Open Access

Research

Prevalence and predictors of alcohol
use during pregnancy: findings from
international multicentre cohort studies
Linda M O’Keeffe,1,2 Patricia M Kearney,2 Fergus P McCarthy,3,4 Ali S Khashan,2,3
Richard A Greene,1 Robyn A North,5 Lucilla Poston,5 Lesley M E McCowan,6
Philip N Baker,7 Gus A Dekker,8 James J Walker,9 Rennae Taylor,10
Louise C Kenny3,4

To cite: O’Keeffe LM,
Kearney PM, McCarthy FP,
et al. Prevalence and
predictors of alcohol
use during pregnancy:
findings from international
multicentre cohort studies.
BMJ Open 2015;5:e006323.
doi:10.1136/bmjopen-2014006323
▸ Prepublication history
and additional material is
available. To view please visit
the journal (http://dx.doi.org/
10.1136/bmjopen-2014006323).
Received 7 August 2014
Revised 26 November 2014
Accepted 27 November 2014

For numbered affiliations see
end of article.
Correspondence to
Dr Linda M O’Keeffe
Cardiovascular Epidemiology
Unit, University of
Cambridge, Strangeways
Research Laboratory,
Cambridge CB1 8RN,
United Kingdom;
lo288@medschl.cam.ac.uk

ABSTRACT
Objectives: To compare the prevalence and predictors
of alcohol use in multiple cohorts.

Design: Cross-cohort comparison of retrospective and
prospective studies.

Setting: Population-based studies in Ireland, the UK,
Australia and New Zealand.

Participants: 17 244 women of predominantly
Caucasian origin from two Irish retrospective studies
(Growing up in Ireland (GUI) and Pregnancy Risk
Assessment Monitoring System Ireland (PRAMS
Ireland)), and one multicentre prospective international
cohort, Screening for Pregnancy Endpoints (SCOPE)
study.

Primary and secondary outcome measures:
Prevalence of alcohol use pre-pregnancy and
during pregnancy across cohorts. Sociodemographic
factors associated with alcohol consumption in each
cohort.
Results: Alcohol consumption during pregnancy in
Ireland ranged from 20% in GUI to 80% in SCOPE,
and from 40% to 80% in Australia, New Zealand and
the UK. Levels of exposure also varied substantially
among drinkers in each cohort ranging from 70%
consuming more than 1–2 units/week in the first
trimester in SCOPE Ireland, to 46% and 15% in the
retrospective studies. Smoking during pregnancy was
the most consistent predictor of gestational alcohol use
in all three cohorts, and smokers were 17% more likely
to drink during pregnancy in SCOPE, relative risk (RR)
=1.17 (95% CI 1.12 to 1.22), 50% more likely to drink
during pregnancy in GUI, RR=1.50 (95% CI 1.36 to
1.65), and 42% more likely to drink in PRAMS,
RR=1.42 (95% CI 1.18 to 1.70).
Conclusions: Our data suggest that alcohol use
during pregnancy is prevalent and socially pervasive in
the UK, Ireland, New Zealand and Australia. New policy
and interventions are required to reduce alcohol
prevalence both prior to and during pregnancy. Further
research on biological markers and conventions for
measuring alcohol use in pregnancy is required to
improve the validity and reliability of prevalence
estimates.

Strengths and limitations of this study
▪ Our study goes beyond measurement of alcohol
use during pregnancy with just one cohort or
one measurement method, but examines prevalence and predictors using different measurement techniques in similar populations.
▪ The study had a large sample size of almost
18 000 women, and we were able to examine
prevalence using different modes of administration (anonymised, self-administered, postal
survey, trained government interview, antenatal
midwife-collected data) and timing of administration including prospective and retrospective
measurement.
▪ However, because we relied on self-reported
alcohol consumption, reporting and recall biases
may exist in our study. Furthermore, differences
in mode and timing of data collection could
explain variation in estimates between studies.
▪ Our analysis only included live born babies, and
thus, there is a possibility that we have excluded
women with the heaviest drinking patterns, since
failure to give birth to a baby could have resulted
from heavy alcohol consumption; for example,
miscarriage occurring due to chronic alcohol use
or binge drinking in early pregnancy.
▪ Participants in our study may also be more
advantaged than the general population, and
thus, the generalisability of our findings to all
pregnancies, or more diverse populations, may
be reduced.

INTRODUCTION
Worldwide, the majority of clinical and government guidelines advocate for pregnant
women to abstain from alcohol consumption
during pregnancy due to potential adverse
effects on pregnancy outcomes.1–4 However,
although the National Institute of Health
and Care Excellence (NICE) guidelines in
the UK advise abstinence from alcohol in

O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

1

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early pregnancy due to increased risk of miscarriage, it
is noted that 1–2 units up to twice per week have not
been shown to be harmful to the unborn baby, if
women choose to drink.5
Conflicting results on the effects of gestational alcohol
consumption on offspring health outcomes and subsequently, lack of coherence in clinical and government
guidelines stem from a lack of biological markers of light
or moderate alcohol use during pregnancy. Thus, studies
of associations with offspring health outcomes rely on
self-reported maternal alcohol consumption which may
be biased by reporting and recall biases. For example,
estimates of prevalence of alcohol use during pregnancy
and its associated predictors in existing cohort data are
highly variable and range from 36% in the Millennium
Cohort Study (MCS)6 to almost 60% in the Avon
Longitudinal Study of Parents and Children (ALSPAC).7
Consequently, whether exposure and its predictors are
reliably measured in observational studies is difficult to
decipher, and thus, approaches which reveal the validity
and reliability of estimates and predictors are required.
Cross-cohort comparisons may be a useful way to
examine plausible and valid self-reported prevalence
estimates and predictors. Comparing multiple cohort
estimates within the same population allows the validity
of prevalence estimates and predictors of alcohol use to
be compared when measured using different techniques; if prevalence is accurately reported and not
subject to substantial recall and reporting biases, prevalence and predictors should be mostly consistent across
studies. Comparing subpopulation estimates within the
same cohort allows for population variation in alcohol
prevalence and predictors to be compared when exposure measurement is constant; if prevalence and predictors vary substantially across countries within the same
study using the same measurement methods, insights
into the impact of culture and attitudes on alcohol consumption, or reporting of alcohol, can be revealed.
Taken together, such techniques may provide increased
insight into plausible prevalence estimates of alcohol use
during pregnancy, improved alcohol exposure measurement during pregnancy, and increased understanding of
the social patterns of alcohol use across cohorts. In turn,
this evidence can be used to inform antenatal care
guidelines on alcohol use.
The objectives of this study were to compare the
prevalence of alcohol use across three cohorts; Growing
up in Ireland (GUI),8 9 Screening for Pregnancy
Endpoints (SCOPE) study10 and Pregnancy Risk
Assessment Monitoring System (PRAMS) Ireland.11 GUI
and PRAMS measured gestational alcohol use retrospectively, while SCOPE obtained measures of alcohol use
during pregnancy. Second, we compared the characteristics associated with alcohol use in all three studies and
within SCOPE countries (New Zealand, Ireland,
Australia and the UK) in order to examine cross-cohort
and cross-country consistency in the prevalence and predictors of gestational alcohol use.
2

