Title

Increased Anterior Pelvic Angle Characterizes
the Gait of Children with Attention
Deficit/Hyperactivity Disorder （ADHD）

Author(s)成瀬, 廣亮Citation

大阪大学, 2017, 博士論文

Version Type VoR
URL

https://doi.org/10.18910/61881

rights
Note

Osaka University Knowledge Archive : OUKA
https://ir.library.osaka-u.ac.jp/
Osaka University

RESEARCH ARTICLE

Increased Anterior Pelvic Angle Characterizes
the Gait of Children with Attention
Deficit/Hyperactivity Disorder (ADHD)
Hiroaki Naruse1,2, Takashi X. Fujisawa1,3, Chiho Yatsuga3,4, Masafumi Kubota2,
Hideaki Matsuo2, Shinichiro Takiguchi5, Seiichiro Shimada2, Yuto Imai6,
Michio Hiratani3,6, Hirotaka Kosaka1,3, Akemi Tomoda1,3*

a1111111111
a1111111111
a1111111111
a1111111111
a1111111111

1 Division of Developmental Higher Brain Functions, United Graduate School of Child Development,
University of Fukui, Eiheiji-cho, Yoshida-gun, Fukui, Japan, 2 Division of Physical Therapy andRehabilitation, University of Fukui Hospital, Eiheiji-cho, Yoshida-gun, Fukui, Japan, 3 Research Center forChild Mental Development, University of Fukui, Eiheiji-cho, Yoshida-gun, Fukui, Japan, 4 National Hospital
Organization Hizen Psychiatric Center, Kanzaki-gun, Saga, Japan, 5 Department of Child and Adolescent
Psychological Medicine, University of Fukui Hospital, Eiheiji-cho, Yoshida-gun, Fukui, Japan, 6 Hiratani Clinic
for Developmental Disorders of Children, Kitayotsui, Fukui City, Fukui, Japan* atomoda@u-fukui.ac.jp

Abstract
OPEN ACCESS
Citation: Naruse H, Fujisawa TX, Yatsuga C,
Kubota M, Matsuo H, Takiguchi S, et al. (2017)
Increased Anterior Pelvic Angle Characterizes theGait of Children with Attention Deficit/Hyperactivity
Disorder (ADHD). PLoS ONE 12(1): e0170096.
doi:10.1371/journal.pone.0170096
Editor: Kenji Hashimoto, Chiba Daigaku, JAPANReceived: October 7, 2016
Accepted: December 28, 2016

BackgroundChildren with attention deficit/hyperactivity disorder (ADHD) frequently have motor problems. Previous studies have reported that the characteristic gait in children with ADHD isimmature and that subjects demonstrate higher levels of variability in gait characteristics forthe lower extremities than healthy controls. However, little is known about body movement
during gait in children with ADHD. The purpose of this study was to identify the characteristic
body movements associated with ADHD symptoms in children with ADHD.

Published: January 18, 2017
Copyright: © 2017 Naruse et al. This is an open
access article distributed under the terms of theCreative Commons Attribution License, which
permits unrestricted use, distribution, andreproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data arewithin the paper.
Funding: This work was supported by a Grant-inAid from the Ministry of Education, Culture, Sports,
Science, and Technology (MEXT) of Japan(KAKENHI, https://www.jsps.go.jp/englis/index.
html, grant number 26780516 to Hiroaki Naruse;grant numbers 24300149 and 15K12720 to Akemi
Tomoda). The funders had no role in study design,
data collection and analysis, decision to publish, or
preparation of the manuscript.

Methods
Using a three-dimensional motion analysis system, we compared gait variables in boys with
ADHD (n = 19; mean age, 9.58 years) and boys with typical development (TD) (n = 21;
mean age, 10.71 years) to determine the specific gait characteristics related to ADHD symptoms. We assessed spatiotemporal gait variables (i.e. speed, stride length, and cadence),
and kinematic gait variables (i.e. angle of pelvis, hip, knee, and ankle) to measure body
movement when walking at a self-selected pace.

Results
In comparison with the TD group, the ADHD group demonstrated significantly higher values
in cadence (t = 3.33, p = 0.002) and anterior pelvic angle (t = 3.08, p = 0.004). In multiple
regression analysis, anterior pelvic angle was associated with the ADHD rating scale hyperactive/impulsive scores (β = 0.62, t = 2.58, p = 0.025), but not other psychiatric symptoms in
the ADHD group.

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 2017

1 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Competing Interests: The authors have declaredthat no competing interests exist.

Conclusions
Our results suggest that anterior pelvic angle represents a specific gait variable related to
ADHD symptoms. Our kinematic findings could have potential implications for evaluating
the body movement in boys with ADHD.

