Sedentary Time and Screen-based Sedentary Behaviours of Children with a Chronic Disease

Sedentary Behaviour in Children with a Chronic Disease“Sedentary Time and Screen-based Sedentary Behaviours of Children with a Chronic Disease” by Walker RG et al.
Pediatric Exercise Science
© 2014 Human Kinetics, Inc.
Note. This article will be published in a forthcoming issue of the
Pediatric Exercise Science. The article appears here in its accepted,
peer-reviewed form, as it was provided by the submitting author. It has
not been copyedited, proofread, or formatted by the publisher.
Section: Original Research
Article Title: Sedentary Time and Screen-based Sedentary Behaviours of Children with a
Chronic Disease
1 , Thanh Nguyen
1 , Hilde Ploeger
2 , Nicole A.
1 , Karen McAssey
1
2 Department of Rehabilitation, University of Amsterdam, Amsterdam, The Netherlands.
Running Title: Sedentary Behaviour in Pediatric Chronic Disease.
Journal: Pediatric Exercise Science
©2014 Human Kinetics, Inc.
DOI: http://dx.doi.org/10.1123/pes.2014-0074
“Sedentary Time and Screen-based Sedentary Behaviours of Children with a Chronic Disease” by Walker RG et al.
ABSTRACT
The objectives of this study were to (i) assess sedentary time and prevalence of screen-based
sedentary behaviours of children with a chronic disease and (ii) compare sedentary time and
prevalence of screen-based sedentary behaviours to age- and sex-matched healthy controls.
Sixty-five children (aged 6-18 years) with a chronic disease participated: survivors of a brain
tumor, haemophilia, type 1 diabetes mellitus, juvenile idiopathic arthritis, cystic fibrosis and
Crohn’s disease. Twenty-nine of these participants were compared to age- and sex-matched
healthy controls. Sedentary time was measured objectively by an ActiGraph GT1M or GT3X
accelerometer worn for 7 consecutive days and defined as <100 counts per minute. A
questionnaire was used to assess screen-based sedentary behaviours. Children with a chronic
disease engaged in an average of 10.2±1.4 hours of sedentary time per day, which comprised
76.5±7.1% of average daily monitoring time. There were no differences between children with a
chronic disease and controls in sedentary time (adjusted for wear time, p=0.06) or in the
prevalence of TV watching, and computer or video game usage for varying durations (p=0.78,
p=0.39 and, p=0.32 respectively). Children with a chronic disease, though relatively healthy,
accumulate high levels of sedentary time, similar to those of their healthy peers.
INTRODUCTION
Canadian youth spend approximately 8.5 hours per day, or 62% of waking hours,
engaged in sedentary behaviours (6). This is concerning since sedentary behaviour is
negatively associated with health (15). For children whose lives are complicated by chronic
disease, the consequences of adopting a sedentary lifestyle may be even more serious.
Children with a chronic disease grow up with a daily burden of disease, such as frequent
doctor visits and/or the use of daily treatments (31). Real or perceived limitations imposed by
their disease may encourage the adoption of a sedentary lifestyle (30), and lead to a cycle of
de-conditioning (2). However, there is a lack of information regarding the sedentary behaviours
of children with a chronic disease. Investigating this issue across multiple diagnoses could
illuminate common themes and characteristics of the lifestyles of these children.
Traditionally, sedentary time has been evaluated using self-reported screen time (9).
This method is subject to recall bias (7) and often limited by presenting only a few of the
potential sedentary behaviours in which an individual might engage. Accelerometry, on the other
hand, is an objective method of capturing sedentary time, which can determine the total volume
of time an individual spends sedentary; however, it is unable to differentiate types of sedentary
behaviours (26). Given both methods’ limitations, the use of a combination of measurement
tools to assess sedentary time and behaviours has been recommended (12). The aim of the
current study was to combine accelerometry and parent-report measures to (i) assess total
sedentary time and prevalence of screen-based sedentary behaviours of children with a chronic
disease; and (ii) compare levels of sedentary time and prevalence of screen-based sedentary
behaviours to age- and sex-matched healthy controls.
