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Association of in utero antibiotic exposure on childhood ear infection trajectories: Results from a national birth cohort study

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  • Murdoch Children’s Research Institute

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Aim: Most prescribed medicines during pregnancy are antibiotics, with unknown effects on a fetus and on the infant’s acquired microbiome. This study investigates associations between in utero antibiotic exposure and ear infection trajectories over the first decade of life, hypothesising effects on early or persistent, rather than later-developing, ear infections. Methods: Design and participants: The Longitudinal Study of Australian Children birth cohort recruited a nationally-representative sample of 5107 infants in 2004. Measures: Mothers reported antibiotic use in pregnancy when a child was 3–21 months old (wave 1), and ongoing problems with ear infection every 2 years spanning ages 0–1 to 10–11 years (waves 1–6). Analysis: Latent class models identified ear infection trajectories, and univariable and multivariable multinomial logistic regression determined odds of adverse trajectories by antibiotic exposure. Results: A total of 4500 (88.1% of original sample) children contributed (mean baseline age 0.7 years; 51.3% boys); 10.4% of mothers reported antibiotic use in pregnancy. Four probability trajectories for ear infection emerged: ‘consistently low’ (86.2%), ‘moderate to low’ (5.6%), ‘low to moderate’ (6.7%) and ‘consistently high’ (1.4%). Antibiotic use in pregnancy was associated with children following ‘consistently high’ (adjusted odds ratio 2.04, 95% confidence interval 1.08–3.88, P = 0.03) and ‘moderate to low’ (adjusted odds ratio 1.78, 95% confidence interval 1.25–2.53, P = 0.001) trajectories. Conclusions: Antibiotic use in pregnancy is associated with an increased risk of persistent and early childhood ear infections. This highlights the wisdom of cautious antibiotic use during pregnancy, and the need for the study of potential mechanisms underlying these associations.
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ORIGINAL ARTICLE
Association of in utero antibiotic exposure on childhood ear
infection trajectories: Results from a national birth cohort study
Yanhong J Hu ,
1,2
Jing Wang,
1,2
Joseph I Harwell
3
and Melissa Wake
1,2
1
Murdoch Childrens Research Institute, The Royal Childrens Hospital,
2
Department of Paediatrics, The University of Melbourne, Melbourne, Victoria,
Australia and
3
Division of Infectious Diseases, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States
Aim: Most prescribed medicines during pregnancy are antibiotics, with unknown effects on a fetus and on the infants acquired microbiome.
This study investigates associations between in utero antibiotic exposure and ear infection trajectories over the rst decade of life, hypothesising
effects on early or persistent, rather than later-developing, ear infections.
Methods: Design and participants: The Longitudinal Study of Australian Children birth cohort recruited a nationally-representative sample of
5107 infants in 2004. Measures: Mothers reported antibiotic use in pregnancy when a child was 321 months old (wave 1), and ongoing prob-
lems with ear infection every 2 years spanning ages 01to1011 years (waves 16). Analysis: Latent class models identied ear infection trajec-
tories, and univariable and multivariable multinomial logistic regression determined odds of adverse trajectories by antibiotic exposure.
Results: A total of 4500 (88.1% of original sample) children contributed (mean baseline age 0.7 years; 51.3% boys); 10.4% of mothers reported
antibiotic use in pregnancy. Four probability trajectories for ear infection emerged: consistently low(86.2%), moderate to low(5.6%), low to
moderate(6.7%) and consistently high(1.4%). Antibiotic use in pregnancy was associated with children following consistently high(adjusted
odds ratio 2.04, 95% condence interval 1.083.88, P= 0.03) and moderate to low(adjusted odds ratio 1.78, 95% condence interval 1.252.53,
P= 0.001) trajectories.
Conclusions: Antibiotic use in pregnancy is associated with an increased risk of persistent and early childhood ear infections. This highlights
the wisdom of cautious antibiotic use during pregnancy, and the need for the study of potential mechanisms underlying these associations.