Introduction
Attention deficit hyperactivity disorder (ADHD) is the most prevalent childhood onset neurodevelopmental disorder, affecting 7.2% of school-age children [1]. ADHD is characterized byage-inappropriate level of inattention, hyperactivity, and impulsivity that are present prior toage 12 years of age [2]. Additionally, up to 50% of children with ADHD demonstrate a subnormal level of motor performance in their age group [3–6]. Previous studies have reported thatpoor coordination and impairments in fine and gross motor function are caused by difficultyin directing attention and by display of impulsive behavior [7, 8]. To date, motor function,
including gait function, has been clinically assessed as a neurological soft sign in children with
ADHD [9]. Gait function is one of the fundamental motor skills requiring both attention andexecutive function [7, 10]. From MRI studies, children with ADHD have a reduction in volume of the cerebellum [11] and dysfunction of the circuits involving basal ganglia [12]. Thesebrain regions have a role in regulating the balance during gait [13, 14] and gait abnormalities
have been reported in this population. However, there are few reports based on objective measurements using instrumented gait analysis techniques.
Previous studies of gait in children with ADHD have mainly focused on the differences ofgait variables in children with ADHD [15], or age-dependent change in gait that bring children
with ADHD closer to typically developed controls [16]. Step length in children with ADHD
has shown great variability, which becomes much more pronounced during dual tasking, andis reduced to levels approaching those of control subjects after initiating medication [15]. In
addition, a tendency toward a higher value for step frequency has been reported, whichbecomes more pronounced during tasks requiring regulation of gait speed [17]. In contrast,
when walking on the treadmill, no differences in step length and frequency were reported [18].
In brief, the gait characteristics common in children with ADHD are a faster pace and higher
variability with each step during free gait. Furthermore, these gait characteristics appear to be
most prominent when attention is redirected to another task during gait. To date, previous
studies have only measured these characteristics spatiotemporally, although there have been a
few studies measuring body movement during gait. One study reported measurements ofbody movement during a continuous performance seated task, providing objective measurements using a motion analysis system to study factors associated with hyperactive behavior,
which subsequently provided insight into the motor activity of children with ADHD [19].
Three-dimensional (3D) motion analysis, which uses an infrared camera to assess body
movement in terms of gait kinematics, has been helpful for investigating and understanding
body movement to determine disease-specific gait characteristics [20]. For pediatric populations, gait characteristics involving body movement have been identified in children with
autism spectrum disorders (ASD) [21] and developmental coordination disorder (DCD) [22].
For instance, stride length and duration variation, lack of motor smoothness, and head andtrunk posture abnormalities have been reported in children with ASD [23, 24]. Moreover, children with DCD reportedly have shorter stride length, higher cadence, reduced range of motionin the lower extremities, flexion of the upper body, and increased complexity and variation in

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20172 / 13

Increased Anterior Pelvic Angle in Children with ADHD

lower limb movement patterns [25]. As described before, body movements during gait havenot been clarified, although spatiotemporal gait characteristics have been identified in children
with ADHD.
The aim of this study was to identify the kinematic gait characteristics of children with
ADHD to measure the body movement of gait quantitatively. Furthermore, to determine the
ADHD-specific gait characteristics, we sought to assess further whether alterations in gait variables are associated with psychiatric symptom measurements. We predicted that the severityof ADHD is related to the kinematic gait variables that have significant differences between
children with ADHD and children with typical development.

Methods
Ethics statement
The protocol of this study was approved by the Ethics Committee of the University of Fukui(Assurance No. 20130066). After reading a complete description of the study, all participants
and their parents provided written informed consent for participation. The experimental protocol was conducted in accordance with the Declaration of Helsinki.

ParticipantsThis study examined 19 boys with ADHD aged 7–12 years [9.58 ± 1.84 years (mean ± S.D.)].
Each child had been referred to the Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital. Diagnosis was made following DSM-5 [2] and DSM-IV
ADHD items taken from the DSM- IV modified Schedule for Affective Disorders and Schizophrenia for School Age Children—Epidemiologic Version by experienced child and adolescent
psychiatrists (C. Y., S. T., H. K., and A.T.). Children were categorized as ADHD combined
type (n = 11) and ADHD inattentive type (n = 8) using ADHD rating scale Japanese version(ADHD-RS). Participants attended the gait laboratory in Fukui University Hospital where testing took place from October 2013 to August 2014. Most ADHD children in this study (15/19)
were taking medication such as methylphenidate (MPH) 0.7–2.1 mg/kg per day or atomoxetine (ATX) 0.1–0.9 mg/kg per day. For patients taking medication, the washout duration for
MPH was at least 24 hours, and for ATX it was at least 1 week. Furthermore, there were no
children meeting the criteria of ASD or DCD. The control group consisted of 21 boys, typicallydeveloped children aged 7–14 years [10.71 ± 2.05 years (mean ± S.D.)] who were recruited forthis study from the community in Fukui Prefecture, and matched for age and handedness.
Intelligence was evaluated using the Wechsler Intelligence Scale for Children Fourth Edition
or Third Edition (WISC-IV or WISC-III) [26, 27]. Exclusion criteria for all patients were any
history of orthopedic disorder within the prior 6 months, past diagnosis of any psychiatric disorder, head trauma with loss of consciousness, epilepsy, presence or absence of significant fetal
exposure to alcohol or drugs as disclosed by their parents, perinatal or neonatal complications,
neurological disorders, premature birth (gestation 36 weeks), and diagnosis of any bipolar,
psychotic, obsessive—compulsive, or tic disorder at any point in their lifetime.