METHODS
Study population
Growing up in Ireland
The National Longitudinal Study of Children is the first
longitudinal study of its kind that focuses on the developmental trajectories of children in Ireland.8
Participants were sampled from the state child benefit
register (>20 000 primary care givers sampled from
approximately 41 000 on the register over the period 1
December 2007 to 30 June 2008) using a simple systematic selection procedure prestratifying by parental
marital status, country of residence, nationality and
number of children.8 Surveys were completed with the
primary and secondary caregivers of 11 134 infants aged
6–9 months, from September 2008 to April 2009.8 This
represented almost a quarter of all births in Ireland over
that period.8 Surveys were administered by trained study
personnel in the home of the caregivers through a
face-to-face interview.8 Non-biological mothers or male
primary caregivers who participated in the study were
excluded from the present analysis (0.3%). Biological
mothers who did not complete the questionnaire were
also excluded from the present study (0.1%). All participants gave informed consent prior to participation in
the study.

Screening for Pregnancy Endpoints
SCOPE is a prospective, multicentre cohort study with
the principal aim of developing screening tests to
predict pre-eclampsia, small for gestational age (SGA)
infants, and spontaneous preterm birth.10 Participants
were healthy nulliparous females with singleton pregnancies (n=8531 originally approached to participate) of
which 5628 were recruited between November 2004 and
February 2011 in Auckland, New Zealand; Adelaide,
Australia; Cork, Ireland; and Manchester, Leeds and
London, UK, as previously described.10 12 Women were
excluded if they were considered at high risk of preeclampsia, delivery of a SGA infant, or spontaneous
preterm birth, because of underlying medical conditions, gynaecological history, three or more previous miscarriages, three or more terminations of pregnancy, or
had received interventions, such as aspirin, that might
modify pregnancy outcome.10 Study participants were
interviewed and examined by study research midwives at
15 and 20 weeks of gestation. At the time of interview,
data were entered on an internet-accessed central database with a complete audit trail (MedSciNet).13
Pregnancy information and pregnancy outcome data
were collected prospectively by research midwives. All
data entries were individually checked (including data
entry errors in the lifestyle questionnaire), and a customised software program was used to detect any systematic data entry errors. All participants gave informed
consent prior to participation in the study. Only participants who delivered a live born baby were included in
the present analysis.
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

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PRAMS Ireland
The aim of PRAMS was to measure the prevalence of a
wide range of maternal health behaviours and experiences before, during and after pregnancy. The sample
for the study was derived using hospital discharge
records of live births at Cork University Maternity
Hospital, a large urban obstetric hospital in the South of
Ireland where almost 9000 live births per year occur.
A constant sampling fraction of 1 in 2 records alternately
sampled 1212 from a sampling frame of approximately
2450 mother–infant pairs discharged between 14 May
2012 and 18 August 2012. Of these, 718 (61%) women
responded and were included in the present analysis.
Mothers of stillbirths, neonatal deaths (n=3) and early
and late miscarriages were planned exclusions (none
identified), as the objective of the study was to characterise maternal behaviours and experiences in women with
live births. Women were invited to participate by post
and were sent three postal surveys, a reminder letter and
a text reminder. The PRAMS questionnaire was based
on PRAMS Phase 6 questions covering sociodemographics, health behaviours and experiences before,
during and after pregnancy,14 and detailed information
on dose, pattern and timing of alcohol exposure for the
3 months before pregnancy, and in each trimester was
based on the work of O’Leary et al, 2009, and described
in detail elsewhere.11 15 On date of receipt of the first
survey, mothers were between 2 and 5 months postpartum. On the date of receipt of the final PRAMS
survey, mothers were between 7 and 9 months postpartum. Thus, respondents of the survey were anywhere
between 2 and 9 months postpartum. PRAMS used an
opt-out consent system whereby women who did not
wish to participate in the survey were permitted to opt
out at the beginning of the study. Women who did not
opt out were treated as willing participants.
Assessment of alcohol
Growing up in Ireland
Women were asked, separately, if they drank in each trimester of pregnancy. Women who reported alcohol use
during pregnancy were asked how much on average they
drank per week ( pints of beer or cider, glasses of wine,
measures of spirits or alcopops) in each trimester.
Screening for Pregnancy Endpoints
Alcohol consumption was reported as units consumed
per week. At the 15-week interview, participants were
asked ‘Were you drinking alcohol prior to pregnancy?’,
‘Were you drinking alcohol earlier in the pregnancy in
the first trimester?’ and finally ‘Are you still drinking
alcohol?’. If the participants answered ‘yes’ to any of the
above, the amount of alcohol was then quantified
including number of units and binges per week.
Participants who confirmed that they had consumed
alcohol during pregnancy were asked when they stopped
drinking. At 20 weeks’ gestation, women were asked the
number of units of alcohol per week consumed at
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

