BODY MASS BIAS EFFECTS ON FITNESS TEST AND TACTICAL PERFORMANCE

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1 GUY LEAHY, MED, CSCS,*D BODY MASS BIAS EFFECTS ON FITNESS TEST AND TACTICAL PERFORMANCE The views expressed in this article are those of the author, and do not necessarily reflect the official position or policy of the Department of Veterans Affairs, the NSCA, the Department of Defense, or the U.S. Government. In competitive sport, size may be a primary indicator of successful sports performance. From 50-kg (~110-lb) jockeys controlling a 500-kg (~1,100-lb) racehorse to 150-kg (~330- lb) offensive linemen in the National Football League protecting a quarterback, the physiological requirements of most sports impose a narrow range of body masses that are critical to excel on the playing field. An excellent microcosm of this is seen in track and field, where each event contains athletes whose body mass and shape is highly specific to optimal performance in those events (50). For example, most sprint specialists are larger and more muscular than endurance specialists (50). Even within endurance specialists, there are optimal body masses which are inversely related to event distance (50). In many sports where high levels of strength and power are advantageous (e.g., powerlifting, wrestling, and boxing), bigger is better. In events such as these, the performance advantages of greater size, strength, and power are such that it would be considered unfair for athletes to compete against each other if there is much variance in the athlete s size, as the bigger and stronger athletes would almost always win. As a result, these sports utilize weight classes so athletes compete only against other athletes with similar body masses. This attempt to minimize the advantage of body mass on performance may help to level the playing field. Arguments for utilizing body mass classes to equalize road race competitions have also been made on physiological grounds. Lactate threshold, for example, appears to be strongly related to body mass (4). The recognition that body mass matters in sport has not extended to fitness testing of active duty personnel, where all members, regardless of body mass, are expected to meet the same passing standards. Though the military does make adjustments for age and gender, 90-kg (~200-lb) service members are expected to compete equally with 60-kg (~132-lb) service members in distance runs, push-ups, and sit-ups, despite the 60-kg service members having a possible advantage due to their smaller body mass. Table 1 provides a summary of fitness test components required of United States Army, Navy, and Air Force officers. Because fitness test results become part of performance evaluations, the intrinsic advantage smaller service members have when performing fitness tests may extend into a higher likelihood of attaining promotions, despite the evidence that suggest that greater body size, strength, power, and load carrying capacity is correlated with in-the-field tactical performance (1,15,25,27,40,42). For example, tests such as one repetition maximum (1RM) box lifts, a 10-min repetitive box lift and carry, and a 3.2-km (~7-lb) load carriage time trial were found to be good predictors of soldier readiness; meanwhile, performance on the Army Physical Fitness Test (AFPT) was found to be a poor predictor of soldier readiness (36,42,49). This paradox between scoring well on fitness tests versus components of tactical performance may even result in scenarios during deployments where smaller personal are used who are literally not big and strong enough to successfully accomplish particular missions, thus placing both the individual service member, and the mission at risk (15,40). This issue is of paramount importance, due to the unique physiological challenges faced by deployed personnel relative to athletes (31). The negative consequences of poor tactical performance while deployed are far greater than that of a professional athlete participating in a sporting event. For instance, poor performance on the playing field may result in the loss of a game, while poor performance on a battlefield may result in loss of life. SCALING AND BODY MASS Allometry, which is used in biological scaling, is defined as the relationship between the size of an organism and the size of any of its parts, such as muscle or