The Neonatal and Obstetric Risk Assessment (NORA) pregnancy cohort study was set up to assess clinical, biochemical and biophysical markers for risk assessment and prediction of the outcomes early in pregnancy. A total of 3271 patients who were in KK Women’s and Children’s Hospital between September 2010 and October 2014 were screened and 1013 patients consented to participate in the study. Women were followed at 18 to 22 weeks, 28 to 32 weeks and 34 weeks and above, till their postnatal discharge from the hospital. Finally, 926 patients remained for studying the outcome. In NORA study, we established locally derived and gestational age-specific reference intervals for the five thyroid hormone parameters. Higher serum progesterone levels at 28–32 weeks of pregnancy were observed in women who had preterm deliveries compared with women with term deliveries in the cohort. We also found that extracellular vesicle (EV) biomarkers enhanced the predictive robustness of an existing pre-eclampsia (PE) biomarker sufficiently to justify PE screening in a low-risk general obstetric population. We plan to further conduct a range of serial assessments from the biosamples which will provide a comprehensive and valuable information of the dynamics of maternal conditions and fetal development during pregnancy.

1. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
IJGOR
Neonatal and Obstetric Risk Assessment (NORA) Pregnancy
Cohort Study in Singapore
Qiu Ju Ng1, Jun Zhang2, Fei Dai3, Mor Jack Ng4, Nurul Syaza Razali5, Nyo Mie Win6, Bernard
Chern7, George SH Yeo8,10, *Kok Hian Tan9,10
1,2,3,4,5,6,7,8,9
Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah
Road, 229899, Singapore
10
Department of Maternal and Fetal Medicine, KK Women’s and Children’s Hospital, 100 Bukit Timah Road, 229899,
Singapore
The Neonatal and Obstetric Risk Assessment (NORA) pregnancy cohort study was set up to
assess clinical, biochemical and biophysical markers for risk assessment and prediction of the
outcomes early in pregnancy. A total of 3271 patients who were in KK Women’s and Children’s
Hospital between September 2010 and October 2014 were screened and 1013 patients consented
to participate in the study. Women were followed at 18 to 22 weeks, 28 to 32 weeks and 34 weeks
and above, till their postnatal discharge from the hospital. Finally, 926 patients remained for
studying the outcome. In NORA study, we established locally derived and gestational age-specific
reference intervals for the five thyroid hormone parameters. Higher serum progesterone levels at
28–32 weeks of pregnancy were observed in women who had preterm deliveries compared with
women with term deliveries in the cohort. We also found that extracellular vesicle (EV) biomarkers
enhanced the predictive robustness of an existing pre-eclampsia (PE) biomarker sufficiently to
justify PE screening in a low-risk general obstetric population. We plan to further conduct a range
of serial assessments from the biosamples which will provide a comprehensive and valuable
information of the dynamics of maternal conditions and fetal development during pregnancy.
Keywords: Cohort profile, neonatal and obstetric risks, adverse pregnancy outcomes
INTRODUCTION
The vast majority of pregnancies result in a smooth
delivery with both healthy mother and baby. However, this
is not always the case, and about 15-20% of pregnancies
are high-risk pregnancies which may suffer from adverse
maternal and/or fetal outcomes. These high-risk
pregnancies require multidisciplinary care and close
monitoring and hence, the management of such patients
is often resource intensive and has a significant impact on
the economics of healthcare delivery. In addition, as the
median age of first-time mother rises in many parts of the
world including Singapore, due to delayed childbearing,
this would increase the proportion of high-risk pregnancies
as advanced maternal age has been associated with
adverse pregnancy outcomes (Mills and Lavender, 2011).
