Does adipose tissue influence bioelectric impedance
in obese men and women?
RICHARD N. BAUMGARTNER,1 ROBERT ROSS,2 AND STEVEN B. HEYMSFIELD3
Nutrition Program, University of New Mexico School of Medicine, Albuquerque,
New Mexico 87131; 2Department of Physical and Health Education, Queen’s University,
Kingston, California; and 3Obesity Research Center, St. Luke’s-Roosevelt Hospital and
Columbia University College of Physicians and Surgeons, New York, New York 10025
1Clinical
obesity; magnetic resonance imaging; fat-free mass; body
mass index
BIOELECTRIC-IMPEDANCE ANALYSIS
(BIA) was first introduced as a method of estimating body composition ,10
years ago (14). Since then, use of the method has
become widespread in both clinical and epidemiological
research. Despite considerable experimentation and
theoretical advances, BIA remains something of a
‘‘black box’’ method of in vivo body-composition analysis. Technical and theoretical aspects of the BIA method
have been reviewed in detail elsewhere (1). In brief,
BIA measures the impedance, or ‘‘opposition,’’ of the
body to the flow of a low-amplitude, high-frequency
alternating electric current. Impedance is measured in
BIA by using a tetrapolar-bridge approach with separate current (source) and voltage (detector) electrodes
placed on the skin surface at standard anatomic locations. The current is introduced between the distally
located source electrodes, and the voltage drop caused
by impedance is measured between the dectector electrodes, which are typically situated ,5–20 cm proximal to their paired source electrodes. The phase shift
caused by the capacitive effects of cell membranes and
other dielectric materials is also measured and is used
to partition total impedance into resistance (R) and
reactance components in most BIA devices, although
some directly determine R and reactance separately.
Both R and reactance are frequency and temperature
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dependent. In the human body, .90% of the measured
impedance is composed of R. For this reason, as well as
others, most BIA applications use R, rather than impedance, to predict body composition (1).
The electrical charge of the current is conducted by
free electrolytes in the body fluids, and the R of any
specific body composition component is proportional to
the concentrations of fluids and mobility of ions in that
component. Thus R is low for blood, urine, and muscle
but high for adipose tissue, bone, and air, which contain
little or no fluid or electrolyte ions. Because the current
tends to follow the path of least resistance, measured R
correlates most strongly with total body water (TBW),
and correlations decrease for other body composition
components, depending on the amount of water in
these components. In vivo measurements of impedance, however, reflect the joint conductive properties of
all the materials within the total body volume (V) or
within the V of the arm, leg, or trunk when body
segments are measured separately. As a result, it is not
clear to what extent in vivo measurements of impedance directly reflect the V of specific components with
high conductivities or are influenced by other component V with lower conductivities (1).
In most applications, BIA is used to predict TBW and
fat-free mass (FFM). These components of body composition do not occupy discrete spaces within the body V
but are distributed in varying concentrations in body
tissues. Consequently, it is difficult, if not impossible, to
model these components as specific conductive paths
within the total body V. Muscle, adipose tissue, and
bone are components that constitute discrete, anatomic
volumes (Vm, Vat, and Vb, respectively). Although the
composition of these components, in particular their
fluid concentration, may vary within and between
individuals, they can be defined as discrete conductive
paths, or resistors, in an equivalent-circuit model as
shown in Fig. 1.
Several investigators have reported that bioelectric
impedance overestimates FFM in samples of obese
people (8, 9, 11, 12, 19, 20). These studies show that
residuals for the prediction of FFM by BIA are correlated significantly with percent body fat. Different
hypotheses have been advanced to explain this effect.
One is that hydration and/or fluid distribution in either
or both the nonadipose and adipose tissues is altered in
obesity and that the criterion methods used for calibrating prediction equations do not account for these
changes. Although some studies have shown that BIA is
sensitive to alterations in hydration and fluid distribution, there have been few, if any, good tests of the
0161-7567/98 $5.00 Copyright r 1998 the American Physiological Society
257
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Baumgartner, Richard N., Robert Ross, and Steven
B. Heymsfield. Does adipose tissue influence bioelectric
impedance in obese men and women? J. Appl. Physiol. 84(1):
257–262, 1998.—Bioelectric-impedance analysis overestimates fat-free mass in obese people. No clear hypotheses have
been presented or tested that explain this effect. This study
tested the hypothesis that adipose tissue affects measurements of resistance by using data for whole body and body
segment resistance and by using muscle, adipose tissue, and
bone volumes from magnetic resonance imaging for 86 overweight and obese men and women (body mass index .27
kg/m2; age 38.5 6 10.2 yr). In multiple-regression analysis,
muscle volumes had strong associations with resistance,
confirming that the electric currents are conducted primarily
in the lean soft tissues. Subcutaneous adipose tissue had a
slight but statistically significant effect in women, primarily
for the leg, suggesting that adipose tissue can affect measured
resistance when the volume of adipose tissue is greater than
muscle volume, as may occur in obese women in particular.
