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Military Fitness Research, 2017

by Guy Leahy, MEd, CSCS,*D
TSAC Report June 2017

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The American College of Sports Medicine (ACSM) 64th Annual Meeting was held in Denver, CO May 30 – June 3, 2017. Overall, there were more than 50 presentations with a military focus, an indication of the importance of this research. The following is a review of some of the presented research.

The American College of Sports Medicine (ACSM) 64th Annual Meeting was held in Denver, CO May 30 – June 3, 2017. Overall, there were more than 50 presentations with a military focus, which included two poster sessions devoted to this topic, and a symposium specific to Special Operations forces across the world, an indication of the importance of this research. The following is a review of some of the presented research.

Female soldiers are now eligible for front line infantry positions, and several presentations examined various aspects of this change in combat operations. One of these research papers investigated the role of fitness and gender of unit Soldier Performance Index (SPI) scores on a “mock” Airborne unit (3).  A total of 71 subjects participated in the study. The subjects included 69 Airborne soldiers, consisting of 26 officers (Rock LT), 43 soldiers (Rock S), and 2 selected U.S. Service Academy female cadets (FC) (3). Airborne units consist of soldiers who receive parachute training as a means of deployment into ground combat situations. These groups completed the SPI (which consists of a strength component: cadence pull-ups; 155-lb bench press; muscular endurance component: 65-lb bench press; 45-lb dumbbell squat; endurance/mobility component: 2-mi run; 300-m forward/ backward run; and the Army Physical Fitness Test which consists of 2-min push-ups and 2-min sit-ups). Ten member mock units were created with highest performance officer and different combinations of 9 highest performance soldiers (HOS), 8 highest performance soldiers and highest performance female (H&F), 7 highest performance soldiers and 2 highest performance female soldiers (72F), and 9 lowest performance male soldiers (LOS). A comparison of the SPI performance of all these groups found that the HOS group displayed the highest SPI, though the difference was not significant when compared to the H&F and 72F groups. The H&F and 72F groups achieved 98.5% and 96.7% of HOS performance on the SPI. The LOS group was significantly (p=0.01) lower compared to the other three groups (3). Interestingly, FC were only 68.4% of SPI ability of the mean Rock LT group, yet had 17.6% greater ability than the Rock LT group on the APFT. These results suggest that the SPI is a better predictor of ground combat performance than gender or APFT scores, and that the poor performance of the APFT to predict ground combat ability may be due to the lack of a strength measure in this test battery. Authors felt integration of Airborne units would be best determined by the SPI, or a similar index which incorporates muscular strength as a test component.

Another study compared male and female British Army personnel performance on three Representative Military Tasks (RMT), passing scores of which are required to become a member of the British Infantry (2). The purpose of the study was to evaluate male versus female performances on the RMT. The RMT include a loaded march (12.8 km, carrying 25 kg, < 2hr); a jerry can carry (two 20-kg jerry cans for 150 m); and a single lift (40 kg powerbag from the floor onto a 1.45 m platform). This study included 135 subjects (48 female, 87 male), completing two sessions separated by at least 7 days. Session 1 consisted of height, weight, and body composition estimated using dual energy X-ray absorptiometry. Participants also completed the single lift and the jerry can carry components of the RMT, plus a 2.4-km run. Session 2 consisted of the 12.8-km loaded march carrying 25 kg (6.4 km paced in 60 min and 6.4 km best effort). Results showed that compared to female participants, male personnel had faster 2.4-km run times, greater body mass, greater total lean body mass, higher single lift scores, and achieved greater jerry can carry distances and faster loaded march times (2). All male personnel and 13% of female personnel passed the Infantry standard across all RMT components. The greatest gender difference among the RMT components was for the single lift; 97% of male personnel met this standard vs. 15% of female personnel. As with the SPI study above, muscular strength accounted for the greatest gender difference in performance (3). Both studies indicate that focusing on improving muscular strength should be a priority for female personnel who wish to serve in front line combat positions.

Another study attempted to quantify the gender differences in external (distance and speed) and internal (ratings of perceived exertion; RPE) and heart rate training loads during the first two weeks of British Army Phase One training (similar to U.S. Army Basic Training) (10). The study subjects were 26 female and 24 male recruits. The subjects were fitted with a combined HR and global position system (GPS) device and monitored during waking hours for the first 10 days of training. Male recruits covered significantly (13.31 + 0.83 km vs. 10.85 + 0.70 km, p<.001) more distance per day than female recruits, and at a greater mean speed (0.88 + 005 km/hr vs. 0.74 + 0.03 km/h, p<.001). Mean HR reserve (HRR) and RPE were not significantly different between males and females (%HRR: male = 31+ 3 vs. female = 32 + 4; RPE: male = 4 + 1 vs. female = 4 + 1). Female recruits did report significantly greater physical fatigue (p<.001) and muscle soreness (p<0.05) than male recruits, despite a lower absolute external training load.

