Subclinical inflammation influences the association between vitamin A- and iron status among schoolchildren in Ghana
Subclinical inflammation influences the association between vitamin A- and iron status among schoolchildren in Ghana
Abdul-Razak Abizari 0 1
Fusta Azupogo 1
Inge D. Brouwer 1
0 Department of Community Nutrition, School of Allied Health Sciences, University for Development Studies , Tamale , Ghana , 2 Department of Family and Consumer Science, Faculty of Agriculture, University for Development Studies , Tamale , Ghana , 3 Division of Human Nutrition, Wageningen University , Wageningen , The Netherlands
1 Editor: Frank Wieringa, Institut de recherche pour le developpement , FRANCE
Background and objective In resource-poor settings, micronutrient deficiencies such as vitamin A deficiency may coexist with iron-deficiency. In this study we assessed the iron and vitamin A status of schoolchildren and the association between vitamin A and iron status.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: Funding for this research was received
from Nestle Foundation for Nutrition Research with
grant number FN4042. The grant was received by
Abdul-Razak Abizari. The funders had no role in
study design, data collection and analysis, decision
to publish, or preparation of the manuscript.
Competing Interests: The authors have declared
that no competing interests exist.
A cross-sectional design using the baseline data of a dietary intervention trial conducted
among randomly selected 5±12 years old schoolchildren (n = 224) from 2 rural schools in
northern Ghana. Hemoglobin (Hb), serum ferritin (SF) and serum transferrin receptor (sTfR)
concentrations were used as measures of iron status. Retinol binding protein (RBP) was
used as a measure of vitamin A status. Subclinical inflammation (SCI) was measured using
C-reactive protein (CRP) and α1-acid glycoprotein (AGP) concentrations. We examined the
cross-sectional association between vitamin A and iron status biomarkers with multiple
The proportions of schoolchildren with anemia (WHO criteria), iron-deficiency (ID, SF <15μg/l
and/or sTfR >8.5mg/l) and iron-deficiency anemia (IDA, concurrent anemia and ID) were
63.8%, 68.3% and 46.4% respectively. Low or marginal vitamin A status (0.70 μmol/l RBP <
1.05μmol/l) was present in 48.2% while 37.5% of the schoolchildren had vitamin A deficiency
(VAD, RBP <0.70 μmol/l). The prevalence of SCI as well as concurrent VAD and ID were
48.7% and 25% respectively. RBP was associated with Hb (β = 7.2, P = 0.05) but not SF (β =
20.7, P = 0.33) and sTfR concentration (β = 12.0, P = 0.63). In the presence of SCI, RBP was
not associated with hemoglobin status but a significant positive association was observed
among children without SCI.
The study shows that RBP is significantly associated with Hb concentration but not with SF and sTfR. The observed relationship between RBP and Hb is only significant in the absence of SCI.
Multiple micronutrient deficiencies are common in resource poor settings [1±3]. These
micronutrient deficiencies are a result of inadequate consumption of nutrient-rich foods, presence
of diseases and inefficient utilization of available micronutrients[
]. One of the important
vulnerable groups, but often neglected by public health interventions, is school-aged children.
Recent studies have emphasized the importance of micronutrient deficiencies among
schoolaged children as they are particularly vulnerable [
]. Iron deficiency (ID) co-exists with
vitamin A deficiency (VAD) [6±8]. Concurrent deficiencies of vitamin A and iron have been
found among school-aged children in Africa [
ID is considered one of the ten leading global risk factors with regards to attributable
] and is believed to be an underlying cause of anemia worldwide [11±13]. ID is also
known to impair cognitive development of children [14±16]. The long term effect of ID is
poor productivity [
]. On the other hand, VAD is known to compromise the immune
system  and is the leading cause of night blindness and a major nutritional determinant
of severe infection and mortality among children in the developing world [
]. In fact,
both ID and VAD increase the risk of morbidity and mortality among young children [22±
24]. The work of Marasinghe et al  also demonstrated that iron status is also associated
with weight-age z-score and vitamin A status is associated with severe stunting. It is
hypothesized that VAD causes anemia through 3 mechanisms: modulation of erythropoiesis,
reduction of the body's immunity to infectious diseases thus leading to anemia of infection
and modulation of iron metabolism [
]. Both observational studies [26±28] and
randomized controlled trials [29±31] have reported an association between vitamin A status
and iron status. VAD may increase the risk of iron deficient-erythropoiesis and anemia as a
result of altering the absorption, storage, release or transport of iron to the marrow .
