October – December 2013 Perspectives 1 MG Stephen L. 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
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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 Lindl 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 rep-resented 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 Lindl and his coau-thors discuss in their article, both physical training and
PerspectivesCOMMANDER’S INTRODUCTION
MG Steve Jones
Instilling fi tness and resilience in our Soldiers, Fami-lies, 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 de-liberate approach to strengthening physical, psychologi-cal, 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 deci-sions 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 Activ-ity, 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, main-tained, and strengthened with an appropriate training regimen. By taking a systematic approach we can bet-ter 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 in-creases fl exibility while reducing stress. Other mental training activities can improve your cognitive function.
Diet has a major infl uence on overall physical and psy-chological fi tness. Quality nutrition means eating the right foods in the right quantities to improve perfor-mance 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 peri-od 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 pro-gram 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 cy-cles 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 over-training and overuse injuries. Finally, keep a training log—it helps you stay motivated, track your progress, and accomplish your goals.
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sports are essential, but are also the main cause of mus-culoskeletal 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, well-researched, carefully developed plan for achieving the necessary levels of fi tness and strength among Soldiers while signifi cantly reducing the number of musculoskel-etal injuries incurred during training and individual fi t-ness activities. This article should be the starting point for anyone charged with the development and implemen-tation of physical training plans, programs, and doctrine for military service members.
In their article, Dr Patricia Deuster and Dr Marni Silver-man 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 re-silience 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 empha-sized 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 effec-tiveness. 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 conduct-ed 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 relation-ships among focused training, regular training, fi tness levels, and injuries incurred by those involved in physi-cal training. Their comprehensive analysis demonstrates various relationships depending on various physiologi-cal 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 pre-senting 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 de-mands of the physical activity mandated by the training. To do that, those demands must be measured and quanti-fi ed. In their study, Dr Jan Redmond and her team evalu-ated 3 measurement instruments used with Soldiers in the basic combat training environment to determine the agreement among them. Each instrument had its respec-tive use limitations, overhead requirements, and other considerations which must be factored into any deci-sions concerning use in the training environment. Their article clearly describes the carefully designed and con-ducted study, the data analysis, and the results, conclu-sions, and recommendations which should be of great assistance for future training planners and evaluators.
Accurate measurement of physical activity during train-ing 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 measur-ing 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 seem-ingly 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, advertis-ing hype, habit, and other lifestyle factors. This trend has long been refl ected in an inexorable increase in obe-sity and other unhealthy, nutrition-related manifesta-tions 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 pro-fessionals. Since nutrition and good health—and there-fore 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 arti-cles presenting studies by Army health professionals ad-dressing 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 methodi-cally reduced, parsed, and analyzed that data, and cor-related 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 Initia-tive. It provides nutrition education and improved dining facility menus to Soldiers at basic combat training and advanced individual training locations in an effort to in-still good dietary habits in trainees as an inherent part of their military lifestyle. However, no program or policy will be successfully implemented without positive, ef-fective leadership, especially in the early phases of the military experience. Dr Theresa Jackson and her re-search 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 rela-tionship 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 (self-reported) eating behaviors of Soldiers in basic combat training to quantify any changes in dietary quality be-tween 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 back-ground of research, and the data collection was detailed. The results of their analysis, clearly presented in the ar-ticle, 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 Perfor-mance 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 teenag-ers 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 re-search in this area, and unquestionably demonstrate that the 3 elements of the Performance Triad are highly in-terdependent 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 educa-tion program which could be taught to military person-nel 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 un-derstood 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.
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Army Medicine is transitioning from a healthcare sys-tem to a System for Health. This means shifting the fo-cus to prevention of disease, injury, and disability. More importantly, it means advocating a culture shift to Sol-diers 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 help-ing to change the mindsets of those for whom we are professionally and personally responsible. If we can im-prove the health literacy of the Army community, our Army family will make better decisions about Activ-ity, 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 vi-tally important. Not only is it important to the survival of Army medicine as an affordable, viable entity, but al-so—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 increas-ing 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 health-care system is simply not sustainable.
The declining health status of our Soldiers, their Fam-ilies 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 mo-rale 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 chal-lenges presented, and we emerged stronger and more re-silient. Today is no different.
Everyone in Army Medicine has an active role in chang-ing 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 posi-tions at the headquarters, the regional medical com-mands, the major subordinate commands, or closer to the point of health care delivery in our medical treat-ment 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. HorohoThe Surgeon General of the United States Army
October – December 2013 5
The United States military is being transformed as de-ployments 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 Pen-tagon, presented from then Secretary of Defense, Leon Panetta and GEN Martin Dempsey, included the rec-ommendation for Army personnel strength reductions from 570,000 to 490,000 over the next 5 years.2 Second-order effects from this decline in troop strength super-imposed 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 mili-tary 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 nan-cial (such as the economic burden from medical, health-care and disability costs) and human. The injuries exac-erbate 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 popula-tions are training-related, overuse injuries.8,9
Strategies for Optimizing Military Physical Readiness and Preventing Musculoskeletal Injuries in the 21st Century
Bradley C. Nindl, PhDThomas J. Williams, PhDPatricia A. Deuster, PhD
COL Nikki L. Butler, SP, USABruce H. Jones, MD, MPH
ABSTRACTWith 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 ex-ample, 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 major-ity (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 sev-eral 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 pre-vented. 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 lever-aging scientifi c, evidence-based best practices by Army senior leadership which supports, prioritizes, and imple-ments innovative, synchronized, and integrated human performance optimization/injury prevention policy changes.
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Controlling MSIs among military personnel and continu-ing to reduce injury rates depend on institutionalizing existing best practices for injury prevention and physi-cal training, plus prioritizing relevant research in the fu-ture. Accomplishing this requires establishing stronger linkages across commands, operational personnel, re-searchers, 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, en-hanced, and protected force, now is the time to critically review military physical readiness practices—both hu-man performance optimization (HPO) and injury pre-vention (IP)—with the Army and other services. The promotion and sustainment of military physical readi-ness requires an energized sense of urgency from senior military leadership responsible for the implementation of policies and strategies that promote and sustain mili-tary 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 mili-tary physical readiness requires a new strategic para-digm that recognizes that physical training, physical fi t-ness, and injury prevention are interrelated and can be optimized simultaneously. For the purposes of this ar-ticle, 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 readi-ness; (3) an assessment of current Army Physical Readi-ness Training Doctrine; (4) an overview of injury risk mitigation strategies and efforts; (5) current HPO/IP ef-forts in the Army targeting military physical readiness; (6) recommendations as to the implementation of orga-nizational, 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 Re-serve 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 fu-ture if nondeployable status remained at the current level:
If we don’t get our arms around the nondeployable popu-lation, and the biggest population is the MNR popula-tion, 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 big-gest medical threat to readiness.8,14,15 In 2012, MSIs resulted in over 2.2 million medical encounters annu-ally 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 en-counters, mental disorders, results in approximately 2.1 million encounters annually, affecting approximately 250,000 service members.17 The biggest share of the in-jury 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 train-ing-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 training-related 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, in-jury 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 propor-tion of these injuries. Army research shows that physi-cal 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 mili-tary 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 hos-pitalizations 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 mus-culoskeletal/connective conditions.16
STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTINGMUSCULOSKELETAL 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 lim-ited 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 organiza-tions is incalculable.
The long-term effects in terms of disability discharges are just as sobering. Disabilities from MSIs have in-creased over time disproportionately to medical treat-ment rates.6,20 From 1982 to 2002, the disability dis-charge 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 disabil-ity 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 ser-vices due to disabilities, the Department of Veterans Af-fairs (VA) costs for compensation have historically been high.6 The VA reported in 2001 that the annual compen-sation 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 under-stood that soldiering is a physically demanding occupa-tion,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 fac-tors 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 ben-efi 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 move-ments 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 judi-cious modifi cations of training that can be calculated to optimize fi tness and minimize injury risks. Of the al-most 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 train-ing/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 activi-ties. 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 re-lated 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 musculoskel-etal 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 training-related injuries is the physical training program itself.
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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 t-ness 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 re-sulting from physical training in order to develop mis-sion essential physical fi tness and accrue the benefi ts of higher levels of fi tness.
Interestingly, it has been shown that there are thresh-olds of physical training above which injury risks in-crease but physical fi tness plateaus or decreases.19,34,38 Increased injury risks and decreased physical perfor-mance 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 lev-els 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 physi-cal 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 Physi-cal 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 En-vironmental Medicine, a program was designed to im-prove Warfi ghter’s physical capability for military op-erations 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 mili-tary tasks. Injury prevention features included reduced running mileage, exercise variety (cross-training), and gradual, progressive training.40 This program was sub-sequently 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 per-forming 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 ev-idence-based Army PRT, several areas of concern and limitations with the current doctrine must be acknowl-edged. 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 re-sistance training provides superior gains in strength, power, muscle hypertrophy, and military task perfor-mance 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 Sol-diers.46 Fortunately, TRADOC is examining ways to en-courage 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 avail-able in the literature, a paucity of research has considered physical performance adaptations over the “life-cycle spectrum” of the Warfi ghter, particularly among opera-tional units. Important considerations for physical train-ing optimization among our Soldiers, in terms of incor-porating resistance training, must be acknowledged. For relatively untrained Soldiers, improvements in strength at the onset of training are primarily due to neural fac-tors (eg, increased agonist activation, improved motor unit coordination, and synchronization). Therefore, pre-viously untrained Soldiers/recruits should participate fi rst in relatively low-load, low-volume resistance ex-ercise 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 ad-aptations has elapsed and most additional strength gains are due to muscular factors (ie, hypertrophy). After the
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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 oc-cupational and/or combat duties.47 However, no other established and accepted metrics of “combat or func-tional 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-min-ute rower, standing long jump, 1-minute push-up, and 2-mile run to replace the APFT; and (2) an Army Com-bat Readiness Test.
Currently, a Baseline Soldier Physical Readiness Re-quirements study is being conducted by the TRADOC Initial Military Training Center with support from lead-ing 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 in-tent 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 as-sess 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 in-cidence 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 Sec-retary 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 char-tered to support this accident and injury prevention di-rective with a focus on interventions that relate to all aspects of military training.49 The Joint services Physi-cal Training Injury Prevention Working Group (JSPTIP-WG) 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 expe-dited systematic review process was used by the work-ing group to: (1) establish the evidence base for making recommendations to prevent physical training-related injuries; (2) prioritize the recommendations for preven-tion 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 sys-tematically reviewed, only 6 intervention strategies to reduce physical training-related injuries had the requi-site evidence-based scientifi c support to recommend for implementation across the military. These interventions in order of priority were: (1) prevent overtraining (ie, ex-cessive running mileage); (2) perform multiaxial, neuro-muscular, proprioceptive, and agility training; (3) wear mouthguards during high-risk activities; (4) wear semi-rigid ankle braces for high risk activities; (5) consume nutrients to restore energy balance within one hour fol-lowing high-intensity activity; and (6) wear synthetic-blend 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 in-tervention strategies with some theoretical basis for ef-fi cacy were identifi ed as lacking suffi cient evidence to recommend at that time.49 The JSPTIPWG recommend-ed that upon determination by systematic reviews that scientifi c information is scant and gaps exist in knowl-edge about prevention, more research is needed before the implementation of policies and programs.50 The ef-forts 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.
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CURRENT HPO/IP EFFORTS IN THE ARMY TARGETING MILITARY PHYSICAL READINESS
The Army published Technical Bulletin MED 592, Pre-vention and Control of Musculoskeletal Injuries Associ-ated with Physical Training19 in May 2010. It is an im-portant comprehensive document that translates state-of-the-art guidance into principles that military and ci-vilian 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 train-ing. The document serves as an authoritative source on HPO/IP and helps military care providers and leaders: understand physiologic and pathophysiologic re-
sponses to exercise, know risk factors associated with training-related
musculoskeletal injuries, understand interventions with varying levels of
evidence for effectiveness in preventing training-related 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 condi-tioning programs (ECPs) (for example, CrossFit (Cross-Fit Inc, Washington, DC), Insanity (Beachbody LLC, Santa Monica, CA), Gym Jones (Gym Jones LLC, Salt Lake City, UT), and others) characterized by high-vol-ume, intense training workouts. These well-marketed and popularized conditioning programs continue to generate interest and support among military and civil-ian fi tness communities. Acceptance of ECPs is rein-forced by anecdotal reports of marked gains in physical performance. However, physicians and other primary care and rehabilitation providers have identifi ed a po-tential 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 Schoo-maker 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 part-nered 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) de-ploy 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 cation2.0 MNR Management Programs3.0 Evidence-Based Health Promotion,
HPO/IP Programs
Line of Effort (LOE) 3.0 of the Soldier Medical Readi-ness Campaign Plan54 (SMR-CP) embodies the key task to coordinate, synchronize, and integrate health promo-tion, injury prevention, and human performance optimi-zation 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, objec-tive statements, quantifi able measures, target goals, and initiatives. The main objectives of this LOE are to: (1) provide evidence-based health promotion services to en-able healthy lifestyle choices and eliminate preventable health issues that contribute to MNR Soldiers; (2) imple-ment, support, and evaluate promising injury prevention and performance optimization best practices/programs;
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(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 evidence-based 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 imple-menting educational programs, motivational strate-gies, 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 op-posed 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 educa-tional 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
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STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTINGMUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
Figure 2. Performance Triad Activity Concept of Operations. The presentation of this Concept of Operations was part of a Perfor-mance 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 Insti-tute 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 Asso-ciation. 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 fos-ter 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 physi-cians, 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 popula-tions (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.
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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 Perfor-mance Triad (Figure 2) could be particularly success-ful 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 opera-tions for activity using education, program, and policy lines of effort.
