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Background: Ubiquitous car ownership may affect children's activity and health. We assessed the cross-sectional and longitudinal associations between household car ownership and children's daily time spent sedentary (SED) and in moderate to vigorous physical activity (MVPA)., Methods: Pooled cohort data were from the International Children's Accelerometry Database. Outcome measures were average daily accelerometer-measured SED and MVPA (in minutes per day). Exposures were household car ownership (none, 1, and ≥2) and change in car ownership. Associations were examined using multivariable mixed-effects linear regression., Results: Mean age of participants (N = 4193) was 10.4 years (SD = 2.0), 53.4% were girls, and mean follow-up duration (N = 1333) was 3.3 years (SD = 1.1). Cross-sectionally, household car ownership was associated with higher SED (vs none: 1 car: β = 14.1 min/d, 95% CI, 6.7-21.5; ≥2 cars: 12.8, 95% CI, 5.3-20.4) and lower MVPA (vs none: 1 car: β = -8.8, 95% CI, -11.9 to -5.7; ≥2 cars: β = -8.8, 95% CI, -12.0 to -5.7). Associations were stronger in boys than girls and in children from lower socioeconomic backgrounds (SED only). Prospectively, there were no associations with increased car ownership. Reductions in household car ownership (of which 93.1% had ≥ 2 cars at baseline) were associated with a greater reduction in MVPA (vs no change: β = -8.4, 95% CI, -13.9 to -3.0) but not SED., Conclusions: Children in households with car access were more SED and less active than those without. Losing access to a second car was associated with greater decreases in MVPA, potentially related to losing access to activity-enabling environments. Reducing car access and use are important public health targets (eg, reducing air pollution), but their potential impact on children's activity opportunities should be mitigated.

Background: Temporal changes in sedentary behavior patterns reflect the evolving nature of our built and social environments, particularly the expanding availability of electronic media. It is important to understand what types of sedentary behavior are assessed in national surveillance to determine whether, and to what extent, they reflect contemporary patterns. The aims of this review were to describe the characteristics of questionnaires used for national surveillance of sedentary behavior and to identify the types of sedentary behaviors being measured., Method: We reviewed questionnaires from national surveillance systems listed on the Global Observatory for Physical Activity (GoPA!) country cards to locate items on sedentary behavior. Questionnaire characteristics were categorized using the Taxonomy of Self-reported Sedentary Behavior Tools (TASST). The purpose and type of sedentary behaviors captured were classified using the Sedentary Behavior International Taxonomy (SIT)., Results: Overall, 346 surveillance systems were screened for eligibility, of which 93 were included in this review. Most questionnaires used a single-item direct measure of sitting time (n = 78, 84%). Work and domestic were the most frequently captured purposes of sedentary behavior, while television viewing and computer use were the most frequently captured types of behaviors., Conclusion: National surveillance systems should be periodically reviewed in response to evidence on contemporary behavior patterns in the population and the release of updated public health guidelines.

Background: Screen behaviours are highly prevalent in adolescents and may be adversely associated with physical and mental health. Understanding how screen behaviours inter-relate with physical activity and sleep may help to clarify pathways through which they impact health and potential routes to behaviour change. This cross-sectional study examines the association of contemporary screen behaviours with physical activity, sedentary behaviour and sleep in adolescents., Method: Data are from sweep 6 (2015/2016) of the Millennium Cohort Study, conducted when participants were aged 14 years. Outcome variables were accelerometer-assessed overall physical activity and moderate-to-vigorous physical activity (MVPA), self-reported sedentary behaviour and sleep duration. Screen behaviours were assessed using a 24-h time-use diary. Multivariable regression was used to examine the association between screen behaviours and each outcome variable separately for weekdays and weekend days., Results: The use of social network sites was associated with (beta coefficient, 95% confidence interval (CI); minutes/day) less time in MVPA (weekdays: - 5.2 (- 10.3, - 0.04); weekend: - 10.0 (- 15.5, - 4.5)), and sedentary behaviours (weekdays: - 19.8 (- 31.0, - 8.6); weekend: - 17.5 (- 30.9, - 4.1)). All screen behaviours were associated with shorter sleep duration on weekdays, whereas only the use of email/texts and social network sites was associated with shorter sleep duration on weekend days. The association of using social network sites with overall physical activity was stronger in girls than in boys; the association of internet browsing with sedentary behaviour was stronger in boys than in girls., Conclusion: Intervention strategies to enhance MVPA and sleep duration by limiting screen-based activities may be warranted., (© 2022. The Author(s).)

Introduction: The United Kingdom and World Health Organization recently changed their youth physical activity (PA) guidelines from 60 min of moderate- to vigorous-intensity PA (MVPA) every day, to an average of 60 min of MVPA per day, over a week. The changes are based on expert opinion due to insufficient evidence comparing health outcomes associated with different guideline definitions. This study used the International Children's Accelerometry Database to compare approaches to calculating youth PA compliance and associations with health indicators., Methods: Cross-sectional accelerometer data (n = 21,612, 5-18 yr) were used to examine compliance with four guideline definitions: daily method (DM; ≥60 min MVPA every day), average method (AM; average of ≥60 min MVPA per day), AM5 (AM compliance and ≥5 min of vigorous PA [VPA] on ≥3 d), and AM15 (AM compliance and ≥15 min VPA on ≥3 d). Associations between compliance and health indicators were examined for all definitions., Results: Compliance varied from 5.3% (DM) to 29.9% (AM). Associations between compliance and health indicators were similar for AM, AM5, and AM15. For example, compliance with AM, AM5, and AM15 was associated with a lower BMI z-score (statistics are coefficient [95% CI]): AM (-0.28 [-0.33 to -0.23]), AM5 (-0.28 [-0.33 to -0.23], and AM15 (-0.30 [-0.35 to -0.25]). Associations between compliance and health indicators for DM were similar/weaker, possibly reflecting fewer DM-compliant participants with health data and lower variability in exposure/outcome data., Conclusions: Youth completing 60 min of MVPA every day do not experience superior health benefits to youth completing an average of 60 min of MVPA per day. Guidelines should encourage youth to achieve an average of 60 min of MVPA per day. Different guideline definitions affect inactivity prevalence estimates; this must be considered when analyzing data and comparing studies., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)

