Rahman et al. BMC Medicine(2021) 19:229
https://doi.org/10.1186/s12916-021-02093-3

RESEARCH ARTICLE

Open Access

Elevated risk of attention deficit
hyperactivity disorder (ADHD) in Japanesechildren with higher genetic susceptibility
to ADHD with a birth weight under 2000 g
Md Shafiur Rahman1,2, Nagahide Takahashi1,2,3, Toshiki Iwabuchi1,2, Tomoko Nishimura1,2, Taeko Harada1,2,
Akemi Okumura1,2, Nori Takei1,2,4, Yoko Nomura1,5 and Kenji J. Tsuchiya1,2*

Abstract
Background: Both genetic and pre- and perinatal factors, including birth weight, have been implicated in theonset of attention deficit hyperactivity disorder (ADHD) traits among children. This study aimed to elucidate towhat extent the genetic risk of ADHD moderates the association between birth weight and ADHD traits among
Japanese children.
Methods: We conducted a longitudinal birth cohort study (Hamamatsu Birth Cohort for Mother and Children
Study) to investigate the association of genetic risk for ADHD and low birth weight with ADHD traits among
Japanese children. Out of 1258 children, we included 796 who completed follow-ups at 8 to 9 years of age. Birthweight was categorized as <2000 g, 2000–2499 g, and ≥2500 g. Polygenic risk score for ADHD was generatedusing the summary data of a large-scale genome-wide association study. The Rating Scale IV (ADHD-RS) assessed
ADHD traits (inattention and hyperactivity/impulsivity) based on parental reports. Following previous studies, sex,
birth order of the child, gestational age at birth, mother’s age at delivery, educational attainment, pre-pregnancy
body mass index, pre-pregnancy or during pregnancy smoking status, alcohol consumption during pregnancy,
father’s age, education, and annual family income were considered as covariates. Multivariable negative binomial
regression was applied to evaluate the association between birth weight and ADHD traits, while adjusting forpotential covariates. The interaction term between birth weight categories and binary polygenic risk was added tothe model.
Results: Birth weight of 2000–2499 g was not associated with ADHD traits. Birth weight under 2000 g was
significantly associated with both inattention and hyperactivity. When accounting for higher and lower genetic risk
for ADHD, only those with higher genetic risk and birth weight < 2000 g were associated with inattention (rateratio [RR] 1.56, 95% CI 1.07–2.27) and hyperactivity (RR 1.87, 95% CI 1.14–3.06).

* Correspondence: tsuchiya@hama-med.ac.jp
1
Research Centre for Child Mental Development, Hamamatsu University
School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu 431-3192,
Japan
2
United Graduate School of Child Development, Osaka University, Kanazawa
University, Hamamatsu University School of Medicine, Chiba University andUniversity of Fukui, Hamamatsu, Japan
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Rahman et al. BMC Medicine(2021) 19:229

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Conclusions: Birth weight under 2000 g, together with the genetic risk of ADHD, contributes to higher levels of
ADHD traits among Japanese children aged 8 to 9 years. The suggested association between low birth weight and
ADHD is confined to children with a genetic susceptibility to ADHD, indicating the relevance of geneticenvironmental interactions in the etiology.
Keywords: Birth weight, Polygenic risk, ADHD, Inattention, Hyperactivity, Cohort study

Key points
 Questions: Does genetic risk moderate theassociation between birth weight and ADHD traits
among Japanese children?
 Findings: Children with birth weight under 2000 g
and higher genetic risk of ADHD showed increased
severity of ADHD traits at age 8 to 9 years,
compared to those with either normal birth weightor lower genetic risk.
 Meaning: Japanese children born with birth weightless than 2000 g are more vulnerable to their genetic
susceptibility to ADHD. Additional attention isneeded to minimize the severity of ADHD traits
during childhood.

