Changes in volume and bouts of physical activity and sedentary time across early childhood: A longitudinal study

Abstract

Background
Understanding changes in physical activity and sedentary time (SED) during early childhood may provide insights into how to effectively promote a healthy start to life. This study examined changes in total volume and bouts of SED, light- (LPA), and moderate- to vigorous-intensity physical activity (MVPA) across early childhood, and explored differences in change between boys and girls.

Methods
Data were drawn from 330 children participating in the Melbourne InFANT Program, collected between 2008 and 2013 and analysed in 2017. Children’s physical activity and SED were assessed for at least 7 days at each timepoint using ActiGraph GT1M accelerometers at 19 months, 3.5 and 5 years of age. Total volume of SED (≤100 counts per minute [CPM]), LPA (101–1680 CPM) and MVPA (≥1681 CPM) were expressed as a percentage of wear time, and the frequency (number of bouts/day) and duration (mins/bout) of SED, LPA and MVPA bouts ≥1 min were calculated at each time point. Multilevel models with random intercepts and slopes were used to examine changes in total volume and bouts of SED, LPA and MVPA for boys and girls.

Results
Compared to aged 19 months, children’s total volume of SED and LPA decreased at 3.5 and 5 years old, while MVPA increased. The frequency of SED bouts at 3.5 and 5 years was greater than at 19 months, but the duration was shorter. Additionally, the frequency and duration of LPA bouts was lower and MVPA bout frequency and duration was greater at 3.5 and 5 years. In general, there was no evidence of sex differences in trajectories of children’s physical activity and SED. However, variations in trajectory were observed at the individual child level.

Conclusions
Children’s total volume and bouts of SED, LPA and MVPA change across early childhood, mostly in a favourable direction. Trajectories appear to be similar for boys and girls. Investigation of individual variation in trajectories is likely to provide greater insight into associations between physical activity and future health and behavioural outcomes.

Full text

R E S E A R C H Open Access
Changes in volume and bouts of physical
activity and sedentary time across early
childhood: a longitudinal study
Jill A. Hnatiuk
1*
, Karen E. Lamb
1,2,3
, Nicola D. Ridgers
1
, Jo Salmon
1
and Kylie D. Hesketh
1
Abstract
Background: Understanding changes in physical activity and sedentary time (SED) during early childhood may
provide insights into how to effectively promote a healthy start to life. This study examined changes in total
volume and bouts of SED, light- (LPA), and moderate- to vigorous-intensity physical activity (MVPA) across early
childhood, and explored differences in change between boys and girls.
Methods: Data were drawn from 330 children participating in the Melbourne InFANT Program, collected between
2008 and 2013 and analysed in 2017. Children’s physical activity and SED were assessed for at least 7 days at each
timepoint using ActiGraph GT1M accelerometers at 19 months, 3.5 and 5 years of age. Total volume of SED (≤100
counts per minute [CPM]), LPA (101–1680 CPM) and MVPA (≥1681 CPM) were expressed as a percentage of wear
time, and the frequency (number of bouts/day) and duration (mins/bout) of SED, LPA and MVPA bouts ≥1 min
were calculated at each time point. Multilevel models with random intercepts and slopes were used to examine
changes in total volume and bouts of SED, LPA and MVPA for boys and girls.
Results: Compared to aged 19 months, children’s total volume of SED and LPA decreased at 3.5 and 5 years old,
while MVPA increased. The frequency of SED bouts at 3.5 and 5 years was greater than at 19 months, but the
duration was shorter. Additionally, the frequency and duration of LPA bouts was lower and MVPA bout frequency
and duration was greater at 3.5 and 5 years. In general, there was no evidence of sex differences in trajectories of
children’s physical activity and SED. However, variations in trajectory were observed at the individual child level.
Conclusions: Children’s total volume and bouts of SED, LPA and MVPA change across early childhood, mostly in a
favourable direction. Trajectories appear to be similar for boys and girls. Investigation of individual variation in
trajectories is likely to provide greater insight into associations between physical activity and future health and
behavioural outcomes.
Keywords: Physical activity, Sedentary behaviour, Trajectories, Patterns, Bouts, Early childhood, Longitudinal,
Accelerometry
Background
Optimising physical activity and minimising sedentary
time in early childhood (infancy –5 years of age) is im-
portant for health [1]. Previous reviews have found that
greater daily physical activity participation during early
childhood is associated with fewer cardiovascular risk
factors and lower adiposity, and improved cognitive
development and bone density in early and later child-
hood [1]. Excessive time spent sedentary in early child-
hood, namely in screen-based behaviours, is negatively
associated with these same health outcomes [2,3]. Des-
pite the growing trend towards promoting physical activ-
ity in early childhood, little is known about how
children’s physical activity and sedentary time are accu-
mulated, and how the total volume and patterns of accu-
mulation (i.e., frequency and bouts) change over time.
This is important for several reasons. Firstly, identifying
how physical activity and sedentary time change across
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
* Correspondence: jill.hnatiuk@deakin.edu.au
1
Institute for Physical Activity and Nutrition (IPAN), School of Exercise and
Nutrition Sciences, Deakin University, Geelong, Australia
Full list of author information is available at the end of the article
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity
(2019) 16:42
https://doi.org/10.1186/s12966-019-0805-6
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