Background: Screen behaviours are highly prevalent in young people and excessive screen use may pose a risk to physical and mental health. Understanding the timing and social settings in which young people accumulate screen time may help to inform the design of interventions to limit screen use. This study aimed to describe diurnal patterns in adolescents' screen-based behaviours and examine the association of social context with these behaviours on weekdays and weekend days., Methods: Time use diary data are from the sixth wave (2015/2016) of the Millennium Cohort Study, conducted when participants were aged 14 years. Outcome variables were electronic games/Apps, TV-viewing, phone calls and emails/texts, visiting social networking sites and internet browsing. Social context was categorised as alone only, parents only, friends only, siblings only, parents and siblings only. Multilevel multivariable logistic regression was used to examine the association between social contexts and screen activities., Results: Time spent in TV-viewing was greatest in the evening with a peak of 20 min in every hour between 20:00 and 22:00 in both sexes on weekdays/weekend days. Time spent using electronic games/Apps for boys and social network sites for girls was greatest in the afternoon/evening on weekdays and early afternoon/late evening on weekend days. Screen activities were mainly undertaken alone, except for TV-viewing. Compared to being alone, being with family members was associated with (Odds Ratio (95% Confidence Interval)) more time in TV-viewing in both boys and girls throughout the week (Weekdays: Boys, 2.84 (2.59, 3.11); Girls, 2.25 (2.09, 2.43); Weekend days: Boys, 4.40 (4.16, 4.67); Girls, 5.02 (4.77, 5.27)). Being with friends was associated with more time using electronic games on weekend days in both sexes (Boys, 3.31 (3.12, 3.51); Girls, 3.13 (2.67, 3.67))., Conclusions: Reductions in screen behaviours may be targeted throughout the day but should be sensitive to differing context. Family members, friends, and adolescent themselves may be important target groups in behaviour change interventions. Future research to address the complex interplay between social context, content and quality of screen behaviours will aid the design of behaviour change interventions., (© 2022. The Author(s).)

Objective: To examine the evidence on the associations between socioeconomic position and young people's physical activity and sedentary behaviours in the UK., Design: Scoping review., Data Sources: PubMed, SCOPUS and Web of Science databases were searched for articles published up to and including January 2021., Eligibility Criteria for Selecting Studies: Observational studies in children and adolescents (aged 5-18 years) from the UK that had assessed associations between at least one indicator of socioeconomic position and at least one outcome of physical activity and/or sedentary behaviour., Data Extraction and Synthesis: Data were extracted by one reviewer and 20% were double checked. Indicators of socioeconomic position were tabulated with domains of physical activity and sedentary behaviour., Results: Fifty-seven publications were included in the review; 37 publications from 19 studies (k=23) of children and 21 publications from 15 studies (k=23) of adolescents. Most studies were cross-sectional. 63% of studies of children, and 40% of studies of adolescents assessed Index of Multiple Deprivation. Eighteen studies measured physical activity in children, 13 measured sedentary behaviour. Eleven studies of adolescents included a measure of physical activity, 10 included a measure of sedentary behaviour. Among children and adolescents, the association between socioeconomic position and measures of either physical activity or sedentary behaviour was highly variable depending on the measure of both socioeconomic position used and the behavioural outcome, with the exception of higher family affluence which was consistently associated with higher reported physical activity among adolescents., Conclusion: Physical activity and sedentary behaviours of children and adolescents in the UK are complex and influenced by multiple indicators of socioeconomic position that are, in most cases, different across age stages, outcomes examined and measurement tools. Greater consistency in the use and measures of socioeconomic position as well as outcomes of behaviour are required for robust country-specific meta-analyses., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Sedentary behaviors are highly prevalent in youth and may be associated with markers of physical and mental health. This systematic review and meta-analysis aimed to quantify the age-related change in sedentary behavior during childhood and adolescence. Ten electronic databases were searched. Inclusion criteria specified longitudinal observational studies or control group from an intervention; participants aged ≥5 and ≤18 years; a quantitative estimate of the duration of SB; and English language, peer-reviewed publication. Meta-analyses summarized weighted mean differences (WMD) in device-assessed sedentary time and questionnaire-assessed screen-behaviors over 1-, 2-, 3-, or more than 4-year follow-up. Effect modification was explored using meta-regression. Eighty-five studies met inclusion criteria. Device-assessed sedentary time increased by (WMD 95% confidence interval [CI]) 27.9 (23.2, 32.7), 61.0 (50.7, 71.4), 63.7 (53.3, 74.0), and 140.7 (105.1, 176.4) min/day over 1-, 2-, 3-, and more than 4-year follow-up. We observed no effect modification by gender, baseline age, study location, attrition, or quality. Questionnaire-assessed time spent playing video games, computer use, and a composite measure of sedentary behavior increased over follow-up duration. Evidence is consistent in showing an age-related increase in various forms of sedentary behavior; evidence pertaining to variability across socio-demographic subgroups and contemporary sedentary behaviors are avenues for future research., (© 2021 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.)