Key words: birth cohort; childhood; ear infection; in utero antibiotic exposure; trajectories.
What is already known on this topic
1 Antibiotic use during pregnancy is common.
2 Middle ear infection is a common early childhood disease.
3 Prenatal antibiotics use can change fetal microbiota.
What this paper adds
1 Ten percent of pregnant women reported antibiotic use during
pregnancy (not including antibiotic use during labour).
2 Children of these mothers were more likely to follow trajectories
characterised by early or consistently high rates of ear infections
across the rst decade of life.
The consumption of antibiotics is increasing world-wide, leading
to concern around the increasing prevalence of antibiotic resis-
tance and potential long-term adverse environmental and health
effects. One in four women receive at least one antibiotic during
pregnancy and the majority of prescribed medicines are
antibiotics,
1
which could affect the fetus and newborn in under-
appreciated ways that may persist throughout childhood.
2
For
example, antibiotics may perturb maternal bacterial ora from
which a newborn infants microbiome is derived.
3
Systematic
reviews, animal models and population studies have shown that
maternal antibiotics exposure changes the gut microbiome
49
and
increases the risk of antimicrobial resistance in neonates.
10,11
In
addition to direct impacts on ora, one of the underlying poten-
tial mechanisms is that gut microbiome may inuence mucosal
innate and adaptive immunity, which may cause systemic
immune disorders and increase susceptibility.
12,13
Antimicrobial
exposure in utero has previously been shown to have associations
with numerous conditions, including asthma,
14
obesity,
15
atten-
tion decit hyperactivity disorder
16
and others.
9
Some antibiotics,
such as aminoglycosides, may also have a direct teratogenic effect
on fetal ear development.
17
Middle ear infection (otitis media) is a common early child-
hood disease. More than 80% of children will experience acute
otitis media before 3 years of age, and 40% will have six or more
recurrences by the age of 7 years.
18
Otitis media represents the
most common reason for childhood physician sick visits and for
antibiotic prescription in early childhood.
19
The natural history of
otitis media is dynamic, including early or late onset, periods of
Correspondence: Dr Yanhong J Hu, Murdoch Childrens Research Insti-
tute, The Royal Childrens Hospital, 50 Flemington Road, Parkville, Vic.
3052, Australia. Fax: +61 3 8341 6212; email: jessika.hu@mcri.edu.au
Yanhong J Hu and Jing Wang contributed equally to this study.
Conict of interest: None declared.
Accepted for publication 13 January 2021.
doi:10.1111/jpc.15371
Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
1
recurrence, persistence and complete resolution.
20
The predomi-
nant bacteria for otitis media in children globally
21
and in
Australia
22
are Streptococcus pneumoniae and Haemophilus inuenzae
identied through bacterial culture. However, otitis media is usually
caused by viral infections. A recent Australian study showed that
antibiotics are over-prescribed for otitis media for children,
23
and a
national Australia population study showed that overall antibiotics
use in general increased more than 50% from 2001 to 2012.
24
If antibiotics during pregnancy were to exert an impact on the
likelihood of otitis media during childhood, via (for instance)
changes to infant microbiome, then we would expect to see this
additional risk in infancy most proximal to the antibiotic expo-
sure and either persist or slowly decline through, rather than
emerge later in, childhood. This is supported by modelling studies
that suggest that, following antibiotic exposure, the gut micro-
biome may return to stability between 3 months and 5 years
later.
25
One way to study this hypothesis is to examine longitudi-
nal trajectories
26
of propensity to ear infections, requiring the col-
lection of both an indicator of antibiotic use during pregnancy
and repeated measurement of ear infection rates at multiple time
points in population studies.