early childhood provides an indication of the age at which
children may be most or least active, which can be used to
inform the timing of intervention programming. Secondly,
identifying typical patterns of accumulation of physical ac-
tivity and sedentary time across early childhood can pro-
vide an indication of how physical activity initiatives
might be structured at various ages to increase total vol-
ume of physical activity and minimise sedentary time, as
well as optimise health outcomes for children.
Previous studies examining changes in total volume of
daily physical activity and sedentary time have generally
reported that physical activity declines and sedentary time
increases from the age of 4–5 years onwards, likely coin-
ciding with the commencement of formal schooling [4–6].
However, little information exists on changes in children’s
total volume of physical activity and sedentary time prior
to commencing primary school (i.e., from when children
begin walking independently through to the preschool
years). A recent longitudinal study from Switzerland that
focused on children from 2.5 years of age found increased
total physical activity and moderate-to-vigorous physical
activity (MVPA) up to age six, with sedentary time
remaining somewhat stable [7].
The majority of research on patterns of physical activ-
ity and sedentary time accumulation (i.e., bout frequency
and duration) is drawn from cross-sectional samples of
school-aged children and adolescents [8–11], rather than
toddlers and pre-schoolers. Only a few studies have in-
vestigated bouts of sedentary time in preschool aged
children [12–16]. Previous studies investigating relatively
long bouts of sedentary time for this age group (i.e., ≥10
min) have shown contrasting findings. Two studies from
Scandinavia (Norway and Sweden) investigated seden-
tary bouts > 10 min. One reported a total of 83 mins/day
was spent in bouts of this duration [12], whilst the other
reported over 300 min per day [14]. Studies from
Australia and Canada that examined several different
sedentary bout lengths (1–4 min; 5–9 min; ≥10 mins) in
children reported that the greatest proportion of seden-
tary time was derived from bouts that were short in dur-
ation < 1 min [15]or1–4 min in length [13,16]. One of
these studies [13] also examined changes in children’s
sedentary time over the course of 1 year (from age 3–5
years to age 4–6 years). They found increases in the total
time spent in 1–4 min bouts and in ≥10 min sedentary
bouts, regardless of whether children had commenced
primary school or not [13].
Despite emerging research on sedentary bouts in early
childhood, we are not aware of any studies that have ex-
amined bouts of physical activity in children under five.
Research on physical activity patterns of accumulation in
school aged children and youth have found that 66% of
8–17 year old children’s physical activity was accumu-
lated through sporadic (1–4min) bouts of MVPA, 16%
through short (5–9 min) bouts and 18% through long
(> 10 min) bouts of MVPA [11]. Other research with
8–10 year old children has found that found most
MVPA was accumulated in bouts less than 1 min and
the mean duration of a LPA bout was just over 1
min [17]. However, patterns of accumulation can be
heavily influenced by how data are collected, particu-
larly when using accelerometry (such as through the
use of short vs long epoch settings) [18], which may
possibly explain some of the differences in bout dur-
ation observed between studies. Additionally, recent
reviews have highlighted that there is a lack of con-
sensus on how physical activity bouts are defined in
the literature [19].
An additional consideration to changes in activity
spectrum patterns in early childhood are the sex differ-
ences from a young age. Previous research has consist-
ently shown that boys’total volume of physical activity
tends to be greater than girls [20]. There is also evidence
that patterns of accumulation of sedentary time may dif-
fer by sex, with boys engaging in more very short (< 1
min) bouts of sitting than girls [15]. Exploring sex differ-
ences in physical activity and sedentary time from when
children commence independent walking is important
for providing insights into how to better design pro-
gramming to optimise physical activity and minimise
sedentary time for both sexes early in life.
In summary, limited evidence exists for how children’s
total volume of physical activity and sedentary time
change across early childhood. Furthermore, no studies
have examined changes in physical activity and sedentary
patterns in early childhood. Consequently, this study
aims to address these gaps and examine changes in total
volume and bouts of sedentary time, LPA and MVPA
across early childhood, and to explore whether there are
any differences between boys and girls.
Methods
Participants
Participants for this study were drawn from the Mel-
bourne InFANT Program and Melbourne InFANT Pro-
gram Follow-Up. The methods of this study have been
previously described elsewhere [21–23]. Briefly, the Mel-
bourne InFANT Program was a cluster-randomised con-
trolled trial focused on childhood obesity prevention and
delivered to first-time parents’groups (existing groups
made up of parents with children born around a similar
time in their local area, run through government-funded
maternal and child health centres in the state of
Victoria, Australia) when children were 4–19 months of
age. Children were then followed up at two later time
points: 3.5 and 5 years old [23]. This study used data col-
lected when children were 19 months (2009–2010), 3.5
(2011–2012) and 5 (2013) years of age. Of the original
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 2 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

