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Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability (1997)

Chapter: 4 Military Application of Body Composition Assessment Technologies

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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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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

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

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 [1961] 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

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

words, the differences in bone mineral content produced individual errors of +2.7 and -4.0 percent body fat in a two-compartment model.

These problems with underwater weighing do not automatically invalidate the military body fat equations that were developed and "calibrated" against underwater weighing. Anthropometric estimates of fatness are less influenced by variations in bone density or hydration of the FFM, which confound the criterion measurement; thus, the military equations may actually be fairer to individuals than underwater weighing (Friedl and Vogel, 1992). The circumference equations also have superior reproducibility, with half of the variance in repeated measurements (0.5% body fat) of the underwater weighing method (1.0%).

Regardless of criterion method parentage, the military equations must be revalidated against the best, most practical criterion methods available so that they can be improved if biological accuracy is a concern and to ensure that the equations are not unintentionally biased (such as by ethnicity). Instead of two-compartment models, which are influenced by ethnic, gender, and various environmental factors, the four-compartment model that includes measurements of total body bone mineral and total body water along with hydrodensitometry is accurate, practical, and achievable (Heymsfield et al., 1990a).

Improved Criterion Measure with a Four-Compartment Model

Early attempts at multicompartment models of body composition were limited by technological barriers, primarily in the accurate assessment of bone mineral (Allen et al., 1959; Selinger, 1977). Three-compartment models, which include measurement of total body water (TBW), have been practical in military studies almost since the development of underwater weighing (Behnke et al., 1942; Freeman et al., 1955; Siri, 1961); however, a key factor in the variability of the FFM has been the fractional contribution of bone mineral. In studies with Army basic trainees, Best and Kuhl (1955) tried to improve on available methods with the use of x-ray outlines of soft tissue and quantification of nonbone tissues. What they lacked was modern computing power and the ability to quantify density of the tissue, now available with soft-tissue analyses by DEXA (Mazess et al., 1990b). The currently available DEXA soft tissue body composition analysis is a side benefit of the development of safer and more practical bone mineral measurement devices. Most importantly, with the advent of dual-photon absorptiometry (DPA) and further improvements with DEXA, four-compartment models, which include measurement of bone mineral content, have finally become practical. Heymsfield and his colleagues (1990a) have demonstrated the accuracy of such a four-compartment model that is safer and more convenient than the current in vivo gold standard of neutron activation analysis and tritiated water dilution.

The comparison of values from the Heymsfield four-compartment model for five male and five female soldiers selected for a range of adiposity with val-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

ues obtained by two-and three-compartment model methods is shown in Table 4-3. Each of these methods provides estimates similar to the four-compartment model, and each of them is superior to field methods such as bioelectrical impedance analysis (BIA) or skinfold equations. Underwater weighing and total body water two-compartment models are related to the four-compartment model with shared components of the calculations (density and body water). DEXA soft tissue analysis is fairly independent since the bone mineral content used in the four-compartment model is measured in the bone-containing pixels that are excluded from the soft tissue analysis of body fat. This also makes the DEXA body composition analysis essentially a three-compartment model involving bone and fat and soft lean tissues.

It is this latter factor that makes DEXA a significant improvement for U.S. military studies, as will be discussed in the next section. It is critical to demonstrate the independence from ethnic bias of any proposed methods, and clearly two-compartment models are not independent because of the effect of bone mineral differences, whether between black and white subjects (Schutte et al., 1984) or even across different ethnic groups (Seidell et al., 1990). It will never be useful for the U.S. Army to develop race-or ethnicity-specific standards,

TABLE 4-3 Percentage Body Fat Estimated by Various Standard Methods in 10 Nonsmoking Young (Age < 40) Male and Female Soldiers Representing a Range of Fatness

Subject Characteristics

Body Fat (%)

Ethnicity

Age

BMI

4-C

DEXA

UWW

TBW

BIA

DW

Males

 

 

 

 

 

 

 

 

W

28

24.6

5.9

4.7

7.6

6.4

12.1

9.9

W

20

22.8

10.1

12.9

8.8

9.4

20.0

16.2

H

35

20.5

15.2

14.4

10.8

15.1

16.0

17.2

H

19

24.0

19.5

18.2

16.2

22.0

21.3

18.6

A

24

27.4

26.6

25.9

26.4

27.1

27.5

19.1

Females

 

 

 

 

 

 

 

 

B

22

23.3

15.7

18.2

15.5

14.5

24.3

19.5

B

19

18.8

18.8

20.0

19.1

17.3

21.1

23.1

W

20

20.9

25.0

26.8

28.3

21.5

29.0

26.3

W

23

20.1

29.4

27.5

27.8

28.6

30.6

25.3

H

20

24.5

34.7

34.1

34.6

33.4

33.0

34.1

NOTE: BMI, body mass index (kg/m2); 4-C, four-compartment; DEXA, dual-energy x-ray absorptiometry; UWW, underwater weighing; TBW, total body water; BIA, bioelectrical impedance analysis; DW, Durnin and Womersley (1974); W, white; H, Hispanic; B, black; A, Asian.

SOURCE: K. E. Friedl (Unpublished data, U.S. Army Research Institute of Environmental Medicine, Natick, Mass., 1993); methods described in Friedl et al. (1992).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

equations, or tables; they must be independent of race and ethnic effects, either through inclusion of the measurements that account for known sources of variation, or it must be demonstrated that they are unaffected by these factors.