We examined associations between youth 24-hour activity behaviour compositions and mental health. Data were collected from 359 participants (aged 9-13 years). Activity behaviours (sleep, sedentary time (ST), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA)) were assessed using wrist-worn accelerometers. Questionnaires and a computerized cognitive test battery assessed mental health outcomes. Linear mixed models examined associations between activity behaviour compositions and mental health. Post-hoc analyses modelled the influence of reallocating fixed durations of time between activity behaviours on mental health. ST was associated with worse internalizing problems (all participants; p < 0.05) and poorer prosocial behaviour (primary school participants only; p < 0.05), relative to the other activity behaviours. LPA was associated with worse cognitive test scores among primary school participants; p < 0.05). For all participants, reallocating time to ST from sleep and MVPA was associated with higher internalizing problems. Among primary school participants, reallocating time to ST from any other behaviour was associated with poorer prosocial behaviour, and reallocating time to LPA from any other behaviour was associated with lower executive function. Children's mental health may be promoted by schools integrating opportunities for MVPA throughout the day. Our results provide further evidence for the influence of daily activity behaviours on youth mental health.

Background: Prolonged sitting time is a risk factor for chronic disease, yet recent global surveillance is not well described. The aims were to clarify: (i) the countries that have collected country-level data on self-reported sitting time; (ii) the single-item tools used to collect these data; and (iii) the duration of sitting time reported across low- to high-income countries., Methods: Country-level data collected within the last 10 years using single-item self-report were included. The six-stage methodology: (1) reviewing Global Observatory for Physical Activity! Country Cards; (2-4) country-specific searches of PubMed, the Demographic and Health Survey website and Google; (5) analysing the Eurobarometer 88.4; and (6) country-specific searches for World Health Organization STEPwise reports., Results: A total of 7641 records were identified and screened for eligibility. Sixty-two countries (29%) reported sitting time representing 47% of the global adult population. The majority of data were from high-income (61%) and middle income (29%) countries. The tools used were the International Physical Activity Questionnaire (IPAQ; n = 34), a modified IPAQ (n = 1) or the Global Physical Activity Questionnaire (GPAQ; n = 27). The median of mean daily sitting times was 4.7 (IQR: 3.5-5.1) hours across all countries. Higher-income countries recorded a longer duration of sitting time than lower-income countries (4.9 vs 2.7 h)., Conclusions: This study provides an updated collation of countries collecting self-reported sitting time data. The daily sitting time findings should be interpreted cautiously. Current surveillance of sitting time is limited by a lack of coverage. Measures of population sitting time that are valid, feasible and sensitive to change should be embedded within global surveillance systems, to help guide future policy, research and practice., Trial Registration: Not applicable.

Background: To gain more understanding of the potential health effects of sedentary time, knowledge is required about the accumulation and longitudinal development of young people's sedentary time. This study examined tracking of young peoples' total and prolonged sedentary time as well as their day-to-day variation using the International Children's Accelerometry Database., Methods: Longitudinal accelerometer data of 5991 children (aged 4-17y) was used from eight studies in five countries. Children were included if they provided valid (≥8 h/day) accelerometer data on ≥4 days, including ≥1 weekend day, at both baseline and follow-up (average follow-up: 2.7y; range 0.7-8.2). Tracking of total and prolonged (i.e. ≥10-min bouts) sedentary time was examined using multilevel modelling to adjust for clustering of observations, with baseline levels of sedentary time as predictor and follow-up levels as outcome. Standardized regression coefficients were interpreted as tracking coefficients (low: < 0.3; moderate: 0.3-0.6; high: > 0.6)., Results: Average total sedentary time at study level ranged from 246 to 387 min/day at baseline and increased annually by 21.4 min/day (95% confidence interval [19.6-23.0]) on average. This increase consisted almost entirely of prolonged sedentary time (20.9 min/day [19.2-22.7]). Total (standardized regression coefficient (B) = 0.48 [0.45-0.50]) and prolonged sedentary time (B = 0.43 [0.41-0.45]) tracked moderately. Tracking of day-to-day variation in total (B = 0.04 [0.02-0.07]) and prolonged (B = 0.07 [0.04-0.09]) sedentary time was low., Conclusion: Young people with high levels of sedentary time are likely to remain among the people with highest sedentary time as they grow older. Day-to-day variation in total and prolonged sedentary time, however, was rather variable over time.

Background: Active living approaches seek to promote physical activity and reduce sedentary time across different domains, including through active travel. However, there is little information on how movement behaviours in different domains relate to each other. We used compositional data analysis to explore associations between active commuting and patterns of movement behaviour during discretionary time., Methods and Findings: We analysed cross-sectional and longitudinal data from the UK Biobank study. At baseline (2006-2010) and follow up (2009-2013) participants reported their mode of travel to work, dichotomised as active (walking, cycling or public transport) or inactive (car). Participants also reported activities performed during discretionary time, categorised as (i) screen time; (ii) walking for pleasure; and (iii) sport and do-it-yourself (DIY) activities, summed to produce a total. We applied compositional data analysis to test for associations between active commuting and the composition and total amount of discretionary time, using linear regression models adjusted for covariates. Adverse events were not investigated in this observational analysis. The survey response rate was 5.5%. In the cross-sectional analysis (n = 182,406; mean age = 52 years; 51% female), active commuters engaged in relatively less screen time than those who used inactive modes (coefficient -0.12, 95% confidence interval [CI] -0.13 to -0.11), equating to approximately 60 minutes less screen time per week. Similarly, in the longitudinal analysis (n = 4,323; mean age = 51 years; 49% female) there were relative reductions in screen time in those who used active modes at both time points compared with those who used inactive modes at both time points (coefficient -0.15, 95% confidence interval [CI] -0.24 to -0.06), equating to a difference between these commute groups of approximately 30 minutes per week at follow up. However, as exposures and outcomes were measured concurrently, reverse causation is possible., Conclusions: Active commuting was associated with a more favourable pattern of movement behaviour during discretionary time. Active commuters accumulated 30-60 minutes less screen time per week than those using inactive modes. Though modest, this could have a cumulative effect on health over time., Competing Interests: The authors have declared that no competing interests exist.

