Association of excessive mobile phone use during pregnancy with birth weight: an adjunct study in Kumamoto of Japan Environment and Children’s Study
Lu et al. Environmental Health and Preventive Medicine
Association of excessive mobile phone use during pregnancy with birth weight: an adjunct study in Kumamoto of Japan Environment and Children's Study
Xi Lu 0 3
Masako Oda 2 3
Takashi Ohba 1 3
Hiroshi Mitsubuchi 3 4
Shota Masuda 0 3
Takahiko Katoh 0 3
0 Department of Public Health, Faculty of Life Sciences, Kumamoto University , Kumamoto City, Kumamoto , Japan
1 Department of Obstetrics and Gynecology, Faculty of Life Sciences, Kumamoto University , Kumamoto City , Japan
2 The Southern Kyushu and Okinawa Unit Center, Faculty of Life Sciences, Kumamoto University , Kumamoto City, Kumamoto , Japan
3 Authors' information 1. Xi Lu is an assistant professor from the Department of Public Health, Faculty of Life Sciences, Kumamoto University, Japan. 2. Masako Oda is a senior lecturer from the Southern Kyushu and Okinawa Unit Center, Faculty of Life Sciences, Kumamoto University, Japan. 3. Takashi Ohba is an associate professor from the Department of Obstetrics and Gynecology, Faculty of Life Sciences, Kumamoto University, Japan. 4. Hiroshi Mitsubuchi is a professor from the Department of Neonatology, Kumamoto University Hospital, Japan. 5. Shota Masuda is a graduate student and medical doctor from the Department of Public Health, Faculty of Life Sciences, Kumamoto University, Japan. 6. Takahiko Katoh is a professor from the Department of Public Health, Faculty of Life Sciences, Kumamoto University , Japan
4 Department of Neonatology, Kumamoto University Hospital , Kumamoto City, Kumamoto , Japan
Background: Low birth weight has been shown to be closely associated with neonatal mortality and morbidity, inhibited growth, poor cognitive development, and chronic diseases later in life. Some studies have also shown that excessive mobile phone use in the postnatal period may lead to behavioral complications in the children during their growing years; however, the relationship between mobile phone use during pregnancy and neonatal birth weight is not clear. The aim of the present study was to determine the associations of excessive mobile phone use with neonatal birth weight and infant health status. Methods: A sample of 461 mother and child pairs participated in a survey on maternal characteristics, infant characteristics, and maternal mobile phone usage information during pregnancy. Results: Our results showed that pregnant women tend to excessively use mobile phones in Japan. The mean infant birth weight was lower in the excessive use group than in the ordinary use group, and the frequency of infant emergency transport was significantly higher in the excessive use group than in the ordinary use group. Conclusions: Excessive mobile phone use during pregnancy may be a risk factor for lower birth weight and a high rate of infant emergency transport.
Birth weight is the body weight of a baby at birth .
There is a widespread belief that the birth weight of
babies has increased in the last several years [2, 3].
However, the Ministry of Health, Labour and Welfare
 reported that the mean neonatal birth weight in
Japan decreased from 3.24 kg for boys and 3.15 kg for
girls in 1975 to 3.04 kg for boys and 2.96 kg for girls in
2014 and that the rate of low-birth-weight infants (birth
weight below 2500 g) increased from 4.7% for boys and
5.5% for girls in 1975 to 8.5% for boys and 10.7% for
girls in 2014. Therefore, the mean birth weight of
Japanese infants is decreasing steadily, and previous
studies support this finding [5, 6]. Low birth weight has
been shown to be closely associated with neonatal
mortality and morbidity, inhibited growth, poor
cognitive development, and chronic diseases later in life . A
previous study reported that low birth weight
predisposes individuals to chronic diseases, such as ischemic
heart disease, diabetes, and hypertension, during adult
life . Maternal factors, such as primiparity, maternal
smoking during pregnancy, maternal age, and multiple
pregnancies, have been shown to be related with
neonatal birth weight ; however, there is still no clarity on
the relationship between many other factors and
neonatal birth weight.