METHODS
Participants
Data from 65 children and adolescents (6-18 years) with a chronic disease who had
previously participated in physical activity-related studies in our laboratory between January
2008 and December 2012 were included in this study (3;17-19;23;24). Chronic diseases
included: survivors of a brain tumor (BT; n=12), haemophilia (Haemo; n=10), type 1 diabetes
mellitus (T1DM; n=11), juvenile idiopathic arthritis (JIA; n=11), cystic fibrosis (CF; n=6) and
Crohn’s disease (CD; n=15). Survivors of a brain tumor were tested ≥1 year post treatment
(3.90 ± 2.58 years). Of 10 participants with haemophilia A or B, 5 were severe and 5 were
moderate. Six of the boys with haemophilia were receiving prophylaxis treatment. Seven
participants with type 1 diabetes mellitus had good glycemic control as defined by glycosylated
hemoglobin (HbA1c) ≤ 7.5 % for 9 months (7.3 ± 0.5 %) and four had poor glycemic control as
defined by HbA1c ≥ 9.0 % for 9 months (10.5 ± 0.5 %). The distribution of subtypes among
participants with juvenile idiopathic arthritis was as follows: 4 oligoarticular, 5 polyarticular, 1
systemic and 1 psoriatic. These patients experienced no pain or swelling in any joint for at least
2 months prior to exercise testing. Patients with cystic fibrosis were clinically stable and had an
average predicted forced expiratory volume in 1 s (FEV1) of 96.3 ± 25.8 %. All participants with
Crohn’s disease were in remission, as determined by a score of <10 on the Pediatric Crohn’s
Disease Activity Index. Twenty-nine of these participants with a chronic disease were matched
to an available healthy control, by chronological age and sex. Children in the healthy control
group were selected from our research database. Written informed consent was collected from
all participants and a parent or guardian. Study procedures were approved by the Hamilton
Health Sciences/ Faculty of Health Sciences Research Ethics Board.
Assessment of Anthropometry
Standing height was measured to the nearest 0.1 cm and body mass to the nearest 0.1
kg. Body mass index (BMI) was calculated as mass/height2. Age- and sex-specific BMI
percentiles were calculated according to the Centers for Disease Control and Prevention
reference data (11).
Assessment of Sedentary Time
The Actigraph GT1M and GT3X (Fort Walton Beach, Fla, USA) activity monitors were
used to measure sedentary time over 7 consecutive days. Three-second epochs (i.e., sampling
intervals) were used to avoid underestimating sedentary time with a longer epoch. Participants
were instructed to wear the accelerometer over their right hip during all waking hours except
when participating in water-related activities. Each participant was given a logbook to record
times the accelerometer was put on and taken off. Wear time for ≥ 10 hours per day and ≥ 4 of
7 days (one of which being a weekend day) (6) was required to be included in the
accelerometer analyses. Any activity counts present in the accelerometer output during parent-
or participant-indicated non-wear time were removed (20). Data from the vertical axis were then
uploaded to a Microsoft Excel-based Visual Basic data reduction program to determine total
wear time and total sedentary time (20). Sedentary time was determined using the widely
accepted cut-point of 100 counts per minute (29). We therefore divided this cut-point by 20 to
analyze our data collected in 3s epochs. Thus, sedentary time was defined as ≤5 counts per 3s.
Assessment of Screen-based Sedentary Behaviours
Types of screen-based sedentary behaviours were assessed using a questionnaire,
which asked each parent to indicate the number of hours in a typical day their child spends
watching television, using a computer, or playing video games. The response categories in
hours per day were <1, 1-2, 2-3, and >3.
Statistical Analyses
All data are presented as mean ± SD, unless otherwise indicated. To examine
differences in participant characteristics and volume of accelerometer-derived sedentary time
between chronic disease groups, 1-way ANOVAs were performed. If significant, Tukey’s
honestly significant difference post hoc test was used to identify differences between disease
groups. Age, sex, BMI percentile and season were included as covariates in the 1-way ANOVA
comparing sedentary time across disease groups. Fisher’s exact test was used to determine
differences in the prevalence of questionnaire-derived screen-based sedentary behaviours
across disease groups. To examine differences in BMI percentile and volume of accelerometer-
derived sedentary time in children with a chronic disease compared to age- and sex-matched
healthy controls, independent t-tests were used. Cohen’s d equation was used to calculate the
effect size of differences in sedentary time between children with a chronic disease and healthy
controls (5). An effect size of 0.2 was thought to represent a small effect, 0.5 a moderate effect
and ≥ 0.8 a large effect (4). A Chi-square test was used to assess differences in the frequency
of seasons in which the accelerometer was worn between children with a chronic disease and
healthy controls. Fisher’s exact test was used to determine differences in the prevalence of
questionnaire-derived screen-based sedentary behaviour between children with a chronic
disease and healthy controls. Statistical significance was set at P ≤ 0.05. ANOVAs were
performed in STATISTICA (StatSoft, Tulsa, Okla., USA) and t tests, Chi-square tests and
Fisher’s exact tests were calculated in SPSS (version 17.0, Chicago, Ill., USA).
