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6559www.foodscience-nutrition.com
1 | INTRODUCTION
Iron deficiency (ID) and iron deficiency anemia (IDA) are a global
health problem affecting developing and developed countries.
Pregnant women were identified as a risk group due to adverse
outcome on pregnancy, maternal and fetal outcome (WHO and
CDC, 2008). Pregnant women with IDA are at a higher risk of post-
partum hemorrhage (PPH), receiving blood transfusion, and heart
failure (Clevenger et al., 2016; Grewal, 2010; Kavle et al., 2008). In
addition, ID and IDA during pregnancy can be considered as a risk
factor for preterm delivery, low birth weight, perinatal, and neo-
natal mortality (Finkelstein et al., 2020; Georgieff, 2020; Rahman
Received: 10 June 2021
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Revised: 2 Se ptember 2021
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Accepted: 3 Septembe r 2021
DOI: 10.1002 /fsn3. 2588
ORIGINAL RESEARCH
Prevalence of iron deficiency in pregnant women:
A prospective cross- sectional Austrian study
Harald Zeisler1 | Wolf Dietrich2 | Florian Heinzl1 | Philipp Klaritsch3 |
Victoria Humpel3 | Manfred Moertl4 | Christian Obruca2 | Friedrich Wimazal1 |
Angela Ramoni5 | Johanna Tiechl5 | Elisabeth Wentzel- Schwarz6
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2021 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.
1Department of Obstetrics and
Gynaecology, Medical University Vienna,
Vienna, Austria
2Depar tment of Obstetrics and
Gynaecology, Karl Landsteiner University of
Health S ciences, Univer sity Hospital Tulln,
Tulln, Austria
3Depar tment of Obstetrics and
Gynaecology, Medical University Graz, Graz,
Austria
4Depar tment of Gynecology and Obstetrics,
Perinatal Center, Klagenfurt am Wörthersee,
Klagenfurt, Austria
5Depar tment of Obstetrics and
Gynaecology, Medical University Innsbruck,
Innsbruck, Austria
6Depar tment of O bstetr ics, St . Josef
Krankenhaus, Vienna, Austria
Correspondence
Harald Zeisler, Department of Obstetrics
and Gynaecology, Medical University
Vienna, A- 1090 Vienna, Waehringer Guer,
Austria.
Email: harald.zeisler@meduniwien.ac.at
Funding information
The study was in part funded by Vifor
Pharma Austria
Abstract
The aim of the study was to determine, for the first time, in a prospective cross-
sectional multicenter study, the prevalence of iron deficiency (ID) in an Austrian
pregnant population. A cohort of 425 pregnant women was classified into four
groups of different weeks of gestation. Group 1 was monitored longitudinally, while
groups 2– 4, iron status, were sampled only once. Evaluation of the prevalence of
ID was performed by comparing the diagnostic criteria of the WHO to the cutoff
proposed by Achebe MM and Gafter- Gvili A (Achebe) and the Austrian Nutrition
Report (ANR). In comparison with the ANR, the prevalence of ID was lower in group
1 and higher in groups 2– 4 (17.2% vs. 12.17%, 25.84%, 35.29%, and 41.76%, respec-
tively) (p- values < .01 except group 1). According to WHO, the prevalence in group
1 was 12.17% at inclusion, 2 months later 31.7%, and further 2 months later 65.71%,
respectively. According to Achebe, the number of cases doubled; for group 1, the
number of cases rose from 13 to 42 (115 patients total); for groups 2– 4, we observed
an increase from 112 to 230 (340 patients total). This study reported a prevalence
of around 12% at the beginning of pregnancy, which increased during pregnancy up
to 65%. ID can have a massive impact on quality of life, justifying screening, as iron
deficiency would be easy to diagnose and treat.