blood vessel cross-sectional area, limb length, eyeball radius, etc., (40). The concept of allometry has been around for quite some time. The first documented reference to allometry in the research literature was published in 1891 (35). Body mass bias (BMB) focuses on the concept of the inequality of physical performance along the continuum from small to large individuals in terms of body mass (40). Body mass is typically correlated with numerous performance measures such as weightlifting, push-up repetitions, oxygen uptake, and many others (40). The problem with BMB arises when the raw performance score is directly proportional to body mass. Most raw scores of athletic performance, however, do not increase in direct proportion to body mass (body mass exponent of 1.0). Astrand and Rodahl hypothesized that because blood vessel cross-sectional area and cardiac output scale to the two-thirds the power of body mass (0.67), maximal oxygen uptake (VO 2 max) would also scale to two-thirds the power (2). This conclusion was supported by data from athletes participating in five endurance sports (marathon, orienteering, skiing, skating, and rowing) where the use of ratio scaling systematically penalized the VO 2 max of heavier athletes (2). Expressing VO 2 as proportional to the NSCA S TSAC REPORT ISSUE 40

2 BODY MASS BIAS EFFECTS ON FITNESS TEST AND TACTICAL PERFORMANCE power of body mass resulted in a measure of aerobic power which was independent of body mass. Heil, who measured the VO 2 max of a heterogeneous sample of 230 women and 210 men (20 79 years old) also found that VO 2 max was proportional to the two-thirds power of body mass (17). Comparing the subjects VO 2 max using the 1.0 and 2/3 exponents, Heil found that the ratio scaling systematically misclassified 29.3% of the sample as more fit or less fit than they were using the 2/3 body mass exponent (17). He concluded that based on these findings and those of others, it seems reasonable to discontinue the use of ratio scaled VO 2 peak values in the literature unless reasonably justified by the researcher, (17). Other authors have reported a scaling exponent of 0.67 for VO 2 max, though this exponent is not universal and may not apply to other groups (5,30,40,42,51). Chia and Aziz found an exponent of 0.67 for males and 0.24 for females, suggesting the possibility that VO 2 max scaling exponents may be affected by gender (4). In a study utilizing mammals ranging in size from kg, Weibel and Hoppeler found different exponents for athletic versus non-athletic species, and that these different exponents were due to differences in total mitochondrial and capillary volumes of muscle (51). BMB also occurs in relation to strength, force, and muscular power. Jaric et al. suggested that muscle force is proportional to the physiological cross-sectional area of the muscle and should increase with body size (19). This exponential relationship has been used often to explain why muscle strength increases at a lower rate than body mass. In addition, tests of muscular endurance and aerobic fitness, such as push-ups, sit-ups, and distance runs, scale with an exponent of since the muscle force required to move body mass against gravity scales with the exponent, whereas bodyweight scales with an exponent of 1.0 relative to body mass (18,35,38). As with VO 2 max, scaling exponents related to strength and power activities may differ in some circumstances (16,29). BODY MASS BIAS IN MILITARY FITNESS TESTING Several investigators have examined relationships between body mass and performance on fitness tests used by military populations. One of the earliest was Vanderburgh and Mahar who assessed body mass effects on two-mile run time using 59 cadets from the United States Military Academy (47). Body mass and body fat percentage, as estimated from a three-site skinfold equation, were collected prior to the two-mile run test. When comparing body mass to cadet two-mile run time, a moderate correlation (r = 0.55) between body mass and two-mile run time was found (47). Interestingly, when the results were reevaluated using fat free mass (FFM), a similar, though smaller correlation (r = 0.32) was found (47). The authors concluded that individuals with lower FFM are at an advantage when competing against individuals with higher FFM in running events (47). In a different study, an allometric scaling