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Comparison of body fat using various bioelectrical impedance analyzers in university students

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Background: At present, the portfolio of devices using the bioelectrical impedance (BIA) method is continuously expanding as a result of the wide use of this method in the field as measurements by this method are fast and staff training is simple and reasonably priced. Nonetheless, the problem is that despite using the same method, bioimpedance analyzers can differ in many parameters. They use different electric current frequencies, a different number of electrodes and the electric current may be conducted through different parts of the body. Objective: The main objective of the study is to compare and evaluate the differences of values of the analysis of the body fat of university students measured by BIA analyzers that differ in the applied electric current frequency, number of electrodes and flow of the electric current through the individual body parts. Methods: The research included 125 participants (70 male and 55 female). The measurements were taken by the following analyzers: Tanita 418 MA, InBody 720, InBody R20 and Omron BF 300. Results: The differences in the mean values of the body fat representation between the used analyzers in men ranged from 0.1 to 3.4% and from 0.0 to 2.4 kg, in women from 0.5 to 6.5% and from 0.4 to 3.8kg in relation to the used analyzer. Conclusions: In men with regular physical activity, the values measured by InBody R20 were statistically and practically different. The analyzer measured higher values that other analyzers. In women, there were statistically and practically significant differences in the values measured by Omron BF 300. This analyzer measured lower values than other analyzers.
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177
2006; Quinney et al., 2008; Rahimi, 2006; Sanchez,
Sanz, & Zabala, 2007) in medicine, it helps us assess
the effect of the applied treatment (such as diet). Very
often monitored parameter is therefore body fat (BF).
There are many methods applied to the evaluation
of body composition that can be classified as reference
and non-reference. According to Heyward and Wagner
(2004) the reference methods (“gold standard”) are
underwater weighting, air-displacement plethysmogra-
phy and dual-energy X-ray absorptiometry (DEXA).
These methods are used for the evaluation of the valid-
ity of other (non-reference) methods. Since the refer-
ence methods are demanding for equipment as well
as implementation of measurement, they are mainly
used in medicine. In practice, non-reference methods
are used most frequently: these are field methods
(standardized anthropometry, methods based on bio-
electrical impedance analysis) that allow examining
larger sample groups in the field, are less demanding
for instrumentation and also are affordable. There have
already been many studies that compare the final values
Introduction
Nowadays, the evaluation of body composition is com-
monly used for the assessment of the medical condi-
tion of an individual, the level of nutrition and physical
fitness (McArdle, Katch, & Katch, 2007). In medicine,
it is used as a part of diagnostics in diabetics, nephrol-
ogy, obesity science and osteology (Parikh et al., 2004;
Pluijm et al., 2001; Pravn et al., 1999). In sports, it
facilitates efficient management of the training pro-
cess. On the basis of the body composition evaluation,
we can to some extent determine the level of readiness
of the athlete’s organism for strain. By monitoring
changes in the body composition, we can also evaluate
the effect of physical exercise on the athlete’s organism
and asses its adequacy (Bauer, Pivarnik, Fornetti, Jallo,
& Nassar, 2005; Green, Pivarnik, Carrier, & Womack,
* Address for correspondence: Petr Kutáč, Human Motion Di-
agnostics Center, University of Ostrava, Varenska 40a, 702 00
Ostrava 1, Czech Republic. E-mail: petr.kutac@osu.cz
Comparison of body fat using various bioelectrical impedance analyzers
in university students
Petr Kutáč
1,
*
and Miroslav Kopecký
2
1
Human Motion Diagnostics Center, University of Ostrava, Ostrava, Czech Republic; and
2
Faculty of Health Sciences,
Palacký University Olomouc, Olomouc, Czech Republic
Copyright: © 2015 P. Kutáč and M. Kopecký. This is an open access article licensed under the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/).
Background: At present, the portfolio of devices using the bioelectrical impedance (BIA) method is continuously
expanding as a result of the wide use of this method in the field as measurements by this method are fast and staff
training is simple and reasonably priced. Nonetheless, the problem is that despite using the same method, bioimped-
ance analyzers can differ in many parameters. They use different electric current frequencies, a different number
of electrodes and the electric current may be conducted through different parts of the body. Objective: The main
objective of the study is to compare and evaluate the differences of values of the analysis of the body fat of university
students measured by BIA analyzers that differ in the applied electric current frequency, number of electrodes and
flow of the electric current through the individual body parts. Methods: The research included 125 participants
(70 male and 55 female). The measurements were taken by the following analyzers: Tanita 418 MA, InBody 720,
InBody R20 and Omron BF 300. Results: The differences in the mean values of the body fat representation between
the used analyzers in men ranged from 0.1 to 3.4% and from 0.0 to 2.4 kg, in women from 0.5 to 6.5% and from 0.4
to 3.8 kg in relation to the used analyzer. Conclusions: In men with regular physical activity, the values measured by
InBody R20 were statistically and practically different. The analyzer measured higher values that other analyzers. In
women, there were statistically and practically significant differences in the values measured by Omron BF 300. This
analyzer measured lower values than other analyzers.
