Comparability of activity monitors used in Asian and Western-country studies for assessing free-living sedentary behaviour
Comparability of activity monitors used in Asian and Western-country studies for assessing free-living sedentary behaviour
Satoshi Kurita 0 1
Shohei Yano 0 1
Kaori Ishii 1
Ai Shibata 1
Hiroyuki Sasai 1
Yoshio Nakata 1
Noritoshi Fukushima 1 2
Shigeru Inoue 1 2
Shigeho Tanaka 1
Takemi Sugiyama 1
Neville Owen 1
Koichiro Oka 1
0 Graduate School of Sport Sciences, Waseda University , Tokorozawa, Saitama , Japan , 2 Faculty of Sport Sciences, Waseda University , Tokorozawa, Saitama , Japan , 3 Faculty Health and Sport Sciences, University of Tsukuba , Tsukuba, Ibaraki , Japan , 4 Faculty of Medicine, University of Tsukuba , Tsukuba, Ibaraki , Japan
1 Editor: FrancËois Criscuolo, Centre National de la Recherche Scientifique , FRANCE
2 Department of Preventive Medicine and Public Health, Tokyo Medical University, Shinjuku-ku, Tokyo, Japan, 6 Department of Nutritional Sciences, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Shinjuku-ku, Tokyo, Japan, 7 Institute for Health & Ageing, Australian Catholic University , Melbourne, Victoria , Australia , 8 Behavioural Epidemiology Laboratory, Baker IDI Heart and Diabetes Institute , Melbourne, Victria , Australia , 9 Swinburne University of Technology , Melbourne, Victoria , Australia
This study aims to compare the outputs of the waist-worn Active style Pro HJA-350IT (ASP; used in studies with Asian populations), the waist-worn ActiGragh™GT3X+ using the normal filter (GT3X+) and the thigh-worn activPAL3 (AP) in assessing adults' sedentary behaviour (total sedentary time, number of breaks) under free-living conditions. Fifty healthy workers wore the three monitors simultaneously during their waking hours on two days, including a work day and a non-work day. Valid data were at least 10 hours of wearing time, and the differences between monitors on the sedentary outputs using the AP as criterion measurement were analyzed by ANOVA. The number of participants who had complete valid data for work day and non-work day was 47 and 44, respectively. Total sedentary time and breaks estimated by the AP were respectively 466.5 ± 146.8 min and 64.3 ± 24.9 times on the work day and 497.7 ± 138.3 min and 44.6 ± 15.4 times on the non-work day. In total sedentary time, the ASP estimated 29.7 min (95%CI = 7.9 to 51.5) significantly shorter than the AP on the work day but showed no significant difference against the AP on the non-work day. The GT3X+ estimated 80.1 min (54.6 to 105.6) and 52.3 (26.4 to 78.2) significantly longer than the AP on the work day and the non-work day, respectively. For the number of breaks from sedentary time, on both days, the ASP and the GT3X+ estimated significantly more than the AP: 14.1 to 15.8 times (6.3 to 22.5) for the ASP and 27.7 to 28.8 times (21.8 to 34.8) for the GT3X+. Compared to the AP as the criterion, the ASP can underestimate total sedentary time and the GT3X+ can overestimate it, and more so at the lower levels of sedentary time. For breaks
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: This work was supported Grants-in-Aid
for Scientific Research from the Japan Society for
the Promotion of Science (No. 26242070) (https://
kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT26242070/) to KO, a grant from industry to support
private universities building up their foundations of
strategic researchfrom Ministry of education(No.
S1511017): (http://www.mext.go.jp/en/) to KO, the
from sedentary time, compared to the AP, both the GT3X+ the ASP can overestimate.
Australian Academy of Sciences: (https://www.
science.org.au/) to NO, the Japan Society for the
Promotion of Science: (https://www.jsps.go.jp/
english/index.html) to NO, NHMRC Centre of
Research Excellence Grant (#1057608): (https://
centres-research-excellence-cre) to NO, NHMRC
Senior Principal Research Fellowship (#1003960):
(https://www.nhmrc.gov.au/grants-funding/applyfunding/research-fellowships) to NO and the
Victorian Government's Operational Infrastructure
Support Program: (https://www2.health.vic.gov.au/
about/clinical-trials-and-research/operationalinfrastructure-support) to NO. The funders had no
role in study design, data collection and analysis,
decision to publish, or preparation of the
Competing interests: The authors have declared
that no competing interests exist.