Another study assessed body composition and physical characteristics of male and female Marines from the Marine Corps Ground Combat Integrated Task Force (1). A total of 302 Marines participated in the study. The tests included body composition using air displacement plethysmography, plus a battery of aerobic/anaerobic, balance, biomechanics, and flexibility tests.  The subjects were then classified by performance clusters (C1, C2, C3). Cluster C1 with the best strength and aerobic/ anaerobic characteristics, C3 with the worst strength and aerobic/ anaerobic characteristics, and C2 between C1 and C3 in those characteristics. These clusters were stratified by gender (male: C1M, C2M, C3M; female: C2W, C3W). Fat free mass (FFM) was significantly (p<0.05) different among all groups and interestingly, C1M and C2W had significantly greater fat mass than C3M (1). This study suggests that FFM may have a stronger association with strength, aerobic and anaerobic tests than BF% or fat mass. Interestingly, new Marine Corps regulations, in effect since January 2017, now permit BF and weight requirements to be waived if personnel achieve scores of 285 or higher on both the Physical Fitness Test (PFT) and Combat Fitness Test (CFT). Scores on the PFT and CFT between 250 and 284 may allow for a 1% upward adjustment in BF% (9). 

Several presentations focused on various methods to predict military task performance. One poster investigated physical fitness and anthropomorphic measures to predict load carriage performance (6). The study involved 67 male and 37 female soldiers who performed a 12-mi foot march for time, carrying a 46.4-kg load (FM12). This task was compared to their scores on the Army Physical Fitness Test, which is a 2-mi run for time + maximum number of push-ups and sit-ups completed in 2 min. Height in cm and body mass in kg were also measured. The results indicated that height, body mass, pull-ups, and 2-mi run all correlated significantly (p<0.001) with FM12 (6). Approximately 56% of the variability on FM12 performance could be predicted by the sum of these four test results. The authors concluded that “these readily available data provide an easy to employ method of predicting a Soldier’s physical capabilities for FM12.” There appear to be a couple of issues with the author’s interpretation of the results, however. The first is that 44% of the variability is not explained by this model, so clearly there are factors influencing FM12 results which are not explained with the model. The second is that predicting a loaded FM12 march using an unloaded 2-mi run may be an inappropriate comparison. For example, in an unloaded run, one would expect to see a significant positive relationship between run time and body mass (i.e., smaller soldiers will have faster run times). With a loaded 2-mi run, however, there will likely be no relationship between body mass and run time, so an unloaded run potentially yields very different results than a loaded run would.

Another study examined which physical fitness components might predict performance of a Warrior Task Simulation Test (WTST). The WTST is a continuous nine sequential event course comprised of running, jumping, crawling, climbing, obstacle negotiation, and material handling tasks (8). For the study, 43 physically active males participated in one WTST session and one laboratory test session. The laboratory sessions included muscular strength, muscular endurance, postural stability, aerobic capacity, anaerobic capacity, flexibility, body composition, fat free mass, and agility. Multiple linear regression analysis was used to predict WTST performance using the physical fitness test results. Muscular endurance, aerobic capacity, body composition, fat-free mass, and agility significantly (p<0.001) contributed to a model which predicted nearly 52% of WTST performance (8). As with the previous poster, a significant amount of variability (48%) was not predicted by the model. Future research should attempt to identity other variables which predict WTST performance.

One presentation investigated the relationship between recruit physical fitness test scores and performance on occupationally relevant tasks (5). A total of 186 male recruits who were taking the Australian Army 12-week basic training course were included in the study. The subjects were subjected to a battery of tests which included generic fitness tests, maximal push-ups in 2 min, and a multi-stage shuttle test (MSST). The subjects also participated in military related tests, including a 1-repetition maximum box lift and place, and a 3.2-km loaded run (22 kg). The “generic fitness tests” form part of the Australian Army recruit physical barrier tests. Physical performance was assessed at weeks 1 and 11. The results indicated that maximal push-up performance was not correlated with box lift and place performance. Push-up performance was moderately to strongly correlated with 3.2-km loaded run performance. Maximal MSST performance was also correlated with performance on the loaded run. The ability of push-ups and MSST to predict 3.2 km run load carriage decreased over the duration of basic military training (BMT). These results indicate, consistent with other research, that generic fitness tests do not predict tactical athletes’ ability to perform important occupational tasks which require strength, such as manual handling (11). Previous findings have concluded that muscular strength is an important predictor of military task performance, and recruit test batteries would be improved by adding a component that assesses muscular strength performance (11).

