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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability 4 Military Application of Body Composition Assessment Technologies Karl E. Friedl1 Excess fat is viewed as the prime factor governing the level of specific gravity. Precise measurements, however, of this excess fat will necessarily await a knowledge of the relative percentage variation of the weight of the skeleton in lean persons. Technical limitations of using body density for estimation of body fat, noted in the U.S. Navy study that established the method of underwater weighing ("The specific gravity of healthy men: Body weight divided by volume as an index of obesity," Behnke et al., 1942) Military operational medicine research focuses on sustainment of the warfighter. Body composition is a critical aspect of this research, reflecting energy stores and other aspects of nutritional status, hydrational status, muscular strength potential, and risk for musculoskeletal injury. Changes in body fat indicate shifts in energy balance, and changes in lean mass suggest adaptive or mal- 1 Karl E. Friedl, Army Operational Medicine Research Program, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702-5012
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability adaptive responses to environmental stressors. Some of these maladaptive changes in body composition are mediated through endocrine stress responses also associated with increased susceptibility to traumatic stress and reduced immunocompetence. Service members may be pregnant women concerned about trade-offs between appropriate weight gain for the health of their newborns and a prompt return-to-duty status following delivery. Adolescent recruits are still physically immature and have not yet reached peak bone mineral accretion or peak muscle mass, yet these youngest soldiers are exposed to some of the Army's most physically demanding training. Overweight individuals need scientifically based guidance in their attempts to comply with military fat standards through sensible fat weight reduction, enhancing (instead of inadvertently impairing) physical readiness. An understanding of physiological mechanisms to maximize fat oxidation and to increase nitrogen and calcium recycling can lead to interventions to minimize muscle and bone loss in special operations. For example, long-range surveillance teams may be in a detraining state, with loss of Type II muscle fibers as a result of remaining virtually motionless for prolonged periods of time in forward positions. At the opposite extreme, direct action missions may require intense sustained performance without recovery from a catabolic state for several days. Thus, body composition technologies are important to enhance military readiness. Research on body composition and metabolism helps the military to develop appropriate standards for selection and fitness; to assess military training programs; and to assess the risks and benefits of optimizing strategies, including exercise, pharmacological, and nutritional interventions. This chapter will review the current body fat standards utilized by the military. It also will cover expedient methods that have been developed to categorize soldiers as overfat or within standards; improved criterion methods (including multicompartment models and dual-energy x-ray absorptiometry [DEXA or DXA]) to revalidate the expedient methods and to determine validity in weight loss settings with and without hydrational changes; and regional aspects of fat, muscle, and bone mineral distribution that identify physical and metabolic risks and advantages more precisely. ARMY BODY COMPOSITION STANDARDS: GOALS AND METHODS Army body composition standards are intended to enhance combat readiness (Friedl, 1992). Except for exclusion of grossly obese individuals, body composition standards are not designed to select for physical capabilities; instead, the standards promote fitness and prevent the development of obesity. Due to the absence of obese soldiers, studies of the relationship between adiposity and physical performance in Army studies demonstrate only weak to nonex-
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability istent relationships (i.e., within this restricted range of adiposity) (Vogel and Friedl, 1992a). Body fat standards also directly support a secondary objective of military appearance (Hodgdon et al., 1990). The Army fat standards are derived from the average fatness of physically fit young men and women, averaging 15 and 25 percent, respectively (U.S. Department of Defense, 1981). These represent mean body fat levels corresponding to an average maximal aerobic capacity of approximately 50 and 39 ml/kg/min for military men and women, respectively. The upper limit of allowable body fat has an additional allowance for a normal distribution around the average and to allow for error in assessment methods; thus, young men and women are allowed up to 20 and 30 percent body fat, respectively. These levels of fatness correspond to break