Figure 3 provides more detailed descriptions for the cur-rent HPO/IP initiatives listed under the SMR-CP strate-gic objective: improve soldier injury prevention/human performance. Although a number of innovative HPO/IP initiatives are currently ongoing, most of these initia-tives are largely unknown beyond where they are being locally conducted; they are not part of a larger synchro-nized, integrated, and coordinated HPO/IP effort. An opportunity exists to use these examples and adopt les-sons learned so we can move forward with a more global, unifi ed, and focused approach. This could lead to pub-lished research fi ndings providing militarily feasible, ac-ceptable, and suitable HPO/IP interventions and perfor-mance 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 Sol-dier Medical Readiness and the Performance Triad cam-paigns, 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 Subse-quently, 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 Opera-tions12 include: (1) manage Warfi ghter fatigue; (2) op-timize human-systems integration; (3) enhance Warf-ighter sensory, cognitive, and motor capabilities; (4) enhance Warfi ghter learning, communications, and de-cision 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 Mis-sions.59 This report spawned a request from the Assis-tant 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 Perfor-mance Optimization in DoD: Charting a Course for the Future.”60
The conference included subject matter experts from over 56 different DoD stakeholder groups: senior lead-ers (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. Recom-mendations from the workshop were published in a re-port 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 di-rective 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 primar-ily due to resistance from Air Force senior leadership.63 With current federal budgetary constraints and the po-tential 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
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STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTINGMUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
Initiative Title: Ranger, Athlete, Warrior (RAW) ProgramProponent: 75th Ranger RegimentDescription/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 ProgramProponent: 101st Airborne/Air Assault Division and the University of PittsburghDescription/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 ProgramProponent: 4th ID/FORSCOMDescription/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 ProgramProponent: 4th ID/FORSCOMDescription/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 InitiativeProponent: TRADOC/MEDCOMDescription/Comments: Uses an MAT concept at TRADOC initial entry sites to address injury incidence rates.
Initiative Title: Tactical Human Optimization Rapid Rehabilitation & Reconditioning ProgramProponent: 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 ConditioningProponent: MEDCOM/25th IDDescription/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 PreventionProponent: MEDCOM/US Army Medical Department Center and SchoolDescription/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 Sur-geon General.57
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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 peer-reviewed, 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 (Medi-cal 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 readi-ness 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 preven-
tion 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 life-
cycle 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 readi-
ness 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) communi-cation, (3) scientifi c, and (4) operational, based upon the type of strategic action required to resolve identi-fi ed obstacles within DoD.60 With regard to organiza-tional issues, existing policies should be reviewed with guidance to ensure consistency of HPO approaches in response to new research and technological develop-ments.60 Another important related issue involves opera-tional 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, Train-ing, 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 PREVENTINGMUSCULOSKELETAL 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 Con-trol of Musculoskeletal Injuries Associated with Physical Training18 (May 2011)
First medical technical bulletin dedicated to dissemi-nating evidence-based guidance for controlling MSIs.
Consortium for Health and Military Perfor-mance and American College of Sports Medi-cine Consensus Paper on Extreme Conditioning Programs in Military Personnel53
This peer-reviewed scientifi c manuscript is the prod-uct of a joint workshop addressing extreme condition-ing programs held September 13-14, 2010, at USUHS, Bethesda, MD.
American Journal of Preventive Medicine, Janu-ary 2010, Volume 38 (Supplement 1)
This supplement contains 25 peer-reviewed articles from the Joint Services Physical Training Injury Pre-vention Working Group which include systematic reviews.3,4,7,8,10,49,50
Military Medicine (Supplement: Total Force Fit-ness 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 Per-formance 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 Depart-ment of Defense Workshop55
This peer-reviewed article is the product of a joint DoD conference which concluded that nutritional optimiza-tion 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 pro-vides a comprehensive overview of the physiological effects of deployment with a particular focus on physi-cal 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 cally-based 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 achieve-ment of HPO. A common concern is that commanders and clinicians in the fi eld are typically unaware of cur-rent 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 unsubstan-tial 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 coopera-tion, and to determine future HPO needs.60
The scientifi c issues raised by the workshop centered on the need to develop operationally relevant and standard-ized 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 consen-sus is needed, particularly for measures of performance and measures of effectiveness. Ideally, research efforts should consider the Warfi ghter through his/her en-tire 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 de-veloping and fi elding feasible, acceptable, and suitable HPO approaches.60 Options for maintaining functional fi tness, performance nutrition, cognitive and psycholog-ical readiness throughout predeployment, deployment/engagement, and postdeployment/ redeployment time-lines are desired and critically needed.60 The HPO pro-gramming should preserve human capital by addressing service member weaknesses, injury and disease pre-vention, 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 transla-tional research and education agendas that address barri-ers and approaches to optimal performance. Developing
effective communication netrworks that cross research, medical and operational boundaries is critical to the suc-cess 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 func-tion. 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 Af-fairs).60 A concerted and integrated strategic HPO effort will serve to: (1) enhance the mental and physical re-silience of the Warfi ghter; (2) reduce injury and illness or facilitate more rapid recovery if injury does occur; (3) provide seamless information and knowledge trans-fer 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/cut-ting edge in this area.60 With the sanctioning of CHAMP and their educational arm, the Human Performance Re-source Center at the USUHS as a Defense Center of Ex-cellence (Figure 5), and the establishment of the Health Affairs Human Performance Optimization Health Sci-ences Advisory Committee, many of the recommenda-tions are being realized.
ALTERNATIVE SCENARIOS FOR HPO/IP
On February 19, 2013, the Strategy Innovation Offi ce of USAPHC conducted an alternative exercise consider-ing 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 politi-cal, economic, organizational, operational, environmen-tal, 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 scien-tifi c, evidence-based best practices; and (2) the extent to which senior leadership supports, prioritizes, and imple-ments scientifi c innovative, synchronized, and integrat-ed 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 estab-lished baseline physical and cognitive requirements to perform military occupations and duties. Better predic-tive models and analytics will yield better placement of Soldiers in military occupational specialties.
The military prioritizes investment in research and de-velopment. Technological advances in materiel science and further refi nement of exoskeletons result in lighter external loads. Biosensor technologies provide great in-sight 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, physi-cal fi tness, and nutritional subject matter experts into
operational units. Deliberate and detailed physiologi-cal studies on women in the military will identify risk mitigation and HPO/IP strategies to protect against in-creased 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 at-tention 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 dis-seminating 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 behav-iors, which lead to improved HPO/IP efforts. The HPO/
STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTINGMUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
Anecdotal and/or historical precendence drives HOP/IP doctrine and policy
“Science-Light”
Senior leadership fails to prioritizeHPO/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 synchronizedHPO/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 stra-tegic 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 sci-entifi c and technological breakthroughs. Additionally, military environments are redesigned and organized to take advantage of the latest HPO/IP scientifi c and tech-nological breakthroughs. Dining facility administra-tion 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 cen-ter is created to ensure a rapid process for systemic re-views and increased research funding for HPO/IP trans-lational research. Research is communicated effectively and in a timely fashion to the operational force. The mil-itary becomes the worldwide leader in HPO/IP, result-ing with the emergence of resilient and dominant War-fi 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 bud-get cuts, a danger exists that preventive medicine, pub-lic health, and HPO/IP research initiatives will be for-saken. 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 re-sources result in the military experiencing a technol-ogy 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 sci-entifi 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. Command-ers become less interested in maintaining military phys-ical 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 in-creased cognitive trauma and stress. Long-term health care and long-term disability costs rise, which over-whelms 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-practic-es 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 po-litical power. Seeking to exploit this vulnerability, other hostile nation states and nonstate actors provoke aggres-sion 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 fol-lowed and pragmatic strategy and policy changes are considered. Figure 5 provides a list of some authorita-tive 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 occupa-tional specialties or additional skill identifi ers dedi-cated 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 per-
formance optimization and injury prevention, and target these gaps for research. Establish routine channels for disseminating infor-
mation based on each public health and evidence-based decision-making process to ensure key stake-holders receive the information and training neces-sary to effectively reduce the impact of injuries on the health and readiness of military personnel. Use readily available military surveillance data-
bases 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 in-juries 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 guid-ance 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 leader-ship 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.
ACKNOWLEDGEMENTSThis 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.
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55. Deuster PA, Weinstein AA, Sobel A, Young AJ. Warfi ghter nutrition: current opportunities and ad-vanced 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: Ea-gle Tactical Athlete Program (ETAP) Part I. J Spec Oper Med. 2010;10(4):2-21.
57. Pendergrass T. Injury Prevention and Human Per-formance 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; Wash-ington, DC.
59. Russell A, Bulkley B, Grafton C. Human Perfor-mance 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. Hu-man 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. Ac-cessed August 29, 2013.
STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTINGMUSCULOSKELETAL INJURIES IN THE 21ST CENTURY
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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/three-branch-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.
AUTHORSDr 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 impor-tant 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 per-spectives (for example, operational, architectural, com-munity, 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 ac-tivity.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 poten-tial 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 ac-tivity, 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 pro-motes resilience; the clinical implications of a sedentary lifestyle; and the relevance of physical fi tness and resil-ience to Army Medicine’s Performance Triad. Through-out this article, the terms physical activity and exercise are used interchangeably, depending on the literature,
recognizing that exercise represents a planned, struc-tured, and regular form of physical activity.
HISTORICAL OVERVIEW
The quest for physical fi tness has been unremitting, how-ever, 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 im-petus for fi tness, which was later followed by the rec-ognition that selected physical movements and activities were important for developing the body and preventing and curing diseases.12-14 In fact, the importance of reg-ular exercise and physical activity has been touted for over 7,000 years.12,13 In China, the philosophical teach-ings of Confucius encouraged participation in regular physical activity, as physical inactivity was recognized as associated with certain diseases.12 The Chinese devel-oped many perspectives on how to achieve and maintain health, and they deemed exercise essential for increasing strength, prolonging life, preventing and curing diseas-es, 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 some-time around 3,000 BC.12 Among the Greeks, Herodicus (circa 450 BC) was the fi rst to promote physical activ-ity, and he even considered exercise a form of medicine. Nonetheless, Hippocrates is usually considered the fa-ther of exercise and medicine.13 These 2 Greeks were fol-lowed 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, identi-fi 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, MPHMarni N. Silverman, PhD
ABSTRACTVarious groups representing a number of different perspectives (for example, operational, architectural, com-munity, 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 domi-nant 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 depri-vation,17-20 it is now applied to diverse disciplines5-7 and populations.21-24 Identifying how and why some indi-viduals are seemingly able to bear up, and sometimes thrive, under adverse conditions with no observable neg-ative physical or psychological outcomes, is a continu-ous quest.5-7,25-33 Personality traits associated with resil-ience 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 op-portunities 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 experi-ences.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 com-petitive, resilient to errors or stress, and have high self-confi 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 mo-tivation.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 t-ness have been shown to be associated with specifi c personality traits and psychological attributes63-72 asso-ciated with resilience. For example, anxiety and depres-sion 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 sig-nifi 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 attri-butes, are essential for resilience.65,66,75 Self-effi cacy gen-erally 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 com-pared 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 intensi-ty aerobic exercise was shown to be most benefi cial and had a strong effect on self-effi cacy, in addition to con-ferring 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 ex-ercise has positive short-term effects on self-esteem and that it might be an important strategy for improving self-esteem. 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, con-trol, and motivation, and although each strategy is im-portant, motivation appears to be key in terms of regular physical activity.70,78,82-85 Research has shown that mo-tivation is very important with regard to commencing and maintaining participation in regular physical exer-cise.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 spe-cifi c objective or derive personal meaning.78,82,83 Over-all, these studies strongly suggest that personality traits (hardiness and mental toughness) and other attributes (self-esteem, self-effi cacy, motivation, self-manage-ment 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 chal-lenge. 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 over-view. However, scientifi c data documenting the essenti-ality 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 litera-ture has become replete with evidence that physical fi t-ness and regular exercise confer resilience and serve as a resistance resource in a variety of ways, including blunt-ing stress reactivity in response to both physical and psy-chosocial 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 medi-ate the stress response are the hypothalamic-pituitary-adrenal axis, with the resultant release of cortisol, and the sympathetic nervous system, which releases the cat-echolamines epinephrine (adrenaline) and norepineph-rine. Activation of these stress systems mediates the fi ght or fl ight response, which entails the rapid mobi-lization 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. To-gether, these stress systems orchestrate the physiologic and behavioral adaptations to stress. However, chronic activation can lead to dysregulation of multiple physi-ologic 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 psy-chologically, 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 Ad-ditionally, physically active people show reduced sym-pathoadrenal reactivity to physical stressors.109,110 When untrained persons are enrolled in a regular exercise pro-gram for 8-12 weeks, their response to the same physical stress prior to beginning exercise training is signifi cant-ly 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 psycholog-ical.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 as-sociated with physical fi tness and resilience and how physical fi tness confers resilience. Physical fi tness confers resilience be-cause 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.
October – December 2013 27
THE ARMY MEDICAL DEPARTMENT JOURNAL
stress in trained men compared to untrained men. More-over, 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, oth-ers have noted blunted cortisol responses115 and reduced cardiovascular responses98,99,115 to psychological labora-tory stressors in physically active as compared to less active persons. Webb et al111 administered a dual chal-lenge of physical and mental stress and noted that low-fi 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 in-dividuals 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 rela-tionship between aerobic fi tness and depressive symp-tomatology and a positive association between fi tness and emotional well-being.116
In addition to cross-sectional studies, longitudinal stud-ies have demonstrated positive effects of exercise train-ing and regular physical activity, and negative effects of exercise withdrawal on mood and depressive symp-toms.68,117-121 Nabkasorn et al117 studied adolescent fe-males 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, stud-ies 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 vari-ability, 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 re-silience and reactivity.