Background
Attention deficit hyperactivity disorder (ADHD) is one of
the most prevalent neurodevelopmental disorders [1, 2], accounting for 1.14 million disability-adjusted life years globally in 2017 [3]. ADHD can be classified as predominantly
inattentive, predominantly hyperactive/impulsive, or a combination of both and usually appears during early childhoodand continues to manifest throughout the life course [1, 4].
ADHD affects functioning, both in school and daily activities[5], and increases the social and economic burden [6, 7]. In
addition, children with ADHD symptoms are often bullied,neglected, and ignored by their peers and others in society
due to their inattentive and restless behavioral phenotypes[8]. Although the etiology of ADHD is complex and multifactorial, both pre- and perinatal conditions and genetic risk
factors have been implicated in the development of ADHD
symptoms among children [9–11]. Specifically, low birthweight [12] is the most consistent environmental factor
identified in the literature to affect neurodevelopment andthe onset of ADHD in childhood [13].
Accumulating evidence suggests that low birth weight isan early biomarker for newborn infants’ vulnerability to experiencing altered neurodevelopment and developmental
disorders [14, 15]. A recent meta-analysis reported thatchildren born with very low birth weight have a higher riskof developing ADHD during childhood [14]. Although several previous studies have investigated the association between birth weight and ADHD traits, the results remaininconclusive [16–24]. For instance, some studies found anegative relationship between birth weight and ADHD
symptoms [17–19, 22, 23], while others failed to confirm
the association [25, 26]. Moreover, the majority of previous
studies have explored the link between ADHD and the extremely low end of the birth weight distribution [14, 27],
that is, either very low birth weight (≤1500 g) or extremely
low birth weight (≤1000 g), or a low birth weight classified
as under 2500 g [18, 21]. A birth weight of 2500 g is thestandard cutoff set by the World Health Organization(WHO) to define low birth weight and is generally considered to indicate high-risk newborns. However, the cut-off
point for low birth weight remains controversial. Given that
Asian children are generally lighter than their Westerncounterparts [28], the limit of 2500 g is inadequate for defining low birth weight. Recently, a multi-national study
suggested a birth weight of around 2000 g as the thresholdfor defining low birth weight among Asians [29]. Notably,
the mean birth weight in Japan has declined significantly inthe last three decades (1980–2010) [30]. Thus, the prevalence of low birth weight, particularly birth weights between
1500 to 2499 g, has increased significantly [30]. Therefore,
it is of paramount importance to investigate whether intermediate birth weight categories, such as 1500 to 1999g and2000 to 2499g, are associated with ADHD symptoms
among Japanese children.
Besides the birth weight implications for ADHD, it iswell known that ADHD is heritable (70–80%) [31, 32]. A
previous meta-analysis found significant associations between ADHD and eight candidate variants connectedwith six genes [33, 34]. In addition, a recent genomewide association study (GWAS) identified 304 genetic
variants in 12 loci that were associated with ADHD [35].
Furthermore, several studies found a significant association between genetic risk, specifically polygenic risk
scores (PRS), and ADHD traits [36–38].
The influence of some individual candidate genes andseveral prenatal factors on ADHD traits is known tosome extent. While previous studies have highlighted
the importance of gene-environmental interactions in
the etiology of ADHD [39, 40], the evidence of this relationship remains limited [40–42]. Thus, the interactionsof genetic liability, measured using PRS, with prenatal
factors such as birth weight could elucidate the etiologyof ADHD [43]. Understanding the mechanistic pathway
between genetic risks and non-genetic risks, such as lowRahman et al. BMC Medicine(2021) 19:229

birth weight, adjusted for lighter Asian infants, may help
identify children at greater risk for ADHD diagnosis
later in childhood. This may subsequently reduce thelong-term sequelae associated with elevated ADHD
traits through timely implementation of behavioral andpharmacological interventions [44]. However, studies on
the interactions between birth weight and the genetic
risk of ADHD on the symptoms of ADHD in childhood
are limited. Therefore, this study aimed to investigate
the association of low birth weight and genetic risk for
ADHD with the presence of ADHD traits in children.
We used a longitudinal birth cohort of the general population in Japan. We hypothesized that a higher polygenic
risk of ADHD, together with a lower birth weight, would
be associated with higher severity of ADHD traits among
Japanese children aged 8 to 9 years.

Methods
Study cohortThis study used data from the Hamamatsu Birth Cohort for Mother and Child (HBC) Study, which is an
ongoing prospective birth cohort study designed toinvestigate the neurodevelopmental trajectories ofchildren in the general population. The children in
the cohort were born in Hamamatsu City, Japan, between November 2007 and March 2011. The detailsof the HBC study are presented elsewhere [45]. In the
HBC study, out of 1258 children, 826 were successfully followed up until 8 to 9 years. We excluded
twins (n=28) and children with Down syndrome (n=2)
from this study. Ultimately, 796 children and theirmothers were included in this study.

Page 3 of 13[47]. Trained clinicians collected buccal swabs (DNAsamples) from children during the follow-up surveys
conducted either at age 32 months, 40 months, 4.5 years,
or 6 years. In this study, out of 796 children, a total of
137 children were excluded from the PRS analysis because genomic DNA was unavailable due to a low callrate (<97%) or a refusal or reluctance of buccal swab collection. A Japonica array was used for SNP genotyping[48] and BEAGLE 5.0 of phase 3 of the 1000 genome
project was used as the reference panel for Japanese
populations in the genotyping imputation [49]. Next, the
PRS was generated in PRSice-2 software using a previous
GWAS study for ADHD, conducted by the Lundbeck
Foundation Initiative for Integrative Psychiatric Research, as the discovery cohort [50]. Although the
ADHD-PRS was estimated at several p-value thresholds,
we considered the best fit PRS for this study. The
ADHD-PRS for the included 659 samples had a bellshaped distribution with a mean of 0.00124 and medianof 0.00123 (Supplementary Figure 1). The score in the
middle of the distribution (a PRS value of 0) corresponds
to the average risk for developing ADHD. The score on
the right tail of the distribution indicates a relatively
higher genetic risk of ADHD than the average, and theleft tail represents a lower risk. When investigated the
distribution of genetic risk across children with different
birth weight categories, we observed that children were
almost equally distributed to higher or lower genetic risk
group in each birth weight category (see Additional file
1: Figure S1).