points where mean aerobic fitness declines to less than average fitness (Vogel and Friedl, 1992a), and military appearance for most individuals declines from ''good" to "fair" (Friedl and Vogel, 1989). Line commanders and selection boards have been consistent in their complaints that the body fat standards are too lax, because many soldiers still look too fat. This is at least partly a problem of enforcement of the existing standards by some commanders (Friedl et al., 1987). Above their body fat limit, soldiers must lose weight in a sensible weight loss program, or face elimination from the Army. Although it is referred to as the Army Weight Control Program, only recently has the regulation (AR 600-9, 1986) been modified to provide more positive assistance to soldiers exceeding the standards and to discourage inappropriate weight loss habits. Very little Army research has been performed in this area of weight loss and maintenance. One difficulty for Army researchers has been recruiting and retaining as experimental subjects individuals whose careers are at risk; most overweight soldiers wish to evade special attention. This research may become more important as the prevalence of obesity in the U.S. population continues to increase. It is important to reiterate that there are gender-appropriate differences in body fat distribution and proportion because these differences still are not universally accepted by military policymakers. In recent Congressional testimony, one of the military services was quoted as claiming that "the higher percentage body fat in American women [is] not physiological, but because they are less fitness conscious. In short, American women are fatter than men and must be held to a higher standard until they get their act together" (U.S. Congress, House, 1992, 117). A ludicrous reversal of this concept, but one favoring women, would be to hold all service members, including men, to a narrow waist circumference standard based on the average for young women. Even in the twelfth century, a gender difference in body fat content was sufficiently well recognized that there was a policy in England that no woman would be put to the ordeal of cold water submersion; women were not likely to pass the test by sinking (they were given the test of the hot iron instead) (Kerr et al., 1992). Qualitative differences in body fat due to gender-specific distributions also make direct quantitative comparisons inappropriate; there can be no direct link-
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability age between male and female fat standards. The Army fat standards allow a constant difference of 10 percent body fat between men and women in each age category only by arbitrary design; this does not translate into a 10 percent physiological equivalency across the range of adiposity. For example, at the extreme low end of body fat, men and women can both achieve 4 to 6 percent body fat (Friedl et al., 1994a; Garg et al., 1992; Mazess et al., 1990a). At the higher end, a male with 30 percent body fat is not equivalent to a female with 40 percent body fat, because the male fat is primarily intraabdominal, with still greater health risks to the male than that to the female, whose fat is distributed to sites with other physiological roles (Lemieux et al., 1993). The standards accommodate apparent but still poorly defined, age-related increases in relative fatness (Table 4-1). The upper end of this sliding scale is anchored by a health-related rather than an aerobic fitness relationship. Health-risk thresholds occur at higher fatness than do reductions in aerobic fitness. Male and female soldiers over age 40 are held to an upper limit of 26 and 36 percent body fat. These body fat levels approximate the body mass index (BMI) defined by the Surgeon General as obesity, the threshold of increased health risks including cardiovascular disease, insulin resistance, and gall bladder disease (DHHS, 1988). The fat standards for the military have been related to the male and female obesity definition using regression equations from a large sample of Army basic trainees, with body fat determined by the Army circumference equations (Friedl et al., 1989). TABLE 4-1 Body Composition Standards* Age (years) Male Female BMI (kg/m2) Body Fat (%) BMI (kg/m2) Body Fat (%) < 21 25.9 20 23.5 30 21-27 26.5 22 24.3 32 28-39 27.2 24 25.0 34 = 40 27.6 26 25.5 36 NOTE: Body mass index (BMI) and equations in this table are the basis for the height-weight tables and body fat computation tables in AR 600-9 (1986) and updated female weight tables in the pending revision *Soldiers exceeding the screening weight threshold (based on BMI) are then assessed for percentage body fat (%BF) using the Army circumference equations. Males: %BF = 43.74 -(68.68 · LOG(HT)) + (76.46 · LOG(ABDOMINAL CIRC-NECK CIRC)). Females: %BF = (105.3 · LOG(WT))-(0.200 · WRIST CIRC)-(0.533 · NECK CIRC)-(1.574 · FOREARM CIRC) + (0.173 · HIP CIRC)-(0.515 · HT) -35.6. Height (HT) is measured in cm; weight (WT) in kg; circumference (CIRC) in cm.