sample of 542 parent-child dyads recruited at baseline
(child aged 4 months old), 480 were still enrolled in the
study at intervention conclusion (child aged 19 months
old), and 361 and 337 families consented to take part in the
study when the children were aged 3.5 years and 5 years
old, respectively. All mothers in the Melbourne InFANT
Program and Melbourne InFANT Program Follow-Up gave
written consent for themselves and their child to take part
in the research. Ethics approval for this project was granted
from the Deakin University Human Research Ethics Com-
mittee and the Victorian Government’s Office for Children.
Physical activity and sedentary time
Children’s physical activity and sedentary time were ob-
jectively assessed at each time point using ActiGraph
GT1M accelerometers (ActiGraph LLC, Pensacola, FL,
USA). The accelerometers were worn on an elastic belt
and placed over the child’s right hip, and parents were
instructed to keep the accelerometer on the child during
all waking hours for at least 7 days, removing only for
sleeping and water-based activities. Data were collected
in 15-s epochs.
Accelerometer data were processed using customised
Excel macros. 10 min of consecutive zeros were consid-
ered to be non-wear time [13,24]. Validated cut-points
of ≤100 counts per minute (CPM), 101–1680 CPM,
and ≥1680 CPM were applied to the data at all ages to
distinguish sedentary time, LPA, and MVPA [25], re-
spectively. The 70/80 rule was applied separately at each
time point to determine a valid day (19 months = 7.4 h;
3.5 years = 6.6 h; 5 years = 6.9 h) [26]. The 70/80 rule rep-
resents non-missing counts for at least 80% of a stand-
ard measurement day, defined as the length of time that
at least 70% of the sample wore the monitor [27,28].
Children were included in the analyses for this study if they
wore the accelerometer for at least 3 valid days [24,27]dur-
ing at least one time point, consistent with previous re-
search [4]. Children’s total volume of sedentary time, LPA
and MVPA, expressed as a percentage of wear time, was av-
eraged across all valid days. The average number of bouts
per day lasting ≥1 min (frequency) and the average duration
in a bout (minutes/day) were also determined. Given there
is presently no consensus on the ‘optimal’bout length for
young children [19],aone-minuteboutlengthwasselected
based on previous research that has focused on children’s
physical activity and sedentary time [11,13]andthespor-
adic nature of young children’s physical activity [19]. No ex-
ceptions were allowed, which has been shown to increase
time accumulated in longer bouts [18].
Demographic information
Mothers reported demographic information about them-
selves and their child including: the sex of their child,
their own education levels (low = secondary school or
lower; medium = trade certificate/diploma; high = univer-
sity degree or higher), and their child’s date of birth. The
child’s date of birth enabled the calculation of the child’s
decimal age, which was based on when the survey was
completed. Mothers also reported whether their child
was attending primary school at the 5 year old time
point (yes/no).
Data analysis
Data were analysed in 2017 using Stata v.14.0 [29]. A
chi-squared test was used to examine whether the num-
ber of valid time points of data differed by maternal edu-
cation. Analysis of variance (ANOVA) tests examined
differences in total SED, LPA and MVPA for children
who had commenced primary school at age five and
those who had not. Linear multilevel models were used
to examine changes in the following outcome variables
over time: total volume of SED, LPA and MVPA
expressed as a percentage of wear time; and frequency
(bouts/day) and duration (mins/day) of bouts of SED,
LPA, MVPA. Multilevel modelling was considered the
most appropriate analysis technique as it can manage
nested data and is robust for dealing with missing data,
assuming the data are missing at random [30]. Each
model included a random intercept for both child and
parent group of recruitment. In addition, the coefficient
of time was allowed to vary randomly by child to allow
each child to have his or her own trajectory of change.
To determine whether there was evidence that there was
random variation in the trajectory of change across par-
ticipants, likelihood ratio tests were used to compare
multilevel models with and without a random slope for
time (i.e., random intercept only vs. random slope and
intercept). In addition, models with an unstructured co-
variance, which allowed for correlations between the
random intercept and slope, were considered. For most
outcome variables (total volume of SED, LPA, MVPA,
SED and MVPA bout frequency, and SED bout duration)
the random slope and intercept with unstructured covari-
ance provided the best fit for the data. For the remaining
outcome variables (LPA bout frequency, and LPA and
MVPA bout duration), a random intercept was sufficient.
Model residuals were checked for normality and constant
variance using QQ-plots and plots of residuals against fit-
ted values. All assumptions appeared reasonable.
Since participants of the Melbourne InFANT Program
were recruited as part of a cluster randomised controlled
trial, models were initially fitted to examine whether
change in the outcomes differed by treatment group (i.e.,
intervention vs. control). However, there was no evidence
of a group by time interaction for any of the outcome vari-
ables. Therefore, data were pooled from both groups for
the remaining analyses to maximise the sample size.
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 3 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