DEXA Soft Tissue Analysis as a Practical Improvement over Underwater Weighing

As a criterion method, DEXA2 provides an improvement in precision, and probably in accuracy, over underwater weighing. More importantly, it is more convenient in large-scale military field research studies and has better reproducibility than underwater weighing (±0.5% vs ±1.0% body fat) (Friedl et al., 1992). Accuracy of the DEXA soft tissue analysis compares well with the four-compartment model for male and female soldiers (Figure 4-2). These data were obtained from fasted, young, nonsmoking soldiers, according to methods previ-

FIGURE 4-2 Percentage body fat (%BF) from dual-energy x-ray absorptiometry (DEXA) analysis compared to a four-compartment model for 37 male and 45 female soldiers. These data were obtained exactly as described in Friedl et al. (1992). SOURCE: Adapted from K. E. Friedl (Unpublished data, U.S. Army Research Institute of Environmental Medicine, Natick, Mass., 1993); methods described in Friedl et al. (1992).

2  

In this paper, DEXA refers to dual-energy x-ray absorptiometry using the DPX device (Lunar Corporation, Madison, Wis.), unless otherwise specified. Norland and Hologics manufacture similar devices but devices manufactured by these companies still appear less frequently in published research. There are differences in body composition results obtained from various devices, presumably related to the choice of energies, the software algorithms, and the design of the scanners.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

ously described (Friedl et al., 1992). A comparison of DEXA to underwater weighing yielded similarly high correlations but a larger error of the estimate (0.90, standard error of the estimate [SEE] = 3.0), reflecting the greater variability introduced by the calculation of percentage body fat from uncorrected density. Other studies comparing the LUNAR DEXA with underwater weighing report high correlations for men and women (Haarbo et al., 1991; Hansen et al., 1993). However, even with good correlations, other studies have produced inexplicably low values (differences of 4–10% body fat units) for DEXA assessments of fatness compared with underwater weighing for lean, young men (Johansson et al., 1993; Van Loan and Mayclin, 1992). Comparison of DEXA results with body fat estimates from anthropometry or total body potassium also produced good results (Jensen et al., 1993; Svendsen et al., 1991).

Assessment of known combinations of lard and lean muscle yield good agreement and a linear relationship to the ratio of attenuation coefficients (on which percentage body fat is based) across the full range of fatness (Haarbo et al., 1991; Jensen et al., 1993; Svendsen et al., 1993). Chemical analysis after postmortem homogenization of seven pigs (35–95 kg weights) demonstrated excellent agreement with DEXA percentage fat, following the line of identity, correlation coefficient of 0.98, and SEE of 2.9 percent (Svendsen et al., 1993). However, earlier versions of the software did not properly adjust total-body bone mineral measures for overlying tissue thickness in heavy individuals (Jebb et al., 1993a; Laskey et al., 1992; Svendsen et al., 1993); the software algorithms have been revised to better take this into account (Mazess et al., 1992). Variations in hydration status may still be a problem for DEXA interpretation of lean mass, as discussed later in this chapter.

DEXA also yields information about regional distribution differences. For limbs, the soft tissue lean measurement is a direct measure of muscle (Heymsfield et al., 1990b). Thus, in the Ranger-I study, a differential catabolism of arm and leg muscle during heavy work with hypocaloric diet could be demonstrated (Friedl et al., 1993a). There was a larger proportion of arm muscle sacrificed, although in absolute terms the legs provided the greatest source of stored energy, both muscle and fat. This was further demonstrated in the Ranger-II study, where the arm fat also was preferentially consumed in the fattest soldiers (Nindl et al., 1996). Even when matched for fatness, these soldiers had a lower proportion of truncal (abdominal) fat than a group of more sedentary soldiers, leading to the conclusion that there is a ''fit-fat" distribution pattern represented by a reduced proportion of fat energy stored in the abdominal region.

Other Technologies for Expedient Body Fat Assessment

Some of the expedient methods that have been considered for field research include anthropometry using skinfold measurements and imaging techniques such as ultrasound, BIA, and infrared interactance. Body composition prediction

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

from skinfolds has a long history in Army research (e.g., Newman, 1955; Pascale et al., 1956). James Vogel brought the skinfold equation of Durnin and Womersley (1974) to U.S. military studies, and it has become the standard of comparison for body composition (Vogel and Crowdy, 1979). The Durnin and Womersley (1974) equations were used as an interim method for body fat assessments in the Army Weight Control Program until the circumference equations were developed. The method has proven reliable even in a setting of extreme weight loss and low body fat, as in the case of studies of Ranger students (Friedl et al., 1994a). Although developed on an ethnically homogeneous sample of Scottish men and women, no ethnic or racial bias has been found in the performance of this equation. However, as evident from even the limited data in Table 4-3, skinfolds are not as accurate as criterion lab methods. As with most anthropometric equations developed against underwater weighing, these equations tend to overestimate body fat in lean individuals and underestimate body fat in fat individuals.

Bioelectrical impedance analysis has also been extensively investigated and was the subject of the National Institutes of Health (NIH) Technology Assessment Conference on Bioelectrical Impedance Analysis in Body Composition Measurement in December 1994 (NIH, 1996). In brief, the conference concluded that the method is about as good as anthropometry but is not a "gold standard" for body composition analysis and is particularly susceptible to variations in hydration status. BIA has been tested for body composition assessment, with emphasis on measurement of FFM in a variety of Army and Navy studies and has not demonstrated significant advantage over skinfold measurements (Hodgdon and Fitzgerald, 1987; Hodgdon et al., 1996). In contrast, the NIH Technology Assessment Conference panel suggested that BIA provides a reasonable measure of total body water. Body fat assessment by BIA has not been tested in field settings where skin temperature and other factors may affect the measurement (Lukaski, 1987).

Ultrasound methods provide measurements that do not substantially improve on anthropometric estimates. This may be due to the regional dependence of ultrasound measurements on the subcutaneous fat layer, making ultrasound a technical approach that is really just a more precise method of measuring what is captured with a doubled-layer skinfold thickness in a caliper.