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability Maturational changes in body composition are still poorly understood, although there are suspected relationships to changes in anabolic hormones that occur with age, parity, menopause, and other aspects of the life cycle. In addition to physiologically regulated changes, there are increases in fatness and declines in muscle mass that reflect increasingly sedentary behavior as careers progress and many soldiers become more "desk bound." Superimposed on physiology and physical activity are the cumulative effects of long-standing health and nutrition habits, including smoking and excessive alcohol consumption (Björntorp, 1990). The only age stratification in the Army regulation (AR 600-9, 1986) that has firm data support is a steady increase in weight (not necessarily fat weight) of young males up to age 21; this is observed irrespective of modern nutritional advantages and lifestyle, in data from Civil War soldiers as well as in data from soldiers nearly a century later (Gould, 1869; Karpinos, 1961). In the Biometric Survey of Army Officers, Reed and Love (1932) analyzed annual physical and medical records of 5,000 officers across a 29-y span. They concluded that there was a physiological increase in body weight and chest measurements that occurred between the late twenties and the forties; however, they also classified approximately 10 percent of the group as remaining at stable low weight over 25 to 30 years. New longitudinal studies of career male and female soldiers held to the current body composition standards using state-of-the-art body composition technologies would be valuable in determining the influence of military lifestyle and fitness on changes typically attributed to normal maturation. All soldiers are assessed for compliance with body composition standards every 6 months throughout their careers. These standards are applied using weight-for-height screens (based on BMI). The weight screen is designed to identify soldiers who may be overfat and should be further assessed using the body fat equations. Adiposity and BMI are only roughly related (r = ~ 0.7 in most military samples) (Friedl and Vogel, 1997; Vogel et al., 1990), and the relationship is particularly susceptible to influences of physical activity, gender, and age. The weight screen is an important step in the assessment. It is not practical to perform body fat assessments on all soldiers every 6 months, nor is it desirable to apply the less precise body fat estimation directly when the weight screen can provide a first-tier assessment to the majority of the force (Table 4-1). The principal change in the administration of the weight control program in this decade has been the addition of an objective second-tier assessment, the measurement of relative body fat, which is an important improvement over the previous reliance on weight tables alone (or a subjective final decision by a physician). This is intended to protect some of the best performers, soldiers who are large but not fat (i.e., those men and women most suited to many military tasks requiring high physical work capacity). As an example of how the weight screen is used, Figure 4-1 shows the distribution of fatness of young male recruits (ages 21–27) divided by results of the
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability FIGURE 4-1 Distribution of soldiers by fatness predicted by the male Army equation, divided by those men within and exceeding the weight screen. Data are shown for 251 men aged 21 to 27. The screening weight thresholds for this age group are based on a body mass index (BMI) of 26.5 kg/m2, and the upper limit of allowable body fat is 22 percent. AR 600-9, Army Regulation 600-9 (1986). SOURCE: Plotted data from the 1988 Accession Body Weight Standards Study (Friedl et al., 1989). weight screen for this age group. These soldiers are held to an upper limit of 22 percent body fat after they leave basic training. Two overlapping distributions of fatness, one for men who are below the weight screen and one for large soldiers who exceed it, illustrate that adiposity and BMI are only roughly related. It also illustrates how the BMI cutoff points have been set for the screening tables. Few overfat soldiers are misclassified as within standards by the weight screen; approximately half of those exceeding the weight screen are determined to be overfat, with the remainder of "overweight" soldiers classified as within fat standards. After more than a decade of enforcing weight control standards in the Army, some military posts with only a small influx of new recruits report that most soldiers exceeding weight standards are within fat standards (Personal communication, S. Newcomb, Office of the Deputy Chief of Staff for Personnel, Washington, D.C., 1995), instead of the 50 percent split in new recruits (Friedl et al., 1989). These reports from the field suggest that the Army weight control program has been effective in eliminating obesity from the Army. There are no data to indicate whether this is reflective of early discharge, prematurely ending careers of soldiers who do not comply with the standards, or if many soldiers are successfully modifying habits and better regulating body weight through their careers. Shortly after the major revision of the Army Weight Control Program (1983–1984), the individual progress of 174 overfat soldiers was quietly surveyed, and it was found that more than one-third did not make weight loss prog-