RESULTS
Sedentary Time in Children with a Chronic Disease
Characteristics of the 65 children with a chronic disease are presented in Table 1.
Males comprised 69.2% of this sample and the average age was 13.8 ± 3.0 years. As
might be expected, there were significant differences in some of the participant characteristics
between disease groups. On average, children with a chronic disease wore the accelerometer 6
of the 7 required monitoring days, with average daily monitoring time ranging from 10.7 to 15.5
h (13.3 ± 1.1 h).
Participants spent 10.2 ± 1.4 hours per day engaged in sedentary time, which comprised
76.5 ± 7.1% of average daily monitoring time. There were no significant differences in average
daily time spent engaged in sedentary time (h/day) across disease groups (p = 0.18). On
average, children with a chronic disease spent 45.9 ± 4.2 min per hour sedentary, with no
significant difference in average daily min of sedentary time per hour of wear time across
disease groups (p = 0.69).
Among all participants, there was a significant relationship between sedentary time
(min/hr) and age (r = 0.61, p < 0.001). There was no difference in sedentary time (min/hr)
according to gender (p = 0.35). Participants engaged in greater amounts of sedentary time
(min/hr) in the summer compared to the fall (47.4 ± 4.2 vs. 43.5 ± 4.8, p = 0.03) and during the
winter compared to the fall (47.7 ± 3.4 vs. 43.5 ± 4.8, p = 0.02). The same results were found for
sedentary time as a % percent of wear time (results not shown).
Screen-based Sedentary Behaviours in Children with a Chronic Disease
Fifty percent of parents reported that their children watched TV for 1-2 hours per day.
The percentage of parents that reported their children used the computer and played video
games, each for <1 hour per day, was 54.3 and 45.3%, respectively. There were no significant
differences between disease groups in the prevalence of participants who reported watching
television, using the computer and playing video games for varying durations (Table 2; p = 0.97,
p = 0.22 and p = 0.69 respectively).
Sedentary Time Compared to Age- and Sex-Matched Healthy Controls
Characteristics of the 29 children with a chronic disease who were matched to healthy
controls, based on age and sex, are presented in Table 3. Males comprised 72.4% of each
group, the combined average age was 13.9 ± 2.5 years, and there was no significant difference
in BMI %ile or frequency of seasons in which the accelerometer was worn, between groups. On
average, both groups wore the accelerometer 6 of the 7 required monitoring days with average
daily monitoring time ranging from 10.7 to 16.2 h (13.4 ± 1.1). There was no significant
difference in sedentary time per hour of wear time (46.6 ± 4.3 min/h vs. 44.3 ± 4.5 min/h, p =
0.06) or as a percent of wear time (77.6 ± 7.2% vs. 73.9 ± 7.5%, p = 0.06), however a strong
trend emerged and suggested a moderate effect size for both variables. For example, the
difference in sedentary time per hour of wear time amounts to an average of 29.0 additional
minutes spent sedentary in a 13.2 h wear period or 3.4 additional hours spent sedentary per
week compared to healthy controls.
Screen-based Sedentary Behaviours Compared to Age- and Sex-Matched Healthy
Controls
Sixty percent of parents reported that participants watched TV for <1 hour per day and
60% reported that their children played video games for <1 hour per day. An equal proportion of
parents reported that children with a chronic disease used the computer for <1 and 1-2 hours
per day (47.4%), while the greatest proportion of parents reported that healthy children used it
for <1 hour per day (63.2%). There were no inter-group differences in the prevalence of
participants who reported watching television, using the computer and playing video games for
varying durations (Table 4; p = 0.78, p = 0.39 and p = 0.32, respectively).
DISCUSSION
Our data indicate that children with a chronic disease spend on average 10.2 hours per
day sedentary. In addition, children with a chronic disease in this sample accumulate similar
levels of sedentary time and do not differ in the prevalence of engagement in screen-based
sedentary behaviours for varying durations, compared to controls. To the best of our knowledge,
this is the first study to assess total sedentary time and prevalence of screen-based behaviours
in multiple pediatric chronic disease groups using both direct and indirect measures.