This resulted in a slight overestimation of fat-free mass
(e.g., 13 kg) when a bioelectric- impedance-analysis equation
calibrated for nonobese female subjects was applied.
258
ADIPOSE TISSUE AND BIOELECTRIC IMPEDANCE
Fig. 1. Parallel tissue-resistor model. This model considers a limb to
represent concentric cylinders of subcutaneous adipose tissue (SAT),
muscle, and bone that form a circuit of resistors in parallel when
conducting an electric current. Am, cross-sectional muscle area; Aat,
adipose tissue area; Ab, bone area; rm, resistivity (r) of muscle; rat, r of
adipose tissue; rb, r of bone.
SUBJECTS AND METHODS
The study group consisted of 40 male and 46 female
volunteers in an exercise-diet weight-loss program at the
School of Physical and Health Education, Queen’s University,
Kingston, CA (16). The mean age of participants was 38.5 6
10.2 yr. All participants had body mass indexes .27 kg/m2,
were weight stable (62 kg) for 6 mo before entry, and were
taking no medications known to affect body composition. The
data set analyzed represents baseline data collected before
initiation of the weight-loss protocol. The study was conducted in accordance with the ethical guidelines of Queen’s
University, and all participants gave informed consent.
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hypothesis that this explains specifically the overestimation of FFM in obese subjects (6).
A second hypothesis is that the tendency of BIA
equations to overestimate FFM in obese subjects is
caused by differences in body geometry. Some studies
have shown that measures of whole body R are dominated by the arms and the legs and depend strongly on
variation in the cross-sectional areas of the distal
extremities (3, 7). Lukaski (13) demonstrated empirically that the use of proximal, rather than distal,
electrode placements on the limbs reduced significantly
the correlation between percent body fat and FFM
residual scores. Despite this finding, there is no clear
theory that explains an association between body geometry and the tendency to overestimate FFM in obese
subjects.
A third hypothesis, which has not been tested, is that
the increased Vat in obese subjects directly affects the
measurement of R. This hypothesis has a theoretical
basis in the parallel tissue-resistor model as described
by Rush et al. (17), which predicts that adipose tissue, if
sufficiently large, will affect directly the measurement
of bioelectric R.
The present study attempts to test the third hypothesis by using a unique data set for body composition
from whole body magnetic resonance imaging (MRI)
scans, and also segmental and whole body measurements of bioelectric R and anthropometry, in 86 overweight and obese men and women.
Anthropometry. All body measurements were taken by
using standardized procedures as described in the Anthropometric Standardization Reference Manual (10). Weight was
measured to the nearest 0.1 kg on a beam-balance scale.
Stature, sitting height, and acromiale height were measured
to the nearest 0.1 cm with a wall-mounted stadiometer. Arm
length, defined as the distance from the anterior-lateral edge
of the acromion to the distal end of the third phalange, was
measured by using flexible steel tape on the right side to the
nearest 0.1 cm. The elbow and fingers were fully extended,
and the arm was abducted slightly from the side. Leg length
was derived as the difference between stature and sitting
height. Trunk length was calculated as acromiale height
minus leg length.
Bioelectric R. Bioelectric R was measured by using a model
101B BIA analyzer (RJL Systems, Detroit, MI) with an
operating frequency of 50 kHz at 800 µA. Whole body
measurements were taken by using standard electrode locations on the hand and foot on the right side when the
participant was fasting and had voided the bladder (14). The
R of the right arm and leg, as well as R of the trunk, were
taken by using the electrode placements described in Chumlea et al. (5). In brief, the R of the arm was measured with one
electrode pair placed in the conventional locations on the
posterior surface of the hand and wrist. The other pair of
electrodes was placed with the detector electrode on a line
from acromial process to the axillary fold, and the source
electrode was ,5 cm medial. The R of the leg was measured
with one electrode pair in standard location on the anterior
surface of the foot and the other at the level of the gluteal
crease. The R of the trunk was measured from the anterior
surface of the thigh at the gluteal crease to the sternal notch.
