Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Body Composition and Physical Performance 1992. Pp. 105-118. Washington, D.C. National Academy Press 7 l The Relationship of Body Size and Composition to the Performance of Physically Demanding Military Tasks Everett A. Harman and Peter N. Frykman INTRODUCTION The most common physically demanding tasks in the U.S. Army are lifting and carrying (including load carriage). Typical military lifting tasks include loading artillery shells, lifting supplies onto and removing them from trucks, moving construction components, and assembling or disassem- bling heavy equipment. Most lifts involve raising an object from the ground to between waist and shoulder height. Carrying is usually associated with lifting. A soldier is generally expected to lift objects weighing as much as 50 kg single-handedly, with heavier objects lifted by more than one individ- ual. Most of the objects lifted do not have handles. In heavy lifting jobs, 85- to 200-pound objects may be lifted and carried up to 200 yards by a single individual. Packs in excess of 100 pounds and other heavy loads may be lifted and carried for several miles (Myers et al., 1983; U.S. Army, 1978). Unfortunately, large numbers of recruits have left the military because of failure to cope with physically demanding military training and work. Some enlisted personnel have been unable to carry out their jobs or have become injured while lifting or carrying heavy equipment and supplies (Myers et al., 1983~. An important question one must ask is whether military screening tests are effective in excluding from service individuals likely to be either ineffective in performing their assigned tasks, or prone to injury due to physical weakness. 105
106 EVERETT A. HARMAN AND PETER N. FRYKMAN Aside from the standard physician's examination, the main physical screening tool for entry into the-U.S. Army is a table of maximal body weight-for-height (accession standard AR 40-501) (K. E. Friedl, U.S. Army Research Institute of Environmental Medicine, unpublished data). Exces- sive body weight-for-height is used to infer obesity. The Army physical fitness test, which is based on age-specific standards for push-ups, sit-ups and 2-mile run time is not an entry screening test and is not administered until after the start of basic training. A lifting test on a stack-type weight machine is administered to potential recruits to help advise them whether they might have difficulty performing physically demanding jobs, but it is never used to exclude anyone from a military occupational specialty. Associations Among Body Fat, Load Carriage Ability, and Running Performance A sound theoretical basis exists for believing that excess body fat (BF) is detrimental to performance. Adipose tissue mainly serves the purpose of energy storage. It is noncontractile and cannot assist in force generation. Yet it has mass and weight, which increases the force-generation require- ments of the muscles for support of body segments against gravity and to overcome inertia during acceleration (Boileau and Lohman, 19774. Accord- ing to Newton's second law, force equals mass times acceleration, so that acceleration equals force divided by mass (Meriam, 19781. Force = Mass x Acceleration Acceleration = Force / Mass (1) For an individual with a given amount of muscle tissue and force-genera- tion capability, fat deposits increase the mass and thus the weight and iner- tia of body segments. Table 7-1, based on calculations using equation 1, shows that for a given amount of force applied to an object, a 10 percent TABLE 7-1 Loss in Acceleration with Increase in Mass Given a Fixed Force Increase in Mass (%) 10 20 30 40 Decrease in Acceleration (%) 9 17 23 29
BODY SIZE/COMPOSITION AND MILITARY TASKS 107 increase in the object's mass reduces acceleration by 9 percent. A 20 percent increase in mass reduces acceleration by 17 percent, and so on. BF then reduces the rate at which the body can be accelerated, as when speed or direction are rapidly changed. For endurance activities, where rate of energy production is a limiting factor, fat weight is detrimental because the work performed in raising an object to a given height is proportional to its weight, and energy required is directly related to work performed. The body's center of mass is raised repeatedly during locomotion. From a simplified point of view the net power output during running equals body weight times the vertical center of mass travel per stride divided by the time per stride. Increasing either body weight or the