Keywords: adipose tissue, young adult, single frequency analyzer, multi frequency analyzer, Bland-Altman analysis
Acta Gymnica, vol. 45, no. 4, 2015, 177–186
doi: 10.5507/ag.2015.021
178
P. Kutáč and M. Kopec
of the body composition parameters acquired by vari-
ous methods. There have been comparisons of results
measured by the DEXA method (and other laboratory
methods), anthropometric methods as well as the bio-
electrical impedance method (BIA). The studies state
both the found differences in the final values of the
measured parameters and the validity of the applied
methods to laboratory methods (Beeson et al., 2010;
Dolezal, Lau, Abrazado, Storer, & Cooper, 2013; Gába,
Kapuš, Cuberek, & Botek, 2015; Gupta, Balasekaran,
Victor, Hwa, & Shun, 2011; Leahy, O’Neill, Sohun, &
Jakeman, 2012; Mojtahedi, Valentine, & Evans 2009;
Rutherford, Diemer, & Scott 2011).
At present, however, the portfolio of devices using
the BIA method is continuously expanding as a result
of the wide use of this method in the field as measure-
ments by this method are fast and staff training is sim-
ple and reasonably priced. Nonetheless, the problem
is that despite using the same method, bioimpedance
analyzers can differ in many parameters. They use dif-
ferent electric current frequencies, a different number
of electrodes and the electric current may be conducted
through different parts of the body. Another issue is
the unavailability of the used equations in the analyzer
software and the lack of information about the proband
groups from which reference data were taken for the
calculation of the final values. It is not possible to cal-
culate any potential differences in the final values when
more sophisticated instrumentation or an analyzer by a
different producer is acquired. A similar problem may
occur when the individual is measured in a different
work station. The only way how to encompass such
differences is to take such measurements in practice
and check any potential differences. The knowledge of
any potential differences is essential in case of repeated
measurements with the aim to understand changes in
body composition that could be caused by ontogenetic
changes or external interventions.
The main objective of the study is to compare and
evaluate the differences of values of the analysis of the
body fat of university students measured by bioimped-
ance analyzers that differ in the applied electric current
frequency, number of electrodes and flow of the elec-
tric current through the individual body parts.
Methods
Participants
The research group included 130 individuals in total
(73 males and 57 females). Three male and two female
were removed from the group after outliers. Thus, the
final number of monitored individuals was 125 (70
males and 55 females). The basic characteristic of the
study sample is presented in the Results part in Table 1.
None of the participants had any medical issues; they
did not take any medicine or food supplements. They
participated in the research voluntarily and they were
informed about the process of the research in advance.
Also, they signed informed consent with the participa-
tion in the research. The research was approved by the
Ethical Board of the University of Ostrava and it is in
compliance with the Helsinki Declaration. The males
were university students studying physical education
and sports. Therefore, we can call them a specific pop-
ulation group and the acquired results may be applied
to athletes of a whole range of sports disciplines that
will show similar values of the monitored parameters
(e.g. body fat representation which is a very frequently
monitored parameter in sports). The females were uni-
versity students of fields that did not focus on sports.
Therefore, we can apply their results on the general
population of women without any medical problems.
Procedures
The participants of the measurements were informed
of the conditions they had to observe prior to measure-
ment in advance (no alcohol consumption for 24 hours
prior to measurement, no vigorous exercise less than
12 hours prior to measurement, no food and beverages
3 hours prior to measurement, urination immediately
before measurement; only women that did not have
their menstrual period were measured).
Measurements took place in the morning (7.30
a.m.–9.00 a.m.) on the same day in the week. All
principles of measurement defined in the operating
instructions for the individual analyzers were met. The
participants attended all measurements wearing under-
wear. The measurement was executed standing, always
by the same team of researchers who have several years
of experience with such measurements. The body fat
of each participant was successively measured on all
applied BIA analyzers in the following order: Tanita
418 MA (SFBIA
4
), InBody 720 (MFBIA
4-720
), InBody
R20 (MFBIA
4-R20
), Omron BF 300 (SFBIA
2
). To
exclude any potential influence of the final measured
value due to delays between measurements (e.g. by con-
sumption of food or liquids), the individual measure-
ments were executed in immediate succession and the
participants were under continuous supervision. The
total body water (TBW), which is a primarily measured
parameter when the BIA method is used, was also
measured. TBW values are not stated for the SFBIA
2
analyzer because the output of this analyzer does not
specify the value. The body height, which is an input
parameter for measurements by the used analyzers,
was measured using the A-226 anthropometer (Trys-
tom, Olomouc, Czech Republic). The body weight as
179
Comparison of body fat using various BIA analyzers
Results
The basic characteristics of the monitored group and
the BF value measured by the individual analyzers are
presented in Table 1 and 2.