Consequently, interventions that control VAD have been shown to improve iron status and
control anemia induced by either ID or infection [
]; this has been attributed to the
increased absorption and mobilization of hepatic iron stores in the presence of adequate
vitamin A .
Although ID and VAD are a significant cause of undernutrition, there is a paucity of data
on the prevalence of VAD, ID and the association between vitamin A status and iron status
among school-aged children in Ghana. Studies on vitamin A and iron status involving
different populations are necessary to further elucidate the interaction between vitamin A and iron
status. The aim of the present study was to investigate the association between vitamin A status
and iron status among rural Ghanaian school-aged children.
Materials and methods
A cross-sectional design using the baseline data of a dietary intervention trial in northern
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The study was carried out in Tolon district; one of the 26 districts in the Northern Region of
Ghana. The district has a single rainy season beginning in April and ending by October. The
vegetation is guinea savannah with a dry season which starts in November and ends in March
with maximum temperatures occurring towards the end of the dry season [
]. About 90% of
the district is rural and subsistence agriculture is the main occupation of the people. The main
staples cultivated include maize, yam and rice. Other crops commonly cultivated and
consumed are groundnuts and cowpeas [
]. The main food sources of vitamin A and iron in the
district are green leafy vegetables such as amaranth (Amaranthus spp.), okra leaves and fruit
(Abelmoschus esculentus), jute mallow (Corchorus olitorius), and kenaf/roselle (Hibiscus
sabdariffa). Although seasonal, mangoes are also a good dietary source of vitamin A and iron in the
The study population consisted of 5±12 years old schoolchildren (n = 241) who were randomly
selected from 2 primary schools in 2 rural communities in the Tolon district of Ghana. Data
was collected in October 2010 on apparently healthy children; details of the selection
procedure has previously been published elsewhere [
]. For this analysis, only schoolchildren with
complete data on vitamin A and iron status biomarkers, inflammation biomarkers (C-reactive
protein and α1-glycoprotein), malaria antigen, anthropometric measurements, dietary
diversity and socio-demographic characteristics were included (n = 224).
The dietary intervention trial within which this baseline data was collected was approved by
the Medical Research Ethics Committee of Wageningen University, The Netherlands and the
Institutional Review Board of Noguchi Memorial Institute for Medical Research, University of
Ghana. Permission was also obtained from the district administration, chiefs, opinion leaders
of the respective communities and thumb-printed informed consent was obtained from each
parent or caregiver
Serum ferritin (SF), soluble transferrin receptors (sTfR), C-reactive protein (CRP), α1-acid
glycoprotein (AGP) and retinol binding protein (RBP) were simultaneously measured using
an in-house sandwich ELISA technique [
]. Hemoglobin (Hb) was analyzed with a Pentra
60C+ automated analyzer on the same day blood was drawn. Details of the measurements have
been previously reported [
]. Anemia was defined using the WHO criteria [
] i.e. Hb <115
g/l for children 5±11 years (n = 213) and 120 g/l for children aged 12 years (n = 11). Using the
WHO criteria [
], we further defined ID as SF concentration <15μg/l and/or sTfR
concentration >8.5 mg/l (Ramco equivalents) [
]. Subclinical inflammation (SCI) was defined as
CRP >5 mg/l and/or AGP >1.0 g/l . IDA was defined as concurrent anemia and ID. We
also defined VAD as RBP <0.7μmol/l and low or marginal vitamin A status as RBP 0.7 but
]. Concurrent VAD and ID was defined as RBP <0.7μmol/l with ID (SF
<15μg/l and/or sTfR>8.5 mg/). The prevalence of ID and VAD were re-calculated after
adjustment for inflammation using the correction factors of Thurnham et al [
The malaria rapid diagnostic cassettes (First Response; Premier Medical) were used to screen
for current or recent malaria. The cassette had a sensitivity of 95% and a specificity of 99.5%
(First Response; Premier Medical). Children who were positive to the malaria antigen were
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subsequently treated following recommended guidelines; details of the screening and
treatment can be found in our previous work [
Weight and height of the children were measured according to standard procedures [
Height was measured to the nearest 0.1cm with a microtoise (Bodymeter 208; Seca) whilst
weight was measured to the nearest 0.1kg with an electronic scale (UNIscale; Seca). The
average of duplicate measurements was used to compute z-scores [height-for-age z-score (HAZ),
BMI-for-age z-score (BAZ) and weight-for-age (WAZ)] for each child using WHO anthro
plus 3.2.2. A verifiable record (birth certificate, health record, community birth register) was
used to estimate each child's age.