20 weeks’ gestation and the number of binges taken
between the 15-week and 20-week interviews.
Pregnancy risk assessment monitoring system
Women were asked to report the number of occasions
per week or month alcohol was consumed ranging from
never, less than 1 occasion per month, 1–2 occasions per
month, 1–2 occasions per week, 3–4 occasions per week
and 5 or more occasions per week for the 3 months
before pregnancy, and each trimester separately. For the
number of occasions indicated in each time period,
women were asked to indicate the number of glasses or
bottles of beer, wine (100 mL), alcopop, sherry or port,
and spirits or liqueurs consumed per occasion.
Comparing and categorising alcohol use
Although the measurement of alcohol use during pregnancy varied across the studies, we standardised classification across each cohort to ensure categories in each study
were comparable (note that some findings on alcohol
use in PRAMS and SCOPE have been published previously using different category definitions and in less
detail than explored here).15 16 For this study, one unit of
alcohol was equivalent to approximately 8–10 g of absolute alcohol (slight variation across studies) equating to
one glass of wine (approximately 100–125 mL), one
small glass of sherry, a single nip of spirits, or half a pint
of lager (regular strength). A can or small bottle/glass of
regular-strength beer (300–330 mL, 4–5% alcohol) was
equivalent to 1.5 units of alcohol, and a bottle of alcohol
pop was equivalent to 2 units of alcohol. Where prepregnancy alcohol consumption was reported, it was
defined as consumption of any alcohol in the 3 months
prior to pregnancy. Where quantity of alcohol before
pregnancy and by trimester was available, alcohol intake
was classified as occasional (1–2 units/week), low (3–
7 units/week), moderate (8–14 units/week) and heavy
(greater than 14 units/week). Median units of exposure
were calculated since alcohol is not normally distributed.
Binge consumption was defined as six or more standard
units per occasion.
In GUI and PRAMS, any alcohol consumption or any
binge consumption was defined as consumption of
alcohol in the first, second or third trimester, or consumption of a binge in any of the trimesters (note,
binge alcohol consumption data not available in GUI).
Binge alcohol use by trimester was defined as any binge
alcohol use in the first, second or third trimester separately. Alcohol use before pregnancy was not available in
GUI. In SCOPE, any alcohol consumption included any
alcohol consumed from conception up to the 20-week
interview, including any binge consumption. First trimester use was reported at the 15-week SCOPE visit. For
second trimester use, consumption in the week preceding the 15-week SCOPE visit and preceding the 20-week
SCOPE visit, were combined and divided by two to
obtain a weekly average consumption which was subsequently categorised as occasional, low, moderate or
3

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heavy, as described. Binge drinking in the second trimester was defined as reporting a binge in the week prior to
the 15-week SCOPE visit, or between the 15-week and
20-week SCOPE visit.
Statistical analysis
We examined the association between low birth weight
and preterm birth (traditionally examined in relation to
the effects of gestational alcohol use) and common confounders of these associations and alcohol use during
pregnancy (including age, ethnicity, education, marital
status, parity, body mass index (BMI), smoking) since
these are characteristics by which social behaviours such
as alcohol use are often patterned, and characteristics
which are commonly examined as predictors of alcohol
use. In all analyses, covariates (age, education, ethnicity,

marital status, parity, delivery mode, smoking, BMI,
preterm birth and birth weight) were categorised in an
identical manner for comparability (see table 1 for
categories).
All statistical analyses were conducted in Stata V.12. We
used frequencies to describe the characteristics of each
cohort and compare reported drinking in all three
studies and across SCOPE countries. We used log linear
binomial regression to examine the relative risk of
alcohol consumption during pregnancy in relation to
sociodemographic characteristics in each cohort and in
each SCOPE country. Log linear binomial regression was
chosen because when an outcome variable is common
(>5%), logistic regression tends to overestimate the association between the independent variable of interest
and the outcome. In GUI, as age appeared to have a

Table 1 Characteristics of women participating in GUI (2008, 2009), SCOPE Ireland (2008–2011) and PRAMS Ireland
(2012) by their pregnancy alcohol consumption

Age (years)
<20
20–24
25–29
30–39
>40
Education
Second
Tertiary
Ethnicity
Caucasian
Other
Marital status
Married
Single
Parity
0
1+
Smoking
Yes
No
BMI (kg/m2)
<18.5
18.5–24.99
25.0–29.9
>30
Preterm birth
Yes
No
Birth weight
<2500 g
>/=2500 g

GUI
n=10 953
Alcohol
Yes
n=2198

No
n=8755

19 (10)
130 (13)
337 (15)
1528 (23)
184 (27)

169 (90)
908 (87)
1938 (85)
5046 (77)
500 (73)

<0.001

30 (82)
137 (83)
433 (80)
828 (83)
16 (73)

727 (15)
1470 (24)

4004 (85)
4551 (76)

<0.001

2160 (22)
36 (5)

7868 (78)
657 (95)

1644 (22)
554 (18)

p Value

SCOPE Ireland
n=1766
Alcohol
Yes
No
n=1444
n=322
7
29
110
164
6

p Value

PRAMS
n=718
Alcohol
Yes
n=324

No
n=394

p Value

(18)
(17)
(20)
(17)
(27)

0.3

2 (50)
4 (17)
53 (38)
248 (49)
17 (44)

2 (50)
19 (83)
85 (62)
255 (51)
22 (56)

0.01

1286 (82)
158 (81)

279 (18)
37 (19)

0.7

47 (40)
277 (47)

72 (60)
307 (53)

0.1

<0.001

1433 (83)
11 (27)

286 (17)
30 (73)

<0.001

316 (47)
3 (10)

253 (53)
26 (90)

<0.01

6021 (78)
2540 (82)

<0.001

1277 (81)
167 (89)

296 (19)
20 (11)

<0.01

306 (46)
18 (39)

355 (54)
28 (61)

0.4

760 (18)
1438 (22)

3401 (82)
5160 (78)

<0.001

1450 (82)
–

318 (18)
–

128 (46)
194 (46)

151 (54)
230 (54)

0.97

445 (24)
1753 (20)

1386 (76)
7174 (80)

<0.001

448 (92)
996 (78)

38 (8)
279 (22)

<0.001

77 (55)
204 (43)

63 (45)
272 (57)

0.01

52 (18)
1143 (22)
626 (21)
275 (17)

232 (82)
4132 (78)
2402 (79)
1376 (83)

<0.001

838 (81)
17 (82)
419 (85)
170 (79)

194
4
74
44

(19)
(18)
(15)
(21)

0.2

9 (36)
220 (48)
69 (46)
21 (41)

16
237
81
31

(64)
(52)
(54)
(59)

0.5

113 (16)
2081 (21)

585 (84)
7947 (79)

<0.01

67 (79)
1377 (82)

18 (21)
298 (18)

0.4

15 (41)
309 (46)

22 (60)
360 (54)

0.5

86 (15)
2095 (21)

500 (85)
7963 (79)

<0.001

1384 (82)
60 (81)

302 (18)
14 (19)

0.8

14 (38)
23 (46)

310 (62)
360 (54)

0.3

–
–

All differences tested with χ2 test for categorical variables.
BMI, body mass index; GUI, Growing up in Ireland; PRAMS, Pregnancy Risk Assessment Monitoring System; SCOPE, Screening for
Pregnancy Endpoints.

