J Electr Bioimp, vol. 13, pp. 66-72, 2022
Received 18 May 2022 / published 7 Nov 2022
https://doi.org/10.2478/joeb-2022-0010
The Russian bioimpedance database: an update
Sergey G. Rudnev 1,2,4, Olga A. Starunova 2, Elena Z. Godina 3,2, Alla E. Ivanova 2, Alexander V. Zubko 2
and Vladimir I. Starodubov 2
1.
2.
3.
4.
Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia
Federal Research Institute for Health Organization and Informatics, Ministry of Health of the Russian Federation, Moscow, Russia
Anuchin Research Institute and Museum of Anthropology, Lomonosov Moscow State University, Moscow, Russia
E-mail any correspondence to:
[email protected]
for generating national reference data and the assessment
of population health [4-7]. In particular cases, manufacturers
report an ongoing global BIA data collection process through
the network and mobile technologies based on their
instruments with the implementation of a big data approach
using huge multi-million datasets of BIA records [8]. On the
other hand, there are examples of meta-analysis of massive
aggregated BIA data from different manufacturers [9].
In Russia, mass BIA data are generated by the national
network of health centers (HCs) which was established in
2009-2010 for the assessment of individual health and
promotion of healthy lifestyle. Currently, this network
involves nearly 800 HCs evenly distributed according to the
population density at the approximate rate of 1 HC per 200
thousand people (figure 1). Once a year, on a free voluntary
basis, every citizen of Russia has the opportunity to pass a
comprehensive examination at any HC with the use of
several assessment methods, including measurement of
height, weight, blood pressure, cholesterol, glucose, blood
oxygen saturation level, the assessment of ankle brachial
index, waist-to-hip ratio, eye examination, smoking test,
spirometry, wrist dynamometry, ECG dispersion mapping
and, optionally, BIA. As a result of the examination, each
patient is given current recommendations by a nutritionist
on maintaining a healthy lifestyle.
The 2010-2015 HCs’ BIA database was used previously
for the construction of the population reference data,
analysis of associated health risks and inter-population
comparisons [10] as well as to develop the data filtration
algorithms and related software [11]. The new data
collection was then organized in 2017 and 2019.
Abstract
Extensive bioelectrical impedance analysis (BIA) data have the
potential of health monitoring and the assessment of health risks
at the population level. The importance of BIA data lies in their
availability and abundance for many countries. In Russia, mass BIA
data are generated by the national network of health centers (HCs).
Our aim was to describe the structure and capabilities of the
updated HCs’ BIA database. Upon several requests between 2012
and 2020, 369 HCs representing all Federal districts of Russia and
60 out of 85 Federal subjects in them, submitted raw bioimpedance
data which were obtained using the same type of BIA instrument,
namely ABC-01 ‘Medas’ (SRC Medas, Russia). After application of
strict selection criteria, 2,429,977 BIA measurement records were
selected that formed the updated 2010-2019 HCs’ database.
Various slices of the BIA data are described according to spatiotemporal, demographic and other characteristics. Reference curves
of the bioimpedance phase angle according to age and sex are
presented. Limitations and prospects for further work are outlined.
We believe that, after appropriate sampling, the database can be
utilized to study biological, geographical, social and other
associations of the bioimpedance and body composition
parameters, for generating updated national references,
international comparisons and data standardization.
Keywords: Bioimpedance data; large database; phase angle
Introduction
Due to ease of use, noninvasiveness, portability, reliability
and relatively low cost, bioelectrical impedance analysis
(BIA) is now one of commonly used body composition
assessment methods with numerous applications in
medicine and biology [1-3]. At present, big databases of BIA
measurements are formed and utilized, among other things,
© 2022 Author(s). This is an open access article licensed under the Creative Commons Attribution License 4.0.
(http://creativecommons.org/licenses/by/4.0/).
