on 

any of the 3 elements of the physical fi tness test (push-ups, sit-ups, 2-mile run) 

were at a higher risk of being injured.

Multivariate Analysis of Injury Risk 

Factors Following Implementation of 

ATAC/ECPs

Table 6 displays the results of a backward-stepping multivariate logistic regression analysis that examined unit PT 

and personal risk factors. Soldiers who 

were overweight, obese, used tobacco 

(cigarettes) and were in the Infantry B, 

Cavalry, or Brigade Support battalions 

were at a higher risk of injury. For unit 

PT, men who ran the greatest amount of 

miles per week were at a higher risk of 

injury, while men who performed any 

resistance training were at a lower risk 

of injury. Further analysis of total miles 

ran per week revealed that Soldiers who 

ran more than 16 miles per week during 

unit PT had identical 2-mile run time 

scores at 14.6±1.51 minutes compared 

to Soldiers who ran less than 16 miles 

per week during unit PT at 14.6±1.61 

minutes.

Table 7 displays the results of a multivariate logistic regression analysis 

examining components of the physical 

fi tness test controlling for age and battalion. Soldiers who performed poorly 

on the 2-mile run were at a higher risk 

of injury.

COMMENT

One of the major fi ndings of this investigation was the 

increase in overall injury incidence for Soldiers who 

did and did not participate in this new program after its 

Table 2. Comparison of Injury Incidence Before and After the Implementation of 

ATAC/ECPs (N=1,032).

Injury 

Type

Injury Incidence

Before ATAC/ECP 

Injury Incidence 

After ATAC/ECP 

Absolute 

Change

Change P

(McNemar Test)

Overall 41% 46% +5% +12% .02

Overuse 32% 37% +5% +16% .02

Traumatic 19% 18% -1% -5% .95

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.

Table 3. Comparison of Injury Incidence Before and After the Implementation of 

ATAC/ECPs on all Soldiers Who did not Participate in ATAC/ECPs (N=340).

Injury 

Type

Injury Incidence

Before ATAC/ECP 

Injury Incidence 

After ATAC/ECP 

Absolute 

Change

Change P

(McNemar Test)

Overall 50% 57% +7% +14% .05

Overuse 42% 46% +4% +10% .28

Traumatic 22% 23% 1% +5% 1.00

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.

Table 4. Personal Characteristics and Risk Factors for Injury Among Men Participating in ATAC/ECPs (N=1,032).

Variable Subcategory of 

Variable

N Injury After

ATAC/ECP

Risk Ratio (95%CI)

After ATAC/ECP

P

Gender Men 950 45% 1.00

Women 82 60% 1.34 (1.11-1.63) <.01

 Age <24 306 44% 1.09 (0.88-1.38) .43

24-25 185 46% 1.15 (0.91-1.45) .23

26-29 203 40% 1.00

30+ 240 48% 1.21 (0.98-1.50) .08

Body Mass

IndexI 

<25 341 37% 1.00

25-29 464 47% 1.27 (1.07-1.51) <.01

30+ 115 60% 1.61 (1.31-1.98) <.01

Current Smoking 

Status 

Nonsmoker 470 39% 1.00

Smoker 443 51% 1.32 (1.14-1.53) <.01

Smokeless 

Status 

Nonsmokeless 655 43% 1.00

Smokeless User 295 49% 1.15 (0.99-1.33) .07

Battalion Infantry A 394 38% 1.00

Infantry B 116 52% 1.38 (1.11-1.71) <.01

Cavalry 136 52% 1.37 (1.11-1.69) <.01

Field artillery 163 42% 1.13 (0.90-1.40) .30

Brigade support 

battalion 84 60% 1.59 (1.28-1.97) <.01

Brigade special 

troops battalion 57 46% 1.21 (0.89-1.66) .24

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.

EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM
 October – December 2013 41

THE ARMY MEDICAL DEPARTMENT JOURNAL

implementation. The increase in injury incidence was 

approximately the same for both groups. Overuse injuries also increased after the implementation of ATAC/

ECPs, while traumatic injuries showed little change. It 

has been stated that overuse injuries typically occur at 

the beginning of new exercise programs and account 

for a majority of the injuries incurred.23,24 Some of the 

common causes of overuse injuries include engaging 

in too much physical activity too soon, exercising too 

long, performing too much of one activity, and improper 

technique. Some studies have also found that the majority of injuries occurring in Army infantry Soldiers are 

attributed to physical fi tness and sports activities.6-10,25

However, the increase in overuse injuries was similar 

Table 5. Physical Training and Physical Fitness Risk Factors for Injury among Men Participating in ATAC/ECPs (n=950).

Variable Subcategory of Variable n Injury After

ATAC/ECP

Risk Ratio

(95% CI)

After ATAC/ECP

P

Physical training at prior assignment Traditional PT 767 46% 1.00

Extreme conditioning programs 47 43% 0.93 (0.66-1.31) .67

Combination ECP and traditional 93 39% 0.85 (0.65-1.11) .20

Other and/or traditional 36 39% 0.85 (0.56-1.29) .42

How often do you participate in unit PT? <5 times per week 109 59% 1.00

5-7 times per week 730 42% 0.72 (0.60-0.86) <.01

>7 times per week 104 45% 0.77 (0.59-1.00) .05

Does your unit perform cross-training/

extreme conditioning programs for PT?

Extreme conditioning programs 610 45% 1.00

ATAC and/or combination of ATAC/

other programs

340 44% 1.00 (0.86-1.16) .96

How many times per week do you perform 

cross-training/ECP?

<1 time per week 66 50% 1.00

1-2 times per week 400 44% 0.88 (0.67-1.15) .36

3-4 times per week 286 43% 0.86 (0.65-1.13) .30

>4 times per week 167 45% 0.90 (0.67-1.21) .48

Estimated total miles per week ran

(unit PT)

≤7 miles per week 445 39% 1.00

7.01-9.00 miles per week 63 48% 1.23 (0.92-1.63) .19

9.01- 16 miles per week 320 44% 1.14 (0.96-1.35) .13

>16 miles per week 81 59% 1.52 (1.23-1.89) <.01

Times per week performed sprint training No sprint training 15 53% 1.00

<1 time per week 163 45% 0.85 (0.52-1.41) .56

1-2 times per week 620 44% 0.82 (0.50-1.32) .45

≥3 times per week 146 47% 0.89 (0.54-1.47) .65

Times per week of resistance training No resistance training 102 59% 1.00

<1 time per week 254 48% 0.82 (0.66-1.00) .07

1-2 times per week 458 41% 0.69 (0.57-0.84) <.01

≥3 times per week 130 41% 0.69 (0.53-0.90) <.01

Times per week of agility drills No agility training 110 58% 1.00

<1 time per week 297 45% 0.78 (0.63-0.95) <.02

1-2 times per week 431 42% 0.72 (0.59-0.87) <.01

≥3 times per week 106 41% 0.70 (0.53-0.92) <.01

How often performed road marches No road marching 29 41% 1.00

<1 time per month 134 55% 1.32 (0.83-2.09) .20

1 time per month 148 41% 0.98 (0.61-1.58) .93

2 times per month 237 48% 1.15 (0.73-1.81) .52

3 times per month 150 37% 0.89 (0.55-1.43) .63

>3 times per month 230 44% 1.05 (0.66-1.66) .83

Push-ups 20-56 repetitions 208 47% 1.21 (0.97-1.50) .09

57-67 repetitions 221 48% 1.23 (0.99-1.52) .06

68-76 repetitions 230 41% 1.05 (0.84-1.31) .69

77-111 repetitions 233 39% 1.00

Sit-ups 19-61 repetitions 223 54% 1.40 (1.14-1.72) <.01

62-69 repetitions 218 43% 1.11 (0.89-1.39) .36

70-78 repetitions 227 40% 1.03 (0.82-1.30) .78

79-109 repetitions 224 38% 1.00

2-mile Run (minutes and fraction of a 

minute)

11.12-13.52 minutes 233 34% 1.00

13.53-14.50 minutes 222 42% 1.23 (0.98-1.56) .08

14.51-15.50 minutes 204 44% 1.27 (1.00-1.61) .05

15.51-32.22 minutes 203 51% 1.49 (1.18-1.86) <.01

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.
42 http://www.cs.amedd.army.mil/amedd_journal.aspx

in both groups; therefore, no recommendations can be 

made for or against either program.

Unit PT Injury Risk Factors

For male Soldiers participating in ATAC/ECPs, those 

who ran greater distances, performed no resistance 

training, and served in either the Infantry B, Cavalry, 

or Brigade Support battalion were at a 

higher risk of injury. Male ATAC/ECPs 

participants who ran more miles per 

week during unit PT were at a higher 

risk of being injured than those who 

ran fewer miles per week. Other studies have also shown that risk of injury 

increases with miles run per week.26-28

As mentioned earlier, analysis of APFT 

scores indicated those who ran greater 

distances per week (16 miles or more) 

had an average 2-mile run time of 14.6 

minutes (±1.51 minutes), and those who 

ran fewer miles per week (less than 16 

miles per week) had identical average 

2-mile run times of 14.6 minutes (±1.61 

minutes). Based on these data, running 

more than 16 miles per week for unit PT 

increases injury risk and provides no 

additional aerobic performance benefi ts.

Soldiers performing resistance training 

with their unit at least once per week 

were at a lower risk of injury than were 

Soldiers in units that did not perform resistance training. In a US Air Force study, 

Walker et al found that replacement of 

a majority of the traditional long-distance running with interval running, agility 

training, and functional strength training 

decreased the overall injury rates by 67%, 

and trainees scored higher on nearly all of 

the measured fi tness parameters.14 Adding resistance training to an aerobic training program can also be benefi cial in the 

completion of job tasks or mission requirements. It has been shown that endurance 

training concurrent with resistance training improves load-bearing performance29-32

and heavy lifting tasks,32 and increases both 

short-term and long-term endurance capacity in sedentary and trained individuals.33

In a meta-analysis, both strength training 

and concurrent training (combination of 

strength and endurance training) had larger 

effects on strength, 1.76 (95% CI, 1.34-2.18) 

and 1.44 (95% CI, 1.03-1.84) respectively, 

when compared to endurance training only (0.78, 95% 

CI, 0.36-1.19).34 The evidence suggests that implementation of a combined resistance and endurance training 

program will enable Soldiers to complete specifi c mission tasks more effectively and with lower risk of injury 

than Soldiers who do not incorporate resistance training 

into their physical fi tness programs.

Table 6. Unit PT and Personal Risk Factors for Injury Among Men Participating in 

ATAC/ECPs Using Multivariate Logistic Regression.

Variable Subcategory of

Variable

n Odds Ratio

(95% CI) 

P

Body mass index (BMI) <25 310 1.00

25-29.9 414 1.77 (1.29-2.44) <.01

30+ 98 2.72 (1.67-4.43) <.01

Tobacco Nonsmoker 430 1.00

Smoker 392 1.80 (1.34-2.42) <.01

Battalion Infantry A 342 1.00

Infantry B 100 1.62 (1.01-2.61) .05

Cavalry 128 1.87 (1.20-2.92) <.01

Field artillery 139 1.36 (0.89-2.08) .15

Brigade support 

battalion

64 1.96 (1.09-3.54) .03

Brigade special troops 

battalion

49 1.20 (0.62-2.32) .60

Times per week performing 

resistance training 

No resistance training 80 1.00

<1 time per week 218 0.53 (0.31-0.92) .03

1-2 times per week 409 0.50 (0.29-0.84) .01

≥3 times per week 115 0.45 (0.24-0.85) .01

Estimated miles per week 

of running 

≤7 miles a week 401 1.00

7.01-9.00 miles a week 54 1.05 (0.57-1.94) .87

9.01-16 miles a week 290 1.00 (0.72-1.40) .99

>16 miles a week 77 2.24 (1.33-3.80) <.01

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.

Variables entered into the model:

Age How often do you participate in unit physical training?

BMI Estimated total miles per week ran

Current smoking status Agility Training

Battalion Resistance Training

Table 7. Physical Fitness Test Risk Factors for Injury Among Men Participating in ATAC/ECPs Using Multivariate Cox Regression.

Variable Level of Variable n Odds Ratio

(95%CI) 

P

Push-ups 20-56 repetitions 188 1.01 (0.62-1.63) .97

57-67 repetitions 207 1.11 (0.71-1.72) .50

68-76 repetitions 218 1.00 (0.66-1.50) .99

77-111 repetitions 222 1.00

Sit-ups 19-61 repetitions 199 1.53 (0.94-2.50) .09

62-69 repetitions 205 1.03 (0.66-1.60) .91

70-78 repetitions 213 0.92 (0.60-1.39) .68

79-109 repetitions 218 1.00

2-mile Run

(minutes and fraction

of a minute)

11.12-13.52 minutes 226 1.00

13.53-14.50 minutes 217 1.42 (0.95-2.12) .09

14.51-15.50 minutes 195 1.45 (0.95-220) .08

≥15.51 minutes 197 1.76 (1.13-2.74) .01

Variables entered into the model: Age, battalion, push-ups, sit-ups, and 2-mile run.

Note: controlled for age and battalion.

ATAC indicates Advanced Tactical Athlete Conditioning program.

ECP indicates extreme conditioning program.

EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM
 October – December 2013 43

THE ARMY MEDICAL DEPARTMENT JOURNAL

Infantry A had the lowest injury incidence (38%) after the implementation 

of ATAC/ECPs. This battalion also had 

the youngest Soldiers, one of the lowest 

average BMIs, performed less running 

per week during unit PT, and performed 

the most sprint, resistance, and agility 

training per week in comparison to the 

other battalions. As previously mentioned, running more miles per week 

increases injury risk.26-28 In addition, injury risk is higher for recruits with lower levels of lowerextremity muscle strength or who lack a consistent lower-extremity weight training program.35,36 The Infantry 

A battalion’s unit PT program involved less running and 

more cross-training activities, likely contributing to its 

lower injury rates.

Interviews of battalion commanders concerning their 

views regarding physical training and fi tness offered additional insights into the difference in injury rates. For 

example, the Infantry A battalion commander spent 

the largest amount of money on fi tness equipment for 

the unit and stated he considered mobility/agility to be 

the most important fi tness ability. In comparison, other 

commanders (including the Infantry B commander) rated endurance as the most important fi tness component. 

Upon examination of the 2 infantry groups (Infantry A 

and Infantry B), a difference in injury incidence of 15% 

was observed. Both commanders had also implemented 

an injury surveillance tracking system to collect injury 

metrics in their respective battalions. However, the Infantry A battalion reported its injury metrics every 3 

weeks, whereas the Infantry B battalion collected them 

at the company level only and did not review or report 

them on a set schedule. Infantry A and Field Artillery, 

the 2 battalions with the lowest injury rates, ran the fewest miles per week for unit PT (10.1 miles and 9.2 miles, 

respectively), and both units tracked and reported their 

injury metrics at least once a month. Therefore, running 

fewer miles per week during unit PT and implementing 

an injury surveillance system11 in which metrics are reported at least monthly may have a positive infl uence on 

lowering injury rates. In a consensus paper concerning 

military personnel involved with ECPs, Bergeron et al 

state that regular monitoring and accurate injury reporting may help reduce injury rates and optimize the physical fi tness benefi ts of ECPs.17

Soldier Injury Risk Factors

In the current study, 62% of the men were considered 

either overweight or obese, which is similar to the US 

population, of which 64% of men aged 20 to 39 years 

are also considered either overweight or obese.37 Injury 

risk for men was higher for those with a BMI classifying 

them as overweight or obese. Other investigations have 

found that Soldiers with a higher BMI are at a greater 

risk of being injured.9,25,38 In a study involving infantry 

Soldiers, Reynolds et al found that Soldiers with a BMI 

of 25 or higher were at 2.2 times greater risk of being 

injured.9

 These fi ndings are similar to the results found 

in this evaluation (1.8 and 2.7 times greater risk of injury 

for overweight or obese Soldiers, respectively).

According to the CDC, BMI is a fairly reliable indicator 

of body fatness for most people.24 Therefore, Soldiers 

with higher BMIs will most likely have larger amounts 

of excess body fat. Investigations examining excessive 

body fat have shown that it adversely affects performance on military tasks that require both aerobic and 

strength components.39-42 In a study investigating physical and physiological performance in Army Soldiers, 

Crawford et al found that Soldiers with 18% or less body 

fat performed signifi cantly better on 7 of 10 fi tness tests, 

compared to Soldiers with body fat greater than 18%. 

The authors suggested that Soldiers who have an excess 

amount of body fat may possess musculoskeletal and 

physiological fi tness defi cits, thereby decreasing military readiness and increasing risk for injury.39 In an investigation of active duty Navy personnel, Bohnker et 

al examined mean BMI and overall physical readiness 

test scores (outstanding, excellent, good, satisfactory, 

and fail). As physical fi tness test scores decreased, the 

mean BMI increased for both men and women.42 This 

trend was also observed in the current study (analysis 

performed on all men who completed the survey and 

had injury data). Soldiers with lower physical fi tness 

test results as examined by quartile also had higher average BMIs.43 Being overweight or obese may not only 

increase a Soldier’s risk of incurring an injury, but may 

also have an adverse effect on aerobic and strength performance. The data is presented in Table 8.

Injury risk was higher in smokers than in nonsmokers. 

Previous studies have also demonstrated an increased 

general risk of injury in smokers compared to nonsmokers, and a defi nable increased risk of musculoskeletal 

Table 8. Mean BMIs and Physical Fitness Test Scores Grouped by Quartiles of 

Poor to High Performance for Men.

Mean BMIs for

Fitness Variables

n Q1 Q2 Q3 Q4 ANOVA 

low P

performance

high

performance

2-mile run (mean 

BMI) 1,091 28.2 BMI 26.1 BMI 25.2 BMI 24.6 BMI <.01

Push-ups

(mean BMI) 1,137 26.6 BMI 26.1 BMI 26.1 BMI 25.8 BMI .03

Sit-ups

(mean BMI) 1,134 27.0 BMI 26.1 BMI 25.7 BMI 25.5 BMI <.01

BMI indicates body mass index.
44 http://www.cs.amedd.army.mil/amedd_journal.aspx

injury.25,44-52 Also, among smokers themselves, the risk 

of injury has been shown to increase in direct relation to 

the number of cigarettes smoked per day.25,44,47 The relationship between tobacco use and injury may be due to a 

 compromised ability to repair damaged tissues, thereby 

increasing susceptibility to the repetitive microtrauma 

that presumably causes overuse injuries.53 In one investigation, researchers showed that tibial fracture healing to 

clinical union took 24% longer in smokers compared to 

nonsmokers,54 while another study showed that smokers 

experienced impaired wound healing when compared 

to nonsmokers.55 Therefore, harsh deployment environments and military occupational specialty requirements 

may result in weakened tissues from training and overuse, which may result in a greater susceptibility to injury among smokers who maintain high levels of physical 

fi tness to meet demanding tasks.

Injury risk for Soldiers with the slowest 2-mile run 

times was higher when compared to those showing the 

fastest 2-mile run times. Previous studies investigating 

run times during basic combat training have also found 

that slower run times place Soldiers at a higher risk of 

injury.8,21,45,56,57 The Soldiers with the slowest 2-mile run 

times would have lower aerobic capacities than those 

with the fastest 2-mile run times.58 Soldiers with lower 

aerobic capacities will likely experience greater physiological stress and/or fatigue during tasks such as running, cross-training, and calisthenics due to exercising 

at a higher percentage of their maximum aerobic capacity in comparison with Soldiers with greater fi tness levels. Soldiers of lower fi tness levels will not only be exercising at a higher percentage of their aerobic capacity to 

accomplish the same task as a more fi t Soldier, but they 

will also perceive tasks as more diffi cult.59 The greater 

physiological stress and/or fatigue experienced may 

lead to a higher risk of injury. Studies on fatigue have 

demonstrated decrements in proprioceptive ability,60 a 

decrease in joint stability,61 alterations in muscle activity,60 changes in gait,62-66 balance,67,68 low-frequency fatigue,69 neuromuscular function,70 and ligament laxity.71

CONCLUSION

This project found similar increases in injury rates for 

units performing ATAC/ECPs and units not performing ATAC/ECPs. Therefore, no recommendations can 

be made for or against use of those programs. Risk factors associated with higher risk of injury following the 

start of a new exercise program included running longer 

distances during unit physical training, having a BMI 

of 25 or more, and smoking cigarettes. However, almost 

any level of resistance training appeared to produce a 

noticeable protective effect. A lower risk of injury was 

found for Soldiers who performed any resistance training compared to Soldiers who performed no resistance 

training.

Soldiers should recognize the challenges and limitations 

of ECPs or exercise programs with ECP components 

and approach them with discretion. The goal of all fi tness programs should be to meet occupational and operational demands and expectations while minimizing 

injury risks.

RELEVANCE TO PERFORMANCE TRIAD

A key aspect of The Army Surgeon General’s Performance Triad is the promotion of optimal physical activity among Army Soldiers, family members, retirees, and 

civilians. Optimal physical activity involves incorporating regular physical activity into daily routines while 

also minimizing injury risk. Prevention of injury during physical activity is crucial to preserving Soldier and 

unit readiness. The results of this analysis suggest that 

injuries can be minimized by limiting longer running 

distances and adding resistance training to unit physical training. The results also suggest that injury risks 

were lower for nonsmokers, Soldiers with higher aerobic endurance, and Soldiers maintaining a healthy body 

weight.

REFERENCES

1. DoD Military Injury Prevention Priorities Working Group. Leading Injuries, Causes and Mitigation Recommendations. Washington, DC: Defense 

Safety Oversight Council, US Dept of Defense; 

2006. Available at: http://www.dtic.mil/cgi-bin/

GetTRDoc?Location=U2&doc=GetTRDoc.

pdf&AD=ADA458257. Accessed July 10, 2013.

2. Almeida SA, Williams KM, Shaffer RA, Luz JT, 

Badong E, Brodine SK. A Physical Training Program to Reduce Musculoskeletal Injuries in U.S. 

Marine Corps Recruits, Version 1.0 [Naval Health 

Research Center Technical Report No. NHRC07-

2B]. San Diego, CA: Naval Health Research Center; May 1997. Available at: http://www.dtic.mil/

cgi-bin/GetTRDoc?AD=ADA326216. Accessed 

July 10, 2013.

3. Lauder TD, Baker SP, Smith GS, Lincoln AE. 

Sports and physical training injury hospitalizations in the Army. Am J Prev Med. 2000;18(suppl 

3):118-128.

4. Smith TA, Cashman TM. The incidence of 

injury in light infantry soldiers. Mil Med. 

2002;167(2):104-108.

EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM
 October – December 2013 45

THE ARMY MEDICAL DEPARTMENT JOURNAL

5. Loringer K, Bedno S, Hauret K, Jones BH, Kao 

TC, Mallon T. Injuries from Participation in Sports, 

Exercise, and Recreation Activities Among Active 

Duty Service Members—Analysis of the April 2008 

Status of Forces Survey of Active Duty Members. 

Aberdeen Proving Ground, MD: US Army Public Health Command; 2011. Report No. 12-HF0DPT-08. Available at: http://www.dtic.mil/cgibin/GetTRDoc?Location=U2&doc=GetTRDoc.

pdf&AD=ADA560733. Accessed July 11, 2013.

6. Tomlinson JP, Lednar WM, Jackson JD. Risk of injury in soldiers. Mil Med. 1987;152(2):60-64.

7. Smith GS, Dannenberg AL, Amoroso PJ. Hospitalization due to injuries in the military. Evaluation of 

current data and recommendations on their use for 

injury prevention. Am J Prev Med. 2000;18(suppl 

3):41-53.

8. Knapik JJ, Ang P, Reynolds K, Jones B. Physical 

fi tness, age and injury incidence in infantry soldiers. J Occup Med. 1993;35(6):598-603.

9. Reynolds K, Cosio-Lima L, Bovill M, Tharion W, 

Williams J, Hodges T. A comparison of injuries, 

limited duty days, and injury risk factors in infantry, artillery, construction engineers, and special 

forces soldiers. Mil Med. 2009;174(7):702-708.

10. Wilkinson DM, Blacker SD, Richmond VL, et al. 

Injuries and injury risk factors among British army 

infantry soldiers during predeployment training. 

Inj Prev. 2011;17(6):381-387.

11. Knapik JJ, Bullock SH, Canada S, et al. Infl uence of an injury reduction program on injury 

and fi tness outcomes among soldiers. Inj Prev.

2004;10(1):37-42.

12. Knapik JJ, Darakjy S, Scott SJ, et al. Evaluation of a standardized physical training program 

for Basic Combat Training. J Strength Cond Res.

2005;19(2):246-253.

13. Knapik JJ, Hauret KG, Arnold S, et al. Injury 

and fi tness outcomes during implementation of 

physical readiness training. Int J Sports Med. 

2003;24(5):372-381.

14. Walker TB, Lennemann LM, Anderson V, Lyons 

W, Zupan MF. Adaptations to a new physical training program in the combat controller training pipeline. J Spec Oper Med. 2011;11(2):37-44.

15. Hofstetter MC, Mäder U, Wyss T. Effects of 

a 7-week outdoor circuit training program on 

Swiss Army recruits. J Strength Cond Res. 

2012;26(12):3418-3425.

16. Knapik JJ, Rieger W, Palkoska F, Van Camp S, 

Darakjy S. United States Army physical readiness training: rationale and evaluation of the 

physical training doctrine. J Strength Cond Res. 

2009;23(4):1353-1362.

17. Bergeron MF, Nindl BC, Deuster PA, et al. Consortium for Health and Military Performance 

and American College of Sports Medicine consensus paper on extreme conditioning programs 

in military personnel. Curr Sports Med Rep. 

2011;10(6):383-389.

18. Jones SB, Knapik JJ, Sharp MA, Darakjy S, Jones 

BH. Validity of self-reported physical fi tness test 

scores. Mil Med. 2007;172(2):115-120.

19. Field Manual 7-22: Army Physical Readiness 

Training. Washington, DC: US Dept of the Army; 

October 2012.

20. Grier T, Knapik JJ, Swedler DI, Spiess A, Jones 

BH. Injury Prevention Effectiveness of Modifi cations of Shoe Type Injuries and Risk Factors Associated with Pain and Discomfort in the US Army 

Band Fort Meyer, Virginia 2007-2008 [Injury 

Prevention Report No. 12-HF-05WC-07]. Aberdeen Proving Ground, MD: US Army Center for 

Health Promotion and Preventive Medicine; June 3, 

2009. Available at: http://www.dtic.mil/cgi-bin/Get

TRDoc?AD=ADA503988. Accessed July 11, 2013.

21. Knapik JJ, Swedler DI, Grier T, et al. Injury Reduction Effectiveness of Prescribing Running Shoes 

Based on Foot Shape in Basic Combat Training

[USACHPPM Report No. 12-MA-05SB-08]. Aberdeen Proving Ground, MD: US Army Center 

for Health Promotion and Preventive Medicine; 

June 2008. Available at: http://www.dtic.mil/cgibin/GetTRDoc?Location=U2&doc=GetTRDoc.

pdf&AD=ADA484214. Accessed August 5, 2013,

22. About BMI for Adults. Centers for Disease Control 

and Prevention website; 2011. Available at: http://

www.cdc.gov/healthyweight/assessing/bmi/adult_

bmi/index.html. Accessed September 5, 2012.

23. Settles DM, Brown TP. US Navy Pre-Entry Physical Training Plan. Pensacola, FL: Naval Service 

Training Command Offi cer Development; 2002. 

Available at http://www.nrotc.navy.mil/pdfs/preconditioning.pdf. Accessed March 22, 2013.

24. Overuse injury: how to prevent training injuries. 

Mayo Clinic website. 2010. Available at: http://

www.mayoclinic.com/health/overuse-injury/

my01092. Accessed March 22, 2013.

25. Reynolds KL, Heckel HA, Witt CE, et al. Cigarette 

smoking, physical fi tness, and injuries in infantry 

soldiers. Am J Prev Med. 1994;10(3):145-150.

26. Koplan JP, Powell KE, Sikes RK, Shirley RW, Campbell CC. An epidemiologic study of the benefi ts and 

risks of running. JAMA. 1982;248(23):3118-3121.

27. Marti B, Vader JP, Minder CE, Abelin T. On 

the epidemiology of running injuries. The 

1984 Bern Grand-Prix study. Am J Sports Med. 

1988;16(3):285-294.
46 http://www.cs.amedd.army.mil/amedd_journal.aspx

28. Samet JM, Chick TW, Howard CA. Running-related mortality: a community survey. Ann Sports Med. 

1982;1:30-34.

29. Kraemer WJ, Vescovi JD, Volek JS, et al. Effects of 

concurrent resistance and aerobic training on loadbearing performance and the Army physical fi tness 

test. Mil Med. 2004;169(12):994-999.

30. Kraemer WJ, Vogel JA, Patton JF, Dziados JE, 

Reynolds KL. The effects of various physical training programs on short duration, high intensity load 

bearing performance and the Army Physical Fitness Test. Technical Report. Natick MA: US Army 

Research Institute of Environmental Medicine; 

1987. Report No. T30-87.

31. Kraemer WJ, Mazzetti SA, Nindl BC, et al. Effect 

of resistance training on women’s strength/power 

and occupational performances. Med Sci Sports 

Exerc. 2001;33(6):1011-1025.

32. Reynolds KL, Harman EA, Worsham RE, Sykes 

MB, Frykman PN, Backus VL. Injuries in women associated with a periodized strength training and running program. J Strength Cond Res.

2001;15(2):136-143.

33. Tanaka H, Swensen T. Impact of resistance training 

on endurance performance. A new form of cross 

training?. Sports Med. 1998;25(3):191-200.

34. Wilson JM, Marin PJ, Rhea MR, Wilson SM, 

Loenneke JP, Anderson JC. Concurrent training: 

a meta-analysis examining interference of aerobic and resistance exercises. J Strength Cond Res.

2012;26(8):2293-2307.

35. Hoffman JR, Chapnik L, Shamis A, Givon U, Davidson B. The effect of leg strength on the incidence of lower extremity overuse injuries during 

military training. Mil Med. 1999;164(2):153-156.

36. Rauh MJ, Macera CA, Trone DW, Shaffer RA, 

Brodine SK. Epidemiology of stress fractures and 

lower extremity overuse injuries in female recruits. 

Med Sci Sports Exerc. 2006;38(9):1571-1577.

37. Flegal KM, Carroll MD, Ogden CL, Curtin LR. 

Prevalence and trends in obesity among US adults, 

1999-2008. JAMA. 2010;303(3):235-241.

38. Knapik JJ, Jones SB, Darakjy S, et al. Injuries and injury risk factors among members of 

the United States Army Band. Am J Ind Med. 

2007;50(12):951-961.

39. Crawford K, Fleishman K, Abt JP, et al. Less body fat 

improves physical and physiological performance 

in Army Soldiers. Mil Med. 2011;176(1):35-43.

40. Harman EA, Frykman PN. The relationship of 

body size and composition to the performance of 

physically demanding military tasks. In: Marriott 

BM, Grumstrup-Scott J, eds. Body Composition 

and Physical Performance. Washington, DC: The 

National Academies Press; 1992:105-118.

41. Mattila VM, Tallroth K, Marttinen M, Pihlajamäki 

H. Body composition by DEXA and its association 

with physical fi tness in 140 conscripts. Med Sci 

Sports Exerc. 2007;39(12):2242-2247.

42. Bohnker BK, Sack DM, Wedierhold L, Malakooti M. Navy physical readiness test scores and 

body mass index (spring 2002 cycle). Mil Med. 

2005;170(10):851-854.

43. Grier T, Chervak M, McNulty V, Jones BH. Evaluation of the advanced tactical athlete conditioning 

and extreme conditioning programs in the 25th Infantry Division, Schofi eld Barracks, Hawaii. Injury 

Prevention Report. Aberdeen Proving Ground, MD: 

United States Army Institute of Public Health; 2010.

44. Knapik JJ, Hauret KG, Jones BH. Primary Prevention of Injuries in Initial Entry Training. In: Lenhart MK, Lounsbury DE, North RB, eds. Textbook 

of Military Medicine: Recruit Medicine. Washington, DC: Borden Institute; 2006.

45. Knapik JJ, Sharp MA, Canham-Chervak M, 

Hauret K, Patton JF, Jones BH. Risk factors for 

training-related injuries among men and women 

in basic combat training. Med Sci Sports Exerc. 

2001;33(6):946-954.

46. Heir T, Eide G. Injury proneness in infantry conscripts undergoing a physical training programme: 

smokeless tobacco use, higher age, and low levels 

of physical fi tness are risk factors. Scand J Med Sci 

Sports. 1997;7:304-311.

47. Altarac M, Gardner JW, Popovich RM, Potter R, 

Knapik JJ, Jones BH. Cigarette smoking and exercise-related injuries among young men and women. 

Am J Prev Med. 2000;18(suppl 3):96-102.

48. Munnoch K, Bridger RS. Smoking and injury 

in Royal Marines’ training. Occup Med (Lond). 

2007;57(3):214-216.

49. Knapik JJ, Swedler DI, Grier TL, et al. Injury reduction effectiveness of selecting running shoes 

based on plantar shape. J Strength Cond Res.

2009;23(3):685-697.

50. Dettori J, Reynolds K, Amoroso P, Barnes J, Westphal K, Lavin P. Smoking and injury risk among female US Army basic combat trainees. Presented at 

the Third International Conference for Injury Prevention and Control. Melbourne, Australia; 1996.

51. Reynolds K, Amoroso P, Dettori J. Association of 

tobacco use with injuries among infantry soldiers 

carrying loads on a 100-mile road march. Presented 

at the Third International Conference for Injury Prevention and Controls. Mebourne, Australia; 1996.

52. Grier TL, Knapik JJ, Canada S, Canham-Chervak 

M, Jones BH. Risk factors associated with selfreported training-related injury before arrival at 

the US Army Ordnance School. Public Health. 

2010;124(7):417-423.

EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM
 October – December 2013 47

THE ARMY MEDICAL DEPARTMENT JOURNAL

53. Amoroso PJ, Reynolds KL, Barnes JA, White DJ. 

Tobacco and injuries: an annotated bibliography. 

Technical Report. Natick, MA: US Army Research 

Institute of Environmental Medicine; 1996. Report 

No. TN96-1.

54. Kyrö A, Usenius J, Aarnio M, Kunnamo I, Avikainen V. Are smokers a risk group for delayed healing of tibial shaft fractures?. Ann Chir Gynaecol.

1993;82(4):254-262.

55. Jones JK, Triplett RG. The relationship of cigarette 

smoking to impaired intraoral wound healing: a review of evidence and implications for patient care. J 

Oral Maxillofac Surg. 1992;50(3):237-249.

56. Jones BH, Bovee MW, Harris JM, Cowan DN. Intrinsic risk factors for exercise-related injuries 

among male and female Army trainees. Am J Sports 

Med. 1993;21(5):705-710.

57. Hauret KG, Knapik JJ, Darakjy S, et al. Reduced 

injury risk in Army basic combat training with a 

standardized physical training program. Med Sci 

Sports Exerc. 2004;36(5):S309.

58. Knapik JJ. The Army Physical Fitness Test 

(APFT): a review of the literature. Mil Med. 

1989;154(6):326-329.

59. Garcin M, Vautier JF, Vandewalle H, Monod H. 

Rating of perceived exertion (RPE) as an index of 

aerobic endurance during local and general exercise. Ergonomics. 1988;41(8):1105-1114.

60. Rozzi SL, Lephart SM, Fu FH. Effects of muscular fatigue on knee joint laxity and neuromuscular 

characteristics of male and female athletes. J Athl 

Train. 1999;34(2):106-114.

61. Melnyk M, Gollhofer A. Submaximal fatigue of 

the hamstrings impairs specifi c refl ex components 

and knee stability. Knee Surg Sports Traumatol Arthrosc. 2007;15(5):525-532.

62. Candau R, Belli A, Millet GY, Georges D, Barbier 

B, Rouillon JD. Energy cost and running mechanics during a treadmill run to voluntary exhaustion in humans. Eur J Appl Physiol Occup Physiol. 

1998;77(6):479-485.

63. Nyland JA, Shapiro R, Stine RL, Horn TS, Ireland 

ML. Relationship of fatigued run and rapid stop to 

ground reaction forces, lower extremity kinematics, 

and muscle activation. J Orthop Sports Phys Ther. 

1994;20(3):132-137.

64. Gerlach KE, White SC, Burton HW, Dorn JM, Leddy JJ, Horvath PJ. Kinetic changes with fatigue and 

relationship to injury in female runners. Med Sci 

Sports Exerc. 2005;37(4):657-663.

65. LeBris R, Billat V, Auvinet B, Chaleil D, Hamard L, 

Barrey E. Effect of fatigue on stride pattern continuously measured by an accelerometric gait recorder 

in middle distance runners. J Sports Med Phys Fitness. 2006;46(2):227-231.

66. Yoshino K, Motoshige T, Araki T, Matsuoka 

K. Effect of prolonged free-walking fatigue 

on gait and physiological rhythm. J Biomech. 

2004;37(8):1271-1280.

67. Johnston RB III, Howard ME, Cawley PW, Losse 

GM. Effect of lower extremity muscular fatigue on 

motor control performance. Med Sci Sports Exerc. 

1998;30(12):1703-1707.

68. Dickin DC, Doan JB. Postural stability in altered 

and unaltered sensory environments following fatiguing exercise of lower extremity joints. Scand J 

Med Sci Sports. 2008;18(6):765-772.

69. Baptista RR, Scheeren EM, Macintosh BR, Vaz 

MA. Low-frequency fatigue at maximal and submaximal muscle contractions. Braz J Med Biol Res. 

2009;42(4):380-385.

70. Wojtys EM, Wylie BB, Huston LJ. The effects of 

muscle fatigue on neuromuscular function and 

anterior tibial translation in healthy knees. Am J 

Sports Med. 1996;24(5):615-621.

71. Sakai H, Tanaka S, Kurosawa H, Masujima 

A. The effect of exercise on anterior knee laxity in female basketball players. Int J Sports Med.

1992;13(7):552-554.

AUTHORS

Mr Grier is a Kinesiologist for the Injury Prevention 

Program of the Epidemiology and Disease Surveillance 

Portfolio, US Army Public Health Command, Aberdeen 

Proving Ground, Maryland.

Dr Canham-Chervak is a Senior Epidemiologist for the 

Injury Prevention Program of the Epidemiology and 

Disease Surveillance Portfolio, US Army Public Health 

Command, Aberdeen Proving Ground, Maryland.

MAJ McNulty is a Physical Therapy Staff Offi cer for 

the Public Health Assessment Program of the Health and 

Wellness Portfolio, US Army Public Health Command, 

Aberdeen Proving Ground, Maryland.

Dr Jones is a Program Manager for the Injury Prevention 

Program of the US Army Public Health Command, 

Aberdeen Proving Ground, Maryland.
48 http://www.cs.amedd.army.mil/amedd_journal.aspx

Butte et al defi ned physical activity (PA) as “any bodily 

movement produced by the contraction of skeletal muscle 

that increases energy expenditure above a resting level.”1

Investigators in the fi eld of PA monitoring have been 

interested in capturing the broad range of human behaviors encompassing “activity” and “inactivity.”1

 This 

also includes PA in physically demanding occupations 

such as those in the military setting. An understanding 

of the amount, type, and intensity of PA is needed to 

help prevent injury while maintaining unit performance 

and morale.2

 The US Army’s Performance Triad initiative seeks to improve Soldier readiness and resilience by 

improving Soldiers’ PA, nutrition, and sleep behaviors. 

An understanding of the present level of PA during Basic Combat Training (BCT) will help determine if those 

levels should be maintained or altered in order to meet 

guidelines for Soldier health and performance.

Measurement tools used to assess PA have included 

subjective measures such as self-report questionnaires, 

logs, and diaries, as well as objective measures such as 

pedometers, accelerometers, heart rate monitors, and 

direct observation. Pedometers are small, lightweight, 

portable, nonintrusive, inexpensive devices that record 

daily step counts. More recently, researchers have used 

accelerometers to provide more detailed information 

about PA. Unlike pedometry, accelerometry allows for 

the characterization of PA intensity and duration. Direct 

observation is considered one of the most valid, reliable, 

and objective methods for assessing PA.3

 However, direct observation is often viewed as labor-intensive and 

tedious. Consequently, it has not often been used to assess PA. Self-report techniques are the instruments of 

choice for assessing PA levels in large-scale epidemiological studies.4

 This is because they are practical, easy 

Measuring Physical Activity During

 US Army Basic Combat Training:

 A Comparison of 3 Methods

Jan E. Redmond, PhD

Bruce S. Cohen, PhD

Kathleen Simpson, MS

Barry A. Spiering, PhD

Marilyn A. Sharp, MS

ABSTRACT

Background: An understanding of the demands of physical activity (PA) during US Army Basic Combat Training (BCT) 

is necessary to support Soldier readiness and resilience. The purpose of this study was to determine the agreement among 

3 different PA measurement instruments in the BCT environment. 

Methods: Twenty-four recruits from each of 11 companies wore an ActiGraph accelerometer (Actigraph, LLC, Pensacola, 

FL) and completed a daily PA log during 8 weeks of BCT at 2 different training sites. The PA of one recruit from each 

company was recorded using PAtracker, an Army-developed direct observation tool. Information obtained from the 

accelerometer, PA log, and PAtracker included time spent in various types of PA, body positions, PA intensities, and 

external loads carried. Pearson product moment correlations were run to determine the strength of association between 

the ActiGraph and PAtracker for measures of PA intensity and between the PAtracker and daily PA log for measures of 

body position and PA type. The Bland-Altman method was used to assess the limits of agreement (LoA) between the 

measurement instruments.

Results: Weak correlations (r=-0.052 to r=0.302) were found between the ActiGraph and PAtracker for PA intensity. 

Weak but positive correlations (r=0.033 to r=0.268) were found between the PAtracker and daily PA log for body position 

and type of PA. The 95% LoA for the ActiGraph and PAtracker for PA intensity were in disagreement. The 95% LoA for 

the PAtracker and daily PA log for standing and running and all PA types were in disagreement; sitting and walking were 

in agreement.