4

O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

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linear effect on alcohol, we repeated the model without
specifying age as categorical variable to examine a
potential trend in the association between age and
alcohol use. In the analysis of SCOPE countries, UK
centres (Manchester, Leeds and London) were combined. All participants provided written informed
consent.

RESULTS
Eleven thousand one hundred and thirty-four participants were recruited to the GUI study of which 10 953
were included in the present analysis after exclusion of
male primary caregivers and women who did not answer
the sensitive questionnaire. Five thousand five hundred
and seventy-three participants with live births in SCOPE
were included (99% of total cohort), 1766 of which
occurred in SCOPE Ireland. All PRAMS (n=718) respondents were included in the analysis.
Online supplementary table S1 describes the overall
participant characteristics of each study. Table 1 shows
reporting of alcohol use by sociodemographics in each
cohort. In addition to the marked variation in reporting
of alcohol use across cohorts, reporting of alcohol use
varied considerably across sociodemographics and
health characteristics in each cohort. For example, there
was evidence of strong social gradients in alcohol consumption for all characteristics in GUI which were not
apparent in SCOPE and PRAMS.
SCOPE had the highest overall reported prevalence of
alcohol both pre-pregnancy (90% vs 77% in PRAMS) and
during pregnancy (82% vs 46% in PRAMS) (table 2).
GUI reported the lowest overall consumption of alcohol
use during pregnancy at 20%. SCOPE participants also
reported the highest overall consumption levels both prepregnancy and during pregnancy, and the highest binge
consumption before (59%) and during pregnancy
(45%). By the second trimester, reported prevalence and
reported consumption levels in SCOPE (29%) were
almost equal to PRAMS (31%). Examining changes
between the first and second trimesters, SCOPE alcohol
prevalence dropped from 82% to 29% consumption
between the first and second trimesters, although
PRAMS and GUI alcohol consumption stayed relatively
constant across all three trimesters at 30% in PRAMS and
10–15% in GUI. Additionally, among the SCOPE participants who continued to drink in the second trimester,
there were also substantial reductions in the levels of
drinking (70% drinking greater than 1–2 units/week in
the first trimester compared with 2% in the second
trimester).
Table 3 shows the characteristics associated with
alcohol consumption in each cohort. Compared with
Caucasian ethnicities, non-Caucasian women in all
cohorts were less likely to drink alcohol during pregnancy. Smoking was related to greater risk of consuming
alcohol during pregnancy in all three cohorts (RR range
from 1.17 to 1.50 for the three cohorts). Younger age
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

was related to lower risk of alcohol use in GUI, and
women aged greater than 39 years were more likely to
drink alcohol during pregnancy compared with women
aged 30–39 years; with evidence of a linear association,
overall, between age and gestational alcohol use
( p value for trend <0.05) in GUI. Having a second-level
education, being multiparous, and having a BMI >30
were related to lower risk of alcohol use during pregnancy in GUI. In SCOPE, single women were more
likely to drink alcohol during pregnancy. In relation to
outcomes commonly examined in relation to the effects
of gestational alcohol use, delivery of a low birth weight
infant was not associated with alcohol use in SCOPE;
however, in both retrospective cohorts, we found evidence that women who delivered low birth weight
infants were less likely to drink alcohol (albeit with CIs
spanning the null). For preterm birth, we did not find
strong evidence of an association with alcohol use in any
of the three cohorts.
Table 4 shows the distribution of alcohol use across
each of the four participating countries in SCOPE where
log linear binomial regression was used to examine the
characteristics associated with alcohol consumption in
each cohort adjusted for other variables in the table.
Reported alcohol use before and during pregnancy was
high in all centres (>40%), but prevalence and quantity
of consumption varied substantially by SCOPE centre
( p<0.05 for differences in all indices of pre-pregnancy
and early pregnancy alcohol consumption). Ireland had
the highest prevalence of any alcohol consumption prepregnancy (90%) and during pregnancy (82%), and the
highest reported binge consumption before (59%) and
during (45%) pregnancy. Reported alcohol consumption dropped substantially for all countries in the second
trimester as did reported binge consumption. In multivariate log linear binomial regression, factors associated
with alcohol use consistently in each SCOPE centre were
smoking during pregnancy (all countries) and ethnicity
(Ireland, the UK and New Zealand). Other factors that
were related to alcohol use but less consistently so, were
age, marital status and education (New Zealand Centre
only) (table 5).

DISCUSSION
Our findings show a high prevalence of alcohol use
during pregnancy (ranging from 20% to 80% in
Ireland), from 40% upwards in the UK, Australia and
New Zealand, and high levels of binge drinking during
pregnancy (in excess of 45% in the Irish centre of the
SCOPE cohort). These findings illustrate low adherence
to alcohol guidelines advising complete abstinence from
alcohol during pregnancy in Ireland,1 New Zealand2
and Australia, and NICE guidelines in the UK advising
consumption of no more than 1–2 units once or twice
per week.5 We found that this high prevalence was, in
general, pervasive across all social groups, and of the
predictors of alcohol consumption examined, smoking
5

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Table 2 Prevalence of alcohol consumption in GUI (2008, 2009), SCOPE Ireland (2008–2011) and PRAMS Ireland (2012)

