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OCR for page 175
Body Composition and Physical Performance 1992.
Pp. 175-184. Washington, D.C.
National Academy Press
10
Body Composition, Morbidity,
and Mortality
William Cameron Chumiea and Richard N. Baumgartner
INTRODUCTION
Relationships among body composition and morbidity and mortality are
complicated by several factors, including the accuracy and reliability of
methods of measuring body composition and the effects of age, gender,
race, genetic, environmental (for example, altitude, climate), and behavioral
(for example, diet, smoking) factors. In discussing measures of body com-
position, it is helpful to distinguish criterion from prediction methods, and
direct measures from indirect estimates. Criterion methods measure physi-
cal properties, chemical or anatomical constituents that are either direct
measures of well-defined components (for example, total body water from
deuterium dilution space), or they can be used to calculate indirect esti-
mates of other components of body composition (for example, percent body
fat [BF] from total body water). Prediction methods are generally based on
measurements of less specific aspects of the body, such as circumferences,
skinfold thicknesses, or bioelectric impedance. These variables must be
used in equations that are calibrated against values from criterion methods.
In the selection of criterion or prediction methods, consideration should be
given as to what aspect of body composition is to be related to a disease.
METHODS OF MEASURING BODY COMPOSITION
Underwater weighing, from which body density is derived, continues to
be considered the "gold standard" among the indirect criterion methods of
175
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76
WILLIAM CAMERON CHUMLEA AND RICHARD N. BAUMGARTNER
estimating body composition, despite long-standing recognition of its limi-
tations (Sir), 1961~. Other indirect criterion methods include potassium 40
counting, total body water from tritium or deuterium dilution, and total
body carbon from neutron activation. In addition to technical errors of
measurement, which are considered to be random, these methods may be
subject to nonrandom and/or systematic errors due to deviations of individ-
uals from the assumed proportionality values for body composition associ-
ated with age, gender, race, and other factors. These errors can distort as
well as attenuate associations with morbidity or mortality.
In addition to technical errors of measurement, methods of predicting
body composition also contain sampling errors, as well as errors associated
with the limitations of the criterion method selected for calibration. The
most commonly used prediction methods at present employ anthropometry
and bioelectric impedance. Equations for predicting fat-free mass (FFM)
and total BE using anthropometric and bioelectric variables have been de-
veloped for young or middle-aged adults, many of which may be appropri-
ate for use with military personnel (Barillas-Mury et al., 1987; Baumgartner
et al., 1989; Chumlea et al., 1988; Hodgdon and Fitzgerald, 1987; Lukaski
et al., 1985; Lukaski and Bolonchuk, 1987; Segal et al., 1985; Zillikens and
Conway, 19871. However, most of these prediction equations have not been
cross-validated properly to determine their accuracy when applied to popu-
lations other than the ones used in development (Guo et al., 19894.
Methods such as neutron activation, computed tomography (CT), dual
photon absorptiometry (DPA), and magnetic resonance imaging (MRI) are
invasive or require cumbersome, expensive equipment and specialized per-
sonnel. As a partial result of these problems, reported reference data for
these measures of body composition and their associations with risk factors
are limited. CT and MRI are most useful as methods of regional body
composition analysis and are among the only methods currently available
for quantifying amounts of intraabdominal adipose tissue for which there
may be considerable risk for several endocrine and metabolic diseases (Baum-
gartner et al., 1987; Kvist et al., 1986; Larsson et al., 1984~. In contrast to
CT, MRI does not involve exposure to ionizing radiation and is associated
with little risk. MRI spectroscopic techniques can provide important infor-
mation regarding the chemical composition as well as anatomical distribu-
tion of muscle and fat.
Photon absorptiometry is an accurate method of quantifying bone min-
eral density and for estimating total body mineral and skeletal mass. Accu-
rate estimates of bone mineral density and total body bone mineral are
needed to adjust equations for estimating BE from body density. The cur-
rent equations are subject to systematic errors since they assume that bone
density and the proportion of FFM that is bone are constants, despite evi
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BODY COMPOSlTlON, MORBlDlTY, AND MORTALITY
177
dence for their variability with factors including gender, ethnicity, and age
(Lohman, 19864. Presently, there is a paucity of information on bone densi-
ty for non-White individuals. DPA has the capability of directly estimating
soft tissue composition for the whole body or body segments. The recent
development of dual-energy x-ray absorptiometry (DEXA) with whole body
scanning at relatively low cost may make this an important criterion method
for body composition in the future (Mazess et al., 19841.
