Maternal sleep and small for gestational age infants in the Japan Environment and Children’s Study: a cohort study
Morokuma et al. BMC Res Notes
Maternal sleep and small for gestational age infants in the Japan Environment and Children's Study: a cohort study
Seiichi Morokuma 0 2
Mototsugu Shimokawa 1
Kiyoko Kato 2 6
Masafumi Sanefuji 2 5
Eiji Shibata 3 4
Mayumi Tsuji 8
Ayako Senju 4 7
Toshihiro Kawamoto 4 8
Koichi Kusuhara 4 7
Children's Study Group
0 Department of Obstetrics and Gynecology, Kyushu University Hospital, Kyushu University , 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582 , Japan
1 Department of Cancer Information Research, Clinical Research Institute, National Kyushu Cancer Center , Fukuoka , Japan
2 Research Center for Environmental and Developmental Medical Sciences, Kyushu University , Fukuoka , Japan
3 Department of Obstetrics and Gynecology, School of Medicine, University of Occupational and Environmental Health , Kitakyushu, Fukuoka , Japan
4 Japan Environment and Children's Study, UOEH Subunit Center, University of Occupational and Environmental Health , Kitakyushu, Fukuoka , Japan
5 Department of Pediatrics, Graduate School of Medical Sciences, Kyushu University , Fukuoka , Japan
6 Department of Obstetrics and Gynecology, Graduate School of Medical Sciences, Kyushu University , Fukuoka , Japan
7 Department of Pediatrics, School of Medicine, University of Occupational and Environmental Health , Kitakyushu , Japan
8 Department of Environmental Health, School of Medicine, University of Occupational and Environmental Health , Kitakyushu, Fukuoka , Japan
Objectives: Small for gestational age infants have an increased risk of immediate complications, short-term morbidity and mortality, and long-term neurologic and metabolic disorders in adulthood. Previous research has shown that reduced sleep duration is a risk factor for SGA birth. However, only a few studies have evaluated maternal sleep as a risk factor for SGA birth. In the present study, we investigated the relationship between the amount and quality of mothers' sleep and infants' birth weight. Results: This cohort study (n = 8631) used data from the Japan Environment and Children's Study, an ongoing cohort study that began in January 2011. Data on sleep status (sleep duration and one indicator of sleep quality) and potential confounding factors were recorded. A log-binomial regression model was used to estimate the risk of small for gestational age birth, and the results were expressed as risk ratios and their respective 95% confidence interval. No significant results were observed for sleep duration or tiredness upon waking. Neither the amount nor the quality of mothers' sleep was associated with the risk of small for gestational age birth.
Maternal sleep; Small for gestational age; Birth cohort
Small for gestational age (SGA) infants have an increased
risk of immediate complications, short-term morbidity
and mortality, and long-term neurologic and metabolic
disorders in adulthood [
] . SGA is defined as a birth
weight below the 10th percentile at any gestational age [
]. Although several risk factors for SGA have been
identified, some remain unknown. In our previous study, the
analysis of the Japan Environment and Children’s Study
(JECS) data set showed that neither severe nausea nor
vomiting in early pregnancy nor hyperemesis gravidarum
was associated with an increased risk for SGA birth [
One study showed that reduced sleep duration was a
risk factor for SGA [
]. However, only a few studies have
evaluated the role of maternal sleep in SGA birth. Thus,
in the present study, we investigated the relationship
between the amount and quality of mothers’ sleep and
infants’ birth weight using data from the JECS.
Data used in this study were obtained from the JECS, an
ongoing cohort study that was started in January 2011.
The JECS was designed to follow-up mothers using a
survey until their newborns reached the age of 13 years. Its
objective was to elucidate the effect of environmental
factors on children’s health. The detailed methodology has
been previously reported [
In brief, pregnant women were recruited during the
approximately 3-year recruitment period until March
2014. 15 study regions were selected throughout Japan.