Since the harmfulness of sedentary behaviour was identified [
], reducing sedentary behaviour
have been an important goal to enhance public health [
] because lifestyles are becoming
increasingly less active [
]. With this goal in mind, there has been increasing research on the
prevalence and determinants of sedentary behaviour and interventions to reduce sitting time
[4±7]. When measuring sedentary behaviour, considering that this is ubiquitous in daily
routines, device-based objective measures have certain advantages over self-report instruments [
]. Such objective measures enable researchers to determine patterns characterized by total
sedentary time and breaks in sedentary time.
So far, various devices have been used in studies, which makes it difficult to compare or
synthesize findings from different countries or populations. More precise international
comparability is important for global health promotion to estimate relative risk of sedentary
behaviour among the countries or populations and identify country or population specific
correlates of sedentary behaviour. These have been examined almost exclusively through the
use of self-report instruments [10±12]. In this context, there is the need for a better
understanding of the comparability between the outputs of the different activity monitors used in
The activPAL3 (AP; PAL Technologies Ltd., Glasgow, UK) is an inclinometer, which is
attached to wearer's thigh, and is known to have high level of accuracy in characterizing
postureÐdiscriminating sitting/reclining, standing and stepping [13±15]. It is often used as a
criterion measure of sedentary behaviour under free-living conditions [
]. The ActiGraph™
(ActiGraph LLC, Pensacola, Florida, USA) is a commonly-used brand of accelerometer for
measuring physical activity and sedentary behaviour. One of the versions, GT3X+, can be
worn on a variety of locations on the body (wrist, waist, arm, thigh or ankle), and a waist-worn
GT3X+ has less accuracy than the AP in assessing sedentary behaviour [
] but has been
used in some cohort studies . More recently, the Active style Pro HJA-350IT (ASP; Omron
Health Care Co., Ltd., Kyoto, Japan), a waist-worn accelerometer released in 2008, has been
used to assess sedentary behaviour in studies that have been conducted primarily with Asian
The ASP is commonly available and affordable device, particularly in the context of the
modest funding that can be available to researchers. The cost of the ASP is approximately
$US150 per unit which is less expensive than the GT3X+ ($US250 per unit) and AP
(approximately $US400 per unit). The ASP processes raw input signal using algorithms containing a
specific equation for sedentary activities, which have been validated with the Douglas Bag
method in a controlled laboratory setting [
]. Although the output of waist-worn GT3X+
has been compared with that of AP [17, 18, 27, ±29], which showed the GT3X+ estimates
more sedentary time and breaks than the AP, there has been no research comparing ASP to
these monitors in their ability to detect sedentary behaviour.
In order to compare or integrate findings from studies using different activity monitors,
not only do the differences between monitors need to be better understood, but relative
differences of each monitor against standard measurement should also be examined. Among
the ASP, AP, and GT3X+, the AP is highly accurate in detecting free-living sedentary
behaviour, and thus may be used as a criterion measure [
]. We compared outputs (total
sedentary time, the number of breaks and sedentary bouts) of the ASP, waist-worn GT3X+ and
AP in measuring free-living sedentary behavior, using the outputs of the AP as a reference
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To compare the outputs under various sedentary patterns, participants were workers engaged
in different task types, and data were collected both on a work day and a non-work day.
Previous studies have shown the sedentary patterns of work day and non-work day to be different
]. Fifty participants (27 men, age range 22 to 69 years) were recruited through
opportunistic sampling at diverse workplaces in Tokyo from November, 2014 to June, 2015. They were
35 staff members from a hospital including physiotherapists and office workers, five manual
laborers from a factory, one system engineer from a company and nine researchers and staffs
from a university. Eligible participants were healthy, aged 20 years or older and full-time
workers who work at least five days a week and eight hours a work day.