Outcome: ADHD traits
Exposures
Birth weight categories

Birth weight below 1500 g and 2500 g are recognized asvery low birth weight and low birth weight, respectively.
However, in this study, we had only three children (outof 796) whose birth weight was below 1500 g. Moreover,a recent multi-national study has highlighted the needfor redefining low birth weight with a threshold of birthweight of around 2000 g among Asian children [29].
Thus, we classified birth weight into three categories:
normal birth weight (≥2500 g), intermediate birth weight(2000–2499 g), and birth weight <2000 g.

The main outcomes were the behavioral traits of ADHD,
which comprise inattention and hyperactivity domains.
To quantify these domains, we used the ADHD Rating
Scale IV (ADHD-RS) based on parental reports to assess
the severity of ADHD traits at ages 8 to 9 years. The
ADHD-RS comprises 18 items covering the spectrum of
the inattention (9 items) and hyperactivity/impulsivity
domains (9 items) [51]. Responses are rated on a 4-point
Likert scale ranging from 0 (“never” or “rarely”) to 3(“very often”) [51].

Covariates
Polygenic risk score for ADHD

The genetic risk for ADHD in the HBC study wasassessed using PRS. PRS represents the approximate
genetic liability for a disease or disorder using the number of risk alleles from a set of single-nucleotide polymorphisms (SNPs) [46]. The detailed estimation
procedure of the PRS and quality controls of SNPs in
the HBC study were described in our previous study

Following previous studies [52, 53], the sex, birth orderof the child, gestational age at birth, mother’s age at delivery, educational attainment, pre-pregnancy body massindex (BMI), pre-pregnancy or during pregnancy smoking status, alcohol consumption during pregnancy, father’s age at birth, education, and annual family income(at birth) were considered as confounders and were included in the model.

Rahman et al. BMC Medicine(2021) 19:229

Statistical analysis

Frequency distribution and univariate statistics wereused to describe the characteristics of children and theirmothers. The data were not normally distributed as indicated by a Shapiro-Wilk test (p<0.001 for all three outcomes related to ADHD-RS total, inattention, andhyperactivity scores). Therefore, negative binomial regression models were employed to investigate the association between the exposure and outcome variables. The
choice of negative binomial models was determined byconsidering overdispersion that was present for both the
Poisson and zero-inflated Poisson models. The negative
binomial regression model provided rate ratios (RR)
along with 95% confidence intervals (CIs), which indicates the number of times that the ADHD score ishigher (when RR>1) or lower (RR<1) than the referencegroup. In the case of continuous exposure, an RR value
higher than 1 indicates a higher severity associated witha one-unit increase in the exposure, and vice versa.
Model 1 was adjusted for variations in survey time only.
Model 2 was additionally adjusted for gender, birthorder of the child, maternal age at delivery, education,
pre-pregnancy BMI, smoking status, and alcohol intake
to control for maternal and infant-related factors. Model
3 was further adjusted to include the father’s age atbirth, education, and annual family income to control
for paternal factors. We found significant interaction effects between birth weight categories and ADHD-PRS.
To facilitate interpretation, we classified the PRS into abinary variable using the median value as the threshold.
Therefore, any PRS above the median was defined as“having higher genetic risk than average” and PRS values
below the median were considered as “having lower genetic risk than average”. We also considered the interaction of birth weight categories and binary polygenic
risk variable in the model to estimate the RR for eachcombination of birth weight category and binary polygenic risk variable. Clustering was allowed for with the
Huber-White sandwich estimator in all the included
models, as some children included in this study wereborn to the same mother. Furthermore, backgroundcharacteristics of children included in the analysis andthose excluded from the analysis were compared. The
Little’s test for Missing Completely at random (MCAR)
was used to test whether missingness of ADHD traitscores and ADHD-PRS were completely at random [54],while an extension of the Little’s MCAR test, with several combinations of auxiliary variables as covariates into
the test, was employed to test the covariate-dependent
missingness [55]. Then we performed multiple imputation of ADHD-PRS for children with missing information, assuming missing completely at random, toevaluate the potential impact of missing observations(17.2%) on the association between birth weight andPage 4 of 13

ADHD traits. In addition, we performed sensitivity analyses by considering missing ADHD-PRS to the end of
the spectrum, i.e., recoding all missing ADHD-PRS ashigh risk or low risk. Statistical analyses were performed
using Stata MP version 16.1.

Results
Characteristics of participants

Table 1 shows the demographic characteristics of thestudy participants. A total of 796 children (49.2% females; 50.8% males) aged 8 to 9 years were included inthis study. Among them, 6.4% were born preterm (before the gestational age of 37 weeks). The mean (±SD)
birth weight and gestational age at birth were 2949.3 g(440.1) and 38.9 weeks (1.52), respectively. Additionally,
87.3% of children had a normal birth weight, 10.3% had
a birth weight between 2000 to 2499 g, and 2.4% had abirth weight under 2000 g. The median scores for
ADHD combined traits, as well as inattention andhyperactivity traits, were significantly higher among children who had a birth weight < 2000 g (see Additional
file 2: Table S1). These scores were lowest among children with birth weights between 2000 and 2499 g (seeAdditional files 3 and 4: Figures S2-S3).
Independent effects of birth weight and ADHD