The differences in the values of the measured BF
and TBW representation by the used analyzers and
the results of their statistical analyses are presented in
Table 3 and 4.
an input parameter for the Omron BF 300 analyzer,
which is not a scale, was taken by the Tanita BC 587
digital scale (Tanita Corporation, Tokyo, Japan).
The used analyzers for the body composition diag-
nostics and their basic characteristics:
Tanita 418 MA (Tanita Corporation, Tokyo, Japan)
is a tetrapolar single-frequency BIA analyzer that
uses the electric current frequency of 50 kHz for
measurement. Eight point touch electrodes are
used for measurement. The analyzer is also a digital
scale.
InBody 720 (Biospace, Seoul, Korea) is a tetrapolar
multi-frequency BIA analyzer that uses the gradual
electric current frequency of 1, 5, 50, 250, 500 and
1000 kHz for measurement. Eight point touch elec-
trodes are used for measurement. The analyzer is
also a digital scale.
InBody R20 (Biospace, Seoul, Korea) is a tetrapo-
lar multi-frequency BIA analyzer that uses the elec-
tric current frequency of 20 and 100 kHz for mea-
surement. Eight point touch electrodes are used for
measurement. The analyzer is also a digital scale.
Omron BF 300 (Omron Corporation, Tokyo,
Japan) is a bipolar single-frequency BIA analyzer
(hand-hand) that uses the electric current frequency
of 50 kHz for measurement.
Statistical processing
The results were statistically processed using the IBM
SPSS Statistics (Version 21; IBM, Armonk, NY, USA).
Remote observations were identified by box plots and
the normality of distribution was verified by the Shap-
iro-Wilk test. With regard to the normal distribution of
values, we used the paired samples t-test to verify the
statistical significance of the differences of the results
between the individual devices. The statistical signifi-
cance level was determined to be α = .05 for all tests
used.
In values where statistically significant differences
were found, we used the effect size to assess practical
significance (Cohen, 1988). Recommendations for
Cohen’s d: 0.2 = minor change, 0.5 = medium change,
0.8 = major change. The value of Cohen’s d ≥ 0.5 was
considered to be a practically significant difference.
To express the level of correlation between the
results of measurement by the individual analyzers for
the body fat, we used Pearson correlation coefficient
(Westgard,
2008). To evaluate the homogeneity of the
results between two analyzers, we also used the Bland-
Altman’s analysis (Bland & Altman, 2010).
Table 1
Characteristics of the monitored group
Males (n = 70) Females (n = 55)
M SD M SD
Age (years) 20.2 1.1 19.8 1.2
Height (cm) 180.8 5.9 166.6 6.0
Weight (kg)
SFBIA
4
75.1 7.4 59.2 5.9
MFBIA
4-720
75.1 7.7 59.4 5.8
MFBIA
4-R20
75.2 7.4 59.3 5.9
BMI (kg/m
2
) 23.0 1.6 21.4 1.8
Note. BMI=body mass index, SFBIA
4
=Tanita BC 418 MA,
MFBIA
4-720
=InBody 720, MFBIA
4-R20
=InBody R20
Table 2
Values of the body fat and total body water
Males (n = 70) Females (n = 55)
M SD M SD
BF (%)
SFBIA
4
10.6 4.0 24.2 4.1
MFBIA
4-720
10.6 4.0 23.6 5.1
MFBIA
4-R20
13.2 4.0 25.2 5.0
SFBIA
2
9.6 3.3 19.0 3.9
BF (kg)
SFBIA
4
8.0 3.3 14.3 3.4
MFBIA
4-720
8.0 3.4 14.0 3.5
MFBIA
4-R20
9.9 3.4 15.0 3.3
SFBIA
2
7.2 3.0 11.3 3.0
TBW (%)
SFBIA
4
65.4 2.9 55.2 2.9
MFBIA
4-720
65.6 3.0 55.7 3.9
MFBIA
4-R20
64.0 2.9 55.1 3.7
TBW (kg)
SFBIA
4
49.1 4.5 32.7 2.6
MFBIA
4-720
49.3 4.8 33.1 3.7
MFBIA
4-R20
48.1 4.7 32.7 3.7
Note. BF=body fat, TBW=total body water, SFBIA
4
=Tanita
BC 418 MA, MFBIA
4-720
= InBody 720, MFBIA
4-R20
=InBody
R20, SFBIA
2
=Omron BF 300.
