International Journal of Obesity (1998) 22, 243±249
ß 1998 Stockton Press All rights reserved 0307±0565/98 $12.00
Bioelectrical impedance analysis to assess body
composition in obese adult women: The effect
of ethnicity
JM Jakicic, RR Wing and W Lang
University of Pittsburgh School of Medicine, Pittsburgh, USA
OBJECTIVE: To examine whether the accuracy of bioelectrical impedance analysis (BIA) to estimate body composition
in overweight women is affected by the ethnicity of the individuals.
DESIGN: Cross-sectional design to compare body composition estimated by BIA to body composition measured by
dual energy x-ray absorptiometry (DEXA), which was the reference method.
SUBJECTS: One hundred twenty three overweight women participated in this study, of which 43 women were
African-American (aged 37.2 5.6 y; BMI, 32.3 4.9 kg/m2) and 80 were Caucasian (aged 36.1 5.7 y; BMI,
31.9 3.5 kg/m2).
MEASUREMENTS: Body composition was estimated from BIA using both a generalized and an obesity-speci®c
equation. These estimations were compared to body composition measured by DEXA, which was the reference
method.
RESULTS: The generalized BIA equation underestimated lean body mass (LBM) by 2.6 3.1 kg in Caucasian women
and 0.4 3.2 kg in African-American women, with the difference between the ethnic groups being signi®cant
(P < 0.001). The obesity-speci®c equation underestimated LBM in Caucasians by 0.9 3.1 kg and overestimated
LBM in African-Americans by 1.2 2.8 kg (P < 0.001). An ethnic-speci®c equation is proposed, and cross-validation
of this equation indicates that it provides a reasonable estimate of body composition in overweight women.
CONCLUSIONS: The accuracy of BIA to estimate body composition appears to be affected by the ethnicity of the
individual. Therefore, an ethnic-speci®c equation for overweight women is proposed. However, further validation of
this prediction model in an ethnically diverse population is necessary.
Keywords: overweight; lean body mass; percent body fat; dual-energy x-ray absorptiometry; African-American
Introduction
Bioelectrical impedance analysis (BIA) is an appealing method of estimating body composition because it
is simple, quick and noninvasive, compared to other
techniques that require expensive equipment (for
example, dual energy x-ray absorptiometry
(DEXA)), skilled laboratory personnel (for example,
anthropometrics, hydrostatic weighing), or a very
cooperative participant (that is, hydrostatic weighing).
Signi®cant correlations have been reported between
percent body fat assessed from BIA and both hydrostatic weighing1,2 and DEXA.3,4 The standard error for
estimating (SEE) percent body fat using empirically
derived equations provided by the manufacturer of the
BIA device has been shown to be approximately
6%.1,2 However, the use of age, gender and fatness-
Correspondence: John M Jakicic, University of Pittsburgh
School of Medicine, 3811 O'Hara Street, Pittsburgh, PA 15213,
USA.
Received 14 February 1997; revised 26 June 1997; accepted 15
October 1997
speci®c equations may enhance the accuracy of the
BIA method to estimate body composition.5,6 For
example, using population-speci®c equations, Rising
et al2 have reported a SEE of 3.2% for estimating
percent body fat in Pima Indians. Furthermore, Stolarczyk et al7 have reported that the SEE decreased
from 8.1 kg to 2.6 kg when a population-speci®c
equation was used to estimate lean body mass in
Native American women.
Despite the development of age, gender, fatness and
population-speci®c equations (for example, Native
Americans, Pima Indians), the majority of studies
that have examined the accuracy of BIA have used
Caucasians.8 Kuczmarski9 has indicated that the lack
of valid and reliable ethnic-speci®c BIA predictionequations limits the usefulness of BIA data collected
in studies that include an ethnically diverse sample
(for example, National Health and Nutrition Examination Survey). For example, few studies have examined
whether BIA can accurately estimate body composition in African-Americans. Since there are differences
in bone mineral density between Caucasians and
African-Americans,10 these differences may have a
signi®cant impact on the measurement of lean body
mass (LBM) using BIA. Consequently, it may be
appropriate to examine the accuracy of BIA compared
Ethnicity and bioelectrical impedance analysis
JM Jakicic et al
244
to DEXA as the reference method, because of the
ability of DEXA to measure both LBM and bone
mineral content (BMC).