A trial with a commercially available infrared device in this laboratory demonstrated values that were no better than would be predicted from height and weight (required inputs to the device) (Unpublished data, K. E. Friedl, U.S. Army Research Institute of Environmental Medicine, Natick, Mass., 1993). In fact, when the device was held over a plastic wall covering and entries were made for a real individual, a reasonable readout of 15 percent body fat was obtained. More problematic is the recommendation from manufacturer representatives that entries be made at "high exercise habits" to obtain more appropriate values for black subjects, apparently because of confounding influences of skin pigmentation. A small study with lean white athletes demonstrated that the opti-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

cal density data from a single biceps site, with or without other subject characteristics, did not provide values comparable to skinfold equations or underwater weighing (Israel et al., 1989). Except for the two original studies, which demonstrated the potential for this technology (performed with a research grade spectrophotometer and using only spectral data inputs in the regression equations) (Conway and Norris, 1987; Conway et al., 1984), this method has not been further developed technically or against credible criterion measures.

Such devices attract the interest of the lay public because they appear to be "high tech." This leads to the conclusion that if the Army circumference method of body fat estimation could be performed with a technologically complex instrumented tape measure, especially if it included a printout with "customized" diet recommendations, the same results would be more readily accepted.

SIGNIFICANCE OF BODY FAT TOPOGRAPHY AND MUSCLE MASS DISTRIBUTION

Abdominal Girth: Male Body Fat Predictor and Marker of Personal Readiness Goals

Although it would be convenient if circumference-based equations could be proven to be accurate predictors of total fatness, this skirts the main issue for the military, which is to identify a measure of excess fat that consistently relates to military appearance, health or nutrition, and exercise habits. The best physical predictor for any of these outcomes may not be total fatness. Differences in regional fat distribution have physiological significance in terms of regulation and metabolic consequences, particularly for women. Thus, assessment of specific regions may be preferential because it targets fat sites related to military goals, a theme that will be developed in this section.

Nearly every published anthropometric equation for males has included an assessment of the abdominal region. In one of the early anthropometric correlates with underwater weighing, Brozék and Keys (1951) demonstrated that the waist circumference and the chest-waist difference increased with increasing percentage body fat. The abdominal circumference used in the Army equation for males is adjusted with a neck circumference (instead of the earlier comparisons with chest circumference), a variable that appears to correct abdominal girth for total body volume (Personal communication, J. A. Hodgdon, Naval Health Research Center, San Diego, Calif., 1995). The Navy equation is essentially the same, with only the choice of coefficients changing the values produced (Table 4-4). The Marine Corps method, one of the first circumference equations produced, neglects only the correction for height, which is used by the Army and Navy equations. An equation developed on overweight civilian males goes even further than the military equations for males in the assessment of the abdomen, including measurement of three separate abdominal circumferences (at the waist, the navel, and above the iliac crests) (Tran and Weltman, 1988).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

ÿþ

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

Army body fat evaluation can be performed reasonably by anyone following simple directions in the Army regulation (AR 600-6, 1986) and using only a stadiometer, calibrated floor scale, and tape measure. These circumference-based equations were developed from an active duty Army sample in the 1984 Army Body Composition Study (Vogel et al., 1988). The equation for males was derived from a sample of 1,126 male soldiers (with body fat ranging from 0 to 39.5% calculated from underwater weighing) at Fort Hood and the Army War College, with a correlation of 0.82 and SEE of ±4.0 percent body fat. Figure 4-3 illustrates the relationship between percentage body fat by the Army equation for males and DEXA in soldiers from three more recent studies. A more recent combined analysis of data from 496 men yielded a best correlation coefficient of 0.81 and SEE approaching 3 percent body fat (Friedl and Vogel, 1997).

Diversity of Female Body Fat Topography and Physiology

In marked contrast to the strong association between abdominal girth and adiposity in males, abdominal girth or any other circumference alone is a poor predictor of body fat in females, where excess fat will accrue in other estrogen-dependent sites such as the hips, triceps, thighs, and breasts. In the 1984 Army Body Composition Study, waist-to-hip ratio remained at a constant average

FIGURE 4-3 Percentage body fat (%BF) predicted from the Army equation for males compared to dual-energy x-ray absorptiometry (DEXA) for 100 male soldiers. The guidelines indicate the most stringent limit of body fat specified in the Army regulation. Note that the equation errs on the side of the soldier, slightly underestimating fatter men. SOURCE: Adapted from the 1991 Ranger study (Friedl et al., 1994a), the 1991 30-d Meal, Ready-to-Eat study (Thomas et al., 1995), and the 1993 Validation of Army Equations Study (based on methods in Friedl et al., 1992).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

across the range of percentage body fat while it rose linearly with percentage body fat in men. Based on a computerized axial tomography scan at the umbilical level, Weits et al. (1988) demonstrated that an abdominal and hip circumference predicted 74 percent of the observed intraabdominal fat in males but only 56 percent of the variance in females. Kvist et al. (1986) have demonstrated that intraabdominal fat does not increase in women until a threshold level is achieved at approximately 30 kg of total body fat, while in men, abdominal fat increases linearly with increasing adiposity. Hattori et al. (1991) demonstrated an inverse relationship between subcutaneous fat and total percentage body fat in women, a relationship that could not be demonstrated in men. In their study, most fat was subcutaneous for lean women (i.e., those who were 15–25% body fat), but this decreased to less than half of the total fat in fatter women ( ~35% body fat). These data are consistent with the finding of this laboratory that abdominal girth is a discriminator of fatness in Army women only in the fattest 10 percent of the subjects of the 1984 Army Body Composition Study (Vogel and Friedl, 1992a). No single discriminator emerges for the remaining 90 percent of Army women in this sample (< 34% body fat), either because of the many choices of sites of fat deposition with precedence over the intraabdominal site, or because a general subcutaneous fat deposition occurs in advance of intraabdominal deposition. One conclusion from this is that an abdominal girth measurement is important in the assessment of fat women but may be less important to the prediction of adiposity in leaner women, possibly including the preselected Army population.