Conclusions: The ActiGraph accelerometer provided the best measure of the recruits’ PA intensity while the PAtracker 

and daily PA log were best for capturing body position and type of PA in the BCT environment. The use of multiple PA 

measurement instruments in this study was necessary to best characterize the physical demands of BCT.
 October – December 2013 49

to administer, and incur a relatively low cost and low participant burden, but their validity may be in question.4,5

Self-report methods rely on the subject’s ability to recall 

and are prone to misrepresentation, including accurately 

recalling the time and intensity of the PA performed.4,5

During BCT, new recruits learn basic soldiering skills 

and participate in physical readiness training between 5 

AM and 7 AM. The recruits are often required to move on 

foot from one training activity to another. Multiple measurement instruments may be needed to characterize all 

of the demands of PA during BCT, including the amount, 

type, and intensity. On the other hand, only one measurement instrument may be required to characterize a 

specifi c component of PA. Therefore, the purpose of this 

study was to determine the agreement between an ActiGraph accelerometer and PAtracker (direct observation) 

for characterizing PA intensity, and between the PAtracker and a daily PA log (self-report) for characterizing body position and PA type in the BCT environment.

METHODS

Study Overview

Data for this study was collected 

from recruits in 2 training battalions during separate BCT cycles. 

The fi rst iteration took place from 

June to August 2010, at Fort Jackson, South Carolina, during which 

recruits from 6 training companies 

were studied. The second iteration 

took place from July to September 

2011, at Fort Sill, Oklahoma, during which recruits from 5 training 

companies were studied. The companies included in the study were 

determined based solely upon their 

availability.

Prior to the start of the study, recruits in each training company 

were informed of the requirements 

and potential risks of participation. Recruits voluntarily signed 

an informed consent document approved by the Institutional Review 

Board of the US Army Research Institute of Environmental Medicine (USARIEM), Natick, Massachusetts. 

Investigators followed the policies for protection of human subjects as prescribed in Army Regulation 70-25,

6

and the research was conducted in compliance with the 

provisions of 45 CFR Part 46, Protection of Human Subjects. Recruits were included in the study if they were at 

least 18 years of age, were assigned to a battalion for a 

10-week BCT course, and were able to participate fully 

in all BCT activities.

Physical Activity Assessment

ActiGraph Accelerometer

The accelerometer used in this study was the ActiGraph 

GT3X triaxial accelerometer (Actigraph, LLC, Pensacola, FL) shown in Figure 1. This device is capable of sensing acceleration along the vertical, anterior-posterior, 

and mediolateral axes . The accelerometer’s output is recorded in “counts,” which are the summation of the absolute values of the sampled changes in acceleration during a user-defi ned time period.7

 From the accelerometers, 

average daily time (minutes) each recruit spent in sedentary, light (<3 metabolic equivalent (MET)), moderate 

(3-6 MET), and vigorous (>6 MET) intensity activities 

was determined using the Freedson categories.7

 Sedentary to light intensity activity is defi ned as 0 to 1,951 

counts per minute, moderate intensity PA is defi ned as 

1,952 to 5,724 counts per minute, and vigorous intensity 

PA is defi ned as 5,725 or more counts per minute.7

Within each training company, 24 

recruits (Fort Jackson n=144, Fort 

Sill n=120) were outfi tted with an 

ActiGraph GT3X accelerometer. 

Each group of 24 recruits was 

comprised of 6 recruits in each of 

4 platoons (6 recruits/platoon4 

platoons/company=24 recruits/

company). When possible, at least 

one of the 6 recruits from each platoon was female. Research staff 

distributed the accelerometers to 

participants before the fi rst formation each morning (5 AM) and collected them immediately before 

or after the dinner meal (approximately 4 PM). Recruits wore the accelerometer in a pouch attached to 

a belt and placed over their left hip 

Monday through Saturday for 8 

weeks. If a recruit became injured, 

ill, or was separated from the platoon for a portion of the day while 

wearing the accelerometer, the accelerometer was worn by another recruit from the same 

training company. Compliance checks were performed 

by research staff at morning formation and morning 

meal times to ensure the devices were being worn properly. Although 24 recruits wore the ActiGraph, accelerometer data was treated as unit data refl ective of the PA 

performed by the entire company.

Figure 1. The Actigraph accelerometer.
50 http://www.cs.amedd.army.mil/amedd_journal.aspx

Direct Observation

The USARIEM and L-3 Communications Corporation 

(San Diego, CA) developed the PAtracker, a novel PA 

tracking software designed specifi cally for direct observation in the BCT environment. The PAtracker software 

was installed on HTC smartphone devices (Figure 2), 

which allowed activities to be logged by selecting them 

from a predetermined menu on a touch-sensitive screen. 

The software automatically added a time stamp to each 

activity recorded. Activities were coded into the following operational defi nitions:

 Time spent asleep versus awake.

 Time spent in the following body positions: lying, 

sitting, standing/on feet, and kneeling.

 Time spent in the following types of PA: cadence 

marching, calisthenics, combatives, crawling, lift/

carry, barracks chores/menial tasks, obstacles/

climbing, running, stationary, and walking.

Physical activity was also classifi ed by load carried (0-

10 lbs, 10-25 lbs, 25-50 lbs, 50-75 lbs, >75 lbs) and PA 

intensity, including the categories of sedentary, light, 

moderate, and vigorous. The direct observation portion 

of this study employed the continuous duration recording method, which allowed trained observers to record 

changes in a recruit’s PA behaviors when changes in activity occurred.8

There were 6 observation teams at Fort Jackson and 5 

observation teams at Fort Sill. Each team consisted of 3 

to 6 observers who monitored and recorded a recruit’s 

activities. Observers were recruited from the local area 

and completed 10 hours of training over 3 consecutive 

days to become familiar with the PAtracker device and 

the operational defi nitions. Direct observation commenced at the beginning of each training day, and all 

activities during the day were recorded until the recruits 

returned to their barracks. The team observed a recruit 

in the designated platoon who was wearing an ActiGraph. If the designated recruit was not training that 

day, another recruit wearing the device was identifi ed 

and followed. Although individual recruits in each company were observed, the direct observation data was 

treated as unit data refl ective of the PA performed by 

the entire company.

Self-Report Daily Physical Activity Log

At the end of each training day, all recruits wearing an 

ActiGraph completed a 24-hour PA recall log, as shown 

in Figure 3. Recruits were asked to report the amount of 

time they spent wearing the ActiGraph during the day 

and the amount of time they spent sleeping the night before. In addition, they were asked to report the amount 

of time they spent sitting, standing, walking/marching, 

running, performing chores or barracks maintenance, 

doing calisthenics/obstacle courses, carrying a load 

pack, and participating in moderate to vigorous intensity activities during the day. All times were recorded as 

hours and minutes.

Statistical Analyses

 Pearson product moment correlations were run to determine the strength of association between the ActiGraph 

and PAtracker on measures of intensity and between 

the PAtracker and the daily PA log on measures of body 

position and PA type. Absolute agreement between the 

measurement instruments was assessed using the BlandAltman method9

 to determine if similar values for PA 

intensity, body position, and type of PA had been captured between 2 measurement instruments. First, differences in average daily time spent in each PA intensity, 

body position, or type of PA as measured by each instrument (ActiGraph, vigorous; PAtracker, vigorous) were 

plotted against their mean (mean of the average daily 

time obtained while in vigorous activity as measured by 

Figure 2. The PAtracker application screen interface on a 

smartphone.

MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING:

A COMPARISON OF 3 METHODS
 October – December 2013 51

THE ARMY MEDICAL DEPARTMENT JOURNAL

the ActiGraph and PAtracker). The data were then analyzed for the presence of heteroscedasticity by plotting 

the absolute values of individual differences between 

the 2 measurement instruments versus the means between the 2 instruments for PA intensity, body position, 

and type of PA.9,10 Data were defi ned as homoscedastic 

if R2 <0.1, or as heteroscedastic if R2 >0.1.9,10 Signifi cant 

Pearson product-moment correlation coeffi cients were 

considered indicative of heteroscedastic data (the random error increased as the average daily time increased). 

If the data were heteroscedastic, the 95% ratio limits of 

agreement (LoA) was calculated as follows:

95% ratio LoA=( SD of the difference 

scores÷average of the mean values)1.96

If the data were homoscedastic, the 95% LoA was calculated as follows:

95% LoA=SD of the difference scores1.96

The LoA indicates that the average daily time spent in 

PA intensity, the body position, or the type of PA obtained from the 2 measurement instruments will differ 

due to measurement error by no more than X average 

daily minutes (for LoA) or X % (for ratio LoA in either 

the positive or negative direction.11 Pearson correlations were performed with IBM SPSS Statistics (V 14.0) 

(IBM Corp, Chicago, IL) for Windows. Bland-Altman 

plots were performed with Microsoft Excel 2007.

RESULTS

 Weak but positive Pearson correlations (association) 

(r=-0.052 to r=0.302) were found between the ActiGraph and PAtracker for average daily time spent in 

sedentary, moderate, and vigorous PA. Alternatively, 

the association was negative and weak for average daily 

time spent in light PA (Table 1). The 95% LoA analyses 

for intensity measurements between the ActiGraph and 

PAtracker were heteroscedastic. The ratio LoA are provided in Table 1.

Weak but positive Pearson correlations (association)

(r=0.033 to r=0.268) were found between the PAtracker 

and daily PA log for body position and type of PA (Table 

2). The 95% LoA analyses for the PAtracker and daily 

PA log for the body positions of standing and running 

were heteroscedastic (Table 2). The 95% LoA analyses 

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Sitting

Hours Minutes

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Running

Hours Minutes

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Load Carried

Hours Minutes

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Walking/Marching

Hours Minutes

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Chores

Barracks Maintenance

Hours Minutes

Standing/Formations

Hours Minutes

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Calisthenics/Obstacle

and Confi dence Courses

Hours Minutes

0

1

2

0

1

2

3

4

5

0

1

2

3

4

5

6

7

8

9

0

1

2

3

4

5

6

7

8

9

Carrying a Load/Pack

Hours Minutes

FIgure 3. Physical Activity Log.
52 http://www.cs.amedd.army.mil/amedd_journal.aspx

for the body positions of walking and sitting were homoscedastic (Table 2). The 

mean bias line (31.7) and random error 

lines (259, -195) forming the 95% limits 

of agreement for sitting are presented in 

Figure 4. The mean bias line (74.0) and 

random error lines (196, -93) forming 

the 95% limits of agreement for walking 

are presented in Figure 5.

COMMENT

To our knowledge, this is the fi rst time 

the physical demands, including PA intensity, body position, and type of PA, of 

US Army BCT have been 

characterized in detail. The 

fi ndings in this study support the use of the ActiGraph as the instrument to 

measure PA intensity and 

the PAtracker and daily PA 

log to measure body position and PA type in the BCT 

environment. To date, no 

single fi eld measure of PA 

has proven valid, reliable, 

and logistically feasible 

over a wide range of population settings and uses.12

Pearson product moment correlations are often used to 

interpret the degree of association between measurement tools, but not the agreement. A high correlation 

may suggest a strong association but does not imply 

close agreement between instruments, and may refl ect 

the possibility of measurement bias.9,10 In this study, 

weak correlations were noted when comparing the use 

of the ActiGraph and PAtracker for measures of PA intensity, and the PA tracker and daily PA log for measures 

of body position and type of PA. These fi ndings suggest 

that the measurement instruments were quantifying the 

intensity of PA, body position, and type of PA in a similar manner and direction. However, the correlations provided no defi nitive conclusions regarding the agreement 

between the measurement instruments for PA intensity, 

body position, and type of PA.

Understanding the intensity of PA during the course 

of BCT is important for assessing its potential role in 

the incidence of musculoskeletal injuries and Soldier 

performance. The LoA method as proposed by Bland 

and Altman9

 was used to assess agreement between the 

ActiGraph accelerometer and PAtracker for measures 

of PA intensity, and between the PAtracker and daily 

PA log for measures of body position and type of PA. 

How far apart the measurements can be without causing diffi culties depends on the interpretation of method 

comparison and the sample size.9,10 The resulting 95% 

LoA indicates that for the measure of intensity, the random error increased as the average daily minutes spent 

in each intensity increased. More specifi cally, there 

was disagreement between the ActiGraph and the PAtracker for all categories of intensity. The accelerometer 

provides an objective measure of movement including 

intensity and has been used as a criterion measure in 

studies validating other PA instruments, such as the 

self-report instruments.4

 The PAtracker also provides 

an objective measure of intensity through direct observation. However, correctly categorizing PA intensity 

through direct observation may be highly dependent on 

the training and experience of the observer and the environment in which the PA is occurring. The PAtracker 

underreported for all categories of intensity except light, 

which was overreported. In this study, the ActiGraph 

accelerometer provided a better measure of PA intensity 

compared to the PAtracker.

Table 1. Comparisons Between the Data Collected by the ActiGraph Accelerometer and PAtracker Regarding Time Spent in Various PA Intensities During 

Army Basic Combat Training.

Measure ActiGraph

Average

Daily Min

PAtracker

Average

Daily Min

Difference

Average

Daily Min

Pearson

Correlation

(r)

Ratio

LoA

PAtrack

Reporting

Sedentary 445±93 393±52 -52 0.302* 81% Underreports

Light 144±73 295±139 150 -0.052 143% Overreports

Moderate 93±25 56±80 -37 0.211* 208% Underreports

Vigorous 37±19 7.1±14 -30 0.077 202% Underreports

Moderately

Vigorous

131±35 63±83 -68 0.282* 163% Underreports

PA indicates physical activity.

LoA indicates limits of agreement.

*P<.01

Table 2. Comparisons Between the Data Collected by PAtracker and the PA log Regarding Daily 

Average Time Spent in Various Body Positions and PA Types During US Army Basic Combat 

Training.

Measure PAtracker

Average

Daily Min

PA Log

Average

Daily Min

Difference

Average

Daily Min

Pearson

Correlation

(r)

95% LoA

(mins/day)

Ratio

LoA

PA Log

Reporting

Stand 432±119 180±57 -252 0.144* 79% Underreports

Sit 255±108 287±66 32 0.186* 227.3 Underreports

Walk 78±69 129±44 51 0.198* 145.0 Underreports

Run 10±13 36±16 26 0.268* 153% Underreports

Menial Chores 212±127 26±14 -186 0.033 209% Underreports

Calisthenics 29±25 59±35 30 0.150* 177% Overreports

Carry Load 755±81 139±66 -674 0.040 65% Underreports

PA indicates physical activity.

LoA indicates limits of agreement.

*P<.01

MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING:

A COMPARISON OF 3 METHODS
 October – December 2013 53

THE ARMY MEDICAL DEPARTMENT JOURNAL

Disagreement was also observed between 

the PAtracker and daily PA log for both 

PA type and body position for some categories. The difference between the observer’s perception and a recruit’s recollection of time spent in various body 

positions and types of PA may have contributed to the lack of agreement between 

these 2 measurement instruments. The 

differences between interpretations of operational defi nitions by an observer and a 

recruit may have also contributed to the 

disagreement. When compared with other 

PA studies that used one instrument alone, 

such as a pedometer for step counts or an 

accelerometer for intensity, the combined 

use of the PAtracker and daily PA log 

added to the characterization of PA in the 

BCT environment.13,14 The use of both of 

these measurement instruments provided 

greater detail regarding the amount of 

time a recruit spent in different body positions and PA types, possible contributing 

factors in the incidence of musculoskeletal 

injuries during BCT.

A careful overview of the strengths and 

limitations of all available techniques is 

essential before an appropriate assessment method for a specifi c research question is chosen.15 The method of choice 

for any environment should be accurate, 

precise, objective, simple to use, robust, 

time-effi cient, cause minimal intrusion 

into habitual activity patterns, be socially 

acceptable, allow continuous and detailed 

recording of usual activity patterns, and 

be applicable to large population groups.16

In this study, the ActiGraph accelerometer 

provided the best measure of a recruit’s PA 

intensity while the PAtracker and daily PA 

log were best at capturing body position 

and type of PA in the BCT environment.

RELEVANCE TO PERFORMANCE TRIAD

The Army Surgeon General’s Performance Triad initiative seeks to improve 

Soldier readiness and resilience by improving Soldiers’ PA, sleep, and nutritional health behaviors. The ability to assess 

the quantity as well as the quality of current PA demands (PA type, body position, 

PA intensity, and load carried), and recovery (rest and sleep) from PA are necessary 

Figure 4. Bland-Altman plots of time spent sitting each day between the PAtracker 

and PALog methods.

Legend:

Mean bias line (31.7)

Random error lines (259, -195)

0 100 200 300 400 500 600

0

100

200

300

400

500

-500

-400

-300

-200

-100

600

Average of the 2 Measurements (min/day)

Difference of the 2 Measurements (min/day)

Figure 5. Bland-Altman plots of time spent walking each day between the PAtracker 

and PALog methods.

Legend:

Mean bias line (74.0)

Random error lines (196, -93)

0 50 100 150 200 250 300

0

100

200

300

-500

-400

-300

-200

-100

Difference of the 2 Measurements (min/day)

Average of the 2 Measurements (min/day)
54 http://www.cs.amedd.army.mil/amedd_journal.aspx

to ensure Soldier safety along with optimal health and 

performance. The fi ndings of this study suggest that in 

order to understand the current demands of PA in BCT, 

it is necessary to use a combination of self-report, direct 

observation, and electronic motion detection measurement instruments.

ACKNOWLEDGEMENT

This study was funded by the US Army Medical 

Research and Materiel Command and the Defense Safety 

Oversight Council.

REFERENCES

1. Butte NF, Ekeland U, Westerterp KR. Assessing 

physical activity using wearable monitors: measures of physical activity. Med Sci Sports Exerc. 

2012;44(1)(suppl 1):S5-S12.

2. Wyss T, Mader U. Recognition of military specifi c PA with body fi xed sensors. Mil Med. 

2010;175(11):858-864.

3. Malina RM, Bouchard C, Bar-Or O. Growth, Maturation, and Physical Activity. 2nd ed. Champaign, 

IL: Human Kinetics. 2004:457-477.

4. Valanou EM, Bamia C, Trichopoulou A. Methodology of physical-activity and energy expenditure assessment: a review. J Public Health. 2006;14:58-65.

5. Jacobs DR, Ainsworth BE, Hartman T, Leon AS. 

A simultaneous evaluation of 10 commonly used 

physical activity questionnaires. Med Sci Sports 

Exerc. 1993;25(1):81-91.

6. Army Regulation 70-25: Use of Volunteers as Subjects of Research. Washington, DC: US Dept of the 

Army; January 25, 1990.

7. Freedson PS, Melanson E, Sirard J. Calibration of 

the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-781.

8. McKenzie TL. Use of direct observation to assess 

physical activity. In: Welk GJ, ed. Physical Activity Assessment for Health-related Research. Champaign, IL: Human Kinetics; 2002:179-195.

9. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical 

measurement. Lancet. 1986;1:307-310.

10. Bland, JM, Altman DG. Applying the right statistics: analyses of measurement studies. Ultrasound 

Obstet Gynecol. 2003;22(1):85-93.

11. Atkinson G, Nevill AM. Statistical methods for 

assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med. 

1998;26(4):217-238.

12. Wood TM. Issues and future directions in assessing physical activity: An introduction to the conference proceedings. Res Q Exerc Sport. 2000;71:ii-vii.

13. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin 

R, Jones BH. Ambulatory physical activity during 

United States Army basic combat training. Int J 

Sports Med. 2007;28(2):106-115.

14. Knapik JJ, Hauret KG, Canada S, Marin R, Jones B. 

Association between ambulatory physical activity 

and injuries during United States Army basic combat training. J Phys Act Health. 2011;8(4):496-502.

15. Vanhees L, Lefevre J, Philippaerts R, Martens M, 

Huygens W, Troosters T, Beunen G. How to assess 

physical activity? How to assess physical fi tness?. 

Eur J Cardiovasc Prev Rehabil. 2005;12(2):102-114.

16. Livingstone MB, Robson PJ, Wallace JM, McKinley M. How active are we? Levels of routine physical activity in children and adults. Proc Nutr Soc. 

2003;62(3):681-701.

AUTHORS

Dr Redmond, Dr Cohen, Ms Simpson, and Ms Sharp are 

in the Military Performance Division of the US Army 

Research Institute for Environmental Medicine, Natick, 

Massachusetts.

Dr Spiering is a Senior Physiologist for the Nike Sport 

Research Lab, Beaverton, Oregon.

MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING:

A COMPARISON OF 3 METHODS

Articles published in the Army Medical Department Journal are indexed in MEDLINE, the 

National Library of Medicine’s (NLM’s) bibliographic database of life sciences and biomedical 

information. Inclusion in the MEDLINE database ensures that citations to AMEDD Journal

content will be identifi ed to researchers during searches for relevant information using any of 

several bibliographic search tools, including the NLM’s PubMed service.
 October – December 2013 55

Army Basic Combat Training (BCT) is a physically demanding, 10-week training program designed to develop 

basic soldiering skills and prepare recruits for the physical and mental rigors of military service.1-3 Depending 

on their military occupational specialty, Soldiers may be 

required to perform a number of tasks involving a high 

degree of physical effort during their military careers. 

Therefore, developing and maintaining a high level of 

physical fi tness among Soldiers is often regarded as a 

priority by the US Army.2

While BCT is designed to enhance the physical fi tness 

and military performance of the recruit, it also has the 

potential to produce less positive outcomes. To improve 

physical fi tness, the physical activity (PA) performed 

by recruits must be of the appropriate frequency, intensity, and duration.2,4 If the volume of physical training 

is too low, it results in little or no change in physical 

performance, but if the volume is too high, it can lead 

to injury.2

 Previous studies show that as the amount of 

physical training increases, so does the risk of injuries in 

a number of populations, including runners,5-12 military 

recruits,3,13,14 and participants in sports and other leisuretime activities.15,16 Injury among recruits poses a problem 

for the military in that it can result in signifi cant medical 

expenses, decrease the number of deployable Soldiers, 

and ultimately compromise military readiness.2,17,18

To improve the physical fi tness of Soldiers while also 

reducing the risk of injury, the Army Physical Fitness 

School, working with the Army Institute of Public 

Health, developed a training program known as Physical Readiness Training (PRT).2

 The PRT program is a 

precise series of calisthenics, dumbbell drills, climbing 

drills, running, and other activities that are performed by 

recruits 3-6 times per week, typically between 5 AM and 

7 AM.

2

 One of the major principles of PRT is that exercise intensity should increase progressively over time by 

increasing the number of repetitions of some exercises 

and/or the speed at which some exercises are performed 

 Quantification of Physical Activity Performed

 During US Army Basic Combat Training

Kathleen Simpson, MS Barry A. Spiering, PhD

Jan E. Redmond, PhD Ryan Steelman, MS

Bruce S. Cohen, PhD Joseph J. Knapik, ScD

Nathan R. Hendrickson, MS Marilyn A. Sharp, MS

ABSTRACT

Purpose: During US Army Basic Combat Training (BCT), graduation requirements, including physical readiness training (PRT), are standardized across training sites. However, there are concerns that the standardization may not be closely followed. Therefore, the purpose of this study was to measure and compare physical 

activity (PA) performed by recruits at 2 Army BCT sites. 

Methods: Twenty-four recruits per company from 11 companies (n=144 at Fort Jackson, SC; n=120 at Fort Sill, 

OK) wore an accelerometer and completed a daily PA log. The PA of one recruit from each company was recorded using an Army-developed direct observation tool (PAtracker). Amounts of time spent in various activity 

types, intensities, body positions, and in carrying external loads were obtained from the accelerometer, PA log, 

and PAtracker. Independent samples t tests were used to compare PA percentage time (%T) across training 

sites. Repeated measures analysis of variance was used to examine weekly differences in time spent in moderate to vigorous intensity PA during morning PRT. 

Results: Physical activity was measured for 47 days at Fort Jackson and 44 days at Fort Sill. Differences in the 

percentage of time spent in various physical activities between the 2 sites ranged from 0.4% to 15.3% (2.0-93.7 

minutes). At Fort Jackson, time spent in moderate to vigorous PA during PRT signifi cantly increased each week 

for the fi rst 4 to 6 weeks of BCT. No difference was observed in PAtracker data between the 2 training sites 

in the percentage of time recruits spent in calisthenics (3.9%±3.6% vs 3.8%±3.0%, P=.700), and only a small 

difference was observed in percentage of time recruits spent running (1.2%±1.7% vs 1.6%±2.0%, P=.037).

Conclusion: Army recruits at the 2 BCT sites spent similar amounts of time in each PA variable, regardless of 

the training site and measurement method.
56 http://www.cs.amedd.army.mil/amedd_journal.aspx

(progressive overload). Compared to traditional BCT 

physical training programs, PRT has been shown to result in the same or greater improvements in physical fi tness while causing fewer injuries.2,19 In addition to PRT, 

BCT recruits are also required to perform other physical activities such as obstacle course negotiation, rifl e 

training, unarmed combat (combatives) training, drill 

and ceremony, land navigation, and road marches with 

rucksacks and other load-bearing equipment.1,3

Although knowledge of the types of activities performed 

is available, information regarding the exposure of new 

recruits to PA (ie, the actual dose) at each of the 4 BCT 

sites is lacking. Additionally, although the graduation 

requirements of BCT are identical across training sites, 

battalions, and companies,20 the amount of time needed 

to teach specifi c soldiering skills may vary. Finally, although doctrine requires that PRT and training for military skill development be standardized across BCT sites, 

there are concerns that the standardization may not be 

closely followed. Therefore, the purposes of this study 

were to (1) characterize and quantify the amount of PA 

actually performed by recruits during a BCT cycle at 

2 of the Army’s 4 BCT sites, and (2) determine the intensity and types of physical training at the 2 locations. 

One of the principles of PRT is progressive overload 

(progressive, systematic increase in exercise intensity 

over days), so the average weekly intensity of physical 

training between 5 AM and 7 AM (when physical training 

was likely to be conducted) was examined.

METHODS

Subjects

Data for this study were collected from recruits in 2 

training battalions during separate 10-week BCT cycles. 

The fi rst iteration took place June to August 2010 at Fort 

Jackson, South Carolina, during which time recruits 

from 6 training companies were observed. The second 

iteration took place July to September 2011 at Fort Sill, 

Oklahoma, during which time recruits from 5 training 

companies were observed. 

Prior to the start of the study, the principal investigator informed the recruits in all training companies of 

the requirements and potential risks of participating in 

the study. Those who chose to volunteer signed an informed consent document approved by the Institutional 

Review Board of the US Army Research Institute of Environmental Medicine (USARIEM). The investigators 

followed the policies for protection of human subjects 

as prescribed in Army Regulation 70-25,

21 as well as the 

provisions of 45 CFR Part 46, Protection of Human Subjects.22 Recruits were included in the study if they were 

at least 18 years of age, were assigned to one of the study 

battalions for the 10-week BCT course, and were able to 

fully participate in all the activities of BCT at the start 

of the investigation. 

Procedures

The length of a typical BCT cycle is 10 weeks. In this 

study, study personnel spent the fi rst week of each BCT 

cycle recruiting volunteers and obtaining their consent. 

During the last week, recruits spent most of their time 

cleaning and turning in equipment, and practicing for 

graduation. Therefore, complete data was obtained for 

the majority of volunteers for the middle 8 weeks of 

their BCT cycle.

Physical activity was assessed by 3 methods: instrumentation with an accelerometer, direct observation, and 

daily PA logs.

Accelerometer

The accelerometer used in this study was the ActiGraph 

GT3X triaxial accelerometer (ActiGraph, LLC, Pensacola, FL). The accelerometer senses acceleration along 3 

axes: vertical, anterior-posterior, and mediolateral. The 

accelerometer output is then recorded in “counts,” which 

are the summation of the absolute values of the sampled 

changes in acceleration measured during a user-defi ned 

time period. The accelerometer has previously been 

shown to be a valid and reliable tool for measuring PA 

intensity among adults.23,24

At the beginning of each BCT cycle, recruits received 

both written and verbal instructions on how to wear the 

accelerometer: over their left hip in a pouch on a belt, 

Monday through Saturday, during most of the BCT cycle. Since Sundays were typically reserved for religious 

observance and rest rather than training, recruits were 

not asked to wear the accelerometer on this day. If a 

recruit who had been selected to wear the accelerometer 

became injured, ill, or was separated from the platoon 

for a portion of the day (Monday–Saturday), that recruit 

was replaced with another from the same training company. Research staff performed compliance checks to 

ensure all volunteers wore the devices properly.

Research staff distributed the accelerometers to participants before the fi rst formation each morning and collected them near the end of training each day, usually 

preceding the evening meal. This allowed for equipment 

accountability, data downloading, and battery recharge. 

From the accelerometers, daily time (minutes) each recruit spent in sedentary-, light- (<3metabolic equivalent 

(MET)), moderate- (3-6 MET), and vigorous-intensity 

(>6 MET) activities was categorized by means of the 

 QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED

DURING US ARMY BASIC COMBAT TRAINING
 October – December 2013 57

THE ARMY MEDICAL DEPARTMENT JOURNAL

Freedson categories, which defi ne sedentary or light-intensity activity as 0 to 1,951 counts/minute, moderate PA 

as 1,952 to 5,724 counts/minute, and vigorous intensity 

PA as 5,725 or more counts/minute.25

Direct Observation

The direct observation portion of this study employed 

the continuous duration recording method. Trained observers recorded changes in a recruit’s PA as the change 

in activity occurred.24 A novel PA tracking software 

(PAtracker), designed specifi cally for this type of direct 

observation and developed jointly by L3-Communications (San Diego, CA) and the USARIEM, was used 

in this study. The PAtracker software was installed on 

smartphone devices. Trained observers logged a recruit’s PA by selecting it from a predetermined menu 

on a touch-sensitive screen. The software automatically 

added a time stamp and recorded the data in each activity to a data fi le.

Within the PAtracker software, PA was coded by body 

position, intensity, activity type, and external load. Body 

positions included kneeling, lying, sitting, and standing. 

Activity types included stationary, menial tasks, walking, calisthenics, cadence marching, combatives, running, obstacles/climbing, crawling, and lifting/carrying. 

Physical activity was also classifi ed by intensity (sedentary, light, moderate, vigorous) and load carried (0-10 

lbs, 10-25 lbs, 25-50 lbs, 50-75 lbs, or >75 lbs). 

Observers recruited from the local BCT geographic area 

were hired to perform the direct observation portion of 

this study. Prior to the start of the study, all observers 

completed training (10 hours over 3 consecutive days) 

on the use of the PAtracker device as well as the body 

positions, activity types, loads, and intensities they 

would observe during the study. 

Direct observation commenced at the beginning of each 

training day when recruits received their accelerometers, and all activities during the day were recorded. 

Within each company, a single recruit who was wearing an accelerometer was followed and observed by one 

trained observer. If this recruit was not training that day, 

another recruit wearing an accelerometer was identifi ed 

and followed. Although individual recruits in each company were observed, the direct observation data were 

treated as unit data refl ective of the PA performed by the 

entire company. 

Daily Physical Activity Log

At the end of each training day, all recruits wearing 

an accelerometer completed a daily PA log; they were 

asked to report the amount of time (hours:minutes) 

they spent wearing the accelerometer that day as well 

as the amount of time (hours:minutes) they spent sleeping during the night before. Regarding the time spent 

wearing the accelerometer that day, recruits were asked 

to account for how much of that time they spent sitting, standing, walking/marching, and running. Finally, 

recruits were asked to report the amount of time they 

spent doing chores or barracks maintenance, doing calisthenics/obstacle courses, and carrying a load. Upon 

the recruit’s completion of the PA log, a study investigator checked the questionnaire to ensure it had been 

completed properly and then clarifi ed any discrepancies 

by speaking with the recruit.

Statistical Analyses

Descriptive statistics (mean ± SD) were calculated for 

all study variables. Independent sample t-tests were performed to examine differences between training sites in 

PA measured by the accelerometer, direct observation, 

and self-report PA Logs. Repeated measures analysis 

of variance was used to examine weekly differences in 

time spent in moderate- to vigorous-intensity PA measured by the accelerometer while recruits performed 

PRT at each training site (between 5 AM and 7 AM). All 

statistical analyses were performed with IBM SPSS Statistics (V 14.0) software (IBM Corp, Chicago, IL) for 

Windows with P <.05 established as the level of statistical signifi cance.

RESULTS

Within each of the 11 training companies included in 

this study, 24 recruits were outfi tted with an accelerometer and completed a daily PA log. This resulted in 

a total of 144 recruits at Fort Jackson and 120 recruits 

at Fort Sill. From each company, 6 recruits from each 

of 4 platoons totaled 24 recruits from each company (6 

recruits/platoon×4 platoons/company=24 recruits/company). When possible, at least one of the 6 recruits from 

each platoon was a woman.

Accelerometer

The Fort Jackson recruits wore the accelerometer a total of 47 days, and the recruits at Fort Sill wore it 44 

days. Table 1 lists the cumulative time as well as the 

number of days that recruits from both training sites 

spent in each intensity category measured by the accelerometer. On average, recruits at Fort Jackson wore 

the accelerometer for a longer period of time each day 

than the recruits at Fort Sill (754.0 ± 112.6 minutes/day 

vs 677.4 ± 102.6 minutes/day, P <.001). Therefore, all accelerometer comparisons between the two training sites 

in this study were made using the average daily percentage of time. The exception was time spent in moderateto vigorous-intensity PA between 5 AM and 7 AM, which 
58 http://www.cs.amedd.army.mil/amedd_journal.aspx

was examined using average daily minutes. 

 This variable was an exception because weekly 

changes were examined 

at each training site as 

opposed to being compared between the 2 

training sites. 

Figure 1 shows the average daily percentage of 

time that recruits from 

each training site spent in each activity intensity over 

the course of the BCT cycle. Recruits at Fort Jackson 

spent a larger percentage of their time engaged in lightintensity activities (23.0% ± 10.4% vs 15.8% ± 2.0%, 

P<.001) and a smaller percentage of their time in sedentary activities (58.9% ± 10.6% vs 65.9% ± 4.9%, P<.001) 

when compared to recruits at Fort Sill. Additionally, recruits at both training sites spent most of their time (60% 

to 70%) in sedentary activities and less time (<10%) in 

vigorous activities. 

Figure 2 shows the average daily percentage of time that 

recruits at both training sites spent in moderate- to vigorous-intensity activity between 5AM and 7AM, when recruits were likely participating in PRT. Over the course 

of BCT, recruits at Fort Jackson spent an average of 

46.1 ± 4.9 minutes/day while recruits at Fort Sill spent an 

average of 44.4 ± 3.8 minutes/day participating in moderate- to vigorous-intensity PA between 5AM and 7AM

(P=.443). Repeated measures analysis of variance indicated that time spent in moderate- to vigorous-intensity 

PA changed week to week at Fort Jackson (P=.009) but 

did not signifi cantly change week to week at Fort Sill 

(P=.211). 

PAtracker

Table 2 shows the number of days trained observers 

followed and observed recruits using the PAtracker. 

Table 2 also lists the average daily time recruits from 

both training sites spent in each body position, activity type, intensity, and carrying various external loads, 

as measured with the PAtracker. Recruits were followed with the PAtracker an average of 783.4 ± 135.3 minutes/day 

for 47 days at Fort Jackson and 

708.9 ± 128.5 minutes/day for 44 

days at Fort Sill (P<.001). As was 

the case with the accelerometer, 

the recruits at Fort Jackson were 

observed with the PAtracker for 

a longer period of time each day 

than were the recruits at Fort Sill. 

Therefore, all PAtracker comparisons between the 2 training sites 

in this study were made using the 

average daily percentage of time.

The average daily percentage of 

time recruits at Fort Jackson and 

Fort Sill spent in each body position is shown in Figure 3A. Recruits at Fort Jackson spent a 

larger percentage of time sitting 

(38.6% ± 12.9% vs 30.9% ± 11.8%, 

P<.001) and a smaller percentage 

of time kneeling (1.2% ± 1.8% vs 

1.9% ± 2.6%, P<.001) and standing 

 QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED

DURING US ARMY BASIC COMBAT TRAINING

Table 1. Cumulative time recruits at both training sites spent in each Activity Intensity category 

measured by the ActiGraph during a Basic Combat Training cycle. Days represent the total number 

of days recruits spent in an intensity at least once.

Fort Jackson Fort Sill

Days Recorded 47 44

Total Time Recorded

(minutes/hours) 28,256.2±1,458.5/5470.9±24.3 29,597.6±596.2/493.3±9.9

Days Time (minutes) Time (hours) Days Time (minutes) Time (hours)

Sedentary 47 20,847.5±702.7 347.5±11.7 44 19,667.7±1,558.6 327.8±26.0

Light 47 8,193.6±512.8 136.6±8.5 44 4,687.6±217.3 78.1±3.6

Moderate 47 4,799.5±360.8 80.0±6.0 44 3,624.3±357.6 60.4±6.0

Vigorous 47 1,602.0±313.2 26.7±5.2 44 1,827.4±207.9 30.5±3.5

80%

70%

60%

50%

40%

30%

20%

10%

0%

Fort Jackson

Fort Sill

Sedentary* Light* Moderate Vigorous

Average Daily Percentage of Time

Activity Intensity

Figure 1. Average daily percentage of time (±SD) recruits spent in each activity intensity 

measured with the accelerometer.

*Fort Jackson vs Fort Sill: P<.05
 October – December 2013 59

THE ARMY MEDICAL DEPARTMENT JOURNAL

(57.0% ± 12.6% vs 64.0% ± 12.2%, 

P<.001) compared with recruits 

at Fort Sill. Little difference was 

observed in the percentage of 

time recruits at both training sites 

spent lying down (2.9% ± 3.4% vs 

3.1% ± 2.1%, P=.951). 

Figure 3B shows the average daily percentage of time recruits at 

Fort Jackson and Fort Sill spent 

in each activity intensity category. 

Recruits at Fort Jackson spent a 

larger percentage of time sedentary 

(54.5% ± 18.1% vs 48.2% ± 22.6%, 

P=.001) and a smaller percentage 

of time in light-intensity activities 

(36.5% ± 15.5% vs 44.1% ± 21.8%, 

P<.001) when compared to recruits 

at Fort Sill. Little difference was 

observed between the 2 training 

sites in terms of percentage of time 

spent in moderate- (8.0% ± 11.9% 

vs 6.8% ± 7.3%, P=.193) or vigorous- (1.1% ± 2.3% vs 0.9% ± 1.9%, 

P=.290) intensity activities. As 

was the case with the accelerometer, recruits at both training sites 

spent a large percentage of time 

(about 50%) in sedentary activities and a small percentage of time (about 1%) in vigorous-intensity activities.

Figure 4 shows the average daily percentage of time 

recruits at both Fort Jackson and Fort Sill spent in 

different types of activities. Recruits at Fort Jackson 

spent a larger percentage of time engaging in combatives (1.6% ± 4.0% vs 0.4% ± 2.0%, P<.001), being 

stationary (55.1% ± 14.3% vs 41.8% ± 16.8%, P<.001), 

and walking (11.6% ± 8.5% vs 8.6% ± 9.7%, P<.001), 

and a smaller percentage of time cadence-marching 

(3.3% ± 3.3% vs 4.7% ± 4.0%, P<.001), completing 

obstacles (0.5% ± 2.1% vs 1.1% ± 4.0%, P=.030), performing menial tasks (22.3% ± 15.0% vs 37.6% ± 17.9%, 

P<.001), and running (1.2% ± 1.7% vs 1.6% ± 2.0%, 

P=.037) when compared to recruits at Fort Sill. Little 

difference was observed between the 2 training sites 

in terms of percentage of time recruits spent in calisthenics (3.9% ± 3.6% vs 3.8% ± 3.0%, P=.700), crawling 

(0.2% ± 1.1% vs 0.1% ± 0.3%, P=.102), and lifting/carrying (0.2% ± 0.9% vs 0.3% ± 0.8%, P=.097).

The average daily percentage of time recruits at both 

training sites spent carrying various external loads over 

the course of a BCT cycle is shown in Figure 5. Recruits 

at Fort Jackson spent a larger percentage of time carrying 0-10 lbs (84.0% ± 19.0% vs 79.6% ± 19.7%, P=.011) 

and a smaller percentage of time carrying 25-50 lbs 

(3.5% ± 7.5% vs 9.7% ± 13.6%, P<.001) and 50-75 lbs 

(0.2% ± 1.2% vs 1.0% ± 3.2%, P<.001). Little difference 

was observed between the two training sites in terms 

of percentage of time recruits spent carrying 10-25 lbs 

(12.2% ± 16.6% vs 9.6% ± 14.8%, P=.066) or greater 

than 75 lbs (0.1% ± 0.3% vs 0.2% ± 1.3%, P=.064). Recruits at both training sites spent a large percentage of 

time (about 80%) carrying 0-10 lbs and a very small percentage of time (≤1%) carrying over 50 lbs.

Physical Activity Log

Table 3 lists the cumulative time (hours and minutes) 

recruits from both training sites reported sitting, standing, walking, running, participating in calisthenics, doing chores, and carrying loads, based on their daily PA 

logs. Recruits at Fort Jackson accounted for an average 

of 601.1 ± 52.5 minutes/day for 47 days, while recruits 

at Fort Sill accounted for an average of 672.7 ± 28.3 

minutes/day for 44 days (P<.001). Recruits at Fort Sill 

accounted for a longer period of time each day than recruits at Fort Jackson did. Therefore, all PA Log comparisons between the 2 training sites in this study were 

Average Time (minutes) During PRT

Training Week

70

75

60

65

50

55

40

45

30

35

20

25

15

10 2 9 3 4 5 6 7 8

Fort Jackson

Fort Sill

Figure 2. Average time (mean±SD) by training week that recruits spent in moderate to 

vigorous intensity physical activity between 5 AM and 7 AM as measured with accelerometers.
60 http://www.cs.amedd.army.mil/amedd_journal.aspx

made using the average daily percentage of time, with 

the exception of time spent sleeping each night. 

The average daily percentage of time recruits from 

both training sites reported sitting, standing, walking, and running is shown in Figure 6. Recruits at Fort 

Jackson reported spending a larger percentage of time 

sitting (48.7% ± 13.6% vs 42.2% ± 5.7%, P<.001) and 

walking (21.8% ± 8.7% vs 18.5% ± 2.7%, P<.001), and 

a smaller percentage of time standing (24.0% ± 7.3% 

vs 33.5% ± 4.8%, P<.001) and running (5.4% ± 3.2% vs 

5.9% ± 1.5%, P=.034) than recruits at Fort Sill. 