vertical travel of the center of mass raises the power require- ment. Also, with all else being equal, a more rapid stride frequency- which results in a shorter stride time in which the work of raising the body is performed increases power output. Because sustainable maximal power output is limited by one's anaerobic threshold, when an individual's body is fatter, it cannot be raised and lowered as frequently as when it is leaner, unless it is raised a shorter distance per stride. All else being equal, the lowering of either stride frequency or vertical center of mass travel (and thereby stride length) reduces running speed. There is considerable evidence that fat weight can diminish running per- formance. Cureton et al. (1978) performed experiments in which they added weight to the trunks of runners to simulate the effects of fat weight. It was found that the added weight systematically and significantly decreased VO2max expressed relative to body weight (which included the added mass) but did not decrease absolute VO2 maX nor VO2 maX relative to lean body weight. The added weight decreased endurance time on a treadmill, the speed of which was increased every 2 minutes, and shortened maximal distance run in 12 minutes. Fifteen percent added weight decreased the speed of the 12- minute run by 8.6 percent. The experiment showed a negative effect on running performance attributable to excess weight alone, independent of any change in cardiovascular capacity. In a similar experiment, Cureton and Sparling (1980) placed weights on each male subject to simulate the percent BF of a paired women subject. The weighting reduced men-women differences by about one-third for both treadmill run time and 12-minute run distance, and by two-thirds for VO2max relative to total running weight. Based on significant correlations of percent BF with both time required to run a fixed distance and distance covered in a fixed amount of time, studies have shown that fatter individuals tend not to perform as well in unloaded running as do leaner individuals. Table 7-2 shows correlations) 1 Pearson product-moment correlations (Ferguson, 1976) were used throughout.
108 EVERETT A. HARMAN AND PETER N. FRYKMAN TABLE 7-2 Correlations of Percent Body Fat with Run Performance Male Female Study Runn* Gender rT r K. E. Friedl 2 miles1048 M -0.36 (U.S. Army Res. 846 F ~.12 Environ. Med., unpublished) M. Knapik 2 miles81 M -0.38 (U.S. Army Res. Environ. Med., unpublished) Mello et al. 2 miles44 M -0.60 (1984) 17 F ~.35 Harman et al. 2 miles32 M ~.46 (1988) Myers et al. 2 miles751 M ~.21 (1983) 450 F -0.19 Cureton et al. 12 minutes55 M ~.30 (1979) 55 F ~.22 Fitzgerald et 2 miles1001 M ~.47 al. (1986) 2 miles253 F -0.31 *n = number of subjects tr = Pearson product-moment correlation coefficient; negative r means fatter subjects ran slower. between percent fat and running performance for several reported studies. It can be seen that the relationship between percent BF and running perfor- mance is not strong. However, all of the studies showed some detrimental effect of percent BF on running performance. Women in the Army show a weaker relationship between percent BF and running performance than do men. One reason might be that the wom- en show less variation in percent BF, so that other factors such as cardio- vascular status, skeletal proportion, and motivation can exert greater influ ence. The relatively weak association between percent BF and 2-mile run time indicates that an individual's running ability cannot be well predicted by fatness. There are many fatter individuals who can run faster than leaner ones and many lean individuals who do not run as fast as expected. Despite the fact that the 2-mile run is part of the semiannual physical fitness test that soldiers must take, there is little evidence that unloaded running ability relates to military performance. Running more than a mile without a load is a task rarely demanded of a soldier. One might assume that a soldier who can run better without a load can run better with one as well. This may not be the case. In experiments in which the performances