Dietary diversity score
A qualitative 24-hour recall (24hR) was used to assess the dietary intake of the schoolchildren.
Mothers and caregivers were first asked to mention all foods including drinks and snacks that
were consumed the previous 24 hours (from wake-up to wake-up) preceding the survey by the
index child from home and outside of home. She was next probed for likely forgotten foods
and then asked to give a detailed description of foods and beverages consumed, including
ingredients for mixed dishes. To ensure intake outside home was captured, children were
asked to assist their mothers/caregivers in the recall. The 24hR was used to complete the Food
and Agriculture Organization's dietary diversity questionnaire consisting of 13 food groups
]. In brief, a score of 1 was assigned if a child consumed a food item belonging to a
particular food group, else 0. Individual food group scores were aggregated into a dietary diversity
score (DDS) for each child. DDS refers to the different number of food groups consumed over
a reference period. Any food consumed on multiple occasions from the 24hR was counted
only once resulting in a maximum attainable score of 13. The scoring did not consider a
minimum intake (in grams) for the food groups.
Demographic and socio-economic related covariates were assessed with a pre-tested
semistructured questionnaire and included child's compound size, educational status of household
head and mother as well as occupation of household head and mother.
Population characteristics were presented as means (standard deviations) for normally
distributed data, median (interquartile range) for skewed data and frequency (percentages) for
categorical variables. We analyzed the cross-sectional association between vitamin A status (RBP)
and iron status (Hb, SF and sTfR) with hierarchical multiple linear regressions using the
General Linear Procedure in SAS. The assumption of normality was assessed with visual inspection
(histograms, boxplots and Q-Q plots) and test for normality with the Kolmogorov-Smirnov
test. Normality violations were corrected by a natural log transformation of the dependent
variables (SF and sTfR) before analysis and the β regression coefficients multiplied by 100 to
determine the effect size in percentages. Potential confounders were selected a priori based on
literature and included sex [
], age [
], SCI [
], malaria [
], nutritional status
of child [
], dietary diversity [
], total family size [
], educational status of household head
and mother [
] as well as occupation of household head and mother [
]. However, only
covariates which had at least a 10% effect on the crude estimate were retained in the complete
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multivariate models. CRP and AGP were significantly correlated (r = 0.61, P < .0001;
Rho = 0.68, P < .0001); although dropping one of the correlated variables is the simplest
method, O'Brien  recommends using a combined measure of correlated variables as an
alternative. We therefore included in our regression models the combined measure of CRP
and AGP, SCI (elevated CRP and/or AGP). The Pearson and Spearman correlation coefficients
showed no multicollinearity between the other covariates in the regression models. Four
multivariable models besides the crude model were formulated. In a hierarchical order, model 1
was adjusted for SCI (dichotomous) and malaria (positive or negative); model 2 was adjusted
for demographic factors: age (continuous) and sex (male or female); model 3 was further
adjusted for nutritional status (BAZ as a continuous variable) and dietary diversity (DDS as a
continuous variable) and model 4 was finally adjusted for socio-economic factors: family size
(continuous) and educational status of mother (literate or non-literate). Interaction terms for
age, sex and SCI with other covariates (e.g. age RBP, sex RBP and SCI RBP) were included in
the models but none was significant. Mathematically, the models were expressed as shown
Crude model: y = β0 + β1 × RBP
Model 1: y = β0 + β1 × RBP + β2 × SCI + β3 × malaria
Model 2: y = β0 + β1 × RBP + β2 × SCI + β3 × malaria + β4 × age + β5 × Sex
Model 3: y = β0 + β1 × RBP + β2 × SCI + β3 × malaria + β4 × age + β5 × sex + β6 × BAZ +
β7 × DDS
Model 4: y = β0 + β1 × RBP + β2 × SCI + β3 × malaria + β4 × age + β5 × Sex + β6 × BAZ +
β7 × DDS + β8 × family size + β9 × Mother's education
Where y = Hb or log (SF) or log (sTfR)
All statistical analyses were done with SAS 9.3 (SAS Institute Inc., Cary NC.) and a
twotailed P-value 0.05 at 95% confidence interval was considered statistically significant.
