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Body Composition and Physical Performance 1992.
Pp. 185-193. Washington, D.C.
National Academy Press
11
Critique of the Military's Approach
to Body Composition Assessment
and Evaluation
Henry C. Lukaski
There are many reasons for assessment and evaluation of body compo-
sition of military personnel. One purpose is to provide objective standards
for recruitment and retention of personnel. Other purposes include the
maintenance of appropriate physical appearance, optimal performance un-
der combat conditions and health. Thus, body composition assessment and
evaluation are important and necessary to meet the duties and responsibili-
ties of the Armed Forces.
APPROACHES
Because of the large numbers of military personnel that require body
composition assessment, any approach must acknowledge and balance the
factors of practicality, reliability and accuracy of measurements, time re-
quirements, and skill required by the test administrator. These constraints
led to the use of weight-for-height tables. Currently, each branch of the
Armed Forces uses gender-specific weight-for-height tables both for re-
cruitment and retention. Interestingly, the target values are different for
recruitment and retention, except for the U.S. Air Force (Table 11-1~. Whether
these discrepancies reflect true differences in requirements for physical de-
mands or historical precedent is unknown.
If an individual fails to meet the weight-for-height guidelines, an evalu-
ation of body composition is performed by using either body circumference
185
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186
HENRY C. LUKASKI
TABLE 11-1 Weight Standards for Recruitment and
Retention of a 70-Inch Man in the U.S. Armed Services
Body Weight (lb)
Recruitment Retention Difference
Army 215 192 23
Navy 215 192 23
Marine Corps 211 194 17
Air Force 194 192 2
SOURCE: Adapted from U.S. Department of Defense (1981).
measurements (AR 600-9, 1986; Hodgdon and Beckett, 1984a,b; Vogel et
al., 1988; Wright et al., 1981) or the combination of skinfold thicknesses
and body circumference measurements (Clark, 1976~. Each of these anthro-
pometric approaches relies on regression equations to predict percent body
fat (BF). As shown in Table 11-2, similar variables (neck and abdominal
circumferences) are found in the currently used equations.
The estimated percent BF values are then compared to BF standards to
determine whether an individual has excess BF. The U.S. Army BF stan-
dards are presented in Table 11-3. More stringent Department of Defense
TABLE 11-2 Variables Used to Predict Body Composition of U.S.
Military Personnel
Source
Gender of
Sample Variables
U.S. Air Force
Clark (1976) Men
Lengths of humerus, radius, acromion, iliac crest,
patella and tibia; circumferences of flexed biceps,
forearm, chest, waist, buttocks, thigh, and calf;
skinfold thickness at triceps, scapula, supra-iliac
crest, and calf; and fat density multiplied by
number of limbs measured
U.S. Navy
Wright et al. (1981) Men Neck and abdominal circumferences
U.S. Navy
Hodgdon and Men Neck and abdominal circumferences; height
Beckett ( 1 984a,b)
Women Neck, abdominal and hip circumferences; height
U.S. Army
Vogel et al. (1988) Men and Neck and abdominal circumferences; height
Women
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BODY COMPOSITION ASSESSMENT AND EVALUATION
TABLE 11-3 Maximum Allowable Percent Body Fat
Standards in the U.S. Army
Age Group (years)
17-20 21-27
28-39 >40
Men
Women
20 22 24 26
28 30 32 34
SOURCE: Adapted from AR 600-9 (1986).
187
guidelines indicate goals of 20 percent BF for men and 26 percent BF for
women (AR 600-9, 1986~.
DISCUSSION
The military program of body composition assessment and evaluation is
ambitious and very challenging. Any critique of the current program needs
to address issues that are philosophical and technical.
It is unclear from the available literature whether the military body
composition program intends to establish norms and standards for the indi-
vidual or for the armed forces as a whole. With the current system of
weight-for-height tables, body circumference measurements, and an allow-
able increase of 2 percent BF standards per decade of age, it appears that
population assessment methods are used for screening, and individual stan-
dards are used for evaluation. Thus, the basis for establishing the percent
BF norms needs detailed examination and probably revision.
Weight-for-height tables have gained considerable use by the civilian
American population. To generate national weight standards requires infor-
mation on a large group of individuals. One approach was to use data on
weight and height from the insurance industry (Society of Actuaries, 1959,
1980a,b). Although these surveys supply data on weight and height for
nearly 5 million people, they suffer from the extreme bias of self-selection.
A second data base has been generated by the National Center for Health
Statistics (Abraham et al., 1983), which developed weight standards for
height by plotting the normal distribution of weight-for-height. This distri-
bution was arbitrarily divided into overweight and severely overweight.
Overweight was defined as those persons exceeding the eighty-fifth percen-
tile of weight-for-height and used as a reference the weights of men and
women between 20 and 29 years of age. Severely overweight was consid-
ered as greater than the ninety-fifth percentile. The major drawback of this
approach is that the standard may change as the weight distribution of the
population changes.