Questionnaires
To evaluate the severity of ADHD symptoms, we used ADHD-RS, an 18-item questionnaire[28]. Each item was scored by frequency of occurrence (i.e., if the patient “never” presented
the symptom, it is coded as 0; if “occasionally”, 1; “often”, 2; and “always”, 3. Total scores
could range from 0 to 54, with higher scores indicating more severe ADHD symptoms. Several
previous studies reported the presence of comorbid disorders such as ASD or DCD in many

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20173 / 13

Increased Anterior Pelvic Angle in Children with ADHD

children with ADHD [29] who had an alteration of gait [20–25]. Therefore, we assessed for
ASD and DCD traits to identify the specificity related to ADHD symptoms. The Autism Spectrum Quotient Japanese Children’s Version (AQ) [30], a 50-item questionnaire, was completed by a parent to evaluate ASD traits, such as social skills, attention switching, attention todetail, communication, and imagination. The Movement Assessment Battery for Children Second Edition (M-ABC2) [31] (Pearson Ltd., London, UK), which has eight subtests, was used toassess DCD traits, such as manual dexterity, ball skills, and static and dynamic balance.

Gait analysis measurement
We measured gait variables (spatiotemporal and kinematic gait variables) by using a 3D
motion analysis system (VICON-MX) that included ten T10 cameras (Vicon Motion Systems
Ltd., Oxford, UK) and four synchronized force plates (Advanced Mechanical Technology Inc.,
Watertown, MA, USA) placed in the middle of a 10-meter walkway (Fig 1). We placed twocones at each end of the walkway. All cameras and force plates were calibrated before data collection. The sampling rate was set at 100 Hz for cameras and force plates.
Height and weight were measured prior to gait assessment to control for body size differences, and spatiotemporal variables were normalized for each trait in accordance with themethod described by Hof [32]. The 14 mm retro-reflective markers were placed on anatomical
landmarks (front and back of the head, 7th cervical vertebrae, 10th thoracic vertebrae, clavicle,
sternum, the middle of right scapula, shoulder, elbow, wrist, anterior superior iliac spine, posterior superior iliac spine, shank, knee, shin, ankle, heel, and toe) according to the Plug-inGait marker set. Participants were instructed to walk with bare feet to the cone at their own
pace. All participants conducted a few warm-up trials to acclimatize to the gait laboratory setting before placing makers.

Data processing
All trials in which the force plates were hit were checked visually using Vicon NEXUS motion
capture software (Vicon Motion Systems Ltd., Oxford, UK). Error trials, such as ones in whichmarkers fell off or no impact was made on the force plate, were excluded from further analysis.
Marker trajectory was reconstructed and filtered using the Woltring filtering routine with
Vicon NEXUS. The gait cycle started when one foot touched the floor and ended when thatsame foot touched the floor again. Gait variables were normalized as a percentage of the gait
cycle using Polygon 3 (Vicon Motion Systems Ltd., Oxford, UK).
The assessed spatiotemporal variables were walking speed (m/s), stride length (m), andcadence (steps/min). The kinematic variables consisted of joint angle (degrees) in the sagittal
plane for pelvis (Fig 2), hip, knee, and ankle. Peak values in each kinematic variable wereextracted. The averages of five trials and right-and-left data were calculated for each participant
to maintain the reliability of data from the 3D motion analysis system [33].

Statistical analysis
Demographic data and gait variables were tested using independent t test and clinical symptoms were tested using ANCOVA with age and FISQ as covariates. To examine the correlation
between ADHD symptoms based on ADHD-RS scores, and gait variables demonstrating significant differences for both groups, partial correlation coefficients were calculated with FSIQ
as a covariate. Additionally, gait variables in children are multifactorial, with contributions
from developmental indices (i.e. age and cognitive function) [20, 34] and neurodevelopmental
symptoms (i.e. ASD traits or DCD traits) [21–25]. Therefore, to investigate the substantial contribution of ADHD traits to gait characteristics for other variables (age, FSIQ, ASD, and/or

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20174 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Fig 1. Three-dimensional motion analysis system. The system is comprised of 10 strobe cameras mounted
from the ceiling and four force plates placed in the middle of the walkway. The white circles represent 14 mm
reflective markers according to the Plug-in-Gait marker set.
doi:10.1371/journal.pone.0170096.g001

DCD traits), we used standard multiple regressions by forced entry method and investigatedtheir relationship. To test our hypothesis that psychiatric symptom measurements could significantly predict gait variables, we performed a multiple regression analysis using psychiatric
symptom measures showing significant between-group differences as independent variables,
and the gait variables showing significant between-group differences as dependent variables.
The statistical threshold was set at p < 0.05 and used the Bonferroni adjustment for multiple

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 2017

5 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Fig 2. Schema for pelvic angle in sagittal angle during gait. A shows the pelvic angle. B shows the pelvic angle during gait. Ant: anterior;
post: posterior.
doi:10.1371/journal.pone.0170096.g002

comparisons. All analyses were conducted using the Statistical Package for the Social Sciences
20 software (SPSS Inc., Chicago, IL, USA).