Over the course of BCT, recruits at Fort Jackson reported spending less time sleeping each night than recruits 

at Fort Sill (364.7 ± 41.1 minutes/night vs 376.6 ± 17.5 

minutes/night, P<.001). Recruits at Fort Jackson also 

reported spending a larger percentage of time doing 

chores (4.5% ± 2.8% vs 3.8% ± 1.3%, P=.002), performing calisthenics (10.0% ± 7.7% vs 8.6% ± 2.5%, P=.006) 

and carrying loads (16.9% ± 12.8% vs 7.9% ± 2.4%, 

P<.001) than recruits at Fort Sill.

COMMENT

To the best of our knowledge, this study was the fi rst 

to characterize and quantify the amount of PA recruits 

actually perform during BCT conducted at 2 different 

training sites. The results of this study revealed that although there were some differences between the 2 sites 

in terms of the PA performed, these differences were 

 QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED

DURING US ARMY BASIC COMBAT TRAINING

Table 2. Cumulative time recruits at both training sites spent in each body position, activity type, activity intensity, and carrying each external load, as measured by the PAtracker during a Basic Combat 

Training cycle. Days represent the total number of days recruits participated in each body position, 

activity type and intensity, and carried each load at least once.

Fort Jackson Fort Sill

Days Observed 47 44

Time Observed

(minutes/hours) 36,463.2±8,444.3/607.7±140.7 30,367.2±8,884.3/506.1±148.1

Days Time (minutes) Time (hours) Days Time (minutes) Time (hours)

Body Position

Kneeling 34 409.2±172.7 6.8±2.9 37 602.5±252.2 10.0±4.2

Lying 37 1,071.8±284.0 17.9±4.7 37 943.0±184.9 15.7±3.1

Sitting 47 13,187.2±1,193.8 219.8±19.9 44 9,374.1±1,056.5 156.2±17.6

Standing/On Feet 47 19,216.3±476.2 320.3±7.9 44 19,447.6±1,752.5 324.1±29.2

Varying 41 2,578.6±344.2 43.0±5.7 NA NA NA

Activity Type

Cadence March 39 1,195.6±325.0 19.9±5.4 40 1,414.6±210.3 23.6±3.5

Calisthenics 38 1,391.9±146.6 23.2±2.4 39 1128.4±46.5 18.8±0.8

Combatives 12 559.6±155.3 9.3±2.6 4 113.5±75.9 1.9±1.3

Crawl 7 63.4±75.2 1.1±1.3 5 16.5±7.2 0.3±0.1

Lifting/Carrying 12 71.1±50.4 1.2±0.8 13 97.8±62.8 1.6±1.0

Menial Tasks 47 7925.0±495.2 132.1±8.3 44 11,335.9±2,180.3 188.9±36.3

Obstacle/Climbing 7 181.0±55.7 3.0±0.9 8 302.4±38.8 5.0±0.6

Run 33 427.7±91.1 7.1±1.5 31 479.7±58.8 8.0±1.0

Stationary 47 20,402.9±1,510.9 340.0±25.2 44 12,871.7±2,922.4 214.5±48.7

Walk 47 4,244.9±720.9 70.7±12.0 44 2,606.8±435.2 43.4±7.3

Intensity

Sedentary 47 19,995.7±2902.8 333.3±48.4 44 14,604.6±3,835.6 243.4±63.9

Light 47 13,126.8±1325.2 218.8±22.1 44 13,506.0±3,380.0 225.1±56.3

Moderate 44 2,975.9±1333.2 49.6±22.2 40 2,018.7±238.1 33.6±4.0

Vigorous 25 360.6±105.0 6.0±1.7 18 238.0±151.3 4.0±2.5

External Load

0-10 lbs 47 30,533.1±2282.2 508.9±38.0 44 24,323.4±859.1 405.4±14.3

10-25 lbs 36 4,585.4±1461.4 76.4±24.4 28 2,869.6±1,416.3 47.8±23.6

25-50 lbs 19 1,266.6±588.3 21.1±9.8 30 2,796.2±628.6 46.6±10.5

50-75 lbs 4 70.0±57.0 1.2±0.9 7 322.1±226.8 5.4±3.8

>75 lbs 3 8.0±11.2 0.1±0.2 4 55.9±68.3 0.9±1.1
 October – December 2013 61

THE ARMY MEDICAL DEPARTMENT JOURNAL

small, for the most part, and likely have little practical 

importance. Furthermore, it appeared that the intensity 

and types of PA were similar at the 2 sites. 

Quantification of Physical Activity

The major purpose of this study was to characterize 

and quantify the PA performed by recruits during the 

middle 8 weeks of BCT and determine whether or not 

there were differences in PA between the training sites. 

The PA performed by recruits was characterized and 

quantifi ed using accelerometry, direct observation, and 

daily PA logs. Despite 

statistical signifi cance, 

the differences in PA 

observed between the 

2 BCT sites were small. 

The magnitude of the 

differences between 

sites can be appreciated by examining the 

range of differences 

(lowest and highest) 

in the amount of time 

recruits spent in various physical activities. 

From the accelerometer, the lowest difference was 7% (3.4 

minutes) for sedentary 

activities, and the highest difference was 7.2% (67.8 

minutes) for light-intensity activities. From the PAtracker, the lowest difference between the 2 training sites was 

0.4% (2 minutes) for running, and the highest difference 

was 15.3% (93.7 minutes) for menial tasks. From the PA 

log, the lowest difference between the 2 training sites 

was 0.5% (7.2 minutes) for running and 9.0% (50.3 minutes) for carrying loads. This result suggests that Army 

BCT recruits spent similar amounts of time in each PA 

intensity, activity type, body position, and carrying various external loads at the 2 locations tested. Whether or 

Standing* Sitting* Lying Kneeling*

80%

70%

60%

50%

40%

30%

20%

10%

0%

Fort Jackson

Fort Sill

Average Daily Percentage of Time

Body Position

Sedentary* Light* Moderate Vigorous

80%

70%

60%

50%

40%

30%

20%

10%

0%

Fort Jackson

Fort Sill

Average Daily Percentage of Time

Intensity

Figure 3. Average daily percentage of time that recruits spent in various body positions (A) and intensities of physical activity (B) 

as measured with the PAtracker.

*Fort Jackson vs Fort Sill: P<.05

A B

Table 3. Cumulative time (mean±SD) recruits at both training sites spent in various physical activities, as reported on the daily PA logs during a Basic Combat Training cycle. Days represent the total 

number of days recruits participated in each variable at least once.

Fort Jackson Fort Sill

Days Self-reported 47 44

Time Self-reported

(minutes/hours) 28256.2±1458.5 / 470.9±24.3 29597.6±596.2 / 493.3±9.9

Days Time (minutes) Time (hours) Days Time (minutes) Time (hours)

Sit 47 13,672.7±1,620.9 227.9±27.0 44 12,430.8±1,296.4 207.2±21.6

Stand 47 6,848.0±743.8 114.1±12.4 44 9,907.6±1,233.9 165.1±20.6

Walk/March 47 6,204.5±1,204.6 103.4±20.1 44 5,506.4±392.2 91.8±6.5

Run 47 1,531.0±263.6 25.5±4.4 44 1,752.8±238.9 29.2±4.0

Sleeping 47 17,140.7±985.7 285.7±16.4 44 16,569.4±567.7 276.2±9.5

Chores/Maintenance 43 1,256.7±323.4 20.9±5.4 44 1,135.4±321.5 18.9±5.4

Calisthenics/Obstacle 

Course 45 2,795.5±669.0 46.6±11.2 44 2,532.8±473.7 42.2±7.9

Carrying Load 46 4,857.8±1,738.4 81.0±29.0 44 2,336.0±289.2 38.9±4.8
62 http://www.cs.amedd.army.mil/amedd_journal.aspx

not this result applies to all BCT sites will need to be 

determined with future studies.

In terms of intensity, the results of this study were the 

same regardless of the technique used to measure PA 

intensity (for example, accelerometer or direct observation). 

Recruits at both training sites 

spent a very large percentage of 

time sedentary (about 80%) and 

a very small percentage of time 

in vigorous-intensity activities 

(about 5%). Between the training sites, there was little difference in the percentage of time 

recruits spent in moderate- or 

vigorous-intensity PA. These 

results further support the idea 

that the intensity of PA at each 

training site was similar. 

External loads carried by recruits were obtained from direct 

observation (PAtracker). Recruits from both training sites 

spent a very large percentage 

of time (roughly 80%) either 

unloaded or carrying very light 

loads (0-10 lbs) and a very small 

percentage of time carrying loads weighing over 50 lbs 

(1%-2%). During their military service, Soldiers may be 

expected to carry extremely heavy loads for long distances over various types of terrain.27 Current US Army 

doctrine recommends that Soldiers carry no more than 

 QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED

DURING US ARMY BASIC COMBAT TRAINING

Average Daily Percentage of Time

Activity Type

Calisthentics* Combatives*

Stationary* Menial Crawl

Tasks* Cadence* Obstacles/

Climbing*

Lift/

Carry

Walk* Run*

80%

70%

60%

50%

40%

30%

20%

10%

0%

Fort Jackson

Fort Sill

Figure 4. Average daily percentage of time that recruits spent in various activity types as measure with the PAtracker.

*Fort Jackson vs Fort Sill: P<.05

External Load

Fort Jackson

Fort Sill

80%

100%

120%

40%

20%

0%

60%

0-10 lbs* >75 lbs 10-25 lbs 25-50 lbs* 50-75 lbs*

Average Daily Percentage of Time

Figure 5. Average daily percentage of time that recruits spent in various activity types 

as measured with the PAtracker.

*Fort Jackson vs Fort Sill: P<.05
 October – December 2013 63

THE ARMY MEDICAL DEPARTMENT JOURNAL

48-72 lbs (or 30%-45% of their body weight) in the fi ghting load and approach march loads, respectively.28,29 Recruits at both training sites had some training in heavy 

loads, providing further evidence that the PA performed 

at each training site was similar. 

Using the daily PA log, recruits from both training sites 

reported getting an average of about 6 hours of sleep each 

night. Current Army doctrine mandates that recruits 

be given the opportunity to receive 7 hours of continuous sleep each night while in garrison unless they are 

scheduled for duty.20 The results of this study suggest 

that although they may be allowed the full 7 hours, BCT 

recruits at both training sites reported getting slightly 

less than the recommended amount of sleep. Additionally, the self-reported amount of sleep in this study is 

similar to the results of a previously published study in 

which US Military Academy cadets reported receiving 

an average of 5 hours and 40 minutes of sleep per night 

during the 6 weeks of cadet basic training.30 The current 

study’s fi ndings indicate that recruits received the same, 

or similar, amounts of recovery time regardless of the 

training site to which they were assigned. 

Physical Training Intensity and Type

The second purpose of this study was to examine the intensity and types of physical training over the course of 

BCT. Intensity was examined to determine whether the 

principle of progressive training (progressive overload), 

one of the major principles of PRT, was being followed.31

The PRT program consists of a variety of standardized 

exercises (such as preparatory drills, conditioning drills, 

movement drills, climbing drills, interval running, long 

distance running, and fl exibility training) and is designed to progressively train Soldiers while reducing the 

risk of developing injuries.2,19

The results of this study show time spent in moderate- to 

vigorous-intensity PA between 5AM and 7AM (when recruits were presumably engaged in PRT) tended to increase during the fi rst 4 weeks of BCT at Fort Jackson 

(Figure 2). Although there was no signifi cant difference 

in the weekly moderate- to vigorous-intensity activity at 

Fort Sill, the graph does show a gradual increase, the 

slope of which is much lower than that shown for Fort 

Jackson. This suggests some increase in exercise intensity but perhaps not enough to be consistent with the progressive overload principle. After week 4 (Fort Jackson) 

or week 7 (Fort Sill), the amount of time recruits spent 

in moderate- to vigorous-intensity PA from 5 AM to 7 AM

at both training sites tended to decrease. This decrease 

could be related to increased time spent in military operations (road marching, basic rifl e marksmanship, land 

navigation, fi eld training exercises, etc). When physically demanding activity was scheduled, physical training 

was either reduced or was not conducted at all in the early morning. The more physically demanding operational 

soldiering tasks are generally conducted later in training.

Over the course of the 8-week BCT monitoring period, 

the average daily percentage of time recruits spent engaging in calisthenics was not signifi cantly different between the training sites. The average daily time spent 

running differed slightly; however, this difference was 

not large. Although we cannot determine from these 

data if the specifi c drills of PRT were followed, it appears that the amount of time spent in these general activities was similar at the 2 sites. 

Strengths and Limitations

This study was limited by the fact that recruits were 

only observed during the middle 8 weeks of training 

as opposed to the entire 10 weeks. Eliminated were 

the fi rst week of BCT, which consists mostly of classroom training; and the fi nal week, consisting primarily of cleaning equipment, completing paperwork, and 

preparing for graduation. We also did not monitor the 

evening activities of the recruits (after the evening meal, 

generally after 1800). Thus, we missed some of the activities performed by recruits, but previous observations 

suggested that there was little PA taking place in the 

evening hours.1,3

Fort Jackson

Fort Sill

50%

30%

40%

20%

60%

70%

10%

0%

80%

Sit* Stand* Walk* Run*

Average Daily Percentage of Time

Figure 6. Average daily percentage of time that recruits spent 

sitting, standing, walking, and running as reported in the

daily PA logs.

*Fort Jackson vs Fort Sill: P<.05
64 http://www.cs.amedd.army.mil/amedd_journal.aspx

Due to limited personnel and resources, we were unable 

to instrument and observe all recruits in each training 

company. Therefore, the PA performed by the 24 recruits per company who were instrumented with an accelerometer and the 1 recruit per company who was followed and observed using the PAtracker was assumed to 

be representative of the PA performed by all recruits in 

each respective company. 

If a recruit wearing an accelerometer or being observed 

using the PAtracker was sick, injured, or not training 

with his or her company that day for any reason, that 

recruit was immediately replaced with another consented volunteer. Due to study design, a limitation to this 

process was the number of times recruits had to be replaced, which was not tracked. However, since recruits 

were immediately replaced, the appropriate number of 

accelerometers was always distributed, and one recruit 

per company was observed. Therefore, data was never 

lost due to attrition. 

This study also used multiple methods of measuring 

PA, including accelerometry, direct observation, and 

self-report questionnaires, all of which allowed study 

investigators to capture a good quality representation of 

the PA actually performed by recruits during BCT. Additionally, the standardization of activities during BCT 

enabled investigators to ensure that recruits fi lled out 

the daily PA log each day.

RELEVANCE TO PERFORMANCE TRIAD

The Army Surgeon General’s Performance Triad initiative seeks to improve Soldier readiness and resiliency by 

improving the activity, sleep and nutritional aspects of 

Soldier health behaviors. This study examined the activity and sleep aspects of the Performance Triad. Physical 

activity is an important variable to support health and 

improve performance. It is important to document the 

physical demands of the training program followed during BCT in order to ensure that the activities performed 

are suffi cient for developing the Soldier’s fi tness, but not 

so excessive that the demands lead to the development 

of musculoskeletal injuries, a key barrier to individual 

and unit readiness. Additionally, these data suggest recruits during BCT are meeting the minimum PA recommendations for healthy adults set forth by the American 

College of Sports Medicine.32

In terms of sleep, these data suggest that recruits are 

receiving slightly less than the recommended 7-8 hours 

per night during BCT, despite being allotted 7 hours 

each night to devote to sleep. This lack of rest and 

recovery during BCT may adversely impact a recruit’s 

ability to perform his or her job suffi ciently and maintain adequate health and resiliency.

ACKNOWLEDGEMENT

Th is study was funded by the US Army Medical 

Research and Materiel Command and the Defense Safety 

Oversight Council.

REFERENCES

1. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin 

R, Jones BH. Ambulatory physical activity during 

United States Army basic combat training. Int J 

Sports Med. 2006;28:106-115.

2. Knapik JJ, Rieger W, Palkoska F, Van Camp S, 

Darakjy S. United States army physical readiness training: rationale and evaluation of the 

physical training doctrine. J Strength Cond Res.

2009;23(4):1353-1362.

3. Knapik JJ, Hauret KG, Canada S, Marin R, Jones 

B. Association between ambulatory physical activity and injuries during United States Army basic 

combat training. J Phys Act Health. 2011;8:496-502.

4. American College of Sports Medicine. The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fi tness, and fl exibility in healthy adults. Med 

Sci Sports Exerc. 1998;30:975-991.

5. Pollock ML, Gettman LR, Milesis CA, Bah MD, 

Durstine L, Johnson RB. Effects of frequency and 

duration of training on attrition and incidence of 

injury. Med Sci Sports Exerc. 1977;9:31-36.

6. Koplan JP, Powell KE, Sikes RK, Shirley RW, 

Campbell CC. An epidemiologic study of the benefi ts and risks of running. JAMA. 1982;248:3118-3121.

7. Jacobs SJ, Berson BL. Injuries to runners: a study 

of entrants to a 10,000-meter race. Am J Sports 

Med. 1986;14:151-155.

8. Blair SN, Kohl HW, Goodyear NN. Rates and risks 

for running and exercise injuries: studies in three 

populations. Res Q. 1987;58:221-288.

9. Marti B, Vader JP, Minder CE, Abelin T. On 

the epidemiology of running injuries. The 

1984 Bern Grand-Prix study. Am J Sports Med.

1988;16:285-294.

10. Walter SD, Hart LE, McIntosh JM, Sutton JR. Th e 

Ontario cohort study of running-related injuries. 

Arch Intern Med. 1989;149:2561-2564.

11. Koplan JP, Rothenberg RB, Jones EL. Th e natural 

history of exercise: a 10-yr follow-up of a cohort of 

runners. Med Sci Sports Exerc. 1995;27:1180-1184.

 QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED

DURING US ARMY BASIC COMBAT TRAINING
 October – December 2013 65

THE ARMY MEDICAL DEPARTMENT JOURNAL

12. Colbert LH, Hootman JM, Macera CA. Physical 

activity-related injuries in walkers and runners in 

the aerobics center longitudinal study. Clin J Sport 

Med. 2000;10:259-263.

13. Almeida SA, Williams KM, Shaff er RA, Brodine 

SK. Epidemiological patterns of musculoskeletal 

injuries and physical training. Med Sci Sports Exerc.

1999; 31:1176-1182.

14. Jones BH, Cowan DN, Tomlinson JP, Robinson 

JR, Polly DW, Frykman PN. Epidemiology of injuries associated with physical training among 

young men in the Army. Med Sci Sports Exerc.

1993;25:197-203.

15. Carlson SA, Hootman JM, Powell KE, et al. Selfreported injury and physical activity levels: United 

States 2000-2002. Ann Epidemiol. 2006;16:712-719.

16. Schneider S, Seither B, Tonges S, Schmitt H. Sports 

injuries: population based representative data 

on incidence, diagnosis, sequelae, and high risk 

groups. Br J Sports Med. 2006;40:334-339.

17. Knapik JJ, Graham B, Cobbs J, Th ompson D, et al. 

Technical Report No. 12-HF-OF6F-11. Th e SoldierAthlete Initiative: Program Evaluation of the Eff ectiveness of Athletic Trainers and Musculoskeletal 

Action Teams in Initial Entry Training, Fort Leonard Wood, June 2010-December 2011. Aberdeen 

Proving Ground MD: US Army Institute of Public 

Health; 2012.

18. Scott SJ, Feltwell DN, Knapik JJ, Barkley CB, 

Hauret KG, Bullock SH, Evans RK. A multiple intervention strategy for reducing femoral neck stress 

injury and other serious overuse injuries in United Stated Army basic combat training. Mil Med. 

2012;177(9):1081-1089.

19. Knapik JJ, Hauret KG, Arnold S, Canham-Chervak 

M, Mansfi eld AJ, et al. Injury and fi tness outcomes 

during implementation of physical readiness training. Int J Sports Med. 2003;24:372-381.

20. TRADOC Regulation 350-6: Enlisted Initial Entry 

Training (IET) Policies and Administration. Fort 

Monroe, VA: US Army Training and Doctrine 

Command; November 2012.

21. Army Regulation 70-25: Use of Volunteers as Subjects of Research. Washington, DC: US Dept of the 

Army; January 25, 1990. 

22. US National Archives and Records Administration. 

Code of Federal Regulations. Title 45. Public Welfare. 2009.

23. Welk GJ, Schaben JA, Morrow JR. Reliability of accelerometry-based activity monitors: 

a generalizability study. Med Sci Sports Exerc.

2004;36(9):1637-1645.

24. Crouter SE, Churilla JR, Bassett DR. Estimating 

Energy Expenditure using Accelerometers. Eur J 

Appl Physiol. 2006;98:601-612.

25. Freedson PS, Melanson E, Sirard J. Calibration of 

the computer science and applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-781.

26. McKenzie TL. Use of direct observation to assess 

physical activity. In: Welk GJ, ed. Physical Activity 

Assessment For Health-Related Research. Champaign, IL: Human Kinetics; 2002:179-195.

27. Harmon EA, Gutekunst DJ, Frykman PN, Nindl 

BC, Alemany JA, Mello RP, Sharp MA. Eff ects of 

two diff erent eight-week training programs on 

military physical performance. J Strength Cond Res.

2008;22(2):524-534.

28. Field Manual 21-18: Foot Marches. Washington, 

DC: US Dept of the Army; June 1990.

29. Knapik J, Reynolds K. Load carriage in military 

operations: a review of historical, physiological, 

biomechanical, and medical aspects. In: Friedl KE, 

Santee WR, eds. Military Quantitative Physiology: 

Problems and Concepts in Military Operational 

Medicine. Fort Sam Houston, TX: Th e Borden Institute; 2012:303-338. 

30. Miller NL, Shattuck LG. Sleep patterns of young 

men and women enrolled at the United States Military Academy: results from year 1 of a 4-year longitudinal study. Sleep. 2005;28(7):837-841.

31. McArdle WD, Katch FI, Katch VL. Exercise Physiology: Energy, Nutrition and Human Performance.

Philadelphia, PA: Lea & Febiger; 1991.

32. Garber CE, Blissmer B, Deschenes MR, Franklin 

BA, Lamonte MJ, Lee IM, et al. American College 

of Sports Medicine position stand. Quantity and 

quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fi tness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc.

2011;43(7):1334-1359.

AUTHORS

Ms Simpson, Dr Redmond, Dr Cohen, Mr Hendrickson, 

and Ms Sharp are in the Military Performance Division 

of the US Army Research Institute for Environmental 

Medicine, Natick, Massachusetts.

Dr Spiering is a Senior Physiologist for the Nike Sport 

Research Lab, Beaverton, Oregon.

Dr Knapik and Mr Steelman are at the US Army Institute 

of Public Health, US Army Public Health Command, 

Aberdeen Proving Ground, Maryland.
66 http://www.cs.amedd.army.mil/amedd_journal.aspx

Nutrition is a critical element for sustaining Soldier 

health and performance. Nutritional fi tness is defi ned as 

the availability and consumption of quality food in appropriate quantities to ensure mission performance and 

protect against disease.1

 Accordingly, the dietary behaviors and intake patterns of a Soldier form the basis of his/

her nutritional fi tness. Optimal nutrition supports health, 

an ideal body composition, positive psychological and 

cognitive status,2-4 and physical readiness.5,6 This is of 

particular importance since military personnel are often 

subjected to physical and environmental extremes that 

demand optimal cognitive, psychosocial, and physical 

performance.7,8 Thus, an appropriate body composition, 

high fi tness, good health, and adequate substrates to fuel 

cognitive and physical activities can positively impact 

individual performance and force readiness.9

 A healthy 

diet is a key countermeasure for individuals to ensure 

optimal body weight and adequate fuels for cognitive 

and physical activity.10,11

Dietary choices and habits affect every aspect of life: 

physical performance,5,6 cognitive performance,4,12

sleep,13,14 mood,7

 and overall health.15-17 The protective 

effects of fruit and vegetable consumption from diseases have been investigated extensively, yet based on 

the 2011 Military Survey of Health Related Behaviors, 

only 11.2% and 12.9% of military personnel met the US 

Dietary Goals of 3 or more servings of fruits and vegetables per day, respectively.18 These numbers, which are 

lower than those from the 2008 survey19 and the Healthy 

Nutrition as a Component of the Performance

 Triad: How Healthy Eating Behaviors

 Contribute to Soldier Performance

 and Military Readiness

Dianna L. Purvis, PhD

Cynthia V. Lentino, MS

Theresa K. Jackson, PhD, MPH

Kaitlin J. Murphy, MS

Patricia A. Deuster, PhD, MPH

ABSTRACT

Objective: Nutrition is a critical element of Soldier health and performance. Food choices, meal timing, and 

dietary intake behaviors contribute to nutritional fi tness. The objectives of this study were to describe Soldier 

dietary behaviors and quantify the association between healthy eating behaviors and demographic, lifestyle, 

and psychosocial factors.

Methods: The Comprehensive Soldier and Family Fitness Global Assessment Tool (GAT) assesses emotional, 

social, family, and spiritual fi tness. In 2012, 57 pilot questions were added to the GAT to create a physical dimension that included nutrition assessments. Participants included 13,858 Active Duty, Reserve, and National 

Guard Soldiers: 83% male; 85% enlisted; a mean age of 28±9 years. A Healthy Eating Score (HES-5) was calculated from 5 questions assessing frequency of fruit, vegetable, whole grain, dairy, and fi sh intake (Cronbach 

α=0.81). Associations between HES-5 and other dietary habits, physical activity patterns, and GAT psychosocial dimension scores were examined.

Results: Soldiers who ate breakfast regularly (6 times/week or more), drank 7 servings or more of water/day, 

and met weekly exercise recommendations were more likely to be in the highest HES-5 quartile than those who 

did not. Those who passed their Army Physical Fitness Test (APFT) in the top quartile were also more likely to 

report high HES-5 scores than those who failed (P<.001). Soldiers with healthy anthropometric measures and 

the highest emotional, social, family, and spiritual fi tness scores were also more likely to be in the top HES-5 

quartile than those with unhealthy measures and with the lowest fi tness scores (P<.001).

Conclusion: The HES-5 may be a useful index for characterizing dietary intake behaviors. Healthy dietary 

intake behaviors are associated with all dimensions of health, physical fi tness, and psychosocial status.
 October – December 2013 67

People 2010 objectives of 75% or more for fruits and 

50% or more for vegetables, are also signifi cantly lower 

than those reported for the civilian sector.20 Conversely, 

excess energy intakes above daily requirements may 

lead to weight gain, increased adiposity, and adverse 

health consequences.21,22 A poor diet and the inappropriate use of dietary supplements (DS) can negatively 

impact human performance and health outcomes.5,6,23,24

This study examined lifestyle habits—nutrition behaviors, sleep quality, psychosocial status, health habits, 

and physical activity—in US Army Soldiers through 

the introduction of a set of questions added to the Global 

Assessment Tool (GAT) as part of the Comprehensive 

Soldier and Family Fitness (CSF2) program, and characterized differences between the healthiest and least 

healthy eaters. The objectives of this study were (1) to 

describe Soldiers’ dietary practices using a brief healthy 

eating score and (2) to evaluate the association between 

demographic and lifestyle factors affecting performance 

(eg, sleep quality, physical activity, and various psychosocial measures) with self-reported dietary behaviors.

METHODS

The CSF2 GAT, an annual requirement for all Soldiers, 

consists of 105 questions and was developed in part by 

Seligman et al25 and others26 to assess fi tness in 4 psychosocial dimensions: emotional, social, family, and 

spiritual fi tness.27,28 In 2012, the CSF2 program introduced a physical dimension by adding 57 pilot questions to assess nutrition behaviors, sleep quality, DS use, 

physical fi tness, and other lifestyle behaviors. During 2 

weeks in July 2012, anyone completing the GAT was directed to the expanded GAT. Upon GAT completion, respondents were informed that physical domain answers 

would not be included in their overall GAT score, and 

they were given the option to consent to the use of their 

GAT responses for further study. The Uniformed Services University of the Health Sciences Institutional 

Review Board concluded that a full review was not required for this investigation. This study was not classifi ed as human subjects research since the CSF2 program 

provided data stripped of identifi cation elements to the 

Consortium for Health and Military Performance per an 

established data use agreement.

Population

A total of 14,850 participants completed the CSF2 GAT 

physical domain pilot questions and consented for their 

data to be used for further study. Three family members, 599 Department of Defense (DoD) civilians, and 

390 participants with missing data were excluded from 

analyses. Hence, we are reporting data from 13,858 Active Duty, Reserve, and National Guard Soldiers.

Measures

Nutrition Behaviors

Nutrition behaviors were assessed in the pilot physical 

GAT domain by means of a 5-question Healthy Eating 

Score (HES-5). The HES-5 was modifi ed from the US 

Department of Agriculture’s (USDA) Healthy Eating 

Index.29-32 The Healthy Eating Index, developed in 2005 

(HEI-2005) to evaluate if an individual is meeting the 

2005 Dietary Guidelines for Americans,31,32 assesses 12 

food components (fruit, vegetables, grains, milk/dairy, 

meat and beans, fi sh, oils, fats, sodium, and added sugar). 

The HEI-200529-32 responses are summed for an overall 

score ranging from 0-100 points,31,32 and the index has 

been modifi ed to assess special populations.33 Since the 

GAT nutrition behavior questions assessed respondents’ 

Table 1. Healthy Eating Score-5.

Over the last 30 days, how often did you eat/drink the following foods/beverages? (Note: Only a few examples of each category are listed to remind you of 

the types of foods—many more are possible.)

3 or More 

Times

per

Day

Twice

per

Day

Once

per

Day

3 to 6

Times

per

Week

1 or 2

Times

per

Week

Rarely

or

Never

FRUIT: fresh, frozen, canned or dried, or 100% fruit juices 5 43 2 1 0

VEGETABLES: fresh, frozen, canned, cooked or raw: dark green vegetables 

(broccoli, spinach, most greens), orange vegetables (carrots, sweet potatoes, 

winter squash, pumpkin), legumes (dry beans, chick peas, tofu), starchy vegetables (corn, white potatoes, green peas), and other (tomatoes, cabbage, celery, cucumber, lettuce, onions, peppers, green beans, cauliflower, mushrooms, 

summer squash, etc)

5 43 2 1 0

WHOLE GRAINS: rye, whole-wheat, or heavily seeded bread; brown or wild rice; 

whole-wheat pasta or crackers; oatmeal; corn tacos 5 43 2 1 0

DAIRY: regular/whole fat milk; low- or reduced-fat milk (2%, 1%, 0.5% or skim), 

yogurt, cottage cheese, low-fat cheese, frozen low-fat yogurt, soy milk, or other calcium-fortified foods (orange juice, soy/rice milk, breakfast cereals, etc)

5 43 2 1 0

FISH: tuna, salmon, or other nonfried fish 5 55 5 3 0

Note. Questions and scoring that comprise the Healthy Eating Score-5. Scores were totaled for a range of 0 to 25. 
68 http://www.cs.amedd.army.mil/amedd_journal.aspx

daily intake of fruits, vegetables, whole grains, dairy, 

and fi sh, the HEI-2005 was modifi ed to create the HES-5. 

The consumption of health-promoting foods assessed by 

the HES-5 (Table 1) is typically defi cient in military populations, and their consumption does not meet national 

guidelines.18,19,34 Each HES-5 question represented a subscale score ranging from 0-5, with 5 indicating that the 

respondent met the USDA dietary recommendation for 

that measure.35 Thus, the total possible value of HES-5 

ranged from 0 to 25. A Cronbach  analysis of the 5 subscale scores was used to determine HES-5 reliability36,37; 

the analysis yielded an internal consistency reliability coeffi cient of 0.81. Classifi cations for Cronbach  va ry, but 

values less than 0.60 are generally considered unacceptable, 0.70 minimally acceptable, and 0.80 very good.37

Respondents’ HES-5 scores were then partitioned into 

quartiles for subsequent analyses. The top quartile consisted of HES-5 scores from 20 to 25, or above the 75th 

percentile. Scores in the third quartile ranged from 17 to 

19, those in the second quartile from 13 to 16, and scores 

of 12 or lower comprised the lowest quartile, representing the lowest 25th percentile.

Additional Physical Domain Measures

The GAT physical dimension assessed a variety of 

lifestyle measures that were dichotomized to indicate 

healthy versus less healthy behaviors. These measures 

included the number of days per week on which respondents ate breakfast (6 or more days per week versus 5 or 

fewer days per week), whether the respondent usually 

consumed a recovery snack (defi ned as a snack eaten 

within 60 minutes of strenuous exercise and classifi ed as 

yes or no), water intake (7 or more glasses per day versus 

6 or fewer glasses per day), consumption of health-promoting supplements (ie, multivitamins and/or mineral 

supplements with 6 or more ingredients; or single-ingredient supplements such as calcium or iron; classifi ed 

as yes or no), consumption of additional supplements (ie, 

omega-3 supplements, protein powders; classifi ed as yes 

or no), and consumption of sodas (diet and/or regular; 

classifi ed as yes or no for any soda consumption).

Two questions from the Pittsburgh Insomnia Rating 

Scale (PIRS-2)38,39 were used to assess sleep quality; 

responses were summed based on scoring guidelines,38

and a threshold of 5 or higher distinguished good sleepers from poor sleepers. This cutoff, although different 

from the typical PIRS-2 threshold, was established in 

conjunction with the scale’s authors to yield a more specifi c rather than sensitive classifi cation of poor sleepers.40 Respondents further answered questions related to 

their perceived health, weight, and alcohol intake. The 3 

specifi c questions were:

1. How do you consider your general health? (excellent, good, fair, poor, don’t know; classifi ed as 

“excellent and good” or “fair and poor”)

2. In thinking about your weight, do you consider 

yourself to be underweight, about the right weight, 

overweight, obese, don’t know? (classifi ed as 

“about the right weight” versus “overweight or 

obese”)

3. Have you exceeded 5 alcoholic drinks on any 

single occasion during the past 3 months? (yes or 

no).

Soldiers’ physical activity was assessed by asking how 

many times per week they participated in aerobic activity for at least 20 minutes, and the frequency with which 

they participated in strength or resistance exercise. Responses were classifi ed as “met national guidelines” or 

“failed to meet national guidelines” for both aerobic and 

strength training, based on the American College of 

Sports Medicine and Centers for Disease Control and 

Prevention exercise recommendations.41 Further, each 

participant entered his or her most recent raw numbers 

for push-ups, sit-ups, and timed run from the Army 

Physical Fitness Test (APFT). Based on this information, 

an additional variable was created to indicate whether 

the respondent passed or failed his or her APFT based 

on Army standards.42 A respondent failed the APFT if 

he or she scored less than 60 in any event. To distinguish top APFT performers, those Soldiers who passed 

the APFT were additionally placed into quartiles based 

on the distribution of scores.

Lastly, participants self-reported their height in inches, 

weight in pounds, and waist circumference in inches. 

Each Soldier’s body mass index (BMI) ((weight in kg)/

(height in m)2

) was calculated and classifi ed as healthy 

or unhealthy using 27.5 kg/m2

 as the upper limit for a 

healthy BMI per Army Regulation 600-9.

43 Waist circumference was classifi ed as healthy or unhealthy using 

35 inches or below as healthy values for females, and 40 

inches or below as healthy values for males.44

GAT Dimensions

The CSF2 provided composite scores for each original 

GAT dimension (emotional, social, family, spiritual). 

Each composite score ranged from 1 to 5, with higher 

scores indicating higher levels of resilience in each dimension.27,28 Subscores for each dimension were further 

classifi ed into quartiles for subsequent analyses.

Statistical Analyses

The IBM SPSS Statistics software package for Windows, Version 20.0 (IBM Corp, Chicago, IL) was used 

for all analyses. Using frequency tables and descriptive 

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 69

THE ARMY MEDICAL DEPARTMENT JOURNAL

statistics, the analysis team reviewed data to remove 

outliers and confi rm assumptions for parametric tests.

Individual indicators on the HES-5 were examined fi rst 

to measure the extent that Soldiers are currently meeting 

national nutrition guidelines. Next, HES-5 means and 

standard deviations for various demographic subgroups 

were calculated. The HES-5 quartiles (the dependent 

variable, designated as highest [Q4] versus lowest [Q1]) 

were assessed to characterize the differences in the most 

healthy and least healthy eaters; binary logistic regression models were used to calculate the odds of being in 

the highest HES-5 quartile versus the lowest quartile for 

a variety of predictors.

Demographic independent variables included age, gender, active duty status, enlistment status, and marital 

status. Lifestyle independent variables included dietary 

behaviors (breakfast, hydration, soda intake, DS use) 

and physical activity, APFT scores, BMI, waist circumference, and GAT fi tness dimensions. Reference groups 

were the “less healthy” as compared to the “more healthy” 

group. Regarding the 4 original GAT dimensions, only 

the highest and lowest quartiles were compared, and the 

lowest quartile served as the reference group. For the 

APFT analysis, Soldiers who passed the test in the top 

quartile were compared to those who failed.

To adjust for infl ated type I error rates associated with 

multiple binary analyses, a Bonferroni adjustment was 

applied, ie, the standard type I error rate (P=.05) was 

divided by 17 (the total number of logistic regression 

analyses) to achieve a signifi cance level set at P<.003.

RESULTS

General Characteristics

Demographic characteristics of the study population 

and mean HES-5 scores are summarized in Table 2. 

Subjects were predominately male (83%) and enlisted 

(85%) with a mean age of 28±9 years, and mean BMI of 

26.6±4 kg/m2

.

Dietary Recommendations

Figure 1 shows that 38.7% of participants met the US 

Dietary Guidelines for fruit intake (at least 2 servings 

per day); 22.2% met the vegetable recommendation (at 

least 2 servings per day for females and 3 servings for 

males); and 16.8% met the whole grain recommendation 

of at least 3 servings per day. Overall, only 17.3% met 

the dairy recommendation of at least 3 daily servings, 

whereas 46.6% met the fi sh recommendation of at least 

2 to 3 servings per week.

Healthy Eating Score and Dietary Behaviors

Means for the HES-5 quartiles are presented in Table 

2. The mean HES-5 for this sample was 15.7±3.4, and 

persons in the highest HES-5 quartile had a mean of 

22.1±1.8 compared to those in the lowest quartile who 

had a mean of 8.6±3.0.

Overall, offi cers (OR 1.48; 95% CI, 1.29-1.70; P<.001), 

and single, divorced, or legally separated persons (OR 

1.21; 95% CI, 1.10-1.33; P<.001) had greater odds of being in the highest HES-5 quartile when compared to 

enlisted and married Soldiers. No signifi cant associations were noted between highest/lowest HES-5 quartile membership and gender (reference group: male [OR 

Table 2. Study Sample Demographic Characteristics (N=13,858).

Frequencies HES-5

Mean±SD

Age, Mean±SD (years) 28.2±9.2

Years Range 17.0-61.0

Age Groups

17 to 29 66.9% 15.9±3.4

30 and over 33.1% 15.1±5.3

Gender

Female 16.7% 15.6±5.5

Male 83.3% 15.7±5.3

Army Duty Status

National Guard/Reserve 47.4% 15.5±5.4

Active Duty 52.6% 15.8±5.3

Service Category

Enlisted 84.9% 15.5±5.5

Officers 14.6% 16.39±4.7

Marital Status

Married 49.0% 15.5±5.2

Single/Divorced/Legally Separated 51.0% 15.8±5.4

Army Physical Fitness Test n=9,845

Failed 13.7% 15.0±5.6

Passed 86.3% 16.0±5.3

BMI Categories n=11,119

Underweight (<18.4 kg/m2) 0.5% 15.1±5.1

Normal/Healthy (18.5-27.5 kg/m2) 65.3% 15.0±5.3

Overweight (27.6-29.9 kg/m2) 16.9% 15.6±5.3

Obese (>30 kg/m2

) 17.3% 15.1±5.5

BMI, Mean±SD (kg/m2) 26.6±4.0

BMI Range 13.4-56.3

Waist Circumference n=5,855

Healthy 90.9% 16.09±5.3

Unhealthy 9.1% 15.28±5.3

HES-5 Quartiles*

Low HES-5 - Quartile 1 25.9 8.6±3.0

Quartile 2 26.0 14.4±1.2

Quartile 3 22.2 17.8±0.8

High HES-5 - Quartile 4 25.9 22.1±1.8

Note: Data are represented as meansstandard deviation (SD) for 

continuous variables and as a percentage for categorical variables. 

Percentages within characteristic groups may not total 100% due to 

missing data.

*HES-5 (Healthy Eating Score-5); High HES-5 is defined as a total ≥20 out 

of 25 or above the 75th percentile; a low HES-5 received a score of 12 or 

below (lower 25th percentile).
70 http://www.cs.amedd.army.mil/amedd_journal.aspx

1.03; 95% CI, 0.91-1.16; P=.64]) or active duty status (reference group: Reserve or National Guard 

[OR 1.12; 95% CI, 1.02-1.23; P=.02]).

Additional results presented in Figure 2 indicate 

that those Soldiers who were younger, ate breakfast 

at least 6 times per week, and ate a postexercise 

recovery snack were more likely to be in the top 

HES-5 quartile when compared to older Soldiers 

and those who did not engage in those behaviors. 

Figure 2 also indicates that Soldiers with healthy 

anthropometric measures had greater odds of being 

in the highest HES-5 quartile than Soldiers without 

healthy anthropometric measures. Moreover, those 

Soldiers who considered themselves to be “about 

the right weight” were more likely be in the highest HES-5 quartile when compared to those who 

considered themselves as overweight or obese (OR 

2.15; 95% CI, 1.94-2.40; P<.001).