The equation for females was also derived in the 1984 Army Body Composition Study; ultimately the equation chosen was one based on a sample of 147 white women only (body fat range: 15.7–50.1%; r = 0.82; SEE = ±3.6%). This was largely because of the great difficulty in obtaining satisfactory data by underwater weighing for Hispanic and black female volunteers, and because an acceptable correlation could not be achieved with the entire sample (Vogel et al., 1988). The equation compared reasonably well with other standard equations and in a cross-validation using the Navy body composition study data (Hodgdon and Beckett, 1984; Vogel et al., 1988). However, with the data from the 1984 Army Body Composition Study, all of the standard anthropometric equations, including the Army equation (using all female soldiers, regardless of ethnicity), gave correlations of less than 0.8 and SEEs in excess of 4.0 percent body fat (Vogel et al., 1990). This highlights the greater difficulty in utilizing anthropometry to assess adiposity accurately in women compared with men. Questions concerning differences among ethnic groups in fat distribution and health risks are also unresolved (e.g., Conway et al., 1995).

Compared with DEXA, the equations for females have better agreement than in the original derivation, which was compared to underwater weighing. Validated against DEXA, the equations have higher correlations and lower SEEs (Figure 4-4). Given the greater choice of sites from which to develop predictive equations in women, it is not surprising that there is far less agreement

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

FIGURE 4-4 Percentage body fat (%BF) predicted from the Army equation for females compared with dual-energy x-ray absorptiometry (DEXA) for 170 female recruits. The guidelines indicate the most stringent limit of body fat specified in the Army regulation. Note that as with the male equation, this equation errs on the side of the soldier, slightly underestimating fatter women. Few women are misclassified by the Army equation as over the limit when they are within the limit of body fat standards. One extremely lean subject is off the scale of this graph. SOURCE: Adapted from the 1993 Fort Jackson Study (Westphal et al., 1995).

among methods of fat estimation in females compared with males (Table 4-4). These differences also produce relatively large differences in body fat predictions, unlike the military equations for males (Table 4-5). The five commonly considered sites of female fat deposition include hips (and gluteal), thighs (femoral), abdomen, upper arms, and breasts. Breast fat is usually discounted from anthropometric equations because of the personal nature of this measure, but this is of little consequence to total adiposity. Breast fat represents only a small proportion of total fat for most women, averaging 3.5 percent of total fat mass, irrespective of total adiposity (Katch et al., 1980). Circumferential measures of the other four sites are all strong correlates of total adiposity and appear in multiple regression analyses in various combinations. Of the three military equations, the Army equation emphasizes hip girth and total body weight as fat markers; the Navy equation emphasizes waist and hip; and the Marine equation uses arm, thigh, and waist (Table 4-4).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

ÿþ

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

equation prediction of percentage body fat (Figure 4-5). However, percentage body fat for the same women, estimated from the Navy equation (Hodgdon and Beckett, 1984), demonstrates a tendency to overestimate fatness in just these strong women. These women are bigger and have more FFM than the weaker soldiers, but the groups had the same relative adiposity ( ~28% body fat) (Table 4-6). At least a part of the difference in the performance of the Army and Navy equations is attributable to the larger abdominal measurement in the stronger Navy women (about 5% greater than in the weaker soldiers), although this is only slightly greater than the increase in hip measurement. However, another reason for the difference may be the many factors in the more complicated Army equation that help to adjust for greater muscularity.

This discrepancy with a select population of strong women highlights a quandary in female body fat standards: the strongest women tend to share the male characteristics of fat distribution to the trunk and may experience a greater

FIGURE 4-5 Percentage body fat (%BF) predicted from the Army equation for females and from the Navy equation for females, compared with dual-energy x-ray absorptiometry (DEXA) for 57 strong female recruits. These recruits all lifted greater than 100 lb in a maximal lift test. The same group of women tended to be overestimated by the Navy equation, which includes an abdominal circumference, compared with the Army equation, which does not. The Army equation also includes more factors (wrist and forearm circumference) to adjust for large body proportions. SOURCE: Adapted from the 1993 Fort Jackson study (Westphal et al., 1995).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

TABLE 4-6 Physical Characteristics of Strong Women Compared with Those Who Cannot Lift 100 lb

 

< 100 lb

(n = 71)

= 100 lb

(n = 57)

BMI (kg/m2)

23.0 ± 2.4

24.5 ± 2.1**

Stature (cm)

161.5 ± 5.9

164.5 ± 6.6*

Body weight (kg)

59.9 ± 8.2

66.2 ± 7.3**

DEXA (%BF)

28.0 ± 6.2

28.3 ± 5.4

Army equation (%BF)

27.5 ± 4.0

28.5 ± 3.3

Navy equation (%BF)

29.1 ± 4.9

31.5 ± 4.1**

Neck circ (cm)

31.5 ± 1.2

32.7 ± 1.3**

Abdominal circ (cm)

75.3 ± 6.8

79.3 ± 6.0**

Hips circ (cm)

96.0 ± 5.8

99.5 ± 4.9**

Fat-free mass (kg)

42.9 ± 4.0

47.3 ± 4.4**

Push ups (count)

18.5 ± 9.3

23.6 ± 11.2*

NOTE: Although percentage body fat (%BF) is similar for the two groups, the strong women were significantly larger, and this includes many of the body circumferences. BMI, body mass index; DEXA, dual-energy x-ray absorptiometry; circ, circumference.