180
P. Kutáč and M. Kopec
There was no significant difference in the mea-
sured results only between the analyzers SFBIA
4
and
MFBIA
4-720
. In other cases, the final significance val-
ues ranged from p < .001 to p < .0001. As for results
with significant differences, medium practical signifi-
cance was found between the results of SFBIA
4
and
MFBIA
4-R20
(BF %, kg and TBW %), MFBIA
4-720
and
MFBIA
4-R20
(BF %, kg and TBW %) and MFBIA
4-R20
and SFBIA
2
(BF %, kg) (d = 0.5–0.7) and high practi-
cal significance only between MFBIA
4-R20
and SFBIA
2
in the values expressed in percentage (d = 0.9). Prac-
tical significance between the analyzers SFBIA
4
and
MFBIA
4-R20
(TBW kg), MFBIA
4-720
vs. MFBIA
4-R20
(TBW kg), SFBIA
4
– SFBIA
2
and MFBIA
4-720
and
SFBIA
2
was not shown in spite of significant differ-
ences (d = 0.1–0.3). The closeness of results between
the individual analyzers expressed in kilograms can
be considered to be high, up to very high (Westgard,
2008). The values of Pearson’s correlation coefficient
r explain 51–90% of variability. In values expressed in
percentage, there is a high closeness of results only
between the values of the analyzers MFBIA
4-720
and
MFBIA
4-R20
and SFBIA
4
and SFBIA
2.
The r values
explain 59–65% of variability. The closeness of results
between other analyzers is considerable (Westgard,
2008). The r values explain 41–46% of variability.
Similarly to the men, there was no significant dif-
ference in the measured values between SFBIA
4
and
MFBIA
4-720
; moreover, the female group also did not
show any significant difference in the values between
SFBIA
4
and MFBIA
4-R20
(except BF %). In other cases,
the significance ranged from p < .05 to p = .0001.
In spite of the significant difference in the results of
SFBIA
4
and MFBIA
4-R20
(BF %), MFBIA
4-720
and
MFBIA
4-R20
(BF %, kg and TBW %, kg), practical sig-
nificance was not shown (d = 0.1–0.3). The practical
significance in other cases was always high (d ≥ 0.8).
The values of the Pearson’s correlation coefficient r
show higher correlations between the results measured
by the used analyzers than in men. The closeness of
Table 3
Differences in measured values – males (n=70)
Diff r d 95% LoA
SFBIA
4
vs. MFBIA
4-720
BF (%) 0.0 .68 (–6.3, 6.3)
BF (kg) 0.0 .75 (–4.8, 4.8)
TBW (%) –0.2 .65 (–5.0, 4.6)
TBW (kg) –0.2 .93 (–3.6, 3.2)
SFBIA
4
vs. MFBIA
4-R20
BF (%) –2.6*** .67 0.6 (–9.1, 3.9)
BF (kg) –1.9*** .75 0.5 (–6.7, 2.9)
TBW (%) 1.4*** .63 0.5 (–3.5, 6.3)
TBW (kg) 1.0*** .93 0.2 (–2.4, 4.4)
MFBIA
4-720
vs. MFBIA
4-R20
BF (%) –2.6*** .81 0.6 (–7.4, 2.2)
BF (kg) –1.9*** .84 0.5 (–5.7, 1.9)
TBW (%) 1.6*** .79 0.5 (–2.1, 5.3)
TBW (kg) 1.2*** .95 0.3 (–4.1, 1.7)
SFBIA
4
vs. SFBIA
2
BF (%) 1.0** .77 0.2 (–4.0, 6.0)
BF (kg) 0.8** .82 0.1 (–3.1, 4.7)
MFBIA
4-720
vs. SFBIA
2
BF (%) 1.0** .66 0.2 (–5.0, 7.0)
BF (kg) 0.8** .72 0.1 (–3.9, 5.5)
MFBIA
4-R20
vs. SFBIA
2
BF (%) 3.6*** .64 0.9 (–2.6, 9.8)
BF (kg) 2.7*** .72 0.7 (–2.2, 7.4)
Note. Diff=difference, r=Pearson correlation coefficient, d=effect size, 95%LoA=95% limits
of agreement, SFBIA
4
=Tanita BC 418 MA, MFBIA
4-720
=InBody 720, MFBIA
4-R20
=InBody
R20, SFBIA
2
=Omron BF 300. **p<.001, ***p<.0001.
181
Comparison of body fat using various BIA analyzers
results is high, up to very high (Westgard, 2008). The
r values between analyzers SFBIA
4
and MFBIA
4-720
(TBW kg), SFBIA
4
and MFBIA
4-R20
(TBW kg), and
MFBIA
4-720
and MFBIA
4-R20
(BF, TBW % and kg)
explain 81–94% of variability. In other cases, the values
range from 50 to 79%.