The DS intake data are shown in Figure 3. Many respondents (40%) reported regular use of health-promoting 

supplements such as a multivitamin/mineral. Soldiers 

who reported taking a health-promoting supplement at 

least once a week were more likely to be in the top HES5 quartile than those who did not. Similarly, those who 

took an omega-3 fatty acid supplement once a week and 

a protein supplement at least once a week had greater 

odds of being in the top HES-5 quartile than Soldiers 

who did not take these supplements. Soldiers who reported taking a performance-enhancing or bodybuilding product (other than a protein powder) at least once 

a week were 2 times as likely to be in the top HES-5 

quartile when compared to those who did not take these 

Health Promoting

Omega-3 Fatty Acid

2.76 2.51-3.03

3.79 3.40-4.20

2.96 2.67-3.28

Odds Ratio

0 1 2 3 4 5

 OR 95% CI

Protein Powders

Figure 3. Dietary Supplements. The relative odds of having 

a high HES-5 and taking a supplement at least once a week 

(versus less than once a month or never), when compared 

to low HES-5. All categories are dichotomous. High HES-5 

is defi ned as a total ≥20 out of 25; a low HES-5 received a 

score of 12 or lower (P<.003).

Healthy

Eater

Healthy

Waist Sizec

OR 1.56*

CI, 1.22-2.00

Exercise

Recovery

Snackb

OR 3.1*

CI, 2.80-3.40

Age

18-29a

Years

OR 1.46*

CI, 1.32-1.61

Breakfastf

OR 4.2*

CI, 3.8-4.70

≥7 Water

Servings/

Daye

OR 7.19*

CI, 5.05-6.98 Healthy

BMId

OR 1.35*

CI, 1.20-1.50

Figure 2. Relative odds of being in the highest HES-5 

quartile versus the lowest HES-5 quartile for several 

indicators. High HES-5 is defi ned as a total ≥20 out of 

25 or above the 75th percentile; a low HES-5 received 

a score of 12 or below (lower 25th percentile).

*P<.003. All reported odds ratios are independent and did 

not control for other factors. a

Reference group: 30 years or older.

bReference group: those who did not regularly consume a 

recovery snack. c

Reference group: waist circumference larger than 35 in for 

women; larger than 40 in for men. dReference group: greater than 27.5 kg/m2. e

Reference group: consumption of 6 or less glasses of 

water per day. f

Reference group: consumption of breakfast 5 or less times 

per week.

38.7%

50%

40%

30%

20%

10%

0% Fruit Vegetables Whole

Grains

Dairy Fish

22.2%

16.8% 17.3%

46.6%

Figure 1. Percentages of Soldiers meeting US Dietary Guidelines by 

category. Overall, less than half met the dietary guidelines for fruit (2 

servings/day), vegetables (2-3 servings/day), whole grains (3 servings/day), dairy (3 servings/day), and fi sh (2-3 servings/week).

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 71

THE ARMY MEDICAL DEPARTMENT JOURNAL

products (OR 2.06; 95% CI, 1.82-2.32; P<.001). Approximately one-fi fth (21%) of the total population reported 

taking all 3 supplements (health-promoting, omega-3, 

and protein powder), and the majority of this group was 

classifi ed as being in the highest HES-5 quartile. Soldiers who consumed all three of these supplements experienced 4 times the odds of being in the highest HES5 group versus the lowest HES-5 group when compared 

with those who did not consume all 3 supplements (OR 

4.04; 95% CI, 3.56-4.60).

Other Lifestyle Behaviors

Approximately 60% of respondents drank regular and/

or diet sodas, and 23.1% of respondents reported binge 

drinking, as defi ned by exceeding 5 alcoholic drinks on 

any single occasion during the previous 3 months. Both 

behaviors were signifi cantly associated with membership in high/low HES-5 quartiles. Soldiers who consumed diet or regular soda (OR 0.56; 95% CI, 0.51-0.61; 

P<.001) were less likely to be in the highest HES-5 quartile than those who did not consume soda. Soldiers who 

self-reported binge drinking were less likely to be in the 

highest HES-5 quartile than Soldiers who did not binge 

drink (OR 0.57; 95% CI, 0.51-0.64; P<.001).

Sleep was also related to a Soldier’s likelihood 

of being in the highest or lowest HES-5 quartile. 

When compared to “poor” sleepers (defi ned as 5 

or more on the PIRS-2), Soldiers who were classifi ed as “good” sleepers had 4 times the odds of 

being in the highest HES-5 quartile (OR 4.38; 

95% CI, 3.85-4.98; P<.001).

A relationship between self-reported health status and being a “healthiest” or “least healthy” 

eater was also observed. Respondents who considered their health to be “good” or “excellent” 

had 3 times the odds of being in the highest HES5 quartile when compared to respondents whose 

health was “fair” or “poor” (OR 3.37; 95% CI, 

2.98-3.82; P<.001).

Physical Activity

Respondents’ self-reported frequency of physical activity and its results were analyzed based 

on the American College of Sports Medicine and 

Centers for Disease Control and Prevention exercise recommendations. A total of 28.5% of respondents met cardiovascular recommendations, 

66.8% met strength-training recommendations, 

86.3% passed their APFT overall, and 20.5% 

passed their APFT in the top quartile. Figure 4 

illustrates for each HES-5 quartile the percentage of respondents who met the physical activity 

recommendations as well as the number of respondents 

who passed their APFT in the top quartile.

When compared to Soldiers who did not meet physical 

activity recommendations, those who engaged in cardiovascular exercise for at least 20 minutes, 5 days per 

week were more likely to be in the highest than the lowest HES quartile (OR 3.23; 95% CI, 2.90-3.60; P<.001), 

as were those who participated in resistance training 

at least 2 days per week (OR 3.60; 95% CI, 3.24-3.99; 

P<.001).

Finally, we compared the likelihood of being in the 

HES-5 high/low quartile among Soldiers who failed 

their APFT and those who passed in the highest quartile. Those who passed their APFT in the highest quartile had more than twice the odds of being in the highest HES quartile versus the lowest HES quartile when 

compared to those who failed their APFT ([n=3,413] OR 

2.53; 95% CI, 2.08-3.08; P<.001).

Healthy Eating Score and GAT Dimensions

Figure 5 characterizes the percentage of respondents who scored in the top quartile of the CSF2 

Figure 4. Physical fi tness and nutrition. Percentage of Soldiers in each 

HES-5 quartile who met the Center for Disease Control and the American 

College of Sports Medicine recommendations for cardiovascular exercise and resistance training or passed the Army Physical Fitness Test 

(APFT) in the Top Quartile. 

Healthy Eating Score Qualities

50%

80%

90%

70%

60%

0%

10%

40%

30%

20%

Cardio Activity

Strength Training

APFT in Top

Quartile

Low

HES-5

High

HES-5
72 http://www.cs.amedd.army.mil/amedd_journal.aspx

dimensions—emotional, social, family, and spiritual—

in each of the HES-5 quartiles. High GAT dimension 

scorers were signifi cantly more likely to be high HES-5 

scorers:

 Emotional Fitness: OR 7.03; 95% CI, 6.08-8.13 

(n=3,688)

 Social Fitness: OR 4.72; 95% CI, 4.10-5.44 

(n=3,698)

 Family Fitness: OR 2.99; 95% CI, 2.99-2.59 

(n=3,222)

 Spiritual Fitness: OR, 4.16; 95% CI, 3.65-4.75 

(n=4,046)

COMMENT

Poor nutritional/dietary habits degrade mission readiness while contributing to other health disorders9

 and 

affect all domains of performance. Nutrition is thus 

deemed an essential component of Total Force Fitness.45 Accordingly, dietary behavior assessment questions were included in the new GAT physical dimension 

along with other lifestyle questions relating to performance. This study characterized nutritional behaviors 

of 13,858 Soldiers and examined their interrelationships with other lifestyle behaviors. We showed that 

dietary behaviors could be characterized by the HES-5. 

The HES-5 was strongly associated with a number of 

health-promoting nutritional behaviors: those 

with healthier BMIs and waist circumferences, 

who performed better on the APFT, and who 

had better psychosocial profi les were also more 

likely to have the highest HES-5 scores.

Although the benefi cial effects of fruit and vegetable consumption are well known, only 38.7% 

of participants met fruit intake recommendations, and 22.2% met vegetable recommendations. These fi ndings are consistent with health 

behavior studies reporting suboptimal fruit and 

vegetable intake in military personnel.18,19 Even 

fewer Soldiers met the guidelines of eating at 

least 3 servings per day of whole grains (16.8%) 

and dairy (17.3%). Importantly, a higher percentage (46.6%) met the recommendation of 

at least 2-3 weekly servings of fi sh, which may 

refl ect the Warriors’ focus on tuna as a quick, 

inexpensive protein. Although it will require 

further exploration, this is a reasonable hypothesis. Our sample did report higher intakes 

of key food groups than were noted in the 2011 

Health Related Behaviors Survey of Active 

Duty Military Personnel18 where only 12.9%, 

11.2% and 12.7% of all military personnel 

met the intake guidelines for vegetables, fruit, 

and whole grains, respectively. Of interest is why the 

percentage of Soldiers meeting the recommendations 

is higher in the present study than in previous survey 

fi ndings. This could be related to differences in assessment tools, sample population differences, or ongoing 

and emerging DoD and Army initiatives targeting nutritional fi tness. Further study might reveal the differential 

effect of these varying campaigns on health outcomes 

among the military services.

The HES-5 was created to assess overall nutrition. In 

our military population, high HES-5 scores were strongly associated with a number of key health promoting nutritional behaviors. Those who consumed breakfast at 

least 6 times per week, 2 snacks daily, 7 or more servings of water daily, and a snack within 60 minutes of 

strenuous exercise were more likely to have high HES5 scores than Soldiers who did not consume breakfast, 

adequate water, or recovery snacks. These behaviors 

have been shown to infl uence health and performance. 

Studies have shown that consumption of breakfast and 

snacks is associated with lower stress, improved cognitive function, and fewer injuries and accidents at 

work,46 along with lower values for BMI and waist circumference.47 Consistent with those fi ndings, Soldiers 

with a healthy BMI and with a healthy waist circumference were more likely to have high HES-5 scores than 

Figure 5. Global Assessment Tool (GAT) Fitness Dimensions and Nutrition. Percentage of each HES-5 quartile scoring in the highest quartile 

of the GAT psychological dimensions.

Healthy Eating Score Qualities

Low HES-5 High HES-5

Emotional

Social

Family

Spiritual

5%

0%

15%

10%

40%

35%

30%

25%

20%

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 73

THE ARMY MEDICAL DEPARTMENT JOURNAL

those with an unhealthy BMI and waist circumference. 

Furthermore, Deshmukh-Taskar et al48 indicated that 

breakfast consumption was associated with more favorable cardiometabolic risk profi les than skipping breakfast. Additionally, carbohydrates, a usual constituent 

of snacks and meals, enhanced physical and cognitive 

performance in Soldiers engaged in sustained and intense physical activities.4,5 Together, these fi ndings demonstrate the infl uence of dietary behaviors on multiple 

aspects of health and performance.

Critical components of performance are hydration, (re-)

fueling, and recovery. Adequate hydration plays a key 

role in physical performance, particularly in the heat,49,50

and those with high HES-5 scores were much more likely to consume recommended amounts of water. Likewise, proper fueling and adequate sleep and rest are 

essential.51-56 Res et al53 found that protein consumption 

prior to sleep improved physical recovery after training. 

Thus, appropriate nutrient timing, such as consuming 

a postworkout snack, can improve performance, delay 

fatigue,6,57 refuel depleted muscular energy stores,6,51 accelerate recovery, decrease muscle soreness following 

prolonged exercise training, and may positively effect 

health outcomes.58 Additional benefi ts of regular nutrient timing include improved morale, stimulation of muscle protein synthesis, and protection against training injuries.51,58 It appears that Soldiers may understand this 

concept in that those who consumed a snack within a 

short time after strenuous training were also more likely 

to have high HES-5 scores. More effort should be focused on making this simple nutritional strategy known 

and ensuring appropriate recovery meals are available.

One question and component of the HES-5 related to the 

frequency of fi sh intake, in particular, to fi sh containing 

omega-3 fatty acids, such as salmon, tuna, and mackerel. 

Research has suggested that omega-3 fatty acids may be 

cardioprotective,59 and the Food and Drug Administration announced in October 2000 a qualifi ed health claim 

for dietary supplements containing omega-3 fatty acids 

and reduced risk of CHD.60 Omega-3s also appear to 

serve an important role in brain health.3,61,62 Specifi cally, 

Kang and Gleason61 concluded that increasing omega-3 

intake may be one way to manage depression. Levant 

et al62 reported that omega-3 fatty acids may regulate 

neurobiological substrates of depression, including serotonergic and dopaminergic transmission and the expression of brain-derived neurotrophic factors in the 

hippocampus. Johnston et al63 reported that blood levels of omega-3 were signifi cantly below what is considered optimal in a sample of deployed Soldiers with mild 

depression. Although data are somewhat inconsistent 

regarding the benefi ts of omega-3s for brain/mental 

health,64 continuing assessment of this nutrient will help 

inform targeted strategies and interventions designed 

to improve cognitive performance, mood, and general 

brain health. Noteworthy is that in addition to a large 

proportion meeting the US Dietary Guidelines for fi sh, 

33.3% of study participants reported weekly intake of 

an omega-3 supplement. Whether this level of intake refl ects the widespread discussion of omega-3s throughout 

the DoD remains to be determined.

Beverage intake, particularly with regard to sodas, is a 

key dietary behavior that can infl uence energy balance 

and consequently, BMI and waist circumference. Of 

note, those who avoided drinking either diet or regular sodas were more likely to have high HES-5. Sugary 

beverages likely contribute to excess energy consumption and increased obesity,65 decreased satiety,66 and 

increased risk of developing type 2 diabetes and heart 

disease.67-69 Whereas artifi cial sweeteners may impair 

neural appetite regulation mechanisms, data also suggest that prolonged consumption may lead to increased 

body weight, obesity, and metabolic syndrome.70-72 Interestingly, in our study, 65.8% of those with an unhealthy waist circumference consumed either diet or 

regular sodas compared to only 34.2% of those who 

consumed neither type of soda beverage. Clearly, beverage intake behaviors are important to consider with 

regard to healthy body mass and health. Further investigations into how these dietary behaviors contribute to 

health and performance could inform the development 

of targeted campaigns and educational strategies to enhance positive dietary behaviors.

Dietary supplement use by military members is high,9,73,74

and supplements are universally available at the commissaries and exchanges of all military installations, as 

well as at convenience and package stores, retail stores, 

and some fi tness centers. Approximately 40% of our 

respondents reported regular multivitamin use, which 

is similar to the 2011 Health Related Behaviors Survey 

of Active Duty Military Personnel18 where 37.2% of 

military personnel reported daily use. In addition, those 

who took one or more supplements per week (healthpromoting, omega-3 fatty acids, and protein powders) 

were also more likely to have high HES-5 than those 

who did not. Although we cannot determine the motivation for supplement use in this population, previous 

research suggests individuals consumed supplements 

to improve or maintain overall health.75 Supplement users also tended to have lower BMIs, frequent physical 

activity, and moderate alcohol intake, all of which are 

refl ected in our research population.
74 http://www.cs.amedd.army.mil/amedd_journal.aspx

Most supplement users received their vitamins and minerals from food alone when compared to nonusers.76,77

Our research showed the majority of persons using 

health-promoting supplements were also the healthiest 

eaters. Therefore, one important message to disseminate throughout the Army is that supplements should 

not replace or make up for a poor quality diet. Unfortunately, popular media cater to Warfi ghters by claiming such products will enhance performance, maximize 

muscle strength, and build muscle. This is a particular 

concern given the many manufacturing violations found 

in half of the fi rms inspected during the US Food and 

Drug Administration investigation.78 An ongoing DoD 

initiative, Operation Supplement Safety, informs providers and Warfi ghters about safe supplement use.

Due to the diverse environments and extreme physical 

demands of military service, Warfi ghters must maintain 

a higher level of physical fi tness and greater physical 

work capacity than the civilian population.79 In particular, lower levels of cardiovascular fi tness, as measured 

by run times, have been consistently and strongly associated with injury risk in both military men and women.80,81 In this study, Soldiers who met aerobic exercise 

recommendations had more than 3 times the odds of being the healthiest eater than those who did not. Further, 

those who met the strength training recommendations 

had similar odds of being a healthy eater. Importantly, 

Soldiers who passed their APFT in the top quartile of 

those who passed were also more likely to be in the top 

HES-5 quartile than those who failed their APFT. The 

APFT measures fi tness components twice a year and ensures our Soldiers are prepared to meet the physical demands of the mission and minimize the likelihood of injury.79,82 The relationship between nutrition and exercise 

may be bidirectional. Brodney et al83 studied physically 

fi t and unfi t men and women and subsequently reported 

that those with higher fi tness levels consumed diets that 

were closer to meeting national dietary recommendations than the diets of their lesser fi t peers. Of key concern to a military population is suffi cient dietary intake 

that supports energy expenditure of sustained physical 

activity.

Strong associations between high HES-5 and GAT emotional, social, family, and spiritual dimension scores 

were found. Those in the top quartiles for these GAT 

dimensions were signifi cantly more likely to score in 

the highest HES-5 quartile. These fi ndings highlight 

the holistic complexity of human performance and are 

consistent with previous reports suggesting that optimal 

nutritional fi tness can assist in enhancing multiple CSF 

dimensions.1,51,52,54-56

Several limitations exist with this study. First, although 

the sample size is large, the data are self-reported. The 

limitations of using self-reported data are well documented: respondents tend to under-report weight and 

over-report height84 and waist circumference,85 and they 

also misreport their physical activity.86 Secondly, individuals who chose to have their data used for research 

purposes may have different characteristics than those 

who did not, which may affect the ability to generalize these results. Next, the relationships between HES-5 

and scores on emotional, social, family, and spiritual fi tness are not suffi ciently granular to characterize specifi c 

dimension components. Further research is needed to 

clarify the contribution of dietary behaviors to emotional, social, family, and spiritual fi tness. All of the logistic 

regression analyses examined the relationship between 

HES-5 and only one other variable at a time. Future analyses should utilize multivariate modeling to determine 

the relative importance of these predictors. Finally, due 

to limited question number, the HES-5 included only 

5 components of the diet, unlike the HEI-2005 which 

encompasses 12 items.31 Future studies should consider 

additional dietary patterns.

In summary, the relationship of dietary behaviors and 

multiple domains of human performance within the context of overall lifestyle habits and psychosocial health in 

a military population were examined. We found that the 

HES-5 is a useful index with which to characterize eating behaviors in a military population and that healthy 

eaters were more likely to engage in a constellation of 

appropriate dietary and activity behaviors and more 

likely to score well on the APFT.

RELEVANCE TO PERFORMANCE TRIAD

The Performance Triad components—nutrition, sleep, 

and activity—are intricately interrelated. An exquisite 

interplay exists between them: (1) sleep quality (and 

duration) affects nutrition through alterations in metabolism, cognitive decrements, and appetite4,53,87-90; (2) 

nutrition affects sleep,4,91,84,85 physical performance, recovery and fatigue51-56; and (3) physical fi tness affects 

appetite mechanisms, social health, sleep, cognitive 

performance, and mood.79,92-96 A recent review96 hypothesized that eating behavior and physical activity may 

share a common neurocognitive link since active individuals have an improved regulation of hunger and satiety mechanisms. Clearly, these relationships are critical 

to optimize health and performance and should be investigated and promoted as a holistic system. This study 

provides data regarding differences in nutrition behaviors and other lifestyle habits that highlight the need to 

provide education regarding the positive performance 

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 75

THE ARMY MEDICAL DEPARTMENT JOURNAL

benefi ts of good dietary behaviors and to provide targeted resources for ensuring optimal nutrition. The HES-5 

may be a useful index for characterizing dietary intake 

behaviors and would be a valuable index with which 

to measure nutrition behaviors in future Performance 

Triad interventions.

ACKNOWLEDGEMENTS

This research was supported by a grant from 

Comprehensive Soldier and Family Fitness (CSF2; 

HT9404-12-1-0017; F191GJ).

The authors appreciate the support and the review of 

this manuscript by LTC Daniel T. Johnston and LTC 

Sharon A. McBride, and gratefully acknowledge Josh 

Kazman for statistical support and Preetha Abraham 

for graphic assistance.

REFERENCES

1. Montain SJ, Carvey CE, Stephens MB. Nutritional 

Fitness. Mil Med. 2010;175(suppl 1):65-72.

2. McClung JP, Karl JP, Cable SJ, et al. Randomized, double-blind, placebo-controlled trial of 

iron supplementation in female soldiers during 

military training: effects on iron status, physical performance, and mood. Am J Clin Nutr. 

2009;90(1):124-131.

3. Parletta N, Milte CM, Meyer BJ. Nutritional modulation of cognitive function and mental health. J 

Nutr Biochem. 2013;24(5):725-743.

4. Lieberman HR. Nutrition, brain function and cognitive performance. Appetite. 2003;40(3):245-254.

5. Montain SJ, Young AJ. Diet and physical performance. Appetite. 2003;40(3):255-267.

6. Rodriguez NR, Di Marco NM, Langley S. American College of Sports Medicine position stand. Nutrition and athletic performance. Med Sci Sports 

Exerc. 2009;41(3):709-731.

7. Askew EW. Environmental and physical stress and 

nutrient requirements. Am J Clin Nutr. 1995;61(suppl 3):631S-637S.

8. Bedno SA, Li Y, Han W, et al. Exertional heat 

illness among overweight U.S. Army recruits 

in basic training. Aviat Space Environ Med. 

2010;81(2):107-111.

9. Deuster PA, Weinstein AA, Sobel A, Young AJ. 

Warfi ghter nutrition: current opportunities and advanced technologies report from a Department of 

Defense workshop. Mil Med. 2009;174(7):671-677.

10. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of 

body mass index among US adults, 1999-2010. 

JAMA. 2012;307(5):491-497.

11. Naghii MR. The importance of body weight and 

weight management for military personnel. Mil 

Med. 2006;171(6):550-555.

12. Schmitt JA. Nutrition and cognition: meeting the 

challenge to obtain credible and evidence-based 

facts. Nutr Rev. 2010;68 (suppl 1):S2-5.

13. Hanlon EC, Van Cauter E. Quantifi cation of sleep 

behavior and of its impact on the cross-talk between 

the brain and peripheral metabolism. Proc Natl 

Acad Sci. USA. 2011;108 (suppl 3):15609-15616.

14. Knutson KL, Van Cauter E, Zee P, Liu K, Lauderdale DS. Cross-sectional associations between 

measures of sleep and markers of glucose metabolism among subjects with and without diabetes: 

the Coronary Artery Risk Development in Young 

Adults (CARDIA) Sleep Study. Diabetes Care. 

2011;34(5):1171-1176.

15. He FJ, Nowson CA, Lucas M, MacGregor GA. Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: 

meta-analysis of cohort studies. J Hum Hypertens. 

2007;21(9):717-728.

16. Ness AR, Powles JW. Fruit and vegetables, and 

cardiovascular disease: a review. Int J Epidemiol. 

1997;26(1):1-13.

17. Steinmetz KA, Potter JD. Vegetables, fruit, and 

cancer prevention: a review. J Am Diet Assoc. 

1996;96(10):1027-1039.

18. Barlas FM, Higgins WB, Pfl ieger JC, Diecker 

K. 2011 Department of Defense Survey of Health 

Related Behaviors Among Active Duty Military 

Personnel. Fairfax, VA: ICF International; February 2013. Available at: http://www.murray.senate.

gov/public/_cache/fi les/889efd07-2475-40ee-b3b0-

508947957a0f/final-2011-hrb-active-duty-surveyreport.pdf. Accessed August 27, 2013.

19. Bray RM, Pemberton MR, Hourani LL, et al. 2008 

Department of Defense Survey of Health Related 

Behaviors Among Active Duty Military Personnel. Research Triangle Park, NC: RTI International; 2009. Available at: http://www.tricare.mil/

tma/2008HealthBehaviors.pdf. Accessed August 

27, 2013.

20. US Department of Health and Human Services. 

Healthy People 2010: Understanding and Improving Health. 2nd ed. Washington, DC: U.S. Government Printing Offi ce; 2000.

21. Haslam DW, James WPT. Obesity. Lancet. 

2005;366(9492):1197-1209.

22. WHO/FAO Expert Consultation on Diet, Nutrition and the Prevention of Chronic Diseases Diet, 

Nutrition and the Prevention of Chronic Diseases

[WHO Technical Report Series, No 916]. Geneva, 

Switzerland: World Health Organization; 2003. 

Available at: http://www.who.int/dietphysicalactiv

ity/publications/trs916/en/. Accessed February 5, 

2013.
76 http://www.cs.amedd.army.mil/amedd_journal.aspx

23. Marriott BM, ed, for the Committee on Military 

Nutrition Research, Institute of Medicine. Not Eating Enough: Overcoming Underconsumption of 

Military Operational Rations. Washington, DC: 

The National Academies Press; 1995. Available at: 

http://www.nap.edu/catalog.php?record_id=5002. 

Accessed February 15, 2013.

24. Greenwoood MRC, Oria M, eds, for the Committee 

on Dietary Supplement Use by Military Personnel, 

Institute of Medicine. Use of Dietary Supplements 

by Military Personnel. Washington, DC: The National Academies Press; 2008. Available at: http://

www.nap.edu/openbook.php?record_id=12095. 

Accessed February 15, 2013.

25. Seligman ME. Building resilience. Harv Bus Rev. 

2011;89(4):100-106, 138.

26. Peterson C, Park N, Castro CA. Assessment for 

the U.S. Army Comprehensive Soldier Fitness program: the Global Assessment Tool. Am Psychol. 

2011;66(1):10-18.

27. Firth KM, Smith K. A Survey of Multidimensional 

Health and Fitness Indexes. Mil Med. 2010;175(suppl 1):110-117.

28. Lester PB, McBride S, Bliese PD, Adler AB. Bringing science to bear: an empirical assessment of the 

Comprehensive Soldier Fitness program. Am Psychol. 2011;66(1):77-81.

29. Guenther PM, Reedy J, Krebs-Smith SM, Reeve 

BB, Basiotis PP. Development and evaluation of 

the Healthy Eating Index-2005: Technical Report. 

Alexandria, VA: Center for Nutrition Policy and 

Promotion, US Dept of Agriculture; 2007. Available at: http://www.cnpp.usda.gov/publications/

hei/hei-2005/hei-2005technicalreport.pdf. 

Accessed July 5, 2013.

30. Guenther PM, Casavale KO, Reedy J, et al. Update 

of the Healthy Eating Index: HEI-2010. J Acad 

Nutr Diet. 2013;113(4):569-580.

31. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet 

Assoc. 2008;108(11):1896-1901.

32. Guenther PM, Reedy J, Krebs-Smith SM, Reeve 

BB. Evaluation of the Healthy Eating Index-2005. J 

Am Diet Assoc. 2008;108(11):1854-1864.

33. Feskanich D, Rockett HR, Colditz GA. Modifying the Healthy Eating Index to assess diet quality in children and adolescents. J Am Diet Assoc. 

2004;104(9):1375-1383.

34. Bray RM, Hourani LL, Olmstead KLR, et al. 2005 

Department of Defense Survey of Health Related 

Behaviors Among Active Duty Military Personnel. 

Research Triangle Park, NC: RTI International; 

2006. Available at: http://www.dtic.mil/cgi-bin/

GetTRDoc?AD=ADA465678. 

Accessed August 27, 2013.

35. Dietary Guidelines for Americans, 2010. 7th ed. 

Washington, DC: US Dept of Agriculture, US 

Dept of Health and Human Services; 2010. Available at: http://www.cnpp.usda.gov/Publications/

DietaryGuidelines/2010/PolicyDoc/PolicyDoc.pdf. 

Accessed August 27, 2013.

36. Cronbach LJ. Coeffi cient alpha and the internal 

structure of tests. Psychometrika. 1951;16:38.

37. DeVellis RF. Scale Development Theory and Applications. 3rd ed. Thousand Oaks, CA: Sage Publications, Inc; 2012.

38. Moul DE, Mai E, Shablesky M, et al. The 2-item 

and 20-item versions of the Pittsburgh Insomnia 

Rating Scale (PIRS): design methods and initial 

modeling. Paper presented at: Annual Meeting of 

the World Psychiatric Association; November 29, 

2009; Melbourne, Australia.

39. Moul DE, Pilkonis PA, Miewald JM, Carey TJ, 

Buysse DJ. Preliminary study of the test-retest 

reliability and concurrent validities of the Pittsburgh Insomnia Rating Scale (PIRS). Sleep. 

2002;25:A246-A247.

40. Lentino CV, Purvis DL, Murphy KJ, Deuster PA. 

Sleep as a component of the Performance Triad: the 

importance of sleep in a military population. US 

Army Med Dep J. October–December 2013:97-107.

41. Garber CE, Blissmer B, Deschenes MR, et al. 

American College of Sports Medicine position 

stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fi tness in apparently 

healthy adults: guidance for prescribing exercise. 

Med Sci Sports Exerc. 2011;43(7):1334-1359.

42. Field Manual 7-22: Army Physical Readiness 

Training. Washington, DC: US Dept of the Army; 

October 26, 2012.

43. Army Regulation 600-9, The Army Weight Control 

Program. Washington, DC: US Dept of the Army; 

November 27, 2006.

44. Lemieux S, Prud’homme D, Bouchard C, Tremblay 

A, Despres JP. A single threshold value of waist 

girth identifi es normal-weight and overweight subjects with excess visceral adipose tissue. Am J Clin 

Nutr. 1996;64(5):685-693.

45. C JCS Instruction 3405.01: Chairman’s Total Force 

Fitness Framework. Washington, DC: Offi ce of the 

Chairman, Joint Chiefs of Staff; 2011. Available at: 

http://www.dtic.mil/cjcs_directives/cdata/unlimit/3405_01.pdf. Accessed July 24, 2013.

46. Chaplin K, Smith AP. Breakfast and snacks: associations with cognitive failures, minor injuries, accidents and stress. Nutrients. 2011;3(5):515-528.

47. Azadbakht L, Haghighatdoost F, Feizi A, Esmaillzadeh A. Breakfast eating pattern and its association with dietary quality indices and anthropometric measurements in young women in Isfahan. Nutrition. 2013;29(2):420-425.

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 77

THE ARMY MEDICAL DEPARTMENT JOURNAL

48. Deshmukh-Taskar P, Nicklas TA, Radcliffe JD, 

O’Neil CE, Liu Y. The relationship of breakfast 

skipping and type of breakfast consumed with overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome 

in young adults. The National Health and Nutrition 

Examination Survey (NHANES): 1999-2006. Public Health Nutr. October 3, 2012:1-10. [epub]

49. Armstrong LE, Casa DJ, Millard-Stafford M, Moran DS, Pyne SW, Roberts WO. American College 

of Sports Medicine position stand. Exertional heat 

illness during training and competition. Med Sci 

Sports Exerc. 2007;39(3):556-572.

50. Sawka MN, Burke LM, Eichner ER, Maughan 

RJ, Montain SJ, Stachenfeld NS. American College of Sports Medicine position stand. Exercise 

and fl uid replacement. Med Sci Sports Exerc. 

2007;39(2):377-390.

51. Beelen M, Burke LM, Gibala MJ, van Loon LJ. Nutritional strategies to promote postexercise recovery. 

Int J Sport Nutr Exerc Metab. 2010;20(6):515-532.

52. Hausswirth C, Le Meur Y. Physiological and nutritional aspects of post-exercise recovery: specifi c 

recommendations for female athletes. Sports Med. 

2011;41(10):861-882.

53. Res PT, Groen B, Pennings B, et al. Protein 

ingestion before sleep improves postexercise overnight recovery. Med Sci Sports Exerc. 

2012;44(8):1560-1569.

54. Shirreffs SM, Sawka MN. Fluid and electrolyte 

needs for training, competition, and recovery. J 

Sports Sci. 2011;29 (suppl 1):S39-S46.

55. Slater G, Phillips SM. Nutrition guidelines for 

strength sports: sprinting, weightlifting, throwing 

events, and bodybuilding. J Sports Sci. 2011;29 

(suppl 1):S67-S77.

56. Stellingwerff T, Maughan RJ, Burke LM. Nutrition 

for power sports: middle-distance running, track 

cycling, rowing, canoeing/kayaking, and swimming. J Sports Sci. 2011;29 (suppl 1):S79-S89.

57. Beelen M, Burke LM, Gibala MJ, van Loon LJ. Nutritional strategies to promote postexercise recovery. 

Int J Sport Nutr Exerc Metabol. 2010;20(6):515-532.

58. Flakoll PJ, Judy T, Flinn K, Carr C, Flinn S. 

Postexercise protein supplementation improves 

health and muscle soreness during basic military training in Marine recruits. J Appl Physiol. 

2004;96(3):951-956.

59. Harris WS, Von Schacky C. The Omega-3 Index: a 

new risk factor for death from coronary heart disease?. Prev Med. 2004;39(1):212-220.

60. US Food and Drug Administration. FDA announces qualifi ed health claims for omega-3 fatty 

acids [internet]. September 8, 2004. Available at: 

http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2004/ucm108351.htm. Accessed 

June 28, 2013.

61. Kang JX, Gleason ED. Omega-3 fatty acids and 

hippocampal neurogenesis in depression. CNS 

Neurol Disord Drug Targets. 2013;12(4):460-465.

62. Levant B. N-3 (omega-3) polyunsaturated fatty acids in the pathophysiology and treatment of depression: pre-clinical evidence. CNS Neurol Disord 

Drug Targets. 2013;12(4):450-459.

63. Johnston DT, Deuster PA, Harris WS, Macrae 

H, Dretsch MN. Red blood cell omega-3 fatty 

acid levels and neurocognitive performance in 

deployed U.S. servicemembers. Nutr Neurosci. 

2013;16(1):30-38.

64. Sinn N, Milte C, Howe PR. Oiling the brain: a review of randomized controlled trials of omega-3 

fatty acids in psychopathology across the lifespan. 

Nutrients. 2010;2(2):128-170.

65. McGuire S. Accelerating progress in obesity prevention: solving the weight of the nation. Adv Nutr. 

2012;3(5):708-709.

66. Pan A, Hu FB. Effects of carbohydrates on satiety: 

differences between liquid and solid food. Curr 

Opin Clin Nutr Metab Care. 2011;14(4):385-390.

67. de Koning L, Malik VS, Kellogg MD, Rimm EB, 

Willett WC, Hu FB. Sweetened beverage consumption, incident coronary heart disease, and biomarkers of risk in men. Circulation. 2012;125(14):1735-

1741, S1731.

68. Fung TT, Malik V, Rexrode KM, Manson JE, Willett WC, Hu FB. Sweetened beverage consumption 

and risk of coronary heart disease in women. Am J 

Clin Nutr. 2009;89(4):1037-1042.

69. Malik VS, Popkin BM, Bray GA, Despres JP, Willett 

WC, Hu FB. Sugar-sweetened beverages and risk 

of metabolic syndrome and type 2 diabetes: a metaanalysis. Diabetes Care. 2010;33(11):2477-2483.

70. Swithers SE, Davidson TL. A role for sweet taste: 

calorie predictive relations in energy regulation by 

rats. Behav Neurosci. 2008;122(1):161-173.

71. Yang Q. Gain weight by “going diet?” Artifi -

cial sweeteners and the neurobiology of sugar 

cravings: neuroscience 2010. Yale J Biol Med. 

2010;83(2):101-108.

72. Nettleton JA, Lutsey PL, Wang Y, Lima JA, Michos ED, Jacobs DR Jr. Diet soda intake and risk 

of incident metabolic syndrome and type 2 diabetes in the Multi-Ethnic Study of Atherosclerosis 

(MESA). Diabetes Care. 2009;32(4):688-694.

73. Deuster PA, Sridhar A, Becker WJ, Coll R, O’Brien 

KK, Bathalon G. Health assessment of U.S. Army 

Rangers. Mil Med. 2003;168(1):57-62.

74. Bovill ME, Tharion WJ, Lieberman HR. Nutrition 

knowledge and supplement use among elite U.S. 

Army soldiers. Mil Med. 2003;168(12):997-1000.
78 http://www.cs.amedd.army.mil/amedd_journal.aspx

75. Bailey RL, Gahche JJ, Miller PE, Thomas PR, Dwyer JT. Why US adults use dietary supplements. 

JAMA Intern Med. 2013;173(5):355-361.

76. Bailey RL, Fulgoni VL, 3rd, Keast DR, Dwyer JT. 

Dietary supplement use is associated with higher 

intakes of minerals from food sources. Am J Clin 

Nutr. 2011;94(5):1376-1381.

77. Bailey RL, Fulgoni VL III, Keast DR, Dwyer JT. 

Examination of vitamin intakes among US adults 

by dietary supplement use. J Acad Nutr Diet. 

2012;112(5):657-663.

78. Tsouderos T. Dietary supplements: manufacturing 

troubles widespread, FDA inspections show. Chicago Tribune [serial online]. June 30, 2012. Available 

at: http://articles.chicagotribune.com/2012-06-30/

news/ct-met-supplement-inspections-20120630_1_

dietary-supplements-inspections-american-herbalproducts-association. Accessed August 27, 2013.

79. Roy TC, Springer BA, McNulty V, Butler NL. 

Physical Fitness. Mil Med. 2010;175(suppl 1):14-20.

80. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and 

injury prevention in military populations. Sports 

Med. 1999;27(2):111-125.

81. Rauh MJ, Macera CA, Trone DW, Shaffer RA, 

Brodine SK. Epidemiology of stress fracture and 

lower-extremity overuse injury in female recruits. 

Med Sci Sports Exerc. 2006;38(9):1571-1577.

82. Lohi JJ, Huttunen KH, Lahtinen TM, Kilpelainen 

AA, Muhli AA, Leino TK. Effect of caffeine on 

simulator fl ight performance in sleep-deprived military pilot students. Mil Med. 2007;172(9):982-987.

83. Brodney S, McPherson RS, Carpenter RS, Welten 

D, Blair SN. Nutrient intake of physically fi t and 

unfi t men and women. Med Sci Sports Exerc. 

2001;33(3):459-467.

84. Elgar FJ, Stewart JM. Validity of self-report screening for overweight and obesity. Evidence from the 

Canadian Community Health Survey. Can J Public 

Health. 2008;99(5):423-427.

85. Bigaard J, Spanggaard I, Thomsen BL, Overvad K, 

Tjonneland A. Self-reported and technician-measured waist circumferences differ in middle-aged 

men and women. J Nutr. 2005;135(9):2263-2270.

86. Helmerhorst HJ, Brage S, Warren J, Besson H, 

Ekelund U. A systematic review of reliability and 

objective criterion-related validity of physical activity questionnaires. Int J Behav Nutr Phys Act. 

2012;9:103.

87. Afaghi A, O’Connor H, Chow CM. High-glycemicindex carbohydrate meals shorten sleep onset. Am J 

Clin Nutr. 2007;85(2):426-430.

88. Peuhkuri K, Sihvola N, Korpela R. Diet promotes sleep duration and quality. Nutr Rev. 

2012;32(5):309-319.

89. Knutson KL, Spiegel K, Penev P, Van Cauter E. 

The metabolic consequences of sleep deprivation. 

Sleep Med Rev. 2007;11(3):163-178.

90. St-Onge MP, Roberts AL, Chen J, et al. Short sleep 

duration increases energy intakes but does not 

change energy expenditure in normal-weight individuals. Am J Clin Nutr. 2011;94(2):410-416.

91. Energy drink consumption and its association with 

sleep problems among U.S. service members on a 

combat deployment – Afghanistan, 2010. MMWR. 

Morb Mortal Wkly Rep. 2012;61(44):895-898.

92. Barbour KA, Blumenthal JA. Exercise training 

and depression in older adults. Neurobiol Aging. 

2005;26 (suppl 1):119-123.

93. Cramer SR, Nieman DC, Lee JW. The effects of 

moderate exercise training on psychological wellbeing and mood state in women. J Psychosom Res. 

1991;35(4-5):437-449.

94. De Moor MH, Beem AL, Stubbe JH, Boomsma DI, 

De Geus EJ. Regular exercise, anxiety, depression 

and personality: a population-based study. Prev 

Med. 2006;42(4):273-279.

95. Driver HS, Taylor SR. Exercise and sleep. Sleep 

Med Rev. 2000;4(4):387-402.

96. Joseph RJ, Alonso-Alonso M, Bond DS, PascualLeone A, Blackburn GL. The neurocognitive connection between physical activity and eating behaviour. Obes Rev. 2011;12(10):800-812.

AUTHORS

Dr Purvis is Director, Strategic Operations and 

Special Projects, Consortium for Health and Military 

Performance, Dept of Military and Emergency Medicine, 

Uniformed Services University of the Health Sciences, 

Bethesda, Maryland.

Ms Lentino and Ms Murphy are Research Associates, 

Consortium for Health and Military Performance, 

Dept of Military and Emergency Medicine, Uniformed 

Services University of the Health Sciences, Bethesda, 

Maryland.

Dr Jackson is a Public Health Scientist, Public Health 

Assessment Program, Army Institute of Public Health, 

US Army Public Health Command, Aberdeen Proving 

Ground, Maryland.

Dr Deuster is Director and Professor, Consortium for 

Health and Military Performance, Dept of Military and 

Emergency Medicine, Uniformed Services University of 

the Health Sciences, Bethesda, Maryland.

NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS

CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
 October – December 2013 79

NUTRITIONAL DEFICIENCIES IN THE

TRAINING ENVIRONMENT

Unhealthy eating habits and nutritional defi ciencies are 

an increasing concern among Army personnel. Current 

literature shows that poor nutrition can affect susceptibility to injury and affect the Soldiers’ ability to carry 

out their missions.1-4 Overweight or obesity status, which 

may result from poor nutrition, degrades combat readiness because it puts Soldiers at risk for attrition, for other 

health problems, and has also increased the number of 

recruits who are ineligible to serve because of their body 

fat composition.5

According to the 2008 Survey of Health Related Behaviors for military personnel, only 17% of women and 14% 

of men reported consuming the USDA-recommended 

servings of fruits and vegetables per day.6

 This mirrors 

the general population of the United States: fewer than 

25% of Americans eat fruits and vegetables 5 or more 

times per day.7

 This suggests the majority of military 

personnel are not consuming the recommended nutrients for the average adult.8

Furthermore, Soldiers usually require increased dietary 

energy intake, especially during training as they maintain high levels of physical activity.1

 Soldiers expending 

more energy than they consume have a negative energy 

balance which results in chronic undernourishment.9

This is a concern because a diet lacking critical nutrients has a negative effect on health, injury, physical performance, and recovery from illness.1,9-11 For example, 

Wentz et al found that insuffi cient nutrient intake and 

The Importance of Leadership in Soldiers’

 Nutritional Behaviors: Results from the

 Soldier Fueling Initiative Program Evaluation

 Th eresa K. Jackson, PhD, MPH, CHES Sabriya D. Dennis, MS

 COL Sonya J. Cable, SP, USA Linda T. Vo, MPH, CHES

 Wana K. Jin, MPH Trish J. Prosser, PhD

 Ayanna Robinson, MPH Jess A. Rawlings, MS

ABSTRACT

Introduction: Improving Soldiers’ nutritional habits continues to be a concern of the US Army, especially 

amidst increasing obesity and high injury rates. This study examines leadership infl uence on nutritional behaviors within the context of the Soldier Fueling Initiative, a program providing nutrition education and improved 

dining facility menus to Soldiers in Basic Combat Training (BCT) and Advanced Individual Training (AIT).