KEYWORDS
Austria, iron deficiency, maternal morbidity, pregnancy, prevalence, quality of life
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et al., 2016; Rahmati et al., 2019; Rao & Georgieff, 2007; Srour
et al., 2018). Maternal iron deficiency, with or without associated
anemia, has an adverse effect on fetal iron status because decreased
maternal hemoglobin concentration is associated with decreased
fetal iron stores (Means, 2020). Children with iron deficiency ane-
mia show to have lower scores in cognitive, motor, social- emotional,
and neurophysiological development compared with group infants
(Lozoff & Georgieff, 2006). Iron plays an important role in the
growth and the development of the central nervous system and for
the normal functioning of the brain (Lozoff et al., 2006). It is import-
ant for the obstetrician to know that human brain and cognitive de-
velopment begin in the third trimester of pregnancy (Radlowski &
Johnson, 2013). In Austria, screening for anemia, but not for iron
deficiency, is part of the prenatal care (Mother- Child- Booklet). The
ongoing discussions on a possible screening for iron deficiency in
pregnancy always end with the reference to missing national data.
Still now, there are neither data on the prevalence of iron deficiency
nor on iron deficiency anemia in pregnancy in Austria. (Auerbach
et al., 2021) reported that 42% of pregnant women were observed
to be iron deficient in the first trimester. Stevens et al. reported a
global prevalence of anemia, 2011, of nearly 30% of reproductive-
age women and 38% of pregnant women, respectively. The median
prevalence in high- income regions was 22% (16– 29) for pregnant
women aged 15– 49 years (Stevens et al., 2013). Global anemia prev-
alence estimated by WHO with data from 1993 to 2005 revealed
an estimated prevalence of IDA in pregnancy of 15.5% for Austria
(WHO and CDC, 2008). In a recent study, 67% of Austrian pregnant
women received iron supplementation, irrespective of whether they
were deficient in iron with no information on the prevalence (Spar y-
Kainz et al., 2019). Since iron deficiency is easy to diagnose and treat,
the aim of this study was to evaluate the prevalence of iron defi-
ciency in Austria for the first time. The results should be compared
with the different diagnostic criteria for ID of the WHO (WHO and
CDC, 2008) and cutoff proposed by Achebe MM and Gafter- Gvili
A (Achebe) (Achebe & Gafter- Gvili, 2017) as well as to the Austrian
Nutrition Report (ANR) 2012 (Elmadfa. 2012) that states that 17.2%
of all nonpregnant women are affected by ID. The results should
serve as the basis for the planned revised guideline of the Austrian
Society for Obstetrics and Gynaecologists.
2 | METHODS
2.1 | Study participants and design
We conducted a cross- sectional study in six Austrian hospitals be-
tween March 2017 and June 2020. The study participants were
(singleton) pregnant women who were in obstetrical care at the
Department of Obstetrics and Gynaecology, Medical University
Vienna, Depar tment of Obstetrics, St. Josef Krankenhaus, Vienna,
Department of Gynaecology and Obstetrics, Perinatal Center
Klagenfurt, Klagenfurt am Wörthersee, Department of Obstetrics
and Gynaecology, Karl Landsteiner University of Health Sciences,
University Hospital Tulln, Tulln an der Donau, Department of
Obstetrics and Gynaecology, Medical University Innsbruck,
Innsbruck, Department of Obstetrics and Gynaecology, Medical
University Graz, Graz. The study participants were divided into four
groups, depending on gestational age at inclusion: group 1: weeks
11 + 0 to 14 + 6, group 2: weeks 24 + 0 to 32 + 6, group 3: weeks
33 + 0 to 37 + 6, and group 4: weeks 38 + 0 to 41 + 6. Women in
group 1 were monitored longitudinally to check for a change in iron
status . In case of normal iron status , they were invited for a fol low- up
visit 2 months after their first one, and then again, two months later
for a third visit. For groups 2– 4, iron status was sampled only once
(at inclusion). In case of ID (A), iron supplementation was adminis-
tered according to the algorithm suggested by Achebe and no fur-
ther appointment was scheduled for patients from group 1. Medical
history, pregnancy data, and laboratory parameters were taken from
the medical record and collected in a web- based database (eCRFs)
by the company SCICOMED e.U. (www.scico med.net) for all groups.
For groups 2– 4, we also collected diagnostic data (day of deliver y,
maternal and neonatal outcome) for possible further analysis. For
early pseudonymization, each study participant received a unique
identification number. Only the principal investigator of each partici-
pating center and their coworkers can link the identification number
to the study participants.