exponent of removed the confounding effect of body mass and eliminated BMB in the run performance (43). When run performance was allometrically scaled with an exponent of -0.41, the correlation between the scaled value and body mass was nonsignificant, indicating that the influence of body mass had been removed. Crowder and Yunker, using a similar population of United States Military Academy cadets, found that push-ups and sit-ups also imposed a BMB on the test subjects (8). They proposed scaling push-up and sit-up performance by an exponent of -0.38, which partitioned out the BMB and rendered the push-up and sit-up scores free of body mass influences (8). They also documented a BMB-free scaling exponent of for the two-mile run time (8). Because the scaling value of predicted by allometric theory fell at the midpoint of and -0.26, Vanderburgh and Crowder proposed that scaling of distance run times with a body mass exponent of is warranted (45). Vanderburgh and Crowder quantified the extent of the BMB for an endurance run and for push-up and sit-up performance for U.S. Army, Air Force, and Navy personnel (45). Comparing the total scores of two 28-year-old hypothetical males with a body mass of 60 kg and 90 kg, plus two 28-year-old hypothetical females with a body mass of 45 kg and 75 kg, these authors found significant BMB for the male and female with the greater body mass (45). For example, in order for the 60-kg male subject to achieve a maximum of 100 points on the Army push-up test, he would have to perform 77 push-ups in two minutes. An equivalent push-up score for the 90-kg male subject, after scaling the result of the 60- kg subject (-0.33), would yield a score of 67 push-ups, which is a point reduction of 11%. The 45-kg female subject would have to run the two-mile run in 15:48 to achieve the maximum of 100 points. The equivalent scaled time of the 75-kg female subject would be 18:44, which is a 26% reduction. The total score penalty ranged from % in males and % for females, depending on which scoring system was used. Since theoretical models were used, there were no differences in body composition between the smaller and larger subjects. In addition, because fitness test scores are a component of performance evaluations, BMB may provide an unfair advantage to smaller statured tactical athletes regarding candidacy for promotion in rank (1,15,25,26,27,40,42). In a follow-up paper, Vanderburgh provided correction factors to partition out the BMB inherent in military fitness tests (44). These correction factors are much easier to use than scaled scores, and could readily be included in statistical software packages, or even as applications, for on the field adjustments. The scaled scores were as follows: if a 120-lb (~54.5-kg) female performed 50 push-ups, then her adjusted score would be 50 x 1.0 (the correction factor) = 50 push-ups (44). If a 150-lb (~68.1-kg) female performed 47 push-ups, then her adjusted score would be 47 x 1.06 (correction factor) = 49.82, or 50 push-ups (44). For adjusting NSCA S TSAC REPORT ISSUE 40 31

3 GUY LEAHY, MED, CSCS,*D two-mile run times, the correction factors decline with increasing body mass, as faster times are preferred (44). Vanderburgh provided the following example: an actual score of for a two-mile run must be converted either to seconds (e.g., 937 s) or minutes with decimals ( /60 or min) before multiplying by the correction factor. For a 189-lb (~85.9-kg) man with a run time, his adjusted score would be 0.93 x 937 s or 871 s, or 14:31, over a one-minute handicap, (44). The idea that added body mass might provide an unfair benefit, even if it is body fat, is not supported by the data. The previous correction factors are derived from allometrically scaled models, with no change in body composition. For example, looking at two soldiers who have 15% body fat, one who is 75 kg (~165 lb) and the other is 90 kg (~198 lb), the 90-kg soldier is 20% larger. Therefore, in this case, the use of correction factors will fairly remove BMB from the uncorrected scores of the two. Conversely, if the 75-kg soldier has 15% body fat, but the 90-kg soldier possessed 25% body fat, the correction factor would actually produce a larger penalty on the score. This result was suggested by data from Vanderburgh and Laubach, which derived an equation for adjusting body mass for a 5-k run (43). Using