In the negative binomial models, birth weight, when
considered as continuous, was not significantly associated with ADHD scores (see Additional files 5: Table
S2). However, when birth weight was considered as categorical, we found that birth weight < 2000 g was significantly associated with higher ADHD trait scores (RR
1.60, 95% CI 1.16–2.22) (Table 2). Similar findings wereobserved for both inattention and hyperactivity domains.
Birth weight < 2000 g was significantly associated withhigher scores of both inattention (RR 1.50, 95% CI 1.10–
2.06) and hyperactivity traits (RR 1.82, 95% CI 1.17–
2.83) compared to normal birth weight (≥2500 g) (model1). After adjusting for potential covariates in model 3,
the results remained statistically significant for both inattention (RR 1.49, 95% CI 1.15–1.94) and hyperactivity
traits (RR 1.78, 95% CI 1.19–2.67).
Interaction of genetic risk of ADHD and birth weight on
ADHD traits

We found a significant interaction effect of birth weightcategories and ADHD-PRS on ADHD scores (Wald chisquared test, p<0.05 for ADHD total score) (see Additional files 6: Table S3). This provided evidence of themoderating effects of genetic risk on the association between birth weight and ADHD traits. Thus, we included
the interaction of birth weight categories and binary
polygenic risk variables in the model.

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Table 1 Background characteristics of study participants (N=796)
n

%

First

401

50.4

Second or higher

395

49.6

Girls

392

49.2

Boys

404

50.8

Characteristics

Mean or median

SD or IQR

38.9

1.52

2949.3440.1

0.0022

1.01

Children’s characteristics
Birth order, n (%)

Gender, n (%)

Gestational age at birth in week, mean (SD)
Preterm birth, n (%)
Yes

51

6.4

No

745

93.6

Birth weight (g), mean (SD)<2000 g19

2.4

2000–2499 g

82

10.3

≥2500 g695

87.3

ADHD-PRS, mean (SD)

a

5

1–10b

Inattention, median (IQR)

a

3

1–7b

Hyperactivity, median (IQR)

1a

0-3b

ADHD-RS total score, median (IQR)

Parent’s characteristics
Mother’s age at delivery, n (%)<35 years

567

71.2

≥35 years

229

28.8

≤12 years

246

30.9

>12 years

550

69.1

170

21.3

Maternal educational attainment, n (%)

Maternal pre-pregnancy BMI, n (%)
Underweight (<18.5)
Normal weight (18.5-24.9)

541

68.0

Overweight (≥25.0)

85

10.7

Yes

155

19.5

No

641

80.5

Yes

110

13.8

No

686

86.2

<25 years45

5.6

25–34 years

456

57.3

≥35 years

295

37.1

≤12 years

59

7.4>12 years

737

92.6

Pre-pregnancy or during pregnancy smoking history, n (%)

Alcohol consumption during pregnancy, n (%)

Father’s age at birth

Father’s education at birthHousehold annual income at birth in JPY

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Table 1 Background characteristics of study participants (N=796) (Continued)
Characteristicsn%≤3 million

36

4.5

3–8 million

604

75.9

≥8 million

156

19.6

Mean or median

SD or IQR

Note: aValues present median; bvalues present interquartile range; ADHD-RS, attention deficit/hyperactivity disorder rating scale; BMI, body mass index; IQR,
interquartile range; PRS, polygenic risk score; SD, standard deviation; JPY, Japanese yen

Higher genetic risk of ADHD and birth weight < 2000
g were associated with higher severity of ADHD traits(RR 1.82, 95% CI 1.10–3.01) compared to those bornwith normal birth weight or had lower genetic risk
(Table 3). Similar findings were observed for both inattention and hyperactivity traits (Table 4 and Fig. 1).
In model 1, birth weight under 2000 g and higher genetic risk of ADHD were significantly associated withhigher scores of inattention (RR 1.70, 95% CI 1.02–2.83)
and hyperactivity (RR 2.10, 95% CI 1.10–3.98). These results remain statistically significant after additionallyadjusting for potential confounders in model 3. The corresponding RRs were 1.56 (95% CI 1.07–2.27) for inattention traits and 1.87 (95% CI 1.14–3.06) for
hyperactivity traits (Table 4).

Attrition

We compared background characteristics of children included in the analysis and those excluded due to missing
information on ADHD trait scores and ADHD-PRS. The
proportion of missing ADHD trait scores or ADHD-PRS
was slightly higher among children of younger mother,less educated, and smoker mother (see Additional files 7:

Table S4). However, the Little’s test confirmed thatmissingness of ADHD trait scores and ADHD-PRS werecompletely at random as well as missingness was notcovariate-dependent (see Additional files 8: Table S5).
We performed multiple imputation of ADHD-PRS forchildren with missing information on ADHD-PRS andthe results remained virtually the same (N=796) (seeAdditional files 9 and 10: Tables S6-S7). The effect sizes
remain almost same and significant in the sensitivity
analyses where we considered all missing PRS as highrisk or low risk (see Additional files 11 and 12: Tables
S8-S9).

