EVALUATION OF THE BOD POD FOR ESTIMATING
PERCENT BODY FAT IN COLLEGIATE TRACK AND
FIELD FEMALE ATHLETES: A COMPARISON OF FOUR
METHODS
KEREN M. BENTZUR,1 LEN KRAVITZ,1
AND
DONNA W. LOCKNER2
1
Health, Exercise and Sports Sciences, Exercise Physiology Laboratory, University of New Mexico, Albuquerque, New Mexico;
and 2Nutrition/Dietetics Program, Department of Individual, Family and Community Education, University of New Mexico,
Albuquerque, New Mexico
ABSTRACT
Bentzur, KM, Kravitz, L, and Lockner, DW. Evaluation of the
BOD POD for estimating percent body fat in collegiate track
and field female athletes: a comparison of four methods.
J Strength Cond Res 22(6): 1985–1991, 2008—This investigation examined the accuracy of the BOD POD on a group
of Division I collegiate track and field female athletes (N = 30).
Hydrostatic weighing (HW) was used as the gold standard
method. Body density (Db) values obtained from the BOD POD
(DbBP) were compared with those determined by HW (DbHW).
Both Db values were converted to percent body fat (%BF)
using the Siri equation for comparison. Percent body fat values
obtained from the BOD POD (BFBP) were also compared with
those obtained from dual-energy X-ray absorptiometry (DXA,
BFDXA) and skinfold (SF, BFSF). The validity of the BOD POD
was assessed using repeated-measures analysis of variance
(ANOVA), and the relationship between the methods was
examined through Pearson correlation. Average DbBP was
0.00890 gcm23 lower (p , 0.05) than DbHW, resulting in
a significant overestimation of %BF (p , 0.05) by the BOD
POD. Values for BFDXA and BFBP also differed significantly (p ,
0.05). On the other hand, BFSF and BFBP were not significantly
different. The correlation between percent body fat values
obtained from HW (BFHW) and BFBP was good (r = 0.88, SEE =
2.30) as well as between BFSF and BFBP (r = 0.85, SEE = 2.05).
Conversely, the correlation between BFDXA and BFBP was poor
(r = 0.25, SEE = 5.73). The strong correlation between BFBP
and BFHW presented here suggests that the BOD POD has the
potential to be used as a body composition analysis tool for
female athletes. The advantages of the BOD POD over HW
Address correspondence to Len Kravitz, [email protected].
22(6)/1985–1991
Journal of Strength and Conditioning Research
Ó 2008 National Strength and Conditioning Association
encourage further investigation of this instrument. However, the
fact that the BOD POD and SF results did not differ significantly
might suggest that the SF could be used in its place until
a better rate of accuracy for this instrument is established.
KEY WORDS air-displacement plethysmography, body composition
INTRODUCTION
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any athletes are aware of the importance of
body composition and percent body fat (%BF)
as it relates to optimal performance (8). In
sports that involve power, speed, and endurance, excessive body fat may impede the athletes’ ability to
jump, run fast, or improve aerobic capacity. Conversely, low
%BF is associated with conditions such as disordered eating,
iron deficiency anemia, amenorrhea, premature osteoporosis,
and sports injuries (3,10). Appearance is known to be a major
factor influencing body composition in female athletes, often
placing them at a risk for developing health problems caused
by inadequate nutrition (17). Women in general and female
athletes in particular are very susceptible to developing body
image problems because of high demands from society or the
sport in which they compete (9,17). Monitoring body
composition during the training and competition season
with an accurate and reliable method is a useful strategy to
ensure proper nutrition for health and athletic competition.
Hydrostatic weighing (HW) is a densitometric method of
body composition analysis based on Archimedes’ principle. It
has been considered the ‘‘gold standard’’ by which other
methods of body composition assessment have been
validated (8). However, it is time consuming, unpleasant
for some subjects, and requires a highly trained technician
(18,19). A few studies (2,10,16) have used dual-energy X-ray
absorptiometry (DXA) instead of HW as a criterion method
for body composition analysis of athletes, suggesting that it
might be a new gold standard. Unlike HW, DXA accounts for
differences in lean mass (bone mineral density and soft
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BOD POD Estimation of Percent Body Fat
tissue), and therefore its accuracy in measuring %BF might be
better for the athletic population. Still, the use of DXA has
higher financial costs.