this equation, if a hypothetical 45-year-old male who is 85 kg (~187 lb) with 15% body fat were to gain 3 kg (~6.6 lb) of muscle, then his adjusted 5-k time would decline by 13 s; conversely, if the same subject gained 3 kg of body fat, then his adjusted 5-k time would decline by 56 s. A follow-up study by Crecelius, Vanderburgh, and Laubach confirmed this equation successfully partitioned out differences in lean body mass while preserving a scoring penalty for excess body fat (9). A related issue is that excess body fat does not appear to affect VO 2 max, but does affect distance run time. Thus, using distance run times to estimate cardiovascular fitness may unfairly penalize heavier subjects, including those who meet national recommendations for frequency, duration, and intensity of aerobic exercise. Cureton et al. measured maximal treadmill time and 12-min run performance in six subjects under four conditions: 0%, 5%, 10%, and 15% added mass (11). The added mass was secured to the trunk with a harness. These authors found that each 5% increase in added mass was correlated by a stepwise reduction in treadmill run duration and 12-min run distance (11). With the 12-min run, for example, each 5% increase in extra mass resulted in an average decline in run distance of 89 m (11). The same 5% increase in added mass reduced maximal treadmill time by 35 s (11). Therefore, an increase of 15% added mass would result in a reduction in run distance of 267 m and a reduction in treadmill time of 1:45. These effects on run time or treadmill duration were primarily the result of the increased oxygen cost of submaximal speeds. Added mass did not affect VO 2 max when expressed as l/ min or as ml/kg/ffm/min. Cureton et al. concluded that failure to distinguish the metabolic effects of body fatness from the influence of cardiorespiratory capacity may result in misleading interpretation of distance run test scores, (11). A related study using children and overweight women by Goran et al. found that total body fat did not affect VO 2 max, but did affect submaximal exercise capacity (14). When VO 2 max was expressed as ml/kg/ FFM/min, there were no significant differences in VO 2 max between obese and lean children (14). Additional recent investigations have focused on the utility of employing allometric scaling to correct for BMB in military fitness testing. Examining U.S. Army infantry soldiers, Hendrickson et al. found significant correlations for two-mile run time and pushup performance with body mass, but no significant correlation between sit-up performance and body mass (16). Using allometric scaling with a correction factor did not remove BMB from either the sit-up or run tests, but did remove BMB from the pushup test (16). Multiple regression models did remove BMB from all test components of both genders. Kobermann et al. found no BMB in the test scores of college Army Reserve Officers Training Corps (ROTC) cadets (20). However, the sample size was very small (41 males and 21 females) and may not have been large enough to detect BMB. In addition, the body mass standard deviation from this population was ±13.1 kg, so the range of body size was very small relative to typical Army populations. Leahy, Crowder, and Mayhew tested allometric scaling with 553 Air Force males, and found significant correlations between body mass and all test components (run, push-ups, and sit-ups,) as well as with total test score (24). Using the allometric scaling exponents of Vanderburgh, they removed BMB from the pushups and from the summed total score, but not from the run or sit-ups. These authors also examined BMB in Air National Guard (ANG) men and women (22,23). For the males (n = 1,004), body mass was significantly correlated with performance on all test components (run, push-ups, and sit-ups) and total score. Application of allometric scaling according to Vanderburgh removed BMB from the run and push-up, but not from the sit-up or total score. A scaled coefficient of did remove BMB from the sit-up component and the sum of the scaled scores (22). For ANG women (n = 197), body mass was also significantly correlated with all test components and total score. The use of Vanderburgh s exponents eliminated BMB from total score but not from any of the test components. Instead, exponents of 0.43, -0.68, and for the run, push-ups, and sit-ups, respectively, removed BMB from all components as well as the scaled total score (23). THE FIT TO TEST VS. FIT TO FIGHT PARADOX An additional problem related to BMB and fitness testing is that traditional fitness tests do not appear to be good predictors of military operational performance; therefore, those personnel who perform well on distance runs, push-ups, and sit-ups may not possess the physical abilities needed to optimize tactical fitness requirements potentially. Walker et al. compared a variety of laboratory measures of physical fitness with military specific tasks 32 NSCA S TSAC REPORT ISSUE 40

