Emerging Technologies for Nutrition Research Potential for Assessing Military Performance Capability (1997) / Chapter Skim
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Emerging Technologies for Nutrition Research, 1997 Pp.
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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.
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relationships (i.e., within this restricted range of adiposity) (Vogel and Friedl, 1992a)
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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.
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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)
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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.
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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)
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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)
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TABLE 4-2 Variations of Underwater Weighing Methodology Reported in 150 PeerReviewed 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 *
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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]
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Ranger students (Friedl et al., 1994a) , make this a risky assumption in military field studies.
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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.
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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)
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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.
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described (Friedl et al., 1992)
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from skinfolds has a long history in Army research (e.g., Newman, 1955; Pascale et al., 1956)
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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)
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TABLE 4-4 Circumference, Weight, and Height Measurements Used in the Various Service Equations Equation Term Army Navy Marines Male Add Abdomen Abdomen Abdomen -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- Subtract Neck Neck Neck Stature Stature Female Add Hips Hips Thigh Weight Waist Abdomen Biceps -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- Subtract Neck Neck Neck Forearm Forearm Wrist Stature Stature NOTE: "Waist" is the minimal abdominal girth; "abdomen" is the girth taken at the navel. The Air Force uses the Navy equations.
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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.
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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.
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Figure 4-4 Percentage body fat (%BF) predicted from the Army equation for females compared with dual-energy x-ray absorptiometry (DEXA)
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TABLE 4-5 Median Percentage Body Fat Estimation Using Different Equations on the Same Sample of Male and Female Soldiers* Males, Age n DW JP7 USA MC USN 17–20 155 16.4 14.0 13.5 13.3 12.5 21–27 371 18.3 15.2 15.0 14.1 14.2 28–39 299 23.3 20.3 19.8 18.2 19.3 40+ 301 26.3 22.0 20.1 19.8 19.7 Females, Age n DW JP7 USA MC USN 17–20 58 27.2 23.0 28.0 19.5 25.5 21–27 155 26.4 21.7 27.3 19.1 24.9 28–39 50 30.1 25.0 29.6 20.5 27.8 40+ n/a NOTE: Note the wider range of body fat estimates produced by the equations for females.
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equation prediction of percentage body fat (Figure 4-5)
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TABLE 4-6 Physical Characteristics of Strong Women Compared with Those Who Cannot Lift 100 lb < 100 lb (n = 71)
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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)
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Figure 4-6 Mean lift capacity for male soldiers (n = 998) divided into body weight and percentage body fat categories.
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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)
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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)
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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.
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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.
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Figure 4-9 Body weight (BW) , fat-free mass (FFM)
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substantially, at a time when muscle catabolism and endocrine stress markers were substantially elevated (Moore et al., 1992)
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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.
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aspects of nutritional status (e.g., as part of an automated soldier status monitoring system)
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Beckett, M.B., and J.A. Hodgdon 1987 Lifting and carrying capacities relative to physical fitness measures.
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Despres, J-P., D Prud'homme, M-C.
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Friedl, K.E., and S.R. Plymate 1985 Effect of obesity on reproduction in the female.
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Goldman, R.F., and E.R. Buskirk 1961 Body volume measurement by underwater weighing: Description of a method.
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Hodgdon, J.A. 1992 Body composition in military services: Standards and methods.
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Katch, V.L., B Champaigne, P
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Mazess, R.B., H.S. Barden, J.P.
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Pi-Sunyer, F.X., and K.R. Segal 1992 Relationship of diet and exercise.
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Siri, W.E. 1961 Body composition from fluid spaces and density: Analysis of methods.
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Van Loan, M.D., and P.L. Mayclin 1992 Body composition assessment: Dual-energy x-ray absorptiometry (DEXA)
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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.
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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.
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