IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 52, NO. 6, JUNE 2005 975
Fat and Hydration Monitoring by Abdominal
Bioimpedance Analysis: Data Interpretation by
Hierarchical Electrical Modeling
Hermann Scharfetter*, Patricia Brunner, Michael Mayer, Bernhard Brandstätter, and Helmut Hinghofer-Szalkay
Abstract—In a previous publication, it was demonstrated that
the abdominal subcutaneous fat layer thickness (SFL) is strongly
correlated with the abdominal electrical impedance when mea-
sured with a transversal tetrapolar electrode arrangement. This
article addresses the following questions: 1) To which extent do
different abdominal compartments contribute to the impedance?
2) How does the hydration state of tissues affect the data? 3) Can
hydration and fat content be assessed independently?
For simulating the measured data a hierarchical electrical model
was built. The abdomen was subdivided into three compartments
(subcutaneous fat, muscle, mesentery). The true anatomical struc-
ture of the compartment boundaries was modeled using finite-ele-
ment modeling (FEM). Each compartment is described by an elec-
trical tissue model parameterized in physiological terms.
Assuming the same percent change of the fat fraction in the
mesentery and the SFL the model predicts a change of 1,24 /mm
change of the SFL compared to 1,1 /mm measured. 42% of the
change stem from the SFL, 56% from the mesentery and 2% from
changes of fat within the muscle compartment. A 1% increase of
the extracellular water in the muscle is not discernible from a 1%
decrease of the SFL.
The measured data reflect not only the SFL but also the visceral
fat. The tetrapolar electrode arrangement allows the measurement
of the abdominal fat content only if the hydration remains constant.
Index Terms—Bioimpedance, fat monitoring, electrical tissue
modeling, finite elements, subcutaneous fat, visceral fat.
I. INTRODUCTION
T
HERE exists a huge number of publications dealing with
the estimation of body composition from measurements
of the electrical impedance of body segments (bioimpedance
analysis (BIA); see, e.g., [1]).
The assessment of the human body composition in terms
of body fat (BF) and lean [fat free mass (FFM)] fractions in
varyious compartments is of particular interest in different dis-
ciplines such as sports sciences, clinical nutrition, assessment
of the nutritional status of the elderly population, management
of obesity and associated risk factors (cardiovascular diseases,
Manuscript received April 6, 2004; revised November 14, 2004. This work
was supported in part by the Austrian Science Fund under Project P16413. As-
terisk indicates corresponding author.
*H. Scharfetter is with the Institute of Medical Engineering, Graz University
of Technology, 8010 Graz, Austria (e-mail: scharfetter@bmt.tu-graz.ac.at).
P. Brunner and M. Mayer are with the are with the Institute of Medical Engi-
neering, Graz University of Technology, 8010 Graz, Austria.
B. Brandstätter is with the Institute of Electrical Measurement and Measure-
ment Signal Processing, Graz University of Technology, 8010 Graz, Austria.
H. Hinghofer-Szalkay is with the Institute for Systems Physiology, Graz Uni-
versity of Technology, 8010 Graz, Austria.
Digital Object Identifier 10.1109/TBME.2005.846733
diabetes). However, the reliability of all impedance methods
presented so far is very limited. The relative deviation of the
BF measured with BIA and reference methods has been inves-
tigated in various validation studies [1]–[5]. When compared to
underwater weighting the BF as determined with BIA shows a
standard error of the difference between 2% and 5% of the total
body mass [1]–[5]. As the BF ranges between 5%–40% in men
and 10%–45% in women, the percent errors are comparatively
large, especially in lean subjects where they can go up to several
tens of percent.
The errors are at least partly due to the low direct sensitivity of
BIA to the quantity of adipose tissue. Instead, the electrical cur-
rent passes essentially through the fat-free, highly conducting
regions. It was found [6] that the fat contributes significantly to
the overall conductance only in considerably obese people so
that the muscle represents the main conductor. The error prop-
agation from the estimated FFM to the derived BF makes the
method highly susceptible to interferences, e.g., with the water
content of the FFM. The redistribution of body fluids, e.g., due
to orthostatic processes, can cause considerable errors in the
estimation of BF by BIA. Moreover, the data obtained from
so-called whole-body measurements (measured from wrist to
ankle) contain only little information about the trunk, as the
latter contributes only with 5%–10% to the total impedance [5].
Essentially the same is true for the leg-to-leg or arm-to-arm con-
figuration, which has also been suggested. Therefore, a more di-
rect method with high sensitivity to the adipose tissue in central
body compartments is highly desirable.
Actually most fat mass estimators are based on the idea that
the fat mass can be obtained by subtracting FFM, which is neg-
atively correlated with impedance, from body mass. To reduce
the error due to poor correlation between impedance and fat
mass usual estimators consider also other anthropometric data
such as body mass, height, sex and age. The best reproducibility
is mostly obtained from such estimators in which the relative
weight of the impedance is comparatively low. This is somewhat
unsatisfactory because in that way impedance measurements do
not really contribute as much diagnostic information as they the-
oretically contain.
Intuitive quantities of interest are an index for the subcuta-
neous fat mass and the fraction of adipose tissue in the muscular
and in the mesenteric compartments. However, it is not trivial
to define these parameters precisely. A more general analysis
might include the frequency dependence of the conductivities
of the different tissues as they contain information about some
microstructural properties, e.g., about the hydration state.
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