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Rudnev et al.: The Russian bioimpedance database. J Electr Bioimp, 13, 66-72, 2022
The 2015-2017 data were obtained according to the Letter
no 7-5/1067 of 27 Nov 2017. The data for the previous years
were obtained according to the Letter of the Ministry of
Health of the Russian Federation no 14-1/10/2-3200 of 24
Oct 2012 as well as from the Federal Information Resource
of HCs as described in [10] and also according to the Letter
no 7-5/434 of 02 Jul 2015. Only BIA data from the ABC-01
‘Medas’ instrument (SRC Medas, Russia) were considered
which were submitted by 369 HCs. The data for 2009 and
2020 were rare and so neglected.
Our aim was to describe the structure and capabilities of
the updated HCs’ BIA database.
Materials and methods
Bioimpedance was measured in HCs during visits between
2009 and 2020. BIA data were collected from HCs in a
depersonalized form in several stages. The data for 20182019 were obtained according to the Letters of the Federal
Research Institute of Health Organization and Informatics no
7-5/1498 of 17 Nov 2019 and no 7-5/1020 of 31 Aug 2020.
Fig.1: The Russian health centers – geographical distribution.
Fig.2: Frequency distribution of the BIA records (n=2,429,977) by the Federal subjects of Russia.
The bioimpedance instrument АВС-01 ‘Medas’ (SRC
Medas, Russia), with the Russian abbreviation ‘ABC’ meaning
‘analyzer of water compartments’, represents a family of
phase-sensitive two-, six-, or multiple-frequency lead-type
BIA meters generating a low-intensity (800 A) electrical
current and utilizing mainly tetrapolar or, optionally,
octopolar electrode configuration. Of them, two-frequency
tetrapolar meters are used in HCs. Currently, these devices
have been discontinued, and ABC-02 ‘Medas’ instruments
are being manufactured instead. With these instruments,
body composition is evaluated using known published
equations, such as for fat-free mass (FFM) in children [12]
and total body water in adults [13].
For every patient attending HC either individually (in
case of adults) or with parents or as part of organized school
team (in case of children), the inclusion criterion for the BIA
was age 5 or older, and the general exclusion criteria were
pregnancy or the presence of a cardiac stent or pacemaker.
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Rudnev et al.: The Russian bioimpedance database. J Electr Bioimp, 13, 66-72, 2022
BIA measurements were carried out after a few minutes
of patient’s staying indoors, with minimal clothing, on the
right side of the body in the lying position with arms and legs
slightly abducted according to a conventional tetrapolar
scheme at the electrical current frequencies 5 and 50 kHz
with the use of disposable bioadhesive electrodes. For every
HC, information about the type of the electrodes and the
mode of BIA application – either selectively (e.g., in case of
overweight) or to the entire flow of patients, was collected.
F9049 (FIAB, Italy) and Schiller biotabs 2234 mm (Schiller,
Switzerland) ECG electrodes were utilized in HCs most often
accounting for about 90% of the measurements followed by
Top Trace Medtab (Ceracarta, Italy), Skintact RT-34
(Leonhard Lang GmbH, Austria), Eurotrode PFR2034 (Pirrone
srl, Italy) and other types of electrodes. Phase angle (PA) was
calculated at 50 kHz as PA=atan(Xc/R)180/π, where Xc is
the reactance, and R the resistance.
Standing height and weight were measured in HCs using
mainly the same type of electronic stadiometer and digital
scale manufactured by JSC Tulinovsky instrument making
plant ‘Tves’ (Tambov region, Russia) with an accuracy 0.5 cm
and 0.1 kg, respectively.
As such, the BIA instrument ABC-01 ‘Medas’ provides
stable measurements with a relative error value of about
0.1% for R and 1% for Xc. The quality control of BIA
measurements in HCs using the ABC-01 ‘Medas’ instrument
was provided through the initial instruction of the personnel
on working with the analyzer from the manufacturer as well
as due to organized annual training sessions of the HCs’ staff
in Moscow. In addition, to check the performance of the BIA
instrument itself, it was recommended in HCs to daily
measure the supplied equivalent electrical circuit before
starting measurements of patients making sure that the
differences between measured and proper values of the
resistance and the reactance, respectively, are minimal.