Another commonly used body composition analysis
method is the skinfold (SF) measurement. The SF technique
is quick and reliable, if done by an experienced technician.
Depending on the equation used, the prediction error of
percent body fat by SF can vary between 2.2 and 3.5% (8). The
skinfold technique is a good alternative for athletes and
coaches who do not have access to a laboratory to perform
HW for body composition assessment.
Similar to HW, air-displacement plethysmography (ADP)
is a densitometric method. The BOD POD Body Composition System (Life Measurement Instrument, Concord,
California) is a commercial device using ADP that was
developed to provide an alternative method for estimating
%BF other than the traditional HW (5). The BOD POD
measures body volume by air displacement to calculate body
density (Db). Previous studies comparing ADP with HW in
men and women have reported close agreement (7,13,18),
whereas other investigations found the results to be
inconsistent (1,4,19,21).
It is beneficial to compare the BOD POD with HW because
both are densitometric methods and, theoretically, should
produce similar results. In addition, it is valuable to investigate
and compare %BF estimation by the BOD POD with the
DXA measurement to establish their relationship in body
composition assessment of the athletic population. The
primary purpose of this study was to examine the accuracy of
%BF estimations obtained by the BOD POD (BFBP) in
a group of Division I collegiate track and field female athletes
(N = 30) using HW as the gold standard. A secondary
purpose was to compare and determine the relationship
between BFBP and the estimation of percent body fat by SF
(BFSF) and DXA (BFDXA) in this group of female athletes.
METHODS
Experimental Approach to the Problem
A female athlete’s health and athletic performance are greatly
affected by her %BF. The availability of a reliable, accurate,
and easy-to-administer body composition analysis tool allows
many coaches and athletes to monitor body composition for
health and performance. Hydrostatic weighing requires
specialized facilities, a trained technician, and ample time
to complete. Additionally, it may be unpleasant for some
subjects. The BOD POD was developed to create an
administratively advantageous method for estimating %BF
other than HW.
This investigation examines the accuracy of the BOD POD
estimation of %BF in a group of track and field female athletes
(N = 30) while comparing it with the results from three other
body composition analysis tools (HW, DXA, and SF)
commonly used on this population. A short health
questionnaire was completed by each subject before data
collection. Data were collected at two laboratories at
1986
the
a Southwestern university in the United States. Excluding
the residual volume (Rv), which was measured earlier, all
measurements were taken on the same day for each subject.
Because the BOD POD requires the subject’s body to be
completely dry, the testing order was DXA and BOD POD
first, followed by SF and HW.
Subjects
Thirty Division I collegiate female athletes (18–24 years)
volunteered from the university track and field team during
their competition season. Physical characteristics of the
female athletes included in this study are presented in Table 1.
The ethnic composition of the sample was 60% Caucasian,
20% Hispanic, 10% black, 3.3% Asian, and 6.7% other (mixed
ethnicities). Before the study, the primary investigator
explained the purposes, goals, and procedures of the study
to each volunteer. All subjects signed a consent form
approved by the human research review committee of the
university. Subjects were asked not to eat or exercise for
4 hours before testing. Because the DXA assessment involves
exposure to radiation, a pregnancy test was conducted on
every woman not taking birth control peels before testing to
ensure she was not pregnant.
Procedures
Body Height and Weight. Height was measured to the nearest
0.1 cm using a wall-mounted stadiometer (Holtain Ltd.,
Crymych, Wales). Subjects stood erect, without shoes, with
their hands at their sides. Height was recorded at the end of
inspiration. After emptying their bladders, body weight was
measured to the nearest 0.01 kg using a calibrated digital
platform scale (Tanita Corporation, BWB 627A, Japan).
Subjects wore only swimsuits.