2.2 | Inclusion criteria
Signed informed consent, maternal age ≥18 and <46, singleton preg-
nancy, and weeks of gestation in accordance with the group defini-
tions above.
2.3 | Exclusion criteria
Ongoing iron supplementation at inclusion (except nutrient supple-
ments), history of hemoglobinopathies or sickle cell anemia, gastro-
intestinal pre- existing diseases (e.g., Crohn's Disease and Ulcerative
Colitis), bariatric surgery, suspected bacterial and parasitic diseases
(malaria, worm diseases, and Helicobacter pylori infection), and
bleeding in case of placental disorders (placenta praevia, placenta
accreta, increta, or percreta).
2.4 | Parameters and definition of ID
The following parameters have been evaluated using the reference
values of the Clinical Institute for Laboratory Medicine, General
Hospital Vienna— Medical University Campus: hemoglobin 12.0–
16.0 g/dl, ferritin 15– 150 μg/l.
The prevalence of ID was examined with respect to three differ-
ent definitions namely ANR, WHO, and Achebe. In ANR , the unusual
cutoff of below 10 μg/l was used. With respect to WHO standards,
ID is given by a ferritin level below 15 μg/l. Achebe and other studies
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ZEISLER Et a L.
warrant a serum ferritin level of <30 μg/l in pregnancy for the di-
agnosis of ID (Achebe & Gafter- Gvili, 2017; DGHO, Leitlinie, 2018;
Pavord et al., 2019; Bouri & Martin, 2018).
2.5 | Statistics
Data are reported via median (numerical variables), respec-
tively via absolute frequencies (categorical variables). Statistical
tests were done with the R sof tware package (version 4.0.3) (R
Core Team, 2020). Data were plotted with the ggplot2 package
(Wickham, 2016).
We employed a chi- square- goodnes of fit test to assess whether
or not the results published in the Austrian Nutrition Report (ANR)
2012 (17.2% of all women show ID) hold true for pregnant women as
well. Confidence intervals (95%) for the true value were computed
via a two- sample test for equality of proportions. The difference in
parameters between groups was examined via Kruskal– Wallis tests,
which were followed up by pair- wise Wilcoxon rank- sum tests in
case of statistical significance. In order to investigate the correlation
between gestational age (in weeks) and serum ferritin, we calculated
Kendall's tau. Results with a p- value less than .05 were considered
statistically significant.
3 | RESULTS
A total of 483 patients have been recruited across all sites; data
from 425 women were used for analysis. Incomplete records were
excluded. Patients have been divided into four groups as shown in
Table 1. Table 2 represents selected data with respect to age, body
mass index (BMI), and serum ferritin. We used the Kruskal– Wallis
test to identify differences between the four groups. The results
for age were not statistically significant; for BMI and serum fer-
ritin, however, we computed p- values < .01. Subsequent analysis
via pair- wise Wilcoxon rank- sum tests revealed that patients from
group 1 have lower prepregnancy BMI than the ones from the other
groups (p- values < .01; the other comparisons yielded no significant
p- values). For serum ferritin levels, we found a significant differ-
ence between group 1 and all the other groups as well as between
group 2 and group 4 (p- values < .01). It is worth pointing out that
all these results would have also been statistically significant when
using Bonferroni correction. In group 2 vs. group 3, we computed
a p- value of .4649; the comparison of groups 3 and 4 yielded the
result of p = .12499. Figure 1 shows the ferritin levels along with the
medians for the respective groups, as well as the two different levels
for the definition of ID (Achebe, WHO). Since values below 15 µg/l
are not reported exactly, we were not able to show the interquartile
range (IQR).
Twelve percent presented with ID during their first visit are
lower than the ANR prediction (17.2%), and group 2 shows a rise of
cases (about 1 in 4 patients tested positive for ID). In group 3, more
than 1 in 3 patients were found to be affected by ID, and in group 4,
we observed a prevalence of more than 40%. Overall, almost 30%
of all patients were diagnosed with ID. Using the 95% confidence
intervals, we expect at least 1 in 4 patients to develop ID over the
course of the pregnancy and up to 50% among all patients with near-
term deliveries. With the exception for group 1, all these findings
were statistically significant with p- values < 0.01 (Figure 2, Table 3).