An interaction between time and sex of the child was
included in models to determine if trajectories of phys-
ical activity and sedentary time across early childhood
differed by sex. All analyses controlled for intervention
group and maternal education (as a proxy for socioeco-
nomic status) at baseline. The analyses examining the
frequency and duration of bouts also controlled for ac-
celerometer wear time, given the outcome was expressed
in bouts or minutes per day, rather than as a percentage
of wear time. As time was included as a categorical pre-
dictor in analyses, post-hoc pairwise comparisons were
conducted to examine the differences in average volume
and bouts of SED, LPA and MVPA between all of the
time points. The Bonferroni correction (set at p< 0.01)
was used in post-hoc testing to adjust for the multiple
comparisons made.
Results
From the 492 children enrolled in the Melbourne In-
FANT Program at 19 months, 330 children (67%) had
sufficient accelerometer data for at least one time point
during the follow-up period (e.g., 19 months, 3.5 and/or
5 years), resulting in 681 data points for the analyses. A
total of 141 children had one time point of valid data,
and 189 had two or more time points of valid data. From
the total sample (n= 330), 52.6% of children were male,
and 59.2% of mothers had a university degree or higher,
with the remainder having a trade certificate (24.0%) or
secondary school or lower (16.8%). Mothers with a uni-
versity degree or higher were more likely to have chil-
dren with 2 time points of data (χ
2
= 7.76, p< 0.05).
Twelve percent of children in the sample were attending
primary school at the 5 year old time point, however,
there was no evidence that their total volume of SED,
LPA or MVPA differed from those who were not
attending school. Consequently, these data were pooled.
Table 1outlines the descriptive physical activity and
SED results at each time point. Mean accelerometer
wear time was 587.21 (69.38) mins/day at 19 months
old, 626.92 (63.08) mins/day at 3.5 years old and 650.18
(61.93) mins/day at 5 years old.
Compared to when children were aged 19 months, the
mean percentage of time (total volume) spent in SED and
LPA decreased at 3.5 (SED: β[95%CI] = −1.60% [−3.13,
−0.07]; LPA: β[95%CI] = −1.40% [−2.53, −0.27]) and 5
years old (SED: β[95%CI] = −2.32% [−3.99, −0.64]; LPA:
β[95%CI] = −2.66% [−3.90, −1.41]), while the percentage
of time spent in MVPA increased at 3.5 and 5 years old
(3.5 years: β[95%CI] = 3.04% [2.28, 3.80]; 5 years: β
[95%CI] = 5.01% [4.19, 5.83]). Post-hoc tests revealed no
differences in the percentage of SED and LPA between 3.5
and 5 years; however, MVPA significantly increased during
this time (d[95%CI] =1.74% [1.01, 2.47]). No difference in
trajectories of SED, LPA or MVPA were observed between
boys and girls, though girls engaged in a greater percent-
age of sedentary time overall than boys (β[95%CI] =
1.50% [0.06, 2.95]).
Compared to when children were aged 19 months,
the average frequency of bouts of SED was greater at
3.5 (SED: β[95%CI] = 3.47 [1.12, 5.81]) and 5 (SED: β
[95%CI] = 4.31 [1.54, 7.07]) years of age, but the dur-
ation was shorter (3.5 years SED: β[95% CI] = −0.30
min [−0.42, −0.17]; 5 years SED: β[95%CI] = −0.35
min [−0.52, −0.18]). There was no evidence of a dif-
ference in either average SED bout duration or fre-
quency between 3.5 and 5 years.
For LPA, compared to when children were aged 19
months, at 3.5 and 5 years the frequency (3.5 years: β
[95%CI] = −4.82 [−8.27, −1.38]; 5 years β[95%CI] = −10.39
[−13.77, −7.00]) and duration (3.5 years: β[95%CI] = −0.06
Table 1 Mean (SD) total volume and bouts of SED, LPA & MVPA at 19 months, 3.5 years and 5 years of age
a,b,c
19 months 3.5 years 5 years
Boys
(n= 160)
Girls
(n= 144)
Combined
(n= 304)
Boys
(n= 71)
Girls
(n= 86)
Combined
(n= 157)
Boys
(n= 80)
Girls
(n= 81)
Combined
(n= 161)
Total volume SED (% wear time/day) 52.1 (6.1) 53.7 (6.8)
d
52.8 (6.5) 49.7 (6.0) 50.9 (5.7) 50.3 (5.9) 49.3 (6.5) 51.3 (6.1)
d
50.3 (6.4)
Total volume LPA (% wear time/day) 39.6 (4.9) 38.5 (5.1) 39.1 (5.1) 38.9 (4.6) 38.3 (3.6) 38.6 (4.1) 3.75 (4.5) 36.6 (4.1) 37.0 (4.3)
Total volume MVPA (% wear time/day) 8.3 (2.6) 7.8 (2.8) 8.1 (2.7) 11.4 (3.4) 10.7 (3.6) 11.0 (3.5) 13.1 (3.8) 12.1 (3.2) 12.6 (3.5)
SED bout frequency (bouts/day) 72.1 (14.1) 77.0 (16.0) 74.5 (15.2) 83.2 (15.0) 84.8 (12.9) 84.1 (13.9) 87.5 (14.5) 89.9 (11.6) 88.7 (13.1)
LPA bout frequency (bouts/day) 78.6 (14.8) 77.1 (15.8) 77.9 (15.3) 81.9 (15.0) 77.1 (11.4)
d
79.3 (13.3) 77.9 (15.6) 73.3 (12.7)
d
75.6 (14.4)
MVPA bout frequency (bouts/day) 7.9 (4.2) 7.4 (4.1) 7.6 (4.2) 15.8 (6.9) 13.7 (6.9) 14.6 (7.0) 20.8 (8.1) 17.6 (7.1)
d
19.2 (7.8)
SED bout duration (mins/bout) 3.2 (0.5) 3.2 (0.5) 3.3 (0.5) 2.9 (0.4) 2.8 (0.3) 2.9 (0.3) 2.8 (0.4) 2.8 (0.7) 2.8 (0.6)
LPA bout duration (mins/bout) 1.6 (0.1) 1.6 (0.1)
d
1.6 (0.1) 1.6 (0.9) 1.5 (0.8) 1.5 (0.1) 1.5 (0.9) 1.5 (0.6)
d
1.5 (0.1)
MVPA bout duration (mins/bout) 1.5 (0.2) 1.5 (0.3) 1.5 (0.2) 1.6 (0.2) 1.5 (0.2) 1.6 (0.2) 1.6 (0.2) 1.6 (0.2) 1.6 (0.2)
a
SED sedentary time, LPA light-intensity physical activity, MVPA moderate- to vigorous-intensity physical activity
b
Bouts defined in this study as any sedentary time, LPA or MVPA > 1 min
c
All values are Mean (SD)
d
Significant difference between boys and girls at p< 0.05
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 4 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