Recently, mobile phones have rapidly become
important and widely available tools that are routinely
used for a variety of purposes by a large number of
people [9–12]. Most people have mobile phones and
use them very often. Many people, especially the
youth, use mobile phones to study, search for
information on the Internet, play games, and communicate
with others . Some studies have shown that
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excessive mobile phone use may lead to a number of
symptoms, such as headache, impaired concentration
and memory, fatigue, and sleep disturbances [14, 15].
Additionally, excessive mobile phone use may
negatively affect mental health and lead to depression,
stress, and anxiety [9–14, 16].
Some studies reported that female individuals are
prone to the adverse effects of excessive mobile phone
use, and several studies have found that the levels of
attachment to mobile phones and dependence on mobile
phones are higher among female individuals than among
male individuals [15, 17–21]. In a previous study of
young adults (n = 1415), it was found that female
individuals aged 20 years or older were nearly three times
more likely than male individuals to agree with the
statement, “I cannot imagine life without the mobile” (25 vs.
9%) . However, the association between neonatal
birth weight and mobile phone use during pregnancy
remains unclear. A previous cohort study reported
associations of prenatal and, to a lesser extent, postnatal
exposures to mobile phones with behavioral problems in
children aged 7 years ; however, very little is known
about the correlation.
The present study aimed to determine the associations
of excessive mobile phone use with neonatal birth
weight and infant health status and to provide basic data
about excessive mobile phone use during pregnancy in a
local area of Japan.
Data were obtained from the Japan Environment and
Children’s Study (JECS) and JECS Adjunct Study in
Kumamoto. In the JECS, three self-administered
questionnaires and four medical record-transfer
questionnaires were administered to the participants. Clinical
measurements and biological samples were collected by
trained nurses. The JECS included 103,106 expecting
mothers, and the consent rate was 78.5%. The
recruitment and exposure protocols are available elsewhere
[23, 24]. The study in Kumamoto included 3012
motherchild pairs, and our study included data from only
hospitals. Finally, we had 521 participants in our study.
In this study, we extracted basic data during pregnancy
obtained with two maternal self-administered
questionnaires and fetal data obtained with the first medical
record-transfer questionnaire from JECS. Additionally,
an original paper questionnaire in the JECS Adjunct
Study was used to collect maternal mobile phone usage
information during pregnancy (e.g., daily mobile phone
use times, location of the phone during the day and at
night, and power state (on/off ) of the mobile phone
during sleep). We distributed the questionnaire about
daily mobile phone use when the expecting mothers
were hospitalized before delivery or after delivery.
Igarashi et al. developed the Self-Perception of
TextMessage Dependency Scale (STDS) for assessing text
message dependency . This self-reported scale
measures the perception of people to their use of text
messages and their attitudes toward compulsive text
messaging in the context of interpersonal relationships.
This scale consists of the following three subscales:
emotional reaction, excessive use, and relationship
maintenance. In the present study, a short version of the STDS
was used. This version consists of 15 items with a 5-point
scale (1 = “strongly disagree” and 5 = “strongly agree”). A
higher score indicates greater dependency on text
messaging and mobile phone use.
All expecting mothers from one rural area in Kumamoto,
Japan, were considered for recruitment between 2012 and
2014. Recruitment was performed with the following two
protocols: (1) recruitment at the time of the first prenatal
examination at cooperating hospitals and (2) recruitment at
local government offices.
We enrolled 521 participants and excluded (1) those
who did not complete the first or second trimester
questionnaires (MT1 or MT2) or the first medical
record-transfer questionnaire (Dr-0M); (2) those who
did not complete the mobile phone daily usage
questionnaire; (3) those with missing data for the maternal
MT1, MT2, Dr-0M, or mobile phone daily usage
questionnaire; and (4) those who had multiple pregnancies.