Discussion
Using a prospective birth cohort study, we found thatbirth weight under 2000 g was significantly associatedwith an increased likelihood of having higher ADHD
trait scores among Japanese children aged 8 to 9 years.
Furthermore, such increased risks were confined but significant for children with relatively higher polygenic riskof ADHD and birth weight under 2000 g. This confirms
our hypothesis that reduced birth weight (<2000 g), together with higher genetic susceptibility for ADHD, areTable 2 Association of birth weight categories with ADHD scores among Japanese children at age 8–9 years (N=796)
Birth weight

Rate ratio (95% confidence intervals)
ADHD total score

Inattention score

Hyperactivity score

Normal birth weight (ref.)

1.00

1.00

1.00

Birth weight 2000–2499 g

0.88 (0.68–1.13)

0.90 (0.70–1.15)

0.83 (0.60–1.15)

Birth weight < 2000 g

1.60 (1.16–2.22)**1.50 (1.10–2.06)*

1.82 (1.17–2.83)**

Model 1†‡Model 2

Normal birth weight (ref.)1.00

Birth weight 2000–2499 g

1.00 (0.77–1.30)

1.00 (0.77–1.29)

0.99 (0.70–1.40)

Birth weight < 2000 g

1.60 (1.21–2.12)**1.51 (1.17–1.95)**

1.85 (1.23–2.77)**§

Model 3

Normal birth weight (ref.)1.00

Birth weight 2000–2499 g

1.00 (0.77–1.29)

1.00 (0.77–1.29)

0.99 (0.71–1.39)

Birth weight < 2000 g

1.57 (1.19–2.09)**

1.49 (1.15–1.94)**

1.78 (1.19–2.67)**

Note: Normal birth weight was defined as birth weight ≥ 2500 g; ref., reference category; values in bold show statistical significance; **p<0.01; *p<0.05†
Model 1 was adjusted for variations in survey time only‡
Model 2 additionally adjusted for gender of child, parity, maternal age, education, pre-pregnancy body mass index, pre-pregnancy smoking status, andalcohol intake§
Model 3 additionally adjusted for father’s age at birth and household annual income

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Table 3 Association of birth weight categories and genetic risk with ADHD total score among Japanese children at age 8–9 years(N=659) (a total of 137 children with missing information on PRS was excluded from this analysis)
Birth weight andgenetic risk of ADHD

Rate ratio (95% confidence intervals)
Model 1†Model 2‡Model 3§

Low risk (ref.)

1.00

1.00

1.00

High risk

0.98 (0.82–1.16)

0.97 (0.83–1.14)

0.98 (0.83–1.15)

Low risk

0.88 (0.56–1.37)

1.04 (0.68–1.61)

1.04 (0.68–1.61)

High risk

0.85 (0.55–1.31)

0.88 (0.56–1.38)

0.87 (0.56–1.37)

Low risk

1.32 (0.83–2.09)

1.32 (0.80–2.19)

1.30 (0.79–2.16)

High risk

1.82 (1.10–3.01)*

1.68 (1.17–2.39)**

1.64 (1.14–2.35)**

Normal birth weight

Birth weight 2000–2499 g

Birth weight <2000 g

Note: Normal birth weight was defined as birth weight ≥ 2500 g; ref., reference category; values in bold show statistical significance; **p<0.01; *p<0.05†
Model 1 was adjusted for variations in survey time only‡
Model 2 additionally adjusted for gender of child, parity, maternal age, education, pre-pregnancy body mass index, pre-pregnancy smoking status, andalcohol intake§
Model 3 additionally adjusted for father’s age at birth and household annual income

Table 4 Association of birth weight categories and genetic risk with inattention and hyperactivity scores among Japanese children
at age 8–9 years (N=659) (a total of 137 children with missing information on PRS was excluded from this analysis)
Birth weight and genetic
risk of ADHD

Rate ratio (95% confidence intervals)
Model 1†Model 2‡Model 3§

Low risk (ref.)

1.00

1.00

1.00

High risk

0.96 (0.81–1.13)

0.95 (0.81–1.12)

0.96 (0.82–1.13)

Low risk

0.89 (0.58–1.35)

1.02 (0.67–1.56)

1.02 (0.67–1.56)

High risk

0.93 (0.62–1.39)

0.96 (0.62–1.50)

0.97 (0.62–1.50)

Low risk

1.21 (0.82–1.77)

1.22 (0.80–1.84)

1.19 (0.78–1.81)

High risk

1.70 (1.02–2.83)*

1.59 (1.09–2.31)*

1.56 (1.07–2.27)*

Low risk (ref.)

1.00

1.00

1.00

High risk

1.02 (0.81–1.29)

1.04 (0.84–1.27)

1.03 (0.84–1.27)

Low risk

0.86 (0.50–1.49)

1.10 (0.62–1.93)

1.10 (0.63–1.91)

High risk

0.68 (0.36–1.28)

0.64 (0.37–1.11)

0.63 (0.37–1.08)

Low risk

1.56 (0.73–3.31)

1.65 (0.75–3.65)

1.64 (0.77–3.48)