Participants were provided with the three monitors and a written description for wearing the
monitors with a diary column to record monitor wear time. They were instructed how to wear
the monitors simultaneously during waking time of two days (a work day and a non-work
day) and to remove them during sleeping, water-based activities such as bathing or swimming
and doing sports that can involve collision. They were also asked to record the date and time
displayed in the liquid crystal screen of the ASP when wearing or removing monitors. The
screen display is shown in a previously-published paper [
]. Participants were asked height,
weight and occupational task type (sitting task/ standing task/ walking task/ physical labor
task) by self-report, and body mass index (BMI) was calculated. After finishing data collection,
participants returned the three monitors and their diary descriptions. The research protocol
was approved by the Ethics Committee at the Waseda University. All participants were
informed the purpose of this study and gave written consent.
The ASP is a tri-axial monitor (74 × 46 × 34 mm and 60 g including a battery that has a
sampling rate of 32 Hz using 12 bit analog-to-digital (A/D) converter. Participants wore the ASP
on the right or left side of the waist using an elastic belt that was changed by odd or even
participant ID. The ASP was initialized to collect data in 10- and 60-sec epochs, and the data of
60-sec epochs were used in the analysis. ASP data with 10sec-epoch was not examined because
no previous studies for adults have used that epoch duration and we needed to standardize the
epoch for comparison purposes with the other monitors. The ASP estimates the intensity of
activity by metabolic equivalents (METs) and defines sedentary behaviour as 1.5 METs. The
CSV data files from the ASP were downloaded by Omron health management software
BI-LINK for physical activity professional edition ver1.0 and then the files were processed by
custom software (Custom-written Macro program for compiling data).
The GT3X+, released in September 2010, is small (46×33×15 mm) and lightweight (19g)
tri-axial monitor that has a sampling rate from 30 to 100 Hz using 12 bit A/D converter.
Participants attached the GT3X+ which was enclosed in a small pocket on elastic waist belt and
placed in line with the axillary line of iliac crest which was the opposite side of the ASP. The
GT3X+ was initialized to collect raw tri-axial acceleration signal at 30 Hz and processed into
60-sec epochs from vertical axis with and without low-frequency extension (GT3X+-Norm
and GT3X+-LFE) using Actilife software version 6.10.4. The cutpoints to estimate sedentary
behaviour were set 100 and 150 counts per min [
]. This paper reports the results of the
GT3X+-Norm-100 and those from different settings (GT3X+-Norm-150, LFE-100 and
LFE3 / 14
150) in the additional file because the GT3X+-Norm-100 has been used widely in previous
The activPAL3, released in December 2012, has small and thin shape (5×35×7 mm) and
lightweight (15g) tri-axial monitor which has a sampling rate of 20 Hz using 8 bit A/D
converter. The AP was taped to the midline of the anterior surface of the right thigh using a square
of pad tape for medical care (Hakujuji Co., Ltd., Tokyo, Japan). The software (PAL Analysis
version 7.2.32) processed raw data and then exported time-stamped ªeventº data file to
calculate sedentary variables. Sedentary bouts were determined by any code of sitting/reclining
(AP) similarly with previous studies.
Reported time of wearing or removing monitors was used as rough indicator of start and stop
time, and wear time was defined by the start and stop time of the ASP. The valid data was at
least 600 min of wear time during 24 hours starting from midnight to midnight excluding
non-wear time which was recorded in the column of the description by participants. In case
the code the AP recorded was different from those of the ASP and GT3X+ on most of wear
time, the data of the AP was judged as malfunctioning. In a previous study, three out of 26 APs
malfunctioned, recording sitting during entire data collection (Steeves, 2015). The three
sedentary outputs were as follows:
· Total sedentary time (min) ― this was the sum of the minutes when the monitors estimated
· The number of breaks ― this was any interruptions in sedentary time which were counted
when a transition occurred from a minute recorded as sedentary to an adjacent following
minute recorded not sedentary: >1.5 METs in the ASP, 100 or 150 counts per min in the
GT3X+, code of standing or stepping in the AP.
· The number of sedentary bouts ―a sedentary bout was defined as from starting to ending
within sedentary time period. The number of sedentary bouts 2, 5, 10, 20, 30 and
60 min were calculated from each monitor.