There are many methods of measuring body composition, and the choice
depends upon the experimental setting. Briefly, in a field setting one is
generally limited to anthropometry, that is, skinfolds and circumferences,
possibly some limited densitometry equipment, body water estimates de-
pending on access to a laboratory for analysis, and more recently bioelectric
impedance. All of these methods can have large measurement errors or
limited specificity depending on the sample studied. For example, in young
adults, the present gold standard of underwater weighing is estimated to
have at best, a minimum residual error of 2.5 percent for estimates of per-
cent BE (Behnke and Wilmore, 19741. This error, however, is likely to be
greater in most settings because the accuracy of underwater weighing de-
pends on the performance of the subject and the quality of the equipment.
The use of an easily accessible water tank and a stable seat or platform
suspended from load cells rather than spring scales will improve perfor-
mance and accuracy of underwater weighing. If validated, DEXA could be
the method of choice in the future, because it can provide both regional and
whole body estimates of fat, lean mass, and bone mass at a relatively low
cost. Because DEXA is passive and involves very low exposure to ionizing
radiation, it is appropriate for repeated observations.
ACCURACY OF MEASUREMENTS
Body composition can be measured with increasingly greater accuracy
than in the past. However, we are still hampered by the way measurement
values are converted into amounts of bone, muscle, and fat. A major con-
cern in this area is the validity of the assumptions underlying estimates of
body composition. To date, most studies of body composition have used
the simple two-compartment model or Siri's equation (19611. This equation
divides the body into fat and FFM on the basis of body density from under-
water weighing. Siri's equation is based on the assumptions that the densi-
ties of fat and FFM are 0.9 g/ml and 1.10 g/ml, respectively (Pace and
Rathburn, 19451. The density of fat varies little among individuals across
age, but the density of FFM can vary substantially among individuals de-
pending on the relative proportions of its constituents, mainly water, pro-
tein, and osseous and nonosseous mineral and the age of the person (Lohm
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78
WILLIAM CAMERON CHUMLEA AND RICHARD N. BAUMGARTNER
an, 19861. A variation of plus or minus 0.02 g/ml away from the assumed
value of 1.10 g/ml for the density of FFM can translate into an error of plus
or minus 5 percent BE for an individual with a body density of 1.05 g/ml.
These errors can be compounded due to reported greater variations in body
water amount and bone mineral content among individuals with differences
in age, race, and gender, which affect body density. Also, individuals who
are physically fit tend to have higher bone mineral content and as a result,
may have artificially low percent BE values when calculated using Siri's
equation.
USING A FOUR-COMPARTMENT MODEL
FOR STUDIES OF BODY COMPOSITION
The problems of estimating body composition can be improved by using a
four-compartment model, which is now considered necessary for studies de-
termining body composition. The equation for this model is as follows:
1/D = F/df + TBW/dw + B/db + C,
where 1/D is the sum of the volumes (fractions of weight/density) for fat
(F), total body water (TBW), total bone mineral (B) and protein plus
small amounts of nonosseous mineral and glycogen (C).
In comparison to the two-compartment model, the volume of FFM is
broken into three constituents: water, bone mineral, and protein. Other
nonosseous minerals and carbohydrates that are only a small fraction of
FFM (about 1.5 percent in young adults) are lumped together with the
protein fraction. Water is the largest fraction of the fat-free body and is
assumed to be about 73 percent of the fat-free volume in young adults.
However, studies show that this percentage is somewhat higher in women
and increases with levels of adiposity (Noppa et al., 1980; Pierson et al.,
1982; Steen et al., 1977, 1979~. An increase in the amount of water will
decrease the overall density of the FFM, but an increase in bone mineral
content will increase the density. The fraction of FFM composed of pro-
tein, nonosseous mineral, and carbohydrate is assumed to be relatively con-
stant, but because of changes in these body tissues, such as an increase in
connective tissue with age, and possible gender and racial differences, this
assumption may be questionable. Before this model can be applied widely,
however, it is necessary to establish the amount of difference among gender
and racial groups that exists in the densities of the body components. With-
out this information, estimates or predictions of body composition will be
subject to significant errors of unknown magnitude when applied to unrep-
resentative samples. Thus, our knowledge of body composition is limited
when applied to women or members of non-White racial or ethnic groups.
