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Single prediction equation for bioelectrical impedance analysisin adults aged 2259 years
B. R. PATIL*{, D. P. PATKAR{, S. A. MANDLIKx, M. M. KUSWARKARx and G. D. JINDALx
{Department of Instrumentation Engineering, Bharati Vidyapeeth College of Engineering,Navi Mumbai, 400 614, India
{MRI Centre, Dr Balabhai Nanavati Hospital, Vile Parle (West), Mumbai, 400 056, IndiaxBio-Medical Section, Electronics Division, Modular Laboratories, B.A.R.C., Mumbai, 400 085, India
(Received 17 October 2010; revised 14 December 2010; accepted 24 November 2010)
The purpose of this study was to validate a single bioelectrical impedance analysis (BIA)
equation in healthy Indian subjects aged 2259 years with a body mass index (BMI)
between 16.8 and 47.3 kg m72. Healthy subjects (34 men and 30 women) were measured
by two methods: bone mineral content (BMC) was measured by a commercial body
composition analyser and bioelectrical impedance at various frequencies was measured
by a newly developed bioelectrical impedance measurement system. As correlations were
high and prediction error was low, a single equation was developed using all subjects
as follows: BMC73.5268 (0.02796 h) (0.01456w) (1846 (h2/Zbody50)) (1.086 (w6 h2/Zbody6.25)) (0.00326 (age)) (0.1036 (sex); men 1, women 0).BMC measured from commercial instrument InBody720 was 2.552+ 0.457 kg. BMCpredicted by equation was 2.554+ 0.447 kg (R 0.976, adjusted R2 0.948, standarderror of estimate 0.104 kg, total error 0.09987 kg). The results of this study show thatthe newly developed multi-frequency bioelectrical impedance measurement system with
the single prediction BIA equation can be used in screening the subjects suspected with
osteoporosis and for follow-up study of the patient under the therapy for osteoporosis.
For validation of commercial instrument InBody720, BMC of 22 healthy subjects was
measured by InBody720 and dual-energy X-ray absorptiometry. High correlation
(R 0.9531) and low error (total error 0.0913 kg) was found between these twomethods.
Keywords: Body parameters; Bioelectrical impedance analysis; Bone mineral content;
Osteoporosis
1. Introduction
Osteoporosis is a disease in which the bones deteriorate and
become weak and fragile. Around 500 million populations
worldwide are estimated to have osteoporosis. Osteoporo-
sis in women is increasingly being recognized as an
important health issue. In the early stage of this disease
there may be no symptoms. It is frequently painless until a
bone breaks. In fact, a fractured bone may be the rst
symptom of osteoporosis. Osteoporosis is also character-
ized by an abnormal loss of bone mineral content, which
leads to a tendency to non-traumatic bone fractures or to
*Corresponding author. Email: babapatil2004@yahoo.co.in
Journal of Medical Engineering & Technology, Vol. 35, No. 2, February 2011, 109114
Journal of Medical Engineering & TechnologyISSN 0309-1902 print/ISSN 1464-522X online 2011 Informa UK, Ltd.
http://www.informahealthcare.com/journalsDOI: 10.3109/03091902.2010.543751
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structural deformations of bone [1]. Osteoporosis is a
widespread medical condition aecting middle-aged and
older people [2]. The accurate estimation of the BMC has
been an important diagnostic indicator for determining the
status of osteoporosis and for the follow-up study of
patients under therapy for osteoporosis. Various BMC
measurement techniques/methods are available, such as
dual-energy X-ray absorptiometry (DEXA), ultrasound
densitometry and quantitative computed tomography
(QCT). DEXA is the most well-known method. However,
the use of DEXA is limited because of its practicability
and cost.