*p < 0.05,

**p < 0.01 significance for differences between groups, compared by t-test.

SOURCE: Based on data from Sharp et al. (1994).

risk of cardiovascular disease (Evans et al., 1983; Hartz et al., 1984). Thus, if health concerns are the key objective, abdominal girth should be a prominent feature of the fat assessment for men and women (as in the Navy equation that is appropriate to Navy health goals); whereas, for an emphasis on combat readiness with importance placed on strength capacity, an abdominal assessment might be better avoided in women (as in the Army equation).

The reason for this difference in regional fat physiology appears to center in large measure on relative androgenicity of the individual woman (Friedl and Plymate, 1985). Even differences among ethnic groups, and among individuals within ethnic groups, correspond to differences in free testosterone levels (Evans et al., 1983; Hediger and Katz, 1986; Kirschner et al., 1990; Seidell et al., 1990). For example, in the European Fat Distribution Study (Seidell et al., 1990), serum free testosterone correlated with waist-to-hip circumference ratio (WHR); Mediterranean women had the highest free testosterone, highest WHR, and lowest triceps-to-subscapular skinfold ratios compared with northern European women who had lower androgenicity and a greater extremity fat distribution.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

The extent to which male pattern adiposity translates into increased androgenicity and a consequent upper body muscularity and strength is unresolved. Krotkiewski and Björntorp (1986) reported a relationship between upper body fat distribution and the proportion of fast-twitch skeletal muscle (a male characteristic). They also found muscle mass increases more like males in abdominally fat women in a training program, compared with women of lower body fat. Ross and Rissanen (1994) also concluded that weight loss in overweight women was most frequently reflected in abdominal (both visceral and subcutaneous) fat.

It is interesting to note that thigh fat may also be a marker of cardiovascular health risks in women, in the opposite direction of abdominal fat (Terry et al., 1991). Thus, if long-term health is the primary consideration, reliance on thigh fat as a marker of adiposity would confound the goals of the standard because it is inversely correlated with serum lipid derangements. Assessment of thigh fat may also be undesirable in an equation that will be used to follow progress in fat reduction, until it is better established that thigh fat can be readily mobilized by exercise and dietary restriction in comparison with other sites. There is some evidence that thigh fat is primarily mobilized in postpartum women under the influence of specific lactational hormones (Rebuffe-Scrive et al., 1985; Steingrimsdottir et al., 1980) and may not be readily mobilized compared with other sites, even in men (Rognum et al., 1982).

Future Standards Development with Lean Mass Assessments

Eventually the military body composition standards may include a regional assessment of FFM, perhaps a flexed biceps or forearm circumference (Martin et al., 1990; Vanderveen et al., 1974), to ensure a minimum muscle mass in low-weight soldiers. One suggestion for a simple approach is a sliding scale that allows for greater relative body fat for heavier soldiers (Vogel, 1992). This would target small soldiers to ensure a minimum FFM (e.g., for a minimum FFM standard of 50 kg, a 60-kg soldier could have no more than ~15% body fat, while a 70-kg soldier could be allowed up to ~20% body fat). This is important because most jobs in the Army and Navy require strength for lifting and carrying (Beckett and Hodgdon, 1987; Harman and Frykman, 1992). The relationships among body weight, percentage body fat, and lifting strength, measured by incremental dynamic lift, is illustrated for males in Figure 4-6. It is evident that the typical 200-lb soldier, even one whose body fat exceeds 24 percent, can lift as much as the 150-lb soldier at 20 percent body fat. Clearly the relationship is explained by FFM, and strength is independent of the overlaying fat. In fact, maximal aerobic capacity is inversely correlated with BMI while maximal life capacity is positively correlated (Gordon and Friedl, 1994). Women who exceed the weight-for-height allowed by the Army weight screening tables are stronger than smaller women, but there is no relationship between muscular strength and adiposity as assessed by the Army equation (Sharp et al., 1994). This re-empha-

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

FIGURE 4-6 Mean lift capacity for male soldiers (n = 998) divided into body weight and percentage body fat categories. SOURCE: Plotted from data from the 1984 Army Body Composition Study (Fitzgerald et al., 1986).

sizes the point that the current Army weight control program is not intended to select for physical performance and would be especially unsuited to predicting strength performance (Vogel and Friedl, 1992b). Eventually, FFM might be a factor to include in military body composition standards, in order to provide some lower limit beneath which excessively thin individuals who cannot perform typical lifting and load-carrying tasks would be penalized or given special help. An immediately foreseeable problem with such a standard is that if it is related to job requirements, the standard must be gender neutral (i.e., the same for men and women). This means that a high proportion of women would be identified as failing to meet the standard. If the goal is to identify soldiers for special physical training rather than to have punitive effects, such a screening tool might be practical and useful. The connection between specific strength tests and regional or total muscle mass is far from clear (Johnson et al., 1994) and requires more research before any screening tests could be proposed.

ASSESSMENT OF CHANGES IN NUTRITIONAL AND HYDRATIONAL STATUS

Validity of Anthropometric Equations Derived from Cross-Sectional Data When Applied to Predict Changes in Body Composition

All of the standard anthropometric equations currently in use have been developed from studies of cross-sectional population data. There are no equations

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

that have been derived from anthropometric changes in a longitudinal study. Many previous reports on weight loss of very large or small magnitude have suggested that anthropometry did not accurately reflect the true changes (Ballor and Katch, 1989; King and Katch, 1986; Moody et al., 1969; Scherf et al., 1986; Wilmore et al., 1970). However, these studies compared anthropometry with changes in total weight or in fat assessed by underwater weighing. As previously noted, the high variability in the underwater weighing technique introduces additional variance that confounds the results. Jebb et al. (1993b) compared changes in density (from underwater weighing), skinfold thickness, and BIA measures with continuous whole-body calorimetry during 12 days of underfeeding or overfeeding. They found that skinfold thicknesses better detected changes in fat mass than BIA; furthermore, skinfold thicknesses yielded a lower coefficient of variation in fat mass prediction than either density or resistance, results that are consistent with findings from this laboratory (Friedl et al., 1992). Within the choices of anthropometric methods, Bray et al. (1978) found that circumferences were superior to skinfolds in assessing progress in weight reduction, demonstrating lower coefficients of variation and better correlations. Nevertheless, the relative insensitivity of any anthropometric method to relatively small changes in fat mass makes it difficult to chart satisfactory progress in fat loss for military regulations. The current Army regulation (AR 600-9, 1986) requires that progress in weight loss or fat loss be demonstrated until body fat goals are achieved.