High risk

2.10 (1.10–3.98)*

1.94 (1.19–3.17)**1.87 (1.14–3.06)*

Inattention symptoms
Normal birth weight

Birth weight 2000–2499 g

Birth weight <2000 g

Hyperactivity symptoms
Normal birth weight

Birth weight 2000–2499 g

Birth weight <2000 g

Note: Normal birth weight was defined as birth weight ≥ 2500 g; ref., reference category; values in bold show statistical significance; **p<0.01; *p<0.05†
Model 1 was adjusted for variations in survey time only‡
Model 2 additionally adjusted for gender of child, parity, maternal age, education, pre-pregnancy body mass index, pre-pregnancy smoking status, andalcohol intake§
Model 3 additionally adjusted for father’s age at birth and household annual income

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Fig. 1 Multivariable-adjusted rate ratios (RR) and 95% confidence intervals (CI) for the association of birth weight categories and genetic risk with
inattention and hyperactivity scores among Japanese children at age 8–9 years. Note: Normal birth weight was defined as birth weight ≥ 2500 g
and considered as the reference category. Models were adjusted for gender of child, parity, maternal age, education, pre-pregnancy body massindex, pre-pregnancy smoking status, alcohol intake, variations in survey time, father’s age at birth and household annual income

associated with an elevated risk of developing ADHD
traits during childhood. To our knowledge, this is thefirst epidemiological study to evaluate the joint contribution of birth weight and polygenic risk of ADHD on thedomains of inattention and hyperactivity/impulsivity.
Consistent with previous studies [14, 56–58], we foundthat children with birth weight < 2000 g had approximately 50% higher ADHD trait scores than those bornwith normal birth weight. This finding is also consistent
with previous studies conducted among participants
who were clinically diagnosed with ADHD [21, 52, 59].
The effect size for the association remained materiallyunchanged even after adjusting for parental factors andother potential confounders, suggesting an independentassociation between birth weight and ADHD traits. Notably, most previous studies considered 1000 g, 1500 g,
or 2500 g as the threshold for extremely low, very low,or low birth weight categories, respectively. However,
our study focused on intermediate low birth weight categories (i.e., <2000 g; 2000 to 2499 g) and observed ahigher risk of ADHD traits for birth weight under 2000
g. This highlights the need for adopting lower cut-off
points to define low birth weight regarding ADHD risk.
This finding is congruent with previous studies that hypothesized that low birth weight, as an early life adversity (e.g., impaired nourishment in utero), is associatedwith neurodevelopmental difficulties [60]. Althoughbirth weight < 1500 g is classified as very low in clinicalpractice, there were only three children in this categoryin our study. Therefore, we could not evaluate the association between very low birth weight and ADHD traits.
Nevertheless, our findings on the higher severity of
ADHD traits and birth weight under 2000 g have clinicalimportance. This is because the percentages of children
born with birth weight between 1500 and 1999 g or2000 and 2499 g are much larger than children bornwith extremely low or very low birth weight, particularly
in Japan [30]. Thus, our study expands on previous research by evaluating the risk estimates for different categories of birth weight, and by adjusting for a wide
range of potential covariates. In addition, this study provides evidence of the independent association between
low birth weight and ADHD traits among children. It
further emphasizes that the neurodevelopmental progress of children with low birth weight under 2000 gshould be monitored closely, as these children are atheightened risk of developing ADHD traits in earlychildhood. Regarding the two domains of ADHD, wefound that children whose birth weight was less than2000 g had 1.49 times higher scores of inattention traits
and 1.78 times higher hyperactivity scores. This is consistent with a previous study conducted among British
and Brazilian children that observed higher risks of attention difficulties for birth weights under 2500 g [61].
Furthermore, although we found no significant difference between the RRs of inattention and hyperactivity
scores for children with birth weights under 2000 g, wefound that the risk of hyperactivity was slightly higher
than that of inattention (RR 1.78 vs. 1.49). To date, nostudy has considered the direct comparison of the effectsize for hyperactivity traits. Therefore, further studies
are necessary to confirm this finding.
By including an interaction term of polygenic risk andbirth weight categories to the multivariable models, therisk-conferring effect of low birth weight under 2000 g
was found in children with higher genetic risk of ADHD,

Rahman et al. BMC Medicine(2021) 19:229

but not in children of lower genetic risk. This effecthighlights that genetic risk could moderate the association between birth weight and ADHD traits. These results were anticipated, as a previous GWAS conductedamong English children aged 7 years found a positive association between PRS and inattentive traits, hyperactive/impulsive traits, and overall ADHD traits [36]. In
addition, another study conducted among Dutch children found a significant association between ADHDPRS and clinical ADHD [37]. Unfortunately, we could
not compare these effect sizes with previous research, asnone of the prior studies evaluated the joint effect of lowbirth weight and genetic vulnerability on ADHD traits.
Notably, the risk was confined to those born under2000 g in our Japanese sample, while previous studies
from the USA indicated that the risk was observed
among children born under 2500 g [62]. This contrast
may indicate the relevance of racial differences in maternal and child body weight to the study variables. However, since we adjusted for maternal BMI, and thelimited sample size did not allow us to calibrate the effect of small differences in birth weight, future studies
with larger sample sizes are warranted to address this asa global public health issue.
Biological mechanisms