Air-Displacement Plethysmography. Body volume was measured by the BOD POD using standardized published
procedures (13). The BOD POD is a dual-chamber ADP
machine, previously described by Dempster and Aitkens (5).
The BOD POD was calibrated according to the manufacturer’s guidelines using a 50-L cylinder. Subjects wore
clothing according to the manufacturer’s recommendation
(a swimsuit and a swim cap) to rule out air trapped in clothes
TABLE 1. Physical characteristics of subjects
(N = 30).
Age (y)
Height (cm)
Body weight (kg)
BMI (kgm22)
Mean 6 SD
Range
20.3 6 1.6
167.1 6 5.5
65.9 6 7.5
21.65 6 2.0
18–24
155.5–182.3
47.6–75.7
18.14–26.20
Range = lowest to highest values.
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and hair. As previously noted, each subject was weighed on
a calibrated digital scale and then entered the BOD POD
chamber. Body volume was measured twice by the machine
to ensure measurement reliability. If the first two readings for
body volume differed by more than 150 ml, a third
measurement was taken. If additional readings were needed,
the BOD POD was recalibrated and the measurements were
repeated for that subject. Each subject’s BFBP was calculated
from the Db obtained by the BOD POD (DbBP) using the Siri
equation (15).
Thoracic Gas Volume. Thoracic gas volume (Tgv) was
measured at the time of the actual BOD POD test following
the manufacturer’s recommendations explained in detail
elsewhere (13). This value was integrated into the calculation
of body volume.
Dual-Energy X-Ray Absorptiometry. Each subject’s BFDXA was
obtained by performing a whole-body scan (slow mode) with
a DXA scanner (Lunar DPX, Lunar Radiation Corp.,
Madison, Wis., using NT software version 3.50.176). All
jewelry and any clothing that contained metal were removed
before the scan. The machine was calibrated before each day
of testing with the manufacturer’s ‘‘standard block’’ (a
bone-simulating substance of known composition and
attenuating capacity), according to the manufacturer’s
recommendations.
Hydrostatic Weighing. Underwater weight was measured using
a four-load cell system (Interface, N. Scottsdale, Ariz.)
attached to a platform, and a digital scale (Precision
Biomedical, State College, Pa.) integrated to an analog
signal-acquisition system (Biopac, MP100, Santa Barbara,
Calif.). Subjects entered the tank, removed air bubbles from
their swimsuits and hair to minimize possible measurement
error, and then positioned themselves with both hands and
knees on the load cell platform. When ready, subjects were
instructed to go under the water and maximally exhale air
from their lungs while fully submerged. The measurement
was taken when air bubbles were no longer seen. Subjects
performed as many trials as needed until three measurements
within 100 g were obtained. The closest three measurements
were then averaged and used to calculate body volume and
Db. Each subject’s BFHW was calculated from Db obtained
from HW (DbHW) using the Siri (15) equation.
Residual Lung Volume. Residual lung volume was measured
before the HW using a closed-circuit helium dilution
technique (Collins, GS modular PFT, Braintree, Mass.). Each
subject sat on a chair outside the hydrostatic weighing tank,
breathing through a closed circuit. Subjects were given as
many trials as needed to obtain two values within 100 ml. The
two closest trials were then averaged and used in the
calculations of Db and %BF.
Skinfolds. The same trained technician performed the SF
measurements for all subjects. Measurements were taken in
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triplicate in a rotational pattern on the right side of the body,
using calibrated Lange SF calipers (Cambridge Scientific
Instrument, Cambridge, Md.). Four different sites were
measured: triceps, suprailiac, abdominal, and thigh. The
average of three measurements for each site was used to
calculate body density according to the Jackson and Pollock
(11) equation for female athletes ages 18–29. Body density
from the SF (DbSF) equation was converted to %BF using the
Siri equation.
Statistical Analyses
All analyses were produced using SPSS (SPSS for Windows,
version 13, Chicago, Ill.). A repeated-measures analysis of
variance (ANOVA) followed by Tukey post hoc comparisons
were performed to detect differences between the four body
composition analysis methods used in this study. Linear
regression and Pearson correlation analyses were used to
determine the relationship between the different body
composition analysis methods. Criterion alpha level for
significance was set at p # 0.05 for all analyses.