Background: Large, heterogeneous datasets are required to enhance understanding of the multi-level influences on children's physical activity and sedentary behaviour. One route to achieving this is through the pooling and co-analysis of data from multiple studies. Where this approach is used, transparency of the methodology for data collation and harmonisation is essential to enable appropriate analysis and interpretation of the derived data. In this paper, we describe the acquisition, management and harmonisation of non-accelerometer data in a project to expand the International Children's Accelerometry Database (ICAD)., Method: Following a consultation process, ICAD partners were requested to share accelerometer data and information on selected behavioural, social, environmental and health-related constructs. All data were collated into a single repository for cataloguing and harmonisation. Harmonised variables were derived iteratively, with input from the ICAD investigators and a panel of invited experts. Extensive documentation, describing the source data and harmonisation procedure, was prepared and made available through the ICAD website., Results: Work to expand ICAD has increased the number of studies with longitudinal accelerometer data, and expanded the breadth of behavioural, social and environmental characteristics that can be used as exposure variables. A set of core harmonised variables, including parent education, ethnicity, school travel mode/duration and car ownership, were derived for use by the research community. Guidance documents and facilities to enable the creation of new harmonised variables were also devised and made available to ICAD users. An expanded ICAD database was made available in May 2017., Conclusion: The project to expand ICAD further demonstrates the feasibility of pooling data on physical activity, sedentary behaviour and potential determinants from multiple studies. Key to this process is the rigorous conduct and reporting of retrospective data harmonisation, which is essential to the appropriate analysis and interpretation of derived data. These documents, made available through the ICAD website, may also serve as a guide to others undertaking similar projects.

Background: The minimum intensity of physical activity (PA) that is associated with favourable body composition and cardiorespiratory fitness (CRF) remains unknown., Objective: To investigate cross-sectional associations of PA and sedentary time (ST) with body composition and CRF in mid-childhood., Methods: PA, ST, body composition and CRF were measured in a population-based sample of 410 children (aged 7.6 ± 0.4 years). Combined heart-rate and movement sensing provided estimates of PA energy expenditure (PAEE, kJ/kg/day) and time (min/day) at multiple fine-grained metabolic equivalent (MET) levels, which were also collapsed to ST and light PA (LPA), moderate PA (MPA) and vigorous PA (VPA). Fat mass index (FMI, kg/m 2 ), trunk fat mass index (TFMI, kg/m 2 ) and fat-free mass index (FFMI, kg/m 2.5 ) were derived from dual-energy X-ray absorptiometry. Maximal workload from a cycle ergometer test provided a measure of CRF (W/kg FFM). Linear regression and isotemporal substitution models were used to investigate associations., Results: The cumulative time above 2 METs (221 J/min/kg) was inversely associated with FMI and TFMI in both sexes (p < 0.001) whereas time spent above 3 METs was positively associated with CRF (p ≤ 0.002); CRF increased and adiposity decreased dose-dependently with increasing MET levels. ST was positively associated with FMI and TFMI (p < 0.001) but there were inverse associations between all PA categories (including LPA) and adiposity (p ≤ 0.002); the magnitude of these associations depended on the activity being displaced in isotemporal substitution models but were consistently stronger for VPA. PAEE, MPA and to a greater extent VPA, were all positively related to CRF (p ≤ 0.001)., Conclusions: PA exceeding 2 METs is associated with lower adiposity in mid-childhood, whereas PA of 3 METs is required to benefit CRF. VPA was most beneficial for fitness and fatness, from a time-for-time perspective, but displacing any lower-for-higher intensity may be an important first-order public health strategy. Clinical trial registry number (website): NCT01803776 ( https://clinicaltrials.gov/ct2/show/NCT01803776 ).

The transition from primary/middle school to secondary/high school is likely to be a key period in children's development, characterised by significant changes in their social and physical environment. However, little is known about the changes in sedentary behaviour that accompany this transition. This review aimed to identify, critically appraise and summarise the evidence on changes in sedentary behaviour across the primary - secondary school transition. Published English language studies were located from computerised and manual searches in 2015. Inclusion criteria specified a longitudinal design, baseline assessment when children were in primary/middle school with at least one follow-up during secondary/high school and a measure of sedentary behaviour at both (or all) points of assessment. Based on data from 11 articles (19 independent samples), tracking coefficients were typically in the range of 0.3 to 0.5 and relatively consistent across the different sedentary behaviours examined and durations of follow-up. Both screen-based sedentary behaviour and overall sedentary time increased during the school transition. Overall there was an increase of approximately 10-20min per day per year in accelerometer-assessed sedentary time. Consistent with the broader age-related changes in behaviour observed during this period, sedentary behaviour increases during the transition from primary/middle to secondary/high school. Investigating features of the social and physical environment that might exacerbate or attenuate this trend would be a valuable next step., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Sedentary behaviours (SB) are highly prevalent in young people and may be adversely associated with physical and mental health. Understanding of the modifiable determinants of SB is necessary to inform the design of behaviour change interventions but much of the existing research is cross-sectional and focussed upon screen-based behaviours., Purpose: To examine the social, psychological and environmental determinants of change in children's objectively measured sedentary time from age 11 to 14 years., Methods: Data are from the second (2008) and third (2011) waves of assessment in the Sport, Physical Activity, and Eating Behaviour: Environmental Determinants in Young People (SPEEDY) study, conducted in the county of Norfolk, United Kingdom. Longitudinal data on accelerometer assessed sedentary time were available for 316 (53.5% female, 11.2±0.3 years at baseline) and 264 children after-school and at the weekend respectively. Information on 14 candidate determinants, including school travel mode and electronic media ownership, was self-reported. Change in the proportion of registered time spent sedentary was used as the outcome variable in cross-classified linear regression models, adjusted for age, sex, body mass index and baseline sedentary time. Simple and multiple models were run and interactions with sex explored., Results: Daily sedentary time increased by 30-40 minutes after-school and at the weekend from baseline to follow-up. Participants who travelled to school by cycle exhibited smaller increases in after-school sedentary time (beta; 95%CI for change in % time spent sedentary: -3.3;-6.7,-0.07). No significant determinants of change in weekend sedentary time were identified., Conclusions: Time spent sedentary increased during the three-year duration of follow-up but few of the variables examined were significantly associated with changes in sedentary time. Children's mode of school travel may influence changes in their sedentary time over this period and should be examined further, alongside broader efforts to identify modifiable determinants of SB during childhood., Competing Interests: The authors have declared that no competing interests exist.