The variables on work day, non-work day and total (the mean of work day and non-work day)
were separately analyzed. The differences of the outputs between monitors were examined
using one-way repeated ANOVA with Tukey's post-hoc test. Overall magnitude correlation of
sedentary time and breaks among monitors were examined by Pearson's correlation
coefficient. In addition, Bland-Altman plots were created to evaluate the bias and limits of
agreement and systematic error of total sedentary time and breaks against the AP as criterion.
Proportional bias was measured by Pearson's correlation coefficient. The plots of the work day
were considered occupational task types. All statistical analyses were performed using IBM
SPSS Statistics 22 software (IBM Japan Inc., Tokyo, Japan). Significant levels were p < 0.05.
The number of participants who had valid data for the total, the work day and the non-work
day was 43, 47 and 44, respectively. Some data were excluded due to lack of the data from the
GT3X+or AP (n = 1 of work day, n = 1 of non-workday), lack of wear time (n = 2 of non-work
day), configuration error of the GT3X+ or AP (n = 1 of work day, n = 1 of non-work day) and
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malfunctioning of the AP (n = 1 of work day, n = 2 of non-work day). Participants'
characteristics and descriptive statistics of the monitors' outputs are summarized in Table 1 and S1 Table.
Of the 47 sets of monitor data for work days, the number of sitting tasks, standing tasks,
walking tasks and physical task at work was 19, 13, 11 and 4, respectively. Among participants who
had the data of both work and non-work days, percent wear time of total sedentary time
recorded by the AP of work day was lower than non-work day (53.1 ± 15.9% wear time for
work days vs. 61.7 ± 15.7% wear time for non-work days, p<0.05).
The differences for each of the outputs between the ASP and the other monitors are
summarized in Table 2 and additional file 1 (S2 Table). For total sedentary time, overall, the ASP
provided shorter time compared to the AP, while the GT3X+-Norm100 provided longer time.
These differences were greater on the work day than on the non-work day. The ASP estimated
29.7 min (95%CI = 7.9 to 51.5) of total sedentary time significantly shorter than the AP on
work day but showed no significant difference against the AP on non-work day. The GT3X
+-Norm100 estimated 80.1 min (95%CI = 54.6 to 105.6) of total sedentary time and 52.3 min
(95%CI = 26.4 to 78.2) significantly longer than the AP on work day and non-work day,
respectively. The difference of total sedentary time between the ASP and GT3X+-Norm100
was more than one hour on both days. Overall magnitude correlations of total sedentary time
among these monitors were significantly clearly shown (Table 3). Bland-Altman Plots of total
sedentary time (Fig 1 and S1 Fig) indicated the ASP and GT3X+-Norm-100 had no systematic
error against the AP in total. The participants' usual task at work did not seem to affect the
difference (middle of Fig 1 and S1 Fig).
For breaks from sedentary time, overall, the GT3X+-Norm100 followed by the ASP
estimated more than the AP. In total, the ASP estimated 14.5 times (95%CI = 8.7 to 20.3) of breaks
significantly more than the AP but 13.3 times (95%CI = 8.8 to 17.8) of breaks significantly less
than the GT3X+-Norm-100. Overall magnitude of the correlations of breaks among between
these monitors were less strong shown than total sedentary time, especially between the ASP
and AP (Table 3). As with the total sedentary time, Bland-Altman plots of breaks (Fig 2 and S2
Fig) showed that the ASP and GT3X+ had no systematic error against the AP. The plots on the
work day (middle of Fig 2 and S2 Fig) suggest that the GT3X+-Norm-100 estimated breaks of
those whose work primarily involves walking tasks and physical labor tasks more than the
In the number of sedentary bouts, the GT3X+-Norm-100 followed by the ASP estimated a
greater number of sedentary bouts 2 min and 5 min than did the AP. The ASP estimated
significantly less bouts 10 min and 20 min than the AP, while the GT3X+-Norm-100
estimated significantly more bouts 10 min and equivalent bouts 20 min against the AP. The
ASP and GT3X+-Norm-100 estimated significantly less bouts 30 and 60 min than the AP,
but there were no significant differences between the ASP and GT3X+-Norm-100 in the bouts
Comparing the outputs of the ASP, GT3X+ and AP in assessing sedentary behaviour under
free-living condition, some key differences were observed between the outputs of the monitors
that have been used in studies with Asian and Western samples. Participants were recruited
from various occupations, so that participants except for those who have mainly sitting task
were more sedentary on the non-work day than on the work day, and the present study was
able to compare the outputs under measuring different sedentary patterns.