RESULTS
Body Fat
Body fat percentages obtained from the BOD POD, HW,
DXA, and SF for all female athletes tested are presented in
Table 2 along with the results for each track and field
specialty group. The repeated-measures ANOVA results
revealed a significant difference (p , 0.05) between BFBP,
BFHW, BFDXA, and BFSF. Post hoc comparisons showed that
BFBP estimations were significantly (p , 0.05) higher than
BFHW and significantly (p , 0.05) lower than BFDXA.
However, the post hoc comparisons showed no significant
(p , 0.05) difference between BFBP and BFSF. Figure 1
illustrates the mean percentages of body fat and their SD of
the HW, SF, BOD POD, and DXA.
A Pearson correlation test revealed that BFBP and BFHW
were significantly correlated (r = 0.88, SEE = 2.30). This
correlation is presented in Figure 2. The correlation of BFSF
and BFBP was good (r = 0.85, SEE = 2.05) and is presented
in Figure 3. A linear regression analysis produced an R2 = 0.71.
On the other hand, as shown in Figure 4, BFBP and BFDXA
had a poor correlation (r = 0.25, SEE = 5.73). A linear
regression analysis produced an R2 = 0.064. Figure 5
illustrates the correlation between BFBP, BFSF and BFHW,
showing similar trends for each subject.
Body Density
The repeated-measures ANOVA results revealed a significant
difference (p , 0.05) between DbBP, DbHW, and DbSF. Post
hoc comparisons show that DbHW was significantly greater
than both DbBP and DbSF. In addition, DbSF was significantly
(p , 0.05) greater than DbBP.
A Pearson correlation test revealed that DbBP and DbHW as
well as DbBP and DbSF were significantly correlated (r = 0.88,
SEE = 0.005, and r = 0.85, SEE = 0.005, respectively). A
linear regression analysis produced a coefficient of
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%BF
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Db (gcm23)
All (N = 30)
Sprinters (n = 8)
Jumpers (n = 9)
Throwers (n = 6)
Distance runners
(n = 7)
HW
BOD POD
1.06367 6 0.01092‡§
1.06856 6 0.00766
1.06296 6 0.01176
1.05377 6 0.01056
1.06749 6 0.00913
1.05477 6 0.00980*‡
1.05872 6 0.00916
1.05520 6 0.01052
1.04652 6 0.00933
1.05676 6 0.00722
SF
1.05845
1.06205
1.05861
1.04887
1.06234
6 0.00855*§
6 0.00752
6 0.00856
6 0.00590
6 0.00583
HW
BOD POD
SF
DXA
15.4 6 4.8†‡§
13.3 6 3.3
15.7 6 5.1
19.8 6 4.7
13.7 6 4.0
19.3 6 4.4*†
17.6 6 4.0
19.1 6 4.7
23.0 6 4.2
18.4 6 3.2
17.7 6 3.8*†
16.1 6 3.3
17.6 6 3.8
21.9 6 2.7
16.0 6 2.6
23.0 6 5.8*‡§
22.8 6 4.3
25.0 6 7.6
24.8 6 5.3
19.0 6 3.9
Values are expressed as mean 6 SD.
HW = hydrostatic weighing; SF = skinfold; DXA = dual-energy X-ray absorptiometry.
*Significantly different from HW (p , 0.05).
†Significantly different from DXA (p , 0.05).
‡Significantly different from SF (p , 0.05).
§Significantly different from BOD POD (p , 0.05).
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Figure 1. Mean percent body fat and SD for each method (N = 30).
determination R2 = 0.77 for DbBP and DbHW and is presented
in Figure 6. For the comparison of DbBP and DbSF, a linear
regression analysis produced an R2 = 0.71 and is presented
in Figure 7.