min [−0.09, −0.03]; 5 years β[95%CI] = −0.11 min [−0.14,
−0.08]) of LPA bouts decreased. There was also a decrease
in LPA bout frequency (d[95%CI] = −5.72 [−8.96, −2.49])
and duration (d[95%CI] = −0.06 min [−0.09, −0.03]) be-
tween 3.5 and 5 years.
For MVPA, compared to child aged 19 months, aver-
age MVPA bout frequency was greater at 3.5 years (β
[95%CI] = 6.96 [5.57, 8.35]) and 5 years (β[95%CI] =
12.31 [10.61, 14.01]), as was MVPA bout duration (3.5
years: β[95%CI] = 0.11 min [0.05, 0.17]; 5 years: β
[95%CI] = 0.21 min [0.07, 0.18]). Between 3.5 and 5
years there was an increase in MVPA bout frequency
(d[95%CI] = 4.63 [3.28, 5.98]), but not duration. Girls
engaged in more sedentary bouts (β[95%CI] = 2.82
[0.28, 5.36]) and shorter LPA bouts (β[95%CI] = −
0.25 [−0.05, −0.001]) overall than boys (main effects)
and their trajectory of MVPA bout frequency was less
steep at 5 years of age (β[95%CI] = −2.44 [−
4.84,-0.04]) (sex X time interaction). No further sex
differences were observed for any of the other vari-
ables examined (p-values all > 0.05).
Tabl e 2reports the estimated standard deviations
and confidence intervals for the random effects (ran-
dom intercept for child and parent group, random
slope for time) from the models of total volume of
SED, LPA and MVPA. For these outcome variables,
there was evidence of variability in the coefficient of
time between children. This means that the slopes
(trajectories) of SED, LPA and MVPA varied between
individual children (see Fig. 1for sample depiction of
individual trajectories, separated by sex). The findings
showninTable2also highlight that there was a neg-
ligible amount of variability in SED, LPA and MVPA
between parent intervention groups.
Discussion
This study was the first to examine changes in total daily
volume and bouts of SED, LPA and MVPA across early
childhood between boys and girls, beginning from
around the time when children commenced independent
walking. Overall, generally favourable trends were ob-
served across the sample. As children aged, a greater
proportion of time was spent in MVPA, which appeared
to be replacing some of the time spent sedentary and in
LPA. This suggests that the recommendation to grad-
ually increase physical activity intensity during the early
childhood period (i.e., 60 mins MVPA of energetic play
from 3 to 5 years of age [31,32]) is consistent with the
trajectory of children’s objectively assessed MVPA, mak-
ing it a feasible recommendation for this age group.
Given the favourable effects of MVPA on children’s car-
diovascular health [33] the progressive replacement of
SED and LPA with MVPA is a promising finding. The
progressive increase could be due to favourable environ-
mental changes (e.g., less time in restricted movement;
greater opportunities for engagement in MVPA with
other children or family members, more independence)
and/or improved motor development (i.e., from inter-
mittent walking to more sustained activity) at these later
ages [34].
Since the mean duration of MVPA bouts increased
only slightly over time, our findings suggest that the
higher total volume of MVPA occurring at 3.5 and 5
years resulted from progressively more bouts rather than
from more prolonged MVPA. By 5 years of age almost
1/3 of children’s MVPA was accumulated through bouts
> 1 min, compared to about 1/5 at 19 months old. This
is possibly due to changes in children’s growth and de-
velopment [35], perhaps coinciding with greater
Table 2 Random effects parameters for total volume of SED, LPA and MVPA
a,b
Variable Random effects parameter Standard deviation
(95% CI)
Total volume SED
(% wear time/day)
Parents group attended 2.98
−7
(2.57
−16
, 346.35)
Child 9.18 (1.42, 59.10)
Time 2.49 (0.48, 12.96)
Residual 5.31 (4.18, 6.75)
Total volume LPA
(% wear time/day)
Parents group attended 4.35
−8
(0.00, 0.00)
Child 8.28 (5.72, 11.98)
Time 2.03 (1.38, 2.98)
Residual 3.93 (3.50, 4.41)
Total volume MVPA
(% wear time/day)
Parents group attended 2.05
−7
(1.19
−10
, 3.52
−4
)
Child 2.34 (0.41, 13.33)
Time 1.04 (0.57, 1.90)
Residual 2.67 (2.34, 2.97)
a
SED sedentary time, LPA light-intensity physical activity, MVPA moderate- to vigorous-intensity physical activity
b
Similar estimates of associations observed when parent group attended was omitted from the models. Variable was retained in model given the study design
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 5 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

opportunities for active play and less time in situations
restricting movement [36].
Little research has investigated physical activity bouts
in children, with none in the early childhood period.
Previous research on primary school-aged children has
reported mixed results regarding the typical bout dur-
ation for that age group. One study found that the aver-
age bout duration in a sample of 12 year old children
was 4.7 min, representing approximately 40% of their
total MVPA time [37]. Others conducted with 6–10 year
old children [17,38] and 14-year old adolescent boys
[39] found most MVPA was accumulated in bouts less
than 1 min; for example, Sanders at et., [39] found an
average bout duration of just 4.1 s. Given that previous
research has shown that methodological decisions, in
particular the epoch length selected when using acceler-
ometers, can heavily influence the results attained [18],
it is likely some of the differences in bout duration esti-
mates are a result of this. Nonetheless, our study find-
ings suggest that activities that are quite brief in
duration (< 1 min) still enable young children to accu-
mulate sufficient volumes of MVPA throughout the day.
Given this, interventions in this age group may want to
focus on providing opportunities to increase the number
of MVPA bouts occurring throughout the day. For ex-
ample, early learning centres might increase the fre-
quency of outdoor play periods during care (as has been
tested previously [40]), or parents might be supported to
encourage play activities that facilitate spurts of MVPA
(e.g., chasing games) throughout the day at home.
A decrease in the duration of sedentary bouts between
19 months and 3.5 and 5 years old, but an increase in
the frequency of these bouts, was also observed. How-
ever, no differences in total volume or bout frequency
and duration were observed between 3.5 and 5 year time
points. This suggests that the biggest change in how sed-
entary time is accumulated occurs between 19 months
and 3.5 years, with minimal change thereafter. It is diffi-
cult to postulate why this finding has occurred, but
could be due to the combined effect of developmental
and environmental changes. For example, the increas-
ingly social play with other children that occurs between
19 months and 3.5 years (shifting from solitary/parallel
play to associative or cooperative play [41]) may impact
on sedentary bout frequency, bout duration and total
volume of sedentary time. Alternatively, changing parent
or caregiver actions that might occur to a greater degree
between 18 months and 3.5 years (compared to 3.5 and
5 years old), such as less reliance on a pram, may reduce
the duration of sedentary bouts and total volume of sed-
entary time. However, as these are just hypotheses, there
appears to be important research opportunities for un-
derstanding sedentary behaviour in this very young (< 2
year old) sample group given that their sedentary time
appears to be accumulated differently to that in the pre-
school years. A noticeable increase in sedentary bout
length may not appear again until children transition to
school, at which point the structure and policies within
the present school environment may negatively impact
children’s total volume of sedentary time [13]. It is im-
portant to note that within our sample, despite more fre-
quent sedentary bouts ≥1 min occurring over time, these
were not enough to increase children’s total volume of
sedentary time. At present the relationship between
Fig. 1 Boys’and girls’moderate- to vigorous-intensity physical activity (MVPA) by age, highlighting varied trajectories across early childhood.
Fitted values attained from multilevel models examining change in children’s average daily percentage of MVPA. Models controlled for
intervention group and maternal education
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 6 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