4 BODY MASS BIAS EFFECTS ON FITNESS TEST AND TACTICAL PERFORMANCE and found that absolute VO 2 peak, medicine ball shot put, and a bench throw using 30% 1RM correlated well with a grenade throw for accuracy, 1RM box lift, and a 3.2-km road march with a 33-kg (~72-lb) load (49). The standing long jump and vertical jump tests correlated with a running long jump while carrying a 20.5-kg (~45-lb) load; by contrast, VO 2 peak expressed as ml/kg/min did not correlate with any military task (49). Bilzon, Allsopp, and Tipton compared the exercise tolerance time of 12 male volunteers while running to exhaustion on a treadmill in an unloaded state and while carrying an 18-kg (~40-lb) backpack (3). Those subjects with greater lean body mass performed significantly better on the tolerance test, despite having lower relative VO 2 as measured by a four minute treadmill run at 9.5 kph (~5.9 mph) (3). These authors concluded that fitness tests that determine aerobic power in units relative to body mass (such as timed distance run) incur a systemic bias against heavier personnel (3). Therefore, they felt such tests were inappropriate for predicting the ability of personnel to work in occupations that encompass load-carrying tasks. A related study found that absolute VO 2 max correlated better with a simulated 40-kg (~88-lb) load carriage task than did relative VO 2 max (26). In addition, Harman and Frykman found that higher lean body mass was positively associated with load carriage and lifting performance, plus the ability to push, carry, and exert torque (15). Vickers, Reynolds, and McGuire compared scores from the Marine Combat Fitness Test (MCFT), a test designed to mimic battlefield conditions, with scores from the more traditional Physical Fitness Test (PFT) and found poor correlations between the two tests (48). More recently, Savage et al. found strong relationships between repetitive lifting performance and 1RM performance, suggesting high muscular strength is an important component of successful military physical tasks (34). As stated earlier, smaller statured personnel might literally not be able to carry the load during loaded military tasks, despite being better performers on the traditional fitness test components (3). According to a June 17, 2013 New York Times article, women will be eligible for front line combat roles beginning in 2016 (37). SOLUTIONS TO BODY MASS BIAS Several solutions have been proposed to remove BMB from fitness testing. The use of weight classes may remove some of the BMB, as this would allow personnel to compete only against peers of similar body mass (40). However, there are a few issues with this, including that this concept has yet to be empirically tested in tactical athletes, it does not address the issue of load carriage and other absolute combat tasks (like an artillery shell move, fire and maneuver, etc.), some BMB would still exist, and personnel in the lowest and highest weight classes would have fewer personnel to compete against (40). The use of scaled scores is not practical in a field setting and may yield complicated numbers that are difficult to interpret (40,42). Correction factors might be easier to use than scaled scores even though they still require calculations. However, individuals who are not familiar with exercise science may not find correction factors an attractive alternative (40,42). One study found that wearing a 30-kg backpack during a twomile run eliminated BMB from the test, while simultaneously incorporating a load carriage component to the assessment (46). A subsequent study has demonstrated that wearing a 30-lb (~13.6- kg) backpack during a two-mile run and while performing pushups successfully removed BMB from both tests components (45). In addition, as noted by these