Pre-pregnancy alcohol consumption
Non-drinkers pre-pregnancy
Severity of consumption (units/week)*
1–2
3–7
8–14
>14
Median (IQR)
Pre-pregnancy binging
Any alcohol in pregnancy
Non-drinkers in pregnancy
Binge (any in pregnancy)
First trimester alcohol consumption
Non-drinkers in first trimester
Severity of consumption (units/week)*
1–2
3–7
8–14
>14
Median (IQR)
Binge first trimester (yes)
Second trimester alcohol consumption
Non-drinkers in second trimester
Severity of consumption (units/week)*
1–2
3–7
8–14
>14
Median (IQR)
Binge second trimester (yes)
Third trimester alcohol consumption
Non-drinkers in third trimester
Severity of consumption (units/week)*
1–2
3–7
8–14
>14
Median (IQR)
Binge third trimester (yes)

GUI
n=10 953
n (%)

SCOPE Ireland
n=1766
n (%)

PRAMS
n=718
n (%)

Not recorded
Not recorded

1586 (90)
180 (10)

545 (77)
173 (23)

Not recorded
Not recorded
Not recorded
Not recorded
Not recorded
Not recorded
2198 (20)
8755 (80)
Not recorded
1127 (11)
9826 (89)

287 (18)
602 (38)
451 (28)
247 (16)
6 (3, 11)
1044 (59)
1444 (82)
322 (18)
795 (45)
1415 (80)
351 (20)

168 (43)
96 (24)
73 (19)
58 (15)
4 (1, 10)
134 (24)
325 (46)
383 (54)
23 (4)
211 (30)
507 (70)

572 (54)
332 (31)
117 (11)
41 (4)
2 (2, 2)
Not recorded
1585 (15)
9368 (85)

424 (30)
600 (42)
266 (19)
125 (9)
4 (2, 7.5)
795 (45)
500 (29)
1266 (71)

142 (85)
11 (7)
8 (5)
7 (4)
1 (1, 2)
21 (3)
216 (31)
502 (69)

1006 (66)
367 (25)
93 (6)
23 (2)
1 (1, 2)
Not recorded
1559 (14)
9394 (84)

486 (98)
11 (2)
1 (0.2)
0
0.5 (0.3, 1.0)
7 (0.4)
Not recorded
No recorded

153 (91)
10 (6)
5 (3)
1 (1)
1 (1, 1)
4 (1)
225 (32)
493 (68)

1016 (70)
341 (23)
78 (5)
21 (1)
1 (1, 2)
Not recorded

Not
Not
Not
Not
Not
Not

161 (90)
13 (7)
4 (2)
1 (1)
1 (1, 1)
6 (1)

recorded
recorded
recorded
recorded
recorded
recorded

*Note that severity of alcohol consumption only refers to women who consumed alcohol during pregnancy.
GUI, Growing up in Ireland; PRAMS, Pregnancy Risk Assessment Monitoring System; SCOPE, Screening for Pregnancy Endpoints.

was the only consistent predictor of alcohol use across
all cohorts and countries examined.
To the best of our knowledge, this is the first crosscohort comparison of the prevalence and predictors of
alcohol use during pregnancy. Our study goes beyond
measurement of alcohol use during pregnancy with just
one cohort or one measurement method, but examines
prevalence and predictors using different measurement
techniques in the same population. It also examines variation in prevalence keeping measurement constant
across different settings. The study had a large sample
size of almost 18 000 women. We were able to examine
prevalence using different modes of administration
6

(anonymised self-administered postal survey in PRAMS,
trained government interview in GUI, antenatal midwifecollected data in SCOPE) and timing of administration
(2–9 months postpartum in PRAMS, 9–12 months postpartum in GUI, and in the second trimester of pregnancy
in SCOPE). However, as we used self-reported alcohol
consumption data, reporting and recall biases may exist,
and where the true estimate lies (ranging from 20% in
GUI to 80% in SCOPE) is unclear. Our findings of
reduced alcohol consumption in women who had low
birth weight infants in both the retrospective studies may
suggest differential recall bias among women with
adverse birth outcomes, since similar evidence was not
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

 Open Access
Table 3 Log linear binomial regression for risk of alcohol during pregnancy
GUI
n=10 953
Adjusted RR
(95% CI)
Age (years)
<20
0.48 (0.30 to 0.77)
20–24
0.56 (0.46 to 0.68)
25–29
0.69 (0.62 to 0.78)
30–39
Reference
>40
1.18 (1.04 to 1.35)
Education*
Secondary
0.65 (0.60 to 0.72)
Tertiary
Reference
Ethnicity
Caucasian
Reference
Other
0.27 (0.19 to 0.37)
Marital status
Married
Reference
Single
1.05 (0.96 to 1.17)
Parity
0
Reference
1+
0.90 (0.83 to 0.98)
Smoking
Yes
1.50 (1.36 to 1.65)
No
Reference
BMI (kg/m2)
<18.5
1.01 (0.79 to 1.29)
18.5–24.99
0.98 (0.90 to 1.07)
25.0–29.9
Reference
>30
0.84 (0.74 to 0.94)
Low birth weight (<2500 g)
No
Reference
Yes
0.76 (0.60 to 0.96)
Preterm birth (<37 weeks gestation)
No
Reference
Yes
0.91 (0.74 to 1.12)

SCOPE Ireland
n=1766
Adjusted RR
(95% CI)

PRAMS
n=718
Adjusted RR
(95% CI)

0.92 (0.85 to 1.00)
0.84 (0.71 to 0.99)
0.95 (0.91 to 1.00)
Reference
0.86 (0.66 to 1.10)

1.31 (0.42 to 4.14)
0.26 (0.09 to 0.77)
0.84 (0.66 to 1.08)
Reference
0.97 (0.67 to 1.39)

0.94 (0.88 to 1.01)
Reference

0.81 (0.62 to 1.07)
Reference

Reference
0.34 (0.20 to 0.56)

Reference
0.31 (0.11 to 0.88)

Reference
1.09 (1.02 to 1.17)

Reference
0.98 (0.65 to 1.47)

–
–

Reference
1.02 (0.86 to 1.21)

1.17 (1.12 to 1.22)
Reference

1.42 (1.18 to 1.70)
Reference

1.06 (0.86 to 1.30)
1.02 (0.97 to 1.07)
Reference
0.96 (0.89 to 1.04)

