Download Bio-electrical impedance analysis: a good tool for

Bio-electrical impedance analysis: a
good tool for dieticians?
NUTRIDAYS, 9 april, Bern
Ir. Paul JM Hulshof
Division of Human Nutrition, Wageningen University,
The Netherlands
The importance of measuring nutritional
status
Deviations from “normal” can result in
• Increased risk morbidity and mortality
• Altered performance
• Functional impairment
Deviations from “normal” status
From: Cederholm et al: Diagnostic criteria for malnutrition – An ESPEN
Consensus Statement; Clinical Nutrition 34 (2015) 335-340
Consensus on diagnostic criteria for
malnutrition in a clinical setting
Expert opinions on
what should be
measured
From: Cederholm et al, 2015
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Measurement of body composition (FFM or
BCM) is key for assessing nutritional status
 Fat Free Mass (FFM) or Body cell mass (BCM):
● Metabolically active, functional tissue
● Key compartment of nutritional status
● Early detection of malnutrition:  loss of
FFM/BCM
 Loss of body weight alone:
● Can be masked by fluid /fat overload:
expansion of ECW or body fat compartment
can cause TBW and weight to remain constant
thus masking loss of FFM
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Body composition methods
Level
Techniques often used
Component
Atomic
Neutron activation analysis
Whole body counting
C, H, N, O, Ca, Na, Cl,
P, other
Total body potassium
Molecular
DEXA
Tracer technique (D2O/ KBr)
Bone mineral /FM/FFM
TBW / ECW
Cellular
Tracer techniques
ICF/ECF, elements,
other
Tissue
Imaging techniques: MRI,
CT, ultrasound
Muscle mass
Adipose tissue,
Ectopic fat tissue
Whole
body
Anthropometry, Under water Anthropometric
weighing, Air displacement
indices, Body Volume,
plethysmography, Impedance resistance/reactance
 Anthropometry
 Bio-electrical impedance
 Total N or K, CT-scan, MRI
multi-component models
• Cost
 DEXA or volume measurement
• Accuracy
 Dilution methods
• Practical applicability
Features of body composition techniques
Criterion methods are not widely available, expensive,
time consuming and require non-portable equipment
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Bio-impedance
Bio-impedance = resistance of a body when a
non perceivable alternating current is applied
 Based on differences in electrical conductivity
(impedance) of body compartments
 Involves application of alternating current to body
 Impedance (Z) has two components:
● Resistance (R) and Reactance (Xc)
 Modes:
● Single and Multi Frequency BIA
● Bio-Impedance Spectroscopy
 Indirect estimate of body comp.
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Tissue conductivity at different
frequencies
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Stahn et al, 2012
Whole body impedance: wrist-ankle
method
From Xitron
Technologies Inc.
Bio-impedance devices
Bio-impedance principle
1-5 kHz
> 50 kHz
Z2 = R2 + Xc2
From Lindley, 2009
Simple electric circuit
No capacitance, only resistor: V and I in phase
Human body: complex electric circuit
Intra- and extracellular fluid: Resistor  R
Cell membrane: capacitor  C
Impedance Z =  (R2 + Xc2)
Phase angle = arctan (Xc/R)
Single and multi-frequency BIA
• Use prediction equations to estimate
compartments of interest (TBW, ECW, FM, FFM)
• Prediction equations:
– Are population specific
– Have been validated most often in healthy
populations
– Have been validated using different reference
populations (size, age, sexe, ethnicity)
– Have been validated against different criterion
methods (DEXA, densitometry, multicomponent models)
– Have been developed using different BIA
devices
Illustration: some FFM prediction
equations
(from Kyle et al, 2004)
All equations: have Impedance index (Ht2/Z)
and weight; often height, sex, age !!
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Single versus multi frequency analyzers
Single frequency
 Operates at 50 kHz
 No differentiation
between ECW and TBW
Multi frequency
 Operates at multiple
frequencies (5, 50, 100,
200, ... kHz
 Differentiation between
ECW and TBW
• Good agreement with criterion methods on group
level if .....