The national Longitudinal Study of Australian Children
(LSAC) offers this opportunity, with prospective biennial
reporting of ongoing ear infections from infancy to age
1011 years. Therefore, the objective of this study is to analyse
the association of parent-reported maternal antibiotic use during
pregnancy with risks of different trajectories of middle ear infec-
tion spanning the entire rst decade of life. We hypothesised that
antibiotic consumption in pregnancy would be associated with
higher rates of early ear infection that either persist or decline,
but not with a tendency to later-onset ear infections.
Methods
Study design and participants
In 2004, the LSAC was launched to improve understanding of
child development, inform social policy debate, and identify
opportunities for intervention and prevention strategies in policy
areas concerning children and their families. It used a two-stage
random sampling framework stratied by state, urban/rural split
and clustered by postcode to recruit two nationally-representative
samples of approximately 5000 Australian children each from the
Australian Medicare database. Medicare is a core funding mecha-
nism for the Australian universal health-care system into which
98% of children are enrolled by their rst birthday.
27
The two
cohorts were the Birth cohort (initially aged 01 years) and the
Kindergarten cohort (initially aged 45 years), both followed
every 2 years with written and interview-administered question-
naires since enrolment covering many areas, including socio-
demographic information, child functioning, and characteristics
of home, community, relationship, education, health and
childcare. This study is ongoing, with subjects now around
16 and 20 years of age in the two cohorts. Details of LSACs ini-
tial study design and recruitment are thoroughly outlined else-
where.
28
This research draws on data from the rst 6 waves
from 2004 to 2014 for the Birth cohort only, with an initial
response rate of 57.2% (5107/8921).
29
Of these, 73.7%
(3764/5107) were retained from wave 1 to wave 6 (the waves
relevant to this paper), when the children were aged
1011 years.
30
The characteristics of participants more likely and
reasons to drop out (e.g. refused, non-contact, away for the
entire enumeration period and death of study child)
31
are similar
to surveys in other countries.
32
Procedures
After obtaining informed consent, trained professional inter-
viewers conducted biennial 90-min face-to-face interviews in the
childrens homes with their primary caregivers (usually the bio-
logical mother). As well as primary caregivers, other parents/
guardians additionally completed written questionnaires, because
they may have different perspectives on the child, and also
because each parents health, wellbeing and views on things like
family relationships may impact differently on the child.
Measures
Use of antibiotics in pregnancy
Mothers reported on their use of antibiotics in pregnancy at base-
line wave (wave 1) when the child was aged 321 months in
face-to-face interviews. The use of antibiotics in pregnancy was
recorded using a categorical question. Mothers were asked Did
you take any medicines/tablets during pregnancy?and, if they
answered yes, What prescribed medicines or tablets were taken?
Antibiotics/penicillin (yes/no)?, with a single yes/no answer
applying to all antibiotics.
Ear infection
Parents reported on childrens ongoing ear infections from waves
1 to 6 (ages 01to1011 years) at face-to-face interviews. The
presence of ear infection was recorded using the same categorical
question at each wave, with the responding parent asked Does
(child of interest) have any of these ongoing conditions - Ear
infections (yes/no)?
33
Potential confounders were age, sex, birthweight and socio-
economic status (wave 1) and passive smoking, all of which have
been associated with both antibiotic use and ear infections in the
literature.
3436
A childs date of birth, sex and birthweight were
taken from LSAC records. Neighbourhood disadvantage was
measured using the disadvantage index from the 2001 Socio-
Economic Indexes for Areas.
37
This is a composite index based on
ranking postcodes according to relative disadvantage, using data
from the ve-yearly Census of Population and Housing adminis-
tered by the Australian Bureau of Statistics. Contributing items
include average household education levels, income levels,
employment status and disability for that postcode. The national
mean for this index is standardised to 1000 (standard deviation
(SD) 100), with higher scores reecting less disadvantage. We
created a binary variable of passive smoking exposurefor chil-
dren if the parent questionnaire recorded any smokers at home
at any LSAC wave from child age 0 to 11 years.