Bioelectrical impedance analysis (BIA) is a user-
friendly, safe, simple, inexpensive and non-invasive
technology for clinical and non-clinical purposes. Mea-
surements can be made quickly and can be repeated at
short time intervals. BIA has the potential to provide
more information regarding the functioning of the human
body. To date the full potential of this technology has
not been realized. Commercial instruments available for
BIA measure electrical parameters in dierent body
segments and yield clinical information regarding total
body water, fat free mass, and body fat, etc. Many
investigators have developed empiric BIA equations for
prediction of fat-free mass, total body water and body
fat [314]. Most of these equations have been validated in
relatively young healthy adults against several body-
composition techniques [10]. Studies have shown that
BIA formulae developed for healthy, normal-weight sub-
jects are not suitable for obese subjects [14, 15]. In
longitudinal studies, the use of dierent BIA formulae in
the same subject who becomes overweight introduces a bias
into body-composition studies, making one question
whether the dierences in body composition are due to
changes in the BIA formula or due to changes in body
composition. Thus, it would be advantageous to use a
single formula that is applicable in both normal and
overweight subjects and permits estimation of body
composition. Roubeno et al. [14] and others concluded
that BIA equations are subject to errors that cannot be
determined a priori unless they are validated in the specic
population in which they are to be applied [1618]. Thus,
BIA equations must be validated in a representative
population sample against a reference method before they
can be accepted as accurate. The purpose of the present
investigation was to validate a single BIA equation for
the assessment of BMC, against the commercial device
InBody720 (Biospace, Seoul, Korea) which was validated
with DEXA [19]. DEXA is a reference method for BMC
that has been validated against many independent methods.
A single BIA equation that is valid in subjects with dierent
BMIs for use in longitudinal studies would be a signicant
advantage in screening subjects suspected with osteoporosis
and for follow-up study of patients under therapy for
osteoporosis.
2. Subjects and methods
2.1. Subjects
The study group consisted of 64 individuals (34 men and 30
women) in the age group of 22 to 59 years. All subjects were
born in India and resided in Mumbai. Although subjects
were randomly selected, statistical analysis showed not
much dierence in (h), (w) and BMI between subjects and a
control group of healthy age-matched 264 men and 279
women. Body height was measured to the nearest 0.5 cm.
The purpose of the study was explained to all subjects and
their oral consent was taken. Each subject was measured by
two methods: bone mineral content (BMC) was measured
by a commercial instrument (InBody720, Biospace) and
bioelectrical impedance at various frequencies was mea-
sured by a newly developed bioelectrical impedance
measurement system.
2.2. Segmental multi-frequency bioelectrical impedance
analysis (MF-BIA) instrument (InBody720)
The BMC of each subject was obtained from the segmental
multi-frequency bioelectrical impedance analysis instru-
ment (InBody720). From segmental impedance values,
using proprietary equations, the instrument gives an
estimated value of BMC. The correctness of this estimated
value is validated against DEXA measurement. This
commercial product is approved by FDA (Food and Drug
Administration, United States, May 2003). The instrument
was operated at frequencies of 1, 5, 50, 250, 500 and 1000
kHz which were pre-set by the manufacturer and intro-
duced into the body in the ascending order of frequency.
This device uses contact electrodes, located in the handgrips
and the footpads. Subjects were asked to stand with the ball
and heel of each foot on two metallic electrodes on the oor
scale and hold handrails with metallic grip electrodes in
contact with the palm and thumb [20, 21]; they were
instructed to keep their arms fully extended and abducted
approximately 208 laterally. For 1 kHz programmedfrequency, an alternating current of 100 mA and for otherprogrammed frequencies, an alternating current of 500 mAwas applied between a pair of carrier electrodes, and
voltage was measured across a pair of sensing electrodes.
For cross validation of InBody720, the BMC of healthy 22
subjects was measured by InBody720 and dual-energy
X-ray absorptiometry (Lunar Prodigy, DPX-IQ, General
Electric Healthcare, Belgium, Europe). High correlation
(R 0.9531) and low error (total error 0.0913 kg) werefound between these two methods (gure 1).