A joint study conducted in the fall of 2020 at Medical
Computer Systems company (Zelenograd, Russia) included 9
replicate BIA measurements of 20 participants (10 women
and 10 men, age 21-54 years, BMI range 18.5-32.0 kg/m2)
with the ABC-01 ‘Medas’ instrument using 8 different types
of disposable bioadhesive electrodes: Ambu White Sensor
0415M (Ambu, Denmark), Bianostic AT (Data Input GmbH,
Germany), Eurotrode PFR2034 (Pirrone srl, Italy), F9049
(FIAB, Italy), Schiller biotabs 22×34 mm (Schiller,
Switzerland), Skintact RT-34 (Leonhard Lang GmbH, Austria),
Top Trace MedTab (Ceracarta, Italy), and Vermed (Nissha
Medical Technologies, Japan). All of them, except for the
Bianostic AT electrodes specially developed for BIA, were
reported to be utilized in HCs. The electrodes were applied
in random order, with the first and the last patient’s
measurement using the same electrode type. The interelectrode technical error of measurements 𝑇𝐸𝑀 =
𝐾
2
𝐾
2
√ ∑𝑁
𝑖=1(∑𝑗=1 𝑀𝑖𝑗 − (∑𝑗=1 𝑀𝑖𝑗 ) /𝐾) /𝑁(𝐾 − 1), where Mij is
the result of j-th measurement for i-th participant, N – the
number of participants (N=20), and K – the number of
electrode types (K=8) [14], was 3.86 ohm R, 0.52 ohm Xc,
0.07 PA, 0.26 kg FFM, and 0.33% percentage body fat (data
not published). Interestingly, for the most frequently utilized
in HCs electrodes F9049 (FIAB, Italy) and Schiller biotabs
2234 mm (Schiller, Switzerland), we observed the minimal
inter-electrode differences in BIA parameters of 1.30 ohm R,
0.26 ohm Xc, 0.02 PA, and 0.04% percentage body fat.
In a limited joint study conducted in the spring of 2018
at the Anuchin Research Institute and Museum of
Anthropology of MSU (Moscow, Russia) with replicate
measurements of 5 participants (4 women and 1 man, age
25-45 years, BMI range 20.1-24.9 kg/m2) using 4 different
ABC-01 ‘Medas’ instruments and F9049 (FIAB, Italy)
electrodes, the inter-instrument TEM, which was calculated
using the above formula, where Mij is the result of
measurement of i-th participant by j-th instrument, N – the
number of participants (N=5), and K – the number of BIA
instruments (K=4), was 2.01 ohm R, 1.19 ohm Xc, 0.10 PA,
0.07 kg FFM, and 0.12% percentage body fat (data not
published).
The BIA data collected at various stages had common
measurement records. For the removal of duplicates, a
quasi-unique identifier was used for each record based on
the HC’s name, date of birth, date of measurement and
patient’s sex. In addition, all but the last repeated
measurement records during the same visit were excluded.
BIA records were also excluded if they did not contain
information on height, weight, electrical resistance and
reactance, date of birth, date or time of measurement, and
patient's sex. The obtained initial dataset of BIA
measurements for 2010-2019 contained 4,162,925 records.
Strict selection criteria were then applied in order to remove
outliers and fraud data according to the developed expert
quality assessment algorithm [11], and the database of
2,429,977 selected measurement records was formed.
Distribution of the selected BIA data across the Federal
subjects of Russia is shown in figure 2.
The structure of the total number of examined patients
was described relative to age, sex, time of examination and
year of birth. Age-related changes of the phase angle in
males and females were assessed. Statistical analysis was
performed using the Minitab 21 and MS Excel 2019 software
packages.
Informed consent
Informed consent to the collection, processing and use of
personal data has been obtained in HCs from all individuals
included in this study, or their legal representatives – for
children under 14 years of age.