Methods: A mixed methods design using surveys (N=486) and focus groups (N=112) was used to collect data 

at Fort Jackson, SC, and Fort Eustis, VA, in 2011.

Results: Survey results showed 75% of Soldiers in BCT believed their drill sergeant was helpful in making 

performance-enhancing food choices, and 86% agreed their drill sergeant believed it is important to eat for 

performance. Soldiers in AIT perceived their cadre as less helpful than their BCT drill sergeants and agreed 

less frequently that the AIT cadre believed it was important to eat for performance (P<.05). These measures 

of leader infl uence were signifi cantly associated with nutritional attitudes and behaviors in both BCT and AIT.

Focus groups revealed 5 key themes related to cadre infl uence and nutrition behavior (listed in order of most to 

least frequent): (1) cadre infl uence food choices through consequences related to selection, (2) cadre teach Soldiers how to eat, (3) cadre rush Soldiers to eat quickly to return to training, (4) cadre infl uence choice through 

example but often do not make healthy choices, and (5) cadre have no infl uence on food choices.

Comment: Leaders infl uence most Soldiers’ nutrition practices within the training environment, particularly 

within BCT. Given that leader infl uence can impact Soldiers’ attitudes and behaviors, it is critical that military 

leaders become knowledgeable about optimal nutrition practices to disseminate appropriate information to 

their Soldiers, avoid reprimand associated with trainees’ food choices, reinforce key messages associated with 

nutrition programming, and lead by example in their own food choices.
80 http://www.cs.amedd.army.mil/amedd_journal.aspx

chronic undernourishment were linked to increased 

rates of stress fractures in military recruits.4

Poor nutrition can also cause Soldiers to become overweight or obese. Approximately 51% to 61% of military 

personnel are overweight, and 12% are classifi ed as 

obese.12 Soldiers are required to maintain weight-forheight standards and to remain below a certain body 

fat percentage. There are reports of Soldiers using unhealthy means such as laxatives or sauna/rubber suits to 

meet those weight standards and avoid attrition based 

on body fat status.5

 Overweight and less fi t individuals 

also take longer to acclimatize to heat and are less tolerant of heat, which can affect mission readiness in hot 

climates.13

THE SOLDIER FUELING INITIATIVE

The Soldier Fueling Initiative (SFI) was designed to 

establish a fueling standard in initial military training 

(IMT) and improve Soldiers’ nutritional status. The SFI 

encompasses Department of Defense nutritional standards, performance nutrition education, menu development, and preparation and serving standards in order to 

optimize IMT Soldier fi tness and performance.14 The 

program includes 2 primary areas of implementation: 

Food Service Operations and Performance Nutrition 

Education.

The food service operation component of SFI consists 

of Go for Green labeling, performance-focused dining 

facility (DFAC) menus, and Fit Pick vending within Advanced Individual Training (AIT). Go for Green labeling is a nutritional recognition tool that provides pointof-decision prompts and allows Soldiers to make quick 

assessments of the menu options as they move through 

the food lines. Food items labeled in green are considered to be high performance and should be eaten often; 

items labeled in amber are moderate performance foods 

that should be eaten occasionally, and items labeled in 

red are performance-limiting and should only be consumed on rare occasions.14

The performance nutrition education component consists of a one-hour training course within the fi rst 2 

weeks of basic combat training (BCT). During this 

course, Soldiers receive information on the importance 

of eating for performance, utilizing the Go for Green 

labels in DFACs, and understanding how their bodies 

use food for fuel. The course, presented in a lecture format, is typically conducted by a drill sergeant or other 

cadre member. As a part of nutrition education, leaders 

receive SFI training on nutrition fundamentals, appropriate nutrition messaging, and instructing the trainees’ 

nutrition education course.

LEADER AND PEER INFLUENCE ON HEALTH 

BEHAVIORS

Throughout this article, the term “leader” refers to drill 

sergeants in BCT and to cadre members in AIT. Leaders are included in the SFI program delivery because 

leader and peer infl uence has the potential to play a role 

in improving the nutritional status of new recruits. The 

social ecological model (SEM) asserts that multiple 

levels of infl uence (individual, interpersonal, organizational, community, and policy) affect health behaviors.15

Interpersonal relationships, such as those with family, 

friends, and teachers, play a role in shaping one’s health 

behaviors. Bandura’s Social Cognitive Theory (SCT) 

also proposes that learning and behavior change occur 

through interactions with an individual’s social environment.16,17 One construct of SCT is observational learning, 

whereby people observe a behavior and then replicate it. 

Studies have also shown that this type of modeling is 

more effective when the observers consider the models 

to be similar to themselves.18

Health promotion programs frequently use opinion leaders to affect behavior change, and programs that use peer 

opinion leaders are generally more effective than those 

that do not.19 This type of infl uence has been used in 

church-based health promotion studies in which pastors 

communicate health messages to their congregants.20-22

Similarly, in the case of new Army recruits, a drill sergeant or other peers may serve as opinion leaders and 

role models that infl uence eating habits. In Glover and 

colleagues’ study, drill sergeant candidates stated that 

mentorship and role modeling were an important part of 

training new recruits.23 These leaders believe they have 

a strong infl uence on BCT Soldiers and try to lead by 

example. With regard to nutrition, drill sergeants stated 

they avoid eating unhealthy foods in front of Soldiers.23

SOLDIER FUELING INITIATIVE PROGRAM 

EVALUATION OVERVIEW

In 2011, the Army Institute of Public Health (AIPH), in 

collaboration with the IMT Center of Excellence (CoE), 

initiated a program evaluation of the SFI. The purposes 

of the SFI program evaluation were to better understand 

infl uences of Soldiers’ nutrition within the training environment, determine effectiveness and reception of 

program components, provide strategies for program 

improvement, and inform subsequent phases of the SFI 

evaluation. The evaluation was guided by 6 primary 

evaluation questions: 

1. What do Soldiers eat in IMT, and what guides 

their food choices? 

2. What is the reach (use and awareness) of the SFI? 

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION
 October – December 2013 81

THE ARMY MEDICAL DEPARTMENT JOURNAL

3. Is the SFI implemented as intended? 

4. What are Soldier perceptions regarding the SFI? 

5. What is the SFI’s effect on nutrition knowledge, 

perceptions regarding eating for performance, 

and eating habits? 

6. To what extent might any healthy behaviors 

obtained in IMT be sustained?

A subelement of evaluation Question 1 included a specifi c examination of leader infl uence on trainees’ nutrition behaviors. Specifi cally, the evaluation team assessed the following:

 To what extent are Army leaders helpful or unhelpful in making performance-enhancing food 

selections? 

 To what extent do Soldiers perceive that leaders think 

it is important to eat for performance? 

 What effect do leaders have on Soldiers’ 

food selection? 

 How does leader infl uence on nutrition 

practices vary across different phases of 

Army training?

To date, no studies have specifi cally examined 

how trainees’ perceptions of their leaders affect their nutritional attitudes and behavior in 

IMT, either positively or negatively. Given the 

potential for leaders to serve as an infl uence 

on nutrition practices, it is critical to understand how, if at all, training leaders help their Soldiers 

choose healthy, performance-oriented foods or hinder 

them from making such choices.

METHODS

Prior to data collection, both the US Army Public Health 

Command Public Health Review Board and the Center 

for Accessions Research Institutional Review Board 

(I RB) reviewed and approved this evaluation. The study 

used both quantitative (survey) and qualitative (focus group) methods among Soldiers in BCT and AIT. 

A mixed methods design combining both quantitative 

and qualitative methods is benefi cial because it leads to 

more robust data than a singular method.24,25

Power Analyses

The IMT CoE Experimentation and Analysis Element 

identifi ed 6 companies of Soldiers at Fort Jackson, SC, 

and 2 companies of Soldiers at Fort Eustis, VA, to participate in the evaluation. The IMT CoE established operational orders to facilitate data collection during October thru November 2011. A total of 598 Soldiers (319 

BCT Soldiers and 279 AIT Soldiers) participated in the 

evaluation. The IRB waived written consent for surveys 

because consent forms would have been the only record 

of study participation; however, Soldiers were given a 

consent briefi ng prior to data collection and were informed that their participation was completely voluntary. Soldiers within the focus groups provided written 

informed consent. Table 1 provides an overview of how 

the sample participated in data collection efforts. All 

BCT surveys (n=247) were administered to Soldiers at 

Fort Jackson in October 2011. The AIT surveys were 

administered at Fort Eustis (November 2011, n=239) 

where the SFI had recently been implemented. A priori 

power analyses revealed this sample was of suffi cient 

size to detect small to moderate effects between groups. 

The AIPH team also conducted focus groups (methodology described below) with a convenience sample of 

BCT Soldiers (n=72) and AIT Soldiers (n=40) at Fort 

Jackson in October 2011.

Survey Methods

The AIPH team distributed anonymous short paper 

questionnaires to Soldiers in both BCT and AIT. Response rates for the participating companies were nearly 

100% (likely because leaders encouraged Soldiers to 

participate), surveys were short (less than 10 minutes 

to complete), data collection was anonymous, and the 

topic was low- to no-risk. The questionnaires asked 

about a variety of constructs including demographics; 

use and perceived helpfulness of various SFI program 

components (eg, Go for Green labels, nutrition education); changes in weight, lean muscle mass, physical performance, and mental performance over time; nutrition 

behaviors (eg, frequency of eating lean protein, fruits, 

vegetables, low fat dairy); and general attitudes about 

nutrition and eating for performance. The surveys also 

contained questions designed to assess Soldiers’ perceived level of leader helpfulness (1=not at all helpful, 

5=very helpful) in making performance-enhancing food 

choices and the extent to which Soldiers agreed that IMT 

leaders believed it was important to eat for performance 

(1=strongly disagree, 5=strongly agree).

Table 1. Participation in Soldier Fueling Initiative Program Evaluation by 

Initial Military Training Class Type, Site, and Source of Data Collected.

Data source

Surveys

(N=486)

Focus

Groups

(N=112)

Basic Combat Training (N=319)

All Soldiers from 3 companies at Fort Jackson, SC n=247

Sample of Soldiers from 1 company at Fort Jackson, SC n=72

Advanced Individual Training (N=279)

All Soldiers from 2 companies at Fort Eustis, VA n=239

Sample of Soldiers from 2 companies at Fort Jackson, SC n=40
82 http://www.cs.amedd.army.mil/amedd_journal.aspx

Focus Group Methods

The evaluation team conducted 6 BCT focus groups 

based on strata by gender (male and female) and performance (high, average, and low performance based on 

physical fi tness test scores). The team conducted 4 AIT 

focus groups on gender strata only (ie, 2 groups of men, 

2 groups of women). 

The structured focus groups assessed Soldiers’ experiences within the dining facilities, SFI effect on eating 

behavior, barriers to SFI implementation, and suggestions for program improvement. The BCT and AIT 

focus group guides consisted of 10 open-ended questions each. To specifi cally gauge how leaders affected 

their nutrition behaviors, moderators asked participants, 

“how do Army cadre infl uence your eating?”

A trained AIPH facilitator led each focus group, and a 

note-taker took extensive notes throughout the session. 

Each focus group was audio-recorded. Before the focus 

group or interview began, the facilitator explained the 

purpose and procedure of the focus group, encouraged 

open discussion within the group, informed the participants that their participation and comments would remain anonymous, and asked for verbal consent to audio-record the session. Subcontractors transcribed the 

focus groups’ audio recordings verbatim and omitted 

any identifying information.

Data Analyses

All survey data were managed and analyzed using the 

IBM SPSS Statistics (V 21.0) application (IBM Corp, 

Chicago, IL). The analysis team generated frequencies 

and descriptive statistics on perceived leader helpfulness 

and Soldiers’ level of agreement that leaders believe it is 

important to eat for performance. Chi square and independent t tests were used to examine differences in these 

measures between BCT and AIT Soldiers. Measures of 

leader infl uence were then additionally correlated with 

other constructs of interest in the evaluation, listed in Table 2, by means of Pearson product-moment correlations. 

Type I error rates (P values) of .05 or lower designated 

statistically signifi cant relationships for all analyses.

The AIPH qualitative analysis group, which consisted 

of three, 2-analyst teams, used NVivo 9 qualitative data 

analysis software (QSR International Proprietary Ltd, 

Doncaster, Australia) for focus group data management 

and analysis. The analysis group used a team-based coding and constant-comparison approach, which consists 

of an iterative process of revising the codebook to refl ect 

emerging themes and applying the codes systematically 

across teams.26 In order to achieve coding reliability, the 

analysts of each team reviewed, discussed, and established consensus on each code, and each team reviewed 

the work of another team. The team then summarized 

results and extracted example quotes to illustrate each 

theme for reporting.

RESULTS

Survey Results

A total of 486 Soldiers completed the survey, of whom 

398 (82%) were male, and 87 (18%) were female. The average age of respondents was 21.3 ± 4.5 years. Additional survey sample demographics are included in Table 3.

Perceived helpfulness of leaders in making performance-enhancing food choices was signifi cantly associated with Soldiers’ level of agreement that their leader 

believed it was important to eat for performance in both 

BCT (r=0.343, P<.01) and AIT (r=0.470, P<.01). Although measures are correlated, moderate effect sizes 

indicate they are measures of two distinct concepts; 

therefore, results from each construct are reported 

independently.

PERCEIVED LEADER HELPFULNESS OF IN MAKING 

PERFORMANCE-ENHANCING FOOD CHOICES 

The majority of BCT Soldiers (75%) responded that 

their leader was somewhat or very helpful in choosing performance-enhancing foods while the majority 

of AIT Soldiers (56%) were neutral (Table 4). Observed 

differences between BCT and AIT were statistically 

signifi cant (χ2

=125.365, df=4, P<.0001).

In both BCT and AIT, this perceived level of helpfulness was signifi cantly associated with several 

constructs related to nutrition (Table 5). In BCT, as 

perceived helpfulness increased, frequency of use 

of Go for Green labels (r=0.173, P<.001), frequency of selecting performance-oriented food choices 

(r=0.169, P<.001), and positive attitude toward eating 

for performance (r=0.131, P<.05) also increased. In AIT, 

as perceived helpfulness increased, frequency of use of 

Go for Green labels (r=0.154, P<.05), frequency of selecting “green” items from the DFAC (r=0.135, P<.05), 

frequency of selecting performance-oriented food 

choices (r=0.255, P<.05), level of perceived knowledge 

about eating for physical performance (r=0.146, P<.05), 

level of perceived knowledge about eating for cognitive 

performance (r=0.178, P<.001), and positive attitude 

toward eating for performance (r=0.225, P<.001) also 

increased. Level of leader helpfulness was not associated with frequency of selecting green, amber, or red 

items from the DFAC in BCT or frequency of selection 

of amber, red, or performance-limiting foods in AIT.

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION
 October – December 2013 83

THE ARMY MEDICAL DEPARTMENT JOURNAL

SOLDIERS’ LEVEL OF AGREEMENT THAT LEADERS 

BELIEVE IT IS IMPORTANT TO EAT FOR 

PERFORMANCE

Eighty-six percent of BCT Soldiers and 45% of AIT 

Soldiers agreed or strongly agreed with the statement 

that their leaders believe it is important to eat for performance (Table 4). Observed differences between BCT 

and AIT were statistically signifi cant (χ2

=146.445, df=4, 

P<.0001). As level of agreement with this statement 

increased, frequency of using Go for Green labels 

(r=0.276, P<.001), frequency of selecting “green” items 

from the DFAC (r=0.179, P<.001), frequency of selecting performance-oriented food choices (r=0.383, 

P<.001), and positive attitude toward eating for performance (r=0.268, P<.001) also increased in BCT 

(Table 5). Within AIT, as agreement with this statement 

increased, frequency of selecting performance-oriented food choices (r=0.235, P<.001), level of perceived 

Table 2. Key Constructs of Interest Within the Soldier Fueling Initiative Program Evaluation.

Construct of Interest Operationalization Characteristics of Construct

Frequency of use of Go 

for Green labels in the 

DFAC

How frequently do you use “Go for Green” labeling when 

considering food choices in the DFAC?

Responses: every meal (5); once a day (4); a few times a 

week (3); about once a week (2); never (1)

Higher score=higher frequency of use.

Analyses run independently for BCT and AIT.

Frequency of selection 

of food with red labels, 

amber labels, and 

green labels in the 

DFAC

How frequently do you select each of the following in 

the DFAC?

Food with green labels; food with amber labels; food 

with red labels

Responses for each variable: 3+ times a day (5); 1-2 times 

a day (4); a few times per week (3); about once a week 

(2); rarely/never (1); I don’t know (user missing)

Higher score=higher frequency of selection.

Analyses run separately for each classification of labels.

Analyses run independently for BCT and AIT.

Frequency of selecting 

performance-oriented 

food choices in BCT 

and AIT

Composite measure of the following items:

How frequently do you select each of the following in 

the DFAC?

Lean meats and proteins; low fat dairy; fruits (fresh, 

canned, dried); vegetables (hot line or salad bar)

Responses for each variable: 3+ times a day (5); 1-2 times 

a day (4); a few times per week (3); about once a week 

(2); rarely/never (1); I don’t know (user missing)

Responses summed across the 4 categories 

of foods (range: 4-20).

Higher scores=Higher frequency of selection 

of performance-oriented choices.

Cronbach α=0.572 for BCT and 0.680 for AIT.

Analyses run independently for BCT and AIT.

Frequency of selecting 

performance-limiting 

food choices in AIT

Composite measure of the following items:

How frequently do you select each of the following in 

the DFAC?

Fried foods; sweets; snack foods; sugary drinks; 

energy drinks

Responses for each variable: 3+ times a day (5); 1-2 times 

a day (4); a few times per week (3); about once a week 

(2); rarely/never (1); I don’t know (user missing)

Responses summed across the 5 categories 

of foods (range: 5-25).

Higher scores=Higher frequency of selection 

of performance-limiting choices in AIT.

Cronbach α=0.689 for AIT.

Analysis for AIT only.

Level of perceived knowledge regarding eating 

for performance

To what extent do you agree or disagree with each of the 

following statements?

 I know what to eat to optimize my cognitive 

performance.

 I know what to eat to optimize my physical 

performance.

Strongly disagree (1); Disagree (2); Not sure (3); Agree (4); 

Strongly agree (5)

Analyses run independently for each category 

of knowledge.

Analysis for AIT only.

Positive attitude toward 

eating for performance 

in BCT/AIT

Composite measure of the following items:

To what extent do you agree or disagree with each of the 

following statements?

 I made a signifi cant effort to eat for performance 

in BCT/AIT.

 Eating quality foods is essential to optimal performance in BCT/AIT.

 I will strive to eat for performance during my career 

as a Soldier.

 In order to perform as a Soldier, I need to think like 

an athlete. 

Strongly disagree (1); Disagree (2); Not sure (3); Agree (4); 

Strongly agree (5)

Responses summed across the 4 items 

(range: 5-20).

Higher scores = Higher level of agreement 

with positive attitudes toward eating for 

performance in BCT or AIT.

Cronbach α=0.698 for BCT and 0.804 for AIT.
84 http://www.cs.amedd.army.mil/amedd_journal.aspx

knowledge about eating for physical performance 

(r=0.254, P<.001), level of perceived knowledge 

about eating for cognitive performance (r=0.263, 

P<.001), and positive attitude toward eating for performance (r=0.336, P<.001) also increased. Level 

of agreement with this statement was not associated 

with frequency of selecting amber or red items from 

the DFAC in BCT or frequency of use of Go for 

Green labels, frequency of selection of green, amber 

or red items from the DFAC, or frequency of selection of performance-limiting food choices in AIT.

Focus Group Results

Seventy-two Soldiers participated in the BCT focus 

groups, of whom 37 (51%) were male and 35 (49%) 

were female. Forty Soldiers participated in the AIT 

focus groups, and the proportion of men and women 

was equivalent.

Results of the 10 focus groups revealed 5 key themes 

related to leader infl uence on eating behavior within 

the training environment:

1. Leaders infl uence food choices through 

consequences related to selection.

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

Table 3. Demographic Characteristics of Soldier Fueling Initiative 

Program Evaluation Survey Sample in Basic Combat Training and 

Advanced Individual Training.

Characteristic BCT

N=247

AIT

N=239

Total

N=486

Gender [n(percentage of N)]a,b

Male 170 (69.1%) 228 (95.4%) 398 (82.1%)

Female 76 (30.9%) 11 (4.6%) 87 (17.9%)

Age (mean±SD, year)c 21.9±4.92 20.7±3.96 21.3±4.50

Weight category

[n(percentage of N)]b,d

Underweight 1 (0.4%) 3 (1.3%) 4 (0.8%)

Normal weight 144 (59.3%) 171 (72.2%) 315 (65.6%)

Overweight 92 (37.9%) 58 (24.5%) 150 (31.3%)

Obese 6 (2.5%) 5 (2.1%) 11 (2.3%)

BMI [mean±SD, kg/m2]

e 24.4±2.56 23.7±3.00 24.0±2.81

a. Gender distribution differed significantly across BCT ad AIT (χ2=55.15, df=1, 

P<.001)

b. All percentages reported are valid percentages.

c. Mean age differed significantly across BCT and AIT (t=2.7963, df=479, 

P<.01).

d. Weight category distribution differed significantly across BCT and AIT 

(χ2

=11.04, df=3, P=.0115); Category: underweight (BMI <18.5), normal 

weight (18.5-24.9), overweight (25.0-29.9), obese (>30.0).

27

e. Mean BMI differed significantly across BCT and AIT (t=2.7545, df=478,

P<.01).

Table 4. Frequency distribution of responses to the statements: “To what extent is your leader helpful or 

unhelpful in making performance-enhancing food choices?” (1=very unhelpful, 5=very helpful) and “My drill 

sergeant/cadre members believe(s) it's important to eat for performance.” (1=strongly disagree, 5=strongly 

agree) (N=486).

BCT (N=247)

n (percentage of N)f

AIT (N=239)

n (percentage of N)f

Total (N=486)

n (percentage of N)f

Please rate the extent to which your leadera is helpful or unhelpful in making performance-oriented 

choices.b

Very unhelpful 5 (2.1%) 28 (11.9%) 33 (6.9%)

Somewhat unhelpful 7 (2.9%) 15 (6.4%) 22 (4.6%)

Neutral 49 (20.2%) 132 (56.2%) 181 (37.9%)

Somewhat helpful 74 (30.5%) 38 (16.2%) 112 (23.4%)

Very helpful 108 (44.4%) 22 (9.4%) 130 (27.2%)

Mean ± SDc 4.12±0.967 3.05±1.04 3.59±1.138

Level of agreement or disagreement that leaders 

believe it is important to eat for performance.d

Strongly disagree 1 (0.4%) 11 (4.6%) 12 (2.5%)

Disagree 6 (2.4%) 22 (9.3%) 28 (5.8%)

Not Sure 27 (11.0%) 98 (41.4%) 125 (25.9%)

Agree 62 (25.3%) 80 (33.8%) 142 (29.5%)

Strongly agree 149 (60.8%) 26 (11.0%) 175 (36.3%)

Mean±SDe 4.44±0.815 3.37±0.960 3.91±1.036

a. Leader refers to drill sergeants in the BCT survey and to cadre in the AIT survey.

b. Level of helpfulness or unhelpfulness response distributions differed significantly across BCT and

AIT (χ2

=125.365, df=4, P<.0001).

c. Mean level of helpfulness differed significantly between BCT and AIT (t=11.6597, df=476, P<.0001).

d. Level of agreement or disagreement response distributions differed significantly across BCT and AIT (χ2

=146.445, df=4, 

P<.0001).

e. Mean level of agreement differed significantly between BCT and AIT (t=13.2067, df=480, P<.0001).

f. All percentages reported are valid percentages.
 October – December 2013 85

THE ARMY MEDICAL DEPARTMENT JOURNAL

2. Leaders teach Soldiers how to eat.

3. Leaders rush Soldiers to eat quickly in order to 

return to training.

4. Leaders infl uence choice through example but 

often do not make the healthy choice.

5. Leaders have no infl uence on food choices.

Table 6 provides an overview of the number of focus 

groups in which each theme emerged, the total number 

of times that Soldiers within the 10 groups made a comment consistent with each theme, and direct quotes that 

exemplify the theme.

When asked how leaders infl uenced their eating habits, 

Soldiers within 9 of the 10 focus groups made 25 references to having experienced negative consequences 

as a result of their food choices, including the amounts 

of food and the types of food they selected. The consequences included being forced to eat, being punished 

with physical activity (eg, doing push-ups), and psychological repercussions such as being made to feel guilty 

or humiliated. In all 10 of the focus groups, Soldiers 

mentioned their leaders taught them how to eat. Most 

(n=18) of the 19 references within this theme suggested 

cadre instructed the Soldiers to select 

the healthiest food options, except in 

one BCT group. In this instance the 

Soldier expressed his drill sergeant instructed him that it did not matter what 

he ate as long as he could keep up his 

physical performance. In all 6 of the 

BCT focus groups and one AIT focus 

group, Soldiers talked about their leaders rushing them to eat and fi nish their 

meals in a minimum amount of time. 

The Soldiers also discussed not having the time to taste their food or not 

being able to eat enough food in the 

allowed time period to keep them full 

until the next meal. Five of the Soldier 

focus groups referenced the fact that 

their leaders led by example but were 

not always effective role models for 

eating in the DFACs or eating healthy 

foods. A number of the Soldiers complained that cadre members would 

purchase fast food and eat it in front 

of the AIT and BCT Soldiers. Soldiers 

perceived this as hypocritical.

Soldiers in 3 groups made a total of 

4 references that their leaders did not 

infl uence the way the Soldiers ate in 

any capacity. These Soldiers stated that they were not 

concerned with repercussions and that they would eat 

whatever they wanted to eat regardless of what their 

cadre told them to do. 

COMMENT

Although there were a few references in the focus groups 

that leaders do not affect eating practices, both survey 

and focus group results suggest BCT drill sergeants and 

AIT cadre infl uence most Soldiers’ nutrition practices 

within IMT to some extent. Overall, two-thirds of the 

survey sample agreed or strongly agreed that their leaders believed it is important to eat for performance, and 

more than half reported their leaders were helpful or 

very helpful in making performance-enhancing food 

choices. This is consistent with past research in similar 

populations demonstrating leaders’ infl uence on health 

behaviors (eg, among college athletes who look to trainers and coaches for nutrition information).28-30 Focus 

group results suggest Soldiers fi nd it particularly useful when cadre members teach them how and what to 

eat to optimize their performance, especially as it relates to the day’s activities or the Army Physical Fitness 

Test (APFT). Various studies have used skill building 

as part of an intervention to improve dietary habits, and 

Table 5. Pearson product-moment correlation coeffi cients of perceived level of 

leadera

 helpfulness in making performance-enhancing food choices and level of 

agreement that leaders believe it is important to eat for performance with various 

additional constructs of interest to the Soldier Fueling Initiative program evaluation.

Perceived level of leader 

helpfulness in making 

performance-enhancing 

food choices

Level of agreement that 

leaders believe it is important to eat for performance

BCT

N=247

AIT

N=239

BCT

N=247

AIT

N=239

Frequency of using Go for Green 

labels 0.173b 0.154c 0.276c 0.014

Frequency of selecting "green" 

items from the DFAC 0.100 0.135c 0.179c 0.115

Frequency of selecting "amber" 

items from the DFAC -0.020 0.100 -0.008 0.100

Frequency of selecting "red" items 

from the DFAC -0.035 0.096 -0.094 0.096

Frequency of selecting performance-oriented food choices 0.169b 0.255c 0.383c 0.235c

Frequency of selecting performance-limiting food choices 0.056 0.070

Level of perceived knowledge 

regarding eating for physical 

performance

0.146c 0.254c

Level of perceived knowledge 

regarding eating for cognitive 

performance

0.178b 0.263c

Attitude toward eating for performance in BCT or AIT 0.131c 0.225b 0.268c 0.336c

a. Leader refers to drill sergeants in the BCT survey and to cadre in the AIT survey.

b. Correlation is statistically significant at P<.001.

c. Correlation is statistically significant at P<.05.
86 http://www.cs.amedd.army.mil/amedd_journal.aspx

these tangible skills may be more useful than knowledge alone.28,29 Moreover, Bandura asserts, “Motivation 

is enhanced by helping people to see how habit changes 

are in their self-interest and the broader goals they value highly.”17 The IMT leaders are encouraged not only 

to educate their Soldiers on nutrition, but also to build 

skills regarding how to eat for performance and use motivational tactics to drive the desired behavior.31-33

Signifi cant differences existed in Soldiers’ perceptions 

of leader infl uence between BCT and AIT. Three times 

as many BCT Soldiers as AIT Soldiers reported their 

leaders were helpful or very helpful in making performance-enhancing food choices, and nearly twice as 

many BCT Soldiers as AIT Soldiers agreed that leaders believe it is important to eat for performance. While 

there are several potential explanations for this fi nding, 

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

Table 6. Themes emerging from focus groups conducted with Initial Military Training Soldiers when asked, “How do Army cadre 

members infl uence your eating?”

Theme Number of groups 

in which theme 

was mentioned 

(N=10)

Total number of 

references to the 

theme within the 

group

Examples of Soldier quotes for each theme

Leaders influence food 

choices through consequences related to 

selection

9 25 ... we get yelled at because we don’t eat everything on our plate so 

that makes us eat a whole bunch more and stuff ourselves.

BCT participant

If they see certain people they’ll heckle certain people in the cafeteria... They never tell us we can’t eat anything, they’re just going to 

make you feel like dirt. You know, “are you sure you should be eating that, fatty? You failed your PT and do you really need that?”

BCT participant

[My Drill Sergeant] figured 44 push-ups a person for one piece of 

cake.

BCT participant

Leaders teach Soldiers how to eat 10 19 Even though they had to pay for meals, [the Drill Sergeants] would 

eat with us, and they would be like, ‘You know, I see you getting that 

cheeseburger right there. You know you got a PT test coming up.’ 

They would, you know, influence us drastically.

AIT participant

Now, in basic, I had a Drill Sergeant and he was really, really healthy, 

working out, eating healthy, and so, he told us kidney beans, wheat 

bread, stuff like that was healthier.

AIT participant

Leaders rush Soldiers 

to eat quickly in 

order to return to 

training

7 19 Oh yeah. What they say, ‘eat now, taste it later.

AIT participant

...we'll go to sit down and even though we just sat down, he'll be like, 

“Alright you got three minutes to eat everything on your plate” when 

we just sat down with a full plate of food.

BCT participant

I believe the Drill Sergeants ... try to rush you out sometimes depending on what we got going so you won't get all of the food we would 

like to get.

BCT participant

They tell you, “You don’t need to taste it. You can just throw it up and 

taste it later.”

BCT participant

Leaders influence 

choice through 

example but often do 

not make the healthy 

choice

5 14 I was riding with a Drill Sergeant the other day and I was with one 

of my battle buddies, they had to go somewhere, and the Drill Sergeant stopped by Taco Bell and I'm thinking to myself “What now?”

BCT participant

... why would you take advice from somebody that's picking on you and 

then brings you Burger King, orders Pizza Hut... Eating the chocolate cake... you know, it’s kind of hypocritical.

BCT participant

I just hate the fact that they eat the stuff that we're supposedly not 

allowed to in front of us like Skittles.

BCT participant

Leaders have no influence on food choices 3 4 I actually just learned to kind of ignore the Drill Sergeants when it 

comes to food because honestly they just give you a hard time.

BCT participant

The Drill Sergeants, they could say something, but unless it’s physically something I can’t eat, I’m going to eat it anyway.

BCT participant
 October – December 2013 87

THE ARMY MEDICAL DEPARTMENT JOURNAL

the disparity warrants additional research. Within BCT, 

drill sergeants are involved in instructing the Performance Nutrition Education course, which may increase 

the extent to which Soldiers perceive them as information brokers or resources related to nutrition information. Furthermore, Soldiers within BCT are under more 

direct supervision and may spend more time with their 

drill sergeants than Soldiers in AIT spend with their 

cadre because of the nature of the training type and 

phase of IMT.34 The physical demands of BCT may also 

be higher than those of AIT, possibly infl uencing the extent to which BCT leaders emphasize the need to eat for 

performance or to consider the day’s duties when making food choices. That said, proper nutrition is essential 

for cognitive performance in addition to physical performance.35-38 Although the duties and demands of AIT 

may differ from those of BCT, it will be important for 

AIT cadre and military leaders who are responsible for 

Soldiers in more cognitively demanding roles to showcase the relationship between nutrition and the ability to 

perform intellectually as well as physically.

As levels of perceived helpfulness of leaders in making 

performance enhancing food choices and agreement 

that leaders believe it is important to eat for performance increased, so too did a variety of relevant SFI 

outcomes. For example, Soldiers who reported higher 

levels of leader helpfulness in making performanceenhancing food choices also reported higher frequency 

of use of Go for Green labels, higher frequency of selecting performance-oriented food choices, a greater 

positive attitude and commitment toward eating for performance, and higher levels of self-reported knowledge 

regarding what to eat for physical and cognitive performance. Correlation coeffi cients with these outcomes indicated small to moderate effect sizes suggesting that in 

addition to leader infl uence, there are other factors that 

affect nutritional attitudes and behavior. This is consistent with ecological models of health behavior which assert there are numerous infl uences to behavior.15 Despite 

small to moderate effect sizes, these fi ndings suggest if 

leaders develop strategies to improve their helpfulness 

in assisting Soldiers to make performance-enhancing 

choices and communicate to their Soldiers that they believe it is important to eat for performance, it could be 

expected that Soldiers will experience at least slight improvements in their nutritional attitudes and behaviors. 

Survey fi ndings suggest leader infl uence is most relevant for positive behaviors (eg, frequency of use of Go 

for Green labels, frequency of selecting performanceenhancing choices, positive attitudes toward nutrition) 

and has no signifi cant association with negative behaviors (eg, selecting “red” foods from the DFAC in BCT 

or AIT, selecting performance-limiting food selections 

in AIT). In other words, data suggest that even as helpfulness and perceptions that eating for performance is 

important to their leaders increased, Soldiers’ consumption of performance-limiting choices did not decrease. 

This sentiment was echoed in a few focus group quotes 

stating that Soldiers were going to eat what they wanted 

despite what their leaders said. Focus groups further 

revealed that the most common theme associated with 

cadre effect on nutrition was that military leaders often issue consequences associated with negative food 

choices within IMT, and BCT in particular. Previous 

literature suggests punishment in the form of ostracism 

may lead to negative emotional and psychological reactions which can impair one’s ability to self-regulate 

and self-monitor, which are required elements for controlled eating.39 Because positive role modelling may be 

a better method for improving diet than punishment or 

attempts to control another person’s diet, IMT leaders 

should be cautioned against controlling choices or using 

punishment to guide Soldiers’ food selection and, rather, should be encouraged to model and support desired 

behaviors.40 Based on fi ndings from this evaluation, this 

strategy is receiving increased emphasis within the IMT 

Drill Sergeants School.

Recent research reports drill sergeant candidates believe 

they are role models for Soldiers and try to avoid eating 

certain foods in front of their Soldiers.23 Our fi ndings 

suggest Soldiers perceive leaders are examples in the 

area of nutrition; however, Soldiers indicated that their 

leaders did not always serve as the most effective role 

models in this area. This may be further refl ected by 

survey results indicating that nearly a third of Soldiers 

in IMT did not agree that their leaders believed it was 

important to eat for performance. There were several 

references to leaders going to fast food establishments, 

and some Soldiers commented that leaders were hypocritical regarding nutrition because they would eat the 

foods they told Soldiers not to eat. The importance of 

effective role models in observational learning is a key 

aspect of several health behavior theories, the Social 

Cognitive Theory in particular.17 Therefore, leaders are 

encouraged to demonstrate positive nutrition practices 

for their Soldiers and to engage in the behaviors they 

want to see in their Soldiers.

Lastly, focus groups revealed that Soldiers in BCT were 

frequently rushed to consume as much food as possible 

in as short a period of time as possible in order to return to physical training. Studies of children and school 

lunches have shown that eating speed is related to the 

loss of control with regard to food intake as well as obesity.41 Insuffi cient time allocated for meals may lead to 

overeating. The importance of physical training within 
88 http://www.cs.amedd.army.mil/amedd_journal.aspx

IMT, and BCT in particular, is indisputable. However, it 

is equally important for Soldiers to develop positive nutritional practices and habits during training. Initial Military Training leaders must prepare Soldiers for future 

success by providing them with a reasonable amount of 

time in which to eat during BCT, as mealtime provides 

Soldiers with the opportunity to refuel for performance.

Conclusions from this study are limited because it used 

only self-report data at one point in time. No causal inferences can be made between any constructs of interest. Th e study used a convenience sample from only 2 

locations (one BCT and one AIT) with a relatively small 

sample size, so results cannot be generalized to the entire 

training community or the military as a whole. Analyses did not control for demographic diff erences between 

BCT and AIT, and some constructs (eg, selection of performance-limiting choices, perceived level of knowledge 

regarding what to eat for physical and cognitive performance) were only measured on the AIT survey, so no 

comparisons could be made with BCT Soldiers. 

To the best of our knowledge, this is the fi rst study using a mixed-methods design to examine the infl uence 

of leadership on nutrition practices within the Army. 

Findings from this investigation suggest the need for additional study, particularly in the areas of variation in 

leader infl uence in different environments (eg, training 

versus operational), the effect of consequences for performance-limiting choices on food selection within the 

military, and the effectiveness of strategies designed to 

increase leaders’ helpfulness and improve their attitudes 

regarding the importance of eating for performance in 

order to change not only their own behaviors and attitudes but those of their Soldiers as well.

RELEVANCE TO THE PERFORMANCE TRIAD

The Army Performance Triad is designed to promote activity, nutrition, and sleep within the Army Family. This 

study suggests Army leaders have the potential to affect 

Soldiers’ nutritional attitudes and behaviors and may 

be likely to infl uence activity and sleep behaviors as 

well. When designing and implementing strategies and 

tactics as part of the Performance Triad, Army leaders 

must be included as a target audience for program messaging (ie, an intervention group), and they could also be 

used as key opinion leaders to disseminate information 

and model positive behaviors for Soldiers.

RECOMMENDATIONS

The Army should do the following to ensure leaders are 

prepared to support positive nutrition practices within 

the Triad:

 Provide up-to-date information to leaders so they 

are knowledgeable regarding healthy, performanceoriented nutrition practices. Previous research indicated some leaders are not as knowledgeable as they 

would like to be about nutrition.23

 Emphasize that leaders should demonstrate a personal commitment to positive habits because their 

Soldiers look to them as role models; it is important that leaders not only tell Soldiers what to do 

but also model that behavior themselves. Instruct 

leaders on how to be helpful to Soldiers with regard 

to nutrition, and provide them with tools and techniques (other than reprimand) to guide Soldiers to 

desired behaviors.

Leaders should do the following to optimize performance-oriented nutrition choices among their Soldiers:

 Deliver additional education in both AIT and in the 

operational environment to continue the momentum initiated in BCT, and help AIT and operational 

Soldiers understand how to eat for performance and 

sustain energy if their activities are less physically 

demanding than in BCT.

 Learn, remember, and reinforce key concepts associated with programming to send consistent messages; approach programming with a positive attitude.

 Routinely emphasize the importance of nutrition for 

both cognitive and physical performance.

 Lead by example by selecting healthy foods and 

modeling positive nutritional habits.

 Avoid reprimand and punishment associated with 

selections such as dessert or nutrient-poor foods; reinforce performance-oriented food choices instead.

 Offer specifi c suggestions to Soldiers about how 

best to eat for the day’s activities.

 Assist Soldiers in making the connection between 

nutrition and outcomes that are meaningful to them 

(eg, APFT performance) in order to motivate them 

to make performance-oriented choices. In addition 

to APFT performance, previous literature suggests 

appearance, health, and meeting military weight 

standards are additional important motivators for 

healthy eating in the military.42

 Serve as a resource to subordinate Soldiers by becoming knowledgeable about nutrition and by identifying additional resources to which Soldiers can 

be directed for additional information.

Although these recommendations and the fi ndings from 

this study are focused solely on nutrition, many of them 

have the potential to translate across activity and sleep. 

When either reinforcing or changing behavior within a 

military community is attempted, leadership engagement, role modeling, and commitment are likely to 

make a positive difference.

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION
 October – December 2013 89

THE ARMY MEDICAL DEPARTMENT JOURNAL

REFERENCES

1. Karl JP, Lieberman HR, Cable SJ, Williams KW, 

Young AJ, McClung JP. Randomized, double blind, 

placebo-controlled trial of iron supplementation in 

female Soldiers during military training: effects on 

iron status, physical performance and mood. Am J 

Clin Nutr. 2009;90(1):124-131.

2. Andersen NE, Karl JP, Cable SJ, et al. Vitamin D 

status in female military personnel during combat 

training. J Int Soc Sports Nutr. 2010;7:38.

3. Jones BH, Thacker SB, Gilchrist J, Kimsey CD Jr, 

Sosin DM. Prevention of lower extremity stress 

fractures in athletes and soldiers: A systematic review. Epidemiol Rev. 2002;24(2):228-247.