Statistical analysis
LSAC is an Open Science resource. All data are released by the
Australian Data Archive (ADA). Under our ADA licence, we
downloaded the LSAC data in Stata format from the ADA
2Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
Results from a national birth cohort YJ Hu et al.
website and extracted the relevant variables through Stata.
All statistical analyses were performed in Stata 15.0 (StataCorp
LLC, USA).
Identication of ear infection trajectories (aim 1)
Trajectory modelling was used to identify groups that have simi-
lar patterns of change over time. To examine ear infection tra-
jectories across waves 16, we conducted group-based trajectory
modelling using the trajplug-in in Stata.
38
Only participants
with ear infection data for at least three waves were included in
the trajectories (Fig. 1). For trajectory modelling, ear infection
data were modelled with binary logit distribution which is
designed for the analysis of longitudinal data on a dichotomous
outcome variable. In order to extract the most meaningful and
distinct trajectories, we considered Bayesian information crite-
rion values, average posterior probabilities, the proportion of
the sample in each trajectory and visual graphs of trajectories.
39
We also dropped non-signicant (e.g. P> 0.05) quadratic or
cubic parameters for each trajectory (Tables S1 and S2,
Supporting Information).
40
Using these criteria, we selected and
named from visual inspection a four-trajectory solution for child
ear infections.
Fig 1 Participant ow chart birth cohort of Longitudinal Study of Australian Children.
Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
3
YJ Hu et al. Results from a national birth cohort
Associations between antibiotic use in pregnancy
and ear infection trajectories
We conducted univariable and multivariable multinomial logistic
regression analyses for the associations between antibiotic use in
pregnancy and ear infection trajectories. For multinomial analy-
sis, we adjusted for age, sex, birthweight, type of delivery (vagi-
nal or caesarean), neighbourhood disadvantage (wave 1) and
passive smoking.
Ethics approval and consent to participate section
The research methodology and survey content of Growing Up in
Australia is reviewed and approved by the Australian Institute of
Family Studies Ethics Committee, which is a Human Research
Ethics Committee registered with the National Health and Medi-
cal Research Council (NHMRC). The Ethics Committee ensures
that Growing Up in Australia meets the ethical standards outlined
in the National Statement on Ethical Conduct in Research Involv-
ing Humans. The LSAC study was approved by the Australian
Institute of Family Studies Ethics Committee (AIFS 14-26) in
Jan-Feb 2014; the Ethics Committee also provides ethical review
and approval for LSAC at every wave.
Results
Sample characteristics
Figure 1 presents the study ow from wave 1 of LSAC onward
with the number of children at each wave of the birth cohort of
LSAC. Both antibiotic exposures and ear infection trajectories
data are available for 4500 children (51.2% boys). Table 1 sum-
marises the participant characteristics. The mean age of children
included in analyses was 0.7 years (SD 0.2) at wave 1. The mean
disadvantage index at wave 1 was 1010 (SD 60), indicating our
sample was on average slightly less disadvantaged and more
homogeneous than the general Australian population. A total of
10.4% (n = 467) had parent-reported antibiotic use in
pregnancy.
Ear infection trajectories
Four probability trajectories of parent-reported ear infection
emerged (Fig. 2). The consistently lowgroup contained the larg-
est number of children (86.2%, n= 3880) and represented a con-
sistently low probability of having ear infections; 5.6% (n= 253)
of children were in the moderate to lowgroup, which represen-
ted a decreasing probability of having ear infections from age 3 to
11 years. 6.7% (n= 302) of children belonged to the low to
moderategroup, representing the rise in the probability of hav-
ing ear infections from age 0 and 9 years. The consistently high
group comprised only a small proportion of children (1.4%,
n= 65) and was characterised by a consistently high probability
of having ear infections.
