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

Transcription

1 Note. This article will be published in a forthcoming issue of the. 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 Authors: Rachel G. Walker 1, Joyce Obeid 1, Thanh Nguyen 1, Hilde Ploeger 2, Nicole A. Proudfoot 1, Cecily Bos 1, Anthony K. Chan 1, Linda Pedder 1, Robert M. Issenman 1, Katrin Scheinemann 1, Maggie J. Larche 1, Karen McAssey 1, and Brian W. Timmons 1 Affiliations: 1 Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada. 2 Department of Rehabilitation, University of Amsterdam, Amsterdam, The Netherlands. Running Title: Sedentary Behaviour in Pediatric Chronic Disease. Journal: Acceptance Date: September 26, Human Kinetics, Inc. DOI:

2 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.

3 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.

4 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 (FEV 1 ) 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.

5 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/height 2. 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 parentor 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.

6 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 accelerometerderived 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 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.

7 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 ± 4.8, p = 0.03) and during the winter compared to the fall (47.7 ± 3.4 vs ± 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).

8 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 ± 4.5 min/h, p = 0.06) or as a percent of wear time (77.6 ± 7.2% vs ± 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).

9 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 sexmatched 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

10 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.

11 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 activityrelated 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 proxy categories in order to capture the majority of time considered sedentary (e.g. screen time, car time, indoor time, etc.) (26). However these categories may not be representative of all the potential sedentary behaviours in which an individual might engage. Conversely, an objective measure can determine the total volume of time an individual spends sedentary; however, it is unable to identify different types of sedentary behaviours (26). The

12 sedentary behaviour questionnaire used in this study measured only screen-based behaviours. However it is possible that differences in non-screen based sedentary behaviours (e.g. reading and playing board games) may exist between children with a chronic disease and healthy children. Finally, since parents filled out the sedentary behaviour questionnaire on behalf of their children, it is possible that the results may have differed, particularly for older children, had the participants filled it out themselves. Conclusion In conclusion, this study helps fill a knowledge gap with regards to understanding sedentary time and screen-based sedentary behaviours in children with a chronic disease. Our data indicate that children with a chronic disease are highly sedentary, similar to that of their healthy peers. Given that children with a chronic disease may experience unique challenges, it is important to examine disease-specific correlates and determinants of sedentary time and behaviours in children with a chronic disease, in order to develop sustainable and effective interventions to reduce sedentary behaviour in this population. The benefits of reducing sedentary behaviour in children with a chronic disease would be particularly meaningful and potentially have added impact in reducing risks of secondary health complications for this population.

13 REFERENCES (1) Aman J, Skinner TC, de Beaufort CE, Swift PG, Aanstoot HJ, Cameron F. Associations between physical activity, sedentary behavior, and glycemic control in a large cohort of adolescents with type 1 diabetes: the Hvidoere Study Group on Childhood Diabetes. Pediatr Diabetes 2009 Jun;10(4): (2) Bar-Or O, Rowland TW. Pediatric Exercise Medicine: From Physiologic Principles to Health Care Applications. Champaign,IL: (3) Bos C, Walker RG, Proudfoot NA, Strike K, Nagel K, Chan AKC, et al. Physical Activity Measured by High-Frequency Accelerometry in Boys with Hemophilia [Abstract]. Hemophilia 2012;18(S3):192. (4) Cohen J. A power primer. Psychol Bull 1992 Jul;112(1): (5) Cohen J. Statistical power analysis for the behavioral sciences. 8 ed. New York: Academic Press; (6) Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS. Physical activity of Canadian children and youth: accelerometer results from the 2007 to 2009 Canadian Health Measures Survey. Health Rep 2011 Mar;22(1): (7) Colley RC, Garriguet D, Janssen I, Wong SL, Saunders TJ, Carson V, et al. The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: results from the Canadian Health Measures Survey. BMC Public Health 2013;13:200. (8) Ewalt LA, Danduran MJ, Strath SJ, Moerchen V, Swartz AM. Objectively assessed physical activity and sedentary behaviour does not differ between children and adolescents with and without a congenital heart defect: a pilot examination. Cardiol Young 2012 Feb;22(1): (9) Foley LS, Maddison R, Jiang Y, Olds T, Ridley K. It's not just the television: survey analysis of sedentary behaviour in New Zealand young people. Int J Behav Nutr Phys Act 2011;8:132. (10) Gonzalez LM, Peiro-Velert C, Devis-Devis J, Valencia-Peris A, Perez-Gimeno E, Perez- Alenda S, et al. Comparison of physical activity and sedentary behaviours between young haemophilia A patients and healthy adolescents. Haemophilia 2011 Jul;17(4): (11) Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al CDC Growth Charts for the United States: methods and development. Vital Health Stat May;(246): (12) Lubans DR, Hesketh K, Cliff DP, Barnett LM, Salmon J, Dollman J, et al. A systematic review of the validity and reliability of sedentary behaviour measures used with children and adolescents. Obes Rev 2011 Oct;12(10): (13) Manns PJ, Dunstan DW, Owen N, Healy GN. Addressing the nonexercise part of the activity continuum: a more realistic and achievable approach to activity programming for adults with mobility disability? Phys Ther 2012 Apr;92(4):