We met with as many pregnant women as possible who
lived in the study area. One of the following recruitment
protocols was carried out: (1) recruitment at the time
of the first prenatal examination at participating health
care institutions, and/or (2) recruitment at local
government offices issuing the Mother–Child Health
Handbook, which is a complimentary official booklet that all
expecting mothers in Japan are given when they become
pregnant. The JECS was conducted after obtaining
written informed consent from all participants. However,
we excluded those who had reasons that made it
difficult for them to fill in the questionnaire in Japanese; for
instance, if an individual was traveling to her hometown
to deliver her baby, she could not participate in the
As of the end of 2011, 9646 participants had delivered
successfully. After excluding missing data and premature
birth, we analyzed the data of the remaining 8631 women
who had singleton, full-term (≥37 weeks, but <42 weeks)
pregnancies (Fig. 1 of the previous article [
present study is based on the dataset of jecs-ag-ai-20131008,
which was released in October 2013.
Follow-ups were done using self-administered
questionnaires, which were filled out during the first and
second trimesters of pregnancy and at 1 month after birth.
We obtained the medical data by transcribing medical
records which were updated during the first trimester, at
the time of delivery, and 1 month after birth. The
questionnaires collected data related to pregnancy history,
general medical history, and confounding and modifying
factors such as social and lifestyle factors. From the
transcribed medical data, we collected the birth weights and
other data related to pregnancy and childbirth, such as
gestational age, parity, and labor complications.
The sleep index was included in the questionnaire for
the second trimester. As a quantitative index of sleep, we
calculated “hours of sleep” as the time interval between
when a pregnant woman went to bed and got out of bed.
Duration of sleep was classified into five categories based
on a previous study among pregnant Japanese women
]. As a qualitative index of sleep, we used the answer
to the following question on the questionnaire based
on a national health investigation [
]: “How would you
rate your average mood upon waking over the previous
month?” Scores of 1, 2, 3, 4, and 5 represented extremely
bad, relatively bad, normal, relatively good, and extremely
good, respectively. Scores of 3, 4, and 5 were used as
references for 1 and 2.
The participants underwent ultrasonography during
their first trimester, and for women with a difference
of ≥7 days in their due date, as calculated from their last
menstrual period, we used the due date derived from
an ultrasound examination. Birth weights were
transcribed from medical records. SGA was defined as birth
weight <10th percentile of birth weight standards by
gestational age for Japanese neonates [
The covariates of maternal age, pre-pregnancy body
mass index (BMI), parity, smoking, hypertension, and
alcohol consumption were included in the
questionnaire for the first trimester. Covariates of education and
income were included in the questionnaire for the second
trimester. The covariate of maternal weight gain during
pregnancy was calculated based on information from
We assessed the relationships among hours of sleep,
tiredness upon waking and SGA birth in subjects who had
single, full-term births. A log-binomial regression model was
used to estimate crude risk, confounder-adjusted risk and
95% confidence interval (CI) for SGA birth. The following
potential factors were assessed for confounder adjusted
risk: maternal age, pre-pregnancy BMI, gestational age at
birth, smoking, hypertension, alcohol consumption, and
education. All statistical analyses were performed using
SAS version 9.3 (SAS Institute Inc., Cary, NC, USA).
The means of maternal age, gestational age at birth, and
birth weight were 30.6 ± 4.98 years, 39.0 ± 1.14 weeks,
and 3051 ± 369.85 g, respectively. Results of the
univariate analysis for birth weight, which accounted for
confounding background and social factors, are shown in a
table in the previous article [
SGA risk ratios for participants with pre-pregnancy
BMI < 18.5 kg/m2, who smoked, had hypertension, and
had weight gain of <7 kg during pregnancy were 1.58
(95% CI 1.32–1.90), 1.48 (95% CI 1.11–1.97), 1.73 (95%
CI 1.17–2.56), and 1.28 (95% CI 1.05–1.55),
respectively, indicating that the risk of SGA birth was slightly
elevated in these participants. When the pre-pregnancy
BMI was ≥25 kg/m2 and weight gain during pregnancy
was >12 kg, the SGA risk ratios were 0.60 (95% CI 0.43–
0.85) and 0.52 (95% CI 0.41–0.66), respectively,
indicating a slightly decreased risk for SGA birth.