Preterm birth is the single largest and most commonly
cited adverse outcome in pregnancy, followed by intra-
uterine growth retardation and pre-eclampsia (Lams et al.,
2008; Lamont, 2003; Gagnon and Wilson, 2008). Reported
incidence for preterm births (less than 37 weeks of
gestation) ranges from 5 – 13%, and it is believed to be on
the rise (Goldenberg et al., 2008; Tribe, 2007). In our
hospital, the combined incidence ranges from 12 % to 18%
for adverse pregnancy outcomes (9% attributed by
preterm births, 3 – 4.5 % attributed by intra-uterine growth
restriction and about 3 – 5% pre-eclampsia) based on our
2008 delivery statistics (KKH Data Warehouse, 2008). It is
estimated that these conditions in combination may
account for over 70% of adverse pregnancy outcomes.
Unfortunately, the causes of the pregnancy complications
remain largely unknown. And clinical outcomes associated
with these conditions have not improved much, particularly
due to the poor understanding of the pathophysiology and
inability to prevent or intervene early in the course of the
pregnancy.
*Corresponding author: Prof Kok Hian Tan, Perinatal
Epidemiology and Audit Unit, Department of Maternal and
Fetal Medicine, KK Women’s and Children’s Hospital, 100
Bukit Timah Road, Singapore 229899.
Email: tan.kok.hian@singhealth.com.sg
Tel: (65) 6394 1319; Fax: (65) 6394 2241
International Journal of Gynecology and Obstetrics Research
Vol. 4(1), pp. 031-037, October, 2018. © www.premierpublishers.org ISSN: 1407-8019
x
Study Profile

2. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
Tan et al. 032
Angiogenic biomarkers, considered to be the markers of
placental function, have the potential to identify the
subsequent risk of these adverse outcomes early in
pregnancy. The pre-symptomatic levels of angiogenic
biomarkers appear to be linked to the severity and timing
of onset of preeclampsia (Grill et al., 2009). Some studies
have suggested that placental growth factor (PlGF) levels
are already significantly lower in the first trimester in
women who develop preeclampsia (Romero et al., 2008).
There has been intensive research into the use of
biochemical markers such as soluble fms-like tyrosine
kinase-1 (sFlt-1) and PlGF for early identification of pre-
eclampsia to reduce adverse outcomes and unnecessary
hospitalisations (Allen et al., 2014; Hund etal., 2014).
KK Women’s and Children’s Hospital (KKH) is the largest
maternity hospital in Singapore and is the main tertiary
referral centre for Paediatrics and Obstetrics and
Gynaecology. The Neonatal and Obstetric Risk
Assessment (NORA) cohort study was set up to target
pregnancy-related causes of adverse outcomes, with a
focus on evaluating the use of clinical, biochemical and
biophysical markers to predict the risks early enough in
pregnancy that some intervention may be implemented to
improve the chance of a healthy pregnancy outcome. The
primary objectives of the NORA study are: (1) to screen
factors that are associated with adverse pregnancy
outcomes; and (2) to develop a multi-factorial prediction
model to identify women in high risk for adverse outcomes
early in pregnancy.
COHORT DESCRIPTION
Participants
The study was conducted at KKH, which has an annual
delivery rate of about 12000 births, comprising
approximately 30 – 35% of national births. It is also the
main referral hospital for complicated pregnancies and
neonatal support, as it provides a full range of tertiary level
support. The study received an approval from the
Institutional Review Board before commencing recruitment
of participants and data collection.
The NORA study recruited pregnant women who had
viable, singleton pregnancies and were attending their first
antenatal visit, at less than 14 weeks of amenorrhoea in
KKH between September 2010 and October 2014. The
exclusion criteria were multiple gestation, chronic medical
conditions such as renal disease or systemic lupus
erythematosus and pregnancies complicated by
aneuploidy or fetal anomaly. Once potential participants
were identified, screening was done by the research
nurses to determine eligibility according to the study’s
inclusion. A written informed consent was obtained once
the participant has met all the inclusion and exclusion
criteria. A total of 3271 patients were screened and 1013
patients consented to participate in the study. Out of 1013
participants, 934 (92.2%) patients completed all 4
antenatal visits. As 8 participants did not deliver in our
institution, we studied the outcome of the remaining 926
(99.1%) patients (Figure 1).