Association between antibiotic use in pregnancy
and ear infection trajectories
The proportion of antibiotic use in pregnancy in each trajectory
was: 9.7% in consistently low, 11.9% in low to moderate,
16.6% in moderate to lowand 18.5% in consistently high
(Table 2). In univariate analysis, antibiotic use in pregnancy was
associated with children following moderate to low(odds ratio
(OR) 1.84, 95% condence interval (CI) 1.312.62, P= 0.001)
and consistently high(OR 2.10, 95% CI 1.113.97, P= 0.02)
trajectories, compared to consistently lowtrajectory. In multi-
variate analysis, adjusting for age, sex, birthweight, type of deliv-
ery, neighbourhood disadvantage and passive smoking, antibiotic
use in pregnancy remained strongly associated with children fol-
lowing moderate to low(OR 1.78, 95% CI 1.252.53,
Fig 2 Latent class categories of parent-reported ear infection trajecto-
ries from wave 1 to wave 6 in Longitudinal Study of Australian Childrens
Birth cohort.
Table 1 Sample characteristics; values are mean (standard deviation)
unless specied otherwise
Characteristics Children (n= 4500)
Age (years)
Baseline wave (wave 1) 0.7 (0.2)
Wave 2 2.8 (0.2)
Wave 3 4.8 (0.2)
Wave 4 6.8 (0.3)
Wave 5 8.9 (0.3)
Wave 6 10.9 (0.3)
Male sex, % 51.3
Neighbourhood disadvantage at wave 1 1010 (60)
Birthweight, kg 3.4 (0.6)
Passive smoking, % 22.3
Antibiotics/penicillin in pregnancy, % 10.4
Ear infection trajectories, %
Consistently low 86.2
Low to moderate 6.7
Moderate to low 5.6
Consistently high 1.4
Type of delivery, %
Caesarean 39.8
Vaginal 60.2
4Journal of Paediatrics and Child Health (2021)
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Results from a national birth cohort YJ Hu et al.
P= 0.001) and consistently high(OR 2.04, 95% CI 1.083.88,
P= 0.03) trajectories (Fig. 3).
Discussion
Principal ndings
This study shows that, compared to those not exposed, children
exposed to parent-reported antibiotics in utero were around twice
as likely to experience high early rates of parent-reported ear
infection that either declined or persisted from 0 to 11 years of
age. However, they were not more likely to have later-onset ear
infections.
While this association does not prove causality, this is impor-
tant information because parents are the drivers of their childs
health care and highly inuential in their diagnoses. A few possi-
ble causal explanations may be considered. One is that maternal
microbiome changes induced through antibiotic use lead to neo-
natal acquisition of a more disordered, higher risk microbiome.
8
Our observation that maternal antibiotic use is associated with a
moderate frequency of otitis media that decreases with time is
consistent with a disordered infant microbiome that is gradually
restored. Second, there may be direct anatomic or structural
impacts from fetal middle ear antibiotic exposures that might not
be reversible and lead to consistently high rates of otitis media. In
addition, a genetic factor that predisposes the mother to infec-
tions could be inherited by the children, or there is an
unmeasured environmental factor that causes both the mother to
be at risk for infection and that also increases the childs risk,
such as air pollution.
41
In our study we included only passive
smoking in the adjusted model though it had a minimum impact.
To the best of our knowledge there is only one other study of
700 children in the Copenhagen Prospective Study that also
found maternal antibiotic use in third-trimester pregnancy was
associated with the risk of otitis media during the rst 3 years of
life (hazard ratio 1.30; 95% CI 1.041.63).