0.80 (0.46 to 1.41)
0.96 (0.78 to 1.18)
Reference
0.89 (0.63 to 1.27)

Reference
1.01 (0.89 to 1.14)

Reference
0.66 (0.36 to 1.22)

Reference
0.94 (0.83 to 1.07)

Reference
0.97 (0.56 to 1.66)

Log linear binomial regression was used to examine the characteristics associated with alcohol consumption in each cohort and adjusted for
all variables in table.
*Secondary includes all education up to university or post school institutions. Tertiary includes any tertiary education at a university or other
post school institution.
BMI, body mass index; GUI, Growing up in Ireland; PRAMS, Pregnancy Risk Assessment Monitoring System; SCOPE, Screening for
Pregnancy Endpoints.

found in the prospective SCOPE cohort where data was
collected concurrently before women knew the outcome
of their pregnancy. Estimates of prevalence may vary
across the studies, in part, due to methodological differences in the assessment of alcohol related to the nature,
content and timing of questions. The interaction of these
methodological differences with a participant’s desire to
report in a socially desirable way may also explain variation in reporting across studies. For example, in the GUI
cohort, women may have under-reported to a greater
extent due to the influence of social desirability in
the presence of a trained government interviewer. This
contrasts with potentially better reporting of alcohol consumption in the anonymised PRAMS postal questionnaire. Therefore, variation in prevalence across the
cohorts is likely to be driven by sociodemographic
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

differences in the cohorts which influence true consumption levels, as well as measurement and reporting differences across the studies. Additionally, we have only
included live born babies in our analysis and thus, there
is a possibility that we have excluded women with the
heaviest drinking patterns, since failure to give birth to a
baby could have resulted from heavy drinking; for
example, miscarriage occurring due to early pregnancy
chronic alcohol use or binge drinking. Participants in
our studies may also be more advantaged than the
general population and thus, the generalisability of our
findings to all pregnancies or more diverse populations
may be reduced. Nonetheless, the cross-cohort comparison improves upon previously published single cohort
analyses, since it shows gestational alcohol use to be
prevalent and socially pervasive during pregnancy, as
7

 Open Access
Table 4 Comparison of alcohol use in SCOPE Centre’s

Pre-pregnancy alcohol consumption
Non-drinkers pre-pregnancy
Severity of consumption (units/week)†
1–2
3–7
8–14
>14
Median (IQR)
Pre-pregnancy binging
Any alcohol in pregnancy
Non-drinkers in pregnancy
Binge (any in pregnancy)
First trimester alcohol consumption
Non-drinking in first trimester
Severity of consumption (units/week)†
1–2
3–7
8–14
>14
Binge first trimester
Median (IQR)
Second trimester alcohol consumption
Non-drinking in second trimester
Severity of consumption (units/week)†
1–2
3–7
8–14
>14
Binge second trimester
Median (IQR)

Total
n=5573

New Zealand
n=2006

Ireland
n=1766

Australia
n=1150

UK*
n=651

4319 (77)
1254 (23)

1552 (77)
454 (23)

1586 (90)
180 (10)

539 (53)
611 (47)

540 (83)
111 (17)

<0.001

1126 (26)
1674 (39)
963 (22)
528 (12)
5 (2, 10)
1741 (31)
3482 (63)
2091 (37)
1282 (23)
3370 (60)
2203 (40)

503 (32)
698 (45)
253 (16)
98 (6)
4 (2, 7)
337 (17)
1107 (56)
899 (44)
167 (9)
1063 (53)
943 (47)

287 (18)
602 (38)
451 (28)
246 (16)
6 (3, 11)
1044 (59)
1444 (82)
322 (18)
795 (45)
1415 (80)
171 (20)

232 (38)
211 (34)
94 (15)
76 (12)
4 (1, 8)
123 (11)
459 (40)
691 (60)
113 (10)
440 (38)
710 (62)

104 (19)
163 (30)
165 (31)
108 (20)
7.5 (3, 13)
247 (38)
476 (75)
175 (25)
207 (33)
451 (69)
200 (61)

<0.001

1078 (32)
1372 (41)
624 (19)
296 (9)
1279 (23)
4 (2, 8)
1018 (19)
4555 (81)

361 (34)
463 (44)
175 (16)
65 (6)
167 (8)
4 (2, 7)
232 (12)
1774 (88)

424 (30)
600 (42)
266 (19)
125 (9)
795 (45)
4 (2, 7.5)
500 (29)
1266 (71)

142 (32)
158 (36)
80 (18)
60 (14)
111 (10)
5 (2, 10)
73 (7)
1077 (83)

151 (34)
151 (34)
103 (23)
46 (10)
206 (32)
4 (1.9, 9)
213 (34)
438 (66)

976 (97)
30 (3)
3 (0.3)
0
18 (0.4)
0.5 (0.3, 1)

220 (97)
7 (3)
0
0
2 (0.1)
0.5 (0.3, 1)

486 (98)
11 (2)
1 (0.2)
0
7 (0.4)
0.5 (0.3, 1)

68 (93)
4 (5)
1 (1)
0
6 (1)
0.5 (0.1, 1)

202 (96)
8 (4)
1 (0.5)
0
3 (1)
0.8 (0.5, 1.5)

p Value

<0.001
<0.001
<0.001
<0.001
<0.001

<0.001

<0.001
0.020
<0.001

0.3

0.2
<0.001

All data are N (%) unless otherwise stated. Median difference between centres tested using Kruskall-Wallis test. All other differences tested
with χ2 test for categorical variables.
*London, Manchester, Leeds.
†Note that severity of alcohol consumption only refers to women who consumed alcohol during pregnancy.
IQR, interquartile range; SCOPE, Screening for Pregnancy Endpoints.