Results
Demographic and clinical characteristics for the study participants are listed in Table 1. Incomparison with the TD group, the ADHD group scored significantly lower on the FSIQ
(t = 2.70, p = 0.011). Significant differences were found in the measures of severity of ADHD
symptoms (ADHD-RS total score, F [1, 36] = 101.18, p < 0.001; Inattentive score, F [1,36] = 79.92, p < 0.001; Hyperactive/Impulsive score, F [1, 36] = 42.08, p < 0.001), ASD traits(AQ total; F [1, 36] = 18.95, p < 0.001), and DCD traits (M-ABC2 total; F [1, 36] = 3.76,
p = 0.060) between the two groups.
Gait variables are shown in Table 2. Between-group comparisons for spatiotemporal andkinematic gait variables were assessed by independent t test. In comparison with the TD
group, the ADHD group showed significantly higher cadence in spatiotemporal variables(t = 3.33, p = 0.002), and also showed significantly higher anterior pelvic angle (t = 3.08,
p = 0.004). Normalization of the data according to Hof [32] did not alter any of the findings
for between-group differences in gait variables. Therefore, we adopted the data before normalization for statistical analysis.
To assess the relationship between gait variables and ADHD symptoms, we explored thecorrelation between the gait variables and ADHD-RS scores beginning with the inter-correlation of the gait variables. There was no significant correlation between the kinematic variables
and cadence as a spatiotemporal variable (r = 0.17, p = 0.287). Therefore, we adopted pelvic
angle and cadence as the representative gait variables for the following correlation analysis
with ADHD symptoms. Since we observed a significant difference in FSIQ between groups,
we calculated partial correlation coefficients between these gait variables and ADHD symptoms, controlling for FSIQ. As shown in Fig 3A, we observed significant partial correlation
coefficients between cadence and ADHD-RS total scores in the entire group (ADHD and TD)

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20176 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Table 1. Demographic and clinical characteristics of ADHD and TD groups.
Variables

Group
ADHD

TD

Statistics

p-value

Subject (n)1921

Age (years)†

9.58 (1.84)

10.71 (2.05)

1.85

0.073

Handedness (n, L/R)

3/16

3/18

0.01

0.894

Height (m) †1.37 (0.13)

1.46 (0.14)

1.97

0.056

Weight (kg) †32.79 (8.82)

37.68 (12.61)

1.42

0.163

FSIQa, †98.05 (13.16)

108.71 (11.68)

2.70

0.011*

Total

28.79 (9.08)

2.90 (3.11)

101.18<0.001**

Inattentive

17.84 (5.80)

2.14 (2.39)

79.92<0.001**Hyperactive /Impulsive

11.37 (6.08)

0.76 (1.18)

42.08<0.001**

AQ total

20.28 (5.06)

12.10 (4.12)

18.95<0.001**

M-ABC2 total

9.74 (2.42)

12.48 (2.44)

3.76

0.060

Demographic characteristics

Clinical characteristics‡
ADHD-RS

Data are presented as mean (SD). a: FSIQ data were based on the WISC-IV (n = 37) and WISC-III (n = 3). Data were not available for one subject becauseof a missing value for AQ (ADHD, 1 subject). FSIQ = Full Scale Intelligence Quotient; AQ = The Autism Spectrum Quotient-Children’s Version;
M-ABC2 = Movement Assessment Battery for Children Second edition.
†
Group difference was tested by independent t-test.
‡

Group difference was tested by ANVOCA with age and FSIQ as covariate.

The statistical threshold is set at * p < 0.05 and ** p < 0.01.
doi:10.1371/journal.pone.0170096.t001(r = 0.38, p = 0.018), whereas there were no significant correlations between these variables ineach group separately (ADHD: r = -0.10, p = 0.690; TD: r = 0.03, p = 0.912). In contrast, asshown in Fig 3B, we observed significant partial correlation coefficients between pelvic angle
and ADHD-RS total score in the ADHD group (r = 0.54, p = 0.021) as well as in the wholegroup (r = 0.65, p < 0.001), whereas no significant correlation was observed in the TD group
Table 2. Differences in gait variables between ADHD and TD groups.
Variables

Group
ADHD (n = 19)

TD (n = 21)

Statistics

p-value

Spatiotemporal variables
Walking Speed (m/s)

1.21 (0.61)

1.19 (0.18)

0.61

0.546

Stride length (m)1.17 (0.15)

1.21 (0.18)

-0.91

0.369

125.26 (6.72)

117.40 (8.19)

3.33

0.002**

Cadence (steps/min)
Kinematic variables (degree)
Anterior pelvic angle

13.13 (5.24)

8.59 (4.36)

3.08

0.004**

Hip flexion angle

34.04 (6.87)

28.72 (5.97)

2.65

0.012

Hip extension angle

11.93 (5.42)

15.56 (6.57)

2.05

0.047

Knee flexion angle

54.60 (3.93)

54.55 (6.48)

0.11

0.915

Knee extension angle

1.30 (3.57)

2.79 (3.84)

1.20

0.237

Ankle dorsal-flexion angle

15.28 (4.01)

15.97 (5.40)

-0.44

0.662

Ankle Plantar-flexion angle

14.79 (5.51)

14.72 (6.27)

0.10

0.919

Data are shown as mean (±SD). Group differences were tested by independent t test. The statistical threshold is set at ** p < 0.005 using the Bonferroni
adjustment for multiple comparisons.
doi:10.1371/journal.pone.0170096.t002