Despite the multiple positive fi ndings, not all are consis-tent,65,122,123 particularly with regard to catecholamine re-lease, 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 re-view of the literature from 1982 to 2008 in which exer-cise 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 pro-posed by Kobasa et al,34 and later by others9,11 who clearly showed that regular exercise and hardiness interact to de-crease 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 buf-fer against depression 63,68,125,129-134 and anxiety.100,125,134-136 In fact, the benefi cial effects of physical activity on posi-tive mood are well recognized.83,137 Rethorst et al131 con-ducted 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 treat-ment. Similarly, a number of prospective studies have demonstrated reductions in state anxiety.129,138 Man-ger 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 interven-tion. 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 anx-iety-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 inac-tivity serves a major role in the rising prevalence of obe-sity, 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 in-take also contributes to obesity,78,94,95, but lack of physi-cal 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 bro-myalgia (FM),146,147 chronic fatigue syndrome (CFS),148,149 osteoarthritis,150-152 rheumatoid arthritis,150,153,154 and in-fl 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 inter-ventions, 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 ap-proximately 3% reduction in CRP levels across the ex-ercise 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 like-ly deleterious for pain regulation in FM. Likewise, Cur-tis 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 mini-mal physical activity during daily life and lower muscle strength and aerobic capacity compared to healthy sed-entary 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, physi-cally 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 long-term health and risk of chronic diseases. Most of the above mentioned chronic diseases/disorders are also as-sociated 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 rela-tion 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 en-gage 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 attri-butes required for resilience. As such, it is one pathway toward resilience. Promoting physical fi tness as a path-way 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 buf-fer 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 usu-ally 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. Ex-cessive activity can lead to overtraining, musculoskel-etal 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.
ACKNOWLEDGMENTSThis 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.
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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 environ-ments 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 phys-ical 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 con-cluded 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, MSMichelle Canham-Chervak, PhD
Vancil McNulty, DPTBruce H. Jones, MD, MPH
ABSTRACT
Context: Brigades and battalions throughout the US Army are currently implementing a variety of exercise and con-ditioning 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 train-ing, 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 com-pared to Soldiers not participating in ATAC/ECPs, no recommendation can be made for or against implemen-tation of ATAC/ECPs.
October – December 2013 37
shown that musculoskeletal injuries are a leading cause of hospitalization.7 In a study investigating hospitaliza-tions 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 in-juries. 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-re-lated injuries have a considerable impact on the health and readiness of Soldiers.
Previous research has identifi ed a number of risk fac-tors 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 in-dex (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 previ-ous back injury.10 More work to identify the most impor-tant risk factors among infantry Soldiers is needed.
Only a few investigations have explored injury risk dur-ing the implementation of a new military fi tness pro-gram.11-15 In 3 investigations, Knapik et al compared Soldiers performing Army Physical Readiness Training (PRT) to Soldiers performing traditional Army physi-cal training. Physical readiness training consists of cal-isthenics, movement drills, climbing drills, dumbbell exercises, interval training, and ability group long-dis-tance running whereas traditional Army physical train-ing consists primarily of warm-up and stretching exer-cises 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 con-cluded that the PRT program results in fewer injuries and equal or greater improvements in fi tness and mili-tary performance compared to traditional Army physi-cal training.11-13,16
In a US Air Force study, a new PT program implemented within the combat controller training pipeline was eval-uated. 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 function-al training program, overall injuries decreased by 67%, and improvements were made in body composition, aer-obic 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).
METHODPopulationThe 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 battal-ion, a fi eld artillery battalion, a brigade support battalion (hereinafter referred to as Infantry A, Infantry B, Cav-alry, 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 in-jury prevention.
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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 Condi-tioning (ATAC) program. The ATAC Program consisted of workouts employing plyometrics, kettlebells, medi-cine balls, high-intensity water exercises, wrestling, lad-der and cone agility drills, tire fl ipping, speed interval training, and cinderblock throwing. Some of the bat-talions 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 Ar-my’s 25th Infantry Division.
CrossFit is a core strength and conditioning program that aims to prepare athletes for any physical contin-gency. CrossFit consists of continuously varied, high-intensity functional movements that generally fall into 3 categories: gymnastics, Olympic weightlifting, and metabolic conditioning or “cardio.”* There are 4 com-ponents to the RAW program: functional fi tness, per-formance nutrition, sports medicine, and mental tough-ness. The functional fi tness component of RAW consists of movement drills (before each PT session), muscular endurance workouts, heavy resistance workouts, pow-er 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 character-ized 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 in-corporated 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 correla-tions 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 ac-cordance 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 (AFH-SC) provided demographic data obtained from the De-fense 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 Surveil-lance System (DMSS). A brigade unit roster was pro-vided to the AFHSC, which returned DMSS data con-taining 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 Novem-ber 1, 2009 and October 28, 2010. Injuries were catego-rized 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 inju-ries. Overuse injuries contain a subset of musculoskel-etal injuries resulting from cumulative microtrauma due to repetitive motion, typically in the 710-739 ICD-9 code series. This series indicates such diagnoses as stress fractures, stress reactions, tendonitis, bursitis, fasciitis, shin splints, and musculoskeletal pain (not oth-erwise specifi ed). Traumatic injuries contain a subset of musculoskeletal injuries resulting from a strong sud-den 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/rawptguide_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, physi-cal 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 ac-cording to the Centers for Disease Control and Preven-tion (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 postimple-mentation of the physical training programs, the McNe-mar 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 in-jury incidence in the 6 months following full im-plementation 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. Po-tential injury risk factors included demographic characteristics obtained from AFHSC as well as health behavior, physical training, and physical fi t-ness data collected by survey.
A backward-stepping multivariate logistic regres-sion and a forced multivariate logistic regression model were used to assess key factors for associa-tion 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 over-weight or obese (61%), white (62%), rank of E4 to E6 (61%), high school graduates (82%), and mar-ried (55%). The descriptive statistics are presented in Table 1.
Due to the small number of Soldiers who partici-pated 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 par-ticipation. 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 in-cidence increased by 12% and 16% for overall injuries
number of Soldiers with 1 or more injuriestotal number of Soldiers
100%
Table 1. Descriptive Statistics for Men and Women in the Light Infan-try Brigade.
Variable Subcategory of Variable
MenM=1,248
WomenW=145
Men andWomenN=1,393
n %M n %W n %NGender 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%
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and overuse injuries, respectively, for Soldiers who par-ticipated (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 percent-age 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, Cav-alry, and Brigade Support battalions. An examination of physical training risk factors determined that injury risk
was higher for Soldiers who participat-ed 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 in-jury. Analysis of APFT data indicated that those with lower performances on any of the 3 elements of the physical fi t-ness 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 back-ward-stepping multivariate logistic re-gression 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 mul-tivariate logistic regression analysis examining components of the physical fi tness test controlling for age and bat-talion. 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 IncidenceBefore ATAC/ECP
Injury Incidence After ATAC/ECP
Absolute Change
Change P(McNemar Test)
Overall 41% 46% +5% +12% .02Overuse 32% 37% +5% +16% .02Traumatic 19% 18% -1% -5% .95ATAC 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 IncidenceBefore ATAC/ECP
Injury Incidence After ATAC/ECP
Absolute Change
Change P(McNemar Test)
Overall 50% 57% +7% +14% .05Overuse 42% 46% +4% +10% .28Traumatic 22% 23% 1% +5% 1.00ATAC indicates Advanced Tactical Athlete Conditioning program.ECP indicates extreme conditioning program.
Table 4. Personal Characteristics and Risk Factors for Injury Among Men Partici-pating in ATAC/ECPs (N=1,032).
Variable Subcategory of Variable
N Injury AfterATAC/ECP
Risk Ratio (95%CI)After ATAC/ECP
P
Gender Men 950 45% 1.00Women 82 60% 1.34 (1.11-1.63) <.01
Age <24 306 44% 1.09 (0.88-1.38) .4324-25 185 46% 1.15 (0.91-1.45) .2326-29 203 40% 1.0030+ 240 48% 1.21 (0.98-1.50) .08
Body MassIndexI
<25 341 37% 1.0025-29 464 47% 1.27 (1.07-1.51) <.0130+ 115 60% 1.61 (1.31-1.98) <.01
Current Smoking Status
Nonsmoker 470 39% 1.00Smoker 443 51% 1.32 (1.14-1.53) <.01
Smokeless Status
Nonsmokeless 655 43% 1.00Smokeless User 295 49% 1.15 (0.99-1.33) .07
Battalion Infantry A 394 38% 1.00Infantry B 116 52% 1.38 (1.11-1.71) <.01Cavalry 136 52% 1.37 (1.11-1.69) <.01Field artillery 163 42% 1.13 (0.90-1.40) .30Brigade 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 inju-ries 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 major-ity 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 AfterATAC/ECP
Risk Ratio(95% CI)
After ATAC/ECP
P
Physical training at prior assignment Traditional PT 767 46% 1.00Extreme conditioning programs 47 43% 0.93 (0.66-1.31) .67Combination ECP and traditional 93 39% 0.85 (0.65-1.11) .20Other 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% 1.005-7 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% 1.00ATAC and/or combination of ATAC/
other programs340 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% 1.001-2 times per week 400 44% 0.88 (0.67-1.15) .363-4 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% 1.007.01-9.00 miles per week 63 48% 1.23 (0.92-1.63) .199.01- 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) .561-2 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) .071-2 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) <.021-2 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) .201 time per month 148 41% 0.98 (0.61-1.58) .932 times per month 237 48% 1.15 (0.73-1.81) .523 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) .0957-67 repetitions 221 48% 1.23 (0.99-1.52) .0668-76 repetitions 230 41% 1.05 (0.84-1.31) .6977-111 repetitions 233 39% 1.00
Sit-ups 19-61 repetitions 223 54% 1.40 (1.14-1.72) <.0162-69 repetitions 218 43% 1.11 (0.89-1.39) .3670-78 repetitions 227 40% 1.03 (0.82-1.30) .7879-109 repetitions 224 38% 1.00
2-mile Run (minutes and fraction of a minute)
11.12-13.52 minutes 233 34% 1.0013.53-14.50 minutes 222 42% 1.23 (0.98-1.56) .0814.51-15.50 minutes 204 44% 1.27 (1.00-1.61) .0515.51-32.22 minutes 203 51% 1.49 (1.18-1.86) <.01
ATAC indicates Advanced Tactical Athlete Conditioning program.ECP indicates extreme conditioning program.
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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 stud-ies 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 re-sistance training. In a US Air Force study, Walker et al found that replacement of a majority of the traditional long-dis-
tance 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 Add-ing resistance training to an aerobic train-ing program can also be benefi cial in the completion of job tasks or mission require-ments. It has been shown that endurance training concurrent with resistance train-ing improves load-bearing performance29-32 and heavy lifting tasks,32 and increases both short-term and long-term endurance capac-ity 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 implemen-tation of a combined resistance and endurance training program will enable Soldiers to complete specifi c mis-sion 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 ofVariable
n Odds Ratio(95% CI)
P
Body mass index (BMI) <25 310 1.0025-29.9 414 1.77 (1.29-2.44) <.0130+ 98 2.72 (1.67-4.43) <.01
Tobacco Nonsmoker 430 1.00Smoker 392 1.80 (1.34-2.42) <.01
Battalion Infantry A 342 1.00Infantry B 100 1.62 (1.01-2.61) .05Cavalry 128 1.87 (1.20-2.92) <.01Field artillery 139 1.36 (0.89-2.08) .15Brigade support
battalion64 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) .031-2 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 1.007.01-9.00 miles a week 54 1.05 (0.57-1.94) .879.01-16 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 ranCurrent smoking status Agility TrainingBattalion Resistance Training
Table 7. Physical Fitness Test Risk Factors for Injury Among Men Participat-ing 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) .9757-67 repetitions 207 1.11 (0.71-1.72) .5068-76 repetitions 218 1.00 (0.66-1.50) .9977-111 repetitions 222 1.00
Sit-ups 19-61 repetitions 199 1.53 (0.94-2.50) .0962-69 repetitions 205 1.03 (0.66-1.60) .9170-78 repetitions 213 0.92 (0.60-1.39) .6879-109 repetitions 218 1.00
2-mile Run(minutes and fractionof a minute)
11.12-13.52 minutes 226 1.0013.53-14.50 minutes 217 1.42 (0.95-2.12) .0914.51-15.50 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.
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THE ARMY MEDICAL DEPARTMENT JOURNAL
Infantry A had the lowest injury inci-dence (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 men-tioned, running more miles per week increases injury risk.26-28 In addition, in-jury risk is higher for recruits with lower levels of lower-extremity muscle strength or who lack a consistent low-er-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 ad-ditional 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) rat-ed 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 In-fantry 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 few-est 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 re-ported 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 report-ing may help reduce injury rates and optimize the physi-cal 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 perfor-mance on military tasks that require both aerobic and strength components.39-42 In a study investigating physi-cal 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 mili-tary readiness and increasing risk for injury.39 In an in-vestigation 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 av-erage 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 per-formance. 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 nonsmok-ers, 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 forFitness Variables
n Q1 Q2 Q3 Q4 ANOVA Plow
performancehigh
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 rela-tionship 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 investi-gation, 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 environ-ments and military occupational specialty requirements may result in weakened tissues from training and over-use, which may result in a greater susceptibility to inju-ry 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 physi-ological stress and/or fatigue during tasks such as run-ning, cross-training, and calisthenics due to exercising at a higher percentage of their maximum aerobic capac-ity in comparison with Soldiers with greater fi tness lev-els. Soldiers of lower fi tness levels will not only be exer-cising 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 activ-ity,60 changes in gait,62-66 balance,67,68 low-frequency fa-tigue,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 perform-ing ATAC/ECPs. Therefore, no recommendations can be made for or against use of those programs. Risk fac-tors 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 train-ing 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 t-ness programs should be to meet occupational and op-erational demands and expectations while minimizing injury risks.
RELEVANCE TO PERFORMANCE TRIAD
A key aspect of The Army Surgeon General’s Perfor-mance Triad is the promotion of optimal physical activ-ity among Army Soldiers, family members, retirees, and civilians. Optimal physical activity involves incorporat-ing regular physical activity into daily routines while also minimizing injury risk. Prevention of injury dur-ing 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 physi-cal training. The results also suggest that injury risks were lower for nonsmokers, Soldiers with higher aero-bic endurance, and Soldiers maintaining a healthy body weight.