authors, carrying a uniform external load mimics actual field conditions for many service members and is more occupationally relevant than conditions where bodyweight is the only resistance, (45). Crowder, Ferrera, and Levinbook recently proposed another solution to BMB (7). These authors compared performance on the Army Physical Fitness Test (APFT) with a novel test battery called the Military Optimal Performance Challenge (MOPC). The MOPC consists of a variety of components including a bench press, back squat, cadence pull-ups, three-mile run, simulated casualty evacuation test, and a mobility for battle drill (see Figure 1). The subjects were 20 male military personnel who performed the tests over a two-week period. The results indicated that the APFT suffered from significant BMB, whereas the MOPC was less impacted (7). Importantly, a negative relationship between lean body mass was found with the APFT, whereas lean body mass did not negatively affect MOPC scores (7). Interestingly, those subjects who performed best on the APFT (average score of 84.2%) did not perform nearly as well on the MOPC (average score of 52%). These authors concluded that the MOPC offers a robust approach to military readiness and is free of the confounding influence of body mass, (7). They further felt that the MOPC is a unique assessment requiring a multitude of abilities to garner success and may assist in training for functional combat performance skills demanding high work capacities (7). The concept that military fitness tests can be designed to remove BMB is reinforced by Vickers et al., who concluded that although individual components of the MCFT exhibited BMB, the cumulative score was not influenced by BMB (47). CONCLUSIONS AND PRACTICAL APPLICATIONS In summary, it appears as though traditional bodyweight supported fitness tests used by all the services impose a substantial BMB on heavier, but not necessarily fatter, participants. This BMB makes it more difficult for larger personnel to perform well on such tests. Since fitness test scores impact both promotion and retention, BMB may make it more difficult for such personnel to have successful military careers. Several solutions to removing BMB from fitness testing have been proposed. The most practical of these involve either keeping the traditional fitness tests, but utilizing an added load, or designing tests such as the MOPC, which minimize BMB while simultaneously testing for tactical NSCA S TSAC REPORT ISSUE 40 33

5 GUY LEAHY, MED, CSCS,*D abilities. Both strategies have empirical support and could represent significant improvements in helping determine which personnel are truly fit to fight. REFERENCES 1. Air Force Instruction , Fitness Program , October Retrieved 2015 from document/afd pdf. 2. Astrand, PO, Rodhal, K, Dal, HA, and Stromme, SB. Body dimensions and muscular exercise. In: Textbook of Work Physiology. (4th ed.) Champaign, IL: Human Kinetics; , Bilzon, JLJ, Allsopp, AJ, and Tipton, MJ. Assessment of physical fitness for occupations encompassing load-carriage tasks. Occupational Medicine 51(5): , Buresh, RJ, Berg, KE, and Noble, JM. Relationship between measures of body size and composition of velocity of lactate threshold. Journal of Strength and Conditional Research 18(3): , Chia, M, and Aziz, AR. Modelling maximal oxygen uptake in athletes: Allometric scaling versus ratio-scaling in relation to body mass. Annals of the Academy of Medicine Singapore 37(4): , Crowder, TA. Sex differences in Army mobility field test performance. Medicine and Science in Sports and Exercise 46: S545-S546, Crowder, TA, Ferrara, AL, and Levinbook, MD. Creation of a criterion-referenced military optimal performance challenge. Military Medicine 178: , Crowder, T, and Yunker, C. Scaling of push-up, sit-up and two-mile run performances by body weight and fat-free weight in young, fit men. Medicine and Science in Sports and Exercise 28: S183, Crecelius, AR, Vanderburgh, PM, and Laubach, LL. Contributions of body fat and effort in the 5K run: Age and body weight handicap. Journal of Strength Conditioning Research 22(5): , Crewther, BT, Kilduff, LP, Cook, CJ, Cunningham, DJ, Bunce, PJ, Bracken, RM, and Gaviglio, CM. Scaling strength and power for body mass differences in rugby union players. Journal of Sports Medicine and Physical Fitness 52 (1): 27-32, Cureton, KJ, Sparling, PB, Evans, BW, Johnson, SM, Kong, UD, and