The results of the Bland-Altman’s analysis of BF rep-
resentation (a primarily monitored parameter in this
study) are illustrated in the form of Bland-Altman’s
plots (Figures 1 and 2). The plots present the differ-
ences found in BF values expressed in percentage,
measured by two different analyzers. The plots show
that for the male group, the smallest differences in
the mean are between analyzers MFBIA
4-720
and
SFBIA
4
where the mean is almost zero (mean = 0.6).
In women, there were differences between MFBIA
4-720
and SFBIA
4
and MFBIA
4-R20
and SFBIA
4
(mean = –3.5
and 3.6). However, according to the 95% interval of
agreement, there are large differences in the individual
persons among the analyzers, which are manifested
by the wide interval of agreement. To assess the size
of the values measured by the individual analyzers,
we can use the assessment of mean displacement (the
Mean axis) in the plots. The displacement of the mean
axis downwards means that the results measured by the
second analyzer are higher than the results measured
by the first analyzers. The displacement of the mean
axis upwards means that the results measured by the
first analyzer are higher than the results measured by
the second analyzer. As an example of the mean dis-
placement downwards, in the male group we provide
a comparison between MFBA
4-720
and MFBIA
4-R20
(mean = –24.4) where MFBIA
4-R20
measures consider-
ably higher values. As an example of the mean displace-
ment upwards, in the male group we provide a compari-
son between MFBIA
4-R20
and SFBIA
2
(mean = 32.6)
where MFBIA
4-R20
also measured considerably higher
values. The relative differences in the measured values
in the individual participants are mostly concentrated
around the mean relative difference in the values of
Table 4
Differences in measured values – females (n = 55)
Diff r d 95% LoA
SFBIA
4
vs. MFBIA
4-720
BF (%) 0.6 .75 (–6.4, 7.6)
BF (kg) 0.3 .82 (–4.6, 4.0)
TBW (%) –0.5 .71 (–6.0, 5.0)
TBW (kg) –0.4 .94 (–3.6, 2.8)
SFBIA
4
vs. MFBIA
4-R20
BF (%) –1.0* .71 0.2 (–6.0, 8.0)
BF (kg) –0.7 .81 (–4.9, 3.5)
TBW (%) 0.1 .72 (–4.8, 5.0)
TBW (kg) 0.0 .95 (–3.0, 3.0)
MFBIA
4-720
vs. MFBIA
4-R20
BF (%) –1.6*** .94 0.3 (–5.1, 1.9)
BF (kg) –1.0*** .95 0.2 (–3.1, 1.1)
TBW (%) 0.6** .90 0.2 (–2.8, 4.0)
TBW (kg) 0.4** .97 0.1 (–1.4, 2.2)
SFBIA
4
vs. SFBIA
2
BF (%) 5.2*** .82 1.3 (–9.9, –0.5)
BF (kg) 3.0*** .89 1.0 (0.0, 6.0)
MFBIA
4-720
vs. SFBIA
2
BF (%) 4.6*** .74 1.0 (–2.2, 11.4)
BF (kg) 2.7*** .82 0.8 (–1.3, 6.7)
MFBIA
4-R20
vs. SFBIA
2
BF (%) 6.2*** .74 1.4 (–0.1, 12.5)
BF (kg) 3.7*** .84 1.1 (0.2, 7.2)
Note. Diff=difference, r=Pearson correlation coefficient, d=effect size, 95%LoA=95% limits
of agreement, SFBIA
4
=Tanita BC 418 MA, MFBIA
4-720
=InBody 720, MFBIA
4-R20
=InBody
R20, SFBIA
2
=Omron BF 300. *p<.05, **p<.001, ***p<.0001.
182
P. Kutáč and M. Kopec
the two analyzers MFBIA
4-720
and MFBIA
4-R20
which
is also reflected in the values of the Pearson’s correla-
tion coefficient r (Tables 3 and 4). It is thus obvious that
these two analyzers provide the most predictable results.
The analyzers have one manufacturer and therefore they
should have the same software for the calculation of BF.