From Table 1, the mean Hb was 109.3 ± 13.4 g/l whilst the median (IQR) for SF and sTfR were
44.8 (29.7 to 93.9) μg/l and 10.1(8.1 to 13.2) mg/l respectively. Overall, 63.8% of the
schoolchildren were anemic. Using a cut-off value of <15μg/l for SF concentration, 7.1% of the children
had ID and this proportion increased to 8.9% after correction with factors proposed by
Thurnham. ID differed widely if based on SF or sTfR (7.1% vs. 68.3%). The overall prevalence of ID
defined as SF <15μg/l and/or sTfR > 8.5 g/l was 68.3%.
We found that 46.4% of the schoolchildren had IDA. The mean RBP concentration was
0.8 ± 0.2 μmol/l with 37.5% of the children being vitamin A deficient; the VAD prevalence
decreased to 30.8% after correction with factors proposed by Thurnham. Furthermore, a half
(50.5%) of the schoolchildren had low or marginal vitamin A status and a quarter (25%) of
them had concurrent VAD and ID. Close to half (48.7%) of the children had SCI. The
prevalence of malaria antigenemia was 81.3%; about 40% of those with malaria antigenemia had
SCI. The mean DDS of the children was 5.9 ± 0.9. Only a quarter (24.6%) of the children
consumed vitamin A-rich dark green leafy vegetables and less than 10% each consumed dairy
products, flesh foods, eggs, vitamin A-rich fruits and vitamin C-rich fruits (S1 Fig).
In the crude model of the multivariate linear regression analysis (Table 2), a unit increase in
RBP was associated with a significant 10.4 g/l increase in Hb concentration (β = 10.4, P = 0.01).
After adjustment for possible confounders, the association between RBP and Hb remained
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statistically significant (β = 7.2, P = 0.05). A unit increase in RBP resulted in a non-significant
1% increase in SF in the crude model (β = 0.01, P = 0.99). When we adjusted for SCI and
malaria, the association between RBP and SF was still not statistically significant (β = 22.5,
P = 0.29); further adjustment for demography, nutritional status and socio-economic factors
did not change the association (β = 20.7, P = 0.38). Table 2 also indicates that a unit increase in
RBP was associated with a 0.9% decrease in sTfR concentration in the crude model (β = -0.9,
P = 0.94). This inverse association became positive after adjustment for SCI, malaria and
background characteristics but remained not statistically significant (β = 5.7, P = 0.63).
Tables 3 and 4 show that RBP is only associated with Hb in the absence of SCI. Tables 3
and 4 demonstrate that in the presence of SCI, there is an overestimation of the association
between RBP and SF and an underestimation of the association between RBP and sTfR.
While controlling for all other potential confounders (Table 5), children without SCI had
3.7g/l significantly higher Hb level compared to those with SCI (P = 0.04). However, children
without SCI compared to those with SCI had a 63% and 0.23% reduction in SF and sTfR
concentrations respectively (P = 0.001 and P = 0.97 respectively). We found a significant positive
association between malaria antigenemia (present vs. absent) and SF (β = 25.1, P = 0.05) and
an insignificant positive association with sTfR (β = 12.8, P = 0.09). In contrast, presence of
malaria resulted in a non-significant 1.3g/l decrease in Hb (P = 0.55). With the exception of
sTfR (R2 = 0.05, P = 0.19), the proportion of variance explained by the multivariate models for
Hb (R2 = 0.17, P < .0001) and SF (R2 = 0.20, P < .0001) were significant. Lastly, the goodness
of fit of the multivariate models as measured by the mean squared errors (MSE) was 12.49,
0.75 and 0.42 respectively for Hb, SF and sTfR.