Another study looked at whether anthropomorphic measures and upper body strength could predict performance on a tank ammunition loading task (TAL) where armor personnel repeatedly lift and carry rounds (13). While wearing a fighting load of approximately 32 kg, minus a weapon, 94 male and 90 female soldiers carried 18 tank rounds, weighing 25 kg each, for a distance of 5 m and lifted the rounds onto a platform simulating an Abrams tank hull. Performance on the TAL was measured by the number of rounds moved per minute. Soldiers performed an isometric biceps curl for upper body strength and their height (measured in cm) and body mass (measured in kg) were measured. For male soldiers, 15% of the variability in TAL performance could be explained by a combination of biceps curl, height, and body mass, in female soldiers, 48% of TAL performance could be explained by this combination (13). For male soldiers, biceps curl was the only significant predictor of TAL performance; for female, body mass and biceps curl had the greatest association. The authors suggest that “training programs designed to develop a Soldier’s upper body strength may enhance TAL task performance and mitigate injury. It would have been interesting to assess body composition in this study to see if lean body mass, versus body mass alone, had an effect on TAL performance,” (13).

There were other studies on a variety of topics which had a tactical emphasis. One study examined the importance of sleep duration on upper respiratory infection (URTI) and subsequent loss of training days in military recruits (16). In civilian populations, habitually sleeping <6 hr per night has been shown to lower immunity, and increase susceptibility to URTI (12). Participants included 651 British Army recruits who completed 13 weeks of Phase 1 military training (67% males, 33% females). At week 13, participants completed a questionnaire asking the normal time they went to sleep and awoke before training. Incidence of physician-diagnosed URTI and reduced or missed URTI-related training days were retrieved from medical records. The results indicated that recruits who slept <6 hr per night were four times more likely to be diagnosed with a UTRI than recruits who slept 7 – 9 hr per night. On average, each URTI resulted in 2.9 + 1.5 reduced or missed training days (16). This study provides more documentation that sleep loss negatively impacts military readiness, and interventions to improve sleep hygiene should be a priority. 

Many studies have documented that body mass bias (BMB) is widespread in military fitness testing, and consequently confounds interpretations of fitness test results (15). Both distance run times and VO2max are body mass dependent, for example, changes in body mass will influence these scores independently of changes in fitness. One study tested this by using 572 personnel from the Croatian Army (7). Subjects performed a 2-mi run, a 300-yd run, and a VO2max test performed on a treadmill. The results yielded an allometric exponent close to the theoretical 0.33, which indicates these tests penalize larger soldiers compared to smaller soldiers, as documented elsewhere (15). There are various ways to correct for BMB. The most practical method involves wearing an added loaded backpack during distance run and push-up tests. This has been documented to remove BMB from these tests, and because personnel usually have to carry added loads while deployed, the added backpack mass also introduces an occupational element to the test (14).

High intensity interval training (HIIT) has become very popular recently, but no previous study has investigated variations in HIIT frequency on performance of an official military cardiovascular fitness test. This study compared HIIT training frequency on 1.5-mi run performance in U.S. Air Force Reserve Officer Training Corps cadets (4). A total of 27 cadets were randomly assigned to three groups: a high frequency group that performed HIIT 3x week, a low frequency group (LF) that performed HIIT 2x week, and a continuous training group (CG) that performed moderate intensity training 3x week. The HIIT protocols consisted of 4 x 3-min intervals at 90 – 100% of velocity at maximal oxygen consumption (VO2max) with 4 min of recovery and 4 x 30s all-out sprints with 4 min of recovery on a running track. Baseline 1.5-mi run performance was measured, and then retested at 6 and 10 weeks. All groups significantly (p< 0.001) improved their run time at the 6-week mark, with no differences between groups. No further improvements were seen at the 10-week mark. More research is needed to test the effectiveness of these protocols with longer distance events.  