Discussion
The study used BIA analyzers that use different fre-
quencies for the measurement, with electric current
going through different body parts. The objective of
the study was not to evaluate their validity against the
reference method as many studies dealing with this
issue have already been published. For the InBody
analyzers, the correlation with the DEXA reference
method was determined to be at the level of .94–.96;
the study included healthy men and women by the age
of 18 (Karelis, Chamberland, Aubertin-Leheudre, &
Duval, 2013). Even though they used a different ana-
lyzer than we did in this study, we can assume that the
InBody analyzers we used will have similar correlations
as they are made by the same manufacturer and use
the same frequencies, number of electrodes as well as
the method of conducting current through the human
Figure 1. Bland-Altman plots with 95% limits of agreement and correlation analysis of the differ-
ences between the body fat values measured by the used analyzers in percentage – males
183
Comparison of body fat using various BIA analyzers
body for the measurement. As for the single-frequency
analyzer SFBIA
4
, the value of correlation to the DEXA
method found in physical education students was
.82–.84 in relation to the used measuring mode (Kutáč,
Gajda, Přidalová, & Šmajstrla, 2008). As for single fre-
quency bipolar hand-to-hand analyzers, the values of
correlation with the DEXA method for the verification
of validity in sporting young men and women ranged
from .82 to .88 in relation to the used analyzers (Esco,
Olson, Williford, Lizana, & Russell, 2011; Loenneke
et al., 2013; Wang et al., 2013). Even though InBody
seems to be the most accurate analyzer, other analyz-
ers can also be considered sufficiently accurate as the
values of correlation in all the aforementioned studies
exceeded .8 which is a high closeness of results (West-
gard, 2008). Analyzers with such closeness of results
to the reference method may be considered to be suffi-
ciently accurate for the needs of the process of physical
education and diagnostics of athletes.
In the males, the lowest differences between the
mean values of BF representation were found between
the analyzers SFBIA
4
and MFBIA
4-720.
The overall anal-
ysis of the differences in the mean values measured by
the individual BIA analyzers did not show any depen-
dence that would be related to the used BIA analyzer.
The difference in the values measured by the analyzer
Figure 2. Bland-Altman plots with 95% limits of agreement and correlation analysis of the differ-
ences between the body fat values measured by the used analyzers in percentage – females
184
P. Kutáč and M. Kopec
of the same manufacturer, MFBIA
4-720
and MFBIA
4-R20
was greater than the difference between the single and
multi-frequency analyzers MFBIA
4-720
and SFBIA
4
or
MFBIA
4-720
and SFBIA
2
. On the other hand, the dif-
ference between the analyzers MFBIA
4-R20
and SFBIA
2
was the greatest of all comparisons in the male.
The diagnostic practice also needs to respond to the
question of the impact of the differences in the results
on the interpretation of the measured values. The
monitored men were students of physical education.
The mean values of the BF representation percentage
measured by the BIA method in physical education
students that are presented in some professional stud-
ies do not exceed 13% (Kutáč, 2012; Kutáč, Gajda, &
idalová, 2009; Kutáč, Přidalová, & Riegerová, 2008).
Therefore, the detailed analysis of the values measured
by the individual analyzers also focused on how many
participants would correspond with the mean values of
physical education students. The limit value was 13%
of body fat. For the SFBIA
4
analyzer it was found that
the body fat representation of 18 participants (25.71%)
did not correspond with the values of physical edu-
cation students (exceeded 13%); the number of 20
(28.57%) for MFBIA
4-720
, 31 (44.28%) for MFBIA
4-R20
and 13 (18.57%) for SFBIA
2
. The results show that
there would be different evaluation of several partici-
pants in case of interpretation of the acquired results.
There would be a significant difference especially when
using MFBIA
4-R20.
In the females, similarly to males, the lowest dif-
ferences in the mean values were found between the
analyzers SFBIA
4
and MFBIA
4-720
. The greatest dif-
ferences were found between the single frequency
BIA hand-to-hand analyzer (SFBIA
2
) and the other
analyzers. The SFBIA
2
analyzer measures the lowest
values. The found differences were even higher than
in the comparison of the measured values by the BIA
and DEXA methods (Gupta et al., 2011; Mojtahedi et
al., 2009; Kutáč et al., 2008; Trutschnigg et al., 2008).
In these studies, the differences did not exceed 2.7%
BF. To assess the impact of the found differences on
the interpretation of results in the diagnostic practice,
we will use the BF representation at the level of 25%,
which is the value stated for young female (Görner,
Boraczyński, & Štihec, 2009; Nazmi, Irfan, Osman,
& Serdar, 2011; Rutherford, Diemer, & Scott, 2011).
The value of 25% BF representation was exceeded in
25 female (45.45%) measured by SFBIA
4
, in 16 women
(29.09%) measured by MFBIA
4-720
, in 27 (49.09%) mea-
sured by MFBIA
4-R20
and only in 5 (9.09%) measured by
SFBIA
2
. There is a noticeable difference that became
apparent when the analyzer was changed. The greatest
difference would occur with the use of SFBIA
2
.
The differences in the mean values we found that
were measured by the used BIA analyzers are lower
than differences stated in other studies. The differences
in studies that dealt with the comparison of whole-
body analyzers with leg-to-leg analyzers reached the
mean value of 7.4% BF, and the value of 6.2% BF when
compared with hand-to-hand analyzers (Chin, Kiew, &
Girandola, 2006; Trutschnigg et al., 2008).
TBW is the primarily measured parameter in the
BIA method, BF values are calculated additionally.