4. Wentz L, Lui PY, Haymes E, Illich JZ. Females 

have greater incidence of stress fractures than 

males in both military and athletic populations: a 

systematic review. Mil Med. 2011;176(4):420-430.

5. Stewart T, May S, Allen HR, et al. Development of 

an internet/population-based weight management 

program for the US Army. J Diabetes Sci Technol. 

2008;2(1):116-126.

6. Deuster PA, Weistein AA, Sobel A, Young AJ. 

Warfi ghter nutrition: current opportunities and advanced technologies report from a department of 

defense workshop. Mil Med. 2009;174(7):671-677.

7. Guide to Community Preventive Services. Promoting good nutrition [internet]. Available at: 

http:www.thecommunityguide.org/nutrition/index.

html [updated March 29, 2012]. Accessed May 28, 

2013.

8. Department of Defense. 2008 Department of Defense Survey of Health Related Behaviors among 

Active Duty Military Personnel. Research Triangle 

Park, NC: RTI International; 2009.

9. Skiller B, Booth C, Coad R, Forbes-Ewan C. Assessment of nutritional status and fatigue among 

Army recruits during Army common recruit training course; Part A: catering services and diet. Defence Science and Technology Organisation, Victoria (Australia) CBRN Defence Centre. 2005.Available at: http://handle.dtic.mil/100.2/ADA447856. 

Accessed May 28, 2013. 

10. Aoi W, Naito Y, YoshikawaT. Exercise and functional foods. Nutr J. 2006;5:15.

11. Henderson NE, Knapik JJ, Shaffer SW, McKenzie TH, Schneider GM. Injuries and injury risk 

factors among men and women in US Army combat medic advanced individual training. Mil Med. 

2000;165(9):647-652.

12. Smith TJ, Sigrist LD, Bathalon GP, McGraw S, 

Karl JP, Young AJ. Effi cacy of a meal-replacement 

program for promoting blood lipid changes and 

weight and body fat loss in US Army Soldiers. J 

Am Diet Assoc. 2010;110(2):268-273.

13. Bedno SA, Li Y, Han W, et al. Exertional heat 

illness among overweight US Army Recruits 

in basic training. Aviat Space Environ Med. 

2010;81(2):107-111.

14. US Army Food Program. Implementation Guide 

for Initial Military Training Soldier Fueling Initiative. Available at: http://www.quartermaster.army.

mil/jccoe/Operations_Directorate/QUAD/nutri

tion/Implementation_Guide_January_2012.pdf 

[updated January 30, 2012]. Accessed May 31, 2013.

15. McLeroy KR, Bibeau D, Steckler A, Glanz K. An 

ecological perspective on health promotion programs. Health Educ Q. 1988;15(4):351-377.

16. Bandura A. Self-effi cacy: toward a unifying theory of behavioral change. Psychol Rev. 

1977;804:191-215. 

17. Bandura A. Health promotion by social cognitive 

means. Health Educ Behav. 2004;31:143-164.

18. Schunk DH. Peer models and children’s behavioral 

change. Rev Educ Res. 1987;57(2):149-174.

19. Valente TW, Pumpuang, P. Identifying opinion 

leaders to promote behavior change. Health Educ 

Behav. 2007;34:881-896.

20. Campbell MK, Hudson MA, Resnicow K, Blakeney N, Paxton A, Baskin M. Church-based health 

promotion interventions: evidence and lessons 

learned. Annu Rev Public Health. 2007;28:213-234.

21. Peterson J, Atwood JR, Yates B. Key elements 

for church-based health promotion programs: outcome-based literature review. Public Health Nurs. 

2002;19(6):401-11.

22. Lumpkins CY, Greiner KA, Daley C, Mabachi NM, 

Neuhaus K. Promoting Healthy Behavior from the 

Pulpit: Clergy share their perspectives on effective 

health communication in the African American 

church [epub ahead of print]. J Relig Health. 2011. 

Available at: http://link.springer.com/article/10.100

7%2Fs10943-011-9533-1. Accessed May 28, 2013.

23. Glover S, Williams E, Kresslein J, et al. Fort Jackson Identifying Health Barriers Project: Soldier 

Health Promotion to Examine and Reduce Health 

Disparities (SHPERHD). Fort Detrick, MD: US 

Army Medical Research and Materiel Command; 

2012.

24. Creswell JW, Fetters MD, Ivankova NV. Designing 

a mixed methods study in primary care. Ann Fam 

Med. 2004;2(1):7-12.

25. Curry LA, Nembhard IM, Bradley EH. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation. 

2009;119(10):1442-1452.
90 http://www.cs.amedd.army.mil/amedd_journal.aspx

26. MacQueen KM, McLellan E, Kay K, Milstein B. 

Codebook development for team-based qualitative 

analysis. Cult Anthropol Meth. 1998;10:31-36.

27. NHLBI Obesity Education Initiative Working 

Group. The Practical Guide. Identifi cation, Evaluation, and Treatment of Overweight and Obesity in 

Adults. NIH Publication Number 00-4084. Bethesda, MD: National Institutes of Health; 2000:1.

28. Torres-McGehee TM, Pritchett KL, Zippel D, Minton DM, Cellamare A, Sibilia M. Sports nutrition 

knowledge among collegiate athletes, caches, athletic trainers, and strength and conditioning specialists. J Athl Train. 2012;47(2):205-211.

29. Jacobson BH, Sobonya C, Ransone J. Nutrition 

practices and knowledge of college varsity athletes: 

a follow-up. J Strength Cond Res. 2001;15(1):63-68.

30. Shiffl ett B, Timm C, Kahanov L. Understanding of athletes’ nutritional needs among athletes, 

coaches and athletic trainers. Res Q Exerc Sport.

2002;73(3):357-362.

31. Carpenter RA, Finley C, Barlow CE. Pilot test 

of a behavioral skill building intervention to improve overall diet quality. J Nutr Educ Behav. 

2004;36(1):20-24.

32. Ball K, McNaughton SA, Le H, Andrianopoulos 

N, Inglis V, McNeilly B, et al. ShopSmart 4 Health 

- Protocol of a skills-based randomised controlled 

trial promoting fruit and vegetable consumption 

among socioeconomically disadvantaged women. 

BMC Public Health. 2013;14(13):466.

33. Fisher JD, FisherW A. The information-motivation-behavioral skills model. In: DiClemente R, 

Crosby R, Kegler R, eds. Emerging Promotion 

Research and Practice. San Francisco, CA: Josey 

Bass Publishers; 2005:40-70.

34. United States Army Training Centers. Initial Entry Training Family Handbook. Available at: http://

www.jackson.army.mil/sites/bct/docs/2 [revised 

January 2010]. Accessed June 6, 2013.

35. Brown JL, Pollitt E. Malnutrition, poverty and intellectual development. Sci Am. 1996;274(2):38-43.

36. Isaacs E, Oates J. (2008). Nutrition and cognition: 

assessing cognitive abilities in children and young 

people. Eur J Nutr. 2008;47(3):4-24.

37. Donohoe RT, Benton D. Cognitive functioning is 

susceptible to the level of blood glucose. Psychopharmacology (Berlin). 1999;145(4):378-385.

38. Turner J. Your Brain on Food: a nutrient rich diet 

can protect cognitive health. J Am Soc Aging. 

2011;35(2):99-106.

39. Salvy SJ, Bowker JC, Nitecki LA, Kluczynski MA, 

Germeroth LJ, Roemmich J N. Impact of simulated ostracism on overweight and normal-weight 

youths’ motivation to eat and food intake. Appetite. 

2011;56(1):39-45.

40. Scaglioni S, Salvioni M, Galimberti C. Infl uence of 

parental attitudes in the development of children’s 

eating behaviour. Br J Nutr. 2008;99: S22-S25. 

41. Zandian M, Ioakimidis I, Bergstrom J, et al. Children eat their school lunch too quickly: an exploratory study of the effect on food intake. BMC Public Health. 2012;12(1):351-358.

42. Sigrist LD, Anderson JE, Auld GW. Senior military offi cers’ educational concerns, motivators and 

barriers for healthful eating and regular exercise. 

Mil Med. 2005;170(10):841-845.

AUTHORS

Dr Jackson, Ms Jin, Ms Robinson, Ms Dennis, Ms Vo, Dr 

Prosser, and Mr Rawlings are with the Health Promotion 

and Wellness Portfolio, Public Health Assessment 

Program, Army Institute of Public Health, US Army 

Public Health Command, Aberdeen Proving Ground, 

Maryland.

COL Cable is with the Initial Military Training Center of 

Excellence, Fort Eustis, Virginia.

THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS:

RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION
 October – December 2013 91

The Dietary Guidelines for Americans (DGAs) provide 

comprehensive nutrition recommendations that promote 

a healthy diet and body weight, thereby reducing the risk 

for chronic disease. The DGAs, released by the United 

States Department of Agriculture (USDA) and the Department of Health and Human Services, are revised every 5 years to refl ect new scientifi c fi ndings. The 2010 

DGAs1

 focus on choosing foods that are nutrient dense 

(food that contains the highest concentration of nutrients 

per unit of energy). The 2010 DGAs specifi cally recommend limiting the intake of sodium, saturated fat, dietary cholesterol, trans fat, added sugars, refi ned grains, 

and alcohol; and increasing the intake of vegetables, 

fruits, whole grains, low-fat dairy, lean protein, seafood, 

oils, potassium, dietary fi ber, calcium, and vitamin D.

Individual adherence to the DGAs can be quantifi ed 

using a scoring rubric known as the healthy eating index (HEI). The HEI controls for the energy intake of 

a diet and measures diet quality.2-4 The fi rst HEI score 

was released in 1995 and subsequently updated in 2005 

to refl ect the revised DGAs. The HEI has been used to 

evaluate diet quality in the American adult population 

using data from the National Health and Nutrition Examination Survey (NHANES).5

 For example, one report 

indicates that individuals in the highest quartile of HEI 

scores (mean±SE of the mean=69.9±0.13) were less 

likely to be obese or overweight, have elevated blood 

pressure, metabolic syndrome, and decreased high-density lipoprotein when compared to those in the lowest 

quartile of HEI scores (33.6±0.10).6

 These data suggest 

that the HEI may be an appropriate tool to identify those 

with a poor diet who may benefi t the most from nutrition 

interventions. The data also demonstrate that lower HEI 

scores are associated with chronic disease risk in older 

adults.

Prior studies that assessed the intake of specifi c nutrients in military populations have revealed dietary inadequacies that may affect Soldier performance and risk for 

injury.7-9 However, comprehensive studies detailing total 

diet quality of meals consumed by military personnel 

 Assessment of Dietary Intake Using the

 Healthy Eating Index During Military Training

Laura J. Lutz, MS, RD

Erin Gaffney-Stomberg, PhD, RD

Jenna L. Scisco, PhD

COL Sonya J. Cable, SP, USA

J. Philip Karl, MS, RD

Andrew J. Young, PhD

James P. McClung, PhD

ABSTRACT

Objective: The objectives of this study were to use the healthy eating index (HEI) as a tool to characterize diet 

quality in Soldiers (n=135) during basic combat training (BCT), and to assess the effects of BCT on diet quality 

by comparing HEI scores before and after the training period.

Methods: HEI scores were calculated from a 110-item semiquantitative food frequency questionnaire. Soldiers 

were then divided into tertiles (high, medium, and low) of diet quality based upon HEI scores at the start of BCT.

Results: No relationships between pre-BCT total HEI score and age, sex, racial background, or physical activity 

were observed. The odds of being a smoker were 4.75 times higher for those in the low HEI tertile and 3.03 times 

higher for those in the medium HEI tertile when compared to those in the high HEI tertile (95% CI, 1.67, 13.48 

and 1.04, 8.82 respectively). Diet quality improved in the medium and low HEI tertiles over the course of BCT, 

as total HEI scores increased by 22% and 46% respectively (P<.05) with time in these groups. Although different at the start of BCT, HEI scores were similar between the medium and high HEI tertiles at the end of BCT.

Conclusion: Study fi ndings suggest that the BCT dining environment elicits positive changes in diet quality for 

Soldiers who enter military training with lower diet quality, and the HEI appears to be a useful tool to identify 

military personnel with lower diet quality at the start of training. This may provide the opportunity to target 

interventions such as diet counseling and education in an effort to improve Soldier health and performance.
92 http://www.cs.amedd.army.mil/amedd_journal.aspx

within garrison environments are limiting. As such, 

the objective of this study was to characterize the diet 

quality of Soldiers, using the HEI, during basic combat 

training (BCT), the 9 to 10 week initial Army training 

course for enlisted personnel. In addition, the effect of 

BCT on diet quality was assessed by comparing HEI 

scores before and after the training period.

METHODS

Volunteers

This study was approved by the Human Use Review 

Committee at the US Army Research Institute of Environmental Medicine and was conducted at Fort Jackson, 

South Carolina. Human volunteers participated in this 

study after providing their free and informed voluntary 

consent. Investigators adhered to US Army Regulation 

70-25 10 and US Army Medical Research and Materiel 

Command Regulation 70-25,

11 both of which provide 

guidance on the participation of volunteers in research. 

The data presented in this manuscript were collected in 

conjunction with a study that assessed the prevalence of 

cardiometabolic risk in Army recruits.12

A total of 209 US Army recruits (118 male, 91 female) 

volunteered to participate in this study. Volunteers 

were excluded if they reported implausible energy intake (<300 or >4,500 kcal/day for women and <800 or 

>5,000 kcal/day for men), or if they were missing data at 

the end of BCT due to separation from their unit or withdrawal from the study. In total, 135 volunteers (76 male, 

59 female) were included in the fi nal analyses. The baseline demographics of the study population are presented 

in Table 1. Dietary intake and background information 

were collected from the volunteers at the beginning and 

end of BCT. In their studies, Knapik et al13,14 describe 

BCT as a 9 to 10 week course consisting of both physical 

and military-specifi c training.

Healthy Eating Index Score

The HEI is the composite of 12 component scores and 

ranges from 0 to 100, with a score of 100 indicating perfect compliance with the DGAs. The 9 adequacy components are:

 Total fruit

 Whole fruit

 Total grains

 Whole grains

 Total vegetables

 Dark green and orange vegetables and legumes

 Meat and beans

 Milk

 Oils

The 3 moderation components are:

 Sodium

 Saturated fat

 Calories from solid fats, alcoholic beverages, and 

added sugars (SoFAAS)

The HEI scores were calculated from a 110-item, semiquantitative, Block 2005 food frequency questionnaire 

(FFQ) (NutritionQuest, Berkeley, CA).15,16 The fulllength, 3-month version of the validated FFQ was used, 

having been adapted from the full-length, 12-month 

version by the omission of seasonality questions about 

fruit consumption. During the second administration of 

the FFQ, volunteers were instructed to provide data regarding dietary intake during the BCT period only. 

Volunteers self-reported dietary intake by completing 

the FFQ at the beginning of BCT, capturing their intake 

over the 3 months prior to entering the Army, and completing it again at the end of BCT, capturing their dietary 

intake during BCT. The food list on the FFQ was developed from NHANES 1999-2002 dietary recall data, 

and volunteers recorded both the quantity of food items 

consumed and the frequency of their consumption. The 

total daily energy and nutrient intake and the number 

of daily servings within food groups were calculated by 

NutritionQuest (Berkeley, CA) using the USDA’s Food 

and Nutrient Database for Dietary Studies v.1.017 and 

the MyPyramid Equivalents Database 2.0.18

ASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING

Table 1. Demographic Characteristics at Baseline.

HEI Tertiles

High

(n=45)

Medium

(n=45)

Low

(n=45)

HEI Score Pre (P<.01) 73.1±6.2 60.3±3.4 46.9±4.4

Age (yr) (mean±SD) (P=.50) 23.8±5.9 23.1±5.1 22.3±5.1

Sex (P=.68)

Male 23 26 27

Female 22 19 18

Racial Background (P=.55)

White 25 30 27

Black/AfricanAmerican 8 8 11

Other 12 7 7

Activity (P=.19)

Less than 20 

minutes per day 14 12 22

More than 20 

minutes per day 31 33 22

Smoker* (P<.01)

Yes 6 14 19

No 39 30 26

HEI indicates Healthy Eating Index.

*Smoker defined as smoking more than every other day over the past 

30 days.
 October – December 2013 93

THE ARMY MEDICAL DEPARTMENT JOURNAL

Twelve HEI component scores and total HEI scores were 

determined according to the HEI guidelines.2-4 Methods for scoring the HEI components appear in Table 

2. Higher scores indicate increased consumption of adequacy components (consume more of) and decreased 

consumption of moderation components (consume less 

of), indicating a greater level of dietary quality.

Statistical Analysis

Changes in HEI total and component scores were analyzed as secondary outcomes in a trial powered to characterize the prevalence of cardiometabolic risk during 

BCT.12 For the present analysis, change in the HEI total 

score was considered the primary outcome of interest. 

Post-hoc power calculations were therefore completed 

using the HEI total score or change in the HEI total 

score as the dependent variable. For all statistical analyses, volunteers were divided into equal tertiles based on 

their baseline HEI score. One-way analysis of variance 

(ANOVA) with Bonferroni corrections was used to determine differences between HEI tertiles for age. The 

χ2

 test was used to determine differences in categorical 

variables across HEI tertiles, and logistic regression was 

used to determine odds ratios and 95% confi dence intervals (CIs). Mixed model ANOVA was used to determine 

within (time) and between (group) tertile differences in 

HEI scores. Signifi cance for all analyses was assumed 

when P<.05. All statistical analyses were completed after normality was assessed using the IBM SPSS Statistics (V 20.0) application (IBM Corp, Chicago, IL).

RESULTS

Baseline HEI scores, indicative of dietary intake prior to 

BCT, did not differ according to age, sex, race, 

or physical activity (Table 1). However, those 

volunteers with low diet quality were more 

likely to be smokers than nonsmokers (P<.05). 

Specifi cally, the odds of being a smoker were 

4.75 times higher for those in the low HEI tertile and 3.03 times higher for those in the medium HEI tertile when compared to those in 

the high HEI tertile (95% CI, 1.67, 13.48, and 

1.04, 8.82 respectively).

Diet quality improved in the medium and 

low HEI tertiles over the course of BCT, as 

total HEI scores increased (P<.05) with time 

in these groups. In fact, total post-BCT HEI 

scores were similar between the medium and 

high HEI tertiles at the end of BCT as shown 

in Table 3. Total HEI scores did not change 

over the course of BCT in those volunteers 

categorized in the high tertile at the start of 

training.

Analysis of the 12 components of the HEI indicate that 

saturated fat, SoFAAS, oils, total fruit, whole fruit, total grain, whole grain, and total vegetable component 

scores improved (P<.05), and sodium scores declined 

(P<.05) during BCT for volunteers in the low tertile. 

Over the course of BCT, volunteers in the medium tertile demonstrated similar improvements (P<.05) in component scores as those in the low tertile, except for a 

lack of improvement in the oil component. Volunteers 

beginning BCT in the high tertile demonstrated improvements (P<.05) in the whole fruit, total grain, and 

whole grain components and a decrement (P<.05) in the 

oil component over the course of BCT.

COMMENT

The objectives of this study were to use the HEI as a 

tool for assessing dietary quality in military personnel 

and to assess changes in diet quality during training. 

The major fi nding was that diet quality improved in Soldiers beginning BCT with the lowest diet quality. These 

fi ndings indicate that the HEI may be used as a tool for 

identifying military personnel with low diet quality for 

nutrition interventions, and that dietary quality may improve during the course of initial military training for 

Soldiers who come into the military with poor eating 

habits.

Consistent with previous fi ndings in US adults, we report diminished diet quality in smokers as compared to 

nonsmokers.3

 However, unlike previous studies in civilian populations using NHANES data,19 we did not observe better diet quality in women than men. This may 

be due to the limited sample size of the current study or 

Table 2. HEI Component Scoring Rubric.

Componenta Score

Range

Standard for the

Maximum Scoreb

Standard for the

Minimum Scoreb

Total fruit 0-5 ≥0.8 cup equiv. 0 cup equiv.

Whole fruit 0-5 ≥0.4 cup equiv. 0 cup equiv.

Total vegetables 0-5 ≥1.1 cup equiv 0 cup equiv.

Dark green and orange

vegetables and legumes 0-5 ≥0.4 cup equiv. 0 cup equiv.

Total grains 0-5 ≥3.0 oz equiv. 0 oz equiv.

Whole grains 0-5 ≥1.5 oz equiv. 0 oz equiv.

Milk 0-10 ≥1.3 cup equiv. 0 cup equiv.

Meat and beans 0-10 ≥2.5 oz equiv. 0 oz equiv.

Oils 0-10 ≥12 grams 0 grams

Saturated fatc 0-10 ≤7% of total energy ≥15% of total energy

Sodiumc 0-10 ≤0.7 grams ≥2.0 grams

Calories from solid fats,

alcoholic beverages,

and added sugars

0-20 ≤20% of total energy ≥50% of total energy

HEI indicates Healthy Eating Index.

a. Defined per HEI guidelines.2

b. Per 1000 kcal, unless percentage of energy.

c. Receive scores of 8 for intakes that reflect Dietary Guidelines for Americans 

recommendations.
94 http://www.cs.amedd.army.mil/amedd_journal.aspx

to differences between military personnel and civilians 

in terms of diet quality in the demographic included in 

the population sampled.

The HEI scores improved during BCT for those who 

began their military service with lower scores. This 

may indicate that when exposed to a military dining 

environment with a variety of food choices, Soldiers 

are inclined to choose and may prefer healthier food 

options. In support of this hypothesis, we observed improvements in saturated fat, whole fruit, total and whole 

grain, and total vegetable intake in both the medium 

and low tertiles of volunteers throughout the course of 

BCT. Similarly, previous studies have demonstrated 

that when military dining facility services were altered 

to promote healthy diet options, such as healthy food 

options at the beginning of service lines and implementing the Go for Green method of rating the nutritional composition of food items, caloric and total fat intake were reduced and customer satisfaction improved 

as compared to the control dining facilities.20 

Nutrition education strategies may also underlie improvements in diet quality. The Soldier Fueling Initiative, which provides nutrition education during BCT 

and highlights the consumption of nutrient dense foods 

in garrison dining facilities, was implemented prior to 

this study and may have contributed to the observed 

improvement in diet quality. Given the fi ndings of the 

current study, it is possible that the HEI can be used as a 

tool for the evaluation of initiatives aimed at improving 

the nutrient quality of dining options within military 

environments.

Pasiakos et al12 previously reported improvements in 

lipid profi les, fasting glucose, and insulin sensitivity 

during BCT in this cohort. These favorable effects may 

be partially attributable to the improved diet quality during BCT observed in this study, as well as the physical 

activity encountered during BCT. Previous studies in 

older cohorts have demonstrated that if those with low 

HEI scores continue to consume poor diets, unfavorable outcomes such as overweight, obesity, and an unhealthy lipid profi le may result.6

 Future studies should 

focus on possible relationships between HEI scores and 

biomarkers of chronic disease risk in military populations, which may be predictive of longer-term health 

outcomes. Similarly, identifying areas of the diet with 

the lowest component scores may add focus to nutrition 

education programs aimed at improving overall diet 

quality in young people, including military personnel, 

thereby establishing positive dietary habits and preventing the negative effects of poor diet later in life.

ASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING

Table 3: HEI Total and Component Score (mean±SD) Before 

and After BCT.

HEI Tertiles

High

(n=45)

Medium

(n=45)

Low

(n=45) Effect

HEI Score T,G,TxG

Pre-BCT 73.1±6.2 60.3±3.4a 46.9±4.4a,b

Post-BCT 75.5±8.8 73.8±8.2c 68.6±7.4a,b,c

Sodium T,G,TxG

Pre-BCT 3.2±1.9 3.3±2.3 4.1±2.5

Post-BCT 2.8±2.0 2.4±1.6c 2.2±1.7c

Saturated Fat T,G,TxG

Pre-BCT 7.1±2.2 5.1±2.9a 4.1±3.3a

Post-BCT 7.6±2.3 7.2±2.3c 6.9±2.2c

Calories from Solid Fats, Alcoholic Beverages, and Added 

Sugars

T,G,TxG

Pre-BCT 15.9±3.1 9.5±4.6a 4.1±3.8a,b

Post-BCT 14.9±3.3 14.6±3.1c 13.3±2.2a,c

Oils G,TxG

Pre-BCT 7.8±2.4 7.0±2.2 5.6±2.5a,b

Post-BCT 6.7±2.2c 7.0±2.5 6.6±2.3c

Milk

Pre-BCT 6.4±3.0 6.2±2.7 5.7±2.9

Post-BCT 5.9±2.9 5.5±2.6 5.4±2.8

Total Fruit T,G,TxG

Pre-BCT 4.4±1.0 3.8±1.5 2.6±1.3a,b

Post-BCT 4.5±0.9 4.3±1.1c 3.9±1.4c

Whole Fruit T,G,TxG

Pre BCT 4.3±1.0 3.5±1.5a 2.3±1.2a,b

Post BCT 4.8±0.5c 4.5±1.1c 4.4±1.1c

Total Grain T,TxG

Pre-BCT 4.0±1.0 4.1±1.0 3.7±1.1

Post-BCT 4.5±0.7c 4.5±0.9c 4.7±0.5c

Whole Grain T,G,TxG

Pre-BCT 2.3±1.5 1.7±1.2 1.0±1.0a,b

Post-BCT 3.1±1.4c 3.2±1.4c 2.8±1.3c

Meat and Beans

Pre-BCT 9.7±1.1 9.9±0.4 9.7±1.0

Post-BCT 9.8±0.7 9.8±0.7 9.7±0.9

Dark Green and Orange Vegetables and Legumes T,G

Pre-BCT 3.6±1.6 2.5±1.6 1.4±1.2

Post-BCT 4.2±2.4 4.0±2.4 2.7±1.7

Total Vegetables T,G,TxG

Pre-BCT 3.9±1.2 3.3±1.1a 2.4±1.0a,b

Post-BCT 3.8±1.2 3.9±1.2c 3.6±1.1c

HEI indicates Healthy Eating Index.

BCT indicates basic combat training.

Effects: T - main effect of time

 G - main effect of group

 TxG - time by group interaction

Notes:

 a. Different (P<.05) from High

 b. Different (P<.05) from Medium

 c. Different (P<.05) from Pre-BCT
 October – December 2013 95

THE ARMY MEDICAL DEPARTMENT JOURNAL

Strengths of this study include the longitudinal design 

and the use of a validated FFQ to collect dietary intake 

data. Weaknesses include the small sample size in comparison to larger studies, such as NHANES, conducted 

in civilian populations. Further, dietary intake was not 

collected for a full year; therefore, seasonal variation in 

nutritional intake may not have been captured. Future 

studies should include larger populations of military personnel in both training and permanent duty assignments 

and should follow Soldiers for longer periods to determine if improvements in their diet quality are sustained. 

Similarly, biomarker data may be used in conjunction 

with the HEI to demonstrate the effects of diet quality 

on indicators of nutritional status and disease risk.

RELEVANCE TO THE PERFORMANCE TRIAD

This study suggests that the BCT dining environment 

elicits positive changes in diet quality for Soldiers entering military training with lower diet quality. The HEI 

appears to be a useful tool to identify military personnel 

with low diet quality at the start of training and may be 

a valuable tool for evaluating nutrition initiatives within 

the Performance Triad Program, The US Army Surgeon 

General’s strategy to improve the wellness, individual 

performance, and resilience of the Army community 

through proper activity, nutrition, and sleep. The identifi cation of military personnel with low diet quality early 

in their careers may provide the opportunity to target interventions such as diet counseling and education in an 

effort to improve Soldier health and performance over 

the course of a military career and beyond.

ACKNOWLEDGEMENT

The authors have no potential confl icts of interest.

This project was funded by the US Army Medical 

Research and Materiel Command. The study sponsor 

had no role in study design, collection, analysis, and 

interpretation of data; writing the report, nor the decision 

to submit the report for publication.

REFERENCES

1. Dietary Guidelines for Americans, 2010. 7th ed. 

Washington, DC: US Dept of Agriculture, US Dept 

of Health and Human Services; 2010. Available at: 

http://www.cnpp.usda.gov/DGAs2010-PolicyDocument.htm. Accessed July 5, 2013.

2. Guenther PM, Reedy J, Krebs-Smith SM, Reeve 

BB, Basiotis PP. Development and evaluation of 

the Healthy Eating Index-2005: Technical Report. 

Alexandria, VA: Center for Nutrition Policy and 

Promotion, US Dept of Agriculture; 2007. Available at: http://www.cnpp.usda.gov/publications/

hei/hei-2005/hei-2005technicalreport.pdf. 

Accessed July 5, 2013.

3. Guenther PM, Reedy J, Krebs-Smith SM, Reeve 

BB. Evaluation of the Healthy Eating Index-2005. J 

Am Diet Assoc. 2008;108(11):1854-1864.

4. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet 

Assoc. 2008;108(11):1896-1901.

5. About the National Health and Nutrition Examination Survey. Hyattsville, MD: Centers for Disease 

Control and Prevention National Center for Health 

Statistics; 2013. Available at: http://www.cdc.gov/

nchs/nhanes/about_nhanes.htm. 

Accessed July 5, 2013.

6. Nicklas TA, O’Neil CE, Fulgoni VL III. Diet quality is inversely related to cardiovascular risk factors in adults. J Nutr. 2012;142(12):2112-2118.

7. McClung JP, Karl JP, Cable SJ, Williams KW, Nindl 

BC, Young AJ, Lieberman HR. Randomized, double-blind, placebo-controlled trial of iron supplementation in female soldiers during military training: effects on iron status, physical performance, 

and mood. Am J Clin Nutr. 2009;90(1):124-131.

8. Karl JP, Lieberman HR, Cable SJ, Williams KW, 

Young AJ, McClung JP. Randomized, double-blind, 

placebo-controlled trial of an iron-fortifi ed food 

product in female soldiers during military training: 

relations between iron status, serum hepcidin, and 

infl ammation. Am J Clin Nutr. 2010;92(1):93-100.

9. Lutz LJ, Karl JP, Rood JC, Cable SJ, Williams KW, 

Young AJ, McClung JP. Vitamin D status, dietary 

intake, and bone turnover in female soldiers during military training: a longitudinal study. J Int Soc 

Sports Nutr. 2012;9(1):38.

10. Army Regulation 70-25: Use of Volunteers as Subjects of Research. Washington, DC: US Dept of the 

Army: January 1990.

11. USAMRMC Regulation 70-25: Use of Human 

Subjects in Research, Development, Testing and 

Evaluation. Fort Detrick, MD: US Army Medical Research and Materiel Command; April 1990 

[amended July 2003].

12. Pasiakos SM, Karl JP, Lutz LJ, et al. Cardiometabolic risk in US Army recruits and the effects of basic combat training. PLoS ONE. 2012;7(2):e31222.

13. Knapik JJ, Sharp MA, Darakjy S, Jones SB, 

Hauret KG, Jones BH. Temporal changes in the 

physical fi tness of US Army recruits. Sports Med. 

2006;36(7):613-634.

14. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin 

R, Jones BH. Ambulatory physical activity during 

United States Army basic combat training. Int J 

Sports Med. 2007;28(2):106-115.
96 http://www.cs.amedd.army.mil/amedd_journal.aspx

ASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING

15. Block G, Hartman AM, Dresser CM, Carroll MD, 

Gannon J, Gardner L. A data-based approach to 

diet questionnaire design and testing. Am J Epidemiol. 1986;124(3):453-469.

16. Block G, Woods M, Potosky A, Clifford C. Validation of a self-administered diet history questionnaire using multiple diet records. J Clin Epidemiol. 

1990;43(12):1327-1335.

17. USDA Food and Nutrient Database for Dietary 

Studies, 1.0. Beltsville, MD: Food Surveys Research 

Group, Agricultural Research Service, US Dept of 

Agriculture; 2004. Available at: http://www.ars.

usda.gov/Services/docs.htm?docid=12082. 

Accessed July 5, 2013.

18. Bowman SA, Friday JE, Moshfegh A. MyPyramid 

Equivalents Database 2.0 for USDA Survey Foods, 

2003-2004. Beltsville, MD: Food Surveys Research 

Group, Agricultural Research Service, US Dept of 

Agriculture; 2008. Available at: http://www.ars.

usda.gov/Services/docs.htm?docid=17563. 

Accessed July 5, 2013.

19. Ervin RB. Healthy Eating Index-2005 total and 

component scores for adults aged 20 and over: National Health and Nutrition Examination Survey, 

2003-2004. Natl Health Stat Report. 2011;13(44):1-9.

20. Crombie AP, Funderburk LK, Smith TJ, et al. Effect of modifi ed foodservice practices in military dining facilities on ad libitum nutritional 

intake of US Army soldiers. J Acad Nutr Diet. 

2013;113(7):920-927.

AUTHORS

Ms Lutz is a project manager for the Military Nutrition 

Division of the United States Army Research Institute of 

Environmental Medicine, Natick, MA.

Ms Gaffney-Stomberg is a research fellow with the 

Oak Ridge Institute for Science and Education Program 

and is currently located with the Military Nutrition 

Division of the United States Army Research Institute of 

Environmental Medicine, Natick, MA.

Dr Scisco is a principal investigator for the Military 

Nutrition Division of the United States Army Research 

Institute of Environmental Medicine, Natick, MA.

COL Cable is the Chief of the Human Dimensions 

Division at the Initial Military Training Center of 

Excellence, Fort Eustis, VA.

Mr Karl is a project manager for the Military Nutrition 

Division of the United States Army Research Institute of 

Environmental Medicine, Natick, MA.

Dr Young is chief of the Military Nutrition Division of the 

United States Army Research Institute of Environmental 

Medicine, Natick, MA.

Dr McClung is a principal investigator for the Military 

Nutrition Division of the United States Army Research 

Institute of Environmental Medicine, Natick, MA.
 October – December 2013 97

THE ARMY MEDICAL DEPARTMENT JOURNAL
98 http://www.cs.amedd.army.mil/amedd_journal.aspx

Sleep, in addition to nutrition and physical activity, is 

a component of the Performance Triad because sleep 

habits among the military are problematic,1-5 and inadequate sleep is prevalent in the Army.6-8 With regard 

to the Performance Triad, sleep is perhaps more diffi -

cult to control than activity and nutrition. Soldiers are 

at a heightened risk for diminished sleep quality as a 

result of dangerous working environments, loud noise 

exposure, and unpredictable hours.9,10 Effective sleep 

practices and habits that contribute to quality nighttime 

sleep and daytime alertness, is essential for high quality 

sleep.11 The phenomenon of poor sleep is occurring in 

parallel with the global increase in obesity and metabolic syndrome,12,13 as well as increases in depression, 

anxiety, and other mental health issues.8,14-19 Interestingly, poor sleep behaviors have also been associated with 

a pro-infl ammatory state.20-24

Many epidemiological and meta-analytic studies suggest these observed relationships may be bidirectional 

and possibly confounded by other issues.13,20,25 For example, psychological state is infl uenced by and directly 

infl uences sleep quality.26-29 Moreover, sleep-induced 

disturbances in circadian rhythms have been shown to 

affect selected endocrine parameters13,30,31 and metabolic 

pathways.12,13,32 Importantly, compromised sleep habits, 

in terms of duration and quality, may lead to insulin resistance and immunologic alterations; whereas, depression, anxiety, and life stressors can interfere with sleep 

duration and quality to create a vicious cycle.12,13,30-32 Finally, exercise and nutritional habits can directly infl uence sleep quality and duration,5,20,33-38 in either negative 

or positive directions. Exercise and sleep interact bidirectionally as well. Military trainees who experienced 

lack of sleep due to night missions, coupled with early 

Sleep as a Component of the Performance

 Triad: The Importance of Sleep in a

 Military Population

Cynthia V. Lentino, MS

Dianna L. Purvis, PhD

Kaitlin J. Murphy, MS

Patricia A. Deuster, PhD, MPH

ABSTRACT

ObjecƟ ve: Sleep habits among military populations are problematic. Poor sleep hygiene occurs in parallel with 

the global increase in obesity and metabolic syndrome and contributes to a decrease in performance. The extent 

of sleep issues needs to be quantifi ed to provide feedback for optimizing warfi ghter performance and readiness. 

This study assessed various health behaviors and habits of US Army Soldiers and their relationship with poor 

sleep quality by introducing a set of new questions into the Comprehensive Soldier and Family Fitness (CSF2) 

Global Assessment Tool (GAT).

Methods: Subjects included 14,148 US Army Active, Reserve, and National Guard members (83.4% male) who 

completed the GAT, a self-report questionnaire that measures 4 fi tness dimensions: social, family, emotional, 

and spiritual. Approximately 60 new questions, including ones on sleep quality, within the fi fth CSF2 dimension (physical) were also answered. A sleep score was calculated from 2 questions validated in the Pittsburgh 

Insomnia Rating Scale (0 to 6).

Results: Poor sleepers (5-6) were signifi cantly (P<.001) more likely than good sleepers (0-1) to consider themselves in fair or poor health, be overweight or obese, and score in the lowest quartile of the emotional, social, 

family, and spiritual fi tness dimensions. Additionally, poor sleepers were signifi cantly (P<.001) less likely to 

have a healthy body mass index and waist circumference, eat breakfast 6 or more times a week, meet aerobic 

exercise and resistance training recommendations, and pass their Army Physical Fitness Test in the top quartile.

Conclusion: This study examined sleep quality in a group of military personnel and indicated signifi cant associations between quality of sleep and physical performance, nutritional habits, measures of obesity, lifestyle 

behaviors and measures of psychosocial status. Targeted educational interventions and resources are needed to 

improve sleep patterns based on behaviors that can be most easily modifi ed.
 October – December 2013 99

morning wake-up calls, reported a diminished ability to 

perform daily physical training and a decline in physical fi tness and marksmanship testing scores.3

 Weekly, 

moderate physical activity improves self-reported sleep 

quality and can result in shortened sleep latency, fewer 

awakenings after sleep onset, longer sleep duration, and 

better overall sleep effi ciency.31,39

The concerns about insuffi cient sleep in the military 

have led researchers to quantify the extent of the sleep 

issues in order to target educational and behavioral practices to improve sleep patterns. Thus, we conducted an 

investigation, in collaboration with the Army’s Comprehensive Soldier and Family Fitness program (CSF2), to 

assess various health behaviors and habits of US Army 

Soldiers. New questions were incorporated into the online Global Assessment Tool (GAT), which all nondeployed Soldiers are required to complete once per year. 

Family members of Soldiers and all Department of Defense (DoD) civilians may also take the GAT. The intent 

of the questions was to determine gaps in Soldier knowledge and behaviors relating to physical fi tness, nutritional habits, and sleep quality, then provide feedback to 

help them modify health behaviors and access resources 

to do so. The study examined sleep quality in Soldiers 

who completed the pilot launch of new GAT questions. 

Specifi cally, we asked about sleep quality and examined 

how it was related to overall emotional, spiritual, social, 

family, physical, and nutritional fi tness.

METHODS

This pilot study was conducted using a sample population of 14,850 Soldiers and DoD civilians during a 

2-week period in July 2012. Currently, the annual GAT 

measures health in 4 psychosocial dimensions: emotional, social, family, and spiritual. Approximately 60 

pilot questions were added to the GAT to assess lifestyle 

behaviors in the physical dimension. After completion 

of the GAT, respondents were informed that the physical 

dimension questions were for validation purposes and 

would not be scored. Respondents were then given the 

option to consent for use of their GAT responses for research purposes. Per an established data use agreement, 

personal identifying information was removed from the 

CSF2 data (thus waiving the requirement for Institutional Review Board approval), which was then provided to 

researchers for analysis.

Population

The total number of participants was 14,850. The following were excluded from analyses: 599 DoD civilians, 

3 family members, and 100 with missing sleep data. 

Therefore, the analyses presented herein are for 14,148 

Active, Reserve, and National Guard members.

Measures

Measures included the GAT, which was developed in 

part by Seligman et al40 and others.41 The details of its 

evaluation and reliability were previously described.41,42

The GAT’s overall purpose is to assess a Soldier’s emotional, social, spiritual, and family fi tness with 105 questions. Each dimension yields an overall score based on 

responses to the questions, and the scores are aggregated into quartiles. For the purposes of this study, the 

fi fth dimension (physical fi tness) was added, and pilot 

questions were incorporated to represent this new dimension assessment. Questions for the physical fi tness 

dimension included items related to nutritional habits 

and behaviors, physical activity patterns, sleep quality, 

and other lifestyle behaviors. 

Participants were asked to report their height and weight, 

and the body mass index (BMI) (weight [kg]/[height 

(m)]2) was calculated from their self-reported data. The 

cutoff was 27.5 kg/m2

 as specifi ed by Army Regulation 

600-9.

43 A healthy waist circumference was defi ned as 

35 inches or less for females and 40 inches or less for 

males.44

Sleep quality was subjectively assessed by self-report, 

and an overall score was calculated from responses to 

the short version of the Pittsburgh Insomnia Rating 

Scale, which had previously been validated.45,46 The 2 

questions and responses were:

1. In the past week, how much were you bothered by 

lack of energy because of poor sleep? (not at all 

bothered, slightly bothered, moderately bothered, 

severely bothered)

2. Over the past week, how would you rate your satisfaction with your sleep? (excellent, good, fair, poor)

Each answer choice was assigned a score of 0 to 3. 

Hence, the sum total score ranged from 0 to 6; we considered scores of 0 or 1 as good sleep, 2 to 4 as moderate 

sleep, and 5 or 6 as poor sleep quality. Although the author of the Pittsburgh Insomnia Rating Score indicated 

that a total score of 2 or more would identify someone 

with presumed problems, we further divided the group 

to look at those with self-reported sleep issues.

In addition to calculating a sleep-quality score, a 

Healthy Eating Score (HES-5) was developed based on 

the US Department of Agriculture’s (USDA) Healthy 

Eating Index,47-50 but modifi ed by using 5 questions 

assessing daily intake of fruit, vegetable, whole grain, 

dairy, and fi sh.51 Other nutrition questions included the 

number of days per week breakfast is consumed and the 

inclusion of recovery snacking, whether or not a snack 

is consumed within 60 minutes of strenuous exercise. 
100 http://www.cs.amedd.army.mil/amedd_journal.aspx

Physical activity information was captured by asking 

Soldiers the number of times per week they participated 

in aerobic activity for at least 20 minutes and strength 

or resistance exercise, based on the American College 

of Sports Medicine (ACSM) and Centers for Disease 

Control and Prevention (CDC) exercise recommendations.52 Additionally, participants provided their most 

recent Army Physical Fitness Test (APFT) score, which 

included number of push-ups, sit-ups, and run time.