Therefore, the purpose of this study was to examine
the effect of ethnicity (Caucasians vs African-Americans) on the accuracy of BIA in estimating body
composition in obese adult females, using DEXA as
the reference method.
Methods
Subjects
One-hundred twenty three overweight women (43
African-American and 80 Caucasian) participated in
this study. All subjects were aged 25±45 y and at least
20 pounds over their ideal body weight according to
the Metropolitan Life weight tables.11 Subject characteristics are presented in Table 1. Subjects were not
taking prescription medication that could affect body
weight (for example, synthroid) or ¯uid balance (for
example, diuretics), nor did they have any metabolic
condition that could affect the results of this study. In
addition, subjects were excluded if they were currently pregnant or had been pregnant within the
previous six months. All subjects gave written
informed consent and all procedures were approved
by the Institutional Review Board at the University of
Pittsburgh prior to beginning this study.
Assessments
Weight and height. Weight was measured to the
nearest 0.25 pounds using a calibrated medical balance-beam scale (Health-O-Meter, Bridgeview, IL),
with subjects wearing a light-weight hospital gown
and no shoes. Height was measured to the nearest
0.1 cm using a calibrated stadiometer (Perspective
Enterprises, Kalamazoo, MI).
DEXA. A Lunar DPX-L densiometer (Madison,
WI) was used to assess body composition in all subjects,
and this was considered the reference method in this
study. DEXA provides an assessment of fat mass, LBM,
percent body fat and BMC. LBM can be computed to
include BMC (LBMtotal) or not to include BMC
(LBMtissue). Subjects were clothed in a light-weight
hospital gown and all jewelry was removed prior to
the DEXA scan being performed. A urine pregnancy test
(hCG, Abbott Laboratories, Abbott Park, IL) was performed immediately prior to the scan. Women with a
positive pregnancy test were excluded from this study.
Each total body scan was performed at the scanning
mode recommended by the manufacturer, with radiation
exposure ranging from 0.02±0.06 mRem depending on
the scanning mode used. Scanning mode was determined according to the thickness of the trunk region,
with a thickness of < 22 cm, 22±28 cm or > 28 cm
corresponding to a fast (10 min), medium (20 min) or
slow (37 min) scanning mode, respectively. The scans
were analyzed using Lunar DPX-L software version 1.3.
Test-retest using DEXA to assess body composition in
our laboratory has shown a difference (mean standard
deviation) of 0.23 0.26% for percent body fat,
0.26 0.18 kg for fat mass, 0.12 0.10 kg for LBM
and 0.02 0.02 kg for BMC. For these test-retest measurements, scans were performed on the same day, with
the subject removed from the DEXA and repositioned
between tests.
BIA. Measurement of LBM using BIA was performed on the same morning as DEXA. A RJL BIA101A (RJL Systems, Inc., Clinton Twp, MI) four
terminal impedance analyzer was used to measure
resistance and reactance to a maximum constant
current of 500 microamps at a frequency of 50 kHz.
This instrument was calibrated throughout the study
using a 500-O resistor according to the procedures
recommended by the manufacturer. Subjects were
instructed to fast (except for normal water intake)
and abstain from vigorous exercise for 12 h prior to
this evaluation. BIA was assessed with subjects in a
supine position. The skin surface was cleaned using
rubbing alcohol prior to applying Unitrac disposable
electrodes. Once the alcohol on the skin surface dried,
electrodes were placed on the right side of the body at
Table 1 Descriptive characteristics of subjects (mean standard deviation)
Age (y)
Height (cm)
Weight (kg)
BMI (kg/m2)
Resistance
Reactance
DEXA measurements
Percent Body Fat (%)
Fat Mass (kg)
LBM (kg)
Tissue
BMC (kg)
Total
(n ˆ123)
Caucasians
(n ˆ 80)
African-Americans
(n ˆ 43)
36.5 5.7
164.7 6.2
87.4 11.0
32.1 4.0
504.0 61.8
58.9 9.6
36.1 5.7
164.3 6.2
86.3 10.0
31.9 3.5
504.3 58.9
58.6 7.3
37.2 5.6
165.5 6.1
89.5 12.6
32.3 4.9
502.9 67.6
59.7 13.0
42.7 4.9
37.2 8.1
43.2 4.7
37.2 7.4
41.6 5.2
37.1 9.3
47.7 4.8
2.6 0.3
46.6 4.4*
2.5 0.3*
49.8 4.8*
2.7 0.3*
* Indicates signi®cant difference between Caucasians and African-Americans at P < 0.001.