The precise biological mechanisms underlying the association between birth weight and ADHD traits remain
uncertain; however, several hypotheses have been proposed by previous studies. It may be attributed to the inadequate supply of oxygen and necessary nutrienttransport from the mother’s blood to the fetus, known
as prenatal ischemia-hypoxia (PIH), which restricts fetal
growth and alters placental development, causing low
birth weight [63]. PIH causes several functional problems and neuropsychiatric disorders, including thesymptoms of ADHD, through altered brain developmentof the fetus and increased susceptibility to neurodevelopmental problems [63, 64]. In addition, the immune system increases the release of circulating proinflammatory cytokines in response to PIH, resulting insystemic inflammation, which further leads to impaired
neurodevelopment [65]. Another possibility is the role ofhypothalamic-pituitary-adrenal (HPA) axis dysregulation, which is the main component of the stress response and regulation system. This is common among
infants born prematurely or born with low birth weight
due to the insufficient supply of nutrients to the fetus[66]. It has been suggested that the disturbances of the
HPA axis and resulting fetal exposure to excess glucocorticoid levels may influence developmental pathways,
leading to impaired brain development, behavioral impairments, and psychiatric disorders, including ADHD
[67, 68]. Further experimental studies are needed toPage 9 of 13

confirm the causal relationships between low birthweight and ADHD traits.
The underlying factors of the interaction of genetic
risk for ADHD and low birth weight on ADHD traits remains unclear. Therefore, few hypotheses have been suggested to explain this interaction. The complex blend ofnumerous common genetic variants, such as dopaminergic, noradrenergic, and serotoninergic genes, and rare
genetic variants are likely to be implicated in the pathophysiology of ADHD [33, 69, 70]. Higher genetic susceptibility to ADHD may moderate the association between
reduced birth weight and ADHD through impaired inflammatory response [65] and/or dysfunctions of the
HPA axis. Specifically, variations in cytokine genes (IL16
and S100B) may moderate the association between birthweight and the severity of ADHD symptoms [71]. In
addition, polymorphism in the glucocorticoid receptor
gene (NR3C1) moderates the relationship between stressresponses and the severity of ADHD symptoms [66, 72].
This may partially explain the elevated risk of ADHD
among children with higher genetic risk for ADHD andreduced birth weight. Previous studies also revealed thatthe complex interaction of reduced birth weight withboth common and rare genetic variants associated with
ADHD further leads to several neurobiological changes
such as dysfunctions in the brain’s default network, cognitive control systems, and the amygdala-frontal or reward circuit [69]. Such neurobiological changes can befurther implicated in several neuropsychological impairments, including among individuals with ADHD symptoms [69].

Limitations and strengths

Our study had several limitations. First, our study had arelatively small sample size, particularly due to the exclusion of participants without genomic DNA collection.
The generalizability of the finding is limited to thispopulation until it can be replicated. However, the participants included in the HBC study comprised a representative sample of the Japanese population. Second, ourstudy lacked diagnostic assessment of ADHD. The
ADHD traits were measured based on parental reportson their children using ADHD-RS, which may be subject
to social desirability bias. However, the ADHD-RS is a
widely used, valid, and reliable scale to assess the severity of ADHD symptoms [73]. Third, participants with
ADHD-PRS values higher than the median were considered to have a higher genetic risk for ADHD, since PRS
has been standardized in our studied sample. Thus, caution should be taken when generalizing these results, as
higher genetic risk in this study indicates a higher risk
than the average population. Finally, this study was conducted among Japanese children; thus, the findings mayRahman et al. BMC Medicine(2021) 19:229

not be generalized to other races or ethnic groups as thegenetic background is quite variable.
Despite these limitations, our study has several
strengths. The major strengths of this study include theprospective design (birth cohort), lower attrition rate,
and representativeness of the sample, making the resultsof this study applicable to the general Japanese populations. Moreover, this is the first study to investigate theassociation between birth weight and ADHD traits inchildhood while accounting for the genetic risks of developing ADHD. As neurodevelopmental disorders are
genetically complex to understand, the inclusion of asingle gene marker in the model may not be useful.
Since the PRS elucidates the genetic risk through theprediction of complex genetic phenotypes, we accounted
for both common and rare genetic risk variants of eachparticipant through the inclusion of PRS in this study[74].
Clinical implications

Taken together, our findings highlight the importance ofvigilant monitoring of children born with birth weight <2000 g, especially for those with genetic susceptibility to
ADHD. Our findings have several clinical implications.
First, it would help clinicians, based on birth weight information, to decide whether a child is at a greater biological risk of developing ADHD symptoms later on.
Subsequently, the genetic risk for ADHD should beassessed for children with reduced birth weight to identify whether their biological risk may be exacerbated bytheir higher genetic loading for clinical ADHD. Such information would also support clinicians in the early detection of other co-occurring neuropsychiatric diseases,
including autism spectrum disorder [37], anxiety [75],and depression [75, 76].