Figure 2 shows the observed prevalence (bold lines) and the 95%
CI (top and bottom of the box) for the respective groups; for com-
parison purpose, we included a line representing the ANR predic-
tion. This tendency (the higher the gestational age the more likely
ID develops) is also present in group 1. Using the WHO definition
of ID, the prevalence for ID was 12% (gestational age of 11 + 0 to
14 + 6); at the second visit (2 months later), we again observe 12%
of such cases (6 out of 49). However, considering that 14 patients
were excluded from the second visit because they already were di-
agnosed with ID, there are now actually at least 20 out of 63 (31.7%)
patients suffering from ID. Furthermore, an additional 30 had to be
excluded from the second visit because iron supplement therapy
was administered as well, due to their serum ferritin level being be-
tween 15 (including) and 30 (excluding). At the third visit , 3 out 15
(20%) presented with ID. Furthermore, 18 had to be excluded from
this visit, again because of a serum ferritin level <30 μg/l. Overall
with respect to the longitudinal arm, 23 out of 115 (20%) developed
ID over the course of the pregnancy. Additionally, 58 presented with
serum ferritin levels between 15 and 30 at either the first or second
visit (50.44%) and 22 dropped out willfully (Table 4). We assume that
a significant number of these patients would have also developed
ID. This assumption is backed up by our above calculations for dif-
ferences in the groups via Kruskal– Wallis, respectively, the pair- wise
Wilcoxon comparisons and the observation that median serum ferri-
tin levels decline through the course of the pregnancy: 38.7 μg/l for
group 1, 23.2 μg/l for group 2, 18.1 μg/l for group 3, and 16.5 μg/l
for group 4 (median overall: 22.7 μg/l) (Table 2). However, since this
point of view is a bit coarse, we also used Kendall's rank correlation
(using all available data) to examine the relationship between the
serum ferritin level and gestational age (in weeks). In order to tighten
the conclusion, we added the Kendall's rank correlation.
According to Achebe definition instead of WHO definition of
ID (<30 μg/l serum ferritin vs. <15 μg/l serum ferritin), we are con-
fronted with more than double the number of cases (for group 1,
the number of cases rose from 13 to 42 (out of 115 patients); for
groups 2 to 4, we observed an increase from 112 to 230 (out of 340
patients) cases. As a result about 1 in 3 patients presents with low
serum ferritin levels already at the beginning of the pregnancy, and
TABLE 1 Patients (counts) were divided into four groups,
depending on gestational age at inclusion
Group Week s Patients
111 + 0 to 14 + 6 115
224 + 0 to 32 + 6 89
3 33 + 0 to 37 + 6 51
438 + 0 to 41 + 6 170
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by the end of it, we observe a deficiency in 2/3 of all women (for 271
out of the 310 patients from groups 2– 4, blood sampling was done
within one week before delivery) (Figure 3).
4 | DISCUSSION
To date, there are no data available on the prevalence of ID in preg-
nant women in Austria. The ANR is the only source for data about
prevalence of ID in Austrian women in the reproductive age. Even
when considering the divergent definitions of ID, the observed
prevalence for patients of a gestational age of 24 + 0 or later de-
viate from ANR’s predictions substantially. In the longitudinal arm
of the study, it could be shown that the prevalence increases sig-
nificantly with the weeks of pregnancy. In group 4, we even found
41.76% of the patients to be suffering from ID. When using Achebe
definition instead of WHO definition of ID, we are confronted with
more than twice as many cases in total. The study participants were
recruited by random selection. Self- selection of study participants
also takes place when health, language, and/or cultural barriers
make participation difficult. The participating centers have a dif-
ferent number of births by year and are distributed throughout
Austria, so that a representative cross- section is achieved. This is
further supported by the inclusion of patients in different weeks of
gestation. We are aware that the selection of the pregnancy weeks
for the group classification shows minimal deviations from the usual
clinical relevance. However, this was necessary in order to achieve
the optimal group size and does not affect the core statements of
this study.