frequency and duration of bouts of sedentary time and
children’s health is not known, so the overall reduction
in total volume of sedentary time between 19 months
and 3.5 and 5 years appears to be a favourable outcome,
irrespective of how sedentary time was accumulated.
Evidence of some sex differences in both volume and
bouts of physical activity and sedentary time were also
noted, though these were predominantly main effects ra-
ther than interactions over time (i.e., changes in trajec-
tory). This supports previous work that has suggested
that girls engage in more sedentary time and less MVPA
than boys [20,42], but also proposes that the trajectories
of physical activity and sedentary behaviour between the
sexes are not dissimilar. The only exception was that
whilst MVPA bout frequency increased from 19 months
among girls and boys, girls appeared to increase to a
lesser extent than boys by 5 years old, although the effect
size of this difference was small (approximately two
fewer bouts/day). Nonetheless, it may be important for
care providers and parents to pay particular attention to
prompting girls to engage in MVPA more regularly
across early childhood to minimise the sex differences
already apparent in MVPA during this period [20] and
continuing later in life [43]. Although there is limited
evidence on strategies to support girls’physical activity
participation in the early years, some ideas can be drawn
from the DADEE program, a father-daughter physical
activity intervention conducted with primary school girls
[44]. In this program, the authors highlight the import-
ance of program aspects such as redefining gender
norms, participating in co-physical activity and improv-
ing fundamental movement skills for successfully in-
creasing physical activity amongst girls [44]. Perhaps the
efficacy of a similar approach, extended to a range of
care providers, could be investigated in early childhood,
especially during the preschool years where the sex dif-
ference in MVPA bout frequency seems to emerge.
A novel finding of this work was that whilst the total
volume of MVPA increased and LPA and sedentary be-
haviour decreased over time, individual children’s activ-
ity trajectories, particularly with respect to children’s
MVPA, differed. Visual inspection of the data showed
that some children demonstrated a linear increase or de-
crease over time, whilst others showed a ‘V’, or inverted
‘V’shape, over time. Understanding how these different
trajectories of physical activity and sedentary behaviour
in early life are associated with future physical activity
and sedentary behaviour patterns, as well as with health
outcomes, will be important for future research in this
field. Additionally, identifying the modifiable factors that
predict different trajectories of physical activity and sed-
entary behaviour across early childhood may be useful
for informing intervention programs. For example, early
targeted support could be provided to those children
who demonstrate decreasing physical activity and in-
creased sedentary patterns.
Strengths and limitations
The strengths of this work include the objective meas-
urement of physical activity and sedentary time, the in-
clusion of both volume and bouts of different intensities
of physical activity and sedentary time, as well as mul-
tiple time points across the early childhood period.
Nonetheless, we recognise that this study is not without
its limitations. It is possible that some change in bout
frequency or duration may have occurred over this time,
but were less than 1 min in length and therefore not
taken into account with the present analysis strategy.
However, it was decided a priori that the bout duration
of greater than 1 min would be used for both physical
activity and sedentary time, consistent with previous re-
search [13,15] to enable comparisons and the brief na-
ture of young children’s physical activity [38]. This is
particularly relevant given that no consensus on ‘long’
vs. ‘short’duration bouts have been established at
present [19]. Additionally, some of the variability in
physical activity and sedentary time estimates at each
time point could be due to measurement error, poten-
tially impacting the trajectories identified. There is also
currently considerable challenges with the application of
cut-points for children during the early childhood years
[45]. This study used the same cut-points across each
time point to ensure that any changes in physical activity
detected were a result of changed movement behaviour
rather than a change in cut-point. However, as some evi-
dence suggests that cut-points should change with age
[46], it is possible that the application of the same
cut-point across these three time periods may have mis-
classified some movement behaviours. Lastly, attrition
occurred over time, a proportion of the sample did not
have all three time points of data and the use of 15-s
epochs may underestimated sedentary time and MVPA,
and overestimated LPA.
Conclusions
This is the first study to focus on changes in young
children’s volume and bouts of physical activity and
sedentary time across the early childhood period. This
study found that from 19 months, children’sMVPA
increased, whilst their LPA and sedentary time de-
creased, largely a result of changes in bout frequency.
Trajectories of physical activity were mostly similar
for boys and girls, but showed different patterns be-
tween individual children in the sample. Future re-
search should consider examining the implications of
different trajectories of physical activity and sedentary
time across early childhood on children’s later
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 7 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