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BODY COMPOSITION, MORBIDITY, AND MORTALITY
ASSOCIATIONS AMONG BODY COMPOSITION,
DISEASE AND DEATH
Bone
179
Until recently, bone has been the largest unknown in body composition
due to our inability to quantify it accurately and noninvasively. The associ-
ations among bone and disease or death are not ones that usually affect
individuals in the age range of most military personnel. With the use of
DEXA, however, the potential exists for identifying young adults with low
or falling amounts of bone mineral content or bone density who are at risk
for osteoporosis or fractures due to physical stress in their military occupa-
tional specialty.
Fat-Free Mass
Differences between individuals in the quantity and quality of FFM
result in variations in physical ability and performance. However, there is
little or no information that associates FFM with disease or death except for
the changes that occur during weight loss or in association with eating
disorders. With greater numbers of women in the military, the incidence of
eating disorders and dieting problems could be expected to increase. These
problems can be associated with potentially harmful losses of FFM in some
individuals. Individuals who gain FFM or attempt to lose BE should be
made aware that changes in FFM are accompanied by concurrent and corre-
sponding changes in adipose tissue. The link in these changes may be due
to the extragonadol aromatization of androgens to estrogens in muscle as
well as adipose tissue (Segal et al., 19871.
Excess Adipose Tissue
The vast majority of the associations among body composition and
morbidity and mortality relate to excess adipose tissue or fat. The main
impact of these associations tends to be on the cardiovascular system, al-
though the effects on an individual can be modified or compounded by
environmental and genetic factors. Fat or lipid is a pervasive component of
the body, but in regard to morbidity and mortality, it can be viewed more in
terms of amounts and distribution of adipose tissue and of-the concentra-
tions of various lipid molecules in the blood. High concentrations of total
cholesterol, triglycerides, and the low-density lipoproteins are significantly
associated with the occurrence of cardiovascular disease and increased risk
of death due to myocardial infarction or stroke (Angel and Roncari, 1978;
Bray, 1987; Hubert et al., 19831.
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180
WILLIAM CAMERON CHUMLEA AND RICHARD N. BAUMGARTNER
Adipose tissue is either subcutaneous or internal. The location of the
tissue may be associated with the type of lipid stored, the metabolic activity
of the tissue, the size and number of adipocytes, its response to diet and
age, and its ease of measurement (Bray, 1987; Kaplan, 1989~. The amounts
and distribution of subcutaneous and internal adipose tissue are related to
an individual's risk for cardiovascular disease, diabetes mellitus, hyperten-
sion, and some forms of cancer (Haines et al., 1987; Kaplan, 1989; Larsson
et al., 1984; Selby et al., 1989; Shimokata et al., 1989; Sparrow et al.,
1986~. Many of these associations are confounded by the effects of smok-
ing, diet, levels of physical activity, and genetic susceptibility.
Measuring Body Fat
The simplest measure of BF is weight. Individuals with above normal
weights for their age and stature tend to have greater than normal levels of
BF either in absolute amounts or in the percentage of the body that is fat
(percent BF). These individuals are considered overweight and obese, but
there can also be individuals who are overweight and not obese and individ-
uals who are not overweight but are obese. Other convenient measures or
indices of obesity are weight over stature squared or the body mass index
(BMI), skinfold thicknesses, and ratios of body circumferences. There are
numerous reports of the statistical relationships between body weight, rela-
tive weight, skinfold thicknesses, weight for stature, or the BMI and risk for
cardiovascular disease. In most of these analyses, the data have come from
large population studies such as Framingham, the first and second National
Health and Nutrition Examination Surveys and several large insurance in-
dustry studies (Donahue et al., 1987; Hubert et al., 1983; Keys, 1989; Neser
et al., 1986; Selby et al., 19891. All of these indices, however, do not have
the same relationships with risk for disease or death. There is still some
controversy depending on the measurement used, on the person's age, and
on smoking habits. Those individuals with extreme levels of BMI are at
risk, and those individuals with significant weight gains are at increased
risk. Recently, Segal and coworkers (1987) reported that weight and BMI
are not as important for the individual as it would appear. Weight and BMI
are useful measures to describe levels of obesity indirectly in large samples,
but for the individual, the amount and distribution of total BF is indepen-
dently related to cardiovascular disease risk factors (Segal et al., 19871.