The TBW value predicates the status of organism
hydration. Professional studies state that when hydra-
tion decreases by 2 to 3%, there is a substantial reduc-
tion of performance in physical activities (García-
Jiménez, Lucas, & García-Pellicer, 2011; Hamouti, Del
Coso, Estevez, & Mora-Rodriguez, 2010; Maughan
& Shirreffs, 2010). A decrease of hydration by 3–5%
causes digestive issues during training and muscle
spasms (Beachle & Earle, 2008; Burke, 2007; Montain,
2008; Oppliger & Bartok, 2002). From this point of
view, we can state that the differences we found in the
mean values measured by the individual analyzers are
negligible. Even though some differences were statisti-
cally significant and the value of Cohen’s d showed the
medium value of the effect of size, none of the differ-
ences exceeded the level of 2% TBW; the differences
ranged from 0 to 1.6% TBW. As for BF, the differences
found were within the difference intentions. However,
a more detailed analysis of the differences in the indi-
vidual participants showed that the difference in the
range of 2–3% TBW was found in 13 (18.6%) males
between SFBIA
4
and MFBIA
4-720
, in 16 (22.3%) males
between SFBIA
4
and MFBIA
4-R20
, and in 11 (15.7%)
males between MFBIA
4-720
and MFBIA
4-R20
. As for
females, there were 11 (20%) participants between
SFBIA
4
and MFBIA
4-720
, 15 (27.3%) between SFBIA
4
and MFBIA
4-R20
, and 6 (10.1%) between MFBIA
4-720
and MFBIA
4-R20
. The difference in the range of 3 to 5%
TBW was found in 10 (14.3%) males between SFBIA
4
and MFBIA
4-720
, 19 (27.1%) males between SFBIA
4
and MFBIA
4-R20
, and 16 (22.9%) males between
MFBIA
4-720
and MFBIA
4-R20
. In females, the differ-
ence was found in 13 (23.6%) participants between
SFBIA
4
and MFBIA
4-720
, 11 (20%) between SFBIA
4
and MFBIA
4-R20
, and 3 (5.5%) between MFBIA
4-720
and
MFBIA
4-R20
. As the detailed analysis implies, the evalu-
ation of the final values of several participants could be
misinterpreted if the analyzers were changed.
Study limitations
We are aware of the fact that the results we obtained
might be influenced by the selected groups. The moni-
tored males are individuals with regular physical activ-
ity which they perform in their field of study. These
185
Comparison of body fat using various BIA analyzers
individuals are also active athletes at the performance
level. Therefore, their results may only apply to the
sporting population.
The validity of the results is also limited by the
used BIA analyzers. Since there is a wide range of BIA
analyzers on the market, the submitted study could be
considered a base for including other BIA analyzers, or
other population groups in the research.
Conclusions
Even though the differences between the mean values
measured by the used analyzers were low in majority
of the cases and ranged at the level of the errors of
measurement, a detailed analysis showed substantially
higher differences in several participants. Replacing an
analyzer with a different one could lead to misinterpre-
tation of the measured values in diagnostics. The differ-
ences found during repeated measurements would not
need to be a result of an external intervention or the
ontogenetic development of the individual; they could
be caused by different measuring of the analyzers.
The results also showed significant (statistically and
practically) differences between analyzers by the same
manufacturer, but a different series. It is thus obvious
that a high correlation of measured values does not
guarantee conformity of results and therefore, it is not
recommended to even use different types of analyzers
by one producer in practice.
Acknowledgment
This study was financed by the project no. SGS 6136/
PdF/2013.
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Dual-energy X-ray absorptiometry (DXA) is rapidly becoming more accessible and popular as a technique to monitor body composition. The reliability of DXA has been examined extensively using a number of different methodological approaches. This study sets up to investigate the accuracy of measuring the parameters of body composition (BC) by means of the whole-body and the segmental DXA method analysis with the typical error of measurement (TEM) that allows for expressing the error in the units of measure. The research was implemented in a group of 63 participants, all of whom were university students. Thirty-eight males (22.6±2.9 years, average body mass 77.5±8.4 kg) and 25 females (21.4±2.0 years, average body mass 58.6±7.2 kg) were recruited. The measured parameters included body mass (BM), fat-free mass (FFM), body fat (BF), bone mineral content (BMC), bone mineral density (BMD). For the whole-body analysis, the determined TEM was: BM at the level of 0.12 kg in females and 0.29 kg in males; BF 0.25kg and 0.44% females, 0.52 kg and 0.66% males; FFM 0.24 kg females and 0.42 kg males; BMC 0.02 kg females and males; BMD 0.01g/cm² females and males. The TEM values in the segmental analysis were: BF within the range of 0.04–0.28 kg and 0.68–1.20% in females, 0.10–0.36 kg and 0.72–1.94% in males; FFM 0.08–0.41 kg females and 0.17–0.86 males, BMC 0.00–0.02 kg females and 0.01–0.02 kg males in relation to the body segment (upper limb, trunk, lower limb). The BMD value was at the level of 0.01–0.02g/cm². The study results showed high reliability in measuring body composition parameters using the DXA method. The whole-body analysis showed a higher accuracy of measurement than the segmental. Only the changes that are greater than the TEM, or the upper bound (95%) of the confidence interval of the measurement can be considered demonstrable when interpreting repeated measurements.