In the 1993 study of the health and performance of women in basic training (Westphal et al., 1995), extensive anthropometric measurements and DEXA measurements were performed on 150 women at the beginning and end of 8 weeks of basic training, in order to assess the effect of weight change, including fat loss with concurrent lean mass gain, on predictions by the Army anthropometric equation. Body water, as indicated by BIA, increased in proportion to the increase in lean mass, and at both the beginning and the end of training, DEXA-assessed body weight closely matched the measured scale weights, suggesting that the measurement artifacts observed earlier in the two Ranger school studies (Friedl et al., 1994a) were not present in the current setting of modest weight change. By DEXA measurements, the women demonstrated a mean gain of 2.0 kg of FFM, regardless of initial fatness. Change in body fat, however, was related to initial fatness, with the fattest soldiers demonstrating the largest losses, and soldiers below 25 percent body fat demonstrating increases in body fat content (Friedl et al., 1994b).

Figure 4-7 shows the changes in body fat predicted by the Army equation for females with respect to changes in fat as measured by DEXA. The equation shows a tendency to underestimate fat weight loss within a range of approximately 2 kg of actual fat loss as measured by DEXA; this is reflected by an apparent gain of up to 2 kg of fat using the Army equation. Higher rates of fat loss (> 2 kg/8 wk) did register correctly as fat loss in the Army equation. This is only

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

FIGURE 4-7 Change in fat weight predicted by Army equations for females compared with change assessed by dual-energy x-ray absorptiometry (DEXA) for 150 women assessed at the start and finish of basic training (8 weeks). Nearly 20 percent of the sample lost fat weight that was not reflected as a net loss by the Army equation. SOURCE: Adapted from Westphal et al. (1995).

a slightly better prediction of change than that reported by Ballor and Katch (1989) for commonly used equations (compared with underwater weighing), applied to a sample of somewhat fatter women (average 37% body fat) losing an average body weight of 3.0 kg over 8 weeks.

An earlier study by Pascale et al. (1955) from the Army Medical Nutrition Laboratory illustrates the need for more than one method of body composition assessment for interpretation of modest body composition changes in some field studies. Unlike the study of female recruits conducted by this laboratory (Westphal et al., 1995), there appear to be more confounding variables, particularly with hydrational derangements, in studies involving environmental extremes or strenuous activity levels. The study of Pascale et al. (1955) was conducted on a dozen selected, lean (< 10% body fat) soldiers going through airborne training of 3 weeks duration. Mean weight loss was 0.6 kg, which underwater weighing partitioned into a 0.8 kg fat loss and a 0.2 kg gain in FFM. However, by deuterium oxide dilution, a loss of 2.7 kg fat and a gain of 2.1 kg FFM were indicated. There were clearly substantial changes in fluid balance. Detailed analyses of fluid balance using deuterium oxide, radiosulfate, and thiocyanate dilutions indicated total body water increases of 1.6 liters (including +2.0 liters intracellular and -0.4 liters extracellular water). Changes in skinfold measurements indicated a decrease change of 1 percent in body fat, supporting

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

the values obtained by underwater weighing. Thus, intensive training, even in approximate energy balance, appears to produce hydrational changes that still confound accurate detection of modest body composition changes.

It may be extraordinarily complicated to measure weight loss and apparent body composition changes in other specialized field settings. For example, in situations of a deployment to altitude to defend border regions, dramatic hydrational derangements could mask changes in body cell mass. Soldiers are at high risk for dehydration with elevated ventilatory rates in a cold, dry environment, but hypoxia promotes a hyperhydration, particularly in the maladaptors who will suffer acute mountain sickness (Singh et al., 1990). Identifying changes in body composition in this setting presents special problems that require measurement of fluid spaces and a critical interpretation of the results that purportedly identify body composition changes. For example, skinfold thicknesses, which are relatively robust indicators of changes in adiposity, are inadequate in the face of altitude-induced fluid shifts that also include regional subcutaneous differences (Gunga et al., 1995; Zachariah et al., 1987). BIA is one method that appears to identify gross hydrational changes reasonably in a field setting (Fulco et al., 1992) and could potentially be used to predict risk of illness.

Confounding Effects of Large Weight Losses in Ranger Training: Increases in Hydration and Questionable Criterion Measures

Small acute changes in TBW, induced by body water manipulations ( ~1-1.5 kg of water gain or loss) are assessed accurately as changes in total weight by DEXA (or the older dual-photon absorptiometry devices), but tend to misplace the specific components of weight change between the fat and soft-tissue FFM (Going et al., 1993; Lands et al., 1991). This effect can be illustrated by the following pilot study that was conducted by this laboratory (Friedl et al., 1993b). DEXA measurements were obtained in duplicate before and after a 6-h furosemide-induced (40 mg p.o.) diuresis in a 37-year-old, 80 kg, 17 percent body fat male. Weight loss totaled 2.4 kg, BIA predicted a water loss of 2.6 liters, and DEXA measurements indicated a reduction in soft-tissue weight of 2.5 kg. However, the DEXA measurement misplaced the change, indicating a loss of 3.0 kg from the soft-tissue FFM and a gain of 0.5 kg in fat mass; thus, body fat appeared to increase by more than 1 percent. This error was much greater than the variation between duplicate measurements (bone mineral content measurements remained constant) (Friedl et al., 1993b).