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability ress within 6 months in the program and that nearly half of these soldiers were lost from record or left the service. Of those soldiers who were initially successful in achieving their weight goals, 13 percent were formally returned to the program within another 6 months (Friedl et al., 1987). Although soldiers operating under these standards are more conscious of nutrition and fitness behaviors than ever before, there are no data on actual nutrition habits and whether these standards are any different from those of the general U.S. population. The current method of body fat estimation is part of the Army regulation (AR 600-9, 1986) and cannot be substituted with any other method. This is a practical consideration that prevents soldiers from shopping around for the most favorable body fat measurement. By having only one approved method of measurement for the Army regulation, the regulation is enforceable and equitable; however, because of the potential impact to an individual's career, there are several requirements that must be satisfied with careful validation. The first critical requirement is the accurate classification of soldiers and the absence of gross errors for any individual. (This is different from a research application, where a method needs to be quantitatively accurate across a range of adiposity; if the equations tend to overestimate at low body fat and underestimate at the high end, as most anthropometric equations do, they may still be fully adequate in classifying soldiers as fat and/or within standards.) The second requirement is that the classification must not inadvertently contradict the goals of the regulation, such as with body fat equations that penalize soldiers with the greatest strength fitness, or with overly stringent standards (i.e., based on the measurement of fat sites that are not readily modifiable) requiring physiologically inappropriate energy restriction that impairs readiness. The adequacy of the current Army body fat equations in satisfying these requirements is considered in the next two sections. VALIDATION OF MILITARY EQUATIONS AGAINST CRITERION METHODS Shortcomings of Underwater Weighing Although all of the current military body fat equations were developed against relative body fat as determined by underwater weighing, the equations utilized by each service produce different results. A part of this difference is related to differences in the techniques used in underwater weighing, and another part of the variation is explained by fundamental shortcomings in this two-compartment model of body composition and by the manner in which the characteristics of the different military study sample behaved, or were interpreted, within the assumptions of this method. Thus, the technique of underwater weighing is not well standardized, and deviations from the assumptions of the two-compartment model can produce sizable errors. In addition, there are practical problems that affect reproducibility. Central to this problem of reproduci-
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability bility is a subject's performance of the underwater breathing maneuvers. This is a big problem for Army sampling since half of the Army cannot swim, and many potential research subjects will not be comfortable with full submersion and underwater exhalation (Fitzgerald et al., 1986). The effects of variations in methodology and calculations are not trivial. A survey of four journals covering a 5-y period, revealed a diversity of techniques used in underwater weighing (Table 4-2). In the face of this variety, it is discouraging to note from this tabulation that nearly a quarter of research articles, including some where body composition is central to the study, provide little information about how the underwater weighing was performed and no reference to a published method. The most commonly provided information is the method of residual volume measurement (Table 4-2), and the reported variations in the methodology used introduce large differences to the measurement of body density. Fixed values and estimates based on vital capacity simply do not provide accurate density measurements (Morrow et al., 1986; Withers and Ball, 1988) but are found in the literature. The expedient oxygen dilution method developed by Wilmore et al. (1980) is the most frequently cited, perhaps because of the wide availability of oxygen monitors associated with exercise labs, whereas helium dilution and nitrogen washout devices are more likely to be found in clinical research labs. In a comparison of the three techniques, Forsyth et al. (1988) reported that helium equilibrium produced higher values than nitrogen washout or oxygen dilution. The mean difference between the helium and oxygen