Utilizing military personnel for research does incur unique challenges. For example, swing and/or night shift work is common in tactical populations, and differences in performance due to circadian rhythms may make it difficult to translate results from personnel who work day shifts to these groups. As noted earlier, body mass is a significant confounder of physical fitness test performance, yet this variable is rarely taken into account in published studies with military populations (15). Mission requirements make it difficult to recruit large numbers of subjects; with this consequence such studies may be underpowered to detect real differences between groups. Another confounder is that military installations are frequently located in extreme environments, and results from studies conducted in arctic climates may not necessarily translate to populations who are stationed in hot desert environments, for example.

Despite these limitations, research presented at conferences such as the National Strength and Conditioning Association (NSCA) and ACSM provide the scientific foundation for evidence-based training of tactical athletes. This research assists tactical strength and conditioning specialists in optimizing training programs for safety and effectiveness. In addition, such research helps in the response to new challenges, such as the integration of females into front line battlefield positions. This type of information is critical in enabling tactical athletes to accomplish their missions successfully.

This article originally appeared in TSAC Report, the NSCA’s quarterly, online-only publication geared toward the training of tactical athletes, operators, and facilitators. It provides research-based articles, performance drills, and conditioning techniques for operational, tactical athletes. The TSAC Report is only available for NSCA Members. Read more articles from TSAC Report 

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References 

1. Allison, KF, Keenen, KA, et al. Body composition and physical determinants of physiological and musculoskeletal readiness in Marines. Medicine and Science in Sports and Exercise 49(5): S69, 2017.

2. Blacker, SD, Coakley, SL, Walker, E, et al. Gender differences in British Army infantry representative military task performance. Medicine and Science in Sports and Exercise 49(5): S71-S72, 2017.

3. Crowder, TS, Kloepper, MF, and MacPherson, IB. Fitness trumps gender; next fit soldier up. Medicine and Science in Sports and Exercise 49(5): S71, 2017.

4. Dahle, J, and Wagner, D. Effects of high intensity interval training frequency on 1.5 mile run times in Air Force cadets. Medicine and Science in Sports and Exercise 49(5): S462, 2017.

5. Drain, JR, Burley, SD, and Billing, DC. Does recruit performance in generic fitness assessments predict performance in military-related tasks? Medicine and Science in Sports and Exercise 49(5): S252-S253, 2017.

6. Frykman, PN, Foulis, SA, Redmond, JE, et al. Predicting load carriage performance using physical fitness and anthropomorphic measures in soldiers. Medicine and Science in Sports and Exercise 49(5): S251, 2017.

7. Gregov, C. Allometric scaling for endurance variables in Croatian Army. Medicine and Science in Sports and Exercise 49(5): S470, 2017.

8. Huang, HC, Nagai, T, Sell, TC, et al. Physical fitness predictors of a warrior task simulation test. Medicine and Science in Sports and Exercise 49(5): S253, 2017.

9. Le, C. Stronger, faster and fitter: CMC overhauls USMC fitness Program. 1 July 2016: http://www.marines.mil/News/News-Display/ Article/822721/stronger-faster-and-fitter-cmc-overhauls-usmcfitness-program.  Accessed 7/8/2017.

10. McGuire, SJ, Saunders, SC, and O’Leary, TJ. Sex differences in training load during British Army phase one training. Medicine and Science in Sports and Exercise 49(5): S72, 2017.

11. Nindl, BC, Alvar, BA, R Dudley J, et al. Executive summary from the National Strength and Conditioning Association’s second blue ribbon panel on military physical readiness: military physical performance testing.  The Journal of Strength and Conditioning Research 29(suppl 11): S216-220, 2015.

12. Prather, AA, Janicki-Deverts, D, Hall, MH, et al. Behaviorally assessed sleep and susceptibility to the common cold. Sleep 38(9): 1353-1359, 2015.

13. Redmond, JE, Foulis, SA, Frkyman, PN, et al. The effect of anthropomorphic measures and upper body strength on a physically demanding soldiering task. Medicine and Science in Sports and Exercise 49(5): S252, 2017.

14. Vanderburgh, PM, and Mickley, NS. Load-carriage distance run and push-ups tests: no body mass bias and occupationally relevant. Military Medicine 176(9): 1032-1036, 2011.

15. Vanderburgh, PM. Occupational relevance and body mass bias in military physical fitness tests. Medicine and Science in Sports and Exercise 40(8): 1538-1545, 2008.

16. Wentz, LM, Ward, MD, Potter, C, et al. Military recruits who typically sleep <6 hours miss training due to upper respiratory infection. Medicine and Science in Sports and Exercise 49(5): S345, 2017.

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Guy Leahy is currently serving as the Health Promotion Program Coordinator at Kirtland Air Force Base in Albuquerque, NM. Leahy is a member of the Ame...

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