DISCUSSION
Body composition can be estimated from a two-component
model based on the measurement of Db. For densitometric
methods, HW is regularly used as the gold standard method
for estimation of %BF (8). Because the BOD POD is also
based on densitometry, HW was used as the reference
method in the present study. In addition, the BOD POD was
Figure 2. Scatter plot of the relationship between percent body fat values
obtained from hydrostatic weighing (BFHW) and percent body fat values
obtained from the BOD POD (BFBP).
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BOD POD Estimation of Percent Body Fat
1988
TABLE 2. Comparison of percent body fat (%BF) and body density (Db) (N =30 ).
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Figure 3. Scatter plot of the relationship between percent body fat values
obtained from skinfolds (BFSF) and percent body fat values obtained from
the BOD POD (BFBP).
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Figure 5. Subject trends in percent body fat values obtained from the
BOD POD (BFBP), percent body fat values obtained from skinfolds
(BFSF), and percent body fat values obtained from hydrostatic weighing
(BFHW).
compared with two other (SF and DXA) commonly used
methods of body composition analysis.
McCrory et al. (13) were the first to evaluate the BOD
POD in comparison with HWon human subjects. Their data,
which were expressed in terms of %BF, reported a nonsignificant mean difference of 0.3% (p , 0.05) (BOD POD
was higher) and concluded that the BOD POD was a valid
instrument for determining %BF in adult men and women.
Since then, other studies (4,6,7,14,18–21) have shown diverse
results when examining the validity of the BOD POD against
HW. Vescovi et al. (20) have reported a nonsignificant (p ,
0.05) difference in the estimation of %BF between the two
methods in a sample of heterogeneous adults. In contrast,
Millard-Stafford et al. (14) tested a heterogeneous group and
found the BOD POD to significantly (p , 0.05) underestimate %BF by 2.8%. On the other hand, Wagner et al. (21)
have reported a significant (p , 0.05) overestimation of
nearly 2% for black men with the BOD POD.
Few studies have examined the accuracy of the BOD POD
on athletes using HW as the reference method (4,6,18,19).
Results from previous studies on athletes are presented
in Table 3. There is no apparent pattern relating the accuracy
of %BF estimation by the BOD POD to that of HW.
Investigating the accuracy of the BOD POD on a group of
collegiate football players, Collins et al. (4) found its
estimation of %BF to be 1.9% lower (significant underestimation) than that of HW. Vescovi et al. (19) showed an
inverse trend (significant overestimation) when they tested it
on a group of college female athletes. In contrast, both
Figure 4. Scatter plot of the relationship between percent body fat values
obtained from dual-energy X-ray absorptiometry (BFDXA) and percent
body fat values obtained from the BOD POD (BFBP).
Figure 6. Scatter plot of the relationship between body density values
obtained from hydrostatic weighing (DbHW) and body density values
obtained from the BOD POD (DbBP).
VOLUME 22 | NUMBER 6 | NOVEMBER 2008 |
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BOD POD Estimation of Percent Body Fat
Figure 7. Scatter plot of the relationship between body density values
obtained from skinfolds (DbSF) and body density values obtained from the
BOD POD (DbBP).
Utter et al. (18) and Dixon at al. (6), who tested the BOD
POD against HW on two different groups of collegiate
wrestlers, found the difference to be nonsignificant (20.33 6
2.34 and 0.7 6 1.78%, respectively).
Similar to Vescovi et al. (19), in the present study the BOD
POD was found to significantly (p , 0.05) overestimate %BF
of the female athletes. Additionally, a previous investigation
by Vescovi et al. (20), who divided their heterogeneous
subjects into three groups (lean, average, and overweight),
showed no significant difference in %BF between the two
methods for the average and overweight groups. They did
report a significant difference for the lean group, with the
BOD POD overestimating by 2.3 6 3.5%. A t-test between
BFHW of the subjects in the present study and the lean group
of the Vescovi et al. (20) study shows that the two groups are
alike (p = 0.22). Similar to their study, the average %BF for
the track and field female athletes in the present study was
significantly overestimated (3.9 6 2.3%, p , 0.05) by the
BOD POD. It is important to note that in the Vescovi et al.