The first objective of our study was to measure sedentary time in children with a chronic
disease using accelerometry and sedentary behaviours using a parent-report questionnaire.
Only one other cross-sectional study has examined this topic using a combination of measures,
but only involving a single disease group (10). Four previous studies involving children and/or
adolescents from a single chronic disease group have measured either sedentary time (8;14;25)
or behaviours (1) separately. One of the five previous studies reported levels of sedentary time
among adolescents with T1DM similar to ours (14). However, the remaining four studies
reported either lower (1;8) or higher levels (10;25) of sedentary time compared to the
participants in our study. This is likely due to the use of a different accelerometer cut point for
sedentary time (10), younger average age of participants, who are reportedly less sedentary
than older children (8;16), different accelerometer wear instructions (wear during sleep) (25),
and the use of only a questionnaire that measured screen time (1), which by itself is not an
appropriate surrogate for total sedentary time (21).
The second objective of our study was to compare total sedentary time and prevalence
of screen-based sedentary behaviours in children with a chronic disease to an age- and sex-
matched healthy control group. There was not a significant difference in sedentary time (min/h
or % WT) between groups, however a strong trend emerged and was consistent with a
moderate effect. On average, children with a chronic disease spent an additional 2.2 minutes
per hour engaged in sedentary time compared to healthy controls, which amounted to an
additional 3.4 hours spent sedentary per week. Three previous studies have compared
sedentary time in a single chronic disease group to healthy controls (8;10;25). One study
concluded that children with haemophilia were less sedentary than healthy controls (10);
however, the remaining studies found no difference in sedentary time in children with congenital
heart disease or T1DM (8;25). In the study involving youth with haemophilia, controls were not
matched for age or sex, resulting in a higher average age of the control group compared to the
haemophilia group. Older children are reportedly more sedentary than younger children (16).
Potential differences in sedentary time between children with a chronic disease and healthy
children may be even more exaggerated at an older age.
There was no difference in the prevalence of children watching television, using the
computer or playing video games, for varying durations between chronic disease and healthy
control groups. However, it is possible that the sedentary behaviours of children with a chronic
disease may not be accounted for by conventional screen-based sedentary behaviour
questionnaires. This highlights the importance of identifying and subsequently quantifying
possible disease-specific sedentary behaviours. We hypothesize that children with a chronic
disease might engage in different sedentary behaviours than healthy peers because they face
unique challenges that encourage the adoption of a sedentary lifestyle. It may be that the daily
burden of disease makes participation in physical activity difficult, as these children can often
experience fatigue, lengthy treatments and a number of co-morbidities (31). Children with a
chronic condition may be restricted due to real or perceived limitations imposed by their disease
(30). Perceived limitations may stem from parents who see their children as vulnerable or ‘at
risk’ (31) and subsequently restrict them to sedentariness. Clearly, more work is required to
better understand the sedentary behaviours of children with a chronic disease.
Increasing evidence supports the association between high levels of sedentary
behaviour and negative health outcomes in children and youth, independent of physical activity
levels (28). As such, the Canadian sedentary behaviour guidelines for children and youth
suggest limiting screen time to no more than 2 hours per day and limiting sedentary transport,
extended sitting and prolonged time spent indoors (27). Clinicians should be encouraged to
promote a reduction in overall sedentary time and an increase in breaks from sedentary time, in
tandem with the current physical activity recommendations (13;22). In the case of children with
a chronic disease, it may be the most feasible option to advise patients to reduce sitting time in
order to act as a stepping-stone to increase other aspects of physical activity (13;22).
Strengths and Limitations
The strengths of our study were the use of both direct and indirect measures of
sedentary time and screen-based behaviours, which is in accordance with the current
recommendations and reduces limitations that are associated with each method individually.
Secondly, we included multiple chronic disease groups to increase the generalizability of our
findings, although we recognize that our patients do not represent every patient with a disease
that we studied. This study did not control for disease severity among participants; however, it is
not expected that this would have played a confounding role since our participants were either
in remission from disease or deemed to be in sufficient health to participate in physical activity-
related research studies. Indeed, had we included patients with more severe disease, the level
of sedentary time may have been even greater. Subjective measures of sedentary behaviour
use global or…