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number of BIA records in the database per one HC was 3260,
with the interquartile range between 908 and 9050 records.
Ethical approval
The research related to human use has been complied with
all relevant national regulations, institutional policies and in
accordance with the tenets of the Helsinki Declaration. Due
to the use of routine diagnostic methods and the lack of
medical interventions, the permission of the ethics
committee was not required.
Results
For the observed time period, the monthly number of BIA
records in the database ranged basically from 10 to 30
thousand and showed a pronounced seasonality with the
local maxima in the spring and autumn seasons, and the local
minima in the winter and summer seasons, respectively
(figure 3, upper panel). The maximal rate of visits occurred
in the morning hours, from about 9 am to 12 am (figure 3,
lower panel). The maximal rate of visits on workdays was
observed, on average, on Wednesday with a decrease in the
intensity of visits towards the beginning and the end of the
week, while the range of differences in the frequency on
different working days of the week did not exceed 10-12%
(data not shown).
Fig.4: Frequency distribution
of the BIA records
(n=2,429,977) by the year of
birth of the measured
persons (upper panel) and of
the total number of HCs
according to the number of
BIA measurements (lower
panel).
Fig.5: Age structure of the measured persons: left – females
(n=1,607,906), right – males (n=822,071).
Fig.3: Frequency
distributions of the BIA
records (n=2,429,977) by
the month and year of
measurement (upper
panel) and the time of day
(lower panel).
School-age children were examined in HCs most often,
with the total number of boys slightly higher than that of girls
(figure 5). After the school age, the number of examinations
per year of age decreased sharply, and the rate of BIA
measurements was dominated by females. The peak rate of
the measurements among adults fell on a subgroup of
women aged 50-65 years.
The children born in 1997-2007 were examined in HCs
most frequently (Fig. 4, upper panel) followed by those
people who were born in 1949-1962. People who were born
in 1942-1945 were examined relatively rarely, which
represents the demographic echo of WW2. The distribution
of the total number of HCs according to the number of
measurements (Fig. 4, lower panel) reflects the fact that at
least some HCs carried out BIA measurements selectively,
and not to the entire flow of patients. In addition, HCs did
not always provide data in response to every request (or
could even be closed or reorganized), so the entire data set
of each individual HC was available quite rarely. The median
Fig.6: Histograms of the resistances R50: left – females
(n=1,607,906), right – males (n=822,071).
Histograms of the resistance values at frequency 50 kHz
are shown in figure 6. For the subgroup of males, the
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Rudnev et al.: The Russian bioimpedance database. J Electr Bioimp, 13, 66-72, 2022
distribution was markedly different from normal (figure 6,
right) due to a higher proportion of school-age children and,
hence, of the measurement records with the bigger R50
values. Meanwhile, the median value of the resistance for a
subgroup of females (590.4 ohm) was higher than that of
males (544.7 ohm).
this study (with a multiple written appeal to the governing
bodies of HCs), the obtained BIA data were necessarily
incomplete, and it took considerable amount of time to
collect and preprocess the data.
Serious contamination of the BIA data by the outliers
and fraud data was observed, which required the
development and application of the efficient algorithms and
software for their filtering [11]. In our view, falsification of
the BIA data can mask low attendance of a HC (i.e., below
the established plan) or lack of measurement electrodes.
Interestingly, the quality of BIA data generated by various
HCs obeyed the Pareto principle, so that the main body of
the fraud data was generated by a relatively small number of
HCs [11] which suggests the potential effectiveness of quality
control of the HCs function based on the assessment of raw
BIA data. Therefore, and also in view of the incompleteness
of the data collected manually, it is important to restore
automated collection of the HCs data at the federal level –
for instance, through the connection of HCs to the Uniform
State Health Information System (USHIS). It can be noted
that the problem of generating fraudulent data is common
to healthcare systems around the world and should not be
neglected when analyzing massive aggregated biomedical
data and making decisions [15].