2.3. Developed multi-frequency bioelectrical impedance
measurement system
The body impedance of each subject at various frequencies
was measured and recorded by the new system, using the
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whole body impedance measurement approach. The system
operated at frequencies of 6.25, 12.5, 25, 50 and 100 kHz
which were pre-set and introduced into the body in the
ascending order of frequency. Before testing, standardiza-
tion of a subjects posture is not required. Subjects were
asked to sit on the chair with connected electrodes. For
each of the programmed frequencies, an alternating current
of 500 mA was applied between silver band currentelectrodes, which are located in the palm and feet on same
side. The two sensing electrodes are located in the wrist and
ankle on the same side. The amplitude of the sensed voltage
drop is directly proportional to the impedance of the body
(Zbody) between the sensing electrodes. Figure 2 shows a
schematic block diagram of the multi-frequency bioelec-
trical impedance measurement system. The Biomedical
Instrumentation Processor Board (BMIPB) is an interface
board used to interface the system with compatible PC. The
100 kHz square wave signal is derived from BMIPB, which
is further divided by the synchronous up/down counter and
produces the four square wave singles of 50, 25, 12.5 and
6.25 kHz frequencies. For smoothening, each square wave
signal is ltered with the help of second order low pass lter
followed by a band pass lter. This produces pure
sinusoidal alternating signals. These signals are then
multiplexed with the help of an analogue multiplexer.
Any one of the signals can be selected at the output of the
multiplexer by the operator through the user interface
panel. The selected signal is applied to the VI (voltage to
current) converter. The sinusoidal alternating current of
constant magnitude produced by VI converter is passed
through the body with the help of isolation transformer.
The voltage signal developed along the current path is
sensed with the help of sensing electrodes and amplied
using a precision instrumentation amplier. The wide band
pass lter removes the superimposed noise and produces a
pure sinusoidal alternating voltage, which is proportional
to the impedance of the body under investigation. Further
the output of the band pass lter is rectied, ltered and
buered to obtain a pure DC voltage which is also
proportional to the body impedance. The injected sinusoi-
dal alternating current and the voltage signal developed
along the current path were multiplied by analogue
multiplier. The two componentsdouble frequency sinu-
soidal signal and DC signal (mean value)were separated
by the second order low pass lter.
2.4. Statistics
Descriptive statistics were calculated for (h), (w), (age),
(sex), BMI and BIA parameters, including body impedance
(Zbody), (Zbody/h), (Zbody/w), (h2/Zbody) and (w6 h
2/Zbody)
at 6.25, 12.5, 25, 50 and 100 kHz frequencies. The values
were expressed as mean+ standard deviation (SD). Simpleregressions were calculated to test correlations between
BMC obtained from InBody720 and BIA parameters
measured from developed bioelectrical impedance measure-
ment system. Student t-test was used to test dierences
between methods. BMC measured by commercial instru-
ment InBody720 was used as the criterion measurement.
Stepwise multiple regression analysis was used to derive a
prediction equation by BIA. Predictor variables, entered
into the BIA model in the order of highest correlation
coecient and smallest standard error of estimation (SEE)
were (h2/Zbody50), h, w, (w6 h2/ ZBody6.25), (sex) and (age)
and a single equation was developed using the entire
sample. In addition to correlation and regression techni-
ques, error analysis was performed. SEEs were calculated
and used as errors of prediction for InBody720 derived
BMC and predicted BMC by BIA equation. The total error
(TE) was calculated as:
TE P
ni BMC1i BMC2i 2
n 2
s; 1
where (BMC1) is the observed value of BMC by In-
Body720 and (BMC2) is the predicted value of BMC by
equation. The total error of measurement estimates the
magnitude of the error for a given measurement and is
dened as the dierence between measurements for the
individual (i), i 1, . . . , n, where n is the number ofindividuals [22]. The total error was compared with the
SEE. A small dierence between total error and SEE
indicates high accuracy of the prediction. To assess the
agreement between the two clinical measurements the
dierence between the values was plotted against their
means because the mean was the best available estimate of
the true value. This analysis allows for the calculation of
bias (estimated by the mean dierences), the 95%
condence interval for the bias, and the limits of agreement
(two SDs of the dierence) [23]. Statistical signicance was
set at p 5 0.05 for all tests.