Large reductions in body weight appear to produce substantial increases in hydration (Deurenberg et al., 1989; Keys et al., 1946), and these changes produce large errors in the estimate of FFM. In the study by Deurenberg et al. (1989), a group of obese women lost an average of 10 kg of body weight during 8 weeks. The nature of this loss was estimated by underwater weighing as 2.3 kg of FFM but an improbable 0.6 kg of FFM (only 6% of the total weight loss) by BIA. Increased hydration would account for this discrepancy, with an expected

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

underestimate of FFM loss based on BIA measurements but an overestimate of the changes in FFM when measured by underwater weighing. Thus, the true FFM loss is a value between these two. In the studies of semistarvation in Ranger students, similar changes were observed, with a 10 kg average weight loss during 8 weeks and a substantial underestimate by BIA of FFM loss (Hodgdon et al., 1996). Possibly also the result of hydrational changes (Roubenoff et al., 1993), DEXA overestimated the total mass present at the end of the Ranger I study by an average of 2.8 kg, an observation that was confirmed in Ranger II (Friedl et al., 1994a). This overestimate by DEXA occurred across all body weights, with a parallel overestimation of mass compared to scale weight (Friedl et al. 1994a) (Figure 4-8). In the second study (Nindl et al., 1996), fat stores were better preserved yet the artifactual error was similar in magnitude, suggesting that the primary error was not a result of deficiencies of the device algorithm at the lower end of the body fat range. Measurements of hydration by isotope dilution in a small subsample of Ranger students demonstrated that total body water did not decrease with the loss of body weight. This was supported by BIA measurements of the whole sample of men (Figure 4-9). An average 10 kg decline in body weight in 50 men included 4 kg of FFM loss but no change in the 50 liters of total body water (as estimated by BIA). This use of BIA to assess total body water during hydrational changes has been validated by Deurenberg et al. (1993).

Roubenoff et al. (1993) have suggested that overhydration causes errors in the DEXA estimate of FFM. Underwater weighing is sensitive to deviations in hydration but in the opposite direction from DEXA, with hydration greater than

FIGURE 4-8 Comparison of body weight of 55 male soldiers assessed by dual-energy x-ray absorptiometry (DEXA) with that obtained with an electronic scale at the start and at the end of Ranger training (8 weeks). The values obtained are virtually identical at the start of training, but tissue mass was significantly overestimated by DEXA at the end of the course.

SOURCE: Adapted from Friedl et al. (1994a).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

FIGURE 4-9 Body weight (BW), fat-free mass (FFM), and total body water (TBW) for 50 male soldiers at the start and end of Ranger training (8 weeks). The TBW data were predicted from resistance values obtained at 50 KHz by bioelectrical impedance analysis. SOURCE: Adapted from the 1992 Ranger study (Hodgdon et al., 1996; Nindl et al., 1996).

the assumed 73 percent of FFM leading to overestimates of fat in two-compartment models. DEXA overestimates total FFM while underwater weighing underestimates FFM in this setting; percentage body fat from the DEXA and actual scale weight give more plausible but still uncertain values. These data indicate that most of the commonly used methods of body composition measurement are affected by hydration status. At a minimum, military studies requiring precise assessments of body composition change (e.g., using DEXA) must also include some estimate of TBW. Body water appears to be suitably estimated from BIA with a high level of precision, although stable isotope dilution may be more accurate (Friedl et al., 1992). When a higher level of precision is not required or practical in a field study, the skinfold equations of Durnin and Womersley (1974) repeatedly have proven their value, as demonstrated by their measurement of fat loss in Ranger students (Friedl et al., 1994a). An understanding of the physiology of hyperhydration during rapid weight loss will be important to optimizing energy metabolism in intensive military scenarios. As Francis Moore noted in a much earlier Army symposium, ''The ideal weight reduction program might be defined as one which would result in oxidation of body fat without erosion of body cell mass on the one hand, or excessive accumulation of extracellular water on the other" (Moore, 1966, 120).

Considerations in the Assessment of Nutritional Compromise

Low body fat is not, by itself, a marker of nutritional compromise. For example, at the end of Ranger training, the sum of skinfold measurements (at the four sites used for the Durnin and Womersley [1974] equation) had declined

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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substantially, at a time when muscle catabolism and endocrine stress markers were substantially elevated (Moore et al., 1992). However, the same skinfold measurements were obtained in a group of weight-stable, elite, Kenyan runners in training who were approaching peak performance (Unpublished data, J. Staab and K. Friedl, U.S. Army Research Institute of Environmental Medicine, Natick, Mass., 1993) (Figure 4-10). In other words, body fat does not distinguish the very different nutritional status of these two groups, one in energy deficit and the other in energy balance. The practical distinguishing characteristic for these two lean groups is recent weight history. The Ranger students experienced large weight losses, with nearly every individual in the Ranger I study losing more than 10 percent of body weight within 8 weeks (Friedl et al., 1994a), while the Kenyan runners remained at stable weight.

There was also a large variation in responses of individuals to the stressors of Ranger training. For example, two individuals who began training with low body fat and other physical similarities later demonstrated weight loss and muscle mass catabolism at opposite ends of the range for the group (Friedl et al., 1994a). This is presumably related to cytokine and other stress hormonal responses, which can be adaptive or maladaptive (e.g., Stouthard et al., 1995). For example, the highest serum cortisol levels (1,200 nmol/liter) and the lowest concentration of serum interleukin-6 in the Ranger I study were measured in the individual who lost the most FFM (Moore et al., 1992). This may have been a

FIGURE 4-10 Mean sum of four skinfolds at the start and end (8 weeks) of the 1991 Ranger study (RGR I, n = 55) and 1992 Ranger study (RGR II, n = 50), compared with skinfolds of five elite Kenyan runners in training. Note that the skinfold thicknesses of the Kenyan runners are very similar to those of students at the end of Ranger training, even though nutritional status is remarkably different. SOURCE: Adapted from the Ranger I study (Friedl et al., 1994a), Ranger II study (Nindl et al., 1996), and elite Kenyan runners study (Unpublished data, J. Staab and K. Friedl, U.S. Army Research Institute of Environmental Medicine, Natick, Mass., 1993).