BMI ˆ body mass index; DEXA ˆ dual energy x-ray absorptiometry; LBM ˆ lean body mass;
BMC ˆ bone mineral content.
Ethnicity and bioelectrical impedance analysis
JM Jakicic et al
the following four sites: between the styloid processes
of the ulna and radius (E1), distal end of the second
and third metacarpals (E2), between the lateral malleolus and medial malleolus (E3), and distal end of the
®rst and second metatarsals (E4). There was a minimum of 8 cm between electrodes E1 and E2, and
electrodes E3 and E4.
LBM was estimated using a generalized equation1
and an obesity-speci®c equation,6 and percent body
fat was then computed using the following equation:
Percent body fat ˆ ……body weight
ÿLBM†=body weight†100:
Because the subjects being examined in this study
were obese, we were interested in using prediction
equations that have been validated on obese populations. The equation proposed by Segal et al1 was
derived from a sample of subjects that included both
lean and obese individuals, and the study by Fuller et
al12 indicates that this equation provides a more
accurate estimate of LBM compared to other existing
equations derived on similar samples. Furthermore,
Fuller et al12 showed that the obesity-speci®c equation
proposed by Segal et al6 provided a more accurate
estimate of LBM in an obese population when compared to other equations derived from primarily obese
populations.
Statistical analysis
Statistical analysis was performed using Statistical
Package for the Social Sciences software (SPSS for
Windows, version 7.5)13 and SAS (version 6.1.1).14 A
two-factor (Measurement6Ethnicity) analysis of variance (ANOVA) was used to assess the difference
between DEXA and BIA. Multiple regression was
performed separately for LBMtissue (tissue of LBM
only) and LBMtotal (tissue of LBM ‡ BMC) as the
dependent variable, with weight, height, age and
ethnicity entered into each analysis and either resistance (R) or height2/R added separately to the analysis
(since both R and height2/R have been used in previous studies). These regression equations were
cross-validated using sub-samples of the original
123 subjects. Statistical signi®cance was de®ned at
P < 0.05.
245
Results
Results of the comparison between African-American
and Caucasian subjects are shown in Table 1. There
were no signi®cant differencse between the ethnic
groups for age, height, weight, body mass index
(BMI), resistance or reactance. In addition, body
composition measured by DEXA showed no difference between the groups for percent body fat or fat
mass. However, both components of LBMtotal, BMC
and LBMtissue, were signi®cantly greater in AfricanAmericans vs Caucasians (P < 0.001).
A two-factor (Measurement6Ethnicity) repeated
measures analysis of variance was used to assess
differences between DEXA and BIA. The signi®cant
Measurement6Ethnicity interaction (P < 0.001) indicates that the difference in LBM measured by DEXA
(LBMtotal) vs BIA using the generalized equation,1
was greater in Caucasians compared to African-Americans (see Table 2). Results showed that BIA overestimated LBM in Caucasians by 2.6 3. kg vs
0.4 3.2 kg in African-Americans (P < 0.001). As a
result, percent body fat using BIA was underestimated
by 3.5 3.5% in Caucasians vs 1.2 3.2% in AfricanAmericans, and the Measurement6Ethnicity interaction was statistically signi®cant (P < 0.004).
Data were also analyzed to examine the accuracy of
an obesity-speci®c equation,6 to estimate LBM using
BIA (see Table 2). Again, a signi®cant (P < 0.001)
Measurement6Ethnicity interaction was found, with
BIA overestimating LBM by 0.9 3.1 kg in Caucasians and underestimating LBM by 1.2 2.8 kg in
African-Americans. This translated into percent
body fat being underestimated by 1.4 3.5% in Caucasians and overestimated by 0.7 2.9% in AfricanAmericans, with the Measurement6Ethnicity interaction again being statistically signi®cant (P 0.001).