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20177 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Fig 3. Partial correlation analysis of gait variables and ADHD rating scale. These show correlation between ADHD-RS and cadence(A), or pelvic angle (B) with FSIQ as covariate. Blue circle and solid line: TD group; Red circle and solid line: ADHD group; Black dotted line:
all subjects.
doi:10.1371/journal.pone.0170096.g003(r = 0.24, p = 0.306). These results suggest the possibility that pelvic angle is specifically associated with the severity of ADHD symptoms.
Next, we determined the core set of variables to develop an explanatory model of gait. We
then performed multiple regression analyses to further characterize the relationship between
psychiatric symptom measures and gait variables such as cadence and pelvic angle. For
cadence, as shown in Table 3, a higher cadence was associated with a decreased age (β = -0.34,
t = -2.08, p = 0.046) in all subjects, although there were no associations with any psychiatric
symptoms. For pelvic angle, however, a higher anterior pelvic angle was associated with anincreased ADHD-RS score in all subjects. As indicated in Table 4, our analysis showed that
Table 3. Regression model statistics and coefficients of variables for cadence.
All (n = 40)
Independentβ

ADHD (n = 19)βt-valueTD (n = 21)βt-valuet-value

ADHD-RS
Inattentive

0.165

0.60

-0.46

-1.12

0.02

0.05

Hyperactive/impulsive

0.136

0.56

0.02

0.07

-0.06

-0.18

Age

-0.34*

-2.08

-0.15

-0.45

-0.43

-1.55

FSIQ

0.06

0.31

0.09

0.31

0.07

0.234

AQ

-0.07

-0.36

-0.50

-1.50

-0.14

-0.46

M-ABC2

-0.19

-1.07

-0.25

-0.71

-0.17

-0.64

Adjusted R2

0.18

-0.06

-0.21

Standardized regression coefficients (β), t values, and R2 are reported. The corrected statistical threshold is set at * p < 0.05. For the analysis, one subject
data was not available due to a missing value in AQ (ADHD, 1 subject).
doi:10.1371/journal.pone.0170096.t003

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20178 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Table 4. Regression model statistics and coefficients of variables for anterior pelvic angle.
All (n = 40)
Independentβ

ADHD (n = 19)βt-valueTD (n = 21)βt-valuet-value

ADHD-RS
Inattentive

0.06

0.23

0.02

0.05

0.44

1.67

Hyperactive/impulsive

0.52*

2.40

0.62*

2.58

-0.47

-1.52

Age

0.03

0.21

0.09

0.32

-0.09

-0.35

FSIQ

0.35*

2.16

0.32

1.25

0.59*

2.27

AQ

0.14

0.82

0.15

0.52

0.27

0.99

M-ABC2

-0.15

-0.91

-0.23

-0.76

-0.18

-0.75

Adjusted R2

0.33**

0.21

-0.07

Standardized regression coefficients (β), t values, and R2 are reported. The corrected statistical threshold is set at * * p < 0.01 and * p < 0.05. For the
analysis, one subject data was not available due to a missing value in AQ (ADHD, 1 subject).
doi:10.1371/journal.pone.0170096.t004

the severity of ADHD symptom measures, based on ADHD-RS hyperactive/impulsive score(β = 0.52, t = 2.40, p = 0.023), and cognitive ability, based on FSIQ (β = 0.35, t = 2.16,
p = 0.038), were significant predictors for anterior pelvic angle in all subjects, and explained
approximately 33% of the variance in the pelvic angle (adjusted R2 = 0.33, F [6,32] = 4.15,
p = 0.003). However, anterior pelvic angle had no association with AQ (β = 0.14, t = 0.82,
p = 0.419) or M-ABC2 (β = -0.15, t = -0.91, p = 0.368). In the ADHD group, anterior pelvic
angle also had an association with ADHD-RS hyperactive/impulsive score (β = 0.62, t = 2.58,
p = 0.025), and explained approximately 21% of the variance in the pelvic angle (adjusted R2 =0.21, F [6,11] = 1.76, p = 0.197). In the TD group, anterior pelvic angle had an association withFSIQ (β = 0.59, t = 2.27, p = 0.040).

Discussion
The purpose of the present study was to determine whether spatiotemporal and kinematic gaitvariables differ between controls and children with ADHD by using a 3D motion analysis system. Our results demonstrated that children with ADHD exhibit higher values for cadence
and anterior pelvic angle compared to healthy controls, and that pelvic angle had a significant
positive correlation with the severity of ADHD symptoms. These results suggest that children
with ADHD have the characteristics of a high frequency gait cycle and an increased anterior
pelvic angle. Furthermore, in multiple regression analysis, anterior pelvic angle was associatedwith the severity of ADHD symptoms, whereas there was no association with ASD or DCD
symptoms in children with ADHD. Additionally, the variable of cadence showed no association with any psychiatric traits. These findings suggest that increased anterior pelvic angle during gait is a specific variable of ADHD symptoms.
As expected, cadence, a spatiotemporal variable, had a positive correlation with ADHD
symptoms in all subjects. A recent study reported that children with ADHD walked faster andwith a higher cadence and that ADHD symptoms were associated with increased cadence inthe “fast walking condition” [17]. Although we could not determine the underlying mechanism for higher cadence in children with ADHD, one possible explanation is that difficulties
in timing regulation may be attributed to cerebellar dysfunction [35], which is one area consistently implicated as a neural basis for ADHD [36]. Nevertheless, it is noteworthy that many
previous studies have reported gait abnormalities in spatiotemporal variables, including higher
cadence, in children with other neurodevelopmental disorders, such as ASD or DCD [21, 22].
As demonstrated by the results of the multiple regression analysis in the present study, we did