BODY SIZEICOMPOSITION AND MILITARY TASKS 109 of both load carriage and unloaded distance running have been assessed, Knapik (U.S. Army Research Institute of Environmental Medicine, unpub- lished data) found a correlation of only 0.16 between the 2-mile run time and 20-km load carriage time, while Kraemer et al. (1987) found a 0.63 correlation between 2-mile run times with and without a load. One reason for the higher correlation among Kraemer's subjects was that both run and load carriage were conducted over the same distance and course. The 20- km distance is much more typical of military marches and normally in- volves considerably more walking than running. Why is the association between performances in load carriage and run- ning not stronger? The answer seems to be that it takes a different body type to carry loads well than to be a good runner. Table 7-3 shows the typical body build of competitive middle- to long-distance runners (McAr- dle et al., 19864. It can be seen that they are slight of build and lean. Elite runners are even more slightly built and linear than very good runners, as shown by Bale et al.'s (1985, 1986) measurements of both men and women distance athletes. Tanaka and Matsuura (1982) showed that simple anthro- pometric measures of linearity and leanness account for as much variance in running ability as do VO2max and cardiac output combined. Not only is the leaner individual favored in unloaded distance running, but so is the smaller individual who carries less muscle tissue. In their text on work physiology, Astrand and Rodahl (1986) extensively discussed the effects of body size on performance, that was based on an earlier exposition by Hill (1950~. They explained why larger people, even if lean, could not be expected to run distances as effectively as smaller people. Their argu- ment was based on the way the various body dimensions change as body size changes. Table 7-4 shows how some selected dimensions change with height if body proportions remain constant. Because areas are two- dimensional, they are related to the square of height. Volume is three- dimensional and thus related to height cubed. Flow rates are related to the square of height, while frequency and acceleration are inversely related to height. The derivations of these relationships are outside the scope of this paper. TABLE 7-3 Typical Body Measurements of Marathon and Middle Distance Runners Height 176 cm (5'9") Weight 63 kg (139 lbs) Percent fat 5 percent Lean body weight 60 kg (132 lbs)
0 EVERETT A. HARMAN AND PETER N. FRYKMAN TABLE 7-4 Various Dimensions as Functions of Height (H) Segment length Muscle cross-sectional area Body mass Skin surface area Flow rate Frequency Acceleration H H2 H3 H2 H2 1/H 1/H Assuming constant body proportions, oxygen requirement is related to body mass, which is in turn proportional to height cubed. Oxygen transport depends on cardiac output, which is a flow rate proportional to height squared. Thus as body size increases, oxygen requirement increases faster than does the ability to transport oxygen. It is for this reason that Astrand proposed measuring aerobic fitness in terms of ml x kg-2/3 x minute-i rather than the conventional ml x kg-i x minute-i, which favors the smaller body. Maxi- mal oxygen uptake in absolute terms increases with body weight but, ex- pressed relative to body mass, decreases with body weight. As a function of body mass raised to the two-thirds power, it remains constant over a wide range of body weights. It must be made clear however, that oxygen uptake expressed in the standard ml x kg- x minuted is closely related to distance running performance. Correlation of 0.91 for men and 0.89 for women between running performance and rate of oxygen uptake expressed relative to body mass enabled Mello et al. (1988a) to develop equations that effectively predict relative oxygen uptake from 2-mile run time. Thus, us- ing Astrand and Rodahl's (1986) recommended kg2/3 for equating aerobic fitness of people of different sizes might indicate one's fitness relative to similar-sized individuals. It doesn't however, alter the fact that smaller people are more likely to run faster over middle to long distances. Law (Burfoot, 1990) developed tables, based on 5,000 10-km perfor- mances and over 7,000 marathon performances from the 1987 Marine Corps Marathon, to compare both men and women of differing body weight. Ta- ble 7-5 shows the ninety-ninth, ninetieth, seventy-fifth and fiftieth percen- tile performance times for the mens' 10-km run. It can be seen that at each percentile, the larger runners were considerably slower. For example, the ninety-ninth percentile 10-km run time was almost 10 minutes slower for men over 195 pounds than for those under 155 pounds. Astrand and Rodahl's (1986) theory is supported in that the times in the table are close to those calculated if oxygen uptake in liters per minute increases with the two- thirds power of body mass, and running speed is proportional to oxygen uptake in ml x kg-i x minute-~.