Purvis, JW. Effect of experimental alterations in excess weight on aerobic capacity and distance running performance. Medicine and Science in Sports and Exercise 10: , Dooman, CS, and Vanderburgh, PM. Allometric modeling of the bench press and squat: who is the strongest regardless of body mass? Journal of Strength Conditioning Research 14(1): Favret, K, Walker, J, Pankey, R, and Ransone, J. Influence of body mass and size on performance of the Air Force physical fitness test. Medicine and Science in Sports and Exercise 42: S79-80, Goran, M, Fields, DA, Hunter, GR, Herd, SL, and Weinsier, RL. Total body fat does not influence maximal aerobic capacity. International Journal of Obesity 24: , Harman, EA, and Frykman, PN. The relationship of body size and composition to the performance of physically demanding military tasks. In: Body Composition and Physical Performance, Washington DC: National Academy Press; , Hendrickson, NR, Sharp, MA, Knapik, JJ, and Marin, R. Body mass bias and allometric scaling in the Army physical fitness test among infantry soldiers. Medicine and Science in Sports and Exercise 41: S50, Heil, DP. Body mass scaling of peak oxygen uptake on 20- to 79-yr-old adults. Medicine and Science in Sports and Exercise 29: , Hoff, J, Kemi, OJ, Helgerud, J. Strength and endurance differences between elite and junior elite ice hockey players. The importance of allometric scaling. International Journal of Sports Medicine 26: , Jaric, S, Mirkov, D, and Markovic, G. Normalizing physical performance tests for body size: A proposal for standardization. Journal of Strength Conditioning Research 19(2): , Kobermann, AM, Mayhew, JL, Leahy, GD, and Crowder, TA. Relationship of body mass to Army physical fitness test performance in college ROTC cadets. Medicine and Science in Sports and Exercise 44: S , Kram, R, and Taylor, CR. Energetics of running: A new perspective. Nature 346: , Leahy, G, Crowder, T, and Mayhew, JL. Allometric scaling of fitness performance tests in Air National Guard men. Journal of Strength and Conditioning Research 27: S63-S64, Leahy, G, Crowder, T, and Mayhew, JL. Allometric scaling of fitness performance tests in Air National Guard women. Journal of Strength and Conditioning Research 27: S75-S76, Leahy, GD, Crowder, TA, and Mayhew, JL. Allometric scaling of Air Force fitness test performances in men. Medicine and Science in Sports and Exercise 44: S205, Leahy, GD. Body mass bias, allometric scaling and military fitness tests. TSAC Report 18: , NSCA S TSAC REPORT ISSUE 40

6 BODY MASS BIAS EFFECTS ON FITNESS TEST AND TACTICAL PERFORMANCE 26. Lyons, L, Allsopp, and Bilzon. J. Influences of body composition upon the relative metabolic and cardiovascular demands of load carriage. Occupational Medicine 55: , Marine Corps Order : Marine Corps Fitness Program. Department of the Navy. 1-64, Mayhew, J, Griffin, L, Godfresen, T, Koch, AJ, and Smith, AE. Allometric modeling of maximal bench press and squat strength in adolescent men and women. Medicine and Science in Sports and Exercise 42: S292-S293, Nevill, AM, Stewart, AD, Olds T, and Holder, B. Are adult physiques geometrically similar? The dangers of allometric scaling using body mass power laws. American Journal of Physical Anthropology 124: , Nevill, AM, Ramsbottom, R, and Williams, C. Scaling physiological measurements for individuals of different body size. European Journal of Applied Physiology and Occupational Physiology 65(2): , Nindl, BC, Castellani, JW, Warr, BJ, Sharp, MA, Henning, PC, Spiering, BA, and Scofield, DE. Physiological Employment Standards III: Physiological challenges and consequences encountered during international military deployments. European Journal of Applied Physiology 113: , Pallares, JG, Lopez-Gullon, JM, Torres-Bonete, MD, and Izquierdo, M. Physical fitness factors to predict female Olympic wrestling performance and sex differences. Journal of Strength Conditioning Research 26(3): , Roberts, TJ, Kram, R, Weyland, PG, and Taylor, CR. Energetics of bipedal running I: Metabolic cost of generating muscular force. Journal of Experimental Biology 201(19): , Savage, RJ, Best, SA, Carstairs, GL, Ham, DJ, and Doyle, TLA. On the relationship between discrete and repetitive lifting performance in military tasks. Journal of Strength Conditioning Research 28(3): , Schmidt-Nielsen, K. Scaling: Why is