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

contributing factor to the catabolism, or it may have been a marker for an increasingly tenuous metabolic status. The critical marker of metabolic compromise in soldiers is the rate of weight loss. Conveniently, this is also the most practical measure in field settings or for nonresearch monitoring applications.

Oritsland (1990) concluded that 10 percent body fat is optimal for the longest period of survival (with declining survival times above and below this level), with or without the customary starvation-induced depression of basal metabolism. His model was based on data from the 1950 Minnesota Starvation Study (Keys et al., 1950) and data from field studies in Holland at the end of World War II (Burger et al., 1948). However, in some circumstances, such as cold combined with energy restriction, there may be a compromise of competing survival mechanisms. For example, Ranger students become hypothyroid in summer courses as a result of the energy restriction; this is also reflected in reduced body temperatures, as in other semistarvation studies (e.g., Fliederbaum et al., 1979, 18; Hehir, 1922). Cold exposure superimposed on energy restriction in Ranger classes during the winter would either produce extra risks to thermoregulation or it would compromise the attempt to reduce metabolic costs, which conserves body tissues. Individuals with a normal energy balance who are very lean (< 10% body fat) require a higher energy expenditure to stay warm during cold exposure through shivering thermogenesis (Glickman-Weiss et al., 1991). Thermogenesis is blunted by energy deficit, and these soldiers operate at a lower body temperature; however, aerobic fitness and the high exercise levels may help to sustain thermogenesis (Pi-Sunyer and Segal, 1992). The issue of special susceptibility of lean, undernourished soldiers in the cold has not been adequately addressed with research into the endocrine and metabolic responses.

AUTHOR'S CONCLUSIONS

This chapter has emphasized some of the methodological problems in the assessment of body composition for military fat standards and for field research. The Army's current approach to field study assessments is heavily dependent on DEXA, with confirmatory data obtained from skinfold thicknesses and hydrational information obtained by BIA. Ultimately, the most important component of body composition in military studies is muscle mass or nitrogen balance, but assessment of this still awaits the development of new enabling technologies such as a DEXA-like scanner for total body nitrogen or identification of suitable biochemical markers.

The evaluation of intervention strategies to prevent the loss of FFM during physically demanding military operations is dependent on a valid measurement of FFM (which must work in the face of other potential confounders). It also demands a better understanding of the biochemical correlates of overtraining, including markers of the breakdown of specific tissues such as collagen, bone, and muscle and a better understanding of cytokine regulation of the balance of muscle and fat tissues. Hydration status may be useful in monitoring of related

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
×

aspects of nutritional status (e.g., as part of an automated soldier status monitoring system).

The study of female recruits in basic training has provided a robust test of the adequacy of the female fat equations (with an increase of FFM concurrent with loss of excess fat weight) (Westphal et al., 1995). The data indicate a clear need for further development of methods that predict modest changes in body composition.

A single set of equations and standards for all services that relate body composition, fitness goals, and physical performance requirements is a desirable goal. Research to support and demonstrate reasonable approaches to achieving and maintaining the standards would make this more defensible as a regulation that enhances readiness. It also would be of interest to know the long-range consequences of these military standards, in terms of both the health risks for those who gain weight after leaving the service following long-term weight suppression, and the benefits of preventing changes currently attributed to aging. Finally, the methods developed for use in surveillance or maintenance of standards need to be simple, with high reproducibility and a suitable relationship to the intended use (i.e., accurate compared to a multicompartment criterion method, or highly correlated with a military end point).

ACKNOWLEDGMENTS

The author wishes to thank Ms. Sherryl Kubel for her careful tabulation of the data on methods of underwater weighing and Ms. Lorraine Farinick for creation of each of the figures. Much of the new data reported here on DEXA and four-compartment models were collected with the expert assistance of Mr. Lou Marchitelli, Mr. Bob Mello, SPC Marjorie Harp, SPC Sherryl Kubel, SPC Sabrina Carson, and SPC Sonya Moore; the author is grateful to all of these individuals for their dedicated work.

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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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DISCUSSION

JOHN VANDERVEEN: Karl, a result of our workshop on body composition, as I recall, was that body fat is a lousy predictor of performance, that lean body mass is a predictor, and I think we recommended that you look at lean body mass.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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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.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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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.

Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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Suggested Citation:"4 Military Application of Body Composition Assessment Technologies." Institute of Medicine. 1997. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability. Washington, DC: The National Academies Press. doi: 10.17226/5827.
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The latest of a series of publications based on workshops sponsored by the Committee on Military Nutrition Research, this book's focus on emerging technologies for nutrition research arose from a concern among scientists at the U.S. Army Research Institute of Environmental Medicine that traditional nutrition research, using standard techniques, centered more on complex issues of the maintenance or enhancement of performance, and might not be sufficiently substantive either to measure changes in performance or to predict the effects on performance of stresses soldiers commonly experience in operational environments. The committee's task was to identify and evaluate new technologies to determine whether they could help resolve important issues in military nutrition research. The book contains the committee's summary and recommendations as well as individually authored chapters based on presentations at a 1995 workshop. Other chapters cover techniques of body composition assessment, tracer techniques for the study of metabolism, ambulatory techniques for the determination of energy expenditure, molecular and cellular approaches to nutrition, the assessment of immune function, and functional and behavioral measures of nutritional status.

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