Finally, participants were asked to respond to several 

questions relating to health, perceived body image, and 

alcohol habits. Specifi cally, they were asked to answer 

the following 3 questions:

1. How do you consider your general health? (excellent, good, fair, poor, don’t know)

2. In thinking about your weight, do you consider 

yourself to be: underweight, about the right weight, 

overweight, obese, don’t know?

3. Have you exceeded 5 alcoholic drinks on any single occasion during the past 3 months? (yes or no)

Internal consistency for the subsets of questions was 

measured using Cronbach α.

53 The values were the following: HES-5=0.810; sleep=0.807; and physical activity=0.793. The GAT dimensions had Cronbach α results 

of 0.724, 0.802 and 0.860 for the social, family, and 

emotional dimensions respectively, based on the current data. A Cronbach α greater than 0.80 is regarded as 

good, above 0.70 is acceptable, and below 0.60 is unacceptable.53 The pilot questions will be validated through 

a collaborative study between CSF2 and the Consortium 

for Health and Military Performance at the Uniformed 

Services University of the Health Sciences.

Statistical Analysis

The IBM SPSS (V 20.0) for Windows (IBM Corp, Chicago, IL) application was used to perform all statistical analyses. Frequency tables and descriptive statistics 

were reviewed to remove outliers and confi rm assumptions for parametric tests. Binary logistic regression was 

used to obtain odds ratios (OR) and 95% confi dence intervals (CI) to compare the relationships between sleep 

quality and nutrition, exercise, and lifestyle behaviors. 

For this purpose, poor sleepers were considered the 

reference group, and independent variables were either 

categorical (gender, active duty status, enlistment status, 

marital status) or categorized into groups (age, dietary 

behaviors, physical activity, APFT scores, BMI, waist 

circumference) based on quartiles or other appropriate classifi cations and/or dichotomized; as noted above, 

responses to the 4 psychosocial GAT dimensions were 

grouped into quartiles. 

A separate multiple linear-regression model was also 

used to predict poor sleep, with demographic variables, 

HES-5, APFT total score, and the 4 dimensions of the 

GAT. Due to the high number of statistical analyses, the 

P value was set at the .0025 signifi cance level. This was 

based on dividing the P value of .05 by the 25 logistic 

regressions conducted.

RESULTS

General Characteristics and Sleep Status

The overall characteristics of the sample are presented 

in Table 1. The distribution of poor, moderate, and good 

sleepers did not differ as a function of age (OR 1.0; 95% 

CI, 0.92-1.10; P=.93). However, women were 1.4 times 

more likely to be poor sleepers than men (OR 1.40; 95% 

CI, 1.24-1.57; P<.001). Additionally, those on active 

duty were 1.69 times more likely to be poor sleepers 

than those in the National Guard or Army Reserve (OR 

1.69; 95% CI, 1.55-1.85; P<.001). Moreover, enlisted 

personnel were 1.74 times more likely to be poor sleepers than offi cers (OR 1.74; 95% CI, 1.53-1.99; P<.001).

Dietary Patterns and Sleep Status

On average, poor sleepers were 50% less likely to meet 

the USDA dietary recommendations for the following: 

fruit (OR 0.48; 95% CI, 0.43-0.52; P<.001); vegetables 

(OR 0.53; 95% CI, 0.47-0.59; P<.001); whole grains (OR 

0.45; 95% CI, 0.43-0.52; P<.001); dairy (OR 0.48; 95% 

CI, 0.42-0.54; P<.001); and fi sh (OR 0.58; 95% CI, 0.53-

0.63; P<.001). Each of the dietary recommendations 

was used to create a HES-5 score. Figure 1 indicates 

that only 17.4% of the poor sleepers were also healthy 

eaters as defi ned by the HES-5 (a score of 20 out of 25). 

Overall, poor sleepers were 77.2% less likely to be a 

healthy eater (OR 0.23; 95% CI, 1.40-1.68; P<.001) than 

good sleepers. Table 2 captures additional dietary behaviors showing that poor sleepers were more likely to 

drink soda and less likely to eat breakfast regularly, or 

consume a snack within 60 minutes after a strenuous 

exercise session. 

Physical Fitness and Sleep

Frequency of physical activity was assessed and respondents met recommendations if they engaged in at 

least 20 minutes of aerobic exercise 5 days per week 

(71.5%), and at least 2 days per week of resistance training (66.8%). Figure 2 illustrates the percentages of each 

sleep group who met the recommendations and how 

many passed their APFT in the top quartile. Soldiers 

were less likely to be poor sleepers if they met aerobic 

exercise recommendations (OR 0.54; 95% CI, 0.49-0.60; 

P<.001), participated in regular resistance training (OR 

0.52; 95% CI, 0.47-0.57; P<.001), or passed their APFT 

in the top quartile (OR 0.53; 95% CI, 0.45-0.64; P<.001).

SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD:

THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION
 October – December 2013 101

THE ARMY MEDICAL DEPARTMENT JOURNAL

Health Self-Assessments and Sleep 

Approximately 42% of respondents provided their waist 

circumference. The mean (±SD) waist circumference 

for women was 30.2±3.7 inches and 34.4±3.6 inches for 

men. Odds ratios to predict healthy anthropomorphic 

measurements are included in Table 3. Although selfreported, the correlation between waist circumference 

and BMI was 0.673 (P<.001). Answers to the health selfassessments are also presented in Table 3. Remarkably, 

poor sleepers were 25.7% less likely to have a 

healthy BMI, 50.0% less likely to have a healthy 

waist circumference, and 17 times more likely to 

consider themselves to be in fair or poor health. 

GAT Dimensions

Figure 3 presents sleep quality category by the 4 

GAT psychosocial dimensions. As noted, those 

who were poor sleepers were signifi cantly more 

likely to score in the lowest quartile relative to the 

other sleep categories. A dose-related response 

was clearly noted, such that 19% to 35% in the 

good sleep group, 54% to 59% in the moderate, 

and 72% to 85% of the poor sleep group scored 

in the lowest quartiles. Table 4 documents the 

Table 1. Demographic characteristics of the study sample 

population (N=14,148).

Frequencies Sleep Score 

Mean±SD

Age mean±SD, years 27.7±8.3

Years range (min-max) 17-61

Age Group

17 to 29 66.9% 2.4±1.7

30 and over 33.1% 2.5±1.6

Gender 

Female 16.6% 2.6±1.6

Male 83.4% 2.4±1.6

Army Status 

Active Duty 52.6% 2.6±1.7

National Guard/Reserve 47.4% 2.3±1.6

Enlisted Status

Enlisted 85.3% 2.5±1.7

Officers 14.7% 2.1±1.5

Marital Status 

Married 49.0% 2.5±1.7

Single/divorced/legally separated 50.9% 2.4±1.6

Army Physical Fitness Test n=10,054

Failed 13.7% 2.6±1.7

Passed 86.3% 2.3±1.6

BMI Categories n=11,545

Underweight (<18.4 kg/m2

) 0.5% 2.4±1.6

Normal/healthy (18.5-27.5 kg/m2) 65.3% 2.4±1.6

Overweight (27.6-29.9 kg/m2) 16.9% 2.5±1.6

Obese (>30 kg/m2) 17.3% 2.7±1.7

BMI Mean±SD, kg/m2 26.6±4.03

Range 13.4-56.3

Waist Circumference n=6,012

Healthy 90.9% 2.4±1.6

Unhealthy 9.1% 2.8±1.7

Sleep Categories 

Good sleepers 32.9% 0.6±0.5

Moderate sleepers 41.8% 2.5±0.5

Poor sleepers* 25.3% 4.7±0.78

Note: Data are represented as mean±SD for continuous variables 

and as a percentage for categorical variables. Percentages within 

characteristic groups may not add up to 100% due to missing data.

*Poor sleepers are defined by a total score of 5 or 6 on the Pittsburgh 

Insomnia Rating Scale-2.

BMI indicates body mass index.

Figure 1. Percentage of healthy eaters in each sleep category. A healthy eater received a score of 20 out of 25 on 

the Healthy Eating Scale-5. Poor sleepers are defi ned by a 

total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6; a 

moderate sleeper scored a 2, 3, or 4; and a good sleeper 

received a score of 0 or 1.

Sleep Category

Good

Moderate

Poor

30%

0%

5%

10%

15%

20%

25%

35%

40%

Healthy Eaters

Table 2. Logistic Regression of Poor Sleepers and Dietary Behaviors.

Good

Sleepers

(n=4,658)

Moderate

Sleepers

(n=5,915)

Poor

Sleepers*

(n=3,575)

OR

(P<.001)

95% CI

Drinks either diet soda 

or regular soda (%n) 54.7% 59.1% 61.7% 1.35 1.24-1.48

Breakfast at least 6

times per week (%n) 52.9% 40.8% 31.2% 0.40 0.37-0.44

Consumes 2 or more 

snacks per day (%n) 45.6% 44.4% 41.1% 0.83 0.76-0.91

Recovery snack (%n) 54.4% 49.3% 43.9% 0.66 0.6-0.72

Note. Data are represented as percentages for the categorical variables.

*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 5 

or 6 and used as the reference group; a moderate sleeper scored a 2, 3, or 4; a 

good sleeper received a score of 0 or 1.

OR indicates odds ratio between poor and good sleepers.

CI indicates confidence intervals.
102 http://www.cs.amedd.army.mil/amedd_journal.aspx

ORs and CIs for the likelihood the poor sleepers would 

score in the lowest quartile of each dimension compared 

to the good sleepers. Most notably, when compared to 

the good sleep quality group, poor sleepers 

were 23.0 times more likely to score in the 

lowest quartile of emotional fi tness. 

Sleep Prediction Model

A step-wise multiple linear regression model was used to predict poor sleep. The following variables were allowed to be incorporated: age, gender, active duty, enlisted, 

and married Soldiers, HES-5, APFT total 

score, and 4 GAT dimensions. Although 

age and spiritual fi tness were initially included in the model, no statistically signifi cant associations were found. Table 5 

shows the fi nal model and the contribution 

of each variable entered. Overall, 22.7% 

of the variance in predicting sleep quality 

could be explained by this model. Emotional fi tness contributed the most with 

13.8%, and HES-5 accounted for 5.1% of 

the total explained variance. 

COMMENT

The adverse health consequences of poor 

sleep quality and inadequate quantity are 

receiving increasing attention. Both are 

strongly affected by lifestyle behaviors 

and daily nutrition and fi tness habits. In 

particular, poor sleep quality has been associated with disturbed or dysfunctional 

neuroendocrine13,30,31 and metabolic12,13,32 pathways, depression, 

anxiety, obesity, cardiovascular 

risk, and multiple life stressors.12,13,30-32 Although these health 

issues are well recognized, few 

have examined the relationship 

between sleep quality and the 

combination of multiple health 

components in a single sample. 

This study examined subjective sleep quality in a group of 

military personnel and indicated 

signifi cant associations between 

quality of sleep and physical 

performance, nutritional habits, 

measures of obesity, lifestyle behaviors, and, importantly, measures of psychosocial status. In 

particular, poor sleepers by selfreport were signifi cantly more 

likely to score in the lowest quartile for emotional, social, and family fi tness; have poorer performance on the 

APFT; and participate less frequently in healthy exercise 

Table 3. Logistic Regression of Poor Sleepers and Health Self-assessment.

Good

Sleepers

Moderate

Sleepers

Poor

Sleepers*

OR

(P<.001)

95% CI

Healthy BMI (18.5 to 27.5 kg/m2

) (n=3,782) (n=4,839) (n=2,924)

68.0% 65.7% 61.2% 0.74 0.67-0.82

Healthy waist circumference† n=2,022 n=2,484 n=1,506

93.2% 91.3% 87.2% 0.50 0.40-0.63

Consider their health to be “fair” 

or “poor” n=4,650 n=5,896 n=3,506 

4.8% 18.7% 46.0% 17.0 14.64-19.77

Consider themselves to be “overweight” or “obese” n=4,337 n=5,438 n=3,200

23.8% 34.1% 45.1% 2.60 2.38-2.90

Exceeded 5 alcoholic drinks on 

any single occasion during the 

past 3 months

n=4,658 n=5,915 n=3,575

16.7% 24% 29.7% 2.10 1.89-2.34

Note: Data are represented as percentages of n for the categorical variables.

*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6 and used as the 

reference group; a moderate sleeper scored a 2, 3, or 4; a good sleeper received a score of 0 or 1. †Healthy waist circumference is defined as 35 inches or less for women and 40 inches or less for men.

OR indicates odds ratio between poor and good sleepers.

CI indicates confidence intervals.

BMI indicates body mass index.

Good Poor

Soldiers in Study

Aerobic Activity

Strength Training

Passed APFT in

Top Quartile

Sleep Category

60%

0%

10%

20%

30%

40%

50%

70%

80%

Moderate

Figure 2. Percentage of Soldiers in each sleep category who met the Centers 

for Disease Control and Prevention and the American College of Sports Medicine recommendations for aerobic exercise (at least 20 minutes, 5 days per 

week) and resistance training (2 days per week), or passed the Army Physical 

Fitness Test in the top quartile. Poor sleepers are defi ned by a total Pittsburgh 

Insomnia Rating Scale-2 score of 5 or 6; a moderate sleeper scored a 2, 3, or 

4; and a good sleeper received a score of 0 or 1.

SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD:

THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION
 October – December 2013 103

THE ARMY MEDICAL DEPARTMENT JOURNAL

and dietary behaviors than good 

sleepers. Additionally, poor sleepers were signifi cantly more likely 

to have larger waist circumferences 

and higher BMI than good sleepers.

The current data support several 

consistent associations between 

poor sleep quality and health in a 

large sample of military persons. A 

key fi nding was the dose-related relationship between sleep quality and 

emotional, social, and family health. 

Importantly, emotional health, as 

measured by the Army GAT, was 

highly dependent on sleep quality, 

with poor sleepers being 23 times 

more likely to have scored in the 

lowest quartile for emotional health. 

Ribeiro et al54 evaluated the severity 

of depressive symptoms, hopelessness, posttraumatic stress disorder 

diagnoses, anxiety disorders, and 

drug and alcohol abuse symptoms 

in a sample of military personnel. 

Their results suggested that after 

controlling for all other symptoms, 

insomnia may possibly predict suicide risk. In other military specifi c 

populations, sleep problems proved to be an important mediator for developing posttraumatic 

stress disorder or depression.3,6 A strong association between sleep quality and perception of 

stress has also been demonstrated.8

 In addition, 

Collen et al1

 found that hypersomnia, sleep fragmentation, obstructive sleep apnea syndrome, 

and insomnia were common among persons with 

mild traumatic brain injury from blast and blunt 

trauma injuries. Minkel et al29 noted that the psychological threshold for perceiving stress was 

lowered by poor sleep quality, and Eliasson et al8

reported that perception of stress was inversely 

related to sleep quality. Of note is the fi nding of 

Mauss et al55 that the ability to regulate negative 

emotions is impaired in persons with poor sleep 

quality. In addition to perception of stress, sleep 

quality appears to signifi cantly affect cognitive performance.26,56,57 Whether this performance decrement in association with sleep quality is confounded by perceived 

stress remains to be determined.

The strong association between sleep quality and emotional health observed in this study was coupled with 

comparable associations for both social and family 

health: self-reported poor sleepers were 14.5 and 6.7 

times more likely to have scored in the lowest quartile 

for social and family health respectively. These fi ndings are supported by previous work.58,59 In particular, 

Ailshire et al58 demonstrated that strained family relationships were associated with troubled sleep; whereas, 

supportive family relationships were related to highquality sleep. Although not directly related to sleep, 

Table 4. Logistic Regression Predicting Likelihood of Poor Sleepers 

Scoring in the Bottom Quartile of Global Assessment Tool (GAT) Dimensions

GAT Fitness

Dimensions

Good

Sleepers

(n=2,575)

Moderate

Sleepers

(n=2,475)

Poor

Sleepers*

(n=1,984)

OR

(P<.001)

95% CI

Emotional 19.3% 54.5% 84.6% 23.00 19.64-26.85

Social 24.1% 54.4% 82.2% 14.47 12.47-16.79

Family 28.1% 52.6% 72.4% 6.71 5.83-7.72

Spiritual 35.1% 59.5% 74.9% 5.52 4.86-6.26

Note: Data are represented as percentages of n for the categorical variables.

*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 

5 or 6 and used as the reference group; a moderate sleeper scored a 2, 3, or 4; a 

good sleeper received a score of 0 or 1.

†Healthy waist circumference is defined as 35 inches or less for women and 40 

inches or less for men.

OR indicates odds ratio between poor and good sleepers.

CI indicates confidence intervals.

BMI indicates body mass index.

Figure 3. Percentage of each sleep category scoring in the lowest quartile for the 

Global Assessment Tool psychological dimensions. Poor sleepers are defi ned by a 

total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6; a moderate sleeper scored a 

2, 3, or 4; a good sleeper received a score of 0 or 1.

Good

Sleep Category

Poor

Emotional

Social

Family

Spiritual

60%

0%

10%

20%

30%

40%

50%

70%

80%

90%

Moderate

Lowest Quartile of Dimensions
104 http://www.cs.amedd.army.mil/amedd_journal.aspx

Pollock et al60 found that close and fl exible family relationships are linked to low individual perceived stress 

levels. Together these data clearly show the remarkable 

interplay among sleep quality, stress, relationships, and 

overall psychosocial functioning.

Sleep impacts other daily activities in addition to psychological and social functioning. This study found a 

strong association between sleep quality and dietary and 

physical activity habits. In particular, poor sleep quality 

was related to larger waist circumferences and higher 

BMIs, greater participation in adverse alcohol-related 

behaviors, and poorer performance on military-related 

tasks. Specifi cally, poor sleepers were less likely to meet 

the USDA dietary guidelines and CDC and ACSM exercise guidelines, eat breakfast on a regular basis, engage 

in positive eating habits, and more likely to drink sugarladen sodas. These fi ndings are also consistent with the 

literature.36,38,61-63 For example, Gerber et al found that 

participants who reported higher fi tness levels exhibited 

lower insomnia scores and had a higher perceived sleep 

quality.52 Golley et al36 reported that both late bedtime 

and late wakeup times were related to poor diet quality, independent of sleep duration. Cheng et al64 noted a 

signifi cant association between poor sleep quality and 

skipping breakfast in undergraduate female students, 

which is indicated in our fi nding that poor sleepers were 

more likely to skip breakfast. Although the research to 

date on breakfast and performance is derived primarily 

from young, school-age children, it is apparent that consuming breakfast is associated with enhanced attention 

and cognitive performance relative to not eating breakfast.65-69 Of particular interest are the recent fi ndings of 

Deshmukh-Taskar et al70 showing that consumption of 

breakfast was associated with more favorable cardiometabolic risk profi les in adults 20 to 39 years of age 

when compared to skipping breakfast. Likewise, Narang et al71 have indicated that adolescents who scored the 

highest on measures of sleep disturbances 

were signifi cantly more likely to have cardiovascular risk factors and hypertension than 

those who scored the lowest. 

Studies have also shown a relationship between sleep and successful weight loss. For 

example, Chaput et al72 found that more fat 

mass was lost over the course of a weightreduction program by those who reported 

good sleep quality prior to starting the program. Consistent with that work, Thomson et 

al73 found that participants who reported better subjective sleep quality were more likely 

to be successful with weight loss. This is not 

unexpected as Kim et al62 examined dietary 

patterns in association with sleep duration and concluded that both habitual short sleepers and very long 

sleepers typically did not eat during conventional eating 

hours—they had disrupted eating patterns with snacks 

being dominant over meals. Of note, both unconventional eating hours and snack dominance were refl ective of a 

low quality diet, that is, lower intakes of fruits and vegetables and higher intakes of sweets and fat as a percentage of energy.62 Together these reports demonstrate the 

close interrelationship between sleep and dietary habits 

and the infl uence on overall health.

The limitations of this study must be acknowledged. 

First, only 2 sleep questions were used, unlike the Pittsburgh Sleep Quality Index which has 20 questions.12,74,75

However, the 2 questions were global and refl ective of 

perceived sleep quality. Moreover, the percent of persons self-reporting poor sleep was what had been anticipated. Thus, the results are most likely accurate given 

the large sample size. Secondly, the relationships between sleep and scores on emotional and social health 

do not allow any determination of the key components of 

either specifi c dimension. However, the strength of the 

relationships demonstrates a clear interaction between 

sleep quality and emotional and social health. Further 

research will be necessary to refi ne the relative contribution of the factors discussed herein. Finally, the information on dietary patterns is not as granular as might be 

desired, but again the trends were quite strong, so these 

data will allow for further examination of specifi c patterns in the future.

RELEVANCE TO PERFORMANCE TRIAD

In summary, this study is one of the fi rst to examine 

self-reported sleep quality within the context of overall 

lifestyle patterns and self-reported psychosocial health 

in a military population. Poor sleepers were more likely 

to be poor eaters, engage in less healthy dietary and 

Table 5. Stepwise Multiple Regression Analysis-Predicting Poor Sleep.

Final Variables

in Model

R R2 R2 Change Standardized

β Coeffi cient

P

Value

1 Active Duty 0.107 0.011 0.011 0.063 .00

2 Enlisted Status 0.127 0.016 0.005 0.020 .03

3 Gender 0.132 0.017 0.001 0.040 .00

4 Married 0.136 0.018 0.001 0.029 .01

5 HES-5 0.262 0.068 0.051 -0.104 .00

6 APFT Total Score 0.273 0.074 0.006 -0.086 .00

7 Emotional Fitness 0.461 0.212 0.138 -0.277 .00

8 Social Fitness 0.473 0.223 0.011 -0.121 .00

9 Family Fitness 0.477 0.226 0.004 -0.073 .00

Note: A stepwise multiple linear regression model was used to predict poor sleep using 

the following variables:

Age Active duty Married APFT total score

Gender Enlisted HES-5 4 GAT dimensions

SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD:

THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION
 October – December 2013 105

THE ARMY MEDICAL DEPARTMENT JOURNAL

lifestyle behaviors, and score in the lowest quartiles 

with respect to emotional and social health. It further 

validates the central and essential relationships among 

physical activity, nutrition, and sleep—they fully support the concept of the Performance Triad. The results 

underscore the need to provide education on the health 

consequences of poor sleep habits and supportive resources for ensuring suffi cient high quality sleep. However, this should be done in an integrative fashion so 

as to include information on nutrition and physical fi tness, as they are intertwined and must be considered as 

a whole.

ACKNOWLEDGEMENTS

This research was supported by a grant from Comprehensive Soldier and Family Fitness (CSF2; HT9404-12-

1-0017; F191GJ).

We appreciate the support in preparation and review of 

this article by LTC Daniel T. Johnston and LTC Sharon 

A. McBride. We also gratefully acknowledge Josh Kazman for statistical support and Preetha Abraham for 

graphic assistance.

REFERENCES

1. Collen J, Orr N, Lettieri CJ, Carter K, Holley AB. Sleep disturbances among soldiers with 

combat-related traumatic brain injury. Chest. 

2012;142(3):622-630.

2. Crowley SK, Wilkinson LL, Burroughs EL, et al. 

Sleep during basic combat training: a qualitative 

study. Mil Med. 2012;177(7):823-828.

3. Macera CA, Aralis HJ, Rauh MJ, Macgregor AJ. 

Do sleep problems mediate the relationship between traumatic brain injury and development of 

mental health symptoms after deployment?. Sleep. 

2013;36(1):83-90.

4. Mackowiak PA, Billings FT III, Wasserman 

SS. Sleepless vigilance: “Stonewall” Jackson 

and the duty hours controversy. Am J Med Sci. 

2012;343(2):146-149.

5. Energy drink consumption and its association with 

sleep problems among US service members on a 

combat deployment–Afghanistan, 2010. MMWR 

Morb Mortal Wkly Rep. 2012;61(44):895-898.

6. Luxton DD, Greenburg D, Ryan J, Niven A, Wheeler G, Mysliwiec V. Prevalence and impact of short 

sleep duration in redeployed OIF soldiers. Sleep. 

2011;34(9):1189-1195.

7. Capaldi VF II, Guerrero ML, Killgore WD. Sleep 

disruptions among returning combat veterans from 

Iraq and Afghanistan. Mil Med. 2011;176(8):879-888.

8. Eliasson A, Kashani M, Dela Cruz G, Vernalis 

M. Readiness and associated health behaviors and 

symptoms in recently deployed Army National 

Guard soldiers. Mil Med. 2012;177(11):1254-1260.

9. Seelig AD, Jacobson IG, Smith B, et al. Sleep patterns before, during, and after deployment to Iraq 

and Afghanistan. Sleep. 2010;33(12):1615-1622.

10. Peterson AL, Goodie JL, Satterfi eld WA, Brim 

WL. Sleep disturbance during military deployment. 

Mil Med. 2008;173(3):230-235.

11. Schaefer EW, Williams MV, Zee PC. Sleep and circadian misalignment for the hospitalist: a review. J 

Hosp Med. 2012;7(6):489-496.

12. Kazman JB, Abraham PA, Zeno SA, Poth M, 

Deuster PA. Self-reported sleep impairment and 

the metabolic syndrome among African Americans. Ethn Dis. 2012;22(4):410-415.

13. Lucassen EA, Rother KI, Cizza G. Interacting epidemics? Sleep curtailment, insulin resistance, and 

obesity. Ann N Y Acad Sci. 2012;1264(1):110-134.

14. Applewhite L, Keller N, Borah A. Mental health 

care use by soldiers conducting counterinsurgency 

operations. Mil Med. 2012;177(5):501-506.

15. Pompili M, Rihmer Z, Gonda X, Serafi ni G, Sher 

L, Girardi P. Early onset of action and sleep-improving effect are crucial in decreasing suicide 

risk: the role of quetiapine XR in the treatment 

of unipolar and bipolar depression. Riv Psichiatr. 

2012;47(6):489-497.

16. Spelman JF, Hunt SC, Seal KH, Burgo-Black AL. 

Post deployment care for returning combat veterans. J Gen Intern Med. 2012;27(9):1200-1209.

17. Vijayalakshmy P, Hebert C, Green S, Ingram CL. 

Integrated multidisciplinary treatment teams; a 

mental health model for outpatient settings in the 

military. Mil Med. 2011;176(9):986-990.

18. Cho HJ, Lavretsky H, Olmstead R, Levin MJ, 

Oxman MN, Irwin MR. Sleep disturbance and 

depression recurrence in community-dwelling 

older adults: a prospective study. A J Psychiatry. 

2008;165(12):1543-1550.

19. Halbauer JD, Ashford JW, Zeitzer JM, Adamson 

MM, Lew HL, Yesavage JA. Neuropsychiatric diagnosis and management of chronic sequelae of 

war-related mild to moderate traumatic brain injury. J Rehabil Res Dev. 2009;46(6):757-796.

20. O’Connor MF, Irwin MR. Links between behavioral factors and infl ammation. Clin Pharmacol Ther. 

2010;87(4):479-482.

21. Irwin MR. Infl ammation at the intersection of 

behavior and somatic symptoms. Psychiatr Clin 

North Am. 2011;34(3):605-620.

22. Irwin MR, Carrillo C, Olmstead R. Sleep loss activates cellular markers of infl ammation: sex differences. Brain Behav Immun. 2010;24(1):54-57.

23. Irwin MR, Wang M, Ribeiro D, et al. Sleep loss activates cellular infl ammatory signaling. Biol Psychiatry. 2008;64(6):538-540.
106 http://www.cs.amedd.army.mil/amedd_journal.aspx

SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD:

THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION

24. Motivala SJ, Sarfatti A, Olmos L, Irwin MR. Infl ammatory markers and sleep disturbance in major 

depression. Psychosom Med. 2005;67(2):187-194.

25. Nicassio PM, Ormseth SR, Kay M, et al. The contribution of pain and depression to self-reported 

sleep disturbance in patients with rheumatoid arthritis. Pain. 2012;153(1):107-112.

26. Alhola P, Polo-Kantola P. Sleep deprivation: Impact 

on cognitive performance. Neuropsychiatr Dis 

Treat. 2007;3(5):553-567.

27. Czeisler CA. Impact of sleepiness and sleep defi ciency on public health–utility of biomarkers. J 

Clin Sleep Med. 2011;7(suppl 5):S6-S8.

28. Liberalesso PB, D’Andrea KF, Cordeiro ML, Zeigelboim BS, Marques JM, Jurkiewicz AL. Effects 

of sleep deprivation on central auditory processing. 

BMC Neurosci. 2012;13:83.

29. Minkel JD, Banks S, Htaik O, et al. Sleep deprivation and stressors: evidence for elevated negative 

affect in response to mild stressors when sleep deprived. Emotion. 2012;12(5):1015-1020.

30. Mong JA, Baker FC, Mahoney MM, et al. 

Sleep, rhythms, and the endocrine brain: infl uence of sex and gonadal hormones. J Neurosci. 

2011;31(45):16107-16116.

31. Weeks SR, McAuliffe CL, Durussel D, Pasquina 

PF. Physiological and psychological fatigue in 

extreme conditions: the military example. PM R. 

2010;2(5):438-441.

32. Hung HC, Yang YC, Ou HY, Wu JS, Lu FH, 

Chang CJ. The association between self-reported 

sleep quality and metabolic syndrome. PLoS One. 

2013;8(1):e54304.

33. Uchida S, Shioda K, Morita Y, Kubota C, Ganeko 

M, Takeda N. Exercise effects on sleep physiology. 

Front Neurol. 2012;3:48.

34. Yamanaka Y, Hashimoto S, Tanahashi Y, Nishide 

SY, Honma S, Honma K. Physical exercise accelerates reentrainment of human sleep-wake cycle but 

not of plasma melatonin rhythm to 8-h phase-advanced sleep schedule. Am J Physiol Regul Integr 

Comp Physiol. 2010;298(3):R681-R691.

35. Grandner MA, Jackson NJ, Gerstner JR, Knutson 

KL. Dietary nutrients associated with short and 

long sleep duration: data from a nationally representative sample. Appetite. 2013;64:71-80.

36. Golley RK, Maher CA, Matricciani L, Olds TS. 

Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI 

in children and adolescents. Int J Obes (Lond). 

2013;37(4):546-551.

37. St-Onge MP. The role of sleep duration in the regulation of energy balance: effects on energy intakes 

and expenditure. J Clin Sleep Med. 2013;9(1):73-80.

38. St-Onge MP, Roberts AL, Chen J, et al. Short sleep 

duration increases energy intakes but does not 

change energy expenditure in normal-weight individuals. Am J Clin Nutr. 2011;94(2):410-416.

39. Gebhart C, Erlacher D, Schredl M. Moderate exercise plus sleep education improves self-reported 

sleep quality, daytime mood, and vitality in adults 

with chronic sleep complaints: a waiting list-controlled trial. Sleep Disord. 2011:809312 [epub Nov 

24 2011].

40. Seligman ME. Building resilience. Harv Bus Rev. 

2011;89(4):100-106, 138.

41. Peterson C, Park N, Castro CA. Assessment for 

the US Army comprehensive soldier fi tness program: the global assessment tool. Am Psychol. 

2011;66(1):10-18.

42. Firth KM, Smith K. A survey of multidimensional 

health and fi tness indexes. Mil Med. 2010;175(suppl 

1):110-117.

43. Army Regulation 600-9: The Army Weight Control 

Program. Washington, DC: US Dept of the Army; 

November 2006: Available at: http://www.apd.

army.mil/pdffi les/r600_9_x.pdf. Accessed February 23, 2013.

44. Lemieux S, Prud’homme D, Bouchard C, Tremblay 

A, Despres JP. A single threshold value of waist 

girth identifi es normal-weight and overweight subjects with excess visceral adipose tissue. Am J Clin 

Nutr. Nov 1996;64(5):685-693.

45. Moul DE, Mai E, Shablesky M, et al. The 2-item 

and 20-item versions of the Pittsburgh Insomnia 

Rating Scale (PIRS): design methods and initial 

modeling. Paper presented at: Annual Meeting of 

the World Psychiatric Association; November 29, 

2009; Melbourne, Australia.

46. Moul DE, Pilkonis P, Miewald J, Carey T, Buysse D. 

Preliminary study of the test-retest reliability and 

concurrent validities of the Pittsburgh Insomnia 

Rating Scale (PIRS). Sleep. 2002;25:A246-A247.

47. Guenther PM, Reedy J, Krebs-Smith S, Reeve 

B, Basiotis PP. Development and Evaluation of 

the Healthy Eating Index-2005: Technical Report. 

Alexandria, VA: Center for Nutrition Policy and 

Promotion, US Department of Agriculture; 2007. 

Available at: http://www.cnpp.usda.gov/publica

tions/hei/hei-2005/hei-2005technicalreport.pdf. 

Accessed August 1, 2013.

48. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet 

Assoc. 2008;108(11):1896-1901.

49. Guenther PM, Reedy J, Krebs-Smith SM, Reeve 

BB. Evaluation of the Healthy Eating Index-2005. J 

Am Diet Assoc. 2008;108(11):1854-1864.
 October – December 2013 107

THE ARMY MEDICAL DEPARTMENT JOURNAL

50. Weinstein SJ, Vogt TM, Gerrior SA. Healthy Eating Index scores are associated with blood nutrient 

concentrations in the third National Health And 

Nutrition Examination Survey. J Am Diet Assoc. 

2004;104(4):576-584.

51. Purvis D, Lentino CV, Jackson TK, Murphy KJ, 

Deuster PA. Nutrition as a component of the Performance Triad: How healthy eating behaviors 

contribute to Soldier performance and military 

readiness. US Army Med Dep J. October-December 

2013:66-78.

52. Garber CE, Blissmer B, Deschenes MR, et al. 

American College of Sports Medicine position 

stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fi tness in apparently 

healthy adults: guidance for prescribing exercise. 

Med Sci Sports Exerc. 2011;43(7):1334-1359.

53. DeVellis RF. Scale development: theory and applications. In: Bickman L, Rog DJ, eds. Applied Social Research Methods Series. Vol 26. Washington, 

DC: Sage; 2012.

54. Ribeiro JD, Pease JL, Gutierrez PM, et al. Sleep 

problems outperform depression and hopelessness 

as cross-sectional and longitudinal predictors of 

suicidal ideation and behavior in young adults in 

the military. J Affect Disord. 2012;136(3):743-750.

55. Mauss IB, Troy AS, Lebourgeois MK. Poorer sleep 

quality is associated with lower emotion-regulation ability in a laboratory paradigm. Cogn Emot. 

2012;27(3):567-576.

56. Gerber M, Brand S, Holsboer-Trachsler E, Puhse 

U. Fitness and exercise as correlates of sleep complaints: is it all in our minds? Med Sci Sports Exerc. 

2010;42(5):893-901.

57. Chang-Quan H, Bi-Rong D, Yan Z. Association 

between sleep quality and cognitive impairment 

among Chinese nonagenarians/centenarians. J Clin 

Neurophysiol. 2012;29(3):250-255.

58. Ailshire JA, Burgard SA. Family relationships and 

troubled sleep among US adults: examining the 

infl uences of contact frequency and relationship 

quality. J Health Soc Behav. 2012;53(2):248-262.

59. Kim H, Rose K. Sleep disturbances in family caregivers: an overview of the state of the science. Arch 

Psychiatr Nurs. 2011;25(6):456-468.

60. Pollock E, Kazman J, Deuster P. Family functioning and stress in African American families: a 

strength based approach. J Black Psychol. In press.

61. Haghighatdoost F, Karimi G, Esmaillzadeh A, 

Azadbakht L. Sleep deprivation is associated with 

lower diet quality indices and higher rate of general 

and central obesity among young female students 

in Iran. Nutrition. 2012;28(11-12):1146-1150.

62. Kim S, DeRoo LA, Sandler DP. Eating patterns and 

nutritional characteristics associated with sleep duration. Public Health Nutr. 2011;14(5):889-895.

63. Hitze B, Bosy-Westphal A, Bielfeldt F, et al. Determinants and impact of sleep duration in children 

and adolescents: data of the Kiel Obesity Prevention Study. Eur J Clin Nutr. 2009;63(6):739-746.

64. Cheng SH, Shih CC, Lee IH, et al. A study on the 

sleep quality of incoming university students. Psychiatry Res. 2012;197(3):270-274.

65. Maffeis C, Fornari E, Surano MG, et al. Breakfast 

skipping in prepubertal obese children: hormonal, 

metabolic and cognitive consequences. Eur J Clin 

Nutr. 2012;66(3):314-321.

66. Wesnes KA, Pincock C, Scholey A. Breakfast is 

associated with enhanced cognitive function in 

schoolchildren. An internet based study. Appetite. 

2012;59(3):646-649.

67. Pivik RT, Tennal KB, Chapman SD, Gu Y. Eating 

breakfast enhances the effi ciency of neural networks engaged during mental arithmetic in schoolaged children. Physiol Behav. 2012;106(4):548-555.

68. Kral TV, Heo M, Whiteford LM, Faith MS. Effects 

on cognitive performance of eating compared with 

omitting breakfast in elementary schoolchildren. J 

Dev Behav Pediatr. 2012;33(1):9-16.

69. Liu J, Hwang WT, Dickerman B, Compher C. 

Regular breakfast consumption is associated with 

increased IQ in kindergarten children. Early Hum 

Dev. 2013;89(4):257-262.

70. Deshmukh-Taskar P, Nicklas TA, Radcliffe JD, 

O’Neil CE, Liu Y. The relationship of breakfast 

skipping and type of breakfast consumed with 

overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome in young adults. The National Health and 

Nutrition Examination Survey (NHANES): 1999-

2006. Public Health Nutr. October 2, 2012 [epub].

71. Narang I, Manlhiot C, Davies-Shaw J, et al. Sleep 

disturbance and cardiovascular risk in adolescents. 

CMAJ. 2012;184(17):E913-E920.

72. Chaput JP, Tremblay A. Sleeping habits predict the 

magnitude of fat loss in adults exposed to moderate 

caloric restriction. Obes Facts. 2012;5(4):561-566.

73. Thomson CA, Morrow KL, Flatt SW, et al. Relationship between sleep quality and quantity and 

weight loss in women participating in a weightloss intervention trial. Obesity (Silver Spring). 

2012;20(7):1419-1425.

74. Buysse DJ, Reynolds CF III, Monk TH, Berman 

SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and 

research. Psychiatry Res. 1989;28(2):193-213.
108 http://www.cs.amedd.army.mil/amedd_journal.aspx

SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD:

THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION

75. Carpenter JS, Andrykowski MA. Psychometric evaluation of the Pittsburgh Sleep Quality Index. J Psychosom Res. 

1998;45(1):5-13.

AUTHORS

Ms Lentino is a Research Associate, Consortium for 

Health and Military Performance, Department of 

Military and Emergency Medicine, Uniformed Services 

University of the Health Sciences, Bethesda, Maryland.

Dr Purvis is Director, Strategic Operations and 

Special Projects, Consortium for Health and Military 

Performance, Department of Military and Emergency 

Medicine, Uniformed Services University of the Health 

Sciences, Bethesda, Maryland.

Ms Murphy is a Research Associate, Consortium 

for Health and Military Performance, Department of 

Military and Emergency Medicine, Uniformed Services 

University of the Health Sciences, Bethesda, Maryland.

Dr Deuster is Professor and Director, Consortium 

for Health and Military Performance, Department of 

Military and Emergency Medicine, Uniformed Services 

University of the Health Sciences, Bethesda, Maryland.
 October – December 2013 109

SLEEP IS A PHYSIOLOGICAL REQUIREMENT

Like the need for food, water, and air, the need for sleep 

is physiologically based. However, sleep differs from 

other basic physiological needs in several key respects. 

The most salient of these is the fact that sleep is not actually necessary to sustain human life. Although there are 

limits to the duration of time that life can be sustained in 

the absence of food, water, or air, there is no known limit 

to the number of hours/days/weeks that humans can go 

without sleep. In a series of studies conducted at the University of Chicago in the early 1980s, Retschaffen and 

colleagues1

 reported that rats that were totally deprived 

of sleep died within 2-3 weeks. At the time those studies 

were published, the mechanism by which total sleep loss 

effected death in the rats was not clear. It was subsequently shown that preceding death, sleep-deprived rats 

display transmigration of bacteria from the gut that results in widespread extraintestinal infection/septic load.2

Similar effects of sleep loss have not been observed in 

any other species, including humans (and notably, neither humans nor rats can volitionally go without sleep 

for more than a few days, meaning that nonvolitional 

behavioral methods or pharmacological methods must 

then be used to maintain wakefulness).