Background: There is increasing policy interest in ensuring that the school environment supports healthy behaviours. We examined the cross-sectional and longitudinal associations between schools' policies, programmes and facilities for physical activity (PA) and adolescents' objectively-measured activity intensity during the school day and lunchtime., Methods: Accelerometer-derived PA (proportion of time spent in sedentary (SED), light PA (LPA) and moderate-to-vigorous PA (MVPA)) during school hours and lunchtime from 325 participants in the SPEEDY study were obtained from baseline measurements (primary school, age 9/10 years) and +4y follow-up (secondary school). School environment characteristics were assessed by teacher questionnaire. Multivariable multi-level linear regression analyses accounting for school and adjusted for sex, age, BMI and family socio-economic status assessed cross-sectional associations with lunchtime and school-day SED, LPA and MVPA; effect modification by sex was investigated. The association of changes in school environment with changes in outcomes was examined using multivariable cross-classified linear regression models., Results: There were significant differences between primary and secondary schools for 6/10 school environment characteristics investigated (including secondary schools reporting shorter breaks, more lunchtime PA opportunities, and higher number of sports facilities). Cross-sectional analyses showed that boys attending secondary schools with longer breaks spent significantly less time in SED and more time in MVPA during the school day. Longitudinally, an increase in break-time duration between primary and secondary school was associated with smaller reductions in MVPA during the school day. Moreover, participants who moved from a primary school that did not provide opportunities for PA at lunchtime to a secondary school that did provide such opportunities exhibited smaller increases in SED and smaller reductions in MVPA at lunchtime., Conclusions: Schools should consider the potential negative impact of reducing break time duration on students' MVPA and SED during the school day. School-based interventions that combine longer breaks and more PA opportunities during lunchtime may be a fruitful direction for future research. Further research should also explore other factors in the school environment to explain the school-level clustering observed, and study sex differences in the way that the school environment influences activity intensity for adolescent populations.

Purpose: Understanding seasonal variation in physical activity is important for informing public health surveillance and intervention design. The aim of the current study was to describe seasonal variation in children's objectively measured physical activity and sedentary time., Methods: Data are from the UK Millennium Cohort Study. Participants were invited to wear an accelerometer for 7 d on five occasions between November 2008 and January 2010. Outcome variables were sedentary time (<100 counts per minute, min·d(-1)) and moderate to vigorous physical activity (MVPA) (>2241 counts per minute, min·d(-1)). The season was characterized using a categorical variable (spring, summer, autumn, or winter) and a continuous function of day of the year. Cross-classified linear regression models were used to estimate the association of each of these constructs with the outcome variables. Modification of the seasonal variation by sex, weight status, urban/rural location, parental income, and day of the week (weekday/weekend) was examined using interaction terms in regression models., Results: At least one wave of valid accelerometer data was obtained from 704 participants (47% male; baseline age, 7.6 (0.3) yr). MVPA was lower in autumn and winter relative to spring, with the magnitude of this difference varying by weekday/weekend, sex, weight status, urban/rural location, and family income (P for interaction <0.05 in all cases). Total sedentary time was greater in autumn and winter compared with spring; the seasonal effect was stronger during the weekend than during the weekday (P for interaction <0.01)., Conclusions: Lower levels of MVPA and elevated sedentary time support the implementation of intervention programs during autumn and winter. Evidence of greater seasonal variation in weekend behavior and among certain sociodemographic subgroups highlights targets for tailored intervention programs.

There is increasing academic and policy interest in interventions aiming to promote young people's health by ensuring that the school environment supports healthy behaviours. The purpose of this review was to summarize the current evidence on school-based policy, physical and social-environmental influences on adolescent physical activity and sedentary behaviour. Electronic databases were searched to identify studies that (1) involved healthy adolescents (11-18 years old), (2) investigated school-environmental influences and (3) reported a physical activity and/or sedentary behaviour outcome or theme. Findings were synthesized using a non-quantitative synthesis and thematic analysis. Ninety-three papers of mixed methodological quality were included. A range of school-based policy (e.g. break time length), physical (e.g. facilities) and social-environmental (e.g. teacher behaviours) factors were associated with adolescent physical activity, with limited research on sedentary behaviour. The mixed-studies synthesis revealed the importance of specific activity settings (type and location) and intramural sport opportunities for all students. Important physical education-related factors were a mastery-oriented motivational climate and autonomy supportive teaching behaviours. Qualitative evidence highlighted the influence of the wider school climate and shed light on complexities of the associations observed in the quantitative literature. This review identifies future research needs and discusses potential intervention approaches to be considered., (© 2015 World Obesity.)