Conclusions
In conclusion, birth weight < 2000 g is significantly associated with an increase in the severity of inattention,
hyperactivity, and combined ADHD traits among Japanese children aged 8 to 9 years. The presence of higher
genetic risk for ADHD among children with reduced
birth weight further elevates such risk. The introductionof effective interventions aimed at reducing the incidence of low birth weight, especially among children
whose parents have known ADHD symptoms and diagnoses, may play a crucial role in reducing the risk of developing ADHD.
Abbreviations
ADHD: Attention deficit hyperactivity disorder; CI: Confidence interval;
GWAS: Genome-wide association study; HBC: Hamamatsu Birth Cohort for
Mother and Child; HPA: Hypothalamic-pituitary-adrenal; PIH: Prenatal
ischemia-hypoxia; PRS: Polygenic risk scores; RR: Rate ratio; SNPs: Singlenucleotide polymorphisms; WHO: World Health Organization

Page 10 of 13

Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12916-021-02093-3.
Additional File 1. Figure S1 - Distribution of polygenic risk score for
ADHD in HBC study.
Additional File 2. Table S1 - Background characteristics of study
participants according to birth weight categories.
Additional File 3. Figure S2 - Distribution of ADHD total scores
between birth weight categories.
Additional File 4. Figure S3 - Distribution of scores on inattention traits
and hyperactivity traits between birth weight categories.
Additional File 5. Table S2 - Association of birth weight (continuous)and polygenic risk with ADHD scores among Japanese children at age 89 years.
Additional File 6. Table S3 - Independent and interaction effects ofbirth weight categories and polygenic risk score for ADHD with ADHD
total score among Japanese children at age 8-9 years.
Additional File 7. Table S4 - Comparison of background characteristics
of children included in the analysis and those excluded from the analysis
due missing information on ADHD-RS or PRS.
Additional File 8. Table S5 - Little’s test for Missing Completely at
random and test for covariate-dependent missingness.
Additional File 9. Table S6 - Association of birth weight categories andgenetic risk with ADHD total score among Japanese children at age 8-9
years after multiple imputation of missing polygenic risk score for 137
children.
Additional File 10. Table S7 - Association of birth weight categories
and genetic risk with inattention and hyperactivity scores among
Japanese children at age 8-9 years after multiple imputation of missing
polygenic risk score for 137 children.
Additional File 11. Table S8 - Sensitivity analysis for the association ofbirth weight categories and genetic risk with ADHD total score among
Japanese children at age 8-9 years after recoding missing PRS to the endof the spectrum.
Additional File 12. Table S9 - Sensitivity analysis for the association ofbirth weight categories and genetic risk with inattention andhyperactivity scores among Japanese children at age 8-9 years after recoding missing PRS to the end of the spectrum.

Acknowledgements
We are grateful to the study participants for their cooperation andparticipation in the HBC Study. We would like to thank Ms. Chikako
Nakayasu, Ms. Yuko Amma, and Ms. Haruka Suzuki for the data collection
and Ms. Noriko Kodera and Ms. Emi Higashimoto for the administration. We
would also like to thank Editage (www.editage.com) for the English
language editing.
Authors’ contributions
MSR, NaT, and KJT have conceptualized the study. KJT supervised the study.
TI, TN, TH, AO, and KJT collected the data for the study. NaT analyzed andimputed the genetic risk score. MSR performed the statistical analysis. MSR
drafted the manuscript in consultation with KJT and intellectual inputs from
NaT, TI, TN, TH, AO, YN, NT, and KJT. All authors contributed to the criticalrevision of the manuscript. MSR and KJT had primary responsibility for finalcontent. All authors have read and approved the final manuscript.
Funding
This research was funded by Grants-in-Aid for Scientific Research from the
Ministry of Education, Culture, Sports, Science and Technology in Japan(Grant Number 19H03582 awarded to KJT and Grant Number 21K17268 toMSR); Japan Agency for Medical Research and Development (AMED BIRTHDAY Grant Number JP20gk0110039 to KJT); HUSM Grant-in-Aid (Grant Number 101337 to MSR); and Collaborative Research Network for Asian Children
with Developmental Disorders (MSR). The funders had no role in the study

Rahman et al. BMC Medicine(2021) 19:229

Page 11 of 13

design; data collection, analysis, and interpretation of data; and writing of
the manuscript.
11.
Availability of data and materials
Data are not publicly available but can be used for onsite analysis on areasonable request to the corresponding author (Prof. Kenji J. Tsuchiya).

12.

Declarations
Ethics approval and consent to participate
The study procedures were approved by the Hamamatsu University Schoolof Medicine and the University Hospital Ethics Committee (approval number:
17-037, 19-145 and 20-233). Written informed consent was obtained fromeach caregiver for his/her infant’s participation. The study was performed following the Helsinki declaration.

13.

14.

Consent for publication
Not applicable

15.

Competing interests
The authors have declared that no competing interests exist.

16.

Author details
1
Research Centre for Child Mental Development, Hamamatsu University
School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu 431-3192,
Japan. 2United Graduate School of Child Development, Osaka University,
Kanazawa University, Hamamatsu University School of Medicine, Chiba
University and University of Fukui, Hamamatsu, Japan. 3Department of Childand Adolescent Psychiatry, Nagoya University Graduate School of Medicine,
Nagoya, Japan. 4Institute of Psychiatry, Psychology & Neuroscience, King’s
College London, London, UK. 5Queens College and Graduate Center, City
University of New York, New York, NY, USA.

17.

18.

19.

20.
Received: 3 March 2021 Accepted: 11 August 2021
21.
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