Results for each of the regression analyses to
predict LBMtotal using height2/R and R are presented
in Table 3. As shown in the table, regardless of
whether height2/R or R were used in the equation,
the demographic variables of height, weight, and
ethnicity were all signi®cant contributors to the prediction of LBMtotal (P < 0.05). These data suggest that
including ethnicity in the BIA equations to estimate
Table 2 Repeated measures analysis of variance to compare body composition by ethnic group using dual energy x-ray
absorptiometry (DEXA) and bioelectrical impedance analysis (BIA), using generalized and obesity-speci®c equations
Body composition measures
DEXA
Lean body mass (kg)
Caucasians (n ˆ 80)
African-Americans (n ˆ 43)
Percent Body Fat
Caucasians (n ˆ 80)
African-Americans (n ˆ 43)
a
b
BIAa
BIAb
P-values for DEXA vs BIAa
Measure
Ethnicity
Measure
6
Ethnicity
P-values for DEXA vs BIAb
Measure
Ethnicity
Measure
6
Ethnicity
49.1 4.5
52.5 5.0
51.7 3.9
52.9 5.3
50.0 4.3
51.3 5.2
< 0.001
0.007
< 0.001
0.58
0.005
< 0.001
43.2 4.7
41.6 5.2
39.7 4.6
40.4 5.0
41.8 2.8
42.4 3.5
< 0.001
0.42
0.004
0.31
0.45
0.001
using generalized equation from Segal et al (1985).1
using obesity-speci®c equation from Segal et al (1988).6
Ethnicity and bioelectrical impedance analysis
JM Jakicic et al
246
Table 3 Multiple regression to predict tissue of lean body mass ‡ bone mineral content (LBMtotal) using bioelectrical impedance
analysis (BIA) and descriptive characteristics of subjects
Dependent variable
(using DEXA)
Predictor
variablea
Equation 1
LBMtotal (kg)
Intercept
Weight (kg)
Resistance (R)
Ethnicity
Height (m)
Equation 2
LBMtotal (kg)
Intercept
Weight (kg)
height2/R
Ethnicity
Height (m)
P-values
for each
independent
variable
Coefficient
2.04
0.19
70.02
2.63
25.83
Predicted
residual
sum of
squares
R2
Mean
square
error
1140.7
0.65
8.8
1159.0
0.65
8.9
< 0.001
< 0.001
< 0.001
< 0.001
2.68
0.19
0.20
2.55
11.57
< 0.001
< 0.001
< 0.001
0.02
a
predictor variables presented in the order in which they entered the model.
Ethnicity: 0 ˆ Caucasian, 1 ˆ African-American.
height2/R ˆ height (cm)2/Resistance.
LBM will account for the 2.5 kg difference in LBM
shown between the overweight Caucasian and African-American women in this study (see Table 1).
Based on the data used in this study, examination of
the residual scores showed no signi®cant outliers.
The data were examined further to assess whether
there were differences in the accuracy of the prediction of LBM or the ®t of the model, when either
height2/R or R was used in the equation. The predicted
residual sum of squares, r2, and the mean square error
were similar for both equations, indicating no difference between the two equations in the accuracy of the
prediction or the ®t of the model (see Table 3). Results
of regression analysis to predict LBMtissue were virtually identical to those described for LBMtotal (data
not shown). We applied these equations to the sample
of 123 subjects in this study, and compared the
LBMtotal to the LBM predicted from these equations.
These results indicate that the equation which uses
height2/R may provide a more accurate estimate of
LBM, and these results are presented in Table 4.
Based on these results, the remaining analyses were
performed on the equations that used LBMtotal and
height2/R.
Random samples of 30 (21 Caucasian, 9 AfricanAmerican) and 60 (39 Caucasian, 21 African-American) subjects were selected from the original 123
subjects for the purpose of cross-validation of the
regression equations shown in Table 3. Using the
regression equation that included height2/R, results
showed no signi®cant difference between the
observed and predicted LBMtotal, with these values
being 49.8 4.4 kg and 49.6 3.3 kg, respectively.
Similar results were found when the equation was
applied to the random sample of 60 subjects, with the
observed LBMtotal being 49.7 4.3 kg and the predicted LBMtotal being 49.3 2.9 kg (NS). In addition,
there was no signi®cant difference between the
observed and the predicted LBMtotal when analyzed
separately for Caucasians and African-Americans in
either of the random samples of 30 or 60 subjects.
To examine further the application of an ethnicity
speci®c equation to estimate body composition, we
randomly divided the original 123 subjects into two
Table 4 Comparison by ethnicity of lean body mass (LBM) measured by dual energy x-ray
absorptiometry (DEXA) and predicted from the proposed bioelectrical impedance analysis
(BIA), ethnic-speci®c equations for 123 overweight women (80 Caucasian and 43 AfricanAmerican)
DEXA (mean s.d.)