Background: We investigated prospective associations between physical activity/sedentary behaviour (PA/SED) and General Certificate of Secondary Education (GCSE) results in British adolescents., Methods: Exposures were objective PA/SED and self-reported sedentary behaviours (screen (TV, Internet, Computer Games)/non-screen (homework, reading)) measured in 845 adolescents (14·5y ± 0·5y; 43·6 % male). GCSE results at 16y were obtained from national records. Associations between exposures and academic performance (total exam points) were assessed using multilevel mixed-effects linear regression adjusted for mood, BMI z-score, deprivation, sex, season and school; potential interactions were investigated., Results: PA was not associated with academic performance. One-hour more accelerometer-assessed SED was associated with (β(95 % CI)) 6·9(1·5,12·4) more GCSE points. An extra hour of screen time was associated with 9.3(-14·3,-4·3) fewer points whereas an extra hour of non-screen time (reading/homework) was associated with 23·1(14·6,31·6) more points. Screen time was still associated with poorer scores after adjusting for objective PA/SED and reading/homework., Conclusions: An extra hour/day of screen time at 14·5y is approximately equivalent to two fewer GCSE grades (e.g., from B to D) at 16y. Strategies to achieve the right balance between screen and non-screen time may be important for improving academic performance. Concerns that encouraging more physical activity may result in decreased academic performance seem unfounded.

Objective: The objective of this study was to investigate whether objectively measured sedentary time and sleep duration are associated with changes in adiposity from mid- to late adolescence., Methods: Students (n = 504, 42% boys) were recruited from schools in Cambridgeshire, UK. At baseline (mean age 15.0 ± 0.3 years), sedentary time was objectively measured by ≥3 days of combined heart rate and movement sensing. Concurrently, sleep duration was measured by combined sensing in conjunction with self-reported bed times. Fat mass index (FMI; kg/m(2)) was estimated at baseline and follow-up (17.5 ± 0.3 years) by anthropometry and bioelectrical impedance. FMI change (ΔFMI) was calculated by subtracting the baseline from follow-up values. Linear regression models adjusted for basic demographics, moderate-to-vigorous physical activity (MVPA), and depressive symptoms were used to investigate associations of sedentary time and sleep duration (mutually adjusted for one another) with ΔFMI., Results: FMI increased by 0.5 and 0.6 kg/m(2) in boys and girls, respectively, but there was no association between sedentary time and ΔFMI in either gender (p ≥ 0.087), and no association between sleep duration and ΔFMI in girls (p ≥ 0.61). In boys, each additional hour of baseline sleep significantly reduced the ΔFMI by 0.13 kg/m(2) (p = 0.049), but there was little evidence for this association after adjusting for MVPA and depressive symptoms (p = 0.15)., Conclusions: Sedentary time may not determine changes in adiposity from mid- to late adolescence, nor may sleep duration in girls. However, sleep length may be inversely associated with adiposity gain in boys, depending on whether the relationship is confounded or mediated by MVPA and depression., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: This study examined the association of adolescent-reported family functioning and friendship quality with objectively-measured moderate to vigorous physical activity (MVPA), sedentary time, and self-reported sedentary behaviours., Methods: Data are from the ROOTS study. MVPA and sedentary time were assessed using combined movement and heart rate sensing. Time spent TV viewing, using the internet, playing video games, doing homework and reading for pleasure was self-reported. Data on objectively-measured and self-reported outcomes for weekdays was available for 738 (age 14.5y, 55.7% female) and 800 (56.3% female) participants, respectively. Adolescents perceived family functioning and friendship quality (Two subscales: 'Good friendship qualities', 'Friendship difficulties') was assessed by questionnaire. Analyses were conducted using multi-level linear or logistic regression., Results: Adolescents reporting better family functioning accumulated more MVPA on weekdays (beta; 95% confidence interval: 0.57; 0.17,0.98). Higher scores on the good friendship qualities subscale was associated with greater MVPA throughout the week (weekdays: 1.13; 0.62,1.65, weekend: 0.56; 0.09,1.02) and lower sedentary time on weekdays (-10.34; -17.03,-3.66). Boys from better functioning families were less likely to report playing video games at the weekend (OR; 95% confidence interval: 0.73; 0.57,0.93) or reading for pleasure (weekday: 0.73; 0.56,0.96 weekend: 0.75; 0.58,0.96). Boys who attained higher scores on the good friendship qualities scale were less likely to play video games at the weekend (0.61; 0.44,0.86) or report high homework on weekdays (0.54; 0.31,0.94). A higher score for good friendship qualities was associated with lower odds of girls playing video games during the week (0.76; 0.58,1.00) or reading for pleasure at the weekend (0.61; 0.42,0.88). Girls that reported fewer friendship difficulties had lower odds of high TV viewing (0.76; 0.62,0.93) or playing video games (0.71; 0.52,0.97) at the weekend, and lower odds of reading for pleasure (0.63; 0.49,0.81) or reporting high homework on weekdays (0.70; 0.52,0.95)., Discussion: Family functioning and friendship quality exhibit a complex pattern of association with physical activity and sedentary behaviour that varies by sex and day of the week. Findings highlight the potential value of targeting interpersonal aspects of the family and friendships as an adjunct to behaviour change interventions.