42
In this Danish study,
37% of the mothers received antibiotics during pregnancy which
is much higher than our cohort. The Copenhagen Prospective
Study utilised clinical and pharmacy records to ascertain antibi-
otic use whereas we relied on maternal recall, with a relatively
low rate reported of 10.4%. LSACs recall approach may be
expected to underestimate antibiotic use in several ways: (i) a
Table 2 Associations between antibiotics use in pregnancy and ear infection trajectories using multinomial logistic regression
Ear infection trajectories Antibiotics in pregnancy, % OR (95% CI)POR*(95% CI)P
Consistently low 9.7 reference reference
Low to moderate 11.9 1.26 (0.871.81) 0.22 1.28 (0.891.85) 0.18
Moderate to low 16.6 1.84 (1.312.62)0.0011.78 (1.252.53)0.001
Consistently high 18.5 2.10 (1.113.97)0.022.04 (1.083.88)0.03
Unadjusted model.
Adjusted for age, sex, neighbourhood disadvantage, bir thweight and passive smoking.
Fig 3 Associations between antibiotic
use in pregnancy and ear infection tra-
jectories using multinomial logistic
regression. Adjusted for age, sex,
neighbourhood disadvantage,
birthweight, passive smoking and type
of delivery. CI, condence interval. ( ),
unadjusted model; ( ), adjusted
model.
Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
5
YJ Hu et al. Results from a national birth cohort
mother may not understand that a medicine given to them is an
antibiotic or may simply forget (recall bias), and (ii) (unlike the
Danish study) the question asked in LSAC did not prompt for
antibiotics during labour (of which many mothers may be
unaware even if prompted). Given that the baseline enrolment
on average occurred when the child was age 0.7 years some
respondents may have forgotten or misreported an antibiotic pre-
scription especially earlier in pregnancy. However, questionnaires
are still a widely used method for many large cohort studies,
43
and the likelihood of recall bias was reduced by asking the ques-
tion in wave 1, soon after the pregnancy. Future study involving
clinical records would increase the reliability and reduce
recall bias.
Strengths and limitations
We were able to examine ear infection trajectories by repeated
biennial reporting throughout the rst 1011 years of life. The
average posterior probability value for each trajectory (Table S2,
Supporting Information) was above the recommended value of
0.70,
44
indicating the model had good assignment accuracy. Our
cohort had a large number of participants more than six times
greater than the Danish cohort. We were also able to follow sub-
jects over a 10-year period to provide a more complete picture of
ear infection events and trends at the population level, while the
Danish study covered only the rst 3 years of life. We thus have
a better understanding of patterns of later-developing ear
infections.
Our study also has limitations. As in most large population-
based studies,
41
otitis media events were based on parent report.
Our parent reports of ongoing ear infectionsis a less valid
source of in the momentinformation than medical assessment,
with one study showing that the diagnostic validity of parent-
reported ear infection is limited (sensitivity 17%, positive predic-
tive value 67%) against tympanograms and pneumatic
otosctopy.
41
However, as our study focused on overall decade-
long trajectories rather than individual event diagnoses, this
repeated biennial report may well give a more complete picture
of ear infection over time than would clinical records. Second,
differential uptake and attrition may limit generalisability; how-
ever, the sample covered a wide social and geographic range and
we adjusted for neighbourhood disadvantage. As our sample
appeared slightly less disadvantaged and more homogeneous
than the general Australian population, these effects may be even
more pronounced in a more disadvantaged population where oti-
tis media is more prevalent. Third, the lack of detailed informa-
tion on which trimester of pregnancy was affected by the
exposure may underestimate or overestimate the actual effect. A
microbiome effect for example might be exaggerated by a late
pregnancy exposure, as was seen in the Copenhagen cohort.
42
An anatomic and/or developmental effect might be more pro-
nounced with early fetal exposures; for example, a study by Fan
et al. highlighted that rst trimester exposure to a macrolide
increased the risk of malformation in children.
1
The timing of
pregnancy exposure will be helpful in further investigations of
underlying mechanisms behind this observed increased risk.
Fourth, a lack of antibiotic prescribing information means we
cannot determine if there is a doseresponse effect. A recent
study has shown that antibiotic exposures had a doseresponse
effect, with multiple antibiotic prescriptions having an increased
association with early childhood infection-related hospitaliza-
tions, consistent with the disordered microbiome effect theory.