BODY SIZEICOMPOSITION AND MILITARY TASKS TABLE 7-5 Times in Minutes for the 10-kilometer Run Referenced by Percentile and Body Weight Percentile Body Weight (lbs) <155 155-174 175-194 195+ Minutes: seconds 99 29:50 33:39 36:54 39:29 90 35:10 39:24 42:49 45:37 75 39:13 42:56 45:57 48:18 50 44:06 47:03 49:44 53:14 111 Load carriage ability is not well predicted by unloaded running, because although ~ slight body build is well adapted to unloaded running, it is not well adapted to load carriage, particularly as loads become heavy. Larger people tend to have greater lean body mass (LBM) which helps to support and move the load carried. Table 7-6 shows correlations of LBM with both height and body weight. It can be seen that, for both men and women, LBM is well related to total body weight, at least for a young, military population. Association of Lean Body Mass with Military Performance Table 7-7 shows correlations of load carriage performance with LBM and percent BE. It can be seen that fatness is associated with slower load carriage. Higher LBM is associated with faster load carriage. The correla TABLE 7-6 Correlations of Lean Body Mass with Height and Weight Study Height Weight l Men Women Men Women r Teves et al. 0.60 0.75 0.91 0.88 (1985) Harman et al. 0.68 0.85 (1988) Myers et al. 0.62 0.72 0.91 0.89 (1983) Fitzgerald et al. 0.63 0.69 0.79 0.76 (1986) r = Pearson product-moment correlation coefficient (see tables that follow).
2 EVERETT A. BARMAN AND PETER N. FRYKMAN TABLE 7-7 Correlations of Load Carriage Performance with Lean Body Mass and Percent Body Fat in Male Subjects Load LBM Study Distance (kg) r r Mello et al. 2 km 46 -0.54 0.00 (1988b) 4 km 46 -0.39 0.38 8 km 46 -0.45 0.48 12 km 46 -0.55 0.29 Knapik 20 km 46 -0.26 0.05 (U.S. Army Res. Inst. Environ. Med., unpublished) Dziados et al. ( 1 987) 10 miles 18 ~.30 0.15 Percent Fat * r = Pearson product-moment correlation coefficient; correlations mean: higher lean body mass ~ faster times; higher percent body fat ~ slower times. lions are stronger for LBM than for percent BF. It thus may be more important to screen potential recruits for LBM than for percent BF. Added evidence as to the importance of LBM for performance of mili- tary tasks is the positive relationship between LBM and lifting ability. Table 7-8 shows correlations of lifting performance with LBM and percent BF. It is clear that LBM is an important factor in lifting, much more so than percent BF. The low but positive correlations of percent BF with lifting ability suggest a weak trend for fatter people to lift more effectively, probably because individuals with more fat tend to have greater LBM. Table 7-9 shows the weak but positive association among men between LBM and fatness. However, the Myers et al. (1983) data suggest that the trend declines or even disappears with training, probably as the fatter men lose weight. Figure 7-1, from the work of K. E. Friedl (unpublished) shows that men above the BF standard lose body weight, while those below the BF standard gain body weight during basic training. Overall, men gain about 2.5 kg of LBM during basic training, while losing 1 to 2 percent fat. Wom- en also gain about 2.5 kg of LBM in basic training, but there is disagree- ment as to whether they gain or lose in percent body fat (K. E. Friedl, unpublished; Myers at al., 1983; Teves et al., 1985~. The weaker correlations for women than for men between lean body weight and lifting ability might be related to lack of experience among women with lifting, which results in greater variability in technique. It should also be noted that the correlations listed for the Myers et al. (1983)
BODY SIZEICOMPOSIT1ON AND MILITARY TASKS 113 TABLE 7-X Correlations of Lifting Performance with Lean Body Mass (LBM) and Percent Body Fat Men Women LBM Percent Fat LBM Percent Fat Study Lift Type r* r r r Teves et al. Maximal 0.45 0.06 0.26 0.10 (1985) Sharp et al. Repetitivet 0.68 0.25 (unpublished) Maximal 0.48 0.15 Myers et al. Maximal 0.64 0.26 0.45 -0.03 (1983) *r = Pearson product-moment correlation coefficient; positive correlations mean: higher lean body mass ~ better lifting; higher percent body fat ~ better lifting. "Maximal number of lifts with 90 pounds in 10 minutes. study are before basic training. Yet the correlations between LBM and lifting ability stayed quite constant through both basic training and ad- vanced individual training. The relationship between LBM and lifting abil- ity for women actually strengthened after training, probably due to practice with lifting, which