Accordingly, there are no known instances in which 

a human death has been directly attributed to sleep 

deprivation. Of course, there are numerous instances in 

which insuffi cient sleep has indirectly resulted in death: 

for example, the Automobile Association of America estimates that between 1999 and 2008 sleepiness was a 

contributing factor in 16.5% of traffi c fatalities (approximately 69,300 deaths) in the United States.3

 And it is 

clear that insuffi cient sleep exacts an enormous economic toll as well, with yearly costs resulting from home and 

industrial accidents, errors, and ineffi ciencies estimated 

to cost the US economy hundreds of billions of dollars 

per year.4

 But there is no evidence that sleep subserves 

any physiological function that is directly necessary for 

sustaining life. Patients with a rare prion disease called 

fatal familial insomnia experience total insomnia for 

several months before eventually succumbing; however, 

it is likely that these deaths are the result of other aspects 

of the disorder (for example, the large thalamic lesions 

that also characterize the disorder).5

 Also, patients can 

be kept alive in a coma for decades, and coma is not

sleep. In fact, some patients with a diagnosis of vegetative state/unresponsive wakefulness syndrome show no 

discernible evidence of sleep.6

This is not to say that sleep plays no role in the maintenance of health. Over the past 2 decades, evidence that 

chronic sleep disturbance is associated with mood disorder,7

 impaired immune function,8 age-related cognitive 

decline,9

 metabolic syndrome/obesity/diabetes,10 heart 

The Challenge of Sleep Management

 in Military Operations

Nancy J. Wesensten, PhD

Thomas J. Balkin, PhD

ABSTRACT

It has long been known that short-term (days) insuffi cient sleep causes decrements in mental effectiveness that 

put individuals at increased risk of committing errors and causing accidents. More recently, it has been discovered that chronic poor sleep (over years) is associated with a variety of negative health outcomes (metabolic 

syndrome, obesity, degraded behavioral health). Implementing an effective sleep health program is, therefore, 

in the best interests of active duty personnel and their families both in the short- and long-term. Like managing 

physical activity or nutrition, effectively managing sleep health comes with its unique set of challenges arising 

from the fact that individuals who routinely do not obtain suffi cient sleep are generally desensitized to feeling 

sleepy and are poor at judging their own performance capabilities—and individuals cannot be compelled to 

sleep. For these reasons, an optimally effective sleep health program requires 3 components: (1) a rigorous, evidence-based sleep education component to impart actionable knowledge about optimal sleep amounts, healthy 

sleep behaviors, the known benefi ts of sleep, the short- and long-term consequences of insuffi cient sleep, and to 

dispel myths about sleep; (2) a nonintrusive device that objectively and accurately measures sleep to empower 

the individual to track his/her own sleep/wake habits; and (3) a meaningful, actionable metric refl ecting sleep/

wake impact on daily effectiveness so that the individual sees the consequences of his/her sleep behavior and, 

therefore, can make informed sleep health choices.
110 http://www.cs.amedd.army.mil/amedd_journal.aspx

THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS

disease,11 and even cancer12 has steadily accrued. The exact mechanism(s) by which sleep exerts its infl uence on 

these disorders is not known. Also unknown is whether 

sleep disturbance exerts a direct causal or indirect infl uence. Compared to food, air, or water—resources obtained from the environment that when removed lead to 

death in a relatively quick and straightforward manner—

sleep (a wholly internal phenomenon that depends on 

the presence of no particular environmental resources) 

is less critical for actual survival. For example, sleep is 

not critical for vegetative processes needed to maintain 

viability of individual brain cells.

Nevertheless, sleep does play a crucial role in day-today functioning: it promotes and sustains waking brain 

(specifi cally, neocortical) processes that constitute and/

or facilitate mass action-potential-dependent functions 

ranging from basic consciousness/alertness to higherorder mental abilities including situation awareness, 

problem-solving, memory, and creativity.13-15 The importance of sleep to higher-order mental abilities is illustrated in Figure 1, which depicts the effects of 24 hours 

of total sleep deprivation on regional brain metabolic 

activity. Among the cortical regions most metabolically 

degraded by sleep loss is the prefrontal cortex (blue areas located in the frontal portion of the brain), the brain 

region responsible for mediating the highest-order cognitive functions.17 A translation of such higher-order 

mental abilities into operationally relevant capabilities 

is presented in the Table. In short, sleep is a process that 

not only occurs in the brain, it is also a process that undoubtedly confers unique benefi ts to the brain itself.

PUBLIC AWARENESS OF THE IMPORTANCE OF SLEEP

Partly as a result of concerted efforts by organizations 

such as the National Institutes of Health,19,20 the Centers 

for Disease Control and Prevention,21 and the National 

Sleep Foundation,22 and partly as a result of the discovery that sleep disorders (most notably obstructive sleep 

apnea) are prevalent in United States, awareness of the 

importance of sleep has rapidly expanded within the 

general population over the past several decades. In fact, 

the term sleep apnea, fi rst coined in the scientifi c medical literature in 1976,23 is now a widely used and understood part of the American lexicon. Also, the possible 

role of insuffi cient sleep in highly publicized incidents 

including the nuclear reactor near-meltdown at Three 

Mile Island on March 28, 1979 (for which the causal human error occurred in the early morning hours24), the 

explosion of the space shuttle Challenger on January 

28, 1986 (for which the serious fl aw in decision-making also occurred during early morning hours, prior to 

launch25), the nuclear reactor meltdown at Chernobyl 

on April 26, 1986 (for which standard opinion is that 

operator error was the root cause of the disaster26), and 

more recently the 2009 Colgan Air Flight 3407 crash 

near Buffalo, NY (for which the sequence of errors that 

ultimately led to the crash are consistent with defi cits in 

higher-order cognitive abilities degraded by insuffi cient 

sleep, perhaps most notably a degraded ability to rapidly 

recognize a failed course of action and adjust accordingly27) have heightened awareness of the importance 

of adequate sleep, particularly for those engaged in occupations for which lapses in attention or judgment can 

have disastrous consequences.

HOW MUCH SLEEP?

Sleep experts are often asked by leaders, “What 

is the minimum amount of sleep that my Soldiers need to remain effective?” This question 

refl ects the tacit calculation that Soldier productivity during all hours spent asleep is zero, 

and productivity for all hours spent awake is 

greater than zero. Viewed this way, it makes 

sense to maximize the number of hours that 

troops spend awake and minimize the number 

of hours that they spend asleep each day.

However, the problem with this calculation 

becomes clear if one substitutes “mental agility” or “situational awareness” for sleep. The 

question then becomes “what is the minimum 

amount of mental agility/situational awareness that my Soldiers need to remain effective?” 

From both a physiological and practical standpoint, the answer is “more is always better.” 

There are 2 reasons for this. First, as discussed 

Figure 1. Characterization of brain metabolic activity after 24 hours of 

total sleep deprivation. Darkest shades of blue indicate areas of greatest metabolic deactivation compared to baseline (normal alertness). 

Adapted from Thomas et al.16
 October – December 2013 111

THE ARMY MEDICAL DEPARTMENT JOURNAL

previously, sleep promotes waking mental acuity: the 

more sleep that is obtained, the better the individual 

is able to maintain situational awareness, anticipate 

and solve problems, generate creative and appropriate 

solutions, etc. In battlefi eld situations, even the smallest “edge” in reaction time, situation awareness, and 

problem solving could be critical to mission success. 

Second, more sleep is always better because it ensures 

not only that sleep debt is not incurred acutely, but it 

also helps ensure that more long-term, subtle sleep debt, 

which becomes apparent under conditions of chronic 

insuffi cient sleep, does not accrue. It is this latter situation which is less appreciated but far more insidious 

and potentially problematic. Stated another way, the 

more sleep a Soldier obtains on a regular basis, the 

more resilient that Soldier becomes to the effects of 

subsequent sleep loss. In effect, the Soldier establishes a “sleep reserve”28 that can be tapped days (and 

perhaps even weeks) later to better sustain alertness 

and performance when subsequently faced with the 

challenge of sleep loss resulting from high tempo of 

operations (OPTEMPO), continuous operations, etc. 

For example, Rupp et al29 showed that volunteers who 

were allowed 10 hours time in bed per night (TIB) for 

7 nights performed better during a subsequent sleep 

restriction challenge of 3 hours TIB than volunteers 

who were allowed 7 hours TIB for 7 nights prior to the 

same 3-hour TIB challenge. The data is presented in 

Figure 2. Critically, the difference between the groups 

grew as the sleep restriction challenge continued across 

days, and recovery was faster in the 10-hour prior TIB 

group (that is, less recovery sleep was needed to restore 

alertness and performance to baseline levels). These 

fi ndings reveal the long time constant associated with 

sleep’s benefi cial effects. It may be that these enduring, 

slowly accumulating benefi cial (or, in the case of insuffi cient sleep, deleterious) effects underlie the relationship between sleep and general health, relationships that 

Operationally Relevant Capability Impacted by Sleep.

MOST IMPACTED ALSO IMPACTED LESS IMPACTED

Acquiring, assigning priorities, allocating, and 

using resources

Anticipating and solving 

problems

Managing and exploiting 

change

Acting decisively under 

pressure

Establishing position

Requesting fire

Coordinating squad 

tactics

Monitoring environment (vigilance)

Attending to preventive maintenance 

Loading 

magazines

Lifting

Digging, etc. 

Adapted from Chapter 4, Field Manual 6-22.5.

18

Study Day

7 nights of 10 hrs 

prior TIB

7 nights of 7 hrs 

prior TIB

3 Hrs 

TIB

3 Hrs 

TIB

3 Hrs 

TIB

3 Hrs 

TIB

3 Hrs 

TIB

3 Hrs 

TIB

3 Hrs 

TIB

7 or 10

Hrs TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB

0

8

6

4

2

10

Mean Estimated Lapses

Figure 2. Objective performance during a sleep restriction challenge of 3 hours time in bed (TIB) for 7 nights. For the 7 

nights immediately preceding the 3-hour TIB challenge, one group was allowed 10-hours TIB per night and the other was 

allowed approximately 7-hours TIB per night. Although performance in both groups deteriorated across the 3-hour TIB 

challenge, the rate of performance deterioration was slower, and recovery was faster, in the 10-hour TIB group. Adapted 

from Rupp et al.29
112 http://www.cs.amedd.army.mil/amedd_journal.aspx

THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS

may only become apparent over years. Little is known 

about the infl uence of prior sleep history. In controlled 

laboratory studies published to date, prior sleep history 

has been recorded only for approximately a week. Also, 

our study was the only one in which prior sleep history 

was manipulated. The infl uence of sleep history may be 

greater than the magnitude shown in results from crosssectional studies,30 that is, the extent to which sleep 

can be banked may be greater than that shown in our 

relatively short-term (7 days of banking) study. Ideally, 

future longitudinal studies will be conducted in which 

volunteers’ daily sleep amounts are tracked over weeks, 

months, and/or years, and compared against sensitive 

and relevant metrics of neurobehavioral performance, 

physical health, behavioral health, etc.

Although more sleep is always better in terms of alertness and performance, it is not invariably the case that 

sleep opportunity should always be maximized during 

military operations. Because recuperative benefi ts do not 

accrue linearly during sleep,32 within every operational 

situation there is a point at which extra sleep provides 

diminishing returns: an infl ection point at which the 

amount of recuperation (mental acuity/resilience) that 

is gained by extending sleep duration is outweighed by 

the short-term benefi ts (in terms of work/productivity) 

that can be realized by having the Soldier remain awake 

performing his or her duties. Thus, just as carrying too 

much fuel, food, and ammunition for a particular mission can exact costs in terms of effi ciency or effectiveness, it is possible that too much time allocated for sleep 

could cut into military effectiveness by ineffi ciently cutting into the number of hours of productive wakefulness.

In reality, the likelihood of a scenario in which too much 

time is allotted for sleep during a military operation is 

low. With the generally high OPTEMPO of military operations, the problem has been (and will likely remain) 

ensuring that nominally adequate time is allotted for 

sleep. In practice, this not only means allotting adequate 

time for sleep itself, but additionally allotting adequate 

time for other activities (calling home, for example) for 

which military personnel will invariably sacrifi ce sleep, 

if forced to choose between the two.

Therefore, the primary target of opportunity, the lynchpin of success for a sleep/alertness management program, will be a change in behavior in which each person 

conscientiously and voluntarily optimizes sleep during 

whatever time(s) he has available. In order to achieve 

this, it will fi rst be necessary to get “buy-in” (through 

reeducation) to the simple truth that in the operational 

environment, Soldiers not only put themselves at risk, 

but also potentially endanger their fellow Soldiers by 

foregoing sleep for nonessential waking activities. It 

will also be necessary to educate the larger Army family regarding the relationship between optimal sleep and 

everyday functioning, including but not limited to better 

on-the-job performance, better motivation to maintain 

a fi tness program, better school performance, and improved mood.

WHAT DRIVES OUR SLEEP BEHAVIOR?

This change in behavior and attitude is neither simple 

nor straightforward because when left to our own devices, we as individuals and as a society rarely opt to 

maximize sleep duration, and thus optimize next-day 

alertness and performance. Instead, we seem to choose 

sleep durations that strike an implicitly self-selected 

balance between engagement in competing waking 

activities (both work-related activities and recreational 

pastimes such as watching television, playing video 

games, etc) and the physiological need/desire to sleep, 

resulting in an objectively less-than-optimal (but subjectively tolerable and sustainable) level of chronic, mild 

sleep restriction.

There is a good explanation for why we do not obtain 

more sleep: over days/weeks (and also months and 

years) of insuffi cient sleep, individuals become inured 

to the feeling of sleepiness, the primary mechanism by 

which the brain communicates the need for sleep. When 

asked how they feel, individuals with untreated obstructive sleep apnea will often reply that they feel normally 

alert, even though they cannot maintain wakefulness 

under nonstimulating situations such as sitting in meetings, watching television, and sometimes even while 

driving a vehicle under monotonous conditions. By all 

objective criteria, these individuals are pathologically 

sleepy (unable to maintain wakefulness for more than 

a few minutes when subjected to a nonstimulating environment), yet they do not consider themselves to be 

excessively sleepy. It is as though over months or years 

of insuffi cient sleep, their set-point or threshold for subjective sleepiness has substantially increased. Similarly, 

in one study, Belenky et al33 showed that this habituation to subjective sleepiness occurs within a few days of 

switching from an 8-hour TIB schedule to a 3-hour TIB 

schedule. Notably, subjective sleepiness did not track 

objective performance, which continued to degrade 

across sleep restriction (Figure 3). The abrupt transition 

from 8 hours TIB to 3 hours TIB may not mimic realworld conditions in which individuals may volitionally 

increase total recuperative sleep time (TrST) over time, 

but a similar lack of correspondence between performance and subjective alertness was evident in both the 

5-hour and 7-hour TIB groups in which the TIB decrement was not so drastic.
 October – December 2013 113

THE ARMY MEDICAL DEPARTMENT JOURNAL

Figure 3. Objective performance (panel A—mean reciprocal reaction time on a simple one-choice 

reaction time task) and subjective alertness (panel B—responses on the Stanford Sleepiness 

Scale) across days on different nightly sleep schedules. Adapted from Belenky et al.33

TIB indicates time in bed per night. RT indicates reaction time.

Study Day

9 Hrs TIB

7 Hrs TIB

5 Hrs TIB

3 Hrs TIB

3.75

2.25

2.75

3.25

4.25

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB 3, 5, 7, or 9 Hrs TIB

Mean Reciprocal Reaction Time

(1/RT×1000)

Panel A

Study Day

9 Hrs TIB

7 Hrs TIB

5 Hrs TIB

3 Hrs TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB

8 Hrs 

TIB 3, 5, 7, or 9 Hrs TIB

1.0

6.0

2.0

3.0

4.0

5.0

7.0 Panel B

Mean Sleeping Score

(Range 1-7)

No longer fi ghting sleep; sleep onset 

soon; having dream-like thoughts

Feeling active, vital,

alert, or wide awake
114 http://www.cs.amedd.army.mil/amedd_journal.aspx

THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS

Stated another way, we generally fail to appreciate the 

deleterious effect of insuffi cient sleep on our own performance. We suffer few (if any) identifi able day-to-day 

negative consequences of insuffi cient sleep. We may 

nod off during an afternoon briefi ng, not appreciating 

that this is a cardinal sign of insuffi cient sleep, but most 

of us have no objective marker (such as productivity 

at work) against which the effect of insuffi cient sleep 

can be quantifi ed and tracked. Serious consequences 

of day-to-day, commonly experienced levels of sleepiness, such as fatal automobile crashes, are relatively 

infrequent even among young adults, for whom traffi c accidents are a leading cause of death. News stories 

on high-profi le, sleepiness-related accidents may fail 

to resonate because they typically focus on workers in 

high-risk professions, such as transportation workers. 

Likewise, news stories and emerging information about 

the long-term health consequences of inadequate sleep 

may not resonate with young adults, simply because the 

potential for such problems seems too remote.

Consequently, a campaign to improve sleep health in 

the military family requires 3 components: (1) an aggressive education component, (2) an accurate, objective personal sleep assessment tool, and (3) the means 

to translate the objectively-measured sleep data into a 

relevant effectiveness prediction.

EDUCATION COMPONENT

Myths, misinterpretations/misrepresentations of fact 

and old wives’ tales regarding sleep are common. This 

situation is magnifi ed by nearly universal access to the 

internet, where misinformation can be rapidly disbursed 

among and perpetuated by millions of people. Self-identifi ed “experts” who appear on television and radio talk 

shows and sensationalize research fi ndings or disseminate misinformation unwittingly compound the problem.

Therefore, a campaign to change sleep behavior starts 

with education to ensure that our active duty military 

personnel and their families receive accurate (nonsensationalized) and timely information about the currently 

known benefi ts of sleep and consequences of insuffi -

cient sleep. Education is required to dispel beliefs based 

in myth, misinformation, and/or outdated information. 

For example, it is widely held, even among some sleep 

experts, that naps should be curtailed or limited in duration to avoid “sleep inertia” (degraded alertness and 

performance upon awakening). This myth appears to 

be rooted in a non–peer-reviewed report in which the 

authors incorrectly extrapolated the transition through 

sleep stages that occurs within the confi nes of a wellcontrolled laboratory environment to real-world conditions. It also appears to be based on a publication in 

which the duration of sleep inertia was estimated to be 

up to 4 hours, an overestimation based on the known 

improvement in performance, even in totally sleep-deprived individuals, that occurs across the day as a result 

of the circadian alertness signal.*

The desired outcome of an educational effort is that 

military leaders appreciate the role of sleep in mission 

success and consequently prioritize sleep in the missionplanning process, and individual Soldiers and their family members likewise understand the importance of sleep 

and also choose to prioritize it: they voluntarily devote 

maximum free time to sleep and voluntarily minimize 

sleep-stealing activities such as video games.

ACCURATE, OBJECTIVE SLEEP ASSESSMENT

The second component for behavior change is an objective and accurate sleep assessment tool to quantify and 

track the behavior of interest, in this case, sleep. For the 

vast majority of individuals (nonclinical settings), the 

key sleep parameter is TrST per 24 hours. The timing 

of sleep within the 24-hour period affects TrST in a predictable way: during a daytime sleep period, individuals awaken frequently, although they may not remember 

these awakenings, which may last only a few seconds 

to a few minutes. Daytime “sleep fragmentation” or degraded “sleep quality” is caused by the brain’s circadian 

alertness signal* and/or from light, noise, or other environmental disruptions. Time spent awake, no matter 

how brief, reduces TrST within a given period allocated 

for sleep. That is, sleep quality and sleep quantity are 

actually the same.34 It was previously thought that sleep 

“continuity” or “fragmentation” was a parameter of sleep 

that was independent of other sleep metrics such as 

amount of time spent in the various sleep stages, which 

sum to total sleep time. However, results of numerous 

studies aimed at determining the basis of sleep continuity led to the same conclusion: there is no evidence that 

sleep continuity or sleep fragmentation are measurable 

factors contributing independently to recuperation during sleep.34

Currently, the technology best suited for objectively 

tracking relevant sleep parameters in the operational 

environment is wrist actigraphy. This mature and wellvalidated technology35 is based on the observable fact 

that normal, healthy humans move their wrists more 

frequently during wakefulness (even when in engaged 

in sedentary activities like watching television) than 

during sleep. Wrist movement data are detected by an 

*The circadian alertness signal is the alertness-enhancing output 

from the suprachiasmatic nucleus that increases from morning 

to peak in the late evening, and then decreases across the night 

to trough near the normal wake time.
 October – December 2013 115

THE ARMY MEDICAL DEPARTMENT JOURNAL

accelerometer contained within the actigraph and then 

scored for sleep or wake using a sleep/wake scoring algorithm. Modern wrist actigraphs are “wear-and-forget” 

wristwatch-like devices that contain suffi cient memory 

to record wrist movement activity continuously for 4-6 

weeks at a time. For some actigraphs, the sleep/wakescoring algorithm resides on a microprocessor in the 

actigraph and sleep/wake is automatically scored. Realtime information regarding amount of time spent sleeping over the last few hours or days can be displayed on 

the actigraph face.

A limitation of actigraphy is that sleep stages cannot be 

distinguished from one another. In particular, the lightest stage of sleep (N1) which appears to have no recuperative value is indistinguishable from deeper stages 

of sleep that have been clearly linked to recuperation. 

In normal sleepers, this limitation is almost inconsequential since normal individuals do not spend appreciable amounts of time in stage N1 (and almost none at 

all if they carry a sleep debt). However, in certain patient populations who experience numerous awakenings 

(and consequently more stage N1), their total recuperative sleep may be overestimated, and less sensitive actigraphs will overestimate recuperative sleep to a greater 

extent than more sensitive devices.36,37 However, for 

purposes of improving sleep health by increasing time 

spent asleep (which is the primary issue), actigraphy 

provides a useful, objective, and cost-effective means 

of measuring the amount of sleep obtained over days/

weeks/months in a large number of individuals. That is, 

it provides individuals with a means to gauge the benefi ts of implementing behaviors and habits that promote 

healthy sleep (see “Ten Effective Sleep Habits” on the 

facing page).

ESTIMATED MENTAL EFFECTIVENESS:

AN ACTIONABLE METRIC

Accurately measuring TrST is important. Translating 

this TrST into an actionable metric is of far greater practical value (for example, knowing how much gas is in 

your vehicle’s tank is useful, but not as useful as knowing how far you can drive on that amount of gas). In this 

respect, the effects of insuffi cient sleep are akin to those 

of blood pressure, diffi cult to self-assess and thus appropriately manage without an external, objective, quantifi able measure against which the success or failure of 

management efforts can be gauged.

In terms of “sleep miles per gallon,” mental effectiveness is a key actionable metric because, as discussed 

above, the main function of sleep is to support mental 

effectiveness, which in turn underlies success in military operations and in daily living. At the group (squad, 

platoon, etc) level, such information is valuable to planners for immediate and future resource allocation. At 

the individual Soldier level, effectiveness feedback is 

valuable for providing the individual with an objective 

estimate of the extent to which his or her sleep/wake 

schedule is affecting mental performance, an estimate 

that may deviate substantially from what the wearer perceives to be his or her current mental effectiveness.

Commercial entities (most notably the airline industry) 

currently use effectiveness prediction models as part 

of prospective fatigue risk management programs. The 

most widely used model was developed by the Department of Defense (DoD).38-45 The Federal Aviation Administration recently determined that effectiveness 

models (and specifi cally the DoD model) have undergone suffi cient evaluation to be used in aviation fatigue 

risk management decisions. The US Naval Safety Center uses the DoD effectiveness model to retrospectively 

analyze the potential role of fatigue (insuffi cient sleep 

and circadian factors) in mishap investigations, and the 

USAF Air Mobility Command uses model predictions 

as a component of its aviation operational risk management matrix. For these types of applications, sleep/wake 

is not measured directly but is estimated based on fl ight 

schedule, travel across time zones, etc. Fatigue mitigation strategies also can be modeled. For example, the 

effectiveness benefi t realized by obtaining a 30-minute 

in-fl ight nap (for operations in which in-fl ight napping 

is allowed) can be modeled, and the resulting effectiveness used as the basis for informed decision-making.

SLEEP, MENTAL EFFECTIVENESS, AND LONG-TERM 

PERFORMANCE TRIAD GOALS

In the short term, the goal of the Performance Triad is to 

“improve individual performance and resilience through 

improved sleep, activity, and nutrition discipline.”46 As 

outlined above, mental effectiveness serves as the objective marker of sleep health.

But what is the long-term goal that can be subserved by 

improved sleep (and thereby improved mental effectiveness)? As Army Surgeon General LTG Patricia Horoho 

stated, 

We will continue to encourage members of the Army 

Family to incorporate health-promoting behaviors and 

decisions into their everyday lives. The success will be 

measured by the improvement in health and the reduction of disease and injury among Army team members.47

As noted earlier, although the exact mechanism(s) by 

which sleep promotes long-term health are not yet clear, 

mounting evidence indicates a link between chronic 

poor sleep and a myriad of behavioral and physical 
116 http://www.cs.amedd.army.mil/amedd_journal.aspx

THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS

health ailments. Regardless of mechanism, the implication is clear: improving sleep health is a “win-win,” both 

in the short-term and the long-term.

SUMMARY AND CONCLUSIONS

One goal of an effective sleep education effort is to ensure that leaders understand the importance of sleep 

and, as a consequence of this understanding, provide 

adequate daily sleep opportunities for their personnel 

during military operations, to the extent possible within 

the constraints of mission requirements and exigencies. 

Also, it is critical that Soldiers and their families appreciate the importance of sleep for overall health so that 

they are motivated to actually use their time wisely to 

optimize the amount of sleep obtained on a daily basis. 

With respect to the latter, the use of technologies such 

as wrist actigraphy and effectiveness prediction models will prove invaluable for tracking and maintaining 

the desired behaviors, ultimately resulting in a healthier, 

more effective, and more productive military.

Ten Effective Sleep Habits

1. Create a quiet, dark, comfortable sleeping environment. Cover windows with darkening drapes or 

shades (dark trash bags work as well), or wear a sleep mask to block light. Minimize disturbance from 

environmental noises with foam earplugs or use a room fan to muffl e noise. If you can, adjust the room 

temperature to suit you. If you cannot, use extra blankets to stay warm. Use a room fan both to muffl e 

noise and keep you cool.

2. Use the bedroom only for sleep and intimacy. Remove the TV, computer, laptop, and other electronic 

distractions from your bedroom. Do not eat or drink in bed. Keep discussions or arguments out of the 

bedroom.

3. Stop caffeine consumption at least 6 hours before bedtime. Caffeine promotes wakefulness and 

disrupts sleep. 

4. Do not drink alcohol before bed. Alcohol initially makes you feel sleepy, but disrupts and lightens 

your sleep several hours later. In short, alcohol reduces the recuperative value of sleep. Nicotine, and 

withdrawal from nicotine in the middle of the night, also disrupts sleep. If you need help quitting drinking 

or using nicotine products, see your healthcare provider for options.

5. Complete your exercise by early evening. Exercising is great, just be sure to fi nish at least 3 hours 

before bedtime so that you have plenty of time to wind down.

6. Do not go to bed hungry. A light bedtime snack (eg, milk and crackers) can be helpful, but do not eat a 

large meal close to bedtime. And empty your bladder just before you go to bed so that the urge to urinate 

does not disrupt your sleep.

7. Maintain a consistent, regular routine that starts with a fi xed wakeup time. Start by setting a fi xed time 

to wake up, get out of bed, and get exposure to light each day. Pick a time that you can maintain during 

the week and on weekends, then adjust your bedtime to target 7-8 hours of sleep.

8. Get out of bed if you cannot sleep. Only go to bed (and stay in bed) when you feel sleepy. Do not try to 

force yourself to fall asleep; it will tend to make you more awake, making the problem worse. If you wake 

in the middle of the night, give yourself about 20 minutes to return to sleep. If you do not return to sleep 

within 20 minutes, get out of bed and do something relaxing. Do not return to bed until you feel sleepy. 

9. Nap wisely. Napping can be a good way to make up for poor or reduced nighttime sleep, but too much 

napping can cause problems falling asleep or staying asleep at night. If you need to nap for safety reasons 

such as driving, try to do so in the late morning or early afternoon, perhaps right after lunch, to take the 

edge off your sleepiness.

10. Move the clock from your bedside. If you tend to check the clock two or more times during the night, 

and if you worry that you are not getting enough sleep, cover the clock face or turn it around so that you 

cannot see it (or remove the clock from the bedroom entirely). 

The Ten Effective Sleep Habits were assembled by the Army Surgeon General’s Performance Triad Sleep Working Group.
 October – December 2013 117

THE ARMY MEDICAL DEPARTMENT JOURNAL

ACKNOWLEDGEMENTS

The authors gratefully acknowledge members of The 

Army Surgeon General’s Performance Triad Sleep 

Work Group: COL Steven Lewis (lead), AMEDDC&S; 

LTC Stephen Franco, US Army Training and Doctrine 

Command; Dr James Cartwright, US Army Public Health 

Command; COL William Frey, San Antonio Military 

Medical Center; LTC Christopher Lettieri, Walter Reed 

National Military Medical Center; and Dr Christine 

O’Riley, Landstuhl Regional Medical Center. The ideas 

presented in this paper were shaped and refi ned through 

weekly discussions with the Sleep Working Group.

REFERENCES

1. Rechtschaffen A, Bergmann BM, Everson CA, 

Kushida CA, Gilliland MA. Sleep deprivation in 

the rat: X. Integration and discussion of the fi ndings. Sleep. 1989;12(1):68-87. 

2. Everson CA, Toth LA. Systemic bacterial invasion 

induced by sleep deprivation. Am J Physiol Regul 

Integr Comp Physiol. 2000;278(4):R905-R916.

3. Tefft BC. The prevalence and impact of drowsy 

driving [internet]. Washington, DC: AAA Foundation for Traffi c Safety; 2010. Available at: 

https://www.aaafoundation.org/sites/default/

files/2010DrowsyDrivingReport.pdf. 

Accessed August 13, 2013.

4. Functional and economic impact of sleep loss and 

sleep-related disorders. In: Colten HR, Altevogt 

BM, eds. Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem. Washington, DC: National Academies Press; 2006: chptr 4. 

Available at: http://www.ncbi.nlm.nih.gov/books/

NBK19958/. Accessed August 13, 2013.

5. Xie WL, Shi Q, Xia SL, et al. Comparison of the 

pathologic and pathogenic features in six different regions of postmortem brains of three patients with fatal familial insomnia. Int J Mol Med. 

2013;31(1):81-90.

6. Cologan V, Drouot X, Parapatics S, Delorme A, 

Gruber G, Moonen G, Laureys S. Sleep in the unresponsive wakefulness syndrome and minimally 

conscious state. J Neurotrauma, 2013;30(5):339-346.

7. Ohayon MM, Roth T. Place of chronic insomnia in 

the course of depressive and anxiety disorders. J 

Psychiatr Res. 2003;37(1):9-15.

8. Rogers NL, Szuba MP, Staab JP, Evans DL, 

Dinges DF. Neuroimmunologic aspects of sleep 

and sleep loss. Semin Clin Neuropsychiatry. 

2001;6(4):295-307.

9. Jelicic M, Bosma H, Ponds RW, Van Boxtel MP, 

Houx PJ, Jolles J. Subjective sleep problems in later 

life as predictors of cognitive decline. Report from 

the Maastricht Ageing Study (MAAS). Int J Geriatr Psychiatry. 2002;17(1):73-77.

10. Van Cauter E, Spiegel K, Tasali E, Leproult R. Metabolic consequences of sleep and sleep loss. Sleep 

Med. 2008;9(suppl 1):S23-S28.

11. Sands-Lincoln M, Loucks EB, Lu B, et al. Sleep 

duration, insomnia, and coronary heart disease 

among postmenopausal women in the women’s 

health initiative. J Womens Health (Larchmt). 

2013;22(6):477-486.

12. Sigurdardottir LG, Valdimarsdottir UA, Mucci LA, 

et al. Sleep disruption among older men and risk 

of prostate cancer. Cancer Epidemiol Biomarkers 

Prev. 2013;22(5):872-879.

13. Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol. 

2005;25(1):117-129.

14. Goel N, Rao H, Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin 

Neurol. 2009;29:320-339.

15. Poe GR, Walsh CM, Bjorness TE. Cognitive neuroscience of sleep. Prog Brain Res. 2010;185:1-19.

16. Thomas M, Sing H, Belenky G, et al. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep 

deprivation on waking human regional brain activity. J Sleep Res. 2000;9(4):335-352.

17. Damasio AR. On some functions of the human prefrontal cortex. Ann N Y Acad Sci. 1995:769:241-251.

18. Field Manual 6-22.5: Combat and Operational 

Stress Control Manual for Leaders and Soldiers. 

Washington, DC: US Dept of the Army; March 

2009: chap 4.

19. NIH: sleep disorders information [internet]. Washington, DC: National Institutes of Health. Available 

at: http://www.nhlbi.nih.gov/health/public/sleep/. 

Accessed August 13, 2013.

20. NIH: brain basics, understanding sleep [internet]. 

Washington, DC: National Institutes of Health; 

[updated May 21, 2007]. Available at: http://www.

ninds.nih.gov/disorders/brain_basics/understand

ing _sleep.htm#dynamic_activity. 

Accessed August 13, 2013.

21. CDC: sleep and sleep disorders [internet]. Atlanta, 

GA: Centers for Disease Control and Prevention; 

[reviewed May 3, 2012]. Available at: http://www.

cdc.gov/sleep/. Accessed August 13, 2013.

22. National Sleep Foundation (US): sleep is vital to 

our health & well being [internet]. Arlington, VA: 

National Sleep Foundation; 2013. Available at: 

http://www.sleepfoundation.org/. 

Accessed August 13, 2013.

23. Guilleminault C, Tilkian A, Dement WC. The sleep 

apnea syndromes. Ann Rev Med. 1976;27: 465-484.
118 http://www.cs.amedd.army.mil/amedd_journal.aspx

24. Report of The President’s Commission on The Accident at Three Mile Island. Washington, DC: US 

Government Printing Offi ce; October 30, 1979. 

Available at: http://www.threemileisland.org/down

loads/188.pdf. Accessed August 13, 2013.

25. R eport of the Presidential Commission on the Space 

Shuttle Challenger Accident. Washington, DC: US 

Government Printing Offi ce; June 6, 1986. Available at http://history.nasa.gov/rogersrep/genindex.

htm. Accessed August 14, 2013.

26. S tang E. Chernobyl-system accident or human error? Radiat Prot Dosimetry. 1996;68(3-4):197-201. 

27. Sumwalt RL. The anatomy of an accident: Colgan 

Air fl ight 3407 [internet]. February 12, 2010. Available at: http://www.ntsb.gov/doclib/speeches/sumwalt/SCAA-100212.pdf. Accessed August 14, 2013.

28. S taff RT. Reserve, brain changes, and decline. Neuroimaging Clin N A. 2012;22(1):99-105,

29. R upp TL, Wesensten NJ, Bliese PD, Balkin TJ. 

Banking sleep: realization of benefi ts during 

subsequent sleep restriction and recovery. Sleep. 

2009;32(3):311-321.

30. Lentino CV, Purvis DL, Murphy KJ, Deuster PA. 

Sleep as a component of the performance triad: the 

importance of sleep in a military population. US 

Army Med Dep J. October-December 2013:97-107.

31. B elenky G. Sleep, sleep deprivation, and human performance in continuous operations. Paper presented 

at: Joint Services Conference on Professional Ethics; 

30-31 January 1997; Washington, DC. Available at: 

http://isme.tamu.edu/JSCOPE97/Belenky97/Belen

ky97.htm. Accessed August 14, 2013.

32. H arrison Y, Horne JA. Long-term extension to 

sleep–are we really chronically sleep deprived?. 

Psychophysiology. 1996;33(1);22-30.

33. Be lenky G, Wesensten NJ, Thorne DR, et al. Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J Sleep Res. 

2003;12(1):1-12.

34. We sensten NJ, Balkin TJ, Belenky G. Does sleep 

fragmentation impact recuperation? A review and 

reanalysis. J Sleep Res. 1999;8(4):237-245.

35. Ma rtin JL, Hakim AD. Wrist actigraphy. Chest. 

2011;139(6):1514-1527. 

36. Mo ntgomery-Downs HE, Insana SP, Bond JA. 

Movement toward a novel activity monitoring device. Sleep Breath. 2012;16(3):913-917.

37. Ru pp TL, Balkin TJ. Comparison of Motionlogger 

Watch and Actiwatch actigraphs to polysomnography for sleep/wake estimation in healthy young 

adults. Behav Res Methods. 2011;43(4):1152-1160.

38. Balkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. System and method for predicting human cognitive 

performance using data from an actigraph. US patent 6 241 686. June 5, 2001.

39. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method for predicting human cognitive performance. US patent 6 419 629. July 16, 2002.

40. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. System and method for predicting human cognitive 

performance using data from an actigraph. US patent 6 527 715. March 4, 2003

41. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method and system for predicting human cognitive 

performance. US patent 6 530 884. March 11, 2003.

42. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method and system for predicting human cognitive 

performance. US patent 6 553 252. April 22, 2003.

43. Balkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method and system for predicting human cognitive 

performance. US patent 6 740 032. May 25, 2004.

44. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method and system for predicting human cognitive 

performance using data from an actigraph. US patent 6 743 167. June 1, 2004.

45. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. 

US Government [Dept of the Army], assignee. 

Method and system for predicting human cognitive 

performance. US patent 7 766 827. August 3, 2010.

46. Abdullah SP. Performance triad to lead Army medicine to system for health [internet]. Washington 

DC: US Dept of the Army; January 7, 2013. Available at: http://www.army.mil/article/93893. 

Accessed August 14, 2013.

47. Bermudez A. Surgeon General defi nes end state 

of performance triad roll out [internet]. Washington DC: US Dept of the Army; February 27, 2013. 

Available at: http://www.army.mil/article/97318. 

Accessed August 14, 2013.

AUTHORS

Dr Wesensten is a Research Psychologist in the Behavioral Biology Branch, Center for Military Psychiatry and 

Neurosciences Research, Walter Reed Institute of Research, Silver Spring, Maryland.

Dr Balkin is a Supervisory Psychologist and Chief of the 

Behavioral Biology Branch, Center for Military Psychiatry and Neurosciences Research, Walter Reed Institute of 

Research, Silver Spring, Maryland.

THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS
 October – December 2013 119

THE ARMY MEDICAL DEPARTMENT JOURNAL

The headquarters and primary instructional facility of the Army 

Medical Department Center and School, Fort Sam Houston, Texas.
120 http://www.cs.amedd.army.mil/amedd_journal.aspx
SUBMISSION OF MANUSCRIPTS TO THE ARMY MEDICAL DEPARTMENT JOURNAL

The United States Army Medical Department Journal is published quarterly to expand knowledge of domestic and international 

military medical issues and technological advances; promote collaborative partnerships among the Services, components, Corps, 

and specialties; convey clinical and health service support information; and provide a professional, high quality, peer reviewed 

print medium to encourage dialogue concerning health care issues and initiatives. 

REVIEW POLICY

All manuscripts will be reviewed by the AMEDD Journal’s Editorial Review Board and, if required, forwarded to the appropriate 

subject matter expert for further review and assessment. 

IDENTIFICATION OF POTENTIAL CONFLICTS OF INTEREST

1. Related to individual authors’ commitments: Each author is responsible for the full disclosure of all financial and personal 

relationships that might bias the work or information presented in the manuscript. To prevent ambiguity, authors must state 

explicitly whether potential conflicts do or do not exist. Authors should do so in the manuscript on a conflict-of-interest 

notification section on the title page, providing additional detail, if necessary, in a cover letter that accompanies the 

manuscript. 

2. Assistance: Authors should identify Individuals who provide writing or other assistance and disclose the funding source for this 

assistance, if any. 

3. Investigators: Potential conflicts must be disclosed to study participants. Authors must clearly state whether they have done 

so in the manuscript. 

4. Related to project support: Authors should describe the role of the study sponsor, if any, in study design; collection, analysis, 

and interpretation of data; writing the report; and the decision to submit the report for publication. If the supporting source

had no such involvement, the authors should so state. 

PROTECTION OF HUMAN SUBJECTS AND ANIMALS IN RESEARCH

When reporting experiments on human subjects, authors must indicate whether the procedures followed were in accordance with 

the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki 

Declaration of 1975, as revised in 2000. If doubt exists whether the research was conducted in accordance with the Helsinki 

Declaration, the authors must explain the rationale for their approach and demonstrate that the institutional review body 

explicitly approved the doubtful aspects of the study. When reporting experiments on animals, authors should indicate whether the 

institutional and national guide for the care and use of laboratory animals was followed. 

INFORMED CONSENT

Identifying information, including names, initials, or hospital numbers, should not be published in written descriptions, 

photographs, or pedigrees unless the information is essential for scientific purposes and the patient (or parent or guardian) gives 

written informed consent for publication. Informed consent for this purpose requires that an identifiable patient be shown the 

manuscript to be published. Authors should disclose to these patients whether any potential identifiable material might be 

available via the Internet as well as in print after publication. Patient consent should be written and archived, either with the 

Journal, the authors, or both, as dictated by local regulations or laws. 

GUIDELINES FOR MANUSCRIPT SUBMISSIONS

1. Manuscripts may be submitted either via email (preferred) or by regular mail. Mail submissions should be in digital format 

(preferably an MS Word document on CD/DVD) with one printed copy of the manuscript. Ideally, a manuscript should be no 

longer than 24 double-spaced pages. However, exceptions will always be considered on a case-by-case basis. 

2. The American Medical Association Manual of Style governs formatting in the preparation of text and references. All articles 

should conform to those guidelines as closely as possible. Abbreviations/acronyms should be limited as much as possible. 

Inclusion of a list of article acronyms and abbreviations can be very helpful in the review process and is strongly encouraged.

3. A complete list of references cited in the article must be provided with the manuscript, with the following required data: 

 Reference citations of published articles must include the authors’ surnames and initials, article title, publication title, 

year of publication, volume, and page numbers. 

 Reference citations of books must include the authors’ surnames and initials, book title, volume and/or edition if 

appropriate, place of publication, publisher, year of copyright, and specific page numbers if cited. 

 Reference citations for presentations, unpublished papers, conferences, symposia, etc, must include as much identifying 

information as possible (location, dates, presenters, sponsors, titles). 

4. Either color or black and white imagery may be submitted with the manuscript. Color produces the best print reproduction 

quality, but please avoid excessive use of multiple colors and shading. Digital graphic formats (JPG, TIFF, GIF) are preferred.

Editable versions with data sets of any Excel charts and graphs must be included. Charts/graphs embedded in MS Word cannot 

be used. Prints of photographs are acceptable. If at all possible, please do not send photos embedded in PowerPoint or MS 

Word. Images submitted on slides, negatives, or copies of X-ray film will not be published. For clarity, please mark the top of

each photographic print on the back. Tape captions to the back of photos or submit them on a separate sheet. Ensure captions 

and photos are indexed to each other. Clearly indicate the desired position of each photo within the manuscript. 

5. The authors’ names, ranks or academic/certification credentials, titles or positions, current unit of assignment, and contact 

information must be included on the title page of the manuscript. Submit manuscripts to: 

EDITOR, AMEDD JOURNAL

AHS CDD BLDG 4011 

2377 GREELEY RD STE T 

FORT SAM HOUSTON, TX 78234-7584 

DSN 471-6301 

Comm 210-221-6301 

Email: amedd.journal@amedd.army.mil 
PIN: 103753-000