measured by various measurement methods and in different settings. Second, across different studies and settings,
maternal smoking is a strong and consistent predictor of
alcohol consumption in pregnancy. Additionally, from a
methodological perspective, the analysis points to the
need for an agreed convention by which to measure gestational alcohol use to avoid substantial variation and heterogeneity in estimates and predictors of gestational
alcohol use in future studies.
Our findings of a range of gestational alcohol use from
20 to 80% are largely consistent with studies of similar
design for each cohort, respectively. In general, prospective ascertainment of exposure has been shown to be
more accurate than retrospective reporting where it has
been suggested that postpartum drinking levels and
poorer memory after the fact could influence reporting.17 In the prospective SCOPE study, the high rates of
pre-pregnancy and gestational alcohol consumption that
were observed in Ireland are compatible with estimates
from another large contemporary prospectively recruited
8

urban Irish cohort (n=65 000) which had a similar prospective design but with both nulliparous and multiparous participants.18 However, GUI estimates are likely to
substantially underestimate gestational alcohol consumption, especially when compared with 37% alcohol prevalence in the UK MCS, a cohort of almost identical design
where exposure was measured 9 months postpartum.6
Potential reasons why GUI and MCS estimates are not
compatible include differences in interviewing techniques and administration of surveys which would easily
influence reporting of socially undesirable behaviours
such as gestational alcohol use. Alternately, the retrospective PRAMS estimate of alcohol consumption of
almost 50% in pregnancy is comparable with estimates
from a number of large European cohorts including
Generation R,19 the Danish National Birth cohort,20
MCS6 and another recent prospective cohort from Leeds
in the UK.21 This suggests that the retrospective component in itself may not always result in an underestimation
of alcohol use. Throughout much of the literature, it is
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

 Open Access
Table 5 Log linear binomial regression for risk of alcohol consumption during pregnancy in SCOPE
New Zealand
n=2006
Adjusted RR (95% CI)
Age (years)
<20
0.78 (0.66 to 0.93)
20–24
0.74 (0.56 to 0.97)
25–29
0.83 (0.76 to 0.91)
30–39
Reference
>40
0.71 (0.52 to 0.98)
Education†
Secondary
0.84 (0.74 to 0.96)
Tertiary
Reference
Ethnicity
Caucasian
Reference
Other
0.67 (0.58 to 0.78)
Marital status
Married
Reference
Single
1.22 (1.02 to 1.46)
Smoking
Yes
1.50 (1.36 to 1.66)
No
Reference
BMI (kg/m2)
<18.5
0.88 (0.55 to 1.41)
18.5–24.99
Reference
25.0–29.9
1.01 (0.93 to 1.10)
>30
0.86 (0.75 to 1.00)
Low birth weight (<2500 g)
No
Reference
Yes
0.94 (0.76 to 1.18)
Preterm birth (<37 weeks gestation)
No
Reference
Yes
0.81 (0.65 to 1.00)

Ireland
n=1766
Adjusted RR (95% CI)

Australia
n=1150
Adjusted RR (95% CI)

UK*
n=651
Adjusted RR (95% CI)

0.92 (0.85 to 1.00)
0.84 (0.71 to 0.99)
0.95 (0.91 to 1.00)
Reference
0.86 (0.66 to 1.10)

0.94 (0.75 to 1.17)
0.90 (0.70 to 1.16)
1.03 (0.81 to 1.30)
Reference
1.33 (0.63 to 2.84)

1.02 (0.90 to 1.16)
0.86 (0.69 to 1.07)
0.93 (0.84 to 1.03)
Reference
0.77 (0.45 to 1.33)

0.94 (0.88 to 1.01)
Reference

0.96 (0.82 to 1.11)
Reference

0.93 (0.79 to 1.09)
Reference

Reference
0.34 (0.20 to 0.56)

Reference
0.77 (0.58 to 1.03)

Reference
0.57 (0.46 to 0.71)

Reference
1.09 (1.02 to 1.17)

Reference
1.07 (0.89 to 1.29)

Reference
1.08 (0.93 to 1.26)

1.17 (1.12 to 1.22)
Reference

1.82 (1.57 to 2.11)
Reference

1.15 (1.05 to 1.27)
Reference

1.06 (0.86 to 1.30)
Reference
1.02 (0.97 to 1.07)
0.96 (0.89 to 1.04)

0.76 (0.47 to 1.22)
Reference
1.18 (1.00 to 1.38)
0.84 (0.70 to 1.01)

0.67 (0.31 to 1.44)
Reference
0.98 (0.88 to 1.08)
0.85 (0.73 to 1.00)

Reference
1.01 (0.89 to 1.14)

Reference
1.29 (0.88 to 1.89)

Reference
1.22 (0.86 to 1.73)

Reference
0.94 (0.83 to 1.07)

Reference
1.02 (0.73 to 1.42)

Reference
1.08 (0.79 to 1.49)

Log linear binomial regression was used to examine the characteristics associated with alcohol consumption in each cohort and adjusted for
all variables in table.
*London, Manchester, Leeds.
†Secondary includes all education up to university or post school institutions. Tertiary includes any tertiary education at a university or other
post school institution.
BMI, body mass index; SCOPE, Screening for Pregnancy Endpoints.

widely shown and accepted that face-to-face interviews
are often the ‘gold standard’ in epidemiological research.
However, in relation to more subjective issues which
could be biased by social desirability, self-administered
questionnaires may elicit better quality data.22 In our
cross-cohort comparison, estimates of alcohol prevalence
in the face-to-face GUI survey were considerably lower
than in PRAMS, a finding which would support the superiority of self-administered questionnaires in measuring
more subjective issues such as alcohol use. However, since
reporting of other socially undesirable behaviours during
the perinatal period in GUI was high (eg, 18% of
smoking in pregnancy), it is possible that low reporting
of alcohol prevalence in GUI could be explained by true
population differences in prevalence of alcohol use in
pregnancy. Finally, our results for other SCOPE centres,
such as the UK, are higher than some British birth
cohorts,6 7 but generally consistent with the high prevalence reported in other large studies, such as ALSPAC.7
O’Keeffe LM, et al. BMJ Open 2015;5:e006323. doi:10.1136/bmjopen-2014-006323

SCOPE Australia and New Zealand estimates also appear
to be reasonably consistent with some previous data in
the region.23–26
The findings of this study have direct application to
policy and practice. Alcohol use during pregnancy is
highly prevalent, and evidence from this cross-cohort
and cross-country comparison shows that gestational
alcohol exposure may occur in over 75% of pregnancies
in the UK and Ireland. Although low proportions of
women engaged in heavy drinking, the adverse consequences of heavy alcohol consumption during pregnancy on birth outcomes, long-term gross motor
function,27 and social, cognitive, emotional and behavioural outcomes28 in offspring make heavy gestational
alcohol consumption a high public health priority.
Additionally, since most women who consume alcohol
do so at lower levels where the offspring growth29 and
development effects are less well understood,30 the widespread consumption of even low levels of alcohol during
9