... The problems seem to be concentrated in the algorithms used to calculate the body segments in the different types of BIA equipment used in research [35]. When applied to the same subjects, different types of BIA provided non-concordant results in the assessment of body composition [35][36][37]. This may explain divergences between results obtained with BIA. ...
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Introduction Bariatric surgery has a significant influence on body composition (BC), which should be monitored. However, there is a need to recommend low-cost practical methods, with good estimation of BC for class III obese and/or bariatric patients. Objective The aim of this study was to determine accuracy and agreement between BC assessed by direct segmental multifrequency bioelectrical impedance analysis (DSM-BIA) and doubly labeled water (DLW) as reference method. Material and Methods Twenty class III obese women (age 29.3 ± 5.1 years; body mass index 44.8 ± 2.4 kg/m²) underwent Roux-en-Y gastric bypass surgery. BC (fat mass [FM], fat-free mass [FFM], and total body water [TBW]) was assessed by InBody 230 and DLW in the following periods: before and 6 and 12 months after surgery. Accuracy between the methods was evaluated by the bias and root mean square error. Pearson’s correlation, concordance correlation coefficient (CCC), and Bland-Altman method were used to evaluate agreement between the methods. Results Correlations were significant (p < 0.001) and CCC was good/excellent between both methods for the evaluation of FM (r = 0.84–0.92, CCC = 0.84–0.95), FFM (r = 0.73–0.90, CCC = 0.68–0.80), and TBW (r = 0.76–0.91, CCC = 0.72–0.81) before and after bariatric surgery. In addition, no significant bias was observed between DSM-BIA and DLW for FM (mean error [ME] = − 1.40 to 0.06 kg), FFM (ME = 0.91–1.86 kg), and TBW (ME = 0.71–1.24 kg) measurements. Conclusion The DSM-BIA was able to estimate the BC of class III obese women submitted to bariatric surgery with values consistent with those of the DLW method.
... In the current study, the same instruments including InBody R20 were used for both the pre and post assessments since the measurement by different analyzers will be misleading. [68] In the current study, the control group was not given chance to gather together, which is a form of social cohesion. In the yoga group, the social cohesion also might have affected stress reduction and sleep quality. ...
... In the current study, the same instruments including InBody R20 were used for both the pre and post assessments since the measurement by different analyzers will be misleading. [68] In the current study, the control group was not given chance to gather together, which is a form of social cohesion. In the yoga group, the social cohesion also might have affected stress reduction and sleep quality. ...
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... Pouzdanost dobijenih vrednosti zavisi i od drugih faktorapoložaja tela, trajanja merenja, hidriranosti, faze mensturalnog ciklusa kod žena i dr. Metoda ima svoju primenu u različitim populacijama zdravih i bolesnih ljudi, kada se može koristiti i za procenu malnutricije kod kritično obolelih [19,20]. ...
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The study deals with one of the characteristic features of a PE teacher. It concerns the area of motional competences, which also includes body composition. Because of the diffculty in collecting data from working PE teachers, we decided to focus on future PE teachers - university students of PE and sports. The data collected indicates typical features of the future PE teacher.
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The purpose of this investigation was to evaluate three bioelectrical impedance analysis (BIA) prediction models for fat-free mass (FFM) using the U.S. National Women’s Gymnastics team ( N = 48; age = 15.8 ± 1.8 years). One model had been developed recently using dual-energy x-ray absorptiometry (DEXA) as the criterion measure, whereas the other two used hydrodensitometry. In this investigation, FFM predictions were compared with measures obtained via DEXA. FFM measured by DEXA averaged 40.5 ± 7.4 kg (± SD ), whereas values generated using the three BIA models were within 0.8 kg of this actual measure. Validity coefficients for all models were high ( Rxy = .95-98). FFM prediction error was lowest with the model using DEXA as the criterion measure (1.3 kg) compared with the other two (1.9 and 2.4 kg). All BIA models underpredicted FFM in the heaviest girls, and the Lohman and Van Loan et al. models overpredicted FFM in the lightest girls. Whereas prediction error was significantly correlated to the girls’ bone mineral density in all BIA models, this relationship was strongest in the two that were developed using hydrodensitometry.
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