Animal Size so Important? New York, NY: Cambridge University Press; 241, Spiering, BA, Walker, LA, Hendrickson, NR, Simpson, K, Harman, EA, Allison, SC, and Sharp, MA. Reliability of military-relevant tests designed to assess soldier readiness for occupational and combat-related duties. Military Medicine 177(6): , Steinhauer, J. Elite units in U.S. military to admit women. The New York Times. June 17, Retrieved 2015 from nytimes.com/2013/06/18/us/elite-units-in-us-military-to-admitwomen.html. 38. Tartaruga, MP, Brisswalter, J, Mota, CB, Alberton CL, Gomenuka, A, and Peyre-Tartaruga, LA. Mechanical work and long-distance performance prediction: The influence of allometric scaling. Journal of Human Kinetics 38: 73-82, Thompson, BJ, Smith, DB, Jacobson, BH, Fiddler, RE, Warren, AJ, Long, BC, et al. The influence of ratio and allometric scaling procedures for normalizing upper body power output in division I collegiate football players. Journal of Strength Conditioning Research 24: , Vanderburgh, PM. Body mass bias in exercise physiology. In: Zaslav, K (Ed.), An International Perspective on Topics in Sports Medicine and Sports Injury. Rijeka, Croatia: In-Tech Publishers; , Vanderburgh, PM, Mickley, NS, Anloague, PA, and Lucius, K. Load-carriage distance run and push-ups tests: No body mass bias and occupationally relevant. Military Medicine 176: , Vanderburgh, PM. Occupational relevance and body mass bias in military physical fitness tests. Medicine and Science in Sports and Exercise 40: , Vanderburgh, PM, and Laubach, LL. Derivation of an age and weight handicap for the 5K run. Measurement in Physical Education and Exercise Science 11(1): 49-59, Vanderburgh, PM. Correction factors for body mass bias in military physical fitness tests. Military Medicine 172: , Vanderburgh, PM, and Crowder, TA. Body mass penalties in the physical fitness tests of the Army, Air Force, and Navy. Military Medicine 171: , Vanderburgh, PM, and Flanagan, S. The backpack run test: A model for a fair and occupationally relevant military fitness test. Military Medicine 165: , Vanderburgh, PM, and Mahar, MT. Scaling of 2-mile run times by body weight and fat-free weight in college-age men. Journal of Strength Cond Research 9(2): 67-70, Vickers, RR Jr, Reynolds, JH, and McGuire, BJ. Body mass bias in a combat fitness test. Naval Health Research Center. Report No , 1-44, Retrieved 2015 from fulltext/u2/a pdf. 49. Walker, LA, Spiering, BA, Simpson, K, Frykman, PN, Ward, RC, and Sharp, MA. Laboratory measures of physical fitness correlate with performance of military tasks in active duty soldiers. Medicine and Science in Sports and Exercise 44: S205, Weyland, PG, and Davis, JA. Running performance has a structural basis. Journal of Experimental Biology 208: , Weibel, ER, and Hoppeler, H. Exercise-induced maximal metabolic rate scales with muscle aerobic capacity. Journal of Experimental Biology 208: , Weibel, ER, Bacigalupe, LD, Schmitt, B, and Hoppeler, H. Allometric scaling of maximal metabolic rate in mammals: muscle aerobic capacity as determinate factor. Respiratory Physiology and Neurobiology 140(2): , NSCA S TSAC REPORT ISSUE 40 35

7 GUY LEAHY, MED, CSCS,*D ABOUT THE AUTHOR Guy Leahy is currently serving as an exercise physiologist in Tucson, AZ. Leahy is a member of the American College of Sports Medicine (ACSM) and National Strength and Conditioning Association (NSCA), and is a Certified Strength and Conditioning Specialist (CSCS ). Leahy is the author/co-author of over 30 professional articles, including original research, which has appeared in publications such as The Journal of Strength and Conditioning Research, TSAC Report, Medicine and Science in Sports and Exercise, Nature, Science, and Scientific American. Leahy holds a Master of Education degree from Western Washington University and a Bachelor of Science degree from the University of Oregon. Leahy can be reached at xrciseguy@gmail.com. TABLE 1. PHYSICAL FITNESS TEST COMPONENTS FOR U.S. ARMY, NAVY, AND AIR FORCE (3,42) MILITARY BRANCH UPPER BODY MUSCULAR STRENGTH/ENDURANCE TRUNK MUSCULAR STRENGTH/ENDURANCE AEROBIC CAPACITY Army 2-min push-ups 2-min sit-ups 2-mi run Navy 2-min push-ups 2-min curl-ups 1.5-mi run Air Force 1-min push-ups 1-min sit-ups 1.5-mi run FIGURE 1. MOBILITY FOR BATTLE DRILL IN MOPC 36 NSCA S TSAC REPORT ISSUE 40

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