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42. Bohnker BK, Sack DM, Wedierhold L, Mala-kooti 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. Evalu-ation of the advanced tactical athlete conditioning and extreme conditioning programs in the 25th In-fantry Division, Schofi eld Barracks, Hawaii. Injury Prevention Report. Aberdeen Proving Ground, MD: United States Army Institute of Public Health; 2010.
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49. Knapik JJ, Swedler DI, Grier TL, et al. Injury re-duction effectiveness of selecting running shoes based on plantar shape. J Strength Cond Res. 2009;23(3):685-697.
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52. Grier TL, Knapik JJ, Canada S, Canham-Chervak M, Jones BH. Risk factors associated with self-reported training-related injury before arrival at the US Army Ordnance School. Public Health. 2010;124(7):417-423.
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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.
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AUTHORSMr 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 be-haviors 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 initia-tive seeks to improve Soldier readiness and resilience by improving Soldiers’ PA, nutrition, and sleep behaviors. An understanding of the present level of PA during Ba-sic 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, di-rect observation is often viewed as labor-intensive and tedious. Consequently, it has not often been used to as-sess PA. Self-report techniques are the instruments of choice for assessing PA levels in large-scale epidemio-logical 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, PhDBruce S. Cohen, PhD
Kathleen Simpson, MSBarry A. Spiering, PhDMarilyn 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 par-ticipant 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 mea-surement 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 mea-surement 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 Acti-Graph accelerometer and PAtracker (direct observation) for characterizing PA intensity, and between the PA-tracker and a daily PA log (self-report) for characteriz-ing body position and PA type in the BCT environment.
METHODS
Study Overview
Data for this study was collected from recruits in 2 training battal-ions during separate BCT cycles. The fi rst iteration took place from June to August 2010, at Fort Jack-son, 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, dur-ing which recruits from 5 training companies were studied. The com-panies included in the study were determined based solely upon their availability.
Prior to the start of the study, re-cruits in each training company were informed of the requirements and potential risks of participa-tion. Recruits voluntarily signed an informed consent document ap-proved by the Institutional Review Board of the US Army Research Institute of Environ-mental Medicine (USARIEM), Natick, Massachusetts. Investigators followed the policies for protection of hu-man 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 Sub-jects. 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, Pensaco-la, FL) shown in Figure 1. This device is capable of sens-ing acceleration along the vertical, anterior-posterior, and mediolateral axes . The accelerometer’s output is re-corded in “counts,” which are the summation of the ab-solute values of the sampled changes in acceleration dur-ing a user-defi ned time period.7 From the accelerometers, average daily time (minutes) each recruit spent in seden-tary, light (<3 metabolic equivalent (MET)), moderate (3-6 MET), and vigorous (>6 MET) intensity activities was determined using the Freedson categories.7 Seden-tary 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/platoon4 platoons/company=24 recruits /company). When possible, at least one of the 6 recruits from each pla-toon was female. Research staff distributed the accelerometers to participants before the fi rst forma-tion each morning (5 AM) and col-lected them immediately before or after the dinner meal (approxi-mately 4 PM). Recruits wore the ac-celerometer 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 pla-toon for a portion of the day while wearing the accelerometer, the ac-
celerometer 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 prop-erly. Although 24 recruits wore the ActiGraph, acceler-ometer 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 obser-vation 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 follow-ing 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 record-ing method, which allowed trained observers to record changes in a recruit’s PA behaviors when changes in ac-tivity 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 com-menced 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 Acti-Graph. If the designated recruit was not training that day, another recruit wearing the device was identifi ed and followed. Although individual recruits in each com-pany 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 be-fore. 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 inten-sity activities during the day. All times were recorded as hours and minutes.Statistical Analyses
Pearson product moment correlations were run to deter-mine 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 Bland-Altman method9 to determine if similar values for PA intensity, body position, and type of PA had been cap-tured between 2 measurement instruments. First, differ-ences in average daily time spent in each PA intensity, body position, or type of PA as measured by each instru-ment (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
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THE ARMY MEDICAL DEPARTMENT JOURNAL
the ActiGraph and PAtracker). The data were then ana-lyzed for the presence of heteroscedasticity by plotting the absolute values of individual differences between the 2 measurement instruments versus the means be-tween the 2 instruments for PA intensity, body position, and type of PA.9,10 Data were defi ned as hom*oscedastic 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 ran-dom 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 hom*oscedastic, the 95% LoA was cal-culated as follows:
95% LoA=SD of the difference scores1.96The LoA indicates that the average daily time spent in PA intensity, the body position, or the type of PA ob-tained 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 correla-tions 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 Acti-Graph 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 pro-vided 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
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FIgure 3. Physical Activity Log.
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for the body positions of walking and sit-ting were hom*oscedastic (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 in-tensity, body position, and type of PA, of US Army BCT have been characterized in detail. The fi ndings in this study sup-port the use of the Acti-Graph as the instrument to measure PA intensity and the PAtracker and daily PA log to measure body posi-tion 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 popu-lation settings and uses.12
Pearson product moment correlations are often used to interpret the degree of association between measure-ment 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 in-tensity, 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 simi-lar manner and direction. However, the correlations pro-vided 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 caus-ing 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 ran-dom error increased as the average daily minutes spent in each intensity increased. More specifi cally, there was disagreement between the ActiGraph and the PA-tracker 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 obser-vation. However, correctly categorizing PA intensity through direct observation may be highly dependent on the training and experience of the observer and the en-vironment 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 Acceler-ometer and PAtracker Regarding Time Spent in Various PA Intensities During Army Basic Combat Training.
Measure ActiGraphAverageDaily Min
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Sedentary 445±93 393±52 -52 0.302* 81% UnderreportsLight 144±73 295±139 150 -0.052 143% OverreportsModerate 93±25 56±80 -37 0.211* 208% UnderreportsVigorous 37±19 7.1±14 -30 0.077 202% UnderreportsModerately
Vigorous131±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 PAtrackerAverageDaily Min
PA LogAverageDaily Min
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95% LoA(mins/day)
RatioLoA
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Stand 432±119 180±57 -252 0.144* 79% UnderreportsSit 255±108 287±66 32 0.186* 227.3 UnderreportsWalk 78±69 129±44 51 0.198* 145.0 UnderreportsRun 10±13 36±16 26 0.268* 153% UnderreportsMenial Chores 212±127 26±14 -186 0.033 209% UnderreportsCalisthenics 29±25 59±35 30 0.150* 177% OverreportsCarry 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
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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 cat-egories. The difference between the ob-server’s perception and a recruit’s rec-ollection of time spent in various body positions and types of PA may have con-tributed to the lack of agreement between these 2 measurement instruments. The differences between interpretations of op-erational 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 posi-tions 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 assess-ment method for a specifi c research ques-tion 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 Perfor-mance Triad initiative seeks to improve Soldier readiness and resilience by im-proving Soldiers’ PA, sleep, and nutrition-al health behaviors. The ability to assess the quantity as well as the quality of cur-rent PA demands (PA type, body position, PA intensity, and load carried), and recov-ery (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:
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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 measure-ment instruments.
ACKNOWLEDGEMENTThis study was funded by the US Army Medical Research and Materiel Command and the Defense Safety Oversight Council.
REFERENCES1. Butte NF, Ekeland U, Westerterp KR. Assessing
physical activity using wearable monitors: mea-sures of physical activity. Med Sci Sports Exerc. 2012;44(1)(suppl 1):S5-S12.
2. Wyss T, Mader U. Recognition of military spe-cifi c PA with body fi xed sensors. Mil Med. 2010;175(11):858-864.
3. Malina RM, Bouchard C, Bar-Or O. Growth, Mat-uration, and Physical Activity. 2nd ed. Champaign, IL: Human Kinetics. 2004:457-477.
4. Valanou EM, Bamia C, Trichopoulou A. Methodol-ogy of physical-activity and energy expenditure as-sessment: 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 Sub-jects 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. accel-erometer. 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 Activ-ity Assessment for Health-related Research. Cham-paign, IL: Human Kinetics; 2002:179-195.
9. Bland JM, Altman DG. Statistical methods for as-sessing agreement between two methods of clinical measurement. Lancet. 1986;1:307-310.
10. Bland, JM, Altman DG. Applying the right statis-tics: 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 vari-ables relevant to sports medicine. Sports Med. 1998;26(4):217-238.
12. Wood TM. Issues and future directions in assess-ing physical activity: An introduction to the confer-ence 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 com-bat 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, McKin-ley M. How active are we? Levels of routine physi-cal activity in children and adults. Proc Nutr Soc. 2003;62(3):681-701.
AUTHORSDr 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 de-manding, 10-week training program designed to develop basic soldiering skills and prepare recruits for the physi-cal 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, inten-sity, 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 leisure-time 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 Physi-cal 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 exer-cise 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, PhDJan E. Redmond, PhD Ryan Steelman, MSBruce S. Cohen, PhD Joseph J. Knapik, ScDNathan R. Hendrickson, MS Marilyn A. Sharp, MS
ABSTRACT
Purpose: During US Army Basic Combat Training (BCT), graduation requirements, including physical readi-ness training (PRT), are standardized across training sites. However, there are concerns that the standardiza-tion 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 re-corded 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 moder-ate 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.
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(progressive overload). Compared to traditional BCT physical training programs, PRT has been shown to re-sult in the same or greater improvements in physical fi t-ness while causing fewer injuries.2,19 In addition to PRT, BCT recruits are also required to perform other physi-cal 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, al-though doctrine requires that PRT and training for mili-tary 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 in-tensity 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 investiga-tor 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 in-formed consent document approved by the Institutional Review Board of the US Army Research Institute of En-vironmental 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 Sub-jects.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: instrumen-tation with an accelerometer, direct observation, and daily PA logs.
Accelerometer
The accelerometer used in this study was the ActiGraph GT3X triaxial accelerometer (ActiGraph, LLC, Pensac-ola, 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 cy-cle. 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 com-pany. Research staff performed compliance checks to ensure all volunteers wore the devices properly.
Research staff distributed the accelerometers to partici-pants before the fi rst formation each morning and col-lected 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 re-cruit 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 PERFORMEDDURING US ARMY BASIC COMBAT TRAINING
October – December 2013 57
THE ARMY MEDICAL DEPARTMENT JOURNAL
Freedson categories, which defi ne sedentary or light-in-tensity 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 ob-servers 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-Communica-tions (San Diego, CA) and the USARIEM, was used in this study. The PAtracker software was installed on smartphone devices. Trained observers logged a re-cruit’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 activ-ity 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, walk-ing, calisthenics, cadence marching, combatives, run-ning, obstacles/climbing, crawling, and lifting/carrying. Physical activity was also classifi ed by intensity (seden-tary, 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 accelerom-eters, and all activities during the day were recorded. Within each company, a single recruit who was wear-ing 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 com-pany 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 sleep-ing 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 sit-ting, standing, walking/marching, and running. Finally, recruits were asked to report the amount of time they spent doing chores or barracks maintenance, doing cal-isthenics/obstacle courses, and carrying a load. Upon the recruit’s completion of the PA log, a study investi-gator 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 per-formed 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 mea-sured 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 Sta-tistics (V 14.0) software (IBM Corp, Chicago, IL) for Windows with P <.05 established as the level of statisti-cal signifi cance.
RESULTS
Within each of the 11 training companies included in this study, 24 recruits were outfi tted with an acceler-ometer 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/com-pany). When possible, at least one of the 6 recruits from each platoon was a woman.Accelerometer
The Fort Jackson recruits wore the accelerometer a to-tal 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 ac-celerometer. 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 ac-celerometer comparisons between the two training sites in this study were made using the average daily percent-age of time. The exception was time spent in moderate- to vigorous-intensity PA between 5 AM and 7 AM, which
58 http://www.cs.amedd.army.mil/amedd_journal.aspx
was examined using av-erage daily minutes. This variable was an ex-ception because weekly changes were examined at each training site as opposed to being com-pared between the 2 training sites.
Figure 1 shows the aver-age 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 light-intensity activities (23.0% ± 10.4% vs 15.8% ± 2.0%, P<.001) and a smaller percentage of their time in seden-tary activities (58.9% ± 10.6% vs 65.9% ± 4.9%, P<.001) when compared to recruits at Fort Sill. Additionally, re-cruits 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 vig-orous-intensity activity between 5AM and 7AM, when re-cruits 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 mod-erate- to vigorous-intensity PA between 5AM and 7AM (P=.443). Repeated measures analysis of variance indi-cated 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, activ-ity type, intensity, and carrying various external loads, as measured with the PAtracker. Recruits were fol-
lowed with the PAtracker an aver-age 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 compari-sons 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 posi-tion is shown in Figure 3A. Re-cruits 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 PERFORMEDDURING 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 44Total 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±26.0Light 47 8,193.6±512.8 136.6±8.5 44 4,687.6±217.3 78.1±3.6Moderate 47 4,799.5±360.8 80.0±6.0 44 3,624.3±357.6 60.4±6.0Vigorous 47 1,602.0±313.2 26.7±5.2 44 1,827.4±207.9 30.5±3.5
80%
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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
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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 dai-ly 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 vigor-ous- (1.1% ± 2.3% vs 0.9% ± 1.9%, P=.290) intensity activities. As was the case with the accelerom-eter, recruits at both training sites spent a large percentage of time (about 50%) in sedentary activities and a small percent-age 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 com-batives (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), per-forming 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 calis-thenics (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/carry-ing (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 carry-ing 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). Re-cruits at both training sites spent a large percentage of time (about 80%) carrying 0-10 lbs and a very small per-centage 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, stand-ing, walking, running, participating in calisthenics, do-ing 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 re-cruits at Fort Jackson did. Therefore, all PA Log com-parisons between the 2 training sites in this study were
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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 acceler-ometers.