The main findings were that the ASP underestimated total sedentary time compared to the
AP (Δ = -25.6 min/day, in total) and GT3X+-Norm-100 (Δ = -89.3 min/day, in total) with
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clear magnitude correlations. For sedentary breaks, the ASP output was greater than the
AP (Δ = 14.5 times/day, in total) but less than the GT3X+ (Δ = -13.3 times/day, in total) with
heterogeneous difference, especially between the ASP and AP. The differences and limits of
agreement of total sedentary time and breaks of the ASP against the AP for non-work days
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were smaller than for work days, which indicates the estimation of the ASP for sedentary
behaviour is more accurate when the sedentary level is relatively high, although the
Bland-Altman plots showed there was no proportional bias. This tendency was similar with the GT3X
+ and was consistent with the findings of a previous study [
]. The ASP tended to
underestimate total sedentary time against the AP, probably because of the difference of epoch length
(one minute for the ASP vs. 15 sec for the AP). It therefore seems that the AP may record
shorter sedentary bouts lasting less than one minute. However, the difference of total sedentary
time per day between ASP and AP was relatively small.
For the number of breaks, the ASP and GT3X+-Norm-100 overestimated against the AP.
These tendencies were similar on both days. Previous studies have also reported the GT3X
+-LFE-100 recorded breaks more than the AP [
]. Lyden and colleagues  compared
the number of breaks of the AP and GT3X (GT3X-Norm100, Norm150, LFE100 and LFE150)
and showed there were differences (baseline condition: 0.3% vs. 77.8% to 110.7% bias for the
AP and GT3X, respectively; and treatment condition: 10.9% vs. 98.1% to 133.3% bias for the
AP and GT3X, respectively). Barreira et al. [
] also compared the number of breaks of the
two monitors under free-living condition and reported the GT3X+ overestimated against the
AP (39.0 ± 3.1 vs. 74.0 ± 4.1 for the AP and GT3X+, respectively). The heterogeneous and
relatively large differences may be caused by the discrepancy of postural classification devices and
energy-expenditure classification devices. The AP estimates the breaks from the angle of the
thigh, while the ASP and the GT3X+ estimates from the acceleration of the waist motion.
There were notable differences in the number of sedentary bouts 2, 5, 30 and 60 min
between monitors which indicated the ASP and GT3X+-Norm-100 overestimated short
sedentary bouts and underestimated prolonged sedentary bouts against the AP. This suggests the
ASP and GT3X+ might estimate breaks during standing or sitting posture. The AP might
classify sitting/lying even when activity while sitting or lying (such as fidgeting or changing
posture) was more than 1.5 METs or 100 counts per min. To detect sedentary breaks accurately by
waist-worn monitor is a future issue of this field. Advanced technology such as machine
] has the potential in the future to resolve this problem. Interpretation with caution is
essential in the results of previous epidemiologic studies on the association of breaks from
sedentary time recorded by the waist-worn accelerometers with indicators of cardiometabolic risk
The ASP may be able to classify sedentary behaviour and standing activity more accurately
than does the GT3X+, because the GT3X+ overestimated breaks of most of those who were
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Fig 1. Bland-Altman plots of total sedentary time between monitors. The shape of the relationships on work
days represent participants' usual task at work; ●- sitting task, ▲- standing task, □- walking task, ×- physical task.
Solid horizontal lines represent mean difference and dashed lines represent levels of agreement.
not primarily engaged in sitting tasks at work, compared to the ASP. Although no studies have
examined how the ASP may misclassify static standing position as less or than 1.5 METs, Kerr
et al. [
] reported that the GT3X+-Norm-100 recorded sedentary time during 72% of static
standing position. Because the AP cannot accurately estimate the intensity of low intensity
activities (sedentary to light) and the present findings showed heterogeneous difference
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Fig 2. Bland-Altman plots of breaks between monitors. The shape of the relationships on work days
represent participants' usual task at work; ●- sitting task, ▲- standing task, □- walking task, ×- physical task.