methods was 360 ml, producing calculated differences of greater than 2 percent body fat. If a body plethysmograph is available, total thoracic gas volumes can be measured. This becomes important in smokers and others who may have obstructive disease, (which would otherwise result in an underestimate of body density). However, this still does not account for gastrointestinal gas (which could be measured by plethysmography using an intragastric balloon). It is most common to ignore gastrointestinal gas or to ask subjects to report to the lab for testing after an overnight fast and/or after a walk; whether or not this reduces variability is only assumed (Durnin and Satwanti, 1982). Less commonly, fixed volumes of 100 ml are subtracted along with residual volumes in the calculation of body density, an average volume measured by Bedell et al. (1956). However, in Bedell's study (1956), some normal individuals had measured volumes as high as 500 ml, and earlier studies suggested mean volumes as high as 1 liter (Blair et al., 1947). The difference between 0 and 500 ml of additional abdominal gas volume results in errors of 2 percent body fat or more. Replication of the conditions for measurement of residual volume and exhalation under water is particularly challenging. Experienced swimmers tend to hold back air under water, and nonswimmers are inconsistent in their underwater performance, compared to maximal exhalation out of the water. To avoid these problems, some studies include measurement of the residual volume si-
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability TABLE 4-2 Variations of Underwater Weighing Methodology Reported in 150 Peer-Reviewed Journal Articles over a 5-y Span* Approach/Technique Number of Studies Subject preparation Fasted 16 Not reported 134 Position for underwater weighing Sitting 14 Prone or kneeling 2 Not specified 134 Trials and selection Average of highest 2–3 of 10 trials 31 Average of all of 6–10 trials 7 Average of last 3 after 6–10 trials 7 Other method of selection 4 Not specified 101 Residual volume—timing of the measurement Underwater 16 In water, head out 1 Separate from underwater weighing† 88 Residual volume—method Oxygen dilution 63 Helium equilibration 25 Nitrogen washout 16 Estimated from vital capacity 6 Fixed value 1 Whole body plethysmography 1 Not specified 38 Method cited Brozék et al., 1963 20 Behnke and Wilmore, 1974 11 Siri, 1961 11 Akers and Buskirk, 1969 8 Katch et al., 1967 7 Goldman and Buskirk, 1961 7 Other specified 42 * Four journals were examined: American Journal of Clinical Nutrition, International Journal of Obesity, Journal of Applied Physiology, and Medicine and Science in Sports and Exercise; 192 articles reported results based on underwater weighing; 42 of these gave no description of (or reference to) methodology used. † Specified or assumed.
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability multaneously with the underwater weight, but corrections for the attached hoses may introduce other inconsistencies. Another technical variation, the use of a snorkel for subjects uncomfortable with underwater exhalation (used in the 1984 Army Body Composition Study [Vogel et al., 1988]), has been empirically determined to add approximately 1 percent body fat to final estimations (Siconolfi et al., 1987). Some investigators claim that a prone position in the water allows subjects to produce a better maximal exhalation, and this may be accompanied by measurement of residual volume outside of the tank in the prone position. There is little consistency in how trials are selected and averaged. The most common approach is to perform two to three residual volume measurements and average the most consistent efforts. Repeated underwater weighing trials (10 trials are common) are usually performed, with an average taken of the highest two or three weights within some level of reproducibility (e.g., within 50 g of each other). However, an average of all of a smaller number of trials is also used. Since the first several trials tend to produce lower weights than subsequent trials (Katch et al., 1967), this approach will tend to give higher body fat estimations than a selection of highest or later trials. The two most commonly used equations for estimating percentage body fat from density, the equations of Siri (1961) and of Brozék et al. (1963), produce different values, with 2 percent body fat difference at the higher end of adiposity ( ~40% body fat). Thus, it is apparent that a wide range of percentage body fat values could be obtained for any one individual across different laboratories simply because of differences in technique. Errors Produced by Assumptions in the Interpretation of Body Density Even within the same laboratory, errors in the way individuals are assessed by underwater weighing can be sizable because of the assumptions of the two-compartment models that are used to interpret density. Small relative changes in body water can have a large effect because it is by far the largest single constituent of human body composition; "bags-of-mostly-water" was the descriptive name for humans used by a Star Trek silica-based