lessened variability in technique. In contrast, correla- tions of lifting ability with percent BF dropped to about zero after basic training for both men and women, and remained there through advanced individual training. Thus, percent BE of the working soldier appears to be unrelated to lifting ability. In addition to being positively associated with load carriage and lifting, LBM is related to other military task performances. Table 7-10 shows that LBM tended to be positively associated with the ability to push, carry and TABLE 7-9 Correlations of Percent Body Fat with Lean Body Mass Study Men Women * r Teves et al. (1985) .42 .15 Myers et al. (1983) before basic training .36 .11 after basic training .1 1 .09 after AITt .09 .06 *r = Pearson product-moment correlation coefficient tAIT = advanced individual training
4 12 8 4 o -4 -8 -12 -16 L 111 1 11 -20- . 1 1 1 1 1 1 1 1 1 1 < 10 10-12 12-14 14-16 16-18 18-20 20-22 22-24 24-26 > 26 PERCENT BODY FAT AT EAD FIGURE 7-l Change in body weight of military men from entry to active duty (EAD) to the end of basic training (BT) and assignment to first unit. _ EAD TO END OF BT EVERETT A. HARMAN AND PETER N. FRYKMAN CHANGE IN WEIGHT (POUNDS) ~,11. . . . . . . . . . . . ~ EAD TO FIRST UNIT exert torque. As observed for lifting, lean body mass was a better indicator of performance ability than was percent BF. There was a weak trend for fatter people to push and exert torque better, probably because they could use their fat mass to generate momentum (Myers et al., 19831. Discussion and Conclusions Where does all this lead? Fat weight clearly impairs distance running ability, but distance running is rarely required of soldiers. The performan- ces of common physically demanding military tasks, including load car- riage, lifting, pushing, and exerting torque, are more closely related to LBM than to percent BF. There is even a weak trend for body fatness to improve performance in lifting, pushing, and torque exertion. The evidence presented suggests that minimum LBM standards may be more important to military performance than are maximum percentage BF standards. Perhaps recruits should be required to meet standards for both minimum LBM and maximum percent BF. Another alternative is to eliminate BF standards completely in favor of performance tests. Despite the consistent trend for LBM to be associated
BODY SlZElCOMPOSlTION AND MILITARY TASKS 115 with lifting and load carriage ability, the correlation coefficients are fair at best. Thus, depending on their stringency, body composition standards could exclude many potential recruits capable of effectively performing military jobs well and grant entry to many individuals physically incapable of satisfactorily performing their military jobs. In contrast to the Army, many police and fire departments only accept applicants who pass physically demanding performance tests that closely simulate job tasks. Advantages of this approach include · actual performance is tested, rather than performance by inference. · recruits who pass physically demanding performance tests might be less likely to be injured after enlistment, saving the Army medical and lost workforce costs. · attrition might be reduced because potential applicants not physically or psychologically prepared for the demands of military duty are less likely to be able to train themselves to pass physically demanding performance tests. · such testing would not necessarily lower the rate of recruit accep- tance. It might help to select applicants more suited to their jobs and less likely to prematurely leave the military. In addition, it does not appear that the existing Army physical fitness (PT) test would be effective for entry screening. Table 7-11 shows some of the minimal existing data relating physical fitness test scores to lifting and load carriage, the two most common physically demanding Army tasks. Of the three studies listed, the correlations from Myers et al. (1983) are based on the largest number of subjects and indicate only a weak positive associa- tion between number of push-ups and maximal lifting ability. The correla TABLE 7-10 Correlations of Performance with Percent Body Fat and Lean Body Mass (LBM) after Advanced Individual Training Percent Fat Lean Body Mass Task Men Women Men Women r Weight pushed .20 .17 .52 .37 Torque .18 .14 .35 .30 Push work .09 .10 .23 .26 Carry work -.03 .17 .27 .02 r = correlation coefficient; positive correlations mean: higher percent body fat ~ better performance; higher lean body mass ~ better performance.