Finally, 461 mother and child pairs were included in
Outcomes of this study were birth weight and infant
health status (birth height, birth head circumference,
birth chest circumference, mode of delivery, weeks of
pregnancy, placental weight, low birth weight), infant
emergency transport, and premature birth.
The results are expressed as mean ± standard deviation
(SD) or number (percentage). In our study, we used a
cutoff of 15 points for the excessive use score in the
STDS to determine excessive mobile phone use.
Participants were divided into an ordinary use group
(excessive use score ≤15 points) or excessive use group
(excessive use score >15 points) . For data analysis,
we used the t test, χ2 test, linear regression analysis,
and logistic regression analysis. All statistical analyses
were performed using SPSS (version 23.0; IBM Corp.,
Armonk, NY). A P value <0.05 was considered to
indicate statistical significance.
The prevalence of excessive mobile phone use was 9.98%
in our study. Table 1 shows the maternal characteristics
and their differences between the ordinary and excessive
use groups. Age at study entry was lower, the time of
first use of a mobile phone was earlier, family income
and education were lower, the frequencies of individuals
who were unmarried and primiparous were higher, the
sleeping time at night was later, the duration of playing
games and using the mobile phone was longer, and the
frequency of placing the mobile phone in the trouser or
shirt pocket was higher in the excessive use group than
in the ordinary use group (all P < 0.05).
Table 2 shows the infant characteristics and their
differences between the ordinary and excessive use groups.
The mean birth weight and birth chest circumference
were higher in the ordinary use group than in the
excessive use group (3167.16 ± 394.05 g vs. 3037.37 ± 324.87 g,
P < 0.05, and 32.45 ± 1.65 cm vs. 31.94 ± 1.77 cm, P < 0.05,
respectively). The frequency of emergency transportation
was higher in the excessive use group than in the
ordinary use group (P < 0.05). However, the proportion of
low-birth-weight infants was not significantly different
between the two groups.
On assessing the correlation between predictor
variables and body weight, we found that maternal age,
maternal body mass index before pregnancy, birth height,
birth head circumference, birth chest circumference, and
placental weight were positively correlated with birth
weight. With regard to sex differences, the birth weight
was lower in female infants than in male infants.
However, maternal smoking history and excessive mobile
phone use were not significantly correlated with birth
weight. Additionally, primiparity and the designated
location for the mobile phone were not significantly associated
with birth weight. The correlation coefficient in univariate
analysis in terms of the association of excessive mobile
phone use with birth weight was −0.10 (P < 0.05).
We performed a linear regression analysis to identify
the predictors of gestational age, birth weight, and low
birth weight. The variables that showed statistical
significance are presented in Table 3. Birth weight, birth chest
circumference, and infant sex showed positive
correlation with gestational age, while placental weight and
primiparity had negative correlation. Birth chest
circumference, birth height, placental weight, and maternal
body mass index before pregnancy showed positive
correlation with birth weight, while excessive mobile phone
use showed negative correlation. Maternal age, birth
height, maternal BMI before pregnancy, birth head
circumference, primiparity, maternal smoking, excessive
mobile phone use, maternal complications, and obstetric
labor complications were predictors added in the
analysis; however, they were deleted during analysis. There
were only 16 low-birth-weight infants in our study. After
linear regression analysis, only the chest circumference at
birth had positive correlation with low birth weight, and
other predictors were non-significant during analysis.
We assessed emergency transport and premature birth
between the ordinary and excessive use groups (Table 4).
The risk of emergency transport was significantly higher
in the excessive use group than in the ordinary use
group (crude OR = 4.07, 95%CI = 1.01–16.30; adjusted
OR = 7.93, 95%CI = 1.40–44.85). The risk of premature
birth was not significantly different between the ordinary
and excessive use groups.
To our knowledge, this is the first study on the
prevalence of excessive mobile phone use during pregnancy in
Japanese women from a local area. Our study findings
suggest that excessive mobile phone use in Japan is not
limited to students and can be noted in adult women,
even during pregnancy. The prevalence of excessive
mobile phone use was 9.98%, which was higher than that
reported among women employed in companies (5.4%) .