We have been looking at different cutoff points for diagnos-
ing ID: <15 μg/l (according to WHO) and <30 μg/l (according
to Achebe). However, ANR used yet another definition, namely
serum ferritin below 10 µg/l. Since most of laboratories used by
sites participating in this study report values below 15 μg/l simply
All Group 1 Group 2 Group 3 Group 4
Age 31 31 32 30 31
BMI 23.3 22.4 24.35 24.4 23.4
Serum ferritin (μg/l) 22.7 38 .7 23.2 18.1 16.5
TABLE 2 Medians for age, BMI, serum
ferritin with respect to the different
groups
FIGURE 1 Scatter plot (gest ational age in weeks at sampling/ferritin levels) detailing the distribution of ferritin levels in each group.
Each dot corresponds to one observed value in the respective week and its size scales with the number of samples with the respective
value. As such, the size reflects relative frequencies of the sampled values per week on a group level. For easy comparison, the median
of the respective group (black dashed line) was included, as well as the two different cutoff points for the definition of ID (red = ÖGGG,
blue = WHO). For better readability, different scales were used for each group
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as “< 15” (or in a similar fashion), we have not been able to di-
rectly compare our results to the one from ANR. As such, we di-
agnosed ID slightly more often than ANR would have. We also
have to point out that in order to use the serum ferritin variable
for statistical testing, we needed to choose a dummy value for
“<15” (all these values were set to 1). To make sure this choice
did not interfere with the results, we did another round of testing
where the dummy values were acquired from a randomly gener-
ated sequence (uniform distribution with values between 1 and
14); while the p- values changed slightly, we observed no change
in (non)significance.
When checking for the correctness of an estimated prevalence of
17.2% for ID in Austria, we compute d a precision ~0. 035 for tot al gro up
screening (n = 425); for groups 1 – 4 with samples sizes of 115, 89, 51
respectively 117, the precision drops to ~0.07, 0.08, 0.10, and 0.07 re-
spectively (in each case at significance level 5% and 95% confidence in-
terval) (Daniel, 1999). As such, we are confident in the findings for the
group of all patients, as well as the results for groups 1 and 4, but we
see the limitations of our calculations for the other groups, especially
group 3. It should be noted that the time frame for inclusion for this
subgroup was pre- emptively extended to guarantee a group as large as
possib le (cl ini cally spea king, one wou ld assum e inc lus ion for group 3 to
start with 34 + 0 ins tead of 33 + 0). The pregnant woman was required
to give birth within one week after taking the blood sample. It was orig-
inally intended to evaluate a possible association between ID and pre-
mature bir th. Furthermore, we would have liked to include a discussion
about IDA as well; however, since the prevalence for IDA is lower than
the one for ID, we would have needed an even larger sample size. For
the sake of completeness, 42 out of 425 patients represented with IDA
according to WHO and an ad ditional two when e mploying according to
Achebe. When comparing our findings (9.88% of all patients presented
with IDA) according to WHO (15.5% cases) via a chi- square- goodnes of
fit test, we observe a statistically significant difference (p- value < .01).
Lastly, while statistical comparisons of the clinical parameters of the
three subgroups (ID according to WHO, ID according to Achebe and
patients with serum ferritin ≥30 μg/l) would have been of great interest
to us, and the individual subgroup sizes have been deemed too low to
allow for appropriate statistical testing. It is important to point out that
ferritin is an acute phase reactant. When interpreting the ferritin val-
ues, however, it must always be taken into account that ferritin can be
speciously normal or above normal. The determination of C- reactive
protein (CRP) and saturation of transferrin (TSAT) can support the cor-
rect interpretation.