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88
HENRY C. LUKASKI
Weight-for-height standards can also be based on the lowest overall
risk to health. For example, the minimal death rate in several prospective
studies was associated with a body mass index (BMI) of 22 to 25 kg/m2;
also, the BMI associated with the lowest risk of death increased with
age (Andrea, 19851. A World Health Organization (1987) group suggested
that a BMI range of 20 to 30 kg/m2 was associated with a modest risk of
mortality.
Another approach to defining healthy weights was taken by a Canadian
review group (Health Promotion Directorate, 1988~. They labeled as "good
weights for most people" the body weights associated with a BMI of 20
to 25 kg/m2. Individuals with a BMI of less than 20 kg/m2, as well as
those with a BMI of 25 to 27 kg/m2, were considered to have an increased
health risk.
Currently available weight-for-height tables do not take into account
ethnic or racial differences, morbidity, and mortality in the distribution of
weight-for-height. Efforts are in progress to develop race-specific weight-
for-height data distributions for Black, Hispanic, and Asian Americans
using the limited data available.
The bases for the derivation and application of weight-for-height tables
in the military need examination. What criteria have been used to establish
the tables currently in use? If the tables were constructed from statistical
analyses assuming normally distributed weight-for-height data and by using
arbitrary cutoff points, the ranges of acceptable weights are biased by
changes in the secular distribution of weight-for-height. Furthermore, these
estimates may not include any consideration of the criteria of health, ethnic-
ity, or performance.
The current weight-for-height standards differ for recruitment and re-
tention. The differences are large (see Table 11-1) and represent unrealistic
goals for weight loss, independent of body composition change, that are
attainable during recruit training. It is reasonable to suggest that these
differences be resolved.
Any attempt to revise weight-for-height tables for military use needs to
Include such factors as gender, ethnicity, performance, appearance, and health.
Realistic consideration of attainable changes in body weight and body
composition during recruit training should be included in deriving weight
estimates for recruitment and retention of military personnel.
Evidence from the military application of anthropometric approaches to
predict densitometrically determined body composition variables indicates
that models for predicting percent BE by using either skinfolds and body
circumferences (Clark, 1976) or neck and abdominal circumferences (Hodg-
don and Beckett, 1984a,b; Vogel et al., 1988) yield biased estimates of
body composition. That is, the equations overpredict body fatness for the
lean individuals and underpredict fatness for the obese. This bias or error
i]
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BODY COMPOSITION ASSESSMENT AND EVALUATION
189
may be attributed to either errors in the biological assumptions associated
with the densitometric and/or anthropometric methods, technical errors of
the measurements or a combination of these two factors.
One critical issue for establishing normative standards for the military
is ethnic or racial differences in body composition. There is accumulating
evidence that distinct differences exist in body composition both within and
among ethnic groups, and these observations indicate the need for race-
specific standards. To date, this approach has not been adopted, but it
appears to be necessary for the development and validation of useful body
composition prediction equations.
The potential impact of the problem of ethnic or racial differences in
body composition is magnified by the use of inadequate reference and can-
didate measurements of body composition. Currently, underwater weighing
or hydrodensitometry is the reference method used in body composition
surveys of military personnel to develop anthropometric models. This ap-
proach uses the two-compartment model to assess BF content (Lukaski,
19871. Unfortunately, bone mineral density or content is an unmeasured
variable that has the potential to significantly bias the BF estimate. Bone
mineral density, which has been shown to be greater in Blacks than in
Caucasians (Cohn et al., 1977), greater in men than women (Cohn et al.,
1977), and possibly reduced in Asians, has not been measured in any of the
previous surveys. Using extrapolations from data on children (Lohman et
al., 1984), the estimate of this error can be as high as 5 percent. Thus,
failure to correct body density measurements for individual differences in
bone mineral density can result in overestimates of BF.
With regard to the densitometric equipment used in previous surveys,
investigators should modify existing apparatus to perform measurements of
residual lung volume while the volunteer is immersed in the water. It is
well established that conditions such as obesity are associated with a signif-
icant reduction in lung compliance and reduced pulmonary ventilatory ca-
pacity (Bray et al., 1977~. The principal ventilatory variable that is reduced
is the expiratory residual volume, whether expressed as a whole number
or as a fraction of the vital capacity (Bartlett and Buskirk, 1983~. Because
this impairment appears to be a continuum over the range of body fatness
from lean to obese, it would be prudent to measure residual lung volume
rather than estimate it using standard equations or tables. Failure to do so
may result in an overestimation of body volume, an underestimation
of body density and an overestimation of BF (Lukaski, unpublished
observations).
The selection of appropriate anthropometric measurements (body cir-
cumferences and bone diameters) and skinfold thickness sites is a challeng-
ing process. However, the availability of a current reference manual (Loh-
man et al., 1988) should be useful. Nevertheless, an important issue is
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190
HENRY C. LUKASKI
the biological basis for using skinfold thicknesses and anthropometric
measurements.
Although measurements of bone diameters, limb circumferences, and
skinfold thicknesses have been used to derive prediction models for esti-
mating body density and percent BE, this approach has generally been limit-
ed by population-specific prediction models (Lukaski, 19871. This point
was recently reinforced by the findings of Hodgdon and Beckett (1984a,b)
and Vogel et al. (1988) with military groups.