Solid horizontal lines represent mean difference and dashed lines represent levels of agreement.
between the ASP and AP, further research is needed to verify how accurately the ASP classifies
standing and sitting time, by comparing these monitors under direct observation. The
difference of the outputs between the ASP and GT3X+ may be explained mainly by the number of
axis for sensing acceleration. The ASP estimate the intensity of the motion from triaxial
information but the GT3X+ from uniaxial information, which is the same way with many previous
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studies. Using only the vertical axis may not be sensitive enough to measure low intensity
physical activity even though the GT3X+ has low frequency extension setting. The GT3X
+ may classify some light intensity activities as sedentary.
Overestimation of the GT3X+ against the AP in total sedentary time was also seen in a
previous study. Two previous studies have compared the outputs of the AP and GT3X with low
frequency extension. Lyden et al. [
] evaluated the validity of the AP and GT3X (LFE-100,
LFE-150, Norm-100 and Norm-150) in measuring sedentary behaviour by direct observation
with intervening participants to reduce sedentary behaviour. The GT3X overestimated total
sedentary time against the AP in pre- and post- intervention (baseline condition: 1.6 vs. 5.6 to
17.8% for the AP and GT3X, respectively; and treatment condition: -0.1% vs. 35.9 to 50.7%
bias for the AP and GT3X, respectively).
The main strength of our study is that it is the first to compare the outputs of the ASP (used
primarily in studies with mainly Asian-country participant samples) and other monitors that
have been used primarily with Western-country participant samples. Another strength is that
this study compared the outputs of each monitor by measuring various activity patterns. We
recruited men and women who engaged in various occupations and asked them to wear
monitors on work day and non-work day. A limitation is the subjects were only healthy adults and
small sample size, therefore the differences between monitors are unknown when they are
used with other groups such as youth or older adults.
In conclusion, the present findings demonstrate that the ASP, a device used mainly in Asian
populations, can underestimate total sedentary time compared to the AP, while the GT3X
+ can overestimate it against the AP. This tendency is more obvious when the sedentary time
of participants is lower. For breaks from sedentary time, the GT3X+ followed by the ASP
overestimated against the AP. Judging from the differences of the number of sedentary bouts
against the AP, the ASP may misclassify sedentary breaks during sitting or standing posture,
but the degree is lower than the GT3X+. These differences should be considered in sedentary
behaviour research, especially in comparing Asian and Western study findings. Further
research is needed to further clarify the differences between these monitors using direct
observation as a criterion.
S1 Fig. Bland-Altman plots of total sedentary time between monitors. The shape of markers
of work day represent participants' usual task at work; ●- sitting task, ▲- standing task,
□walking task, ×- physical task. Solid horizontal lines represent mean difference and dashed
lines represent levels of agreement.
S2 Fig. Bland-Altman plots of breaks between monitors. The shape of markers of work day
represent participants' usual task at work; ●- sitting task, ▲- standing task, □- walking task,
×physical task. Solid horizontal lines represent mean difference and dashed lines represent levels
S1 Table. Descriptive statistics of outputs of GT3X+-Norm-150, GT3X+-LFE-100 and
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S2 Table. Mean differences in sedentary outputs between monitors. Values [monitors (A)
minus monitors (B)] are mean differences (95% CI). p < 0.05, p < 0.01, p < 0.001.
The authors would like to thank all the participants in the study.
Conceptualization: Koichiro Oka.
Formal analysis: Satoshi Kurita.
Funding acquisition: Neville Owen, Koichiro Oka.
Investigation: Satoshi Kurita, Shohei Yano, Kaori Ishii, Koichiro Oka.
Methodology: Kaori Ishii, Ai Shibata, Hiroyuki Sasai, Yoshio Nakata, Noritoshi Fukushima,
Shigeru Inoue, Shigeho Tanaka, Koichiro Oka.
Resources: Koichiro Oka.
Writing ± original draft: Satoshi Kurita.
Writing ± review & editing: Kaori Ishii, Ai Shibata, Hiroyuki Sasai, Yoshio Nakata, Noritoshi
Fukushima, Shigeru Inoue, Shigeho Tanaka, Takemi Sugiyama, Neville Owen, Koichiro
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