With regard to maternal characteristics, the maternal
age and age at first use of a mobile phone were lower in
the excessive use group than in the ordinary use group.
These findings are consistent with the results of previous
studies [9, 16]. Young individuals tend to show high
excitement and interest in the use of a new mobile phone.
We also found that single mothers had excessive mobile
phone use. The frequencies of loneliness, depression,
and anxiety may be higher among single mothers than
among mothers who have support during pregnancy. In
a previous study, Shaw and Grant found that Internet
chat alleviated loneliness and depression and increased
perceived social support and self-esteem .
Additionally, Igarashi and Yoshida  found that among first-year
university students, a higher frequency of text messaging
at the beginning of the first semester was correlated with
a lower feeling of loneliness at the end of the semester.
We believe that single mothers need more time to use a
mobile phone as a communication tool to maintain
contact with others. We found that the family income and
maternal schooling degree were lower in the excessive use
group than in the ordinary use group; however, we did not
identify any previous study to support these results.
Nonetheless, we believe that different income and education
levels may influence mobile phone use frequency and
habit. We also found that the excessive use group
preferred to place the mobile phone in the trouser or shirt
pocket, indicating that the excessive use group preferred
to have the mobile phone in an easily accessible location.
With regard to infant characteristics, birth weight and
chest circumference at birth were lower and the
emergency transport rate was higher in the excessive use
Table 1 Maternal characteristics and their differences between the normal and excessive use groups
Maternal characteristics Total (N = 461) Mobile normal user (N = 415) Mobile excessive user (N = 46)
Maternal age 29.54 (±5.35) 30.03 (±5.08) 25.09 (±5.70)
Mobile start age, years 17.29 (±2.81) 17.48 (±2.80) 15.63 (2.33)
Wight change during pregnancy 11.25 (±3.88) 11.20 (±3.85) 11.67 (±4.12)
Maternal BMI before pregnancy 21.49 (±3.01) 21.52 (±3.43) 21.13 (±3.16)
Yes 29 (6.3%) 24 (5.8%) 5 (10.9%)
No 432 (93.7%) 391 (94.2%) 41 (89.1%)
Single 31 (6.7%) 18 (4.3%) 13 (28.3%)
Married 430 (93.3%) 397 (95.7%) 33 (71.7%)
Full-time joba 111 (24.1%) 96 (23.1%) 15 (32.6%)
Part-time job 152 (33.0%) 135 (32.5%) 17 (37.0%)
Housewife 162 (35.1%) 152 (36.6%) 10 (21.7%)
Independent business 18 (3.9%) 16 (3.9%) 2 (4.3%)
No answers 18 (3.9%) 16 (3.9%) 2 (4.3%)
Family income, ¥ per year
<4,000,000 255 (55.3%) 225 (54.2%) 30 (65.2%)
4,000,000–7,999,999 141 (30.6%) 133 (32.0%) 8 (1.7%)
8,000,000–11,999,999 15 (3.3%) 15 (3.6%) 0 (0%)
≧12,000,000 12 (2.6%) 11 (2.7%) 1 (2.1%)
No answer 38 (8.2%) 31 (7.5%) 7 (15.2%)
Maternal schooling degree
High schoola 253 (54.9%) 216 (52.0%) 37 (80.4%)
Collegeb 206 (44.7%) 197 (47.5%) 9 (19.6%)
Otherwise 2 (0.4%) 2 (0.5%) 0 (0%)
Yes 307 (66.6%) 281 (67.7%) 26 (56.5%)
No 154 (33.4%) 134 (32.3%) 20 (43.5%)
Time of laid up (excluding sleep), hours 5.00 (±3.68) 4.95 (±3.74) 5.57 (±2.93)
Time of watch TV, hours 2.67 (±2.05) 2.56 (±2.00) 3.59 (±2.27)
Time of playing game, minutes 28.0 (±56.5) 21.17 (±0.7) 89.90 (±1.8)
Time of mobile use, minutes 133.7 (±191.4) 113.91 (±167.9) 314.91 (279.0)
Designated spot for mobile
Bag 364 (79.0%) 335 (80.7%) 29 (63.0%)
Trouser pocket 48 (10.4%) 34 (8.2%) 14 (30.4%)
Shirt pocket 5 (1.1%) 5 (1.2%) 0 (0%)
Coat pocket 17 (3.7%) 14 (3.4%) 3 (6.5%)
Others 27 (5.9%) 27 (6.5%) 0 (0%)