The limitation of using skinfold thicknesses to predict BE is found in
the basic assumptions of this approach. It is generally assumed that the
subcutaneous adipose tissue reflects a constant proportion of the total body
adipose tissue and hence fat. Also, the sites selected for measurement
represent the average thickness of the adipose tissue and thus are the best
predictors of BF. Neither of these assumptions has been validated (Lukas-
ki, 1987~. Furthermore, the validity of such assumptions is dubious because
of the extremes in distribution of body adipose tissue in the population.
In addition to the theoretical limitations of using skinfold thicknesses
to predict BE, there also exist some practical concerns. The within- and
between-observer variability in determining skinfold thickness can be great-
er than 5 percent (Burkinshaw et al., 1973; Jackson et al., 1978~. Thus,
trained and certified specialists are required. In addition, most prediction
equations based on skinfold thicknesses are population specific (Edwards,
1951; Jackson, 1984; Lukaski, 1987~. These factors limit the use of skin-
fold thickness measurements for precisely and accurately estimating body
composition in the heterogeneous military population.
In contrast to the interobserver error in skinfold thickness measure-
ments, the measurement of body circumferences is more reliable (Lohman
et al., 1988~. Unfortunately, this approach still suffers from population
specificity in the development of prediction equations.
Statistical approaches for the development of prediction models need
some consideration. Using power analysis to assess sample sizes for various
racial groups based on estimates of both technical errors of the instrumenta-
tion and biological variability in the chemical composition of the fat-free
mass (FFM) would enhance the probability of developing valid prediction
equations. Furthermore, stepwise multiple regression analysis and factor
analysis are needed to describe the most important predictor variables in the
model.
An appropriate design for cross-validation of the candidate model is
also needed. It is necessary to develop the prediction equation in one
sample and then to cross-validate it in an independent sample. This ap-
proach has been used in previous cross-validation trials of equations de-
rived in military personnel (Hodgdon and Beckett, 1984a,b; Vogel et al.,
1988).
_
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BODY COMPOSITION ASSESSMENT AND EVALUATION
TABLE 11-4 Variability Estimates for Prediction Models and
Cross-Validation Trials for Estimation of Percent Body Fat in U.S.
Military Groups
Standard Error of
the Estimate (percent body fat)
Sex of
Source Sample Model Validation
Hodgdon and Beckett (1984a,b) Men 3.52 2.7*
Women 3.72 4.36*
Vogel et al. (1988) Men 4.02 3.7*
Women 3.60 4.4
*Statistically significant (p < 0.05) difference between predicted and measured
values.
191
Another statistical analysis that would be appropriate is a determination
of the directional bias of the error relative to the magnitude of the measured
and predicted variable. This approach for cross-validation of values whose
accuracy is unknown was proposed by Bland and Altman (1986~. It in-
volves the graphical representation of the residual scores plotted against the
mean of the measured and predicted values. This is the appropriate statisti-
cal approach for cross-validation of the derived model.
The variability of the distribution of the relationship between measured
and predicted percent BF values from the military trials using neck and
abdominal circumference measurements and height is summarized in Table
1 1-4. It is clear that the standard errors of the estimate of percent BF are
quite large and exceed the theoretical precision of the densitometric method
(Lohman, 1981~. These data indicate that the models are adequate for
assessments of percent BF in population groups but are inadequate for
individuals.
CONCLUSIONS AND RECOMMENDATIONS
Presently, the available anthropometric equations for estimating percent
BF in the U.S. military are not valid for assessing body composition of
individuals. This conclusion may be due to technical errors in the densito-
metric method, differences in the chemical composition of the fat-free body,
the lack of specificity of the anthropometric measurements used in the pre-
diction model, or a combination of these factors.
In retrospect, the major limitation of using regression equations to pre-
dict human body composition is the reliance on a mathematical equation
derived in one group to predict a variable in another individual who may be
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92
lIENRY C. LUKASKI
a member of another group. This approach is susceptible to factors that can
adversely influence its validity for estimating body composition of the indi-
vidual. If factors such as ethnic differences in the bone density and BE
distribution can be assessed and improvements in the technical measure-
ment of the body can be made, perhaps an improved and more sensitive
assessment and evaluation of body composition in the military population
can be achieved.
These difficulties can be addressed and controlled by the following
recommendations.
· Use current and technically accurate methods and equipment for den-
sitometry and anthropometry.
· Use a multicompartmental model of body composition, and include
measurements of bone mineral density (regional and total body) to correct
apparent whole body density obtained by underwater weighing.
· Use appropriate statistical methods to determine appropriate sample
sizes for model development and cross-validation. Calculations for sample
sizes need to include estimates of technical and biological variability of
measurements.
.
Use stepwise multiple regression analysis and factor analysis to de-
velop the prediction model.
· Establish the need or lack of need for race-specific prediction models.
· Ascertain the validity of the model or models to determine change in
body composition after weight loss.
· Establish practical and valid criteria for implementing the new modelts)
in the U.S. military environment.
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Representative terms from entire chapter:
composition assessment