All R measurements were taken with the participant supine
and with the arms abducted slightly, but not touching the
sides, and with the legs separated so that there was no
contact between the thighs.
Whole body MRI. The protocol used to acquire the MRI
data for whole body and body-segment tissue V is described in
detail elsewhere (16). In brief, images were taken with a
Siemens 1.5-T whole body scanner (Erlangen, Germany). A
series of 41 10-mm-thick axial images were made at 50-mm
intervals from the tips of the extended fingers to the feet by
using a T1-weighted, spin-echo sequence with a 210-ms
repetition time and 15-ms echo time. Images for the abdomen
were obtained by using a rectangular field of view (192 3 256
pixels) and a one-half Fourier transformation. The use of
these parameters reduced the image-acquisition time for the
abdominal images to ,26 s, during which the participants
held their breath to minimize respiratory noise. The total
time to acquire all 41 images was ,25 min.
For each scan sequence, the participant lay prone inside
the magnet with the arms extended horizontally above the
head. The intervertebral space between L4 and L5 was located
from a sagittal scout scan and was used as the reference point
of origin. A set of images was then acquired at 50-mm
intervals superior from L4-L5 to the tips of the fingers. A
second set was then acquired similarly, working from L4-L5 to
the feet. The scan data were transferred to a stand-alone Iris
personal computer (Silicon Graphics, Mountain View, CA),
and tissue areas were measured by using interactive imageanalysis software, as described previously (16).
Tissue V were estimated by adding the V of truncated
pyramids defined by pairs of consecutive slices. Whole body V
were calculated by using all 41 slices. V for the arm, leg, and
trunk were calculated separately by using slices between
specific landmarks. V of tissue for the arm was calculated
with the use of slices extending from the hand to humeral
ADIPOSE TISSUE AND BIOELECTRIC IMPEDANCE
1/Req 5 1/R1 1 1/R2 1 1/R3
(1)
where R1, R2, and R3 correspond to the R of muscle, fat, and
bone tissues, as shown in Fig. 1. The standard assumption
applied in BIA is that the conductive V is related to R by the
equation V 5 rL2/R, where L is a measure of conductor length
Fig. 3. Theoretical effects of increasing adipose tissue and changes in
tissue r on measured R and estimation of muscle mass for leg. r,
Increasing SAT volume relative to muscle, with no change in r; s,
increasing SAT/muscle with decreasing rat caused by increased
hydration; j, increasing SAT/muscle with decreasing rm tissue
caused by increased hydration; l, increasing SAT/muscle with both
decreasing r of SAT and decreasing rm. Length, 70 cm; muscle
volume, 6 liters; rm, 300 V · cm; r of SAT, 3,000 V · cm.
and r is resistivity. Thus, 1/R 5 V/rL2, and Eq. 1 can be
rewritten as
1/Ro 5 Vm/rm L2 1 Vat/rat L 2 1 Vb/rb L2,
where Ro is the observed or measured R and rm, rat, and rb are
the specific r of these tissues, respectively.
To illustrate the theoretical potential effect of Vat in this
model, we generated the following simulation. Using data for
the leg, we assumed constant values for the parameters in Eq.
2 of L 5 70 cm, Vm 5 6 liters, rm 5 300 V · cm, rat 5 3,000
V · cm, and Vb/rb 5 0. The values assumed for rm and rat are
derived from our previous work (15) and from Brown et al. (4),
who suggest that rat is 10- to 12-fold greater than rm. The rb is
considered to be so great relative to Vb that, in any model,
this term should effectively approach zero. We then varied
Vat over a range from 100 to 166% of Vm and derived values
for Ro. These values were then inserted into an equation for
predicting leg Vm that assumed no effect of Vat on measured
R: Vm 5 (300 V · cm) 3 L2/R. Figure 3 shows that Vm is
overestimated by 6% when Vat is 1.6-fold greater than Vm
(Vat/Vm 5 9.6/6 5 1.60). This verifies that Vat can affect Ro as
calculated under Eq. 2, despite the large value of rat. Figure 3
also shows more extreme effects if changes in the specific rm
and rat are assumed to be caused by alterations in hydration
or fluid distribution with increasing adiposity. In sum, this
simulation predicts that the substantial Vat found in obesity
can affect measured R under the parallel tissue-conductor
model.