The non-uniform attendance of HCs depending on age
and sex can be noted (figure 5) that does not match the
demographic structure of the Russian population, which is a
result of free access to HCs for all citizens without any official
regulations, especially in adults. For example, in figure 5, one
can see a predominance of middle-aged and elderly women
in the structure of HCs’ attendance compared to men of the
same age which may reflect a more attentive attitude of
women to their health. (Note that in Russia the average life
expectancy among women steadily exceeds that of men by
about 9-10 years [16].) The above discrepancy raises an
important question of whether the obtained BIA data are
representative. Our previous results suggest close similarity
of the HCs’ data in school-age children to the general
population data as exemplified by the analysis of the BIA
records of a sample of Moscow children directly assessed in
schools (n=1949): in this group, the mean standard deviation
score for BMI relative to the Moscow HCs’ reference data
described in [10] was as low as 0.06 and 0.09 in boys and
girls, respectively [17]. A similar study needs to be conducted
in adults.
One of the advantages of the HCs’ BIA database is the
use of the same type of BIA instrument – ABC-01 'Medas'.
Due to the lack of validated prediction formulae for the
Russian population, appropriate foreign body composition
formulae were utilized instead to generate relative body
composition scales and local references [12,13]. Upon the
development of the nationally representative formulae body
composition estimates and local references will be updated
using the obtained HCs’ BIA data.
Fig.7: HCs’ reference data on the phase angle at 50 kHz
according to age: the medians and interquartile range (blue
lines). Upper panel – females (n=1,607,906), lower panel –
males (n=822,071). The red lines show estimated mean values
according to meta-analysis of pooled data from 46 studies [9].
Figure 7 shows HCs’ data on age-related changes of the
phase angle values in males and females. In adults, these
values were generally higher, and in children were similar to
those obtained in a meta-analysis of pooled data from
different countries involving more than 250,000 subjects [9].
Discussion
The importance of BIA data lies in their availability and
abundance for many countries. In particular, such data may
allow us to obtain a holistic picture of the distributions of
bioimpedance parameters, body composition estimates and
associated health risks at the population level. This work
presents the structure of the updated database of BIA
measurements in Russian HCs.
Many HCs reported routine use of BIA as a part of
comprehensive examination of every patient (in the
presence of electrodes and serviceable instruments), while
others reported a selective approach. In view of termination
of the automated collection of HCs data at the federal level
in 2014 and essentially manual data collection from HCs in
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(Valhalla Scientific, USA) instruments involved in Fels
Longitudinal Study and NHANES III, respectively, utilizing the
same scheme of electrode placement (r2=0.99, [4]).
Combined use of the Medas and Diamant data could be
potentially important for studying the regional variability of
bioelectric and body composition parameters in the
population.
Application of different BIA instruments and types of
electrodes affects the result of BIA measurements [18,19].
Our data suggest an acceptable level of the reproducibility of
the BIA measurement data obtained in HCs using different
ECG electrodes and ABC-01 ‘Medas’ instruments which is
similar to the inter-individual TEM reported in [20] for the
Seca 515/514 instrument. Also, in the above-mentioned
study at Medical Computer Systems company (Zelenograd,
Russia) with the use of 8 types of electrodes, the mean
differences in the phase angle between the other electrode
types and the reference Bianostic AT (Data Input GmbH,
Germany) electrode were all positive, between +0.1–0.2,
while other authors reported the negative differences at the
level –0.1 for the 3M Red Dot 2330 and Ambu BlueSensor
2330 electrodes, and even –0.8 for the small skin contact
area Ambu BlueSensor SU-00-C electrode [19] which
emphasizes the importance of the proper choice of
electrodes. So, the results of comparison of the phase angle
data presented in figure 7 may be explained, at least in part,
by the differences in electrode types (as mostly the lead-type
instruments were included in the meta-analysis of pooled PA
data from 46 studies [9]). Even the greater disagreement can
be observed when using BIA instruments of different
manufacturers, especially those utilizing distinct
measurement approaches. The study at Medical Computer
Systems company (Zelenograd, Russia) also included a
comparison of the ABC-01 ‘Medas’ analyzer with the phasesensitive Tanita MC-780A instrument (Tanita Corp., Japan),
and the mean difference in PA values of +0.7 was obtained
(lower values were observed with the Tanita instrument).