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, walk-ing, 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 report-ed 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), perform-ing 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 al-though there were some differences between the 2 sites in terms of the PA performed, these differences were
QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMEDDURING US ARMY BASIC COMBAT TRAINING
Table 2. Cumulative time recruits at both training sites spent in each body position, activity type, activ-ity 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 44Time 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±4.2Lying 37 1,071.8±284.0 17.9±4.7 37 943.0±184.9 15.7±3.1Sitting 47 13,187.2±1,193.8 219.8±19.9 44 9,374.1±1,056.5 156.2±17.6Standing/On Feet 47 19,216.3±476.2 320.3±7.9 44 19,447.6±1,752.5 324.1±29.2Varying 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±3.5Calisthenics 38 1,391.9±146.6 23.2±2.4 39 1128.4±46.5 18.8±0.8Combatives 12 559.6±155.3 9.3±2.6 4 113.5±75.9 1.9±1.3Crawl 7 63.4±75.2 1.1±1.3 5 16.5±7.2 0.3±0.1Lifting/Carrying 12 71.1±50.4 1.2±0.8 13 97.8±62.8 1.6±1.0Menial Tasks 47 7925.0±495.2 132.1±8.3 44 11,335.9±2,180.3 188.9±36.3Obstacle/Climbing 7 181.0±55.7 3.0±0.9 8 302.4±38.8 5.0±0.6Run 33 427.7±91.1 7.1±1.5 31 479.7±58.8 8.0±1.0Stationary 47 20,402.9±1,510.9 340.0±25.2 44 12,871.7±2,922.4 214.5±48.7Walk 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±63.9Light 47 13,126.8±1325.2 218.8±22.1 44 13,506.0±3,380.0 225.1±56.3Moderate 44 2,975.9±1333.2 49.6±22.2 40 2,018.7±238.1 33.6±4.0Vigorous 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±14.310-25 lbs 36 4,585.4±1461.4 76.4±24.4 28 2,869.6±1,416.3 47.8±23.625-50 lbs 19 1,266.6±588.3 21.1±9.8 30 2,796.2±628.6 46.6±10.550-75 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
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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 appreci-ated by examining the range of differences (lowest and highest) in the amount of time recruits spent in vari-ous physical activities. From the accelerom-eter, the lowest dif-ference was 7% (3.4 minutes) for sedentary
activities, and the highest difference was 7.2% (67.8 minutes) for light-intensity activities. From the PAtrack-er, 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 min-utes) 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 var-ious external loads at the 2 locations tested. Whether or
Standing* Sitting* Lying Kneeling*
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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 activi-ties, 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 44Time 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±21.6Stand 47 6,848.0±743.8 114.1±12.4 44 9,907.6±1,233.9 165.1±20.6Walk/March 47 6,204.5±1,204.6 103.4±20.1 44 5,506.4±392.2 91.8±6.5Run 47 1,531.0±263.6 25.5±4.4 44 1,752.8±238.9 29.2±4.0Sleeping 47 17,140.7±985.7 285.7±16.4 44 16,569.4±567.7 276.2±9.5Chores/Maintenance 43 1,256.7±323.4 20.9±5.4 44 1,135.4±321.5 18.9±5.4Calisthenics/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, acceler-ometer 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 train-ing sites, there was little differ-ence 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 re-cruits were obtained from direct observation (PAtracker). Re-cruits 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 dis-tances over various types of terrain.27 Current US Army doctrine recommends that Soldiers carry no more than
QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMEDDURING US ARMY BASIC COMBAT TRAINING
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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
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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
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THE ARMY MEDICAL DEPARTMENT JOURNAL
48-72 lbs (or 30%-45% of their body weight) in the fi ght-ing load and approach march loads, respectively.28,29 Re-cruits 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 continu-ous 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. Addition-ally, 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 in-tensity 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 de-signed 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 re-cruits were presumably engaged in PRT) tended to in-crease 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 inten-sity but perhaps not enough to be consistent with the pro-gressive 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 op-erations (road marching, basic rifl e marksmanship, land navigation, fi eld training exercises, etc). When physical-ly demanding activity was scheduled, physical training was either reduced or was not conducted at all in the ear-ly 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 en-gaging in calisthenics was not signifi cantly different be-tween 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 ap-pears that the amount of time spent in these general ac-tivities 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 class-room training; and the fi nal week, consisting primar-ily 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 ac-tivities performed by recruits, but previous observations suggested that there was little PA taking place in the evening hours.1,3
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Figure 6. Average daily percentage of time that recruits spent sitting, standing, walking, and running as reported in thedaily 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 re-cruits per company who were instrumented with an ac-celerometer and the 1 recruit per company who was fol-lowed 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 consent-ed volunteer. Due to study design, a limitation to this process was the number of times recruits had to be re-placed, 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. Ad-ditionally, 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 initia-tive seeks to improve Soldier readiness and resiliency by improving the activity, sleep and nutritional aspects of Soldier health behaviors. This study examined the activ-ity 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 dur-ing 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 re-cruits during BCT are meeting the minimum PA recom-mendations 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 main-tain adequate health and resiliency.
ACKNOWLEDGEMENTTh is study was funded by the US Army Medical Research and Materiel Command and the Defense Safety Oversight Council.
REFERENCES1. 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 readi-ness 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 activ-ity and injuries during United States Army basic combat training. J Phys Act Health. 2011;8:496-502.
4. American College of Sports Medicine. The recom-mended quantity and quality of exercise for devel-oping and maintaining cardiorespiratory and mus-cular 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 bene-fi 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 PERFORMEDDURING 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 in-juries 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. Self-reported 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 Soldier-Athlete Initiative: Program Evaluation of the Eff ec-tiveness of Athletic Trainers and Musculoskeletal Action Teams in Initial Entry Training, Fort Leon-ard 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 in-tervention strategy for reducing femoral neck stress injury and other serious overuse injuries in Unit-ed 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 train-ing. 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 Sub-jects 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 Wel-fare. 2009.
23. Welk GJ, Schaben JA, Morrow JR. Reliabil-ity 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. accel-erometer. 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. Cham-paign, 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 In-stitute; 2012:303-338.
30. Miller NL, Shattuck LG. Sleep patterns of young men and women enrolled at the United States Mili-tary Academy: results from year 1 of a 4-year longi-tudinal study. Sleep. 2005;28(7):837-841.
31. McArdle WD, Katch FI, Katch VL. Exercise Physi-ology: 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 maintain-ing cardiorespiratory, musculoskeletal, and neu-romotor fi tness in apparently healthy adults: guid-ance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-1359.
AUTHORSMs 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 ap-propriate quantities to ensure mission performance and protect against disease.1 Accordingly, the dietary behav-iors 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 dis-eases 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 veg-etables 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, PhDCynthia V. Lentino, MS
Theresa K. Jackson, PhD, MPHKaitlin J. Murphy, MS
Patricia A. Deuster, PhD, MPH
ABSTRACTObjective: 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 di-mension 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 cal-culated 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 psychoso-cial 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 inappro-priate use of dietary supplements (DS) can negatively impact human performance and health outcomes.5,6,23,24
This study examined lifestyle habits—nutrition behav-iors, 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 char-acterized 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 psycho-social 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 psy-chosocial dimensions: emotional, social, family, and spiritual fi tness.27,28 In 2012, the CSF2 program intro-duced a physical dimension by adding 57 pilot ques-tions 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 di-rected to the expanded GAT. Upon GAT completion, re-spondents 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 Ser-vices University of the Health Sciences Institutional Review Board concluded that a full review was not re-quired for this investigation. This study was not classi-fi 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 mem-bers, 599 Department of Defense (DoD) civilians, and 390 participants with missing data were excluded from analyses. Hence, we are reporting data from 13,858 Ac-tive 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/bever-ages? (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
perDay
TwiceperDay
OnceperDay
3 to 6Times
perWeek
1 or 2Times
perWeek
Rarelyor
Never
FRUIT: fresh, frozen, canned or dried, or 100% fruit juices 5 4 3 2 1 0VEGETABLES: 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 veg-etables (corn, white potatoes, green peas), and other (tomatoes, cabbage, cel-ery, cucumber, lettuce, onions, peppers, green beans, cauliflower, mushrooms, summer squash, etc)
5 4 3 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 4 3 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 oth-er calcium-fortified foods (orange juice, soy/rice milk, breakfast cereals, etc)
5 4 3 2 1 0
FISH: tuna, salmon, or other nonfried fish 5 5 5 5 3 0Note. Questions and scoring that comprise the Healthy Eating Score-5. Scores were totaled for a range of 0 to 25.
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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 pop-ulations, and their consumption does not meet national guidelines.18,19,34 Each HES-5 question represented a sub-scale 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 sub-scale scores was used to determine HES-5 reliability36,37; the analysis yielded an internal consistency reliability co-effi cient of 0.81. Classifi cations for Cronbach va ry, but values less than 0.60 are generally considered unaccept-able, 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 con-sisted 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, represent-ing 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 respon-dents 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-pro-moting supplements (ie, multivitamins and/or mineral supplements with 6 or more ingredients; or single-in-gredient 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 sleep-ers 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 spe-cifi c rather than sensitive classifi cation of poor sleep-ers.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? (excel-lent, 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 activ-ity for at least 20 minutes, and the frequency with which they participated in strength or resistance exercise. Re-sponses 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 distin-guish 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 cir-cumference 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 di-mension.27,28 Subscores for each dimension were further classifi ed into quartiles for subsequent analyses.Statistical Analyses
The IBM SPSS Statistics software package for Win-dows, 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 BEHAVIORSCONTRIBUTE 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 regres-sion 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, gen-der, 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 circum-ference, 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.RESULTSGeneral CharacteristicsDemographic 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 BehaviorsMeans 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 be-ing in the highest HES-5 quartile when compared to enlisted and married Soldiers. No signifi cant associa-tions were noted between highest/lowest HES-5 quar-tile membership and gender (reference group: male [OR Table 2. Study Sample Demographic Characteristics (N=13,858).
Frequencies HES-5Mean±SD
Age, Mean±SD (years) 28.2±9.2Years Range 17.0-61.0Age Groups
17 to 29 66.9% 15.9±3.430 and over 33.1% 15.1±5.3
GenderFemale 16.7% 15.6±5.5Male 83.3% 15.7±5.3
Army Duty StatusNational Guard/Reserve 47.4% 15.5±5.4Active Duty 52.6% 15.8±5.3
Service CategoryEnlisted 84.9% 15.5±5.5Officers 14.6% 16.39±4.7
Marital StatusMarried 49.0% 15.5±5.2Single/Divorced/Legally Separated 51.0% 15.8±5.4
Army Physical Fitness Test n=9,845Failed 13.7% 15.0±5.6Passed 86.3% 16.0±5.3
BMI Categories n=11,119Underweight (<18.4 kg/m2) 0.5% 15.1±5.1Normal/Healthy (18.5-27.5 kg/m2) 65.3% 15.0±5.3Overweight (27.6-29.9 kg/m2) 16.9% 15.6±5.3Obese (>30 kg/m2) 17.3% 15.1±5.5BMI, Mean±SD (kg/m2) 26.6±4.0BMI Range 13.4-56.3
Waist Circumference n=5,855Healthy 90.9% 16.09±5.3Unhealthy 9.1% 15.28±5.3
HES-5 Quartiles*Low HES-5 - Quartile 1 25.9 8.6±3.0Quartile 2 26.0 14.4±1.2Quartile 3 22.2 17.8±0.8High HES-5 - Quartile 4 25.9 22.1±1.8
Note: Data are represented as meansstandard 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 sta-tus (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 high-est 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 respon-dents (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 HES-5 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 re-ported taking a performance-enhancing or bodybuild-ing 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 Ratio0 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).
HealthyEater
HealthyWaist Sizec
OR 1.56*CI, 1.22-2.00
ExerciseRecoverySnackb
OR 3.1*CI, 2.80-3.40
Age18-29a
YearsOR 1.46*
CI, 1.32-1.61
Breakfastf
OR 4.2*CI, 3.8-4.70
≥7 WaterServings/
Daye
OR 7.19*CI, 5.05-6.98
HealthyBMId
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.aReference group: 30 years or older.bReference group: those who did not regularly consume a
recovery snack.cReference group: waist circumference larger than 35 in for
women; larger than 40 in for men.dReference group: greater than 27.5 kg/m2.eReference group: consumption of 6 or less glasses of
water per day.fReference group: consumption of breakfast 5 or less times
per week.
38.7%
50%
40%
30%
20%
10%
0%VegetablesFruit Whole
GrainsDairy 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 serv-ings/day), dairy (3 servings/day), and fi sh (2-3 servings/week).
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products (OR 2.06; 95% CI, 1.82-2.32; P<.001). Approx-imately 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. Sol-diers who consumed all three of these supplements ex-perienced 4 times the odds of being in the highest HES-5 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 member-ship in high/low HES-5 quartiles. Soldiers who con-sumed 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 quar-tile 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 clas-sifi 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 sta-tus and being a “healthiest” or “least healthy” eater was also observed. Respondents who con-sidered their health to be “good” or “excellent” had 3 times the odds of being in the highest HES-5 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 physi-cal activity and its results were analyzed based on the American College of Sports Medicine and Centers for Disease Control and Prevention ex-ercise recommendations. A total of 28.5% of re-spondents 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 percent-age 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 car-diovascular exercise for at least 20 minutes, 5 days per week were more likely to be in the highest than the low-est 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 quar-tile. Those who passed their APFT in the highest quar-tile had more than twice the odds of being in the high-est 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 respon-dents 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 exer-cise 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 TopQuartile
LowHES-5
HighHES-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)
COMMENTPoor nutritional/dietary habits degrade mission readi-ness while contributing to other health disorders9 and affect all domains of performance. Nutrition is thus deemed an essential component of Total Force Fit-ness.45 Accordingly, dietary behavior assessment ques-tions were included in the new GAT physical dimension along with other lifestyle questions relating to perfor-mance. This study characterized nutritional behaviors of 13,858 Soldiers and examined their interrelation-ships 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 veg-etable consumption are well known, only 38.7% of participants met fruit intake recommenda-tions, and 22.2% met vegetable recommenda-tions. 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 per-centage (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 hy-pothesis. 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 assess-ment tools, sample population differences, or ongoing and emerging DoD and Army initiatives targeting nutri-tional 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 strong-ly associated with a number of key health promoting nu-tritional behaviors. Those who consumed breakfast at least 6 times per week, 2 snacks daily, 7 or more serv-ings of water daily, and a snack within 60 minutes of strenuous exercise were more likely to have high HES-5 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 cog-nitive function, and fewer injuries and accidents at work,46 along with lower values for BMI and waist cir-cumference.47 Consistent with those fi ndings, Soldiers with a healthy BMI and with a healthy waist circumfer-ence were more likely to have high HES-5 scores than
Figure 5. Global Assessment Tool (GAT) Fitness Dimensions and Nutri-tion. Percentage of each HES-5 quartile scoring in the highest quartile of the GAT psychological dimensions.