Distribution of Body Fat in Adults
Vague (1956) first reported that in adults the pattern of adipose tissue
distribution differed by gender and that the masculine distribution was more
closely related to endocrine and metabolic diseases. In the early 1980s,
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BODY COMPOSITION, MORBIDITY, AND MORTALITY
181
these facts were noticed again by Kissebah and coworkers (1982) who relat-
ed the adipose tissue distribution or the waist-hip ratio to levels of cardio-
vascular risk. This ratio attempts to describe an individual with a large
waist circumference compared to a small hip circumference, that is, the
masculine type, with the converse consisting of large hips to a small waist,
or the feminine type. The masculine type or centripetal form tends to be
produced by large deposits of internal adipose tissue, while the feminine
type is due to large deposits of subcutaneous adipose tissue. This simple
difference between internal and subcutaneous adipose tissue deposits is also
related to differing levels of risk. The masculine or centripetal pattern is
strongly associated with increased glucose intolerance resulting in non-in-
sulin-dependent diabetes, heart disease, hypertension, and stroke and an
increased risk for premature mortality (Bray, 1987; Donahue et al., 1987;
Haines et al., 1987; Larsson et al., 1984; Seidell et al., 1985; Selby et al.,
1989~. Individuals with the masculine pattern tend to have increased con-
centrations of saturated fat within the internal adipose tissue deposits, high-
er triglycerides, and lower high-density lipoprotein (HDL) cholesterol blood
levels regardless of their gender (Baumgartner et al., 1987; Kaplan, 1989;
Leclerc et al., 1983; Sedgwick et al., 1984; Segal et al., 1987; Wing et al.,
19891. It has also been observed that smokers, even though they may be
thin, have a greater waist-to-hip ratio than do nonsmokers who may have
higher body weights. Upon the cessation of smoking, the body configura-
tions of the smokers tend to move toward that of the feminine pattern with a
smaller waist-to-hip ratio (Shimokata et al., 1989~.
The primary problem with the use of the waist-hip ratio has been in
measuring the circumferences at accepted locations. Much of the literature
is confusing because someone's waist measurement is someone else's hip
measurement. If the ratio is to be used, suitable landmarks for the measure-
ments need to be identified and adhered to strenuously. Fortunately, the
association between waist circumference and internal adipose deposits has
been confirmed by computed tomography (Baumgartner et al., 1988; Kvist
et al., 1986~. The increased availability of MRI combined with spectro-
graphic analysis will provide further detail about the amounts and chemical
content of internal adipose tissue. Thus, it appears that one of the major
problems of BE and disease is primarily one of the deposition of internal
adipose tissue. Upper body, centripetal, or masculine type of adipose tissue
deposition is the major contributor to the risk of overweight or obesity.
With weight reduction, and corresponding decreases in the amounts of in-
ternal adipose tissue, many of the risks for cardiovascular disease are re-
duced accordingly.
Much of the work relating fat patterning and risk for disease has in-
volved White women. There are only a few studies of men or Blacks
except what has been reported from the national health surveys. There are
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82
WlLLlAM CAMERON CHUMLEA AND RICHARD N. BAUMGARTNER
possible ethnic or racial differences in the levels of thresholds for risk or in
the patterning of adipose tissue. These differences are being explored in
Mexican-Americans where the waist-hip ratio is the preferred measure, but
skinfold thickness ratios may be significant (Haffner et al., 1986, 1987;
Reichley et al., 19871. Because of the diverse ethnic background of U.S.
military personnel, the use of any single criterion for risk should be dis-
cussed carefully.
SUMMARY
Body composition is an interdependent, multifaceted quantity. It is not
yet possible to describe and quantify the tissues in the body with consistent
levels of accuracy. It is hopeful that in the near future this goal will be
attained in laboratory settings, but clinical or field procedures may remain
relatively inaccurate and subject dependent. One can, however, determine
when the distribution of tissues in the body's composition shifts toward a
greater-than-normal level of fat or adipose tissue. In an individual with
such a condition, the risk for disease and early death increases, but the
magnitude of the shift relative to the threshold for the increased risk is
affected by the age, gender, race, and living habits of the individual. Some
of this change may be a normal manifestation of age, but it is evident that
increased amounts of internal adipose tissue in the abdomen put one at the
greatest health risk.
ACKNOWLEDGMENT
This work was supported by Grant HD-12252 and AG-08510 from the
National Institutes of Health, Bethesda, Maryland.
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Representative terms from entire chapter:
adipose tissue