Designated spot for mobile
Bag or coat pocket and others 408 (88.5%) 376 (90.6%) 32 (69.6%)
Trouser pocket or shirt pocket 53 (11.5%) 39 (9.4%) 14 (30.4%)
Bed time (time go to bed, PM) 10:54 10:54 11:48
Table 1 Maternal characteristics and their differences between the normal and excessive use groups (Continued)
Power state of the mobile phone during sleep
On 425 (92.2%) 381 (91.6%) 44 (95.7%)
Usually on 22 (4.8%) 20 (4.8%) 2 (4.3%)
Sometimes on 6 (1.3%) 6 (1.4%) 0 (0%)
Off 8 (1.7%) 8 (1.9%) 0 (0%)
Location of the phone during sleep
0.5 m from abdominal 115 (24.9%) 99 (23.9%) 16 (34.8%)
1 m from abdominal 236 (51.2%) 216 (52.0%) 20 (43.5%)
1.5 m from abdominal 62 (13.3%) 55 (13.3%) 7 (15.2%)
2 m from abdominal 48 (10.4%) 45 (10.8%) 3 (6.5%)
Total sleep time (hours) 7.5 (±1.48) 7.5 (±1.46) 7.7 (±1.64)
Yes 12 (2.6%) 12 (2.9%) 0 (0%)
No 449 (97.4%) 403 (97.1%) 46 (100%)
Obstetric labor complication
Yes 219 (47.6%) 193 (46.5%) 27 (58.7%)
No 241 (52.4%) 222 (53.5%) 19 (41.3%)
aIncluding junior high school
bIncluding technical college and junior college
Table 2 Infant characteristics and their differences between the normal and excessive use groups
Infant characteristics Total (N = 461) Mobile ordinary user (N = 415) Mobile excessive user (N = 46)
Boy 247 (53.6%) 227 (54.7%) 20 (43.5%)
Girl 214 (46.4%) 188 (45.3%) 26 (56.5%)
Mode of delivery
Transvaginal 386 (83.7%) 346 (83.4%) 40 (87.0%)
Caesarean section 75 (16.3%) 69 (16.6%) 6 (13.0%)
Gestational age 39.39 (±1.18) 39.41 (±1.18) 39.21 (±1.18)
Birth weight (g) 3154.25 (±389.34) 3167.16 (±394.05) 3037.74 (±324.87)
Birth height (cm) 48.94 (±1.70) 48.93 (±1.72) 49.00 (±1.51)
Birth head circumference (cm) 33.35 (±1.38) 33.39 (±1.37) 32.98 (±1.43)
Birth chest circumference (cm) 32.40 (±1.67) 32.45 (±1.65) 31.94 (±1.77)
Placental weight (g) 587.74 (±111.76) 588.71 (±114.11) 579.00 (88.34)
Low birth weight
1500–2500 g 16 (3.5%) 15 (3.6%) 1 (2.2%)
>2500 g 445 (96.5%) 400 (96.4%) 45 (97.8%)
Yes 14 (3.0%) 12 (2.9%) 2 (4.3%)
No 447 (97.0%) 403 (91.7%) 44 (95.7%)
Yes 10 (2.2%) 7 (1.7%) 3 (6.5%)
No 451 (97.8%) 408 (98.3%) 43 (93.5%)
Table 3 Association between predictor variables and birth weight
Gestational agea (N = 416)
Birth weightb (N = 416)
Birth chest circumference
Maternal BMI before pregnancy
** P < 0.01
aR2 = 0.34, ANOVA P < 0.01. Predictor variables deleted during analysis: maternal age, birth height, maternal BMI before pregnancy, maternal age, birth head
circumference, primiparity, maternal smoking, mobile excessive use, maternal complications, and obstetric labor complication
bR2 = 0.85, ANOVA P < 0.01. Predictor variables deleted during analysis: maternal age, birth head circumference, primiparity, infant sex, maternal smoking, maternal
complications, and obstetric labor complication
cR2 = 0.70, ANOVA P < 0.001. Predictor variables deleted during analysis: maternal age, birth height, birth head circumference, placental weight, maternal BMI
before pregnancy, primiparity, infant sex, gestational age, mobile excessive use, maternal smoking, maternal complications, and obstetric labor complication
group than in the ordinary use group. In the linear
regression analysis, excessive mobile phone use was a
significant predictor of low birth weight. In the logistic
regression analysis, interestingly, we found that excessive
mobile phone use increased the emergency transport
rate, even after adjusting for confounding factors. Many
factors affect the duration of gestation and fetal growth
and, thus, the birth weight. They relate to the infant,
mother, or physical environment and play important