Healthy Eating Score QualitiesLow HES-5 High HES-5
Emotional
Social
Family
Spiritual
5%
0%
15%
10%
40%
35%
30%
25%
20%
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those with an unhealthy BMI and waist circumference. Furthermore, Deshmukh-Taskar et al48 indicated that breakfast consumption was associated with more favor-able cardiometabolic risk profi les than skipping break-fast. Additionally, carbohydrates, a usual constituent of snacks and meals, enhanced physical and cognitive performance in Soldiers engaged in sustained and in-tense physical activities.4,5 Together, these fi ndings dem-onstrate 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 like-ly to consume recommended amounts of water. Like-wise, 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 ac-celerate recovery, decrease muscle soreness following prolonged exercise training, and may positively effect health outcomes.58 Additional benefi ts of regular nutri-ent timing include improved morale, stimulation of mus-cle protein synthesis, and protection against training in-juries.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 fo-cused 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 Administra-tion 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 se-rotonergic and dopaminergic transmission and the ex-pression of brain-derived neurotrophic factors in the hippocampus. Johnston et al63 reported that blood lev-els of omega-3 were signifi cantly below what is consid-ered 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 re-fl 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 regu-lar sodas were more likely to have high HES-5. Sugary beverages likely contribute to excess energy consump-tion 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 sug-gest that prolonged consumption may lead to increased body weight, obesity, and metabolic syndrome.70-72 In-terestingly, in our study, 65.8% of those with an un-healthy waist circumference consumed either diet or regular sodas compared to only 34.2% of those who consumed neither type of soda beverage. Clearly, bev-erage intake behaviors are important to consider with regard to healthy body mass and health. Further inves-tigations into how these dietary behaviors contribute to health and performance could inform the development of targeted campaigns and educational strategies to en-hance positive dietary behaviors.
Dietary supplement use by military members is high,9,73,74 and supplements are universally available at the com-missaries 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 (health-promoting, 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 moti-vation for supplement use in this population, previous research suggests individuals consumed supplements to improve or maintain overall health.75 Supplement us-ers also tended to have lower BMIs, frequent physical activity, and moderate alcohol intake, all of which are refl ected in our research population.
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Most supplement users received their vitamins and min-erals 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 dissemi-nate throughout the Army is that supplements should not replace or make up for a poor quality diet. Unfor-tunately, popular media cater to Warfi ghters by claim-ing 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 pro-viders 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 particu-lar, lower levels of cardiovascular fi tness, as measured by run times, have been consistently and strongly as-sociated with injury risk in both military men and wom-en.80,81 In this study, Soldiers who met aerobic exercise recommendations had more than 3 times the odds of be-ing 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 en-sures our Soldiers are prepared to meet the physical de-mands of the mission and minimize the likelihood of in-jury.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 recommenda-tions than the diets of their lesser fi t peers. Of key con-cern 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 emo-tional, 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 docu-mented: respondents tend to under-report weight and over-report height84 and waist circumference,85 and they also misreport their physical activity.86 Secondly, indi-viduals 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 general-ize these results. Next, the relationships between HES-5 and scores on emotional, social, family, and spiritual fi t-ness are not suffi ciently granular to characterize specifi c dimension components. Further research is needed to clarify the contribution of dietary behaviors to emotion-al, 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 anal-yses 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 con-text 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 eat-ing 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 me-tabolism, cognitive decrements, and appetite4,53,87-90; (2) nutrition affects sleep,4,91,84,85 physical performance, re-covery and fatigue51-56; and (3) physical fi tness affects appetite mechanisms, social health, sleep, cognitive performance, and mood.79,92-96 A recent review96 hypoth-esized that eating behavior and physical activity may share a common neurocognitive link since active indi-viduals have an improved regulation of hunger and sati-ety mechanisms. Clearly, these relationships are critical to optimize health and performance and should be in-vestigated and promoted as a holistic system. This study provides data regarding differences in nutrition behav-iors and other lifestyle habits that highlight the need to provide education regarding the positive performance
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benefi ts of good dietary behaviors and to provide target-ed 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.
ACKNOWLEDGEMENTSThis 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.
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56. Stellingwerff T, Maughan RJ, Burke LM. Nutrition for power sports: middle-distance running, track cycling, rowing, canoeing/kayaking, and swim-ming. J Sports Sci. 2011;29 (suppl 1):S79-S89.
57. Beelen M, Burke LM, Gibala MJ, van Loon LJ. Nu-tritional 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 mili-tary 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 dis-ease?. Prev Med. 2004;39(1):212-220.
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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 ac-ids in the pathophysiology and treatment of depres-sion: 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 re-view 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 pre-vention: 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 consump-tion, incident coronary heart disease, and biomark-ers of risk in men. Circulation. 2012;125(14):1735-1741, S1731.
68. Fung TT, Malik V, Rexrode KM, Manson JE, Wil-lett 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 meta-analysis. 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, Mi-chos ED, Jacobs DR Jr. Diet soda intake and risk of incident metabolic syndrome and type 2 diabe-tes 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.
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75. Bailey RL, Gahche JJ, Miller PE, Thomas PR, Dw-yer 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.
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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.
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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.
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85. Bigaard J, Spanggaard I, Thomsen BL, Overvad K, Tjonneland A. Self-reported and technician-mea-sured 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 ac-tivity questionnaires. Int J Behav Nutr Phys Act. 2012;9:103.
87. Afa*ghi A, O’Connor H, Chow CM. High-glycemic-index carbohydrate meals shorten sleep onset. Am J Clin Nutr. 2007;85(2):426-430.
88. Peuhkuri K, Sihvola N, Korpela R. Diet pro-motes 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 indi-viduals. 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 well-being 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.
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AUTHORSDr 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 BEHAVIORSCONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS
October – December 2013 79
NUTRITIONAL DEFICIENCIES IN THETRAINING ENVIRONMENT
Unhealthy eating habits and nutritional defi ciencies are an increasing concern among Army personnel. Current literature shows that poor nutrition can affect suscepti-bility 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 readi-ness 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 Behav-iors 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 nutri-ents for the average adult.8
Furthermore, Soldiers usually require increased dietary energy intake, especially during training as they main-tain 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 nutri-ents has a negative effect on health, injury, physical per-formance, 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 behav-iors 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 Sol-diers 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.
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chronic undernourishment were linked to increased rates of stress fractures in military recruits.4
Poor nutrition can also cause Soldiers to become over-weight 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-for-height standards and to remain below a certain body fat percentage. There are reports of Soldiers using un-healthy 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 toler-ant 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 stan-dards, performance nutrition education, menu develop-ment, 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 Ad-vanced Individual Training (AIT). Go for Green label-ing is a nutritional recognition tool that provides point-of-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 consid-ered 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 con-sumed on rare occasions.14
The performance nutrition education component con-sists 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 for-mat, is typically conducted by a drill sergeant or other cadre member. As a part of nutrition education, leaders receive SFI training on nutrition fundamentals, appro-priate 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. Lead-ers 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, organiza-tional, 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 environ-ment.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 lead-ers 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 ser-geant 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 en-vironment, 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?
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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 spe-cifi c examination of leader infl uence on trainees’ nu-trition behaviors. Specifi cally, the evaluation team as-sessed the following: To what extent are Army leaders helpful or un-
helpful 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 af-fect 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 under-stand 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 (fo-cus 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 par-ticipate in the evaluation. The IMT CoE established op-erational orders to facilitate data collection during Oc-tober 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 in-formed that their participation was completely volun-tary. 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 (method-ology 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. Re-sponse 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 educa-tion); changes in weight, lean muscle mass, physical per-formance, 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’ per-ceived 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 sourceSurveys(N=486)
FocusGroups(N=112)
Basic Combat Training (N=319)
All Soldiers from 3 companies at Fort Jackson, SC n=247Sample 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=239Sample of Soldiers from 2 companies at Fort Jackson, SC n=40
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Focus Group MethodsThe evaluation team conducted 6 BCT focus groups based on strata by gender (male and female) and perfor-mance (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’ experi-ences within the dining facilities, SFI effect on eating behavior, barriers to SFI implementation, and sugges-tions for program improvement. The BCT and AIT focus group guides consisted of 10 open-ended ques-tions 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 partici-pants that their participation and comments would re-main anonymous, and asked for verbal consent to au-dio-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 inde-pendent 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 Ta-ble 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 cod-ing 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 estab-lished 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.
RESULTSSurvey Results
A total of 486 Soldiers completed the survey, of whom 398 (82%) were male, and 87 (18%) were female. The av-erage age of respondents was 21.3 ± 4.5 years. Addition-al survey sample demographics are included in Table 3.
Perceived helpfulness of leaders in making perfor-mance-enhancing food choices was signifi cantly associ-ated 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). Al-though 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 choos-ing 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 help-fulness 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), frequen-cy 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 se-lecting “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 associ-ated 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
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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 per-formance (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 se-lecting performance-oriented food choices (r=0.383, P<.001), and positive attitude toward eating for per-formance (r=0.268, P<.001) also increased in BCT (Table 5). Within AIT, as agreement with this statement increased, frequency of selecting performance-orient-ed 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 and Characteristics of ConstructFrequency of use of Go
for Green labels in the DFAC
How frequently do you use “Go for Green” labeling when considering food choicesin 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 both 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 classifi cation 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 knowl-edge 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 significant 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 four 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
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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 per-formance (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 selec-tion 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 BCTN=247
AITN=239
TotalN=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±4.50Weight 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 help-ful 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±1.138Level 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±1.036a. 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.
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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 com-ment 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 ref-erences 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 con-sequences included being forced to eat, being punished with physical activity (eg, doing push-ups), and psycho-logical 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 in-structed 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 lead-ers rushing them to eat and fi nish their meals in a minimum amount of time. The Soldiers also discussed not hav-ing 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 com-plained 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 lead-ers 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 train-ers and coaches for nutrition information).28-30 Focus group results suggest Soldiers fi nd it particularly use-ful when cadre members teach them how and what to eat to optimize their performance, especially as it re-lates 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 im-portant to eat for perfor-mance
BCTN=247
AITN=239
BCTN=247
AITN=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 perfor-mance-oriented food choices 0.169b 0.255c 0.383c 0.235c
Frequency of selecting perfor-mance-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 perfor-mance 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.
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these tangible skills may be more useful than knowl-edge 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 val-ue 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 mo-tivational 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 perfor-mance-enhancing food choices, and nearly twice as many BCT Soldiers as AIT Soldiers agreed that lead-ers 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 con-sequences 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 participantIf they see certain people they’ll heckle certain people in the cafete-
ria… 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 eat-ing 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 Sol-diers 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 participantNow, 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 participantLeaders 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 participantI believe the Drill Sergeants … try to rush you out sometimes depend-
ing on what we got going so you won't get all of the food we would like to get.
BCT participantThey 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 Ser-geant 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 choco-late cake… you know, it’s kind of hypocritical.
BCT participantI 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 influ-ence 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 physi-cally something I can’t eat, I’m going to eat it anyway.
BCT participant
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the disparity warrants additional research. Within BCT, drill sergeants are involved in instructing the Perfor-mance Nutrition Education course, which may increase the extent to which Soldiers perceive them as informa-tion brokers or resources related to nutrition informa-tion. 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 ex-tent to which BCT leaders emphasize the need to eat for performance or to consider the day’s duties when mak-ing food choices. That said, proper nutrition is essential for cognitive performance in addition to physical per-formance.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 show-case 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 perfor-mance increased, so too did a variety of relevant SFI outcomes. For example, Soldiers who reported higher levels of leader helpfulness in making performance-enhancing food choices also reported higher frequency of use of Go for Green labels, higher frequency of se-lecting performance-oriented food choices, a greater positive attitude and commitment toward eating for per-formance, and higher levels of self-reported knowledge regarding what to eat for physical and cognitive perfor-mance. Correlation coeffi cients with these outcomes in-dicated 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 consis-tent with ecological models of health behavior which as-sert 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 be-lieve it is important to eat for performance, it could be expected that Soldiers will experience at least slight im-provements in their nutritional attitudes and behaviors. Survey fi ndings suggest leader infl uence is most rele-vant for positive behaviors (eg, frequency of use of Go for Green labels, frequency of selecting performance-enhancing choices, positive attitudes toward nutrition) and has no signifi cant association with negative behav-iors (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 help-fulness and perceptions that eating for performance is important to their leaders increased, Soldiers’ consump-tion 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 of-ten 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 re-actions which can impair one’s ability to self-regulate and self-monitor, which are required elements for con-trolled 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, rath-er, 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 hypo-critical 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 re-turn 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 obe-sity.41 Insuffi cient time allocated for meals may lead to overeating. The importance of physical training within
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IMT, and BCT in particular, is indisputable. However, it is equally important for Soldiers to develop positive nu-tritional practices and habits during training. Initial Mil-itary 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 in-ferences can be made between any constructs of inter-est. 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. Analy-ses did not control for demographic diff erences between BCT and AIT, and some constructs (eg, selection of per-formance-limiting choices, perceived level of knowledge regarding what to eat for physical and cognitive perfor-mance) 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 us-ing 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 ad-ditional study, particularly in the areas of variation in leader infl uence in different environments (eg, training versus operational), the effect of consequences for per-formance-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 atti-tudes but those of their Soldiers as well.