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 20179 / 13

Increased Anterior Pelvic Angle in Children with ADHD

not observe any significant association between cadence and ADHD symptoms or other psychiatric traits of ASD and DCD, suggesting that cadence may not be a variable specificallyrelated to ADHD pathogenesis. Instead, spatiotemporal gait variables, including cadence, may
reflect heterogeneous clinical conditions between ADHD and other neurodevelopmental disorders, making it difficult to determine whether cadence is a critical gait characteristic related
to ADHD symptoms.
Curiously, in the present investigation we found a positive association between pelvic angle
as a kinematic gait variable and ADHD symptoms. Why pelvic angle might be associated with
ADHD is an interesting question. Pelvic movement is essential as an inherent mechanism of
postural control in normal children [37] and has often been observed clinically to estimate thebiomechanics of different gait patterns [38]. An increased anterior pelvic angle is necessary tomove the center of gravity forward in order to walk efficiently [39]. Specifically, pelvic angle isdetermined by the muscle strength or stiffness around the pelvis needed to maintain upright
posture, which is regulated by the basal ganglia and/or cerebellar vermis [14, 40]. Increased
anterior tilt angle has been observed in infants, implicating an immature neuromuscular system [37, 41]. A meta-analysis of functional magnetic resonance imaging (fMRI) studies in children with ADHD revealed a neurological delay in basal ganglia development [42]. In children
with ADHD, meta-analysis suggested that deregulation of front-basal ganglia-parietal network
may cause the deficit of attention and inhibition [12]. These brain networks, known as the
motor loop, involve the basal ganglia and have a role in generating the gait pattern and control
for muscle tone to regulate gait and posture. Moreover, meta-analysis of structural imaging
reported a volume reduction of the cerebellar vermis [43], which has been related to inattentive symptoms [44] and verbal working memory performance in children with ADHD. The
cerebellum has a role of maintaining equilibrium during gait. Another previous study reported
that step variability decreases with age. Together, these studies suggest that immature gait isrelated to delayed brain development [15]. Although we have discussed this finding in terms ofa potential cause and effect mechanism, it must be emphasized that our evidence only supports
an association.
Moreover, as suggested by multiple regression analysis, we have observed that anterior pelvic angle shows an association with the severity of ADHD symptoms, although it shows no
association with ASD or DCD symptoms, suggesting that pelvic angle may be one of the candidates for gait-specific variables in ADHD. To the best of our knowledge, the present study isthe first to clarify the association between kinematic gait variables and the severity of ADHD
symptoms.
There were several limitations of this study. The first major limitation is the small sample
size in this study. The cleanliness of the sample (all drug-naive, very narrow age range, noother form of ASD or DCD traits, matched socio-economic status, past histories of sports
activities) might have compensated for that shortcoming, at least in part, by reducing error
variance. To generalize our results, studies involving a larger number of participants must be
conducted to compare with children with ASD or DCD. Second, this study used a cross-sectional design that precludes identification of causal links between ADHD and gait variables.
Longitudinal studies must be conducted to investigate how gait variable differences associatedwith ADHD change in response to treatment programs aimed at diminishing signs of ADHD.
In conclusion, increased anterior pelvic angle was associated with increased severity of
ADHD symptoms. These preliminary findings could have potential implications for our
understanding of gait control related to ADHD and a possible contribution for evaluating the
body movement in boys with ADHD. Combining 3D motion analysis for body movementwith neurophysiological indicators of brain activity should prove fruitful in further elucidating
the mechanisms underlying motor control in children with ADHD.

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 201710 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Supporting Information
S1 Dataset. The demographic, psychology assessments and gait data.
(XLSX)

Acknowledgments
This work was supported by a Grant-in-Aid from the Ministry of Education, Culture, Sports,
Science, and Technology (MEXT) of Japan (KAKENHI, https://www.jsps.go.jp/english/index.
html, grant number 26780516 to Hiroaki Naruse; grant numbers 24300149 and 15K12720 toAkemi Tomoda). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author Contributions
Conceptualization: MH AT.
Formal analysis: HN TXF.
Investigation: HN MK HM ST SS YI.
Methodology: MH CY AT.
Supervision: MH HK.
Writing – original draft: HN TXF AT.

References
1.

Thomas R, Sanders S, Doust J, Beller E, Glasziou P. Prevalence of attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. Pediatrics. 2015; 135(4):e994–1001. doi: 10.1542/peds.
2014-3482 PMID: 25733754

2.

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th Edition.
4th ed. Washington, D.C.: American Psychiatric Press; 2013.

3.

Pitcher TM, Piek JP, Hay DA. Fine and gross motor ability in males with ADHD. Developmental medicine and child neurology. 2003; 45(8):525–35. PMID: 12882531

4.