Crude and adjusted risk ratios for the influence of sleep
on birth weight are shown in Table 1. No significant
results were observed for any sleep duration in our
investigation. In addition, sleep quality was not associated
with risk of SGA birth.
In the present study, neither sleep duration nor tiredness
upon waking was associated with risk of SGA birth.
Similar to other biologic variables, daily sleep duration in any
healthy adult population is normally distributed. The sleep
duration of pregnant Japanese women is also normally
distributed, and the most common sleep duration is
7–7.9 h [
]. According to a previous national health
investigation, 20% of general adults experience bad quality of
]. Consistent with this finding, in this study, 23.3%
of pregnant women experienced bad quality of sleep.
Sleep disorders during pregnancy are known to
influence the occurrence of hypertension in pregnant women
]. Thus, although it was thought that sleep
disorders were a risk factor for low birth weight, the results
of the present study did not confirm this. Abeysena et al.
 reported that shorter sleep duration (<8 h) was a risk
factor for SGA birth when SGA was defined as a birth
weight less than the fifth percentile. However, no other
study has reported reduced sleep duration as a risk
factor for SGA birth [
]. The definition of “shorter sleep
duration” may differ between countries and regions, and
in some regions, time spent not sleeping may be
interpreted as time at work. Thus, in future studies, it is
necessary to carefully investigate the effect of various factors
including sleep duration, working hours, and mental
stress on the risk of SGA birth.
This study showed that neither the amount nor the
quality of mothers’ sleep was associated with the risk of SGA
birth. Further studies will be needed to investigate the
effect of various other factors such as sleep duration,
working hours, and mental stress on the risk of SGA birth.
Our study has a methodologic limitation in that the
data on sleep duration were obtained by a
self-administered questionnaire, and thus, may have been prone
to misclassification. However, a previous study showed
that self-assessed sleep duration yielded valid results
in comparison with quantitative sleep assessment
using actigraphy [
]. Our study has another
limitation in that although the incidence of SGA births was
relatively high among mothers who lacked weight gain
information, we were unable to ascertain why this was
so. Mothers excluded from this study due to
unavailability of weight gain information might have influenced
95% CI: 95% confidence interval; BMI: body mass index; JECS: Japan
Environment and Children’s Study; RR: risk ratio; SD: standard deviation; SGA: small for
KK, KK, TK, and SM designed the study. MS, MT, and SM analyzed and
interpreted the data. SM, MS, ES, and AS wrote the manuscript. All authors
contributed to the critical revision of the manuscript. All authors read and approved
the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
The data used to derive our conclusions are unsuitable for public
deposition due to ethical restrictions and specific legal framework in Japan. It is
prohibited by the Act on the Protection of Personal Information (Act No. 57
of 30 May 2003, amended on 9 September 2015) to publicly deposit data
containing personal information. The Ethical Guidelines for Epidemiological
Research enforced by the Japan Ministry of Education, Culture, Sports, Science,
and Technology and the Ministry of Health, Labor and Welfare also restricts
the open sharing of epidemiological data. All inquiries about access to data
should be sent to . The person responsible for handling
inquiries at this e-mail address is Dr. Shoji F. Nakayama, JECS Programme
Office, National Institute for Environmental Studies.
Consent for publication
Ethics approval and consent to participate
The JECS protocol was approved by the Review Board of the Ministry of the
Environment (approval number: 2010-2R-11) for epidemiological studies,
and by the Ethics Committees (approval number: 27-334) of all participating
institutions. The JECS is conducted in accordance with the Declaration of
Helsinki and other nationally valid regulations, and written informed consent
was obtained from all participants.
JECS was funded by the Japanese Ministry of the Environment. The findings
and conclusions of this article are solely the responsibility of the authors
and do not represent the official views of the government. This article was
supported in part by MEXT KAKENHI (24119004) and JSPS KAKENHI (Nos.