To test the hypothesis by using the MRI and BIA data, the
following regression equation was derived for the arm and the
leg based on Eq. 2
1/Ro 5 a 1 b1Vm /L2 1 b2Vat/L2 1 b3Vb/L2 1 e
Fig. 2. Equivalent-circuit model. Parallel tissue-resistor model in
terms of a simple electric circuit. V, voltage; I, current; Rm, muscle
resistor; Rat, adipose tissue resistor; Rb, bone resistor; I1, I2, and I3,
currents through each resistor in circuit.
(2)
(3)
where R, Vi, and L are defined as above; a is the intercept of
the multiple regression; b1-b3 are regression coefficients; and
e is random error (mean 5 0, SD 5 1). The null hypothesis
that b2 5 b3 5 0 was tested statistically at a 5 0.05.
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head. Calculations of V for the leg used slices from the foot to
femoral head. Both the humeral and femoral heads were
clearly visible on an image for most participants. The use of
these landmarks, however, resulted in the inclusion of some
shoulder or gluteal tissues in the estimates for the arm and
the leg, respectively. The separation of organ and skeletal
muscle tissues in the trunk is difficult because of the similarity of their pixel-intensity values and the anatomic complexity of this region. As a result, the quantification of muscle in
the trunk was more subjective.
The reliability of the MRI tissue-V estimates was assessed
by comparing duplicate measurements for two obese men. For
each man, two complete sets of 41 images were acquired on
the same day. The mean difference between lean tissue
(muscle) V calculated from these two sets was ,2%. The
mean difference for whole body Vat was ,4% (16).
Analytic models and methods. Body composition is measured by using MRI on what Wang et al. (21) have referred to
as the tissue-system level of organization. Thus it is important to keep in mind that the Vat, Vm, and Vb that are
measured from MRI scans do not correspond directly to fat
and fat-free soft-tissue and bone mineral masses on the
molecular level, as measured by using techniques such as
dual-energy X-ray absorptiometry. This distinction is important for the approach taken to analysis in the present study,
because the MRI tissue V fit better in the theoretical,
geometric model of parallel conductors described in Fig. 1.
Figure 1 models the arm or leg as a set of concentric
cylindrical conductors consisting of subcutaneous adipose
tissue (SAT), muscle, and bone. This model is really only
appropriate for the limbs. The torso is more complex anatomically, including intra-abdominal adipose tissue (IAT), gastrointestinal and digestive organs, heart, and lungs that cannot
be described in this simple model. Although the model in Fig.
1 is still an obvious oversimplification of the structure of the
limbs from an anatomic point of view, it is useful in the
context of bioelectric theory because it translates readily in
the equivalent-circuit model shown in Fig. 2.
In Fig. 2, the Vat, Vm, and Vb tissues are represented by
parallel resistors. For a circuit composed of resistors in
parallel, the total equivalent R (Req ) is determined by the
formula
259
260
ADIPOSE TISSUE AND BIOELECTRIC IMPEDANCE
Table 1. Anthropometric and bioelectric
impedance measurements
Men
(n 5 40)
Women
(n 5 46)
41.37 6 11.77
101.92 6 15.20
177.41 6 6.87
32.29 6 3.90
148.54 6 6.27
95.14 6 4.76
36.83 6 7.42
92.25 6 14.72
164.18 6 5.63
34.20 6 4.99
136.31 6 5.52
89.89 6 2.96
75.23 6 4.39
82.27 6 3.96
66.27 6 4.33
68.89 6 3.61
74.29 6 3.85
62.02 6 2.58
436.08 6 43.36
209.25 6 22.42
220.35 6 26.49
77.73 6 11.22
515.98 6 56.34
270.65 6 31.22
251.74 6 30.59
100.67 6 14.29
Characteristics
Age, yr
Weight, kg
Stature, cm
Body mass index, kg/m2
Acromiale height, cm
Sitting height, cm
Segment lengths, cm
Arm
Leg
Trunk
Resistance, V
Whole body
Arm
Leg
Trunk
Table 3. Results for multiple regressions of 1/R
on tissue volumes for body segments
Values are means 6 SD; n 5 no. of subjects.