Figure 1: Progress of the NORA study
Cohort follow-up
After consent, the participants were followed up till their
postnatal discharge from the hospital. At recruitment,
detailed interviews, a dating ultrasound scan and routine
antenatal blood collection were done. Subsequently, the
women were seen at 18 to 22 weeks, 28 to 32 weeks and
34 weeks and above (Table 1). The women were closely
followed up through their pregnancies and clinical and
laboratory data were collected prospectively. Following
delivery, detailed information on pregnancy complications,
labour and delivery and neonatal outcomes was collected
through medical chart review.
DATA COLLECTION
Table 1 describes the data collected at each visit for the
entire cohort. A detailed questionnaire was administered
to participants at recruitment (less than 14 weeks) to obtain
their demographics, personal medical and obstetric
history, socio-economic status and lifestyle. Follow-up
questionnaires were then administered at each
subsequent visit. Neonatal anthropometric assessments,
Apgar scores at 1 and 5 minutes were obtained. Quality of
sleep was assessed using the Pittsburgh Sleep Quality
Index (Buysse et al,. 1989). Maternal mental health was
gauged by the State_Trait Anxiety Inventory (Spielberger,
1983), Original Perceived Stress Scale (Cohen et al.,1983)
Roesch Questionnaire (Roesch et al., 2004) and
Edinburgh Postnatal Depression Scale (Cox et al.,1987) at
each visit.

3. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
Int. J. Gynecol. Obstet. Res. 033
Demographic and laboratory measurement
At each visit, maternal blood pressure, central aortic
systolic pressure (by non-invasive arterial pulse waveform
analysis), height and weight were measured. Ultrasound
and Doppler studies included fetal biometry, cervical
length, amniotic fluid, placental localization, uterine artery
and fetal Doppler studies.
A total of 15 ml blood sample was collected at each visit.
Serum, plasma and buffy coat samples were separated
and stored at -80° for subsequent analysis. A number of
hormones were measured, including thyroid hormones,
human chorionic gonadotrophin beta unit (βHCG),
pregnancy-associated plasma protein A (PAPP-A), sFlt-1,
PlGF, progesterone, prolactin, and cortisol at all visits.
Markers for preterm labour included speculum
examination for placental growth factor binding protein-1
(PIGFBP-1) assessment and high vaginal swab for
infection or colonization were done at 11 to 14 weeks and
at more than 34 weeks.
Patient and public involvement
The NORA pregnancy cohort study was developed based
to a significant extent on patients’ priorities and
experiences. Besides aiming to develop better risk
assessments to benefit patients, there has been strong
considerations for outcome measures based on patient
satisfaction and their experiences in pregnancy. Thus
sleep satisfaction and mental wellness outcome measures
were given priority and included in the study with the use
of various survey scales e.g. Pittsburgh Sleep Quality
Index, State_Trait Anxiety Inventory, Original Perceived
Stress Scale, Roesch Questionnaire on stress in
pregnancy and Edinburgh Postnatal Depression Scale at
each visit.
In the design of study schedule, patients’ feedbacks on
making it convenient for them to participate in the study
were taken into account. The study investigations were
arranged and performed at the specific 4 time-points when
they visited the hospital for clinical consultations. In
addition, in previous studies, the issue of adequate and fair
reimbursement for their transport fares was noted. In
NORA appropriate transport reimbursement were
undertaken. NORA results have been presented at public
forums in the hospital and also in community centers in
Singapore. It is expected there will be more sharing of the
results with the patients and public in the near future.