roles in determining birth weight and the future health
of the infant. Our results showed that excessive mobile
phone use during pregnancy may decrease infant birth
weight, although this does not result in low-birth-weight
infants. With regard to the mechanism, it has been
shown that the levels of depression and state-trait
anxiety are higher, and sleep quality is poorer in users
who showed texting and digital audio player dependence
than in ordinary users . Another study reported that
anxiety and dependence increased with daily smartphone
usage and a high rate of nighttime awakening was noted,
which, in turn, affected sleep . Our study suggests
that excessive mobile phone use during pregnancy may
cause mental problems, such as anxiety and depression,
and health problems, such as sleep problems and
sleeplessness. We also found that the sleep time was later
in the excessive use group than in the ordinary use group,
and therefore, excessive users may have poor sleep quality;
however, there was no significant difference in the total
sleep duration between the excessive and ordinary use
groups. The maternal health and mental problems may
lead to a low birth weight and neonatal health, which may
eventually necessitate infant emergency transport.
The present study had some limitations. First, the
sample size was relatively small, and therefore, it may not
provide sufficient power to estimate the association
between excessive mobile phone use and infant birth
weight. The number of emergency transports was only
10, and there was a possibility of chance with regard to
our finding. Second, we did not account for the potential
effects of mental health, such as depression and anxiety,
which were mainly noted in excessive mobile phone
users and users with high dependency and may be
predictors of birth weight. Third, all information was
reported by the participants themselves; therefore, the
reliability of the responses may not be high. Despite these
limitations, our study had some merits and values.
Table 4 Infant emergency transport and premature birth differences between the normal and excessive use groups
Adjusted ORa (95%CI)
Adjusted ORa (95%CI)
Finally, the subjects were not representative of all
pregnant Japanese women, as they were recruited from a
local area of Japan. Therefore, we might need a larger
sample from all areas of Japan to verify our results.
Although our research is important, there are many
shortcomings. To our knowledge, this is the first study to
analyze the prevalence of excessive mobile phone use
during pregnancy in a local area in Japan.
Pregnant women tend to excessively use mobile phones
in Japan. Excessive mobile phone use during pregnancy
may be a risk factor for lower birth weight and a high
rate of infant emergency transport.
XL and TK made the conception and design of this study. MO contributed
to the acquisition of the data. TO, HM, and SM were involved in drafting the
manuscript and revising it critically for important intellectual content. All
authors read and approved the final manuscript.
Ethics approval and consent to participate
The present study was approved by the Ethics Committee of Kumamoto
University Graduate School of Life Sciences, and the committee’s reference
number is Ethics No. 493. Participants were informed in advance that their
participation was strictly voluntary and that all information provided would
remain confidential. Participants had the option not to respond to any part
of the questionnaire and could discontinue participation at any point.
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