(20) investigation, the lean group consisted mainly of women.
Supported by the findings of Vescovi et al. (20), two possible
reasons why the BOD POD differs significantly from HW in
the present study are (a) the overestimation of the lean group
might suggest a possible limitation in measuring lean
subjects, and (b) the overestimation of a group consisting
mainly of women might suggest a possible gender bias
by the BOD POD.
The strong correlation between %BF estimated by the
BOD POD and HW suggests that it has the potential to be
useful for body composition measurement of female athletes.
However, additional research with this instrument on this
population is needed to establish agreement between the two
methods before it can be used as an alternative to HW for this
population. Until then, practitioners should reconsider the
use of the BOD POD for the purpose of estimation of %BF of
lean female athletes and, perhaps, use SF for that purpose.
Because SF is a field method that is quick and reliable when
done by a trained technician, one can save the effort involved
with going to a laboratory to use the BOD POD.
The relationship between %BF estimations by the BOD
POD and that measured with DXA has been examined a few
times in the past. Similar to the present study, Collins et al. (4)
found that the %BF estimated by the BOD POD was
significantly lower than that measured by DXA, reporting
a smaller difference (2%) than the one in the present study
(3.7 6 6.3%). On the other hand, Ballard et al. (2) have
recently reported a valid measurement of body composition
by the BOD POD when compared with DXA. They found
the two methods to be highly correlated and report no
significant difference between the two instruments (mean
BFBP = 22.5%, BFDXA = 22.0%). Possible explanations for the
disagreement in results of this study and the one done by
Ballard et al. include the following: (a) their female athlete
TABLE 3. A comparison of past research testing the accuracy of the BOD POD.
Reference
Gold
standard
Population (sport)
N
Results*
Accuracy of the
BOD POD
Current study
Dixon et al. (2005)
Ballard et al. (2004)
Utter et al. (2003)
Vescovi et al. (2002)
Collins et al. (1999)
Collins et al. (1999)
HW
HW
DXA
HW
HW
HW
DXA†
Collegiate females (track and field)
Collegiate males (wrestling)
Collegiate females (various sports)
Collegiate males (wrestling)
Collegiate females (various sports)
Collegiate males (football)
Collegiate males (football)
30
25
47
66
80
69
20
Significant difference
No significant difference
No significant difference
No significant difference
Significant difference
Significant difference
Significant difference
Overestimating
Accurate
Accurate
Accurate
Overestimating
Underestimating
Underestimating
HW = hydrostatic weighing; DXA = dual-energy X-ray absorptiometry.
*Significant difference (p , 0.05).
†Used as an alternative gold standard.
1990
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population consisted of only non-Hispanic, Euro-American
women, which might suggest ethnic bias measurement, (b)
the DXA scan was done using a different DXA machine
(Holigic QDR 4500A software version 12.01, Waltham,
Mass.), and (c) a whole-body scan in the present study took
10–15 minutes, and they reported theirs to be approximately
5 minutes. Different than both Collins et al. (4) and Ballard
et al. (2), in the present study the correlation between the two
methods was poor, indicating a weak relationship between
the BOD POD and DXA. As previously mentioned by
Lohman (12), differences in calibration procedures, software
version, and the instrument’s company and model might lead
to differences in the results of validation studies. The poor
correlation presented here between %BF estimated by the
BOD POD and those measured by DXA, as well as the
significant difference (p , 0.05) between DXA and HW,
should lead researchers to reconsider the use of DXA as
a gold standard with female athletes in research until
specifications for standardized instrumentation and software
are established.
PRACTICAL APPLICATIONS
Although the BOD POD has been available for several years
for estimating %BF, its accuracy, especially in athlete
populations, is not well established. The use of the skinfold
method on female athletes is a good alternative that saves the
time and effort of going to a laboratory setting. The good
correlation between HWand the BOD POD might eventually
secure the use of this instrument as a good body composition
analysis tool, but its accuracy will need to be improved in the
female athlete population before it can replace HW.
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