14 (14) Michaliszyn SF, Faulkner MS. Physical activity and sedentary behavior in adolescents with type 1 diabetes. Res Nurs Health 2010 Oct;33(5): (15) Mitchell JA, Mattocks C, Ness AR, Leary SD, Pate RR, Dowda M, et al. Sedentary behavior and obesity in a large cohort of children. Obesity (Silver Spring) 2009 Aug;17(8): (16) Mitchell JA, Pate RR, Dowda M, Mattocks C, Riddoch C, Ness AR, et al. A prospective study of sedentary behavior in a large cohort of youth. Med Sci Sports Exerc 2012 Jun;44(6): (17) Nguyen T, Obeid J, Ploeger HE, Takken T, Pedder L, Timmons BW. Inflammatory and growth factor response to continuous and intermittent exercise in youth with cystic fibrosis. J Cyst Fibros 2012 Mar;11(2): (18) Nguyen T, Obeid J, Walker RG, Krause MP, Hawke TJ, McAssey K, et al. Fitness and physical activity in youth with type 1 diabetes mellitus in good or poor glycemic control. Pediatr Diabetes 2014 Jan 20. (19) Obeid J, Larche MJ, Timmons BW. Optimizing the Wingate Anaerobic Cycling Test for youth with juvenile idiopathic arthritis. Pediatr Exerc Sci 2011 Aug;23(3): (20) Obeid J, Nguyen T, Gabel L, Timmons BW. Physical activity in Ontario preschoolers: prevalence and measurement issues. Appl Physiol Nutr Metab 2011 Apr;36(2): (21) Olds TS, Maher CA, Ridley K, Kittel DM. Descriptive epidemiology of screen and nonscreen sedentary time in adolescents: a cross sectional study. Int J Behav Nutr Phys Act 2010;7:92. (22) Owen N, Healy GN, Howard B, Dunstan DW. Too Much Sitting: Health Risks of Sedentary Behaviour and Opportunities for Change. Research Digest 2012;13(3). (23) Ploeger H, Obeid J, Nguyen T, Takken T, Issenman R, de GM, et al. Exercise and inflammation in pediatric Crohn's disease. Int J Sports Med 2012 Aug;33(8): (24) Scheinemann K, Obeid J, Timmons BW. Fitness, physical activity, and body composition after treatment for a CNS tumour [Abstract]. Neuro-Oncology 2012;14(S1):i134-i135. (25) Sundberg F, Forsander G, Fasth A, Ekelund U. Children younger than 7 years with type 1 diabetes are less physically active than healthy controls. Acta Paediatr 2012 Nov;101(11): (26) Tremblay MS, Colley RC, Saunders TJ, Healy GN, Owen N. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab 2010 Dec;35(6): (27) Tremblay MS, LeBlanc AG, Janssen I, Kho ME, Hicks A, Murumets K, et al. Canadian Sedentary Behaviour Guidelines for Children and Youth. Applied Physiology Nutrition and Metabolism-Physiologie Appliquee Nutrition et Metabolisme 2011;36(1): (28) Tremblay MS, LeBlanc AG, Kho ME, Saunders TJ, Larouche R, Colley RC, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. International Journal of Behavioral Nutrition and Physical Activity 2011;8.

15 (29) Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of Accelerometer Cut Points for Predicting Activity Intensity in Youth. Med Sci Sports Exerc 2011;43(7): (30) van BM, van der Net J, Hulzebos E, Helders PJ, Takken T. The Utrecht approach to exercise in chronic childhood conditions: the decade in review. Pediatr Phys Ther 2011;23(1):2-14. (31) Wilkes DL, Schneiderman JE, Nguyen T, Heale L, Moola F, Ratjen F, et al. Exercise and physical activity in children with cystic fibrosis. Paediatr Respir Rev 2009 Sep;10(3):105-9.