 Open Access
pregnancy is a significant public health concern. As we
do not find compelling evidence that alcohol use is
more prevalent in any particular sociodemographic
group, for example, in single or less well educated
women which were also shown in a recent systematic
review to be inconsistently related to alcohol use during
pregnancy,31 healthcare professionals should continue
to advise all pregnant women to abstain from alcohol
during pregnancy in line with best practice clinical care
guidelines, irrespective of professionally perceived risk of
exposure. Given evidence of higher risk of drinking
during pregnancy among smokers which was consistent
across cohorts and within countries examined, and
which is also consistent with recent evidence of
increased drinking among smokers in other cohorts,32–
34
dual targeting of smoking and alcohol consumption
should potentially be increased and delivered routinely
upon a woman’s indication of either behaviour during
pregnancy. New policy and interventions are also
required to reduce alcohol prevalence both prior to and
during pregnancy.
This cross-cohort comparison highlights the urgent
need for a biological marker of gestational alcohol use,
since it is difficult to estimate to what extent estimates and
their predictors are plausible even in more robust study
designs (prospective measurement being the most superior), and when data is analysed in a comparative design
such as ours. Additionally, this research highlights the
need for a clear convention and standard method of measurement of alcohol use across observational studies which
minimises heterogeneity in measurement, insofar as is
possible using self-reported measurement of socially
undesirable behaviours. Population differences in actual
alcohol consumption are a plausible reason for variation
in prevalence. However, variation in measurement
methods may also explain differing prevalence and predictors, such as differences in interviewing techniques of
SCOPE midwives across centres. Another potential reason
for variation in reporting, or indeed actual alcohol use,
may include variation in professional and patient attitudes
to the acceptability of alcohol consumption during pregnancy, such that propensity to report alcohol use or
consume alcohol during pregnancy would be easily influenced by a combination of measurement method, cultural
attitudes to alcohol and social desirability, thereby underscoring the need for objective measures of gestational
alcohol use.
Author affiliations
1
National Perinatal Epidemiology Centre, Cork University Maternity Hospital,
Wilton, Cork, Ireland
2
Department of Epidemiology and Public Health, University College Cork,
Cork, Ireland
3
The Irish Centre for Foetal and Neonatal Translational Research (INFANT),
University College Cork, Cork, Ireland
4
Department of Obstetrics and Gynecology, University College Cork, Cork,
Ireland
5
Division of Women’s Health, Women’s Health Academic Centre, King’s
College London, and King’s Health Partners, London, UK

10

6

Department of Obstetrics and Gynaecology, Faculty of Medical and Health
Sciences, South Auckland Clinical School, University of Auckland, Auckland,
New Zealand
7
National Centre for Growth & Development and Maternal and Fetal Health,
Liggins Institute, University of Auckland, Auckland District Health Board and
Counties Manukau District Health Board, Auckland, New Zealand
8
Women’s and Children’s Division Lyell McEwin Hospital, University of
Adelaide, Adelaide, South Australia
9
St James University Hospital, Leeds, UK
10
Department of Obstetrics and Gynaecology, Faculty of Medical and Health
Sciences, University of Auckland, Auckland, New Zealand
Contributors LMO’K had the original idea for the study, wrote the first draft of
the article, applied critical revisions to the article based on other coauthor
recommendations, and approved the final version for publication. PMK, FM
and ASK conceptualised the design of the study with other coauthors,
assisted in interpretation of the data, reviewed and revised the manuscript and
approved the final version for publication. RAG conceptualised the design of
the study, assisted in the interpretation of the data, contributed to critical
revisions of the article, and approved the final version for publication. RAN,
LP, LMEM, PNB, GAD, JJW and RT conceptualised the design of the study,
contributed to critical revisions of the article and approved the final version
for publication. LCK supervised the write up of the manuscript, contributed to
critical revisions of the article and approved the final version for publication.
Funding The New Zealand SCOPE study was funded by the New Enterprise
Research Fund, Foundation for Research Science and Technology; Health
Research Council (04/198); Evelyn Bond Fund, Auckland District Health Board
Charitable Trust. The Australian SCOPE study was funded by the Premier’s
Science and Research Fund, South Australian Government (http://www.dfeest.
sa.gov.au/science-research/premiers-research-and-industry-fund). The Irish
SCOPE study was funded by the Health Research Board of Ireland (CSA/2007/2)
(http://www.hrb.ie). The UK SCOPE study was funded by National Health
Service NEAT Grant (Neat Grant FSD025), Biotechnology and Biological
Sciences Research council (http://www.bbsrc.ac.uk/funding) (GT084) and
University of Manchester Proof of Concept Funding (University of
Manchester); Guy’s and St Thomas’ Charity (King’s College London) and
Tommy’s charity (http://www.tommys.org/) (King’s College London and
University of Manchester); and Cerebra UK (http://www.cerebra.org.uk)
(University of Leeds). The Growing Up in Ireland study is funded by the
Government of Ireland through the Department of Children and Youth Affairs
in association with the Department of Social Protection and the Central
Statistics Office. PRAMS was conducted with both the administrative and
financial support of the National Perinatal Epidemiology Centre, Cork and staff
of Cork University Maternity Hospital and with assistance from Health
Research Board (HRB) in Ireland (grant no PHD/2007/16).
Competing interests None declared.
Ethics approval Ethical approval for GUI was provided by an independent
research ethics committee convened by the Department of Health and
Children in Ireland especially for the GUI study. Ethical approval for PRAMS
was received from the Clinical Research Ethics Committee of the Cork
Teaching Hospitals. Ethical approval for SCOPE was obtained from local
ethics committees (New Zealand AKX/02/00/364, Australia REC 1712/5/2008,
London and Manchester 06/MRE01/98 and Cork ECM5 (10)05/02/08).
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement No additional data are available.
Open Access This is an Open Access article distributed in accordance with
the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work noncommercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See: http://
creativecommons.org/licenses/by-nc/4.0/

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