FINDINGS TO DATE
The cohort consisted of 470 (50.7%) Chinese, 250 (27.0%)
Malay, 100 (10.8%) Indian and the remaining 106 (11.4%)
were of other ethnicity. Table 2 describes the baseline
characteristics of the study population. The average age of
the cohort was 30.6 years; Chinese (31.1 years) and other
ethnicities (31.0 years) were a little older. Malays were
much less likely to attend university than other ethnicities
while Chinese had the lowest unemployment rate. Chinese
also had a substantially higher rate of unmarried status.
Overall, Malays had the lowest total monthly household
income while Chinese had the highest.
More than half of the study participants were nulliparous.
Chinese had the lowest body mass index (BMI) in early
pregnancy while Malays and Indians had a similar BMI.
The prevalence of chronic hypertension and preexisting
diabetes mellitus was 1.1% and 1.4%, respectively. Very
few women smoked (2.6%) or drank alcohol (1.2%) during
pregnancy. 8.4% of women reported exercise in
pregnancy.
The mean gestational age at birth was 38.7±1.5 weeks
with a preterm birth rate of 7.1%. The mean birthweight
was 3105±458 g with little variation among ethnic groups.
The rates of low birthweight (<2500 g) and macrosomia (
≥4000 g) were 7.3% and 1.8%, respectively. Incidence of
intrauterine growth restriction, defined as estimated fetal
weight or abdominal circumference < the 5th percentile
adjusting for gender and ethnicity, or birthweight < the 3rd
percentile, was 4.0%. Gestational hypertension and
preeclampsia occurred in 2.0% and 2.3% of women,
respectively. Glucose tolerance test was prescribed only
to high risk women. Approximately 40% of women had the
test, among whom 20.9% were diagnosed as gestational
diabetes. Malay appeared to have the lowest incidence
(12.3%) among the ethnic groups.
The NORA Cohort has established locally derived and
gestational age-specific reference intervals for the five
thyroid hormone parameters (Ho et al., 2017). Another
study tested if circulating extracellular vesicles (EVs) such
as cholera toxin B chain (CTB)- or annexin V (AV)-binding
EVs could enhance the predictability of existing
biomarkers (e.g. PlGF) for preeclampsia. We found that
EV biomarkers enhanced the predictive robustness of an
existing PE biomarker sufficiently to justify PE screening in
a low-risk general obstetric population (Tan et al., 2017).
In NORA study, higher serum proesterone levels at 28–32
weeks of pregnancy were observed in women who had
preterm deliveries compared with women with term
deliveries (Feng et al., 2018).
STRENGTHS AND LIMITATIONS
This is a prospective cohort study. Over 92% of women
completed all four follow-up visits. Although the
participation rate among the eligible women was less than
50%, the baseline characteristics of the participants were
similar to those of general obstetric population at the KK
Hospital (Roesch et al., 2004). Thus, our study population
is a good representation of the hospital population. We

4. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
Tan et al. 034
also conducted a wide range of assessments, repeated
multiple times during pregnancy. They provided a
comprehensive picture of the dynamics of maternal
conditions and fetal development during pregnancy.
However, several limitations of the current study are also
worth noting. First, women who chose to participate in the
study may differ from those who declined to participate.
Second, prescription or treatment bias may have altered
the natural progression to adverse pregnancy outcomes.
Finally, our study population may not represent the total
obstetric population in Singapore.
ACKNOWLEDGEMENTS
We would like to acknowledge and thank all healthcare
staff and patients who participate in the NORA cohort
study.
COLLABORATION
Currently, the data are not openly accessible by outside
investigators but any reasonable request can be sent to
the corresponding author and Principal Investigator, Dr.
Kok Hian Tan, for consideration of collaboration.
CONTRIBUTORSHIP STATEMENT
Kok Hian Tan was involved in the design conception of the
study. Mor Jack Ng, Nurul Syaza Razali and Nyo Mie Win
were involved in management and acquisition of data. Fei
Dai was involved in data analysis. Qiu Ju Ng and Jun
Zhang were involved in manuscript writing and
interpretation. Kok Hian Tan, Jun Zhang, George SH Yeo
and Bernard Chern were involved in manuscript revision.