Figure 1. Relationship between bone mineral content
(BMC) measured with DEXA and the commercial instru-
ment InBody 720.
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3. Results
A total of 64 healthy adults aged 2259 years were recruited
as subjects. Table 1 shows the anthropometric character-
istics and table 2 shows the BIA characteristics of subjects
grouped by dierent frequencies. The prediction equation
developed from all subjects is shown in table 3. The order
of entry of predictor variables was (h2/Zbody50), h, w, (w6h2/Zbody6.25), (sex) and (age) for the BIA model (table 4).
(h2/Zbody50) accounted for 84.12% of the variability
(SEE 0.182 kg) of the equation whereas (h) aloneaccounted for only 74.51% of the variability (SEE0.231kg) and (w) alone accounted for 53.74% of the
variability (SEE 0.311 kg). Inclusion of height (h), weight(w), (age) and (sex) without BIA parameters accounted for
92.62% of the variability with a SEE of 0.124 kg. Thus
inclusion of BIA parameters clearly improved the prediction
power and decreased the SEE compared with anthropo-
metric parameters only. Figure 3 shows the correlation and
mean dierence, according to Bland and Altman [23], using
the prediction equation in all subjects [23]. Subjects (data
not shown) with BMIs above 27 kg m72 were analysed
separately to determine whether greater error occurred with
the BIA equation in larger subjects. BMC measured for 22
subjects with BMIs above 27 kg m72 from commercial
instrument InBody720 was 2.701+ 0.5473 kg. BMCpredicted by equation was 2.706+ 0.5173 kg (R 0.978,total error 0.114 kg). Thus, it is possible to estimate BMCwith the same equation for overweight and obese subjects.
Figure 2. Schematic block diagram of the multi-frequency bioelectrical impedance measurement system.
Table 1. Anthropometric Characteristics of healthy subjects.
Men Women Combined
n 34 30 64
(age) (years) 36.15+ 8.72 43.9+ 7.83 39.78+ 9.12h (cm) 167.1+ 6.47 155.2+ 5.08 161.50+ 8.33w (kg) 73.23+ 14.44 62.08+ 8.79 68.01+ 13.26BMI (kg m72) 26.2+ 4.88 25.9+ 4.18 26.1+ 4.53
nnumber of subjects; hheight; wweight; BMI body mass index
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Table 2. Bioelectrical impedance analysis characteristics of healthy subjects (n 64).Frequency (kHz)
6.25 12.5 25 50 100
(Zbody) (O) 658.31+ 101.10 563.98+ 91.41 499.44+ 78.74 460.19+ 73.31 425.22+ 62.87(Zbody /h) (O cm
71) 4.09+ 0.73 3.51+ 0.66 3.11+ 0.57 2.87+ 0.53 2.65+ 0.46(Zbody/w) (O kg
71) 10.17+ 3.06 8.72+ 2.66 7.72+ 2.33 7.11+ 2.15 6.56 + 1.89(h2/Zbody) (m
2 O71) 0.0041+ 0.0009 0.0048+ 0.001 0.0054+ 0.001 0.0058+ 0.001 0.0063+ 0.001(w6 h2/Zbody)(kg m2 O71)
0.289 + .137 0.338+ 0.162 0.382 + 0.179 0.415+ 0.196 0.447+ 0.211
nnumber of subjects; Zbody body impedance; hheight; wweight.
Table 3. Prediction equation for BMC using all subjects(n 64).