Federal subjects of Russia were presented in the BIA
data relatively disproportionately (figure 2), whereas some
Federal subjects were not involved at all. This is partly due to
the use in HCs, along with the ABC-01 ‘Medas’ analyzer, of
other bioimpedance instruments, manufactured mainly by
the Diamant LLC company (Russia). These data, although also
collected, need special attention as the Diamant instruments
use untypical measurement frequencies (28 and 115 kHz)
and the original scheme of electrode placement on arms and
legs (along with the reusable electrodes of own production),
so that the measured impedance values for the Diamant
instrument are normally about half the values of those for
the Medas instrument. Our preliminary results suggest
comparability of the Medas and Diamant body composition
data in adults at the group level after cross-calibration of
measured impedances and application of the same
assessment algorithm. Meanwhile, the proportion of
explained variance using the conversion formula between
the Medas and Diamant impedances in paired measurements (r2=0.90, unpublished data) was similar to that of the
lead-type Medas vs standing-on Tanita BC-418MA (Tanita
Corp., Japan) instrument (r2=0.91, [21]) and lower than
previously reported in a classical work on the comparison of
the lead-type RJL 101 (RJL Systems, USA) and Valhalla 1990B
Conclusion
The structure of the updated Russian HCs’ BIA database is
presented. We believe that, after appropriate sampling, it
can be utilized to study biological, geographical, social and
other associations of the bioimpedance and body
composition parameters, for generating updated national
references, international comparisons and data standardization.
Acknowledgments
This work was supported by the Russian Science Foundation
(grant no 20-15-00386).
Conflict of interest
Authors state no conflict of interest.
References
1. Lukaski HC, Bolonchuk WW, Hall CB, Siders WA. Validation of
tetrapolar bioelectrical impedance method to assess human
body composition. J Appl Physiol. 1986;60(4):1327-32.
https://doi.org/10.1152/jappl.1986.60.4.1327
2. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M,
Gómez JM, et al. Bioelectrical impedance analysis - part II:
utilization in clinical practice. Clin Nutr. 2004;23(6):1430-53.
https://doi.org/10.1016/j.clnu.2004.09.012
3. Ward LC. Electrical bioimpedance: from the past to the future.
J Electr Bioimp. 2021;12:1-2.
https://doi.org/10.2478/joeb-2021-0001
4. Chumlea WC, Guo SS, Kuczmarski RJ, Flegal KM, Johnson CL,
Heymsfield SB, et al. Body composition estimates from
NHANES III bioelectrical impedance data. Int J Obes.
2002;26(12):1596-609. https://doi.org/10.1038/sj.ijo.0802167
5. Bosy-Westphal A, Danielzik S, Dörhöfer RP, Later W, Wiese S,
Müller MJ. Phase angle from bioelectrical impedance analysis:
population reference values by age, sex, and body mass index.
JPEN J Parenter Enteral Nutr. 2006;30(4):309-16.
https://doi.org/10.1177/0148607106030004309
6. Du H, Li L, Whitlock G, Bennett D, Guo Yu, Bian Zh, et al.
Patterns and socio-demographic correlates of domain-specific
physical activities and their associations with adiposity in the
China Kadoorie Biobank study. BMC Public Health.
2014;14:826. https://doi.org/10.1186/1471-2458-14-826
7. Franssen FME, Rutten EPA, Groenen MTJ, Vanfleteren LE,
Wouters EFM, Spruit MA. New reference values for body
composition by bioelectrical impedance analysis in the general
population: results from the UK Biobank. J Am Med Dir Assoc.