RESULTS
Descriptive statistics (means 6 SD) for the anthropometric, bioelectric R, and MRI volume measurements
are shown in Tables 1 and 2. The mean body mass index
was 32.29 6 3.90 kg/m2 in the men and 34.20 6 4.99
kg/m2 in the women, verifying that the study participants were overweight or obese. The mean SAT volume
was 41 and 42% of the total volume of the arm and the
leg, respectively, in the men. The ratios of adipose
Men
(n 5 40)
P
b 6 SE
0.94 6 1.69
0.10 6 0.58
20.03 6 14.49
0.05
NS
NS
NS
2.83 6 0.84 ,0.002
0.01 6 0.26
NS
5.48 6 8.40
NS
0.29
2.82 6 0.44
20.22 6 0.16
7.19 6 3.68
0.50
,0.0000
NS
NS
0.75 6 0.29 ,0.001
0.30 6 0.16 (0.06)
2.51 6 2.83
NS
0.22
1.15 6 0.64
20.46 6 0.19
20.33 6 0.75
0.22
,0.07
,0.02
NS
11.06 6 5.80 (0.06)
211.55 6 5.74 ,0.05
20.84 6 0.90
NS
0.12
Values are means 6 SE; men, n 5 40; women, n 5 46; R, resistance;
NS, not significant; b, regression coefficient.
tissue to Vm in the men averaged 0.77 for the arm and
0.83 for the leg. In the women, SAT volume averaged
57% of total V of the arm and 54% of total V in the leg.
The ratios of Vat to Vm in the women averaged 1.47 for
the arm and 1.35 for the leg. In the men, 43% of total
trunk V was SAT and 12% was IAT. In the women, in
contrast, 29% of trunk V was SAT and 10% was IAT.
Thus adipose tissue constituted a substantial fraction
of the V of each body segment. In the women, SAT V
was substantially greater than Vm for the arm and the
leg and was well into the range in which an effect on
measured R would be expected under the parallel
tissue-resistor model.
Tables 3 and 4 show results for the multipleregression analyses of 1/R on the MRI tissue V, adjusted for segment length according to formula (2), for
the arm, leg, trunk, and whole body. Vm had statistically significant associations with 1/R, with the exceptions of the arm in the men and the trunk in both the
Table 4. Results for multiple regressions
of 1/resistance on tissue volumes for whole body
Table 2. MRI tissue volumes
Segment/Tissue
Arm resistance
Muscle
SAT
Bone
Total R 2
Leg resistance
Muscle
SAT
Bone
Total R 2
Trunk resistance
Muscle
SAT
IAT
Total R 2
P
value
b 6 SE
Women
(n 5 46)
Women
Men
Arm
Muscle
SAT
Bone
Leg
Muscle
SAT
Bone
Trunk
Muscle
Nonmuscle lean
SAT
IAT
2.68 6 0.32
2.07 6 0.87
0.29 6 0.04
1.81 6 0.31
2.66 6 1.05
0.17 6 0.03
8.74 6 1.23
7.23 6 2.79
1.14 6 0.15
6.16 6 1.21
8.33 6 2.23
0.81 6 0.16
10.49 6 1.99
15.06 6 2.24
14.59 6 6.31
4.03 6 1.55
7.26 6 1.36
15.11 6 1.61
7.25 6 1.36
2.44 6 0.95
Values are means 6 SD in liters; n 5 no. of subjects. MRI, magnetic
resonance imaging. SAT, subcutaneous adipose tissue; IAT, intraabdominal adipose tissue. Nonmuscle lean tissues include bone and
organ.
Segment/
Tissue
b 6 SE
P
b 6 SE
P
value
Model A: whole body resistance on body segments
Arm muscle
Leg muscle
Trunk muscle
Arm SAT
Leg SAT
Trunk SAT
Total R 2
20.88 6 0.59
0.66 6 0.23
0.11 6 0.10
0.31 6 0.25
0.03 6 0.12
20.02 6 0.03
0.39
NS
0.007
NS
NS
NS
NS
1.07 6 0.49
0.29 6 0.14
0.62 6 0.65
20.26 6 0.14
0.30 6 0.07
20.60 6 0.65
0.57
,0.03
,0.04
NS
NS
,0.0001
NS
Model B: whole body resistance on sums of tissue volumes
Total muscle
Total SAT
Total R 2
1.913 6 0.52
0.03 6 0.18
0.27
0.0007
NS
1.18 6 0.46
0.98 6 0.34
0.42
Values are means 6 SE; men, n 5 40; women, n 5 46.