6 EVERETT A. HARMAN AND PETER N. FRYKMAN TABLE 7-11 Correlations of Army Physical Fitness Test (PT) Scores with Lifting and Load Carriage Performance Lifting Load Carriage Study Men Women Men Women r J. Knapik (U.S. Army Res. Inst. Med., unpublished) (n = 89 males) push-ups sit-ups 2-mile run Myers et al. (1983) (n = 751 males, 450 females) push-ups sit-ups 2-mile run Harman et al. (1988) (n = 32 males) 2-mile run . * _ 0.09 0.19 0.16 0.24 0.06 -0.06 -0.37 0.32 0.24 -0.14 *r = correlation coefficient; positive correlations mean: better PT score ~ better lifting or load carriage lions of 2-mile run performance with lifting show no association in the Myers et al. (1983) data and weak association in the Harman et al. (1988) report, where the negative correlation indicates some tendency for the better runners to lift less effectively. This is not surprising given the ten- dency for greater LBM to be detrimental to running ability but salutary to lifting ability. The J. Knapik data (unpublished) also show little relation- ship between the physical fitness test scores and load carriage ability. There are obvious reasons, in addition to the differences between load- ed and unloaded running abilities already discussed, why the PT tests do not effectively predict military task performance. The first relates to As- trand and Rodahl's (1986) discussion of body size. Assuming constant body shape, body weight increases with the cube of height, while strength, which reflects muscle cross sectional area (Ikai and Fukanaga, 1968; Ryushi and Fukanaga, 1986), is proportional to the square of height. Because muscle strength does not keep pace with increasing body mass, larger individuals are at a disadvantage in manipulating their own bodies. Thus, smaller people can more easily perform push-ups and sit-ups but cannot lift as much be- cause the greater absolute strength of larger muscles can be effectively applied to the manipulation of objects external to the body, as in lifting. An additional reason why push-up, sit-up, and 2-mile run scores are not strongly associated with military task performance relates to the concept of
BODY SIZEICOMPOSITION AND MILITARY TASKS 117 strength specificity, which holds that the more dissimilar two exercises are, the less their performances can be expected to be associated. The move- ments involved in push-ups and sit-ups are quite dissimilar to those in- volved in lifting and load carriage. The development of new physical fit- ness tests more specifically related to military tasks would require careful analysis and experimentation. There are many different jobs in the U.S. Army, yet all soldiers must meet the same age- and gender-specific standards for BE and physical fit- ness. Because the Army is already dealing with great diversity and com- plexity in other areas, perhaps it can also deal with a limited number of different physical standards for different jobs. Tough standards could be applied to combat units and physically demanding occupational specialties. More lenient standards for non-physically demanding jobs could help avoid excluding fatter or weaker individuals who might have skills and abilities of potential benefit to the Army. The U.S. Army should clearly define its reasons for having body com- position standards. This report has shown that the existing standards are not well related to military task performance. If performance is the main reason for having standards, then new standards should be developed. If appearance is an important consideration, then psychological studies should be undertaken to determine how the appearance of fatness affects military morale and interpersonal relations. If health is the critical factor, then epidemiologic studies should be given priority. Identification of the prob- lem is the most important step in finding its solution. REFERENCES Astrand, P. and K. Rodahl. 1986. Pp. 391-410 in Textbook of Work Physiology, 3rd ed. New York: McGraw-Hill. Bale, P., S. Rowell, and E. Colley. 1985. Anthropometric and training characteristics of female marathon runners as determinants of distance running performance. J. Sports Sci. 3(2):115-126. Bale, P., D. Bradbury, and E. Colley. 1986. Anthropometric and training variables related to 10 km running performance. Br. J. Sports Med. 20(4):170-173. Boileau, R. A., and T. G. Lohman. 