2014;15(6):448.e1-6.
https://doi.org/10.1016/j.jamda.2014.03.012
71
Rudnev et al.: The Russian bioimpedance database. J Electr Bioimp, 13, 66-72, 2022
8. InBody [Internet]. InBody 970 body composition analyser.
Available from: https://uk.inbody.com/products/inbody-970/
16. World Health Organization [Internet]. Life expectancy and
Healthy life expectancy: Data by country. Available from:
https://apps.who.int/gho/data/view.main.SDG2016LEXv?lang=
en
9. Mattiello R, Amaral MA, Mundstock E, Ziegelmann PK.
Reference values for the phase angle of the electrical
bioimpedance: Systematic review and meta-analysis involving
more than 250,000 subjects. Clin Nutr. 2020. 39(5):1411-7.
https://doi.org/10.1016/j.clnu.2019.07.004
17. Anisimova AV, Rudnev SG, Godina EZ, Nikolaev DV, Chernykh
SP. Body composition in Moscow children and adolescents:
evaluation of representativeness of the bioimpedance data in
health centers. Treatm Prophylaxis. 2014;1(9):24-9. (In
Russian)
10. Rudnev SG, Soboleva NP, Sterlikov SA, Nikolaev DV, Starunova
OA, Chernykh SP, et al. Bioimpedance study of body
composition in the Russian population. Moscow: Federal
Research Institute for Health Organization and Informatics;
2014. (In Russian)
18. Nescolarde L, Lukaski H, De Lorenzo A, de-Mateo-Silleras B,
Redondo-Del-Río MP, Camina-Martín MA. Different
displacement of bioimpedance vector due to Ag/AgCl
electrode effect. Eur J Clin Nutr. 2016;70(12):1401-7.
https://doi.org/10.1038/ejcn.2016.121
11. Starunova OA, Rudnev SG, Starodubov VI. HCViewer: software
and technology for quality control and processing raw mass
data of preventive screening. Russ J Numer Anal Math Model.
2017;32(5):315-26. https://doi.org/10.1515/rnam-2017-0030
19. Dupertuis YM, Pereira AG, Karsegard VL, Hemmer A, Biolley E,
Collet T-H, et al. Influence of the type of electrodes in the
assessment of body composition by bioelectrical impedance
analysis in the supine position. Clin Nutr. 2022;41(11):P245563. https://doi.org/10.1016/j.clnu.2022.09.008
12. Houtkooper LB, Going SB, Lohman TG, Roche AF, Van Loan M.
Bioelectrical impedance estimation of fat-free body mass in
children and youth: a cross-validation study. J Appl Physiol.
1992;72(1):366-73.
https://doi.org/10.1152/jappl.1992.72.1.366
20. Bosy-Westphal A, Schautz B, Later W, Kehayas JJ, Gallagher D,
Müller MJ. What makes a BIA equation unique? Validity of
eight-electrode multifrequency BIA to estimate body
composition in a healthy adult population. Eur J Clin Nutr.
2013;67:S14-21. https://doi.org/10.1038/ejcn.2012.160
13. Kushner RF, Schoeller DA. Estimation of total body water by
bioelectrical impedance analysis. Am J Clin Nutr.
1986;44(3):417-24. https://doi.org/10.1093/ajcn/44.3.417
21. Rudnev S, Burns JS, Korrick SA, Hauser R, Williams PL, Lee MM,
et al. Comparison of bioimpedance body composition in young
adults in the Russian Children's Study. Clin Nutr ESPEN.
2020;35:153-61. https://doi.org/10.1016/j.clnesp.2019.10.007
14. Ulijaszek SJ, Kerr DA. Anthropometric measurement error and
the assessment of nutritional status. Br J Nutr. 1999;82(3):16577. https://doi.org/10.1017/S0007114599001348
15. Mikkers M, Sauter W, Boertjens J, editors. Healthcare fraud,
corruption and waste in Europe: National and academic
perspectives. Odense: Eleven International Publishing; 2017.
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