FIGURE 2 Boxplots (groups/observed
prevalence) showing the rise of ID
prevalence throughout the pregnancy
with respect to the WHO’s definition
of ID. The bold lines in the middle of
the boxes show the observed values,
while the bottom and top of the boxes
represent the 95% CI. For comparison
sake, we included a box based on the
data of the entire cohort, as well as a line
representing the ANR’s prediction
TABLE 3 Obser ved prevalences for the four groups compared
with the Austrian Nutrition Report's prediction via goodness of fit
test and Confidence intervals
Groups
% iron
deficiency p- Valuea
Confidence
interval 95%b
Group 1 12.17 . 3243 5.3 – 19.1
Group 2 25.84 .007016 15.8 – 35.8
Group 3 35.29 9. 385 e− 0 5 20.9 – 49.6
Group 4 41.76 <2. 2 e −16 33.6 – 49.9
All 29. 65 1. 0 4 9e −11 24.5 – 34.7
aChi- square goodness of fit test.
bTwo- sample test for equality of proportions with continuity correction.
TABLE 4 Longitudinal data concerning iron status for patients
from group 1 (absolute frequencies)
Iron status (Serum
ferritin μg/l)
Visit
1 (115
Patients)
Visit
2 (49
Patients)
Visit
3 (15
Pats) To tal
Iron deficiency
<15 14 6323
1 5 – 3 0 30 18 10 58
<30 44 24 13 81
Normal iron status
>15 101 43 12 -
>30 71 25 2 -
Drop out/LoFU - 24 10 34
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5 | CONCLUSION
The pregnancy care program “Mother- Child- Booklet” in Austria pro-
vides for two blood tests, namely up to 16 + 0 weeks of gestation and
between 25 and 28 weeks of gestation. Colleagues who are convinced
of possible adverse outcomes support the additional screening for ID.
Due to the design of the study, it was not possible to show an associa-
tion bet ween ID and adverse outcomes. However, it is clear that ID can
have a massive impact on quality of life. This alone justifies screening,
as diagnosis and therapy are very simple. The aim should also be to
avoid IDA at birth, in order to prevent higher maternal morbidity.
ACKNOWLEDGEMENT
A great thanks to the Study Nurse Rosey Punnackal Kilukken, who
did an excellent job for this study.
CONFLICT OF INTEREST
HZ received lecture fees and a grant from Vifor Pharma Austria. FH,
MM, JT, WD, CO, PK, VH, AR, EW, FW have nothing to declare.
AUTHOR CONTRIBUTIONS
Harald Zeisler: Conceptualization (lead); Data curation (lead); Formal
analysis (equal); Funding acquisition (lead); Investigation (lead);
Methodology (lead); Project administration (lead); Writing- original
draft (lead); Writing- review & editing (lead). Wolf Dietrich: Data cu-
ration (supporting); Writing- review & editing (supporting). Florian
Heinzl: Conceptualization (equal); Data curation (supporting);
Formal analysis (lead); Methodology (equal); Writing- original draft
(equal); Writing- review & editing (equal). Philipp Klaritsch: Data cu-
ration (supporting); Writing- review & editing (supporting). Victoria
Humpel: Data curation (suppor ting); Writing- review & editing (sup-
porting). Manfred Mörtl: Data curation (supporting); Writing- review
& editing (supporting). Christian Obruca: Data curation (support-
ing); Writing- review & editing (supporting). Friedrich Wimazal:
Conceptualization (supporting); Writing- review & editing (support-
ing). Angela Ramoni: Data curation (supporting); Writing- review &
editing (supporting). Johanna Tiechl: Data curation (supporting);
Writing- review & editing (supporting). Elisabeth Wenzel- Schwarz:
Data curation (supporting); Writing- review & editing (supporting).
ETHICAL APPROVAL
The ethics committee of the Medical University of Vienna approved
this study (EK 2010/2016).
INFORMED CONSENT
Written Informed consent was obtained from all study participants.
FIGURE 3 Scatter plot (gest ational age in weeks at sampling/ferritin levels) detailing the distribution of ferritin levels at each visit. Each
dot corresponds to one observed value in the respective week and its size scales with the number of samples with the respective value. As
such, the size reflects relative frequencies of the sampled values per week on a visit level. For easy comparison, the median of the respective
visit (black dashed line) was included, as well as the two different cutoff points for the definition of ID (red = ÖGGG, blue = WHO). For
better readability, different scales were used for each visit
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ZEISLER Et a L.
DATA AVAIL ABI LIT Y S TATEM ENT
Data available on request from the authors.
ORCID
Harald Zeisler https://orcid.org/0000-0003-4995-4561
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