,0.01
,0.006
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Similar regression models were constructed and tested for
the trunk and the whole body. Those for the trunk, however,
are recognized to have poor validity, because trunk anatomy,
as noted above, does not really fit the simplistic model of
parallel resistors formed by concentric cylinders of tissues.
Nonetheless, an important feature of these analyses is the
inclusion of IAT, as distinct from SAT. IAT was defined as the
sum of the visceral, pelvic, and thoracic (e.g., pericardial)
adipose tissues. Two different models were tested for the
whole body. In model A, 1/R for the whole body was regressed
on all of the segment muscle and Vat variables. In model B,
1/R was regressed on the sums of the segment muscle and
Vat.
Women
Men
Segment/
Tissue
ADIPOSE TISSUE AND BIOELECTRIC IMPEDANCE
1/R 5 0.00237 1 0.7519 (Vm/L2 )
1 0.2986 (Vat/L2 ) 1 2.5138 (Vb/L2)
Using the data in Table 1, we calculated R, assuming
L 5 74.29 cm, Vm 5 6.2 liters, Vb 5 0.8 liters, and
Vat 5 Vm. The calculated R 5 255.7 V was then used in
the equation (300 V · cm) 3 L2/R to calculate Vm 5 6.48
liters, or ,5% greater than the actual value. We then
recalculated R, assuming that Vat 5 1.6 3 Vm 5 9.86
liters. The calculated R was 243.3 V, or ,5% less, and
resulted in an estimated Vm 5 6.81 liters, or ,10%
greater than the actual value. To further illustrate the
effect, in Table 4, we estimated R values by using model
B for the whole body, first assuming Vat 5 Vm and then
Vat 5 1.6 3 Vm. The calculated R was 14.4% less when
Vat was assumed to be 1.6 3 Vm than when the V were
assumed to be equal.
Finally, we evaluated the effect of a 14% reduction in
measured R caused by the effect of adipose tissue when
applied to a standard model for estimating FFM. One of
Lukaski’s equations for women (13) has been given as
FFM 5 0.473(stature2/R) 1 0.265(weight) 1 3.54
where R is whole body R. When the mean values
reported in Table 1 for stature, R, and weight in the
women are inserted into this equation, the resulting
estimated FFM is 52.6 kg and percent body fat is ,43%.
If we assume that R is reduced by the effect of adipose
tissue and recalculate FFM by using an R value that is
14% greater, the resulting estimated FFM is 49.56 kg,
corresponding to ,46% body fat.
DISCUSSION
The results of the present study suggest that adipose
tissue, when sufficiently large, may directly affect
measured R. This effect on R may result in an overestimation of muscle, lean soft tissue, or FFM when
equations are applied that are calibrated by using data
for nonobese, lean individuals. These effects are normally small, but they increase rapidly when the Vat is
greater than Vm, as is the case in many persons with
moderate to severe obesity.
The present study confirms for the first time that,
from a simple body-composition model, the primary
conductor in the bioelectric impedance method is appendicular skeletal muscle. Leg Vm in men and arm and
leg Vm in women were correlated significantly with the
R for the arm and the leg, as well as the for whole body.
At this time, there is no clear explanation why arm Vm
was not significantly associated with arm or whole body
R in the men. The lack of association was not attributable to the presence of one or more unusual data points
or outliers.
SAT on the trunk was associated significantly with
the measurement of trunk R in both sexes. These
results, however, should be considered with caution,
because the parallel-tissue resistor model lacks validity
for this body segment. Nonetheless, these findings for
the trunk could help explain why the specific measurement of trunk R is greater than is theoretically expected and why trunk phase angle (ratio of reactance to
R) is correlated with percent body fat (2, 3, 7, 13). In
addition, this may pose a major limitation to the
segment-impedance approach, because unbiased specific r for the trunk cannot be estimated with confidence
from measurements of trunk R. It is important to note
that neither trunk Vm nor Vat significantly influences
whole body R. This suggests that the composition of the
trunk is of relatively little concern in the conventional
BIA approach to estimating body composition by using
whole body R. As noted previously, the electrical conductive characteristics of the limbs are reported to primarily determine the use of BIA in predicting body composition (3, 7). However, Scheltinga (18) has noted that
measurements of the trunk should be taken without
moving the source electrodes (i.e., leaving them in their
distal locations). It is possible that the use of this
method would have improved results for the trunk.