Physical activity and sedentary behaviour are associated with metabolic and mental health during childhood and adolescence. Understanding the inter-relationships between these behaviours will help to inform intervention design. This systematic review and meta-analysis synthesized evidence from observational studies describing the association between sedentary behaviour and physical activity in young people (<18 years). English-language publications up to August 2013 were located through electronic and manual searches. Included studies presented statistical associations between at least one measure of sedentary behaviour and one measure of physical activity. One hundred sixty-three papers were included in the meta-analysis, from which data on 254 independent samples was extracted. In the summary meta-analytic model (k = 230), a small, but significant, negative association between sedentary behaviour and physical activity was observed (r = -0.108, 95% confidence interval [CI] = -0.128, -0.087). In moderator analyses, studies that recruited smaller samples (n < 100, r = -0.193, 95% CI = -0.276, -0.109) employed objective methods of measurement (objectively measured physical activity; r = -0.233, 95% CI = -0.330, -0.137) or were assessed to be of higher methodological quality (r = -0.176, 95% CI = -0.215, -0.138) reported stronger associations, although effect sizes remained small. The association between sedentary behaviour and physical activity in young people is negative, but small, suggesting that these behaviours do not directly displace one another., (© 2014 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of International Association for the Study of Obesity.)

Background: Having electronic media in the bedroom is cross-sectionally associated with greater screen-time in children, but few longitudinal studies exist. The aim of this study was to describe longitudinal patterns of ownership and examine cross-sectional and longitudinal associations of bedroom media with children's sedentary behaviour., Methods: Data are from the Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people (SPEEDY) study, collected at 3 time-points: baseline (2007, T0; age 10.3 ± 0.3 years), 1-year (T1y) and 4-year (T4y) follow-up. For each assessment, 1512 (44.9% male), 715 (41.0% male), and 319 (48.3% male) participants provided valid accelerometer data. Outcome variables were accelerometer-assessed sedentary time and self-reported screen-time. The presence of a television or computer in the bedroom was self-reported by participants and a combined bedroom media score calculated as the sum of such items. Cross-sectional and longitudinal associations between bedroom media and each outcome were examined using multi-level linear regression., Results: Bedroom TV ownership fell from 70.9% at T0 to 42.5% at T4y. Having a TV in the bedroom (beta; 95% CI*100, T0: -1.17; -1.88, -0.46. T1y: -1.68; -2.67, -0.70) and combined bedroom media (T0: -0.76; -1.26, -0.27. T1y: -0.79; -1.51, -0.07) were negatively associated with objectively measured weekly sedentary time at T0 and T1y. Having a computer in the bedroom (beta; 95% CI, T0: 0.15; 0.02, 0.29. T4y: 0.35; 0.10, 0.60) and combined bedroom media (T0: 0.09: 0.01, 0.18. T4y: 0.20; 0.05, 0.34) were positively associated with screen-time at T0 and T4y. Relative to participants without a computer throughout the study, children that had a computer in their bedroom at T0 but not at T4y (beta; 95% CI for change in screen-time: -8.02; -12.75, -3.29) reported smaller increases in screen-time., Conclusions: The bedroom media environment changes with age and exhibits a complex relationship with children's sedentary behaviour. Modifying children's bedroom media environment may impact upon screen-time but appears unlikely to influence overall sedentary time.

Background: Little is known regarding the patterning and socio-demographic distribution of multiple sedentary behaviours in children. The aims of this study were to: 1) describe the leisure-time sedentary behaviour of 9-10 year old British children, and 2) establish associations with objectively-measured sedentary time., Methods: Cross-sectional analysis in the SPEEDY study (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people) (N=1513, 44.3% boys). Twelve leisure-time sedentary behaviours were assessed by questionnaire. Objectively-measured leisure-time sedentary time (Actigraph GT1M, <100 counts/minute) was assessed over 7 days. Differences by sex and socioeconomic status (SES) in self-reported sedentary behaviours were tested using Kruskal-Wallis tests. The association between objectively-measured sedentary time and the separate sedentary behaviours (continuous (minutes) and categorised into 'none' 'low' or 'high' participation) was assessed using multi-level linear regression., Results: Sex differences were observed for time spent in most sedentary behaviours (all p ≤ 0.02), except computer use. Girls spent more time in combined non-screen sedentary behaviour (median, interquartile range: girls: 770.0 minutes, 390.0-1230.0; boys: 725.0, 365.0 - 1182.5; p = 0.003), whereas boys spent more time in screen-based behaviours (girls: 540.0, 273.0 - 1050.0; boys: 885.0, 502.5 - 1665.0; p < 0.001). Time spent in five non-screen behaviours differed by SES, with higher values in those of higher SES (all p ≤ 0.001). Regression analyses with continuous exposures indicated that reading (β = 0.1, p < 0.001) and watching television (β = 0.04, p < 0.01) were positively associated with objectively-measured sedentary time, whilst playing board games (β = -0.12, p < 0.05) was negatively associated. Analysed in categorical form, sitting and talking (vs. none: 'low' β = 26.1,ns; 'high' 30.9, p < 0.05), playing video games (vs. none: 'low' β = 49.1, p < 0.01; 'high' 60.2, p < 0.01) and watching television (vs. lowest tertile: middle β = 22.2,ns; highest β = 31.9, p < 0.05) were positively associated with objectively-measured sedentary time whereas talking on the phone (vs. none: 'low' β = -38.5, p < 0.01; 'high' -60.2, p < 0.01) and using a computer/internet (vs. none: 'low' β = -30.7, p < 0.05; 'high' -4.2,ns) were negatively associated., Conclusions: Boys and girls and children of different socioeconomic backgrounds engage in different leisure-time sedentary behaviours. Whilst a number of behaviours may be predictive of total sedentary time, collectively they explain little overall variance. Future studies should consider a wide range of sedentary behaviours and incorporate objective measures to quantify sedentary time where possible.