16 Table 1. Characteristics of children with a chronic disease. BT Haemo T1DM JIA CF CD Combined n = 12 n = 10 n = 11 n = 11 n = 6 n = 15 n = 65 Age (yrs) 14.3 ± ± ± ± ± ± 2.5 a 13.8 ± 3.1 Sex (M/F) 6/6 10/0 7/4 4/7 4/2 14/1 45/20 BMI %ile 69.5 ± 26.2 b 55.6 ± ± ± ± ± ± 26.6 Wear Time h/day 12.4 ± ± ± ± ± ± ± 1.4 Sedentary Time h/day 9.9 ± ± ± ± ± ± ± 1.5 min/h 47.9 ± ± ± ± ± ± ± 4.2 % WT 79.4 ± ± ± ± ± ± ± 7.0 Data are presented as mean ± SD. BT, brain tumour survivors; Haemo, haemophilia; T1DM, type 1 diabetes mellitus; JIA, juvenile idiopathic arthritis; CF, cystic fibrosis; CD, Crohn s disease; BMI%ile, body mass index percentile, based on the Centers for Disease Control and Prevention reference data (10); % WT, percent of wear time. a Significantly different from Haemo, p = b Significantly different from CF, p = 0.04.

17 Table 2. Distribution of children with a chronic disease according to type and duration of parentreported screen time behaviours. BT Haemo T1DM JIA CF CD Combined Television a <1 hour 4 (36.4) 4 (44.4) 2 (18.2) 2 (50.0) 2 (33.3) 4 (30.8) 18 (33.3) 1-2 hours 4 (36.4) 4 (44.4) 8 (72.7) 2 (50.0) 3 (50.0) 6 (46.2) 27 (50.0) 2-3 hours 2 (18.2) 1 (11.1) 1 (9.1) 0 (0.0) 1 (16.7) 2 (15.4) 7 (13.0) >3 hours 1 (9.1) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (7.7) 2 (3.7) Computer b <1 hour 6 (85.7) 3 (42.9) 5 (55.6) 3 (75.0) 5 (83.3) 3 (23.1) 25 (54.3) 1-2 hours 1 (14.3) 4 (57.1) 4 (44.4) 1 (25.0) 0 (0.0) 7 (53.8) 17 (37.0) 2-3 hours 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (16.7) 1 (7.7) 2 (4.3) >3 hours 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (15.4) 2 (4.3) Video Games c <1 hour 7 (63.6) 3 (42.9) 4 (36.4) 3 (75.0) 2 (33.3) 5 (35.7) 24 (45.3) 1-2 hours 3 (27.3) 3 (42.9) 5 (45.5) 1 (25.0) 1 (16.7) 6 (42.9) 19 (35.8) 2-3 hours 1 (9.1) 1 (14.3) 2 (18.2) 0 (0.0) 2 (33.3) 1 (7.1) 7 (13.2) >3 hours 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 1 (16.7) 2 (14.3) 3 (5.7) Data are presented as number of participants (percentage of group). a Due to incomplete answers, sample size varies by disease: BT (n=11); Haemo (n=9); T1DM (n=11); JIA (n=4); CF (n=6); CD (n=13); Combined (n=54). b Due to incomplete answers, sample size varies by disease: BT (n=7); Haemo (n=7); T1DM (n=9); JIA (n=4); CF (n=6); CD (n=13); Combined (n=46). c Due to incomplete answers, sample size varies by disease: BT (n=11); Haemo (n=7); T1DM (n=11); JIA (n=4); CF (n=6); CD (n=14); Combined (n=53).

18 Table 3. Characteristics of children with a chronic disease compared to age- and sex-matched healthy controls. Chronic Disease Healthy Controls Δ Effect Size n = 29 n = 29 Age (yrs) 14.0 ± ± 2.5 Sex (M/F) 21/8 21/8 BMI %ile 53.2 ± ± 19.0 Wear Time h/day 13.2 ± ± 1.1 Sedentary Time h/day 10.2 ± ± ± [9.7, 10.7] [9.5, 10.8] [-0.6, 0.8] min/h 46.6 ± ± ± [44.9, 48.2] [42.6, 46.1] [0.4, 4.1] % WT 77.6 ± ± ± [74.9, 80.3] [71.0, 76.8] [0.63, 6.8] Data are presented as mean ± SD. BMI %ile, body mass index percentile, based on the Centers for Disease Control and Prevention reference data (10); % WT, percent of wear time.

19 Table 4. Distribution of children according to type and duration of parent-reported screen time behaviours. Television Computer Video Games Chronic Disease Healthy Controls Chronic Disease Healthy Controls Chronic Disease Healthy Controls n=20 n=20 n=19 n=19 n=22 n=22 <1 hour 6 (30.0) 5 (25.0) 9 (47.4) 12 (63.2) 11 (50.0) 12 (54.5) 1-2 hours 12 (60.0) 12 (60.0) 9 (47.4) 6 (31.6) 8 (36.4) 4 (18.2) 2-3 hours 2 (10.0) 2 (10.0) 0 (0.0) 1 (5.3) 3 (13.6) 4 (18.2) >3 hours 0 (0.0) 1 (5.0) 1 (5.3) 0 (0.0) 0 (0.0) 2 (9.1) Data are presented as number of participants (percentage of group). Due to incomplete answers, sample size varies by screen time activity.