BIA (mean s.d.)
Mean difference
49.1 4.5
52.5 5.0
50.8 3.2
54.2 4.2
1.7 3.0*
1.7 2.8*
49.1 4.5
52.5 5.0
48.9 3.2
52.3 4.4
0.2 3.0
0.2 2.8
a
LBMtotal (kg)
Caucasians (n ˆ 80)
African-Americans (n ˆ 43)
LBMtotal (kg)b
Caucasians (n ˆ 80)
African-Americans (n ˆ 43)
a
BIA computed using equation from Table 3 which incorporates resistance in the model.
BIA computed using equation from Table 3 which incorporates height2/R.
* indicates statistically signi®cant at P < 0.001.
LBMtotal ˆ tissue of lean body mass ‡ bone mineral content.
b
Ethnicity and bioelectrical impedance analysis
JM Jakicic et al
Table 5 Multiple regression to predict tissue of lean body mass ‡ bone mineral content (LBMtotal) using bioelectrical impedance
analysis (BIA) and descriptive characteristics in sub-samples of 30 and 60 subjects
Sample
size
Dependent
variable
(using DEXA)
30a
LBMtotal (kg)
60b
LBMtotal (kg)
P-values for each
independent
variable
Predictor
variable
Coefficient
Intercept
Weight (kg)
ht2/R
Ethnicity
Height (m)
74.76
0.16
0.28
2.88
15.38
0.01
0.03
0.02
0.22
Intercept
Weight (kg)
ht2/R
Ethnicity
Height (m)
5.49
0.17
0.29
2.46
15.18
< 0.001
< 0.001
0.005
0.04
Predicted
residual sum
of squares
R2
Mean
square
error
280.1
0.68
7.3
581.9
0.53
9.1
Ethnicity: 0 ˆ Caucasian, 1 ˆ African-American.
ht2/R ˆ height (cm)2/Resistance.
a
indicates 21 Caucasians and 9 African-Americans.
b
indicates 39 Caucasians and 21 African-Americans.
groups which consisted of 60 (39 Caucasian, 21
African-American) and 63 subjects (41 Caucasian,
22 African-American). We generated regression
models to estimate LBMtotal for each of these groups
(see Table 5) and found that these equations were
similar to the original equation shown in Table 3.
Furthermore, when we applied the regression equation
generated on the sample of 60 to the sample of 63, no
signi®cant difference was shown between the
observed (50.8 5.5 kg) and predicted (51.8 5.2 kg) LBMtotal, and the results were similar when
separated by ethnicity.
Discussion
The results of this study support previous studies
suggesting that BIA overestimates LBM in obese
adults when a generalized equation1 is used to predict
LBM. Valero et al15 examined the accuracy of BIA in
10 obese patients and showed LBM to be overestimated by approximately 7 kg when compared to
DEXA, and a similar pattern was reported by Beshyah
et al16 in a sample of obese hypopituitary patients.
However, when separated by ethnicity, the results of
this study suggest that the error in the estimate of BIA
using a generalized equation is primarily a result of
the error in Caucasian subjects not in African-Americans (see Table 2). The ethnicity of the sample
population used to derive the prediction equation
proposed by Segal et al1 was not reported, but the
majority of studies of BIA have been undertaken
using, primarily, a Caucasian population.8 Because
these prediction equations are based on data from,
primarily, Caucasian populations, one might expect
these equations to be more accurate for Caucasians
than African-Americans. However, the result of this
study do not con®rm this hypothesis, and are contrary
to what was expected.
To improve the estimate of body composition using
BIA in obese adults, Segal et al6 have proposed an
obesity-speci®c equation. The results of the current
study show that the accuracy of the estimate of body
composition using BIA for obese Caucasian women is
improved when an obesity-speci®c prediction equation is used, with the overestimation of LBM reduced
from 2.6 kg to 0.9 kg (Table 2). These ®ndings are
very similar to the results reported by Fuller et al12 in
a study of 15 obese Caucasian women. In this previous study, the generalized equation1 overestimated
LBM by 2.6 10.4 kg and the obesity-speci®c equation6 reduced this to 0.0 9.4 kg.