A considerable portion of the variability in measured
R was not explained by volumetric composition. This
suggests that other factors contribute importantly to
bioelectric R over and above the relative volumes of
more- or less-conductive tissues and their errors of
measurement. These factors probably include physiological and structural variables, such as body temperature, tissue composition, and fluid distribution, as well
as anisotropic effects of muscle fibers. Technical factors
affecting the accuracy of the measurement of resistance
also must be studied.
It is important to consider some of the limitations of
the model used in the present study. The model considers measured R in terms of parallel R offered by the
major tissue V. Each tissue V, however, is composed of
more basic constituents at cellular or chemical levels
that may or may not be modeled in terms of parallel R
circuits. In addition, tissues have different structural
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men and women. SAT V for the trunk were associated
significantly with trunk R in both sexes. The association of leg SAT V with leg R approached statistical
significance (P , 0.06) in the women. Leg SAT and total
SAT were associated significantly (P , 0.05) with whole
body R in the women. IAT was not associated significantly with either whole body or body-segment R in any
of the regression models. Vb were not associated significantly with 1/R for any of the body segments or the
whole body. The variance explained by the combined
tissue V ranged from 5% for the arm to 50% for the
trunk in the men and from 12% for the trunk to 29% for
the arm in the women. The combined segment tissue V
explained 39–57% of the variance in whole body R in
the men and women, respectively, in model A; and the
sums of the tissue V explained 27–42% of whole body R
in model B. Correlations between the length-adjusted
muscle and SAT V were small (r , 0.25). Thus these
results are not distorted by high multicollinearity
among the variables.
We further evaluated the magnitude of the effect of
SAT on R by using the regression equations and data
for the leg and the whole body in the women. The full
regression equation for the leg in women was
261
262
ADIPOSE TISSUE AND BIOELECTRIC IMPEDANCE
This work was supported by Natural Sciences and Engineering
Research Council of Canada Grant OGPIN 030, by Canadian Fitness
and Lifestyle Research Institute Grant 951R057 (to R. Ross), and by
National Institutes of Health Grants R01-AG-08510 (to R. N.
Baumgartner) and P01-DK-42618 (to S. B. Heymsfield).
Address for reprint requests: R. N. Baumgartner, Clinical Nutrition Program, 215 Surge Bldg., 2701 Frontier Pl., University of New
Mexico School of Medicine, Albuquerque, NM 87131 (E-mail:
[email protected]).
Received 4 November 1996; accepted in final form 27 August 1997.
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characteristics that may affect R. For example, skeletal
muscle fibers can produce anisotropic effects on R.
Moreover, reactance was not considered in the equivalent-circuit model, although reactance is small relative
to R in biological conductors (1).
It is not known how variability in the composition of
different tissues affects their specific r. For example,
although the increase in Vat in obesity is primarily
caused by the increased amounts of lipid deposited
within the adipocytes, there is controversy as to whether
the concentration of water in adipose tissue changes
with the expansion of V (15). An increase in the
concentration of water with increasing Vat would be
expected to lower the r of this tissue. In the parallel
tissue-resistor model, an increased Vat with a reduced r
would be predicted to have an even greater effect on
total measured R. An expanded adipose tissue mass
might also be associated with changes in the distribution of fluid and electrolytes within muscle, altering its
r. There is no way of testing this hypothesis with the
present data; however, our model predicts that changes
in muscle r would have much greater effect on measured R than observed in the present study, as illustrated in Fig. 3.
In summary, the results of the present study suggest
that the measurement of bioelectric R may be affected
by adipose tissue and that these effects may explain the
slight overestimation of FFM, and subsequent underestimation of percent body fat, that has been observed in
obese subjects. Insofar as the results of the present
study have validity, it may not be possible to eliminate
this effect of adipose tissue by using the current equipment. This effect, however, appears to be slight and
occurs only for moderately to severely obese subjects.
BIA can be used in most applications with confidence
that the true conductive V is muscle and that estimates
are relatively unbiased by adipose tissue. Thus, the
BIA method may be used to predict Vm and muscle
mass with high validity, although the precision of the
estimates remains to be established. Further research
needs to be conducted to determine the best approaches
for reducing the slight bias produced by the effect of
adipose tissue on measured R in obese women.