1977. The measurement of human physique and its effect on physical performance. Orthop. Clin. North Am. 8(3):563-581. Burfoot, A. 1990. The big leagues. Runner's World 25(2):66-68. Cureton, K. J., and P. B. Sparling. 1980. Distance running performance and metabolic respons- es to running in men and women with excess weight experimentally equated. Med. Sci. Sport Exerc. 12(4):288-294. Cureton, K. J., P. B. Sparling, B. W. Evans, S. M. Johnson, U. D. Kong, and J. W. Purvis. 1978. Effect of experimental alterations in excess weight on aerobic capacity and distance running performance. Med. and Sci. Sports 10(3):194-199. Cureton, K. J., L. D. Hensley, and A. Tiburzi. 1979. Body fatness and performance dif- ferences between men and women. Res. Q. 50(3):333-340. Dziados, J., A. Damokosh, R. Mello, J. Vogel, and K. Farmer. 1987. The physiological deter
118 EVERETT A. HARMAN AND PETER N. FRYKMAN minants of load carriage. Technical Report T19-87. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. Ferguson, G. A. 1976. Statistical Analysis in Psychology and Education. New York: McGraw- Hill. Fitzgerald, P. I., J. A. Vogel, W. L. Daniels, J. E. Dziados, M. A. Teves, R. P. Mello, and P. J. Reich. 1986. The body composition project: A summary report and descriptive data. Technical Report T5-87. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. Friedl, K. E., J. A. Vogel, M. W. Bovee, and B. H. Jones. 1989. Assessment of body weight standards in male and female army recruits. Technical Report T15-90. U.S. Army Re- search Institute of Environmental Medicine, Natick, Mass. Harman, E., M. Sharp, R. Manikowski, P. Frykman, and R. Rosenstein. 1988. Analysis of a muscle strength data base (abstract). J. Appl. Sports Sci. Res. 2(3):54. Hill, A. V. 1950. The dimensions of animals and their muscular dynamics. Proc. Royal Inst., Great Britain, 34:450. Ikai, M. and T. Fukanaga. 1968. Calculation of muscle strength per unit cross-sectional area of human muscle by means of ultrasonic measurement. Int. Z. angew. Physiol. einschl. Arbeitphysiol. 26:26-32. Knapik, J., J. Staab, M. Bahrke, J. O'Conner, M. Sharp, P. Frykman, R. Mello, K. Reynolds, and J. Vogel. 1990. Relationship of soldier load carriage to physiological factors, military experience and mood states. Technical Report T17-90. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. Kraemer, W. J., J. A. Vogel, J. F. Patton, J. E. Dziados, and K. L. Reynolds. 1987. The effects of various physical training programs on short duration, high intensity load bearing performance and the Army physical fitness test. Technical Report T30-87. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. McArdle, W. D., F. I. Katch, and V. L. Katch. 1986. p. 516 in Exercise Physiology: Energy, Nutrition, and Human Performance, 2nd ed. Philadelphia: Lea and Febiger. Mello, R. P., M. M. Murphy, and J. A. Vogel. 1984. Relationship between the Army two mile run test and maximal oxygen uptake. Technical Report T3-85. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. Mello, R. P., M. M. Murphy, and J. A. Vogel. 1988a. Relationship between a two mile run for time and maximal oxygen uptake. J. Appl. Sport Sci. Res. 2(1):9-12. Mello, R. P., A. I. Damokosh, K. L. Reynolds, C. E. Witt, and J. A. Vogel. 1988b. The physiological determinants of load bearing performance at different march distances. Technical Report T15-88. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. Meriam, J. L. 1978. p. 6 in Engineering Mechanics: Dynamics. New York: John Wiley & Sons. Myers, D. C., D. L. Gebhardt, C. E. Crump, and E. A. Fleishman. 1983. Validation of the military enlistment physical strength capacity test. Technical Report 610. U.S. Army Research Institute for the Behavioral Sciences, Natick, Mass. Ryushi, T., and T. Fukanaga. 1986. Influence of muscle fiber composition and muscle cross-sectional area on maximal isometric strength. Tairyoku Kagaku 35:168-174. Tanaka, K., and Y. Matsuura. 1982. A multivariate analysis of the role of certain anthropo- metric and physiological attributes in distance running. Ann. Hum. Biol. 9(5):473-482. Teves, M. A., J. E. Wright, and J. A. Vogel. 1985. Performance on selected candidate screen- ing test procedures before and after Army basic and advanced individual training. Technical Report T13-85. U.S. Army Research Institute of Environmental Medicine, Natick, Mass. .. U.S. Army. 1978. U.S. Army Infantry School Physical Task List. Fort Benning, Ga.