RELEVANCE TO THE PERFORMANCE TRIAD
The Army Performance Triad is designed to promote ac-tivity, 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 mes-saging (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, performance-oriented nutrition practices. Previous research indi-cated some leaders are not as knowledgeable as they would like to be about nutrition.23
Emphasize that leaders should demonstrate a per-sonal commitment to positive habits because their Soldiers look to them as role models; it is impor-tant 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 tech-niques (other than reprimand) to guide Soldiers to desired behaviors.
Leaders should do the following to optimize perfor-mance-oriented nutrition choices among their Soldiers:
Deliver additional education in both AIT and in the operational environment to continue the momen-tum 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 asso-ciated with programming to send consistent messag-es; 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; re-inforce 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 be-coming knowledgeable about nutrition and by iden-tifying 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 engage-ment, role modeling, and commitment are likely to make a positive difference.
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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. Chil-dren eat their school lunch too quickly: an explor-atory study of the effect on food intake. BMC Pub-lic Health. 2012;12(1):351-358.
42. Sigrist LD, Anderson JE, Auld GW. Senior mili-tary offi cers’ educational concerns, motivators and barriers for healthful eating and regular exercise. Mil Med. 2005;170(10):841-845.
AUTHORSDr 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 De-partment of Health and Human Services, are revised ev-ery 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 recom-mend limiting the intake of sodium, saturated fat, di-etary 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 in-dex (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 Ex-amination 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-den-sity 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 nutri-ents in military populations have revealed dietary inade-quacies 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, RDErin Gaffney-Stomberg, PhD, RD
Jenna L. Scisco, PhDCOL Sonya J. Cable, SP, USA
J. Philip Karl, MS, RDAndrew J. Young, PhD
James P. McClung, PhD
ABSTRACTObjective: 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 differ-ent 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.
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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.
METHODSVolunteersThis study was approved by the Human Use Review Committee at the US Army Research Institute of Envi-ronmental 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 in-take (<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 with-drawal from the study. In total, 135 volunteers (76 male, 59 female) were included in the fi nal analyses. The base-line 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 per-fect compliance with the DGAs. The 9 adequacy com-ponents 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, semi-quantitative, Block 2005 food frequency questionnaire (FFQ) (NutritionQuest, Berkeley, CA).15,16 The full-length, 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 re-garding 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 com-pleting it again at the end of BCT, capturing their dietary intake during BCT. The food list on the FFQ was de-veloped 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 TertilesHigh
(n=45)Medium(n=45)
Low(n=45)
HEI Score Pre (P<.01) 73.1±6.2 60.3±3.4 46.9±4.4Age (yr) (mean±SD) (P=.50) 23.8±5.9 23.1±5.1 22.3±5.1
Sex (P=.68)Male 23 26 27Female 22 19 18
Racial Background (P=.55)White 25 30 27Black/African-
American 8 8 11
Other 12 7 7Activity (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 19No 39 30 26
HEI indicates Healthy Eating Index.*Smoker defined as smoking more than every other day over the past
30 days.
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Twelve HEI component scores and total HEI scores were determined according to the HEI guidelines.2-4 Meth-ods for scoring the HEI components appear in Table 2. Higher scores indicate increased consumption of ad-equacy 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 ana-lyzed as secondary outcomes in a trial powered to char-acterize 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 analy-ses, volunteers were divided into equal tertiles based on their baseline HEI score. One-way analysis of variance (ANOVA) with Bonferroni corrections was used to de-termine 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 inter-vals (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 af-ter normality was assessed using the IBM SPSS Statis-tics (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 ter-tile and 3.03 times higher for those in the me-dium 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, to-tal 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 ter-tile demonstrated similar improvements (P<.05) in com-ponent 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 im-provements (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 Sol-diers 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 im-prove 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 re-port diminished diet quality in smokers as compared to nonsmokers.3 However, unlike previous studies in civil-ian populations using NHANES data,19 we did not ob-serve 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
RangeStandard for theMaximum Scoreb
Standard for theMinimum 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 gramsSaturated fatc 0-10 ≤7% of total energy ≥15% of total energySodiumc 0-10 ≤0.7 grams ≥2.0 gramsCalories 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.
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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 im-provements 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 imple-menting the Go for Green method of rating the nutri-tional composition of food items, caloric and total fat in-take were reduced and customer satisfaction improved as compared to the control dining facilities.20
Nutrition education strategies may also underlie im-provements in diet quality. The Soldier Fueling Initia-tive, 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 dur-ing 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, unfavor-able outcomes such as overweight, obesity, and an un-healthy lipid profi le may result.6 Future studies should focus on possible relationships between HEI scores and biomarkers of chronic disease risk in military popula-tions, 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 prevent-ing 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 TertilesHigh
(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±2.5Post-BCT 2.8±2.0 2.4±1.6c 2.2±1.7c
Saturated Fat T,G,TxGPre-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,TxGPre-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±2.9Post-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±1.1Post-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±1.0Post-BCT 9.8±0.7 9.8±0.7 9.7±0.9
Dark Green and Orange Vegetables and Legumes T,GPre-BCT 3.6±1.6 2.5±1.6 1.4±1.2Post-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 interactionNotes: a. Different (P<.05) from High b. Different (P<.05) from Medium c. Different (P<.05) from Pre-BCT
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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 com-parison 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 per-sonnel in both training and permanent duty assignments and should follow Soldiers for longer periods to deter-mine 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 enter-ing 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 identi-fi cation of military personnel with low diet quality early in their careers may provide the opportunity to target in-terventions such as diet counseling and education in an effort to improve Soldier health and performance over the course of a military career and beyond.
ACKNOWLEDGEMENTThe 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.
REFERENCES1. 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-PolicyDoc-ument.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. Avail-able 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. Develop-ment of the Healthy Eating Index-2005. J Am Diet Assoc. 2008;108(11):1896-1901.
5. About the National Health and Nutrition Examina-tion 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 qual-ity is inversely related to cardiovascular risk fac-tors 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, dou-ble-blind, placebo-controlled trial of iron supple-mentation in female soldiers during military train-ing: 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 dur-ing military training: a longitudinal study. J Int Soc Sports Nutr. 2012;9(1):38.
10. Army Regulation 70-25: Use of Volunteers as Sub-jects 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 Medi-cal Research and Materiel Command; April 1990 [amended July 2003].
12. Pasiakos SM, Karl JP, Lutz LJ, et al. Cardiometa-bolic risk in US Army recruits and the effects of ba-sic 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.
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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 Epide-miol. 1986;124(3):453-469.
16. Block G, Woods M, Potosky A, Clifford C. Vali-dation of a self-administered diet history question-naire 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: Na-tional 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. Ef-fect of modifi ed foodservice practices in mili-tary dining facilities on ad libitum nutritional intake of US Army soldiers. J Acad Nutr Diet. 2013;113(7):920-927.
AUTHORSMs 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.
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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 inad-equate 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 meta-bolic syndrome,12,13 as well as increases in depression, anxiety, and other mental health issues.8,14-19 Interesting-ly, poor sleep behaviors have also been associated with a pro-infl ammatory state.20-24
Many epidemiological and meta-analytic studies sug-gest these observed relationships may be bidirectional and possibly confounded by other issues.13,20,25 For ex-ample, 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 re-sistance and immunologic alterations; whereas, depres-sion, anxiety, and life stressors can interfere with sleep duration and quality to create a vicious cycle.12,13,30-32 Fi-nally, exercise and nutritional habits can directly infl u-ence sleep quality and duration,5,20,33-38 in either negative or positive directions. Exercise and sleep interact bidi-rectionally 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, MSDianna L. Purvis, PhDKaitlin J. Murphy, MS
Patricia A. Deuster, PhD, MPH
ABSTRACT
Objec 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 dimen-sion (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 them-selves 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 as-sociations 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 physi-cal 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 prac-tices to improve sleep patterns. Thus, we conducted an investigation, in collaboration with the Army’s Compre-hensive Soldier and Family Fitness program (CSF2), to assess various health behaviors and habits of US Army Soldiers. New questions were incorporated into the on-line Global Assessment Tool (GAT), which all nonde-ployed Soldiers are required to complete once per year. Family members of Soldiers and all Department of De-fense (DoD) civilians may also take the GAT. The intent of the questions was to determine gaps in Soldier knowl-edge and behaviors relating to physical fi tness, nutri-tional 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 popu-lation 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: emo-tional, 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 re-search purposes. Per an established data use agreement, personal identifying information was removed from the CSF2 data (thus waiving the requirement for Institution-al Review Board approval), which was then provided to researchers for analysis.Population
The total number of participants was 14,850. The fol-lowing 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.
MeasuresMeasures 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 emo-tional, social, spiritual, and family fi tness with 105 ques-tions. Each dimension yields an overall score based on responses to the questions, and the scores are aggre-gated 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 di-mension 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 satis-faction 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 con-sidered scores of 0 or 1 as good sleep, 2 to 4 as moderate sleep, and 5 or 6 as poor sleep quality. Although the au-thor 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.
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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 recommenda-tions.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? (excel-lent, 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 sin-gle 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 fol-lowing: HES-5=0.810; sleep=0.807; and physical activ-ity=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 cur-rent data. A Cronbach α greater than 0.80 is regarded as good, above 0.70 is acceptable, and below 0.60 is unac-ceptable.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, Chi-cago, IL) application was used to perform all statisti-cal analyses. Frequency tables and descriptive statistics were reviewed to remove outliers and confi rm assump-tions for parametric tests. Binary logistic regression was used to obtain odds ratios (OR) and 95% confi dence in-tervals (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 appropri-ate 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.
RESULTSGeneral 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 sleep-ers 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 be-haviors 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 re-spondents 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 train-ing (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).
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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 self-reported, the correlation between waist circumference and BMI was 0.673 (P<.001). Answers to the health self-assessments 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 Group17 to 29 66.9% 2.4±1.730 and over 33.1% 2.5±1.6
Gender Female 16.6% 2.6±1.6
Male 83.4% 2.4±1.6Army Status
Active Duty 52.6% 2.6±1.7 National Guard/Reserve 47.4% 2.3±1.6
Enlisted StatusEnlisted 85.3% 2.5±1.7Officers 14.7% 2.1±1.5
Marital Status Married 49.0% 2.5±1.7
Single/divorced/legally separated 50.9% 2.4±1.6Army Physical Fitness Test n=10,054
Failed 13.7% 2.6±1.7 Passed 86.3% 2.3±1.6
BMI Categories n=11,545Underweight (<18.4 kg/m2) 0.5% 2.4±1.6Normal/healthy (18.5-27.5 kg/m2) 65.3% 2.4±1.6Overweight (27.6-29.9 kg/m2) 16.9% 2.5±1.6
Obese (>30 kg/m2) 17.3% 2.7±1.7BMI Mean±SD, kg/m2 26.6±4.03
Range 13.4-56.3 Waist Circumference n=6,012
Healthy 90.9% 2.4±1.6Unhealthy 9.1% 2.8±1.7
Sleep Categories Good sleepers 32.9% 0.6±0.5Moderate sleepers 41.8% 2.5±0.5
Poor sleepers* 25.3% 4.7±0.78Note: 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 cat-egory. 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%
Hea
lthy
Eate
rs
Table 2. Logistic Regression of Poor Sleepers and Dietary Behaviors.
GoodSleepers(n=4,658)
ModerateSleepers(n=5,915)
PoorSleepers*(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 0.6-0.72Note. 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.
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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 mod-el was used to predict poor sleep. The fol-lowing variables were allowed to be incor-porated: 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 in-cluded in the model, no statistically sig-nifi 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. Emo-tional 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 as-sociated with disturbed or dysfunctional
neuroendocrine13,30,31 and meta-bolic12,13,32 pathways, depression, anxiety, obesity, cardiovascular risk, and multiple life stress-ors.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 subjec-tive 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 be-haviors, and, importantly, mea-sures of psychosocial status. In particular, poor sleepers by self-report were signifi cantly more
likely to score in the lowest quartile for emotional, so-cial, 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.
GoodSleepers
ModerateSleepers
PoorSleepers*
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 0.67-0.82Healthy waist circumference† n=2,022 n=2,484 n=1,506
93.2% 91.3% 87.2% 0.50 0.40-0.63Consider their health to be “fair”
or “poor”n=4,650 n=5,896 n=3,506
4.8% 18.7% 46.0% 17.0 14.64-19.77Consider themselves to be “over-
weight” 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=3,57516.7% 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
Sold
iers
in S
tudy
Aerobic Activity
Strength Training
Passed APFT inTop 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 Medi-cine 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.
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and dietary behaviors than good sleepers. Additionally, poor sleep-ers 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 re-lationship 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, hopeless-ness, 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 sui-cide risk. In other military specifi c populations, sleep problems proved to be an im-portant mediator for developing posttraumatic stress disorder or depression.3,6 A strong asso-ciation between sleep quality and perception of stress has also been demonstrated.8 In addition, Collen et al1 found that hypersomnia, sleep frag-mentation, 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 psy-chological 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 perfor-mance.26,56,57 Whether this performance decrement in as-sociation with sleep quality is confounded by perceived stress remains to be determined.
The strong association between sleep quality and emo-tional 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 nd-ings are supported by previous work.58,59 In particular, Ailshire et al58 demonstrated that strained family rela-tionships were associated with troubled sleep; whereas, supportive family relationships were related to high-quality 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) Dimen-sionsGAT FitnessDimensions
GoodSleepers
(n=2,575)
ModerateSleepers(n=2,475)
PoorSleepers*(n=1,984)
OR(P<.001)
95% CI
Emotional 19.3% 54.5% 84.6% 23.00 19.64-26.85Social 24.1% 54.4% 82.2% 14.47 12.47-16.79Family 28.1% 52.6% 72.4% 6.71 5.83-7.72Spiritual 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.