lifeform. Bone mineral content also has a prominent effect on variability of the fat-free mass (FFM) because of its high density compared to other constituents. Thus, these two components, which are lumped into the FFM, introduce variations to the assumed density of 1.100 g/cm3. Lesser contributors to variation in FFM, such as glycogen stores and nonosseous minerals, may also be important in military environmental stress studies. Although 73.2 percent is a commonly used value for the assumed hydration of the FFM, this value represents an average from six experiments with nonhuman mammalian species where the species averages ranged between 69.9 and 74.5 percent (Pace and Rathbun, 1945, 689). Physiological variations outside of this range in humans, such as those that have been encountered in semistarved
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability Ranger students (Friedl et al., 1994a), make this a risky assumption in military field studies. In some military settings, changes in body water may not have a very marked effect. For example, a modest dehydration of 3 percent of body weight in a typical 70 kg, 15 percent body fat male soldier can be calculated to produce a relatively small underprediction of fatness (14.3% body fat) by underwater weighing. However, larger variations in body water may occur physiologically. In young women with complaints of water retention, Bunt et al. (1989) measured mean fluctuations in total body water of 1.5 liters over the course of single menstrual cycles. Mean body densities were 1.0434 and 1.0374 g/cm3 at low and high weights through the menstrual cycle, corresponding to body fat estimations of 24.4 and 27.2 percent, respectively. With adjustments for actual body water measures, the true body fat was estimated to be 25.6 percent. In studies of Ranger students with high rates of weight loss, an excess hydration of FFM has been observed, where decreases in fat and body cell mass were not accompanied by a concomitant reduction in total body water (Friedl et al., 1994a). Keys et al. (1950) observed this hydrational derangement in the semistarved men of the Minnesota Starvation Study and attempted corrections to the body fat estimates obtained from body density measured by underwater weighing. They found that corrections for the disproportionately high thiocyanate space (a measure of extracellular water) were approximately canceled by the increased contribution to density of the estimated bone mineral content (which was assumed not to have changed markedly within the period of the study, even as body cell mass diminished). However, whole body densities of greater than 1.100 g/cm3 were still obtained for a few individuals. Errors from variations in the fractional bone mineral contributions to the density of FFM have presented problems in several settings. Estimates of skeletal weights and bone mineral content differences suggest that the average bone mineral content is 20 percent greater in black compared with white subjects. Thus, it is not surprising that in the 1984 Army Body Composition Study, of the lean young men who had whole body densities of greater than 1.100 g/ml (i.e., for which a meaningful percentage body fat could not be calculated), five were black and one was Hispanic (Friedl and Vogel, 1992). Osteopenic subjects (subjects with low bone density), particularly young amenorrheic white women, deviate from a reference man in the opposite direction. The effects of bone mineral differences can be demonstrated by measurements on two women at opposite extremes of total-body bone mineral densities, measured in a study by Cote and Adams (1993). These two young women were assessed with total-body bone mineral densities of 1.060 and 1.392 g/cm2 (for reference, normal young female soldiers average ~1.15 g/cm2); body fat by underwater weighing (and the Siri  equation) was estimated at 21.4 and 16.7 percent, respectively. However, more accurate body fat estimates using measurements of bone mineral and body water in a four-compartment model, yielded values of 18.7 and 20.7 percent, respectively (Cote and Adams, 1993). In other
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability Despres, J-P., D. Prud'homme, M-C. Pouliot, A. Tremblay, and C. Bouchard 1991 Estimation of deep abdominal adipose-tissue accumulation from simple anthropometric measurements in men. Am. J. Clin. Nutr. 54:471–477. Deurenberg, P., J.A. Weststrate, and J.G.A.J. Hautvast 1989 Changes in fat-free mass during weight loss measured by bioelectrical impedance and by densitometry. Am. J. Clin. Nutr. 49:33–36. Deurenberg, P., F.J.M. Schouten, A. Andreoli, and A. de Lorenzo 1993 Assessment of changes in extracellular water and total body water using multifrequency bio-electrical impedance. Pp. 129–132 in Human Body Composition, K.J. Ellis and J.D. Eastman, eds. New York: Plenum Press. DHHS (U.S. Department of Health and Human Services) 1988 The Surgeon General's Report on Nutrition and Health—Summary and Recommendations. DHHS (PHS) Publ. No. 88-50211. Public Health Service, U.S. Department of Health and Human Services. Washington, D.C.: U.S. Government Printing