16H01880 and 16K13072) at the time of the design and composition. The
funding bodies had no role in the study design, collection and analysis of data,
interpretation of results, writing of the manuscript, or decision to publish.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. Kok JH , den Ouden AL , Verloove-Vanhorick SP , Brand R . Outcome of very preterm small for gestational age infants: the first nine years of life . Br J Obstet Gynaecol . 1998 ; 105 : 162 - 8 .
2. Patterson RM , Prihoda TJ , Gibbs CE , Wood RC . Analysis of birth weight percentile as a predictor of perinatal outcome . Obstet Gynecol . 1986 ; 68 : 459 - 63 .
3. Committee on Practice Bulletins-Gynecology, American College of Obstetricians and Gynecologists. Intrauterine growth restriction. Clinical management guidelines for obstetrician-gynecologists . Int J Gynaecol Obstet . 2001 ; 72 : 85 - 96 .
4. Goldenberg RL , Cutter GR , Hoffman HJ , Foster JM , Nelson KG , Hauth JC . Intrauterine growth retardation: standards for diagnosis . Am J Obstet Gynecol . 1989 ; 161 : 271 - 7 .
5. Morokuma S , Shimokawa M , Kato K , Sanefuji M , Shibata E , Tsuji M , et al. Relationship between hyperemesis gravidarum and small-for-gestationalage in the Japanese population: the Japan Environment and Children's Study (JECS) . BMC Pregnancy Childbirth . 2016 ; 16 : 247 .
6. Abeysena C , Jayawardana P , DE A , Seneviratne R . Maternal sleep deprivation is a risk factor for small for gestational age: a cohort study . Aust N Z J Obstet Gynaecol . 2009 ; 49 : 382 - 7 .
7. Kawamoto T , Nitta H , Murata K , Toda E , Tsukamoto N , Hasegawa M , et al. Working group of the epidemiological research for children's environmental health. Rationale and study design of the Japan Environment and Children's Study (JECS) . BMC Public Health . 2014 ; 14 : 25 .
8. Ministry of the Environment . Japan Environment and Children Study . 2013 . http://www.env.go.jp/en/chemi/hs/jecs/. Accessed 22 Sept 2013 .
9. Suzuki K , Ohida T , Sone T , Takemura S , Yokoyama E , Miyake T , et al. An epidemiological study of sleep problems among the Japanese pregnant women . Nihon Koshu Eisei Zasshi . 2003 ; 50 : 526 - 39 (in Japanese).
10. Ministry of Health, Labour and Welfare. National health and nutrition survey Japan . 2014 . http://www.mhlw.go.jp/stf/houdou/0000106405. html (in Japanese). Accessed 8 Aug 2017 .
11. Itabashi K , Miura F , Uehara R , Nakamura Y . New Japanese neonatal anthropometric charts for gestational age at birth . Pediatr Int . 2014 ; 56 : 702 - 8 .
12. Micheli K , Komninos I , Bagkeris E , Roumeliotaki T , Koutis A , Kogevinas M , et al. Sleep patterns in late pregnancy and risk of preterm birth and fetal growth restriction . Epidemiology . 2011 ; 22 : 738 - 44 .
13. Owusu JT , Anderson FJ , Coleman J , Oppong S , Seffah JD , Aikins A , et al. Association of maternal sleep practices with pre-eclampsia, low birth weight, and stillbirth among Ghanaian women . Int J Gynaecol Obstet . 2013 ; 121 : 261 - 5 .
14. Pamidi S , Pinto LM , Marc I , Benedetti A , Schwartzman K , Kimoff RJ . Maternal sleep-disordered breathing and adverse pregnancy outcomes: a systematic review and metaanalysis . Am J Obstet Gynecol . 2014 ; 210 : 52e1 - 14 .
15. Chang JJ , Pien GW , Duntley SP , Macones GA . Sleep deprivation during pregnancy and maternal and fetal outcomes: is there a relationship? Sleep Med Rev . 2010 ; 14 : 107 - 14 .
16. Lockley SW , Skene DJ , Arendt J . Comparison between subjective and actigraphic measurement of sleep and sleep rhythms . J Sleep Res . 1999 ; 8 : 175 - 83 .