All authors had read and approved the final manuscript.
FUNDING
The study was funded by the National Medical Research
Council (NMRC) Programme Project Grant
(NMRC/PPG/KKH/2010) and Integrated Platform for
Research in Advancing Metabolic Health Outcomes of
Women and Children (IPRAMHO/CGAug16C008).
CONFLICT OF INTEREST
None declared.
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Accepted 8 August 2018
Citation: Ng QJ, Zhang J, Dai F, Ng MJ, Razali NS, Win
NM, Chern B, Yeo GSH, Tan KH (2018). Neonatal and
Obstetric Risk Assessment (NORA) Pregnancy Cohort
Study in Singapore. International Journal of Gynecology
and Obstetrics Research, 4(1): 031-037.
Copyright: © 2018 Tan et al. This is an open-access
article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.
AUTHORS INFORMATION
1. Qiu Ju Ng , Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah Road,
Singapore 229899. Tel. (65) 96361842, Email: qiuju.ng@mohh.com.sg
2. Jun Zhang, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah Road,
Singapore 229899. Tel. (65) 86479759, Email: zhang.jun.jim@kkh.com.sg
3. Fei Dai, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah Road,
Singapore 229899. Tel. (65) 98911568, Email: dai.fei@kkh.com.sg
4. Mor Jack Ng, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah Road,
Singapore 229899. Tel. (65) 93866284, Email: ng.mor.jack@kkh.com.sg
5. Nurul Syaza Razali, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah
Road, Singapore 229899. Tel. (65) 96914593, Email: Nurul.Syaza@kkh.com.sg
6. Nyo Mie Win, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah Road,
Singapore 229899. Tel. (65) 91068022, Email: nyo.mie.win@kkh.com.sg
7. Bernard Chern, Department of Obstetrics and Gynaecology, KK Women’s and Children’s Hospital, 100 Bukit Timah
Road, Singapore 229899. Tel. (65) 92732233, Email: bernard.chern.s.m@singhealth.com.sg
8. George SH Yeo, Department of Obstetrics and Gynaecology/Maternal and Fetal Medicine, KK Women’s and Children’s
Hospital, 100 Bukit Timah Road, Singapore 229899. Tel. (65) 96774386 Email: dr.george.sh.yeo@gmail.com
9. Kok Hian Tan, Department of Obstetrics and Gynaecology/Maternal and Fetal Medicine, KK Women’s and Children’s
Hospital, 100 Bukit Timah Road, Singapore 229899. Tel. (65) 98375120, Email: tan.kok.hian@singhealth.com.sg

6. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
Tan et al. 036
APPENDIX
Table 1: NORA study data collection
NORA study visit
11-14
weeks
18-22
weeks
28-32
weeks
≥34
weeks
Delivery
Mother
Demographics and social
Age ●
Ethnic group ●
Marital status ●
Education and employment status ●
Lifestyle
Smoking status ● ● ● ●
Alcohol and drug use ● ● ● ●
Caffeinated drinks ● ● ● ●
Physical activity ● ● ● ●
Use of supplements ● ● ● ●
Height ● ● ● ●
Weight ● ● ● ●
Sleep quality ● ● ● ●
Health
Medical and Surgical history ●
Stress / anxiety / depression ● ● ● ●
Obstetrics history
Gravida, Parity ●
Personal history of preterm delivery/PIH1/ pre-
eclampsia/gestational diabetes mellitus
●
Family history of hypertension/preterm
delivery/diabetes
●
Type of pregnancy (spontaneous or assisted
reproductive techniques)
●
Maternity Data Set
Blood Pressure ● ● ● ● ●
Urine dipstick ● ● ● ●
Pulsewave analysis (BPro2 reading) ● ● ● ●
Haematological and clinical chemistry ● ● ● ●
Serum biomarkers ● ● ● ●
Ultrasound and Doppler studies ● ● ● ●
High vaginal swab for culture ● ●
Gestational age at delivery ●
Mode of delivery ●
Birth weight ●
Apgar scores ●
Placenta weight ●
Complications during delivery ●
1 PIH- Pregnancy-induced hypertension
2The BPro device analyses the radial pulse wave to generate a central aortic pressure, which acts as a measure of
arterial stiffness.

7. Neonatal and Obstetric Risk Assessment (NORA) Pregnancy Cohort Study in Singapore
Int. J. Gynecol. Obstet. Res. 037
Table 2: Maternal characteristics and perinatal outcome by races
Total
N=926
Chinese
N=470
Malay
N=250
Indian
N=100
Others
N=106
P
Maternal Characteristics
Age (years, mean±SD) 30.6±5.0 31.1±5.0 29.8±4.8 29.7±5.0 31.0±4.8 0.001
Education (%)
Secondary school or under 9.5 11.3 10.8 3.0 4.7 0.000
High school 25.5 17.9 38.4 32.3 22.6
Junior college 28.4 26.2 36.4 21.2 26.4
University or above 36.5 44.7 14.4 43.1 46.2
Occupation (%)
White-collar worker 67.6 71.9 65.6 66.0 55.2 0.017
Blue-collar worker 10.3 10.2 10.8 7.0 12.4
Unemployment 22.1 17.9 23.6 27.0 32.4
Marital status
Married 94.1 90.9 98.0 98.0 95.3 0.001
Single/Divorced/Widowed 5.9 9.1 2.0 2.0 4.7
Total monthly household income (S$, %)
< 3500 34.5 29.1 43.6 36.0 35.8 0.000
3500-5500 30.3 26.3 35.9 35.0 31.1
5501-8500 22.0 25.9 16.0 19.0 21.7
>8500 13.2 18.8 4.8 10.0 11.3
Parity
0 previous birth 54.1 57.4 50.8 50.0 50.9 0.229
1+ previous birth 45.9 42.6 49.2 50.0 49.1
1st trimester BMI (kg/m2, mean±SD) 24.2±4.7 23.0±4.1 25.7±5.0 25.6±4.7 24.3±4.7 0.000
Disease history
Chronic Hypertension (%) 1.1 1.3 0.0 2.0 1.9 0.078
Diabetes mellitus (%) 1.4 1.6 0.9 3.2 0.0 0.181
Smoking in pregnancy (%) 2.6 3.2 2.4 0.0 2.8 0.115
Drinking in pregnancy (%) 1.2 2.1 0.0 0.0 0.9 0.01
Exercise in pregnancy (%) 8.4 9.1 8.0 7.0 7.5 0.862
Perinatal outcome
Gestational age (weeks, mean±SD) 38.7±1.5 38.7±1.4 38.7±1.7 39.0±1.1 38.7±1.9 0.386
Preterm birth (<37 weeks, %) 7.1 7.5 7.2 6.1 5.7 0.899
Birth weight (g, mean±SD) 3105±458 3099±444 3091±487 3124±399 3146±499 0.723
Birth weight (g, %)
<2500 7.3 7.7 8.0 6.0 5.7 0.886
2500-3999 90.8 90.2 90.0 93.0 93.4
≥4000 1.8 2.1 2.0 1.0 0.9
Intrauterine growth restriction (%) 4.0 4.0 3.6 5.0 3.8 0.920
Gestational hypertension (%) 2.0 2.8 1.6 1.0 0.0 0.096
Pre-eclampsia (%) 2.3 2.2 3.2 2.0 1.0 0.609
Gestational diabetes (%)1 20.9 24.6 12.3 21.7 25.6 0.076
1Glucose tolerance test was only prescribed to high risk women, which accounted for approximaTely 40% of all pregnant
women.