Office. Ducimetiere, P., J. Richard, and F. Cambien 1986 The pattern of subcutaneous fat distribution in middle-aged men and the risk of coronary heart disease: The Paris Prospective Study. Int. J. Obes. 10:229–240. Durnin, J.V.G.A., and Satwanti 1982 Variations in the assessment of the fat content of the human body due to experimental technique in measuring body density. Ann. Hum. Biol. 9:221–225. Durnin, J.V.G.A., and J. Womersley 1974 Body fat assessed from total body density and its estimation from skinfold thickness: Measurements on 481 men and women aged from 16 to 72 years. Br. J. Nutr. 32:77–97. Evans, D.J., R.G. Hoffmann, R.K. Kalkhoff, and A.H. Kissebah 1983 Relationship of androgenic activity to body fat topography, fat cell morphology, and metabolic aberrations in premenopausal women. J. Clin. Endocrinol. Metab. 57:304–310. 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. Natick, Mass.: U.S. Army Research Institute of Environmental Medicine. Fliederbaum, J., A. Heller, K. Zweibaum, and J. Zarchi 1979 Clinical aspects of hunger disease in adults. Pp 13–36 in Hunger Disease–Studies by the Jewish Physicians in the Warsaw Ghetto, M. Wynick, ed. New York: John Wiley and Sons. Forsyth, R., M.J. Plyley, and R.J. Shephard 1988 Residual volume as a tool in body fat prediction. Ann. Nutr. Metab. 32:62–67. Freeman, S., J.H. Last, D.T. Petty, and I.L. Faller 1955 Total body water in man: Adaptation of measurement of total body water to field studies. Technical Report EP-11. NTIS AD-067 598. Natick, Mass.: Quartermaster Research and Development Center. Friedl, K.E. 1992 Body composition and military performance: Origins of the Army standards. Pp. 31–55 in Body Composition and Physical Performance, Applications for the Military Services, B.M. Marriott and J. Grumstrup-Scott, eds. A report of the Committee on Military Nutrition Research, Food and Nutrition Board, Institute of Medicine. Washington D.C.: National Academy Press.
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability KARL FRIEDL: That is exactly right, and that would be one of our goals. Eventually what we need is the technology—I guess it is going to take faster computers so we can do these full-body MRI scans, and we will come up with a muscle volume, and then we will be looking at the right thing. Because if you look at the same data, for example, from that Army body composition study, with increasing body weight we have a big increase in lift capacity in these 1,000 or so male soldiers, and some of the fattest soldiers out here can still lift—If you are 200 lbs with 24 percent body fat, you have 150 lbs or more of lean body mass, which is more than the leanest guy back in the corner here. So at a minimum, maybe what we need right now, just using simple techniques that are available, is a minimum body weight for soldiers. You are exactly right that there is this sort of reverse relationship, and lean body mass is much more important for predicting performance, if we wanted to predict performance. But remember, we are trying to motivate soldiers, too. We do not want obese soldiers. That is the bottom line in the Army, and it is for appearance reasons and some other things, too. JOHANNA DWYER: Just a compliment. Karl, it was a wonderful presentation, and to point out, again, this research is very valuable because of all the groups in society, I think the Armed Forces are the only ones who have been able to decrease obesity over the past 10 or 15 years. So we civilians have a lot to learn from the techniques you are doing. KARL FRIEDL: One of my questions is how much are we decreasing it or getting soldiers to maintain appropriate weights, and how much are we just making people who are not successful hit the street? And we do not really have data on that. There is a balance of the two. But we see a lot of soldiers running at noontime, which we did not used to see. I have to do it and there are a lot of us who have to do it just to maintain an appropriate weight. DOUGLAS WILMORE: Karl, have you looked at the geometry of the body in the DEXA system, which is probably accounting for your errors of the DEXA? KARL FRIEDL: Yes, especially at the upper end, there is still a body size problem. DOUGLAS WILMORE: Even with the Rangers, just losing 12 kg, probably just the geometry of the body is— KARL FRIEDL: We are concerned about that, and we need to look at it.
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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability DOUGLAS WILMORE: And as you get into the systems that do more spherical kinds of counting, as DEXA really gets developed, I think you will minimize that error more and more. But what that means is you are going to have to go back and redefine your equations and redevelop your equations as the technology gets better. KARL FRIEDL: We do not have to change them every time, but we need to keep checking on them to make sure that we are not doing something grossly inappropriate. DOUGLAS WILMORE: You can make phantoms [models imitating body composition, used to calibrate instruments], though, and get into that without using people.
Representative terms from entire chapter: