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Physical activity (PA) promotes better cardiometabolic health, physical function, brain health and longevity. In contrast, prolonged sedentary behaviour (SB) is a risk factor for many chronic diseases and poor health. Limited research has evaluated or synthesised how competitive sports participation influences PA across the lifespan. Some evidence suggests, ironically, that former competitive athletes may be insufficiently active and current athletes may be highly sedentary away from sport. This study describes the protocol for a systematic review and meta-analysis on activity levels across the intensity spectrum in athletes, addressing the primary research question: is sports participation significantly associated with PA and/or SB among current and former competitive athletes? PubMed, Embase, Cochrane Database of Systematic Reviews, Web of Science and SPORTDiscus databases will be searched. Two reviewers will independently screen titles/abstracts and full texts of selected abstracts. Data will be extracted regarding the study population, sport played, PA measures and protocols, outcomes of interest and findings. Primary outcomes will include step counts, daily activity across the intensity spectrum (ie, sedentary, light, moderate and vigorous PA), metabolic equivalent of task and whole-day energy expenditure. Secondary outcomes will include additional accelerometry measures of PA, activity patterns and self-reported PA. The risk of bias will be assessed using the National Institutes of Health Study Quality Assessment Tools. Extracted data will be presented using narrative synthesis and tabular presentation. Meta-analyses will be conducted to determine outcomes with sufficient data.PROSPERO registration number: CRD42024469267.

Introduction Efficacious programmes require implementation at scale to maximise their public health impact. TransformUs is an efficacious behavioural and environmental intervention for increasing primary (elementary) school children’s (5–12 years) physical activity and reducing their sedentary behaviour within school and home settings. This paper describes the study protocol of a 5-year effectiveness–implementation trial to assess the scalability and effectiveness of the TransformUs programme.Methods and analysis A type II hybrid implementation–effectiveness trial, TransformUs is being disseminated to all primary schools in the state of Victoria, Australia (n=1786). Data are being collected using mixed methods at the system (state government, partner organisations), organisation (school) and individual (teacher, parent and child) levels. Evaluation is based on programme Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework. RE-AIM domains are being measured using a quasi-experimental, pre/post, non-equivalent group design, at baseline, 12 and 24 months. Effectiveness will be determined in a subsample of 20 intervention schools (in Victoria) and 20 control schools (in New South Wales (NSW), Australia), at baseline, 12 and 24 months. Primary outcomes include TransformUs Reach, Adoption, Implementation and organisational Maintenance (implementation trial), and children’s physical activity and sedentary time assessed using accelerometers (effectiveness trial). Secondary outcomes include average sedentary time and moderate to vigorous-intensity physical activity on weekdays and during school hours, body mass index z-scores and waist circumference (effectiveness trial). Linear mixed-effects models will be fitted to compare outcomes between intervention and control participants accounting for clustering of children within schools, confounding and random effects.Ethics and dissemination The trial was approved by the Deakin University Human Research Ethics Committee (HEAG-H 28_2017), Victorian Department of Education, the NSW Department of Education, Australian Catholic University (2017-145R), Melbourne Archdiocese Catholic Schools and Catholic Schools NSW. Partners, schools/teachers and parents will provide an informed signed consent form prior to participating. Parents will provide consent for their child to participate in the effectiveness trial. Findings will be disseminated via peer-reviewed publications, scientific conferences, summary reports to schools and our partner organisations, and will inform education policy and practice on effective and sustainable ways to promote physical activity and reduce sedentary behaviours population-wide.Trial registration number Australian Clinical Trials Registration Registry (ACTRN12617000204347).

BackgroundAdolescence is a critical age where steep declines in physical activity and increases in sedentary time occur. Promoting physical activity should therefore be a priority for short- and long-term health benefits. Wearable activity trackers in combination with supportive resources have the potential to influence adolescents’ physical activity levels and sedentary behavior. Examining the pathways through which such interventions work can inform which mediators to target in future studies. ObjectiveThe aim of this paper is to examine the impact of the Raising Awareness of Physical Activity (RAW-PA) intervention on potential mediators of behavior change after intervention, and whether these mediated the intervention effects on physical activity and sedentary time at 6-month follow-up. MethodsRAW-PA was a 12-week intervention, grounded in social cognitive theory and behavioral choice theory, aimed at increasing physical activity among inactive adolescents through combining a wearable activity tracker with digital resources delivered via a private Facebook group (n=159 complete cases). The targeted potential mediators were identified from previous studies conducted in adolescents and included self-efficacy, peer support, family support, teacher support, self-regulation strategies, barriers, and enjoyment. Outcomes included sedentary time as well as light- and moderate-to-vigorous–intensity physical activity. A series of mixed linear models were used to estimate intervention effects on physical activity and sedentary behavior at follow-up and on potential mediators after intervention and to test whether there were indirect effects of the intervention on physical activity and sedentary behavior via mediators. ResultsAdolescents in the intervention group (n=75) engaged in higher sedentary time and lower light intensity at 6-month follow-up compared to the wait-list controls (n=84). There were no intervention effects for moderate-to-vigorous–intensity physical activity. The intervention group perceived more barriers to physical activity than the wait-list control group at 6-month follow-up (mean adjusted difference=1.77; 95% CI 0.19-3.34; P=.03). However, indirect effects for each outcome were not statistically significant, indicating that perceived barriers to physical activity did not mediate intervention effects for physical activity or sedentary time. ConclusionsRAW-PA did not beneficially impact hypothesized mediators in these inactive adolescents, despite strategies being designed to target them. This suggests that the lack of overall intervention effects on physical activity and sedentary time observed in the RAW-PA study could be due to the limited impact of the intervention on the targeted mediators. Future studies should consider different strategies to target theoretically informed potential mediators and identify intervention strategies that effectively target key mediators to improve physical activity among inactive adolescents. Finally, intervention effects according to level of wearable tracker use or level of engagement with the intervention should be explored. This may provide important insights for designing successful wearable activity tracker interventions. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12616000899448; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370716&isReview=true International Registered Report Identifier (IRRID)RR2-10.1186/s12889-016-3945-5

Abstract Background Children and adolescents spend a lot of time sitting at school. Implementing standing desks in the classroom is one potential strategy to reduce and break up sitting time. The first aim was to evaluate the effect of implementing standing desks in classrooms in primary and secondary schools on pupils’ sitting-related behaviour and determinants. The second aim was to quantitatively and qualitatively evaluate the process of implementing the desks in the classroom. Methods We conducted a cluster-randomised controlled trial with a pre-, mid-, and post-test design including 10 intervention schools (5 primary, 5 secondary schools) and 9 control schools (5 primary, 4 secondary schools) across Flanders, Belgium. Three standing desks were placed in one class in each intervention school for 6 months. At pre-, mid- and post-test, all pupils (n = 311; 54.5% girls) completed a questionnaire whilst a subsample of three pupils per class wore an activPAL inclinometer for one school week. Focus groups with pupils and interviews with teachers were conducted at mid-test. Process evaluation questions were added to the mid- and post-test questionnaire for the intervention group. Qualitative data were analysed using NVivo 11. Multilevel regression analyses were conducted in MLwiN 2.31. Results Few significant intervention effects were observed, although activPAL data showed favourable intervention effects on primary school pupils’ sitting and standing time and bouts. Focus groups and interviews showed a generally positive attitude towards using standing desks in both teachers and pupils, although some barriers and suggestions for future implementation were noted, for example regarding the amount of desks per classroom. Quantitative process evaluation data showed a low individual use of standing desks (between 57 and 83 min per week), which significantly decreased across the school year for primary school pupils only. Conclusions Although pupils and teachers were generally positive about the desks, relatively few intervention effects were found. Future studies should consider how to optimise the use of standing desks in classrooms to impact on sitting time, by for example, determining the most feasible intervention design and by encouraging the continued use of standing desks throughout the school year. Moreover, additional intervention strategies (e.g. educational strategies) might be needed. Trial registration NCT03163004. ClinicalTrials.gov. Registered 22 May 2017 (retrospectively registered).

INTRODUCTION:Total volumes of physical activity and sedentary behaviour have been associated with cardio-metabolic risk profiles; however, little research has examined whether patterns of activity (e.g., prolonged bouts, frequency of breaks in sitting) impact cardio-metabolic risk. The aim of this review was to synthesise the evidence concerning associations between activity patterns and cardio-metabolic risk factors in children and adolescents aged 5-19 years. MATERIALS AND METHODS:A systematic search of seven databases was completed in October 2017. Included studies were required to report associations between objectively-measured activity patterns and cardio-metabolic risk factors in children and/or adolescents, and be published between 1980 and 2017. At least two researchers independently screened each study, extracted data, and undertook risk of bias assessments. RESULTS:From the 15,947 articles identified, 29 were included in this review. Twenty-four studies were observational (cross-sectional and/or longitudinal); five were experimental. Ten studies examined physical activity patterns, whilst 19 studies examined sedentary patterns. Only one study examined both physical activity and sedentary time patterns. Considerable variation in definitions of activity patterns made it impossible to identify which activity patterns were most beneficial to children's and adolescents' cardio-metabolic health. However, potential insights and current research gaps were identified. DISCUSSION AND CONCLUSION:A consensus on how to define activity patterns is needed in order to determine which activity patterns are associated with children's and adolescents' cardio-metabolic risk. This will inform future research on the impact of activity patterns on children's and adolescents' short- and longer-term health.

Adolescents spend large amounts of time sitting at school. Little is known about the impact of reducing and breaking-up prolonged sitting during school lessons on adolescents' health. This study aimed to investigate the impact of an intervention to reduce classroom sitting time on adolescents' energy expenditure (EE; kcal/lesson), body mass index (BMI), waist circumference (WC), and musculoskeletal discomfort. A secondary school classroom was equipped with height-adjustable desks, posters promoting the health benefits of and strategies for breaking-up sitting time, and desk stickers reminding students to periodically stand up. Classroom teachers participated in a professional development session. Using a quasi-experimental design, differences between 49 participants who utilised the intervention classroom 2-5 times/week and a comparison group (39 adolescents, matched by year level and subject) who used traditional classrooms, were examined. EE, BMI and WC were objectively measured and musculoskeletal discomfort was self-reported at baseline, 4-weeks, and 17-weeks. Hierarchical linear and multilevel logistic regression-mixed models were used to examine intervention effects, adjusting for baseline values, sex and age. EE was significantly higher at 4-weeks and 17-weeks (29.4 and 37.7 kcal/lesson, respectively), BMI was higher at 4-weeks (0.34 kg/m2), and WC was lower at 4-weeks and 17-weeks (-3.53 and -2.64 cm, respectively) in the intervention compared to the comparison group. No intervention effect was found for musculoskeletal discomfort. Findings provide preliminary indications that these strategies may benefit health among adolescents in the short term. However, extended longer-duration trials are needed to determine longer-term health effects.

More knowledge is warranted about multilevel ecological variables associated with context-specific sitting time among adolescents. The present study explored cross-sectional and longitudinal associations of ecological domains of sedentary behaviour, including socio-demographic, social-cognitive, health-related and physical-environmental variables with sitting during TV viewing, computer use, electronic gaming and motorized transport among adolescents.For this longitudinal study, a sample of Belgian adolescents completed questionnaires at school on context-specific sitting time and associated ecological variables. At baseline, complete data were gathered from 513 adolescents (15.0±1.7 years). At one-year follow-up, complete data of 340 participants were available (retention rate: 66.3%). Multilevel linear regression analyses were conducted to explore cross-sectional correlates (baseline variables) and longitudinal predictors (change scores variables) of context-specific sitting time.Social-cognitive correlates/predictors were most frequently associated with context-specific sitting time. Longitudinal analyses revealed that increases over time in considering it pleasant to watch TV (p < .001), in perceiving TV watching as a way to relax (p < .05), in TV time of parents/care givers (p < .01) and in TV time of siblings (p < .001) were associated with more sitting during TV viewing at follow-up. Increases over time in considering it pleasant to use a computer in leisure time (p < .01) and in the computer time of siblings (p < .001) were associated with more sitting during computer use at follow-up. None of the changes in potential predictors were significantly related to changes in sitting during motorized transport or during electronic gaming.Future intervention studies aiming to decrease TV viewing and computer use should acknowledge the importance of the behaviour of siblings and the pleasure adolescents experience during these screen-related behaviours. In addition, more time parents or care givers spent sitting may lead to more sitting during TV viewing of the adolescents, so that a family-based approach may be preferable for interventions. Experimental study designs are warranted to confirm the present findings.

PurposeAdolescents' physical activity levels during school break time are low and understanding correlates of physical activity and sedentary time in this context is important. This study investigated cross-sectional and longitudinal associations between a range of individual, behavioural, social and policy/organisational correlates and objectively measured school break time physical activity and sedentary time.MethodsIn 2006, 146 adolescents (50% males; mean age = 14.1±0.6 years) completed a questionnaire and wore an accelerometer for ≥3 school days. Time spent engaged in sedentary, light (LPA) and moderate-to-vigorous physical activity (MVPA) during school break times (recess and lunchtime) were calculated using existing cut-points. Measures were repeated in 2008 among 111 adolescents. Multilevel models examined cross-sectional and longitudinal associations.ResultsBringing in equipment was cross-sectionally associated with 3.2% more MVPA during break times. Females engaged in 5.1% more sedentary time than males, whilst older adolescents engaged in less MVPA than younger adolescents. Few longitudinal associations were observed. Adolescents who brought sports equipment to school engaged in 7.2% less LPA during break times two years later compared to those who did not bring equipment to school.ConclusionThese data suggest that providing equipment and reducing restrictions on bringing in sports equipment to school may promote physical activity during school recess. Strategies targeting females' and older adolescents', in particular, are warranted.

BackgroundThe minimal physical activity intensity that would confer health benefits among adolescents is unknown. The purpose of this study was to examine the associations of accelerometer-derived light-intensity (split into low and high) physical activity, and moderate- to vigorous-intensity physical activity with cardiometabolic biomarkers in a large population-based sample.MethodsThe study is based on 1,731 adolescents, aged 12-19 years from the 2003/04 and 2005/06 National Health and Nutrition Examination Survey. Low light-intensity activity (100-799 counts/min), high light-intensity activity (800 counts/min to ResultsAdjusted for confounders, each additional hour/day of low light-intensity activity was associated with 0.59 (95% CI: 1.18-0.01) mmHG lower diastolic blood pressure. Each additional hour/day of high light-intensity activity was associated with 1.67 (2.94-0.39) mmHG lower diastolic blood pressure and 0.04 (0.001-0.07) mmol/L higher HDL-cholesterol. Each additional hour/day of moderate- to vigorous-intensity activity was associated with 3.54 (5.73-1.35) mmHG lower systolic blood pressure, 5.49 (1.11-9.77)% lower waist circumference, 25.87 (6.08-49.34)% lower insulin, and 16.18 (4.92-28.53)% higher HOMA-%S.ConclusionsTime spent in low light-intensity physical activity and high light-intensity physical activity had some favorable associations with biomarkers. Consistent with current physical activity recommendations for adolescents, moderate- to vigorous-intensity activity had favorable associations with many cardiometabolic biomarkers. While increasing MVPA should still be a public health priority, further studies are needed to identify dose-response relationships for light-intensity activity thresholds to inform future recommendations and interventions for adolescents.

PurposeTo test a field-based protocol using intermittent activities representative of children's physical activity behaviours, to generate behaviourally valid, population-specific accelerometer cut-points for sedentary behaviour, moderate, and vigorous physical activity.MethodsTwenty-eight children (46% boys) aged 10-11 years wore a hip-mounted uniaxial GT1M ActiGraph and engaged in 6 activities representative of children's play. A validated direct observation protocol was used as the criterion measure of physical activity. Receiver Operating Characteristics (ROC) curve analyses were conducted with four semi-structured activities to determine the accelerometer cut-points. To examine classification differences, cut-points were cross-validated with free-play and DVD viewing activities.ResultsCut-points of ≤ 372, >2160 and >4806 counts • min(-1) representing sedentary, moderate and vigorous intensity thresholds, respectively, provided the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of the activity). Cross-validation data demonstrated that these values yielded the best overall kappa scores (0.97; 0.71; 0.62), and a high classification agreement (98.6%; 89.0%; 87.2%), respectively. Specificity values of 96-97% showed that the developed cut-points accurately detected physical activity, and sensitivity values (89-99%) indicated that minutes of activity were seldom incorrectly classified as inactivity.ConclusionThe development of an inexpensive and replicable field-based protocol to generate behaviourally valid and population-specific accelerometer cut-points may improve the classification of physical activity levels in children, which could enhance subsequent intervention and observational studies.

Abstract Background Managing children’s screen time is challenging for most families. Interventions have had limited success in reducing screen time, potentially due to a lack of understanding of the experiences, needs and recommendations of families. This study aimed to 1) understand the screen time experiences of families, particularly during COVID-19 lockdowns; and 2) explore parent and child suggestions for the design, components, and content of a screen time management program. Methods Parents and children from 30 families living in Victoria, Australia completed a semi-structured interview (63 interviews) via Zoom in October–November 2021. Parents were maged 40.8 (± 8.9) years and predominantly female (90%). Children were maged 11.4 (± 2.4) years and 47% female. The interviews were audio recorded, transcribed verbatim and analysed using inductive thematic analysis combined with a summative content analysis approach. Results Three themes under Aim 1 emerged. Theme 1) ‘Screen time management experiences and practices’, including rules and strategies, challenges, and the impact of COVID-19 lockdowns. Theme 2) ‘Impact of screens on family interaction and communication’ including conflicts within the family, reduced face-to-face interactions, and negative impact on child’s behaviour and wellbeing. Theme 3) ‘Benefits of increased screen time due to COVID-19 lockdowns’ including continuation of social interactions, extracurricular activities, improved technology skills and using screens as a ‘babysitter’. Findings from Aim 2 suggest that families want a screen time management program delivered online to parents and children, which includes static and interactive content that incorporates health information, alternative activities, cyber-safety information, tips for goal setting and rewards, screen monitoring tools, links to reputable information, and parent social connections. Reminders via text message or through the online platform would help maintain engagement in the program. Conclusions Families are experiencing challenges in managing the complex balance between the increased need for screens and the impact it has on the family. These findings provide valuable parent and child insights to assist in developing screen time management programs that are created with an understanding of the needs and challenges of families.

Abstract Background Hip-worn accelerometer cut-points have poor validity for assessing children’s sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data. Methods Participants were 278, 8–11-year-olds recruited from nine primary schools in Melbourne, Australia with differing socioeconomic status. Participants concurrently wore a thigh-worn activPAL (ground truth) and hip-worn ActiGraph (test measure) during up to 4 seasonal assessment periods, each lasting up to 8 days. activPAL data were used to train and evaluate the CHAP-child deep learning model to classify each 10-s epoch of raw ActiGraph acceleration data as sitting or non-sitting, creating comparable information from the two monitors. CHAP-child was evaluated alongside the current practice 100 counts per minute (cpm) method for hip-worn ActiGraph monitors. Performance was tested for each 10-s epoch and for participant-season level sedentary time and bout variables (e.g., mean bout duration). Results Across participant-seasons, CHAP-child correctly classified each epoch as sitting or non-sitting relative to activPAL, with mean balanced accuracy of 87.6% (SD = 5.3%). Sit-to-stand transitions were correctly classified with mean sensitivity of 76.3% (SD = 8.3). For most participant-season level variables, CHAP-child estimates were within ± 11% (mean absolute percent error [MAPE]) of activPAL, and correlations between CHAP-child and activPAL were generally very large (> 0.80). For the current practice 100 cpm method, most MAPEs were greater than ± 30% and most correlations were small or moderate (≤ 0.60) relative to activPAL. Conclusions There was strong support for the concurrent validity of the CHAP-child classification method, which allows researchers to derive activPAL-equivalent measures of sedentary time, sit-to-stand transitions, and sedentary bout patterns from hip-worn triaxial ActiGraph data. Applying CHAP-child to existing datasets may provide greater insights into the potential impacts and influences of sedentary time in children.

Abstract Background It is unknown if and how children’s movement behaviour accumulation patterns change as a result of physical activity and/or sedentary behaviour interventions. It is important to establish the effectiveness of interventions targeting changes in such accumulation patterns. This study aimed to investigate the effect of the Transform-Us! school- and home-based intervention program on children’s movement behaviour accumulation patterns, focusing on sporadic accumulation versus time in bouts. Methods Baseline and post-intervention (18 months) accelerometer data from the Transform-Us! 2 × 2 factorial design cluster randomised controlled trial was used (Melbourne, 2010–2012; analytical sample n = 267; aged 8–9 years). Linear mixed models were fitted to examine effects of three different interventions (targeting increases in physical activity [PA-I], reductions in sedentary time [SB-I], or both [PA + SB-I]) compared to a usual practice (control) group on post-intervention movement behaviour accumulation compositions with eight components, including sporadic time and bouts of sedentary time, and light-, moderate- and vigorous-intensity physical activity. Results Intervention effects on distribution of time in the post-intervention waking movement behaviour accumulation composition (adjusted for baseline composition) were small and not significant. However, visual inspection of the change in compositions over time revealed that only groups with a sedentary behaviour intervention component (SB-I and PA + SB-I) reduced time in sedentary bouts, compared to the overall sample compositional mean. In addition, the SB-I group was the only group with an increase in vigorous-intensity physical activity. The combined intervention group (PA + SB-I) was characterized by the largest proportional increase in MPA bouts. The usual practice group was characterized by the largest proportional increases in both sporadic and bouts of sedentary time. Conclusions This study showed some early evidence to suggest that the “break up your sitting” message may result in greater impact than the “move more” message. Future research, including larger sample sizes, should investigate if this type of messaging is indeed more effective in changing movement behaviours and ultimately child health. Trial registration International Standard Randomized Controlled Trial Number ISRCTN83725066 ; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279 .

Abstract Background This study examined the frequency of and differences in sedentary bouts of different durations and the total time spent in sedentary bouts on a weekday, a weekend day, during school hours, during after-school hours and in the evening period in a sample of 10- to 12-year-old Belgian children. Methods Accelerometer data were collected as part of the ENERGY-project in Belgium (n = 577, 10.9 ± 0.7 years, 53% girls) in 2011. Differences in total sedentary time, sedentary bouts of 2–5, 5–10, 10–20, 20–30 and ≥30 min and total time accumulated in those bouts were examined on a weekday, a weekend day, during school hours, during after-school hours and in the evening period, using multilevel analyses in MLwiN 2.22. Results More than 60% of the participants’ waking time was spent sedentary. Children typically engaged in short sedentary bouts of 2–5 and 5–10 min, which contributed almost 50% towards their total daily sedentary time. Although the differences were very small, children engaged in significantly fewer sedentary bouts of nearly all durations during after-school hours compared to during school hours and in the evening period. Children also engaged in significantly fewer sedentary bouts of 5–10, 10–20, and 20–30 min per hour on a weekend day than on a weekday. Conclusions Although primary school children spend more than 60% of their waking time sedentary, they generally engaged in short sedentary bouts. Children’s sedentary bouts were slightly longer on weekdays, particularly during school hours and in the evening period, although the differences were very small. These results suggest that in this age group, interventions focusing on reducing total sedentary time rather than interrupting prolonged sedentary time are needed.

Abstract Background Recent technological advances provide an alternative yet underutilised opportunity for promoting physical activity in youth. The primary aim of the Raising Awareness of Physical Activity (RAW-PA) Study is to examine the short- and longer-term impact of a wearable activity monitor combined with digital behaviour change resources on adolescents’ daily physical activity levels. Methods/Design RAW-PA is a 12 week, multicomponent physical activity intervention that utilises a popular activity tracker (Fitbit® Flex) and supporting digital materials that will be delivered online via social media. The resources target key behaviour change techniques. The intervention structure and components have been informed by participatory research principles. RAW-PA will be evaluated using a cluster randomised controlled trial design with schools as the unit of randomisation. Twelve schools located in Melbourne, Australia, will allocated to either the intervention or wait-list control group. The target sample size is 300 Year 8 adolescents (aged 13–14 years). Participants’ moderate- to vigorous-intensity physical activity will be the primary outcome. Survey measures will be completed. Process factors (e.g. feasibility, acceptability/appeal, fidelity) will also be collected. Discussion To our knowledge, this study will provide some of the first evidence concerning the effect of wearable activity trackers and digital behaviour change resources on adolescents’ physical activity levels. This study will provide insights into the use of such technologies for physical activity promotion, which may have a significant impact on health education, promotion, practice and policy. Trial registration Australian and New Zealand Clinical Trials Registry No: ACTRN12616000899448 . Date of registration: July 7, 2016.

Abstract Background Schools are a key setting for promoting children’s physical literacy development. This review aimed to identify school-based interventions that adopted a holistic conceptualisation of physical literacy and examine the effects on children’s physical literacy and any other outcomes, including physical activity (PA). Methods Searches were conducted in seven databases (APA PsycINFO, EMBASE, ERIC, CINAHL, Global Health, MEDLINE Complete, SPORTDiscus with Full Text), and Google and Google Scholar, to identify articles published since 1/1/2017. Studies were included if they (i) adopted a holistic conception of physical literacy as represented by the Australian Physical Literacy Framework (APLF), (ii) were grounded in movement, (iii) assessed three or more domains of learning (either quantitatively or qualitatively), and (iv) included children aged 5–14 years. Quantitative research designs needed to provide pre-and post-intervention measures, whereas qualitative designs (e.g. post-intervention interviews) did not. Study selection, data extraction and quality assessment were conducted independently by teams of two authors. For intervention effects, quantitative and qualitative data were synthesised separately. For quantitative data, level of evidence for intervention effects was assessed by physical literacy domain and/or elements/items by examining the proportion of tests with a significant change in the expected direction. Qualitative data were synthesised using the framework synthesis method and mapped to a framework that included APLF domains/elements, PA, and additional outcomes. Results Twelve interventions with 1,427 participants from seven countries were identified: six physical education-based, three afterschool, one structured recess, and two multicomponent. All studies assessed the physical domain quantitatively, with strong positive evidence of intervention effects for the controlled designs (10 of 15 tests). For the affective and cognitive domains, evidence was mixed, and there was no evidence for interventions improving the social components of children’s physical literacy (although this was understudied). Most studies assessed PA and one measured cognitive performance; however, there was no evidence for positive intervention effects (i.e. ≥35% of tests reporting an improvement) for either outcome. Five studies assessed intervention effects qualitatively, with positive results reported for all physical literacy domains, PA, and cognitive performance. Conclusions Holistic interventions in schools can improve the physical domain of children’s physical literacy. For wider benefits, future interventions should aim to develop all facets of physical literacy, especially domains of learning less frequently targeted and examined. Trial Registration PROSPERO CRD42022351317.

Abstract Background There is limited evidence of the associations between postural-derived sitting time, waist-worn derived sedentary time and children’s health and the moderation effect of physical activity (PA). This study examined associations of children’s device-measured sitting time with cardiometabolic health risk factors, including moderation by physical activity. Methods Cross-sectional baseline data from children (mean-age 8.2 ± 0.5 years) in Melbourne, Australia (2010) participating in the TransformUs program were used. Children simultaneously wore an activPAL to assess sitting time and an ActiGraph GT3X to assess sedentary time and physical activity intensity. Cardiometabolic health risk factors included: adiposity (body mass index [BMI], waist circumference [WC]), systolic and diastolic blood pressure (SBP, DBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), cholesterol, triglycerides, fasting plasma glucose (FPG), serum insulin, and 25-hydroxyvitaminD (25[OH]D). Linear regression models (n = 71–113) assessed associations between sitting time with each health risk factor, adjusted for different PA intensities (i.e. light [LIPA], moderate-vigorous intensities [MVPA], separately on each model), age, sex, adiposity, and clustering by school. Interaction terms examined moderation. The analyses were repeated using device-measured sedentary time (i.e. ActiGraph GT3X) for comparison. Results Sitting time was positively associated with SBP (b = 0.015; 95%CI: 0.004, 0.026), DBP (b = 0.012; 95%CI:0.004, 0.020), and FPG (b = 0.001; 95%CI: 0.000, 0.000), after adjusting for higher PA intensities. The association between sitting time and insulin (b = 0.003; 95%CI: 0.000, 0.006) was attenuated after adjusting for higher PA intensities. When the models were adjusted for LIPA and MVPA, there was a negative association with LDL (b=-0.001; 95%CI: -0.002, -0.000 and b=-0.001; 95%CI: -0.003, -0.000, respectively). There was a negative association of sedentary time with WCz (b=-0.003; 95%CI: -0.005, 0.000) and BMIz (b=-0.003; 95%CI: -0.006, -0.000) when the models were adjusted by MVPA. Sedentary time was positively associated with triglycerides (b = 0.001; 95%CI: 0.000, 0.001) but attenuated after adjusting for MVPA. No evidence of moderation effects was found. Conclusions Higher volumes of sitting and sedentary time were associated with some adverse associations on some cardiometabolic health risk factors in children. These associations were more evident when sitting time was the predictor. This suggests that reducing time spent sitting may benefit some cardiometabolic health outcomes, but future experimental research is needed to confirm causal relationships and identify the biological mechanisms that might be involved. Trial registration Australian New Zealand Clinical Trials Registry: ACTRN12609000715279.

Abstract Background Globally, just one in five adolescents meet physical activity guidelines and three-quarters of the school day is spent sitting. It is unclear which types of school-based interventions strategies increase physical activity and reduce sedentary time among adolescents, or how these interventions are implemented influences their effectiveness. Objective The three aims of our systematic review were to (a) identify intervention strategies used within secondary school settings to improve students’ movement behaviours throughout school-based initiatives, delivered at or by the school; (b) determine the overall effect of the interventions (meta-analysis) on physical activity (all intensities), sedentary time, cognitive/academic, physical health and/or psychological outcomes; and (c) describe factors related to intervention implementation. Methods Searches were conducted in MEDLINE complete, EMBASE, CINAHL, SPORTDiscus, APA PsycINFO, and ERIC in January 2023 for studies that (a) included high school-aged adolescents; (b) involved a school-based intervention to increase physical activity and/or decrease sedentary time; and (c) were published in English. Reported effects were pooled in meta-analyses where sufficient data were obtained. Results Eighty-five articles, representing 61 interventions, met the inclusion criteria, with 23 unique intervention strategies used. Interventions that involved whole-school approaches (i.e., physical activity sessions, environmental modifications, teacher training, peer support and/or educational resources) were favourably associated with most of the outcomes. The meta-analyses showed: (a) non-significant effects for sedentary time (Standardized mean difference [SMD] = -0.02; 95%CI, -0.14, 0.11), physical activity at all intensities (light: SMD= -0.01; 95%CI, -0.08, 0.05; moderate: SMD = 0.06; 95%CI, -0.09, 0.22; vigorous: SMD = 0.08; 95%CI, -0.02, 0.18; moderate-to-vigorous: SMD = 0.05; 95%CI, -0.01, 0.12) and waist circumference (SMD = 0.09; 95%CI, -0.03, 0.21), and (b) a small statistically significant decrease in body mass index (SMD= -0.09, 95%CI -0.16, -0.0). Factors related to intervention implementation were reported in 51% of the articles. Conclusion While some intervention approaches demonstrated promise, small or null effects were found in meta-analyses. Future school-based interventions should utilize a whole-school approach designed to increase adolescents’ activity across the day. Consistent reporting of implementation will increase understanding of how interventions are adopted, implemented and sustained. Registration PROSPERO (CRD42020169988).

Abstract Background Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8–9 year old children (Transform-Us!). Methods Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort’s lifetime from the public-payer perspective, assuming the intervention was delivered to all 8–9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions. Results Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were “dominant”, meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 − 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years. Conclusions The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained. Trial registration International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).

Abstract Background The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners). Methods Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin ‘top 10’ lists of the most important research needs. Results From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT. Conclusions Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities.

Abstract Background Despite significant interest in assessing activity patterns in different populations, there has been no consensus concerning the definition and operationalisation of this term. This has limited the comparability, interpretability, and synthesis of study findings to date. The aim of this study was to establish a consensus regarding the way in which activity patterns and activity pattern components are defined and reported. Methods The activity patterns literature was searched to identify experts to be invited to participate and to develop a proposed definition of activity patterns and activity pattern components. A three-round modified Delphi survey was conducted online (November 2021 to May 2022). In Round 1, participants were asked to rate their agreement with a proposed activity patterns definition, which also included six activity pattern components (e.g., activity intensity, activity bout, transitions), six examples of activity patterns (e.g., frequency of postural transitions in discrete time periods) and eight items for reporting activity patterns in future research (n = 21 items). Open-ended questions enabled participants to provide further comments and suggestions for additional items. Consensus was defined a priori as ≥ 80% participants rating their agreement with an item. In Round 2, participants were asked to rate their agreement with 25 items (13 original items, eight amended, and four new). In Round 3, participants rated their agreement with 10 items (five original items, four amended, and one new). Results Twenty experts in activity patterns research participated in Round 1, with response rates of 80% and 60% in Rounds 2 and 3, respectively. The proposed activity pattern definition, all activity pattern components definitions, four of the six activity pattern examples, and 10 items in the activity patterns reporting framework achieved consensus. The removal of one activity component item between Rounds 1 and 2 achieved consensus. Conclusion This modified Delphi study achieved consensus for defining and reporting activity patterns for the first time. This consensus definition enables standardisation of activity patterns terminology, which is important given the significant interest in quantifying how individuals accumulate their physical activity and sedentary behaviour across the lifespan to inform the development of future public health guidelines and interventions efforts.

Abstract Background Combinations of movement behaviors (i.e., physical activity, sedentary behavior, sleep) are associated with health and developmental outcomes in youth. Youth vary in how they accumulate these behaviors, both in volume and specific domains (e.g., sedentary time spent on recreational screen activities vs homework). The aim of this study was to examine how youth’s combined general and domain-specific movement trajectories differ by socioeconomic position. Methods We conducted a longitudinal, group-based multi-trajectory analysis to identify general and domain-specific movement trajectory profiles for 2457 youth from age 10 to 14 years from the Longitudinal Study of Australian Children from 2014–2018. We used multinomial logistic regression to test if socioeconomic position predicted profile membership. Results We identified three general movement trajectory profiles for both sexes, four domain-specific profiles for males, and five for females. For general movement trajectories, females from lower socioeconomic positions were more likely to be a combination of less active and more sedentary than females from higher socioeconomic positions. Males across socioeconomic positions spend similar amounts of time in physical activity, sedentary time, and sleep. For domain-specific movement trajectories, youth from lower socioeconomic positions were likely to spend a combination of less time in education-based sedentary behavior and more time in recreational screen activities than their higher socioeconomic position peers. Conclusion Our results indicate that socioeconomic position predicted in which domains youth accumulate their movements. Future observational research and interventions targeting different socioeconomic groups should therefore consider domain-specific movement trajectories.

Background/Objective: Past Physical Activity Report Cards have indicated a minority of Australian children and young people are sufficiently active. The purpose of this paper is to summarise grades across 10 indicators of the 2022 Australian Physical Activity Report Card, to assess physical activity behaviours and supports. Methods: A development team consisting of research experts synthesised and evaluated national and state level data to inform grades for each indicator. Data were drawn from nationally and state/territory representative datasets spanning 2016–2021. Results: Overall Physical Activity Levels and Screen Time were both assigned grades of D-, remaining the worst performing indicators. Australia's best performing indicator was Community and the Built Environment (A-), followed by Organised Sport and Physical Activity (B-). Remaining indicators were Family and Peers (C+), School (C+), Strategies and Investments (C-), Active Transport (D-) and Physical Fitness (D-). Active Play was unable to be graded, due to lack of consensus on a primary metric for this indicator and a lack of representative data. Conclusion: Evidence suggests that physical activity levels of Australian children remain consistently low, despite access to and availability of facilities and open spaces. There is a strong need for a National Physical Activity Plan to address this. The theme for the 2022 Australian Physical Activity Report Card, REBOOT! Reimagining physically active lives encourages us all to think more imaginatively about how we might engage all children and young people through diverse physical activity opportunities to be more active.

Abstract Background TransformUs was a four-arm school-based intervention to increase physical activity and reduce sedentary behaviour among primary school children. Pedagogical and environmental strategies targeted the classroom, school grounds and family setting. The aims of this study were to evaluate program fidelity, dose, appropriateness, satisfaction and sustainability, and associations between implementation level and outcomes among the three intervention arms. Methods At baseline, 18-months (mid-intervention) and 30-months (post-intervention), teachers, parents and children completed surveys, and children wore GT3X ActiGraph accelerometers for 8 days at each time point to determine physical activity and sedentary time. Implementation data were pooled across the three intervention groups and teachers were categorised by level of implementation: (i) ‘Low’ ( 67% delivered). Linear and logistic mixed models examined between group differences in implementation, and the association with children’s physical activity and sedentary time outcomes. Qualitative survey data were analysed thematically. Results Among intervention recipients, 52% (n = 85) of teachers, 29% (n = 331) of parents and 92% (n = 407) of children completed baseline evaluation surveys. At 18-months, teachers delivered on average 70% of the key messages, 65% set active/standing homework, 30% reported delivering > 1 standing lesson/day, and 56% delivered active breaks per day. The majority of teachers (96%) made activity/sports equipment available during recess and lunch, and also used this equipment in class (81%). Fidelity and dose of key messages and active homework reduced over time, whilst fidelity of standing lessons, active breaks and equipment use increased. TransformUs was deemed appropriate for the school setting and positively received. Implementation level and child behavioural outcomes were not associated. Integration of TransformUs into existing practices, children’s enjoyment, and teachers’ awareness of program benefits all facilitated delivery and sustainability. Conclusions This study demonstrated that intervention dose and fidelity increased over time, and that children’s enjoyment, senior school leadership and effective integration of interventions into school practices facilitated improved intervention delivery and sustainability. Teacher implementation level and child behavioural outcomes were unrelated, suggesting intervention efficacy was achieved irrespective of implementation variability. The potential translatability of TransformUs into practice contexts may therefore be increased. Findings have informed scale-up of TransformUs across Victoria, Australia. Trial registration International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Registered 19 August 2009. Available at: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=308387&isReview=true

Abstract Background Globally, significant efforts have focused on increasing physical activity and reducing sedentary behaviour in youth and adults across a range of settings (e.g., schools, workplaces, community, and home). Despite this, interventions have had varied efficacy and typically have failed to sustain changes in behaviours over time. One explanation that has been put forth to explain the mixed success of interventions is activity compensation. However, little is known about activity compensation, including whether compensation occurs, and perceptions and potential mechanisms of activity compensation. Understanding activity compensation would assist in tailoring and targeting of potential intervention strategies. The primary aim of this review was to synthesise research that has investigated activity compensation in youth and adults. The secondary aim was to identify potential reasons for and/or awareness of compensatory changes that may have occurred. Methods An electronic search of the EBSCOhost (via Academic Search Complete, CINAHL Complete, Education Source, Health Source: Nursing/Academic Edition, PsycINFO, SPORTdiscus with Full Text), MEDLINE Complete, Global Health, EMBASE, Scopus and Web of Science databases up to May 2021 was conducted. Quality assessment of included quantitative studies used a modified compensation-specific McMaster Quality Assessment Tool. Results A total of 44 studies met the inclusion criteria (22 = adult populations; 22 = youth populations) and were classified as (1) quantitative (n = 31); (2) combination of quantitative and behavioural (n = 11); (3) behavioural only (n = 1); and (4) qualitative (n = 1). Of the 42 studies that included a quantitative component, 11 (26%) reported compensation occurred. Within the 13 studies examining specific behaviours, 35 behaviours were assessed, and evidence of compensation was inconsistent. Compensation mechanisms included fatigue, time constraints, lack of motivation, drive to be inactive, fear of overexertion, and autonomous motivation. Conclusion Little evidence of compensation was reported in the included quantitative studies; however, inconsistencies between studies makes comparisons difficult. There was considerable variability in the types of behaviours assessed in quantitative studies, and few studies examined potential compensatory mechanisms. Future research, using compensation specific study designs, methods, and analytic techniques, within different population sub-groups, should address these evidence gaps.

Purpose: The study aimed to describe youth time-use compositions, focusing on time spent in shorter and longer bouts of sedentary behavior and physical activity (PA), and to examine associations of these time-use compositions with cardiometabolic biomarkers. Methods: Accelerometer and cardiometabolic biomarker data from 2 Australian studies involving youths 7–13 years old were pooled (complete cases with accelerometry and adiposity marker data, n = 782). A 9-component time-use composition was formed using compositional data analysis: time in shorter and longer bouts of sedentary behavior; time in shorter and longer bouts of light-, moderate-, or vigorous-intensity PA; and “other time” (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as

Abstract Background There has been increasing interest in using wearable activity trackers to promote physical activity in youth. This study examined the short- and longer-term effects of a wearable activity tracker combined with digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas. Methods The Raising Awareness of Physical Activity (RAW-PA) Study was a 12-week, multicomponent intervention that combined a Fitbit Flex (and accompanying app), and online digital behaviour change resources and weekly challenges delivered via Facebook. RAW-PA was evaluated using a cluster-randomised controlled trial with 275 adolescents (50.2% female; 13.7 ± 0.4 years) from 18 Melbourne secondary schools (intervention n = 9; wait-list control group n = 9). The primary outcome was moderate- to vigorous-intensity physical activity (MVPA), measured using hip-worn ActiGraph accelerometers. The secondary outcome was self-reported physical activity. Data were collected at baseline, 12-weeks (immediately post-intervention), and 6-months post-intervention (follow-up). Multilevel models were used to determine the effects of the intervention on daily MVPA over time, adjusting for covariates. Results No significant differences were observed between intervention and wait-list control adolescents’ device-assessed MVPA immediately post-intervention. At 6-months post-intervention, adolescents in the intervention group engaged in 5 min (95% CI: − 9.1 to − 1.0) less MVPA per day than those in the wait-list control group. Males in the intervention group engaged in 11 min (95% CI: − 17.6 to − 4.5) less MVPA than males in the wait-list control group at 6-months post-intervention. No significant differences were observed for females at either time point. For self-reported physical activity, no significant effects were found at 12-weeks and 6-months post-intervention. Conclusions Combining a wearable activity tracker with digital behaviour change resources and weekly challenges did not increase inactive adolescents’ accelerometer-derived and self-reported physical activity levels immediately post-intervention. This contrasts previous research that has suggested wearable activity tracker may increase youth physical activity levels in the short-term. Lower engagement in MVPA 6-months post-intervention was observed for males but not for females, though it is unclear why this finding was observed. The results suggest wearable activity trackers, in combination with supporting materials, may not be effective for increasing physical activity levels in adolescents. Trial registration ACTRN12616000899448 . Australian and New Zealand Clinical Trials Registry. Registered 7 July 2016.

In Northern Ireland (NI), many children do not meet the recommended levels of physical activity (PA). To reduce the prevalence of physical inactivity and associated health conditions, it is important to understand the influences on children's PA, which in turn has the potential to inform future intervention design. The purpose of this formative study was to examine the current views, barriers, facilitators, experiences, and perceptions of children in relation to PA in the classroom, school, and home environments, and to assess the acceptability of components for a school-based intervention. Write and draw tasks and semi-structured focus groups (n = 10) were conducted with 50 children aged 7–9 years (22 boys, 28 girls) from six primary schools. Focus groups were recorded, transcribed, and analyzed thematically. Pen profiles were constructed from the transcripts in a deductive manner and represent key emergent themes. Results indicated that children's perception and knowledge of PA was mainly structured and sport-based, while some referred to fun, play and health. Fun, social support and outdoor activity were identified as key facilitators. Barriers included parental restrictions, lack of time and space in the different environments. The acceptability of intervention components was examined, children recognized the potential benefits of additional movement in the classroom, but opinions differed on the sit-to-stand desks. Findings contribute to a more detailed understanding of children's perceptions of context specific PA, the barriers they face, in addition to factors that support them to lead a physically active lifestyle, which may inform future PA promotion strategies.

Background: Low cardiorespiratory fitness is an independent predictor of all-cause and cardiovascular mortality, and interventions that increase fitness reduce risk. Water-walking decreases musculoskeletal impact and risk of falls in older individuals, but it is unclear whether water-walking improves aerobic fitness in the same way as weight-dependent land-walking. This randomized controlled trial involved 3 intervention groups—a no-exercise control group (CG), a land-walking (LW) group, and a water-walking (WW) group—to investigate the comparative impacts of LW and WW to CG on fitness. Methods: Both exercise groups attended individually tailored, center-based, intensity-matched 3 × weekly sessions for 24 weeks, which progressed to 150 min of exercise per week. This was followed by a 24-week no-intervention period. Maximal graded exercise tests were performed on a treadmill at Weeks 0, 24, and 48. Results: Maximal oxygen uptake increased from Week 0 to Week 24 in both exercise groups (0.57 ± 0.62 mL/kg/min, 0.03 ± 0.04 L/min for LW; 0.93 ± 0.75 mL/kg/min, 0.06 ± 0.06 L/min for WW, mean ± SE) compared to the CG (–1.75 ± 0.78 mL/kg/min, –0.16 ± 0.05 L/min) (group × time, p < 0.05). Time to exhaustion increased significantly following LW only (123.4 ± 25.5 s), which was significantly greater (p = 0.001) than the CG (24.3 ± 18.5 s). By Week 48, the training-induced adaptations in the exercise groups returned to near baseline levels. Conclusion: Our study supports current physical-activity recommendations that 150 min/week of moderate-intensity exercise produces improvements in fitness in previously sedentary older individuals. Also, LW and WW elicit similar improvements in fitness if conducted at the same relative intensities. Exercise-naïve older individuals can benefit from the lower impact forces and decreased risk of falls associated with WW without compromising improvements in cardiorespiratory fitness.

Abstract Background Understanding changes in physical activity and sedentary time (SED) during early childhood may provide insights into how to effectively promote a healthy start to life. This study examined changes in total volume and bouts of SED, light- (LPA), and moderate- to vigorous-intensity physical activity (MVPA) across early childhood, and explored differences in change between boys and girls. Methods Data were drawn from 330 children participating in the Melbourne InFANT Program, collected between 2008 and 2013 and analysed in 2017. Children’s physical activity and SED were assessed for at least 7 days at each timepoint using ActiGraph GT1M accelerometers at 19 months, 3.5 and 5 years of age. Total volume of SED (≤100 counts per minute [CPM]), LPA (101–1680 CPM) and MVPA (≥1681 CPM) were expressed as a percentage of wear time, and the frequency (number of bouts/day) and duration (mins/bout) of SED, LPA and MVPA bouts ≥1 min were calculated at each time point. Multilevel models with random intercepts and slopes were used to examine changes in total volume and bouts of SED, LPA and MVPA for boys and girls. Results Compared to aged 19 months, children’s total volume of SED and LPA decreased at 3.5 and 5 years old, while MVPA increased. The frequency of SED bouts at 3.5 and 5 years was greater than at 19 months, but the duration was shorter. Additionally, the frequency and duration of LPA bouts was lower and MVPA bout frequency and duration was greater at 3.5 and 5 years. In general, there was no evidence of sex differences in trajectories of children’s physical activity and SED. However, variations in trajectory were observed at the individual child level. Conclusions Children’s total volume and bouts of SED, LPA and MVPA change across early childhood, mostly in a favourable direction. Trajectories appear to be similar for boys and girls. Investigation of individual variation in trajectories is likely to provide greater insight into associations between physical activity and future health and behavioural outcomes.

Objectives: To investigate the acute benefits of breaking up prolonged sitting with light-intensity physical activity on (i) glucose metabolism under conditions of sleep restriction, and (ii) cognitive deficits associated with sleep restriction. Methods: This counterbalanced, crossover trial consisted of two five-day (5 night) experimental conditions separated by a two-week washout period. On the first night, participants were given a 9-h sleep opportunity to allow the collection of steady-state baseline measures the following day. This was followed by three consecutive nights of sleep restriction (5-h sleep opportunity). In the sitting condition (SIT), participants remained seated between 1000 and 1800 h. In the physical activity condition (ACT), participants completed 3-min bouts of light-intensity walking every 30 min on a motorised treadmill between 1000 and 1800 h. At all other times, in both conditions, participants remained seated, except when walking to the dining room or to use the bathroom (max distance = 32 m). Six physically inactive, healthy males were randomised to one of two trial orders, 1) SIT then ACT, or 2) ACT then SIT. Continuous measures of interstitial glucose were measured at 5-min intervals. A cognitive and subjective test battery was administered every two hours during wake periods. Analyses were conducted using a series of linear mixed-effect ANOVAs. Results: No differences in interstitial glucose concentration or cognitive performance were observed between the SIT condition and the ACT condition. Participants reported higher levels of sleepiness, and felt less alert in the SIT condition compared with the ACT condition. Conclusions: There were no observable benefits of breaking up prolonged sitting on glucose metabolism under conditions of sleep restriction. These findings have implications for behaviour change interventions. Future studies will need to include larger, less homogenous study populations and appropriate control conditions (i.e., 8–9 h sleep opportunities). Keywords: Physical activity, Exercise, Sitting breaks, Sedentary behaviour, Fatigue, Sleepiness

This study aimed to examine the associations between play behaviors during preschool recess and foundational movement skills (FMS) in typically developing preschool children. One hundred and thirty-three children (55% male; mean age 4.7 ± 0.5 years) from twelve preschools were video-assessed for six locomotor and six object-control FMS using the Champs Motor Skill Protocol. A modified System for Observing Children’s Activity and Relationships during Play assessed play behaviors during preschool recess. Associations between the composition of recess play behaviors with FMS were analyzed using compositional data analysis and linear regression. Results: Relative to time spent in other types of play behaviors, time spent in play without equipment was positively associated with total and locomotor skills, while time spent in locomotion activities was negatively associated with total and locomotor skills. No associations were found between activity level and group size play behavior compositions and FMS. The findings suggest that activity type play behaviors during recess are associated with FMS. While active games without equipment appear beneficial, preschool children may need a richer playground environment, including varied fixed and portable equipment, to augment the play-based development of FMS.

Children spend over 60% of their school day sitting; much of this occurs in the classroom. Emerging research has examined the impact of environmental interventions on classroom sitting. While this research is promising, it has predominantly focused on the primary school setting. This study examined the impact and feasibility of height-adjustable desks on time spent sitting/standing during classroom lessons in a secondary school. Traditional desks in a Melbourne secondary school classroom were replaced with 27 height-adjustable desks (intervention classroom). Forty-three adolescents (51% male; mean age 13.7 ± 1.4 years) from Grades 7, 9 and 10 wore an inclinometer and accelerometer for schooldays and completed a survey after using the desks during lessons for seven weeks. Ten teachers (50% male) completed a survey. Time spent sitting, standing, and the length of sitting bouts were compared between periods when adolescents were in the intervention classroom versus traditional classrooms (matched on teacher and subject). Compared to the traditional classroom, adolescents spent 25% less time sitting and 24% more time standing in the intervention classroom (effect size > 0.8), and had a greater frequency of short sitting bouts and fewer longer bouts. The majority of teachers (71%) and students (70%) reported wanting to continue to use the height-adjustable desks. When standing during lessons, adolescents reported working well (69%); however, a third reported difficulties paying attention (28%) and becoming distracted (36%). Few teachers reported negative influences on adolescents’ ability to work (14%) and concentrate (14%). Half the adolescents reported leg, or back pain with standing. Introducing height-adjustable desks resulted in lower levels of sitting compared with traditional classrooms, was acceptable and had some adverse effects on concentration and discomfort. The study provides preliminary evidence that height-adjustable desks may help reduce prolonged sitting in school among adolescents. Future research should incorporate a control group and explore behavioural and academic outcomes.

Background: To investigate the impact of playing sports Active Video Games on children's actual and perceived object control skills. Methods: Intervention children played Active Video Games for 6 weeks (1 h/week) in 2012. The Test of Gross Motor Development-2 assessed object control skill. The Pictorial Scale of Perceived Movement Skill Competence assessed perceived object control skill. Repeated measurements of object control and perceived object control were analysed for the whole sample, using linear mixed models, which included fixed effects for group (intervention or control) and time (pre and post) and their interaction. The first model adjusted for sex only and the second model also adjusted for age, and prior ball sports experience (yes/no). Seven mixed-gender focus discussions were conducted with intervention children after programme completion. Results: Ninety-five Australian children (55% girls; 43% intervention group) aged 4 to 8 years (M 6.2, SD 0.95) participated. Object control skill improved over time (p = 0.006) but there was no significant difference (p = 0.913) between groups in improvement (predicted means: control 31.80 to 33.53, SED = 0.748; intervention 30.33 to 31.83, SED = 0.835). A similar result held for the second model. Similarly the intervention did not change perceived object control in Model 1 (predicted means: control: 19.08 to 18.68, SED = 0.362; intervention 18.67 to 18.88, SED = 0.406) or Model 2. Children found the intervention enjoyable, but most did not perceive direct equivalence between Active Video Games and ‘real life’ activities. Conclusions: Whilst Active Video Game play may help introduce children to sport, this amount of time playing is unlikely to build skill.

Cardiometabolic disease poses a serious health and economic burden worldwide and its prevalence is predicted to increase. Prolonged sitting, lack of physical activity, poor diet, and short sleep duration are ubiquitous behaviors in modern society, and all are independent risk factors in the development of cardiometabolic disease. Existing evidence demonstrates that breaking up prolonged periods of sitting is beneficial for cardiometabolic health, however, studies have not controlled for prior sleep duration. This article examines how prolonged sitting and short sleep duration independently contribute to cardiometabolic risk, and how breaking up sitting and obtaining adequate sleep may reduce this risk. We suggest that as prolonged sitting and short sleep duration influence the same cardiometabolic parameters, there is potential for short sleep to attenuate the positive impact of breaking up prolonged sitting with physical activity. Likewise, breaking up prolonged sitting and obtaining adequate sleep together could improve predictors of cardiometabolic disease, i.e., the combined effect may be stronger than either alone. To explore these perspectives, we propose a research agenda to investigate the relationship between breaking up prolonged sitting with physical activity and short sleep duration. This will provide an evidence-base for informing the design of interventions to reduce the burden of cardiometabolic disease on communities worldwide.