Prevalence of anemia, ID, IDA and VAD
In this population of schoolchildren from rural northern Ghana, the overall prevalence rates of
anemia, ID, IDA and VAD were of severe public health significance [
]. In the same area,
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an earlier work among school children corroborates the severity of anemia, ID and IDA .
Overall, the prevalence of anaemia and ID were about twice the rates reported by Herrador
et al (anemia = 30.9%, ID = 3.4%) [
] in Ethiopia and higher compared to Righetti et al in CoÃte
d'Ivoire (anemia = 47.3%, ID = 2.7%) [
]. However, the VAD prevalence among this cohort
of schoolchildren was similar to that reported by Herrador et al (VAD = 29.3%) [
Ethiopia. Using serum retinol concentration, a study among schoolchildren in the Volta region of
Ghana reported a similar prevalence of VAD (35.6%) [
] and associated it with inadequate
dietary vitamin A intake.
Among this group of schoolchildren, adjusting of RBP with Thurnham et al [
factors or excluding children with SCI had no influence on the public health significance of
VAD. Similarly, adjusting SF with Thurnham et al [
] correction had little influence on the
prevalence of ID based on SF <15 μg/l. However, we observed that the prevalence estimates of
ID varied widely depending on the biomarker used (SF or sTfR); caution may therefore be
needed when estimating ID prevalence in a country like Ghana.
In the present study, a quarter of the children had concurrent VAD and ID; a
phenomenon described by others[3,6±8,32]. The co-existence of high of ID and VAD could partly be
explained by the heavy burden of infections and infestations in the study area, reflected in
β,regression co-ef®cient; SE(β), standard error of regression coef®cient; Model1: adjusted for malaria; Model 2: further adjusted for age and sex; model 3
was adjusted for nutritional status (body-mass index for-age z-score/BAZ) and dietary diversity score (DDS) and model 4 ®nally adjusted for family size and
education of mother.
*Values were log-transformed and estimates are in percentages.
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the high prevalence of malaria and SCI (81.3% and 48.7% respectively). Inadequate intake
of ID and VAD-related micronutrients among the school-age children may also partly
explain our findings as their dietary pattern was mainly monotonous plant based foods with
poor consumption of animal foods as well as vitamin A-rich fruits and vegetables (S1 Fig).
Studies have shown that monotonous plant based diets are poor sources of micronutrients
due to high concentrations of phytates and other dietary inhibitors in such diets [
study among school-aged children in the study area confirms micronutrient inadequacy
among the children .
Association between vitamin A and iron status
To our knowledge, the present study was the first to examine the association between vitamin
A status and iron status of school-aged children in northern Ghana. The association between
RBP and iron status showed a significant result for only Hb (P = 0.05) with a unit increase in
β = co-ef®cient of regression, SE (β) = standard error of regression coef®cient; SCI, sub-clinical in¯ammation. Note: For Hb, R2 = 0.17, root mean squared
error (MSE) = 12.49 and P < .0001; for SF, R2 = 0.20, MSE = 0.75 and P < .0001; for sTfR, R2 = 0.05, MSE = 0.42 and P = 0.19
*P-value statistically signi®cant at α = 0.05.
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RBP resulting in a 7.2g/l increase in Hb concentration after adjusting for possible confounders;
the present findings corroborate those of other studies [
]. Several intervention studies
have associated vitamin A supplementation with an increase in hemoglobin concentration
]. In this regard, suggestions that anemia prevention programmes should include
vitamin A improvement programmes are justified. In the present study, we hypothesized a
significant positive association between RBP and SF as well as sTfR. However, we found no
significant association between RBP and SF nor between RBP and sTfR, a phenomenon described
by Hashizume et al [
] and Sales et al [
]. Nevertheless, some studies have reported significant
associations between vitamin A status and SF and sTfR [
]. Indeed, the association
between RBP and SF as well as sTfR has been inconsistent in the literature and may be
attributed to extraneous or intrinsic factors within the population that can influence both vitamin A
and iron status indicators.