Karatekin C, Markiewicz SW, Siegel MA. A preliminary study of motor problems in children with attention-deficit/hyperactivity disorder. Percept Mot Skills. 2003; 97(3 Pt 2):1267–80. doi: 10.2466/pms.
2003.97.3f.1267 PMID: 15002871

5.

Tervo RC, Azuma S, Fogas B, Fiechtner H. Children with ADHD and motor dysfunction compared withchildren with ADHD only. Developmental medicine and child neurology. 2002; 44(6):383–90. PMID:
12088306

6.

Kadesjo B, Gillberg C. Attention deficits and clumsiness in Swedish 7-year-old children. Developmental
medicine and child neurology. 1998; 40(12):796–804. PMID: 9881675

7.

Konicarova J, Bob P, Raboch J. Balance deficits and ADHD symptoms in medication-naive schoolaged boys. Neuropsychiatr Dis Treat. 2014; 10:85–8. doi: 10.2147/NDT.S56017 PMID: 24476629

8.

Piek JP, Barrett NC, Dyck MJ, Reiersen AM. Can the Child Behavior Checklist be used to screen formotor impairment? Developmental medicine and child neurology. 2010; 52(2):200–4. doi: 10.1111/j.
1469-8749.2009.03326.x PMID: 20015254

9.

Patankar VC, Sangle JP, Shah HR, Dave M, Kamath RM. Neurological soft signs in children with attention deficit hyperactivity disorder. Indian J Psychiatry. 2012; 54(2):159–65. doi: 10.4103/0019-5545.
99540 PMID: 22988324

10.

Woollacott M, Shumway-Cook A. Attention and the control of posture and gait: a review of an emerging
area of research. Gait & posture. 2002; 16(1):1–14.

11.

Seidman LJ, Valera EM, Makris N. Structural brain imaging of attention-deficit/hyperactivity disorder.
Biol Psychiatry. 2005; 57(11):1263–72. doi: 10.1016/j.biopsych.2004.11.019 PMID: 15949998

12.

Hart H, Radua J, Nakao T, Mataix-Cols D, Rubia K. Meta-analysis of functional magnetic resonanceimaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 201711 / 13

Increased Anterior Pelvic Angle in Children with ADHD

specific, stimulant medication, and age effects. JAMA psychiatry. 2013; 70(2):185–98. doi: 10.1001/
jamapsychiatry.2013.277 PMID: 23247506
13.

Morton SM, Bastian AJ. Mechanisms of cerebellar gait ataxia. Cerebellum. 2007; 6(1):79–86. doi: 10.
1080/14734220601187741 PMID: 17366269

14.

Takakusaki K, Oohinata-Sugimoto J, Saitoh K, Habaguchi T. Role of basal ganglia-brainstem systems
in the control of postural muscle tone and locomotion. Prog Brain Res. 2004; 143:231–7. doi: 10.1016/
S0079-6123(03)43023-9 PMID: 14653168

15.

Leitner Y, Barak R, Giladi N, Peretz C, Eshel R, Gruendlinger L, et al. Gait in attention deficit hyperactivity disorder: effects of methylphenidate and dual tasking. Journal of neurology. 2007; 254(10):1330–8.
doi: 10.1007/s00415-006-0522-3 PMID: 17401735

16.

Manicolo O, Grob A, Lemola S, Hagmann-von Arx P. Age-related decline of gait variability in children
with attention-deficit/hyperactivity disorder: Support for the maturational delay hypothesis in gait. Gait
Posture. 2016; 44: 245–249. doi: 10.1016/j.gaitpost.2015.12.012 PMID: 27004666

17.

Papadopoulos N, McGinley JL, Bradshaw JL, Rinehart NJ. An investigation of gait in children with
Attention Deficit Hyperactivity Disorder: a case controlled study. Psychiatry Res. 2014; 218(3):319–23.
doi: 10.1016/j.psychres.2014.04.037 PMID: 24837426

18.

Buderath P, Gartner K, Frings M, Christiansen H, Schoch B, Konczak J, et al. Postural and gait performance in children with attention deficit/hyperactivity disorder. Gait & posture. 2009; 29(2):249–54.

19.

Teicher MH, Ito Y, Glod CA, Barber NI. Objective measurement of hyperactivity and attentional problems in ADHD. J Am Acad Child Adolesc Psychiatry. 1996; 35(3):334–42. doi: 10.1097/00004583199603000-00015 PMID: 8714322

20.

Chester VL, Tingley M, Biden EN. A comparison of kinetic gait parameters for 3–13 year olds. Clin Biomech (Bristol, Avon). 2006; 21(7):726–32.

21.

Calhoun M, Longworth M, Chester VL. Gait patterns in children with autism. Clin Biomech (Bristol,Avon). 2011; 26(2):200–6.

22.

Deconinck FJ, De Clercq D, Savelsbergh GJ, Van Coster R, Oostra A, Dewitte G, et al. Differences ingait between children with and without developmental coordination disorder. Motor control. 2006; 10(2):125–42. PMID: 16871009

23.

Nayate A, Tonge BJ, Bradshaw JL, McGinley JL, Iansek R, Rinehart NJ. Differentiation of high-functioning autism and Asperger’s disorder based on neuromotor behaviour. Journal of autism and developmental disorders. 2012; 42(5):707–17. doi: 10.1007/s10803-011-1299-5 PMID: 21660499

24.