• May give substantial error at individual level
• Application in clinical populations (with disturbed
fluid balance) to assess TBW and ECW (and hence
FM and FFM) can be erroneous
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Bio-impedance spectroscopy (BIS)
Cole-Cole plot
R KHz
R0 KHz
R KHz represents TBF resistance
R0 KHz represents ECF resistance
• Estimates not based on
population derived
prediction equations
• Instead, body is scanned by
range of frequencies
• (~ 4 -1000 kHz), and then
biophysical modelling is used
to derive ECF and ICF
• Sensitive in detecting
changes in fluid balance
• Raw impedance data
(resistance and reactance)
independent of model
assumptions can be used
Bio-impedance spectroscopy (summary)
 Not dependent on prediction (regression) equations
 Makes use of so-called Hanai equations to calculate ECW
from R
0KHz
and TBW from R
∞KHz
 Better able to monitor shifts in water compartments
(ECW/ICW) than MF-BIA: potential advantages in
patients with altered fluid status
 Deviations from general assumptions in Hanai equations
may lead to less reliable results on individual level
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BIVA plots (biavector approach)
 Uses raw data
(resistance and
reactance) from
impedance analyzer at
50 kHz
 Not dependent on
regression equations
 Not dependent on
assumptions in Hanai
equations used in BIS
Patented approach: US20040167423 A1
Invented by Luana Pillon, Antonio Piccoli
 Direct comparison with
reference population
using tolerance ellipse
In software of Akern impedance analyzers
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BIVA and Cole-Cole plot
 Hemodialysis for 180
minutes causes the Cole
semi-circle to move to the
right and increases the
impedance vector
 Both show loss of
extracellular water but
BIVA also allows tracking
of fluid removal with
direct comparison of
impedance readings with
reference
From Piccoli et al, 2005
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Bio-impedance for measuring body
composition
Pro:
 Quick
 No adverse effects
 Not invasive
 Highly reproducible
 Not expensive
 Easy to perform
 Results directly available
Con:
 Requires proper
standardization
 Dependent on regression
equations (BIA) or model
assumptions (BIS)
 Lack of calibration between
instruments
 In general good accuracy of
body composition results at
group level
 Accuracy of body composition
at individual level may be
questionable
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Group level versus individual level
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Correlation between percentage body fat in
Selinger’s 4-component model (%BF4C)
and InBody 720 device (%BF720)
Example of a
typical output
from a validation
study
Ann L Gibson et al. Am J Clin Nutr 2008;87:332-338
Bland-Altman plot of %BF-4C and %BF720
in women
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Proposition: “Cut-off values for FFMI are compromised by
the uncertainty of BIA results at the individual level. This
pleads for the use of raw impedance data to track changes
in body composition and a reserve in using FFMI cut-off
values in individuals when data are collected by BIA.”
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What should dieticians consider when
choosing and using impedance devices?
Take home messages & considerations (1)
 Instrument choice
● Validated and published? Which criterion method
used? Acceptable for the purpose? (r, bias and SEE)
● Single Frequency (TBW) or Multi Frequency (TBW
and ECW)? So which type of information is required?
● Access to raw data (resistance, reactance, phase
angle)? Access to prediction formula used in device?
● Phase sensitive device? E.g. can it measure
membrane capacity?
● Instrument cost?
● Are results exchangeable with other devices?
Calibration between manufacturers is desired!!!
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What should dieticians consider when
choosing and using impedance devices?
Take home messages & considerations (2)
 Do you want to use body composition data on group level
(research) or individual level (diagnostic use)?
 Do you want to make body composition assessments in
apparently healthy subjects or diseased subjects?
 Do you want to compare results with reference
population cut-off points for FFM? Or track changes using
raw data only?
 Be cautious when interpreting body composition results
because of uncertainty at individual level!!
 Standardize your measurement!!
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Thank you for your
patience!
Disclosure statement: the
speaker declares to have no
conflict of interest