45
However, this may not apply to ear infection if antibiotic use
affects the ear structure during a narrow window in early fetal
development. Fifth, we lack information on potentially con-
founding cross-generational variables, both behavioural (tenden-
cies for mothers to seek antibiotics for themselves and their child,
and for prescribers to provide) and genetic/environmental predis-
position to infection. Sixth, we also acknowledge the maternal
infection for which the antibiotic was given rather than antibiotic
exposure itself may contribute independently to the association,
and our survey questionnaire data do not indicate whether the
antibiotics were taken as prescribed or the type and severity of
the maternal infection. Early antibiotic use by the infants and
children themselves were not analysed in this study. However,
antibiotics use for otitis media is increasing.
23
This might further
exacerbate infant microbiome disruption. In any case, should
infants require antibiotic treatment this would support the under-
lying hypothesis that prenatal exposure increases the risk for
infections like otitis.
Much larger studies with biological sampling and detailed
individual-level data on antibiotic class, duration and diagnoses
would further clarify and explain these observations and the
underlying mechanisms, causal or otherwise. This population-
based study was not designed to answer a causal question but
nonetheless emphasises the wisdom of appropriate and cautious
antibiotic use during pregnancy. Previous studies have found that
inappropriate antibiotic use may be linked to a prescribers belief
that antibiotics are harmless, especially when they feel pressured
to ensure patient satiscation.
4648
The nding of this study
(i.e. that there may be under-appreciated harms) could perhaps
help doctors to limit their prescriptions during pregnancy and
reduce antibiotics demanding from parents.
Conclusions
Parent-reported used of prescription antibiotics during pregnancy
is associated with an increased risk of persistent or early ear
infection in childhood. This emphasises the importance of appro-
priate antibiotic use during pregnancy. Further studies with
detailed information on antibiotic exposure timing in relation to
pregnancy as well as assessments of maternal and infant micro-
biome will be needed to dene causality, mechanisms and
resulting burden.
Acknowledgements
This study uses unit record data from Growing Up in Australia,
the LSAC. The study is conducted in partnership between the
Department of Social Services, the Australian Institute of Family
Studies, and the Australian Bureau of Statistics. The ndings and
views reported in this paper are solely those of the authors. YJ
Hu and J Wang had full access to all the data in the study and
take responsibility for the integrity of the data and the accuracy
of the data analysis. We thank the LSAC study participants and
staff for their contributions and Australian Data Archive for data
management. Research at the Murdoch Childrens Research
Institute (MCRI) is supported by the Victorian Governments
6Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
Results from a national birth cohort YJ Hu et al.
Operational Infrastructure Support Program. The funding bodies
did not play any role in the study. JW was supported by the
MCRI Lifecourse Postdoctoral Fellowship. M Wake was supported
by the National Health and Medical Research Council (NHMRC)
Senior Research Fellowship (1046518) and (Principal Research
Fellowship 1160906) in this work.
Data Availability Statement
The data that support the ndings of this study are available from
Australian Data Archive (ADA) but restrictions apply to the avail-
ability of these data, which were used under license for the current
study, and so are not publicly available. Data are however avail-
able from the authors upon reasonable request and with permis-
sion from Australian Data Archive and corresponding author.
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Supporting Information
Additional Supporting Information may be found in the online
version of this article at the publishers web-site:
Table S1. Criteria for selecting the number and shape of
trajectories.
Table S2. Average posterior probability value for ear infection
trajectory groups.
8Journal of Paediatrics and Child Health (2021)
© 2021 Paediatrics and Child Health Division (The Royal Australasian College of Physicians)
Results from a national birth cohort YJ Hu et al.
... Average posterior probability; Methods S1: Dagitty codes for construction of directed acyclic graph; Methods S2: Trajectory analysis. References [5,10,36,[49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65] Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. ...
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