physical activity and sedentary behaviours, as well as
associations with health.
Abbreviations
CPM: Counts per minute; LPA: light-intensity physical activity;
MVPA: Moderate- to vigorous-intensity physical activity; SED: Sedentary time
Acknowledgements
None applicable.
Funding
The Melbourne InFANT Program was funded by the National Health &
Medical Research.
Council (APP425801 & APP1008879). NDR is supported by a National Heart
Foundation of Australia Future Leader Fellowship (ID 101895). JS was
supported by a National Health and Medical Research Council Principal
Research Fellowship during this study (APP1026216). KDH is supported by an
Australian Research Council Future Fellowship (FT130100637) and an
Honorary Heart Foundation Future Leader Fellowship (100370). The funding
sources did not play a role in the study design, data collection, analysis or
interpretation, writing of the report and the decision to submit the report for
publication.
Financial disclosure: All authors have no financial disclosure.
Availability of data and materials
The datasets generated and/or analysed during the current study are not
publicly available due to ethics board requirements, but are available from
the corresponding author on reasonable request.
Authors’contributions
JH conceptualised the idea for the study with input from KDH, JS, NDR and
KL. JH and KL conducted statistical analyses and JH drafted the manuscript.
KDH and JS conducted the study from which the data were drawn. All
authors contributed to the interpretation of data and provided feedback on
the draft and approved the final version.
Ethics approval and consent to participate
All mothers in the Melbourne InFANT Program and Melbourne InFANT
Program Follow-Up gave written consent for themselves and their child to
take part in the research. Ethics approval for this project was granted from
the Deakin University Human Research Ethics Committee and the Victorian
Government’s Office for Children.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Publisher’sNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
Institute for Physical Activity and Nutrition (IPAN), School of Exercise and
Nutrition Sciences, Deakin University, Geelong, Australia.
2
Murdoch Children’s
Research Institute, Royal Children’s Hospital, Parkville, Australia.
3
Department
of Paediatrics, The University of Melbourne, Parkville, Australia.
Received: 18 October 2018 Accepted: 26 April 2019
References
1. Carson V, Lee E-Y, Hewitt L, Jennings C, Hunter S, Kuzik N, et al. Systematic
review of the relationships between physical activity and health indicators
in the early years (0-4 years). BMC Public Health. 2017;17(5):854.
2. LeBlanc AG, Spence JC, Carson V, Gorber SC, Dillman C, Janssen I, et al.
Systematic review of sedentary behaviour and health indicators in the early
years (aged 0-4 years). Appl Physiol Nutr Metab. 2012;37:753–72.
3. Poitras VJ, Gray CE, Janssen X, Aubert S, Carson V, Faulkner G, et al.
Systematic review of the relationships between sedentary behaviour and
health indicators in the early years (0–4 years). BMC Public Health. 2017;
17(5):868.
4. Cooper AR, Goodman A, Page AS, Sherar LB, Esliger DW, van Sluijs EM, et al.
Objectively measured physical activity and sedentary time in youth: the
international children’s accelerometry database (ICAD). Int J Behav Nutr
Phys Act. 2015;12(1):1.
5. Taylor RW, Murdoch L, Carter P, Gerrard DF, Williams SM, Taylor BJ.
Longitudinal study of physical activity and inactivity in preschoolers: the
FLAME study. Med Sci Sports Exerc. 2009;41(1):96–102.
6. Taylor RW, Williams SM, Farmer VL, Taylor BJ. Changes in physical activity
over time in Young children: a longitudinal study using accelerometers.
PLoS One. 2013;8(11):e81567.
7. Schmutz EA, Haile SR, Leeger-Aschmann CS, Kakebeeke TH, Zysset AE,
Messerli-Bürgy N, et al. Physical activity and sedentary behavior in
preschoolers: a longitudinal assessment of trajectories and determinants. Int
J Behav Nutr Phys Act. 2018;15(1):35.
8. Saunders TJ, Tremblay MS, Mathieu M-È, Henderson M, O’Loughlin J,
Tremblay A, et al. Associations of sedentary behavior, sedentary bouts and
breaks in sedentary time with cardiometabolic risk in children with a family
history of obesity. PLoS One. 2013;8(11):e79143.
9. Júdice PB, Silva AM, Berria J, Petroski EL, Ekelund U, Sardinha LB. Sedentary
patterns, physical activity and health-related physical fitness in youth: a
cross-sectional study. Int J Behav Nutr Phys Act. 2017;14(1):25.
10. Gabel L, Ridgers N, Della Gatta P, Arundell L, Cerin E, Robinson S, et al.
Associations of sedentary time patterns and TV viewing time with
inflammatory and endothelial function biomarkers in children. Pediatr Obes.
2016;11(3):194–201.
11. Mark AE, Janssen I. Influence of bouts of physical activity on overweight in
youth. Am J Prev Med. 2009;36(5):416–21.
12. Andersen E, Borch-Jenssen J, Øvreås S, Ellingsen H, Jørgensen KA, Moser T.
Objectively measured physical activity level and sedentary behavior in
Norwegian children during a week in preschool. Prev Med Rep. 2017;7:130–5.
13. Carson V, Salmon J, Crawford D, Hinkley T, Hesketh KD. Longitudinal levels
and bouts of objectively measured sedentary time among young Australian
children in the HAPPY study. J Sci Med Sport. 2016;19(3):232–6.
14. Berglind D, Tynelius P. Objectively measured physical activity patterns,
sedentary time and parent-reported screen-time across the day in four-year-
old Swedish children. BMC Public Health. 2017;18(1):69.
15. Ellis YG, Cliff DP, Janssen X, Jones RA, Reilly JJ, Okely AD. Sedentary time,
physical activity and compliance with IOM recommendations in young
children at childcare. Prev Med Rep. 2017;7:221–6.
16. Kuzik N, Clark D, Ogden N, Harber V, Carson V. Physical activity and
sedentary behaviour of toddlers and preschoolers in child care centres in
Alberta, Canada. Can J Public Health. 2015;106(4):178–83.
17. Baquet G, Stratton G, Van Praagh E, Berthoin S. Improving physical activity
assessment in prepubertal children with high-frequency accelerometry
monitoring: a methodological issue. Prev Med. 2007;44(2):143–7.
18. Aadland E, Andersen LB, Anderssen SA, Resaland GK, Kvalheim OM. Associations
of volumes and patterns of physical activity with metabolic health in children: a
multivariate pattern analysis approach. Prev Med. 2018;115:12–8.
19. Verswijveren SJ, Lamb KE, Bell LA, Timperio A, Salmon J, Ridgers ND. Associations
between activity patterns and cardio-metabolic risk factors in children and
adolescents: a systematic review. PLoS One. 2018;13(8):e0201947.
20. Bingham DD, Costa S, Hinkley T, Shire KA, Clemes SA, Barber SE. Physical
activity during the early years: A systematic review of correlates and
determinants. Am J Prev Med. 2016;51(3):384–402.
21. Campbell K, Lioret S, McNaughton S, Crawford D, Salmon J, Ball K, et al. A
parent-focused intervention to reduce Infant obesity risk behaviors: a
randomized trial. Pediatrics. 2013;131(4):652-60.
22. Campbell KJ, Hesketh K, Crawford D, Salmon J, Ball K, McCallum Z. The
Infant feeding activity and nutrition trial (INFANT) an early intervention to
prevent childhood obesity: cluster-randomised controlled trial. BMC Public
Health. 2008;8(1):103.
23. Hesketh KD, Campbell K, Salmon J, McNaughton SA, McCallum Z, Cameron
A, et al. The Melbourne Infant feeding, activity and nutrition trial (InFANT)
program follow-up. Contemp Clin Trials. 2013;34(1):145–51.
24. Hinkley T, O'Connell E, Okely AD, Crawford D, Hesketh K, Salmon J.
Assessing volume of accelerometry data for reliability in preschool children.
Med Sci Sports Exerc. 2012;44(12):2436–41.
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 8 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