GoodSleep Category
Poor
Emotional
Social
Family
Spiritual
60%
0%
10%
20%
30%
40%
50%
70%
80%
90%
Moderate
Low
est Q
uart
ile o
f Dim
ensi
ons
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Pollock et al60 found that close and fl exible family rela-tionships 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 psy-chological 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 exer-cise guidelines, eat breakfast on a regular basis, engage in positive eating habits, and more likely to drink sugar-laden 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 qual-ity, 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 con-suming breakfast is associated with enhanced attention and cognitive performance relative to not eating break-fast.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 cardio-metabolic risk profi les in adults 20 to 39 years of age when compared to skipping breakfast. Likewise, Nara-ng et al71 have indicated that adolescents who scored the
highest on measures of sleep disturbances were signifi cantly more likely to have cardio-vascular risk factors and hypertension than those who scored the lowest.
Studies have also shown a relationship be-tween sleep and successful weight loss. For example, Chaput et al72 found that more fat mass was lost over the course of a weight-reduction program by those who reported good sleep quality prior to starting the pro-gram. Consistent with that work, Thomson et al73 found that participants who reported bet-ter 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 con-cluded 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 unconvention-al eating hours and snack dominance were refl ective of a low quality diet, that is, lower intakes of fruits and veg-etables and higher intakes of sweets and fat as a percent-age 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 Pitts-burgh 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 per-sons self-reporting poor sleep was what had been antici-pated. Thus, the results are most likely accurate given the large sample size. Secondly, the relationships be-tween 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 contri-bution of the factors discussed herein. Finally, the infor-mation 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 pat-terns 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 Variablesin Model
R R² R² Change Standardizedβ Coeffi cient
PValue
1 Active Duty 0.107 0.011 0.011 0.063 .002 Enlisted Status 0.127 0.016 0.005 0.020 .033 Gender 0.132 0.017 0.001 0.040 .004 Married 0.136 0.018 0.001 0.029 .015 HES-5 0.262 0.068 0.051 -0.104 .006 APFT Total Score 0.273 0.074 0.006 -0.086 .007 Emotional Fitness 0.461 0.212 0.138 -0.277 .008 Social Fitness 0.473 0.223 0.011 -0.121 .009 Family Fitness 0.477 0.226 0.004 -0.073 .00Note: A stepwise multiple linear regression model was used to predict poor sleep using the following variables:
Age Active duty Married APFT total scoreGender Enlisted HES-5 4 GAT dimensions
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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 sup-port the concept of the Performance Triad. The results underscore the need to provide education on the health consequences of poor sleep habits and supportive re-sources for ensuring suffi cient high quality sleep. How-ever, this should be done in an integrative fashion so as to include information on nutrition and physical fi t-ness, as they are intertwined and must be considered as a whole.
ACKNOWLEDGEMENTSThis research was supported by a grant from Compre-hensive 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 Ka-zman for statistical support and Preetha Abraham for graphic assistance.
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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-im-proving 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 veter-ans. 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 di-agnosis and management of chronic sequelae of war-related mild to moderate traumatic brain in-jury. J Rehabil Res Dev. 2009;46(6):757-796.
20. O’Connor MF, Irwin MR. Links between behavior-al 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 acti-vates cellular markers of infl ammation: sex differ-ences. Brain Behav Immun. 2010;24(1):54-57.
23. Irwin MR, Wang M, Ribeiro D, et al. Sleep loss ac-tivates cellular infl ammatory signaling. Biol Psy-chiatry. 2008;64(6):538-540.
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24. Motivala SJ, Sarfatti A, Olmos L, Irwin MR. In-fl 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 con-tribution of pain and depression to self-reported sleep disturbance in patients with rheumatoid ar-thritis. 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 de-fi 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, Zei-gelboim 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 depriva-tion and stressors: evidence for elevated negative affect in response to mild stressors when sleep de-prived. Emotion. 2012;12(5):1015-1020.
30. Mong JA, Baker FC, Mahoney MM, et al. Sleep, rhythms, and the endocrine brain: infl u-ence 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 acceler-ates reentrainment of human sleep-wake cycle but not of plasma melatonin rhythm to 8-h phase-ad-vanced 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 repre-sentative sample. Appetite. 2013;64:71-80.
36. Golley RK, Maher CA, Matricciani L, Olds TS. Sleep duration or bedtime? Exploring the associa-tion 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 regu-lation 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 indi-viduals. Am J Clin Nutr. 2011;94(2):410-416.
39. Gebhart C, Erlacher D, Schredl M. Moderate ex-ercise plus sleep education improves self-reported sleep quality, daytime mood, and vitality in adults with chronic sleep complaints: a waiting list-con-trolled 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 pro-gram: 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 Febru-ary 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 sub-jects 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/publications/hei/hei-2005/hei-2005technicalreport.pdf. Accessed August 1, 2013.
48. Guenther PM, Reedy J, Krebs-Smith SM. Develop-ment 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.
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50. Weinstein SJ, Vogt TM, Gerrior SA. Healthy Eat-ing 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 Per-formance 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 devel-oping and maintaining cardiorespiratory, muscu-loskeletal, 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 appli-cations. In: Bickman L, Rog DJ, eds. Applied So-cial 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-regula-tion 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 com-plaints: 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 care-givers: an overview of the state of the science. Arch Psychiatr Nurs. 2011;25(6):456-468.
60. Pollock E, Kazman J, Deuster P. Family function-ing 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 du-ration. Public Health Nutr. 2011;14(5):889-895.
63. Hitze B, Bosy-Westphal A, Bielfeldt F, et al. Deter-minants and impact of sleep duration in children and adolescents: data of the Kiel Obesity Preven-tion 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. Psy-chiatry 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, Pinco*ck 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 net-works engaged during mental arithmetic in school-aged 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 car-diometabolic risk factors and the metabolic syn-drome 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. Rela-tionship between sleep quality and quantity and weight loss in women participating in a weight-loss 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 In-dex: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193-213.
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75. Carpenter JS, Andrykowski MA. Psychometric evaluation of the Pittsburgh Sleep Quality Index. J Psychosom Res. 1998;45(1):5-13.
AUTHORSMs 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 actu-ally 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 Uni-versity 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 subse-quently shown that preceding death, sleep-deprived rats display transmigration of bacteria from the gut that re-sults in widespread extraintestinal infection/septic load.2 Similar effects of sleep loss have not been observed in any other species, including humans (and notably, nei-ther 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 es-timates that between 1999 and 2008 sleepiness was a contributing factor in 16.5% of traffi c fatalities (approxi-mately 69,300 deaths) in the United States.3 And it is clear that insuffi cient sleep exacts an enormous econom-ic 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 vegeta-tive state/unresponsive wakefulness syndrome show no discernible evidence of sleep.6
This is not to say that sleep plays no role in the mainte-nance of health. Over the past 2 decades, evidence that chronic sleep disturbance is associated with mood disor-der,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, PhDThomas J. Balkin, PhD
ABSTRACTIt 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 discov-ered 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, ev-idence-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.
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disease,11 and even cancer12 has steadily accrued. The ex-act 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 u-ence. Compared to food, air, or water—resources ob-tained 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-to-day 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 higher-order mental abilities including situation awareness, problem-solving, memory, and creativity.13-15 The im-portance of sleep to higher-order mental abilities is illus-trated 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 ar-eas located in the frontal portion of the brain), the brain region responsible for mediating the highest-order cog-nitive 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 un-doubtedly confers unique benefi ts to the brain itself.
PUBLIC AWARENESS OF THE IMPORTANCE OF SLEEPPartly 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 discov-ery 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 medi-cal literature in 1976,23 is now a widely used and under-stood 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 hu-man 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-mak-ing 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 accord-ingly27) have heightened awareness of the importance of adequate sleep, particularly for those engaged in oc-cupations 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 Sol-diers need to remain effective?” This question refl ects the tacit calculation that Soldier pro-ductivity 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 agil-ity” or “situational awareness” for sleep. The question then becomes “what is the minimum amount of mental agility/situational aware-ness that my Soldiers need to remain effective?” From both a physiological and practical stand-point, 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 great-est metabolic deactivation compared to baseline (normal alertness). Adapted from Thomas et al.16
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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 small-est “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 situ-ation 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 estab-lishes 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 insuf-fi cient sleep, deleterious) effects underlie the relation-ship between sleep and general health, relationships that
Operationally Relevant Capability Impacted by Sleep.
MOST IMPACTED ALSO IMPACTED LESS IMPACTED
Acquiring, assigning pri-orities, allocating, and using resources
Anticipating and solving problems
Managing and exploiting change
Acting decisively under pressure
Establishing positionRequesting fireCoordinating squad
tacticsMonitoring environ-
ment (vigilance)Attending to preven-
tive maintenance
Loading magazines
LiftingDigging, 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 10Hrs TIB
8 Hrs TIB
8 Hrs TIB
8 Hrs TIB
8 Hrs TIB
8 Hrs TIB
8
6
4
2
10
Mea
n Es
timat
ed L
apse
s
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
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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 cross-sectional 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 alert-ness 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 mis-sion can exact costs in terms of effi ciency or effective-ness, it is possible that too much time allocated for sleep could cut into military effectiveness by ineffi ciently cut-ting 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 op-erations, 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 lynch-pin of success for a sleep/alertness management pro-gram, 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 fam-ily 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 im-proved mood.
WHAT DRIVES OUR SLEEP BEHAVIOR?
This change in behavior and attitude is neither simple nor straightforward because when left to our own de-vices, 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 sub-jectively 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 obstruc-tive sleep apnea will often reply that they feel normally alert, even though they cannot maintain wakefulness under nonstimulating situations such as sitting in meet-ings, 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 en-vironment), 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 sub-jective sleepiness has substantially increased. Similarly, in one study, Belenky et al33 showed that this habitua-tion 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 real-world conditions in which individuals may volitionally increase total recuperative sleep time (TrST) over time, but a similar lack of correspondence between perfor-mance and subjective alertness was evident in both the 5-hour and 7-hour TIB groups in which the TIB decre-ment was not so drastic.
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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 TIB3, 5, 7, or 9 Hrs TIB
Mea
n R
ecip
roca
l Rea
ctio
n Ti
me
(1/ R
T×10
00
)
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 TIB3, 5, 7, or 9 Hrs TIB
1.0
6.0
2.0
3.0
4.0
5.0
7.0 Panel B
Mea
n Sl
eepi
ng S
core
(Ran
ge 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 per-formance. 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 sleepi-ness, such as fatal automobile crashes, are relatively infrequent even among young adults, for whom traf-fi 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 ag-gressive education component, (2) an accurate, objec-tive 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-iden-tifi ed “experts” who appear on television and radio talk shows and sensationalize research fi ndings or dissemi-nate 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 (nonsen-sationalized) 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 du-ration 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 well-controlled laboratory environment to real-world con-ditions. 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-de-prived 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 mission-planning process, and individual Soldiers and their fami-ly 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 objec-tive 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 pre-dictable way: during a daytime sleep period, individu-als awaken frequently, although they may not remember these awakenings, which may last only a few seconds to a few minutes. Daytime “sleep fragmentation” or de-graded “sleep quality” is caused by the brain’s circadian alertness signal* and/or from light, noise, or other en-vironmental 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 continu-ity led to the same conclusion: there is no evidence that sleep continuity or sleep fragmentation are measurable factors contributing independently to recuperation dur-ing sleep.34
Currently, the technology best suited for objectively tracking relevant sleep parameters in the operational environment is wrist actigraphy. This mature and well-validated 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.
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accelerometer contained within the actigraph and then scored for sleep or wake using a sleep/wake scoring al-gorithm. 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/wake-scoring algorithm resides on a microprocessor in the actigraph and sleep/wake is automatically scored. Real-time information regarding amount of time spent sleep-ing 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 light-est stage of sleep (N1) which appears to have no recu-perative value is indistinguishable from deeper stages of sleep that have been clearly linked to recuperation. In normal sleepers, this limitation is almost inconse-quential since normal individuals do not spend appre-ciable amounts of time in stage N1 (and almost none at all if they carry a sleep debt). However, in certain pa-tient populations who experience numerous awakenings (and consequently more stage N1), their total recupera-tive sleep may be overestimated, and less sensitive acti-graphs 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 ben-efi 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 prac-tical value (for example, knowing how much gas is in your vehicle’s tank is useful, but not as useful as know-ing 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 appro-priately manage without an external, objective, quanti-fi able measure against which the success or failure of management efforts can be gauged.
In terms of “sleep miles per gallon,” mental effective-ness 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 mili-tary operations and in daily living. At the group (squad,
platoon, etc) level, such information is valuable to plan-ners 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 per-ceives 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 Depart-ment of Defense (DoD).38-45 The Federal Aviation Ad-ministration recently determined that effectiveness models (and specifi cally the DoD model) have under-gone suffi cient evaluation to be used in aviation fatigue risk management decisions. The US Naval Safety Cen-ter 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 manage-ment 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 mitiga-tion 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 effective-ness 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 objec-tive marker of sleep health.
But what is the long-term goal that can be subserved by improved sleep (and thereby improved mental effective-ness)? 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 reduc-tion 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
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THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS
health ailments. Regardless of mechanism, the implica-tion 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 en-sure 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 appre-ciate 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 mod-els 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.
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ACKNOWLEDGEMENTSThe 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.
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AUTHORSDr Wesensten is a Research Psychologist in the Behav-ioral Biology Branch, Center for Military Psychiatry and Neurosciences Research, Walter Reed Institute of Re-search, Silver Spring, Maryland.Dr Balkin is a Supervisory Psychologist and Chief of the Behavioral Biology Branch, Center for Military Psychia-try and Neurosciences Research, Walter Reed Institute of Research, Silver Spring, Maryland.
THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS
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