Background: Understanding the determinants of sedentary time during childhood contributes to the development of effective intervention programmes., Purpose: To examine family and home-environmental determinants of 1-year change in objectively measured sedentary time after-school and at the weekend., Methods: Participants wore accelerometers at baseline and 1 year later. Longitudinal data for after-school and weekend analyses were available for 854 (41.5%male, mean ± SD age 10.2 ± 0.3 years) and 718 (41.8%male, age 10.2 ± 0.3 years) participants. Information on 26 candidate determinants, including socioeconomic status (SES), availability of electronic media and parental rules for sedentary behaviours was self-reported by children or their parents at baseline. Change in the proportion of registered time spent sedentary was used as the outcome variable in multi-level linear regression models, adjusted for age, sex, body mass index and baseline sedentary time. Simple and multiple models were run and interactions with sex explored., Results: Children from higher socioeconomic status families exhibited greater increases in after-school (beta; 95% CI for change in % time spent sedentary 1.02; 0.37, 1.66) and weekend (1.42; 0.65, 2.18) sedentary time. Smaller increases in after-school sedentary time were observed in children with more siblings (-1.00; -1.69, -0.30), greater availability of electronic media (-0.81; -1.29, -0.33) and, for boys, more frequent family visits to the park (-1.89; -3.28, -0.51) and family participation in sport (-1.28; -2.54, -0.02). Greater maternal weekend screen-time (0.45; 0.08, 0.83) and, in girls, greater parental restriction on playing outside (0.91; 0.08, 1.74) were associated with larger increases in weekend sedentary time. The analytical sample was younger, more likely to be female, had lower BMI and was of higher SES than the original baseline sample., Conclusions: Intervention strategies aimed at reducing parents' weekend screen-time, increasing family participation in sports or recreation (boys) and promoting freedom to play outside (girls) may contribute towards preventing the age-related increase in sedentary time.

Purpose: Accelerometry is increasingly being used to assess sedentary time in epidemiological studies, yet the most appropriate means of processing these data remains uncertain. This cross-sectional study examined the influence of selected accelerometer cut points and nonwear criteria on associations of sedentary time with adiposity and clustered metabolic risk., Methods: Data were from the European Youth Heart Study, which included assessment of sedentary time by accelerometer. Sixteen sedentary time variables were constructed based on combinations of frequently used cut points (100, 500, 800, and 1100 counts per minute) and nonwear criteria (10-, 20-, 60-, and 100-min consecutive zeros). Adiposity was assessed by sum of four skinfold thickness measures. A clustered metabolic risk score was calculated as the mean of standardized metabolic syndrome components, including blood pressure, insulin resistance, and inverted fasting HDL-cholesterol. Analyses were conducted using multilevel cross-sectional time series regression, adjusted for overall physical activity (accelerometer counts per minute). Meta-analysis was used to obtain pooled estimates of the exposure-outcome association over all processing protocols; meta-regression was used to determine the influence of nonwear and cut point protocol on observed associations., Results: Sedentary time follows a power law with cut point (exponent = 0.27) and zero string (exponent = 0.03), and it was positively associated with clustered metabolic risk (β = 0.0051; 95% confidence interval = 0.0018-0.0085). The association was moderated by cut point, with higher cut points typically producing stronger associations. No significant association between sedentary time and adiposity was observed., Conclusions: The choice of accelerometer cut point may moderate the association between sedentary time and clustered metabolic risk, suggesting that direct comparisons of associations between studies using different cut points must be made with caution.

Background: Research examining sedentary behaviour as a potentially independent risk factor for chronic disease morbidity and mortality has expanded rapidly in recent years., Methods: We present a narrative overview of the sedentary behaviour measurement literature. Subjective and objective methods of measuring sedentary behaviour suitable for use in population-based research with children and adults are examined. The validity and reliability of each method is considered, gaps in the literature specific to each method identified and potential future directions discussed., Results: To date, subjective approaches to sedentary behaviour measurement, e.g. questionnaires, have focused predominantly on TV viewing or other screen-based behaviours. Typically, such measures demonstrate moderate reliability but slight to moderate validity. Accelerometry is increasingly being used for sedentary behaviour assessments; this approach overcomes some of the limitations of subjective methods, but detection of specific postures and postural changes by this method is somewhat limited. Instruments developed specifically for the assessment of body posture have demonstrated good reliability and validity in the limited research conducted to date. Miniaturization of monitoring devices, interoperability between measurement and communication technologies and advanced analytical approaches are potential avenues for future developments in this field., Conclusions: High-quality measurement is essential in all elements of sedentary behaviour epidemiology, from determining associations with health outcomes to the development and evaluation of behaviour change interventions. Sedentary behaviour measurement remains relatively under-developed, although new instruments, both objective and subjective, show considerable promise and warrant further testing.

Background: Emerging evidence suggests that sedentary behaviour may be adversely associated with physical health, but few studies have examined the association with mental well-being., Purpose: This study examined the association of four non-occupational sedentary behaviours, individually and in total, with mental well-being in employed adults., Methods: Baseline data from the evaluation of Well@Work, a national workplace health promotion project conducted in the UK, were used. Participants self-reported sitting time whilst watching television, using a computer, socialising and travelling by motorised transport. Mental well-being was assessed by the 12-item version of the general health questionnaire. Analyses were conducted using multiple linear regression., Results: In models adjusted for multiple confounders, TV viewing, computer use and total non-occupational sitting time were adversely associated with general health questionnaire-12 assessed mental well-being in women. Computer use only was found to be adversely associated with mental well-being in men., Conclusion: Sedentary behaviour may be adversely associated with mental well-being in employed adults. The association may be moderated by gender.