25. Pate RR, Almeida MJ, McIver KL, Pfeiffer KA, Dowda M. Validation and
calibration of an accelerometer in preschool children. Obesity. 2006;14(11):
2000–6.
26. Ridgers ND, Timperio A, Crawford D, Salmon J. Five-year changes in school
recess and lunchtime and the contribution to children's daily physical
activity. Br J Sports Med. 2012;46(10):741–6.
27. Hnatiuk J, Ridgers ND, Salmon J, Campbell K, McCallum Z, Hesketh K.
Physical activity levels and patterns of 19-month-old children. Med Sci
Sports Exerc. 2012;44(9):1715–20.
28. Catellier DJ, Hannan PJ, Murray DM, Addy C, Conway T, Yang S, et al.
Imputation of missing data when measuring physical activity by
accelerometry. Med Sci Sports Exerc. 2005;37(11):S555–S62.
29. StataCorp. Stata Statistical Software: Release 14. College Station: StataCorp
LP; 2015.
30. Twisk J. Applied multilevel analysis. Cambridge: Cambridge University Press;
2006.
31. Department of Health. Australian 24-hour movement guidelines for the
early years (birth to 5 years): an integration of physical activity, sedentary
behaviour and sleep. 2017.
32. Tremblay MS, Chaput J-P, Adamo KB, Aubert S, Barnes JD, Choquette L, et
al. Canadian 24-hour movement guidelines for the early years (0–4 years):
an integration of physical activity, sedentary behaviour, and sleep. BMC
Public Health. 2017;17(5):874.
33. Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al.
Systematic review of the relationships between objectively measured
physical activity and health indicators in school-aged children and youth 1.
Appl Physiol Nutr Metab. 2016;41(6):S197–239.
34. Haywood KMG, Nancy. Lifespan motor development. 5th ed. Champaign:
Human Kinetics; 2009. p. 391.
35. Malina RM, Bouchard C, Bar-Or O. Heart, blood and lungs. Growth,
maturation and physical activity. 2nd ed. Champaign: Human Kinestics;
2004. p. 181–93.
36. Hesketh KD, Crawford DA, Abbott G, Campbell KJ, Salmon J. Prevalence and
stability of active play, restricted movement and television viewing in
infants. Early Child Dev Care. 2015;185(6):883–94.
37. Brooke HL, Atkin AJ, Corder K, Brage S, van Sluijs EMF. Frequency and
duration of physical activity bouts in school-aged children: a comparison
within and between days. Prev Med Rep. 2016;4:585–90.
38. Bailey RC, Olson J, Pepper SL, Porszasz J, Barstow TJ, Cooper DM. The level
and tempo of children’s physical activities: an observational study. Med Sci
Sports Exerc. 1995;27(7):1033–41.
39. Sanders T, Cliff DP, Lonsdale C. Measuring adolescent Boys' physical activity:
bout length and the influence of accelerometer epoch length. PLoS One.
2014;9(3):e92040.
40. Razak LA, Yoong SL, Wiggers J, Morgan PJ, Jones J, Finch M, et al. Impact of
scheduling multiple outdoor free-play periods in childcare on child
moderate-to-vigorous physical activity: a cluster randomised trial. Int J
Behav Nutr Phys Act. 2018;15(1):34.
41. Sigelman CR, Elizabeth. Lifespan human development. 7th ed. Belmont:
Cengage Learning; 2012.
42. Byun W, Dowda M, Pate RR. Correlates of objectively measured sedentary
behavior in US preschool children. Pediatrics. 2011;128(5):937–45.
43. Sterdt E, Liersch S, Walter U. Correlates of physical activity of children and
adolescents: a systematic review of reviews. Health Educ J. 2014;73(1):72–89.
44. Morgan PJ, Young MD, Barnes AT, Eather N, Pollock ER, Lubans DR.
Engaging fathers to increase physical activity in girls: the “dads and
daughters exercising and empowered”(DADEE) randomized controlled trial.
Ann Behav Med. 2018;53(1):39–52.
45. Hnatiuk J, Salmon J, Hinkley T, Okely A, Trost SG. A review of preschool
children's physical activity and sedentary time using objective measures.
Am J Prev Med. 2014;47(4):487–97.
46. Sirard JR, Trost SG, Pfeiffer KA, Dowda M, Pate RR. Calibration and evaluation
of an objective measure of physical activity in preschool children. J Phys Act
Health. 2005;2(3):345.
Hnatiuk et al. International Journal of Behavioral Nutrition and Physical Activity (2019) 16:42 Page 9 of 9
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com