BMC73.5268 (0.02796 h) (0.01456w) (1846 (h2/Zbody50) (1.086 (w6 h2/Zbody6.25)) (0.00326 (age)) (0.1036 (sex);men 1, women 0)
Observed BMC by commercial instrument (InBody720) 2.552+0.457 kg
Predicted BMC 2.554+ 0.447 kg (R 0.976, adjusted R2 0.948,SEE 0.104 kg, TE 0.09987 kg)
nnumber of subjects; BMC bone mineral content; Zbody50bodyimpedance at 50 kHz; h height; wweight; Zbody6.25body im-pedance at 6.25 kHz; R validity coecient; SEE standard error ofthe estimate; TE total error.
Table 4. Contribution and order of entry of variables to thebioelectrical impedance analysis model and anthropometric
model for bone mineral content (n 64 subjects).
Model and variables
Cumulative variables
used in model Variables
Ad.R2 SEE P Ad.R2 SEE P
BIA
(h2/Zbody50) 84.12 0.182 0.0001 84.12 0.182 0.0001
h 91.87 0.130 0.0001 74.51 0.231 0.0001w 93.70 0.115 0.0001 53.74 0.311 0.0001(w6 h2/Zbody6.25) 94.39 0.108 0.0001 62.89 0.278 0.0001(sex) 94.57 0.106 0.0001 49.49 0.325 0.0001(age) 94.80 0.104 0.0001 6.24 0.442 0.0001
BMI
h 74.51 0.231 0.0001
hw 91.82 0.131 0.0001hw (age)
92.73 0.123 0.0001
hw (age) (sex)
92.62 0.124 0.0001
n number of subjects; BIA bioelectrical impedance analysis;BMIbody mass index; hheight; wweight; BMCbone mineralcontent; Zbody50body impedance at 50 kHz; Zbody6.25 bodyimpedance at 6.25 kHz; SEE standard error of the estimate;P signicance of contribution of each additional individual para-meter to the stepwise multiple regression model; Ad.R2% adjustedsquared value of the validity coecient.
Figure 3. Correlations (a) and dierences (b) of bone
mineral content (BMC) in all subjects estimated by
commercial instrument InBody720 and developed BIA
equation. The dierence (BMC obtained by InBody720
BMC calculated by BIA equation per BlandAltman) is
plotted against the mean of the measurements of BMC by
commercial instrument InBody720 and developed BIA
equation. SEE, standard error of the estimate; R, validity
coecient; TE, total error. Circles indicate men; triangles
indicate women.
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4. Discussion
BIA has been developed for eld use and has shown great
potential for use in estimating body composition and it is
easy, non-invasive, and inexpensive. In osteoporosis, bones
become porous and bone mineral content reduces as
minerals such as calcium leach out. Bones aected by
osteoporosis are less dense than the normal bones, resulting
in reduction in their density and an increase in their
resistivity. Due to the change in resistivity of bones, the
bioelectrical parameters of the body changes and provide
quantitative information about the BMC.
All subjects in this study were reported to be healthy. The
BIA equation developed in this study is valid for healthy
adults 2259 years old. Slightly lower accuracy should be
expected in subjects older than 60 years. Validity of the BIA
equation in subjects older than 60 years is unknown and
requires further validation. It is also necessary in subjects
with BMIs below 17 kg m72.
5. Conclusion
The results of this study show that the newly developed
system with the single prediction BIA equation validated
against commercial instrument (InBody720, Biospace, Seoul,
Korea) can be used to predict BMC in subjects aged 2259
years and with BMIs ranging from 16.8 to 47.3 kg m72. This
low cost, portable and simple system will help in screening
subjects with suspected osteoporosis and in follow-up studies
of patients under therapy for osteoporosis.
Acknowledgements
This studywas supportedby theElectronicsDivision,Bhabha
Atomic Research Centre (BARC),Mumbai and Dr Balabhai
Nanavati Hospital, Mumbai. We are thankful to Aarti
Karkera for helping in data collection and S. K. Athawale
for proof-reading. We are also grateful to G. P. Srivastava,
Director, E & I Group, R. K. Patil, Associate Director, E & I
Group (C) and C. K. Pithawa, Head, Electronics Division of
BARC for their support and encouragement.
Declaration of interest: The authors declare that they have
no conict of interest.
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