After adjusting for SCI and malaria antigenemia, the β regression coefficients for sTfR and
SF increased from to -0.9 to 2.9 and from 0.01 to 22.5 respectively, emphasizing the influence
of infection and inflammation on iron status biomarkers. In other words, the findings support
evidence that interpretations of the interaction between vitamin A and iron metabolism can be
masked by infections which lead to increased SF and sTfR concentrations and decreased
plasma retinol concentrations [
]. Notably, SF has been shown to increase during
infection, giving false negative results [
]; this explains why we observed a significant
positive correlation between SF concentration and the inflammation biomarkers (CRP and AGP,
data not shown). Thus, the lack of statistical significance between RBP and SF in the present
study could be that SCI exerts its impact on SF independent of the vitamin A status of the host.
The prevalence of malaria in the present study was high compared to Otupiri et al (58.6%)
in the south of Ghana [
]. Whilst this may suggest a geography variation in the prevalence of
malaria even within the same country, studies suggest malaria infection alters the
concentrations of iron indicators (notably sTfR) independent of iron status [
]. Although this
may have affected the measured associations in the current study, by mathematically adjusting
for malaria, we presume its effect on the iron status indicators was sufficiently accounted for.
Strengths and limitations of study
In this study, we could not assess the status of other relevant micronutrients such as the
B-vitamins, vitamins C and D as well as Zn which have all been linked to iron and vitamin A status
[1±3,25]. Hence, though plausible, the co-existence of VAD and ID with other micronutrient
deficiencies in our study population which may partly explain our findings cannot be
ascertained. In our analysis, however, we controlled for dietary diversity which is known to be a
good proxy indicator of micronutrient intake [
We used RBP as a proxy measure of vitamin A status rather than serum retinol which may
affect our estimates of vitamin A status. Infection, protein malnutrition and inflammation
depress RBP concentration because it is an acute phase protein [
]. It was thus plausible
the RBP levels of the children were not a true reflection of their vitamin A status; but, we
presume the multivariate adjustment for SCI and BAZ may have curtailed the influence of protein
malnutrition and inflammation on the measured effects. RBP has been shown to correlate well
with serum retinol and is a simple, inexpensive tool for assessing vitamin A status in
population studies [
]In addition, sickle cell traits are prevalent in Ghana [
] and may be
associated with increased sTfR [
]; however, because we did not measure hemoglobin variants, we
are unable to examine the extent to which these conditions contribute to elevated sTfR in this
population. Although residual confounding is often a problem in observational studies even
with extensive statistical adjustments [
], we presume this was not a major issue in our
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present analysis as we had sufficient information on the main potential confounders and
adjusted for them. Additionally, high correlations between the predictors may cause large
problems in the estimation process [
], but our test for multicollinearity was acceptable in
all predictors used.
The major limitation of the present study is its cross-sectional design. Notably, the inference
of a possible causality is unfounded since it is not possible to determine whether improved
vitamin A status precedes a better iron status. A prospective study would better address this issue.
Finally, the school-aged children we studied may not necessarily be representative of all
children in Ghana for two reasons. Firstly, our study population is rural, which limits the
generalization of our findings to all school-aged children in Ghana. Secondly, Ghana is a multi-ethnic
country with diverse cultural and dietary patterns making it rather impossible to account for all
variations among school aged children in Ghana. At best, the present findings can be
extrapolated to all rural school-aged children in Northern Ghana where culture and dietary patterns are
The study shows that RBP is significantly associated with Hb concentration but not with SF and
sTfR. The observed relationship between RBP and Hb is only significant in the absence of SCI.
S1 Fig. Percentage consumption of different food groups for school-aged children in
Tolon district (in October 2010). Vit. A, vitamin A; Vit. C, vitamin C; DGLV, dark green
leafy vegetables; YORV, yellow orange and red vegetables; vegs, vegetables.
The authors are grateful to the teachers of the two schools: Y. Abdul-Majeed, A. Alaru, A.A.
Suhuyini, and A. Wumbei. The authors also thank the mothers/caregivers who participated in
Conceptualization: A-RA IDB.
Formal analysis: A-RA FA.
Funding acquisition: A-RA IDB.
Methodology: A-RA IDB.
Project administration: A-RA IDB.
Supervision: A-RA IDB.
Writing ± original draft: A-RA FA.
Writing ± review & editing: A-RA FA.
11 / 15
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