Nobile M, Perego P, Piccinini L, Mani E, Rossi A, Bellina M, et al. Further evidence of complex motor
dysfunction in drug naive children with autism using automatic motion analysis of gait. Autism: the international journal of research and practice. 2011; 15(3):263–83.

25.

Rosengren KS, Deconinck FJ, Diberardino LA 3rd, Polk JD, Spencer-Smith J, De Clercq D, et al. Differences in gait complexity and variability between children with and without developmental coordination
disorder. Gait & posture. 2009; 29(2):225–9.

26.

Wechsler D. Wechsler Intelligence Scale for Children, third edition. The Psychological Corporation,
San Antonio, TX. 1991.

27.

Wechsler D. Wechsler Intelligence Scale for Children, fourth edition. The Psychological Corporation,
San Antonio, TX. 2003.

28.

Zhang S, Faries DE, Vowles M, Michelson D. ADHD Rating Scale IV: psychometric properties from amultinational study as a clinician-administered instrument. International journal of methods in psychiatric research. 2005; 14(4):186–201. PMID: 16395872

29.

Reiersen AM, Constantino JN, Todd RD. Co-occurrence of motor problems and autistic symptoms in
attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2008; 47(6):662–72. doi:
10.1097/CHI.0b013e31816bff88 PMID: 18434922

30.

Auyeung B, Baron-Cohen S, Wheelwright S, Allison C. The Autism Spectrum Quotient: Children’s Version (AQ-Child). Journal of autism and developmental disorders. 2008; 38(7):1230–40. doi: 10.1007/
s10803-007-0504-z PMID: 18064550

31.

Henderson SE. Movement Assessment Battery for Children—Second Edition. London: Pearson.
2007.

32.

Hof AL. Scaling gait data to body size. Gait & posture. 1996; 4(3):222–3.

33.

Tsushima H, Morris ME, McGinley J. Test-retest reliability and inter-tester reliability of kinematic datafrom a three-dimensional gait analysis system. J Jpn Phys Ther Assoc. 2003; 6(1):9–17. doi: 10.1298/
jjpta.6.9 PMID: 25792928

34.

Piek JP, Dyck MJ, Francis M, Conwell A. Working memory, processing speed, and set-shifting in children with developmental coordination disorder and attention-deficit-hyperactivity disorder.

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 201712 / 13

Increased Anterior Pelvic Angle in Children with ADHD

Developmental medicine and child neurology. 2007; 49(9):678–83. doi: 10.1111/j.1469-8749.2007.
00678.x PMID: 17718824
35.

Ivry RB, Keele SW. Timing functions of the cerebellum. J Cogn Neurosci. 1989; 1(2):136–52. doi: 10.
1162/jocn.1989.1.2.136 PMID: 23968462

36.

Berquin PC, Giedd JN, Jacobsen LK, Hamburger SD, Krain AL, Rapoport JL, et al. Cerebellum in attention-deficit hyperactivity disorder: a morphometric MRI study. Neurology. 1998; 50(4):1087–93. PMID:
9566399

37.

Assaiante C. Development of locomotor balance control in healthy children. Neurosci Biobehav Rev.
1998; 22(4):527–32. PMID: 9595565

38.

Heyrman L, Feys H, Molenaers G, Jaspers E, Monari D, Meyns P, et al. Three-dimensional head andtrunk movement characteristics during gait in children with spastic diplegia. Gait & posture. 2013; 38(4):770–6.

39.

Sutherland DH, Olshen R, Cooper L, Woo SL. The development of mature gait. The Journal of boneand joint surgery American volume. 1980; 62(3):336–53. PMID: 7364807

40.

Fukuyama H, Ouchi Y, Matsuzaki S, Nagahama Y, Yamauchi H, Ogawa M, et al. Brain functional activity during gait in normal subjects: a SPECT study. Neurosci Lett. 1997; 228(3):183–6. PMID: 9218638

41.

Thummerer Y, von Kries R, Marton MA, Beyerlein A. Is age or speed the predominant factor in thedevelopment of trunk movement in normally developing children? Gait & posture. 2012; 35(1):23–8.

42.

Nakao T, Radua J, Rubia K, Mataix-Cols D. Gray matter volume abnormalities in ADHD: voxel-based
meta-analysis exploring the effects of age and stimulant medication. The American journal of psychiatry. 2011; 168(11):1154–63. doi: 10.1176/appi.ajp.2011.11020281 PMID: 21865529

43.

Valera EM, Faraone SV, Murray KE, Seidman LJ. Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biol Psychiatry. 2007; 61(12):1361–9. doi: 10.1016/j.biopsych.2006.
06.011 PMID: 16950217

44.

Ashtari M, Kumra S, Bhaskar SL, Clarke T, Thaden E, Cervellione KL, et al. Attention-deficit/hyperactivity disorder: a preliminary diffusion tensor imaging study. Biol Psychiatry. 2005; 57(5):448–55. doi: 10.
1016/j.biopsych.2004.11.047 PMID: 15737658

PLOS ONE | DOI:10.1371/journal.pone.0170096 January 18, 201713 / 13