In contrast, for the obese African-American
women, the generalized equation1 provided a reasonable estimation of LBM (see Table 2), whereas use of
the obesity-speci®c equation resulted in BIA underestimating LBM by 1.2 kg. Therefore, the BIA equation used to predict LBM for obese African-American
women may need to be different from the equation
used for obese Caucasian women. The results of this
study suggest that the ethnicity of the subjects can
affect the magnitude and the direction of the error in
the estimation of body composition when using BIA.
This may be due to African-Americans having greater
body density17 and greater BMC10 compared to Caucasians, and these differences have not been
accounted for in the existing BIA equations. Therefore, we propose the use of an ethnic-speci®c BIA
equation to estimate body composition (Table 3,
Equation 2).
A search of MEDLINE (National Library of Medicine, Bethesda, MD) databases from 1966±1996 was
performed using BIA and African-Americans as keywords. When combined, these keywords indicated that
there were only four published articles, with none of
these articles published prior to 1992. Furthermore,
only one of these articles examined the accuracy of
BIA in African-Americans, supporting the belief that
research in this area is lacking.8,9 Clark et al18
247
Ethnicity and bioelectrical impedance analysis
JM Jakicic et al
248
reported that BIA overestimated percent body fat by
6% in African-American collegiate football players,
when hydrostatic weighing was used as the criterion
measure. In comparison, BIA overestimated percent
body fat by 3% in Caucasian athletes in the same
study. We were unable to ®nd any studies that
examined the accuracy of BIA in obese AfricanAmerican women. Given this, researchers and clinicians should consider using the ethnic-speci®c equations proposed in this study when assessing body
composition in a sample of obese women that include
both Caucasians and African-Americans. These equations accounted for the 2.5 kg difference in LBM
between Caucasians and African-Americans who participated in this study (Table 1, Table 3). Results of
cross-validation analyses showed that the proposed
BIA equation using height2/R (Table 3, Equation 2)
provides an accurate estimate of LBM in overweight
Caucasian and African-American women. Despite
these promising ®ndings, the accuracy of this
equation needs to be further validated in other samples
which include both Caucasians and African-Americans.
The need for an ethnic-speci®c equation to enhance
the prediction of body composition using BIA may
suggest that there is biological and/or metabolic
difference between Caucasians and African-Americans. Schutte et al17 have suggested that the biological
and physiological assumptions related to the measurement of LBM which are based largely on Caucasian
samples may not be accurate for African-Americans.
For example, it has been suggested that the density of
muscle and bone may be greater in African-Americans compared to Caucasians.10,19 Thus, because the
majority of BIA prediction equations are based on
Caucasian samples, the impact that this difference in
the density of LBM has on the accuracy of BIA has
not been thoroughly examined.
The accuracy of both DEXA and BIA may be
affected by altered ¯uid distribution and volume.20
Because an overweight population was examined in
this study, it is possible that edema may have been
present which could have affected the accuracy of
both the DEXA and BIA. We did not conduct a
clinical examination to assess whether this condition
was present in any of the subjects in this study.
However, based on self-reported medical histories,
none of the subjects in this study reported edema,
nor were any of the subjects taking medication that
would affect ¯uid balance (for example, diuretics).
However, future studies examining the accuracy of
BIA, that use DEXA as the reference method, should
consider examining this parameter and the impact this
may have on body composition in both Caucasian and
African-American subjects.
In summary, few studies have examined the accuracy of BIA to estimate body composition in speci®c
ethnic groups (for example, African-Americans). The
results of this study suggest that the use of a commonly cited generalized BIA prediction model1 can
accurately estimate LBM in overweight AfricanAmerican women, but this same equation overestimates LBM in overweight Caucasian women. The use
of an obesity-speci®c equation6 improved the estimation of LBM using BIA for the Caucasian women in
this study, but decreased the accuracy for the AfricanAmerican women. Therefore we propose the use of a
prediction model that accounts for potential differences between these two ethnic groups (see Table 3),
and the results of this study indicate that these
equations may be expected to perform reliably for
African-American and Caucasian women with characteristics similar to the subjects used in this study.
Therefore, the ®ndings of this study are limited to
overweight Caucasian and African-American women;
thus future studies should examine whether the use of
an ethnicity-speci®c BIA equation is also applicable
in men and leaner populations.
Acknowledgments
This study was supported by the National Institutes of
Health with awards to Dr Wing (DK29757) and Dr
Jakicic (HL561227), and the Obesity/Nutrition
Research Center at the University of Pittsburgh
(DK46204).
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