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Objective: To examine associations between work and commute hours with food consumption and test whether neighbourhood type (20-minute neighbourhood (20MN)/non-20MN) moderate associations. Design: Cross-sectional analysis of the Places and Locations for Activity and Nutrition study (ProjectPLAN). Exposures were work hours (not working (0 h), working up to full-time (1–38 h/week), working overtime (> 38 h/week)), and among those employed, combined weekly work and commute hours (continuous). Outcomes were usual consumption of fruit, vegetables, takeaway food, snacks and soft drinks, and number of discretionary food types (takeaway, snacks and soft drinks) consumed weekly. Generalised linear models were fitted to examine associations between each exposure and outcome. The moderating role of neighbourhood type was examined through interaction terms between each exposure and neighbourhood type (20MN/non-20MN). Setting: Melbourne and Adelaide, Australia, 2018–2019. Participants: Adults ≥ 18 years old (n 769). Results: Although all confidence intervals contained the null, overall, patterns suggested non-workers and overtime workers have less healthy food behaviours than up-to-full-time workers. Among those employed, analysis of continuous work and commute hours data suggested longer work and commute hours were positively associated with takeaway consumption (OR = 1·014, 95 % CI 0·999, 1·030, P-value = 0·066). Patterns of better behaviours were observed across most outcomes for those in 20MN than non-20MN. However, differences in associations between work and commute hours with food consumption across neighbourhood type were negligible. Conclusions: Longer work and commute hours may induce poorer food behaviours. There was weak evidence to suggest 20MN moderate associations between work and commute hours with food consumption, although behaviours appeared healthier for those in 20MN.

Physical activity (PA) among children and adolescents is often reported by time segments centered around the school day, including before school. However, there is no consistent approach to defining the before-school segment, to accurately capture PA levels and facilitate synthesis of results across studies. Therefore, this study aimed to (a) examine how studies with children and adolescents have defined the before-school segment, and (b) compare adolescents’ before-school PA using various segment definitions. We conducted a systematic search and review of literature from six databases, and subsequently analyzed accelerometer data from Australia (n = 472, mean age 14.9 years, 40% male), to compare PA across five before-school definitions. Our review found 69 studies reporting before-school PA, 59 of which used device-based measures. Definitions ranged widely, but justifications were rarely reported. Our empirical comparison of definitions resulted in a range of participants meeting wear time criteria (≥3 days at >50% of segment length) from the latest-starting definition (30 min prior to school; n = 443) to the earliest-starting definition (6:00 a.m.–school start; n = 155), implying that for many participants, accelerometer wear was low in the early hours due to sleep or noncompliance. Statistically significant differences in light and moderate-to-vigorous PA (mean minutes/school day, proportion of segment length, and proportion of wear time) were found between definitions, indicating that before-school PA could potentially be underestimated depending on definition choice. We recommend that future studies clearly report and justify segment definition, apply segment-specific wear time criteria, and collect wake time data to enable individualized segment start times and minimize risk of data misclassification.

This study examined adolescent muscle-strengthening exercise (MSE) participation at home and associated socioecological correlates during Australia’s initial COVID-19 lockdown restrictions. Adolescents (N = 731, Mage = 16.3, SD = 1.2 years, 73% female) self-reported their MSE participation in February 2020 (pre-lockdown; at a gym or at home) and April/May (during lockdown; at home only as gyms were closed). They also reported a range of potential individual, family, and home environment correlates. Remoteness and area-level socioeconomic disadvantage were also considered. Logistic regression models examined potential correlates of participation in any MSE and MSE engagement ≥3 times/week during April/May. Fewer adolescents participated in MSE during April/May (48%) than February (54%), however, the proportions that engaged in MSE ≥3 times/week were the same (30%). Prioritising being active every day (OR = 2.43, 95% CI = 1.52, 3.90), being active with sibling/s ≥ 5 days/week (OR = 2.24, 95% CI = 1.00, 5.00) and access to weights at home (OR = 2.98, 95% CI = 1.94, 4.57) were associated with higher odds of any MSE participation at home during April/May. These variables were also positively associated with MSE participation at home ≥3 times/week. Understanding how to support adolescents to prioritise being active, engage in MSE with siblings, and provide equipment may assist adolescents to engage in home-based MSE. Refereed/Peer-reviewed

The majority of Australian adolescents are insufficiently active and becoming car dependent. Replacing short passive travel (i.e. car, public transport) with active travel could be an important potential strategy to increase physical activity. This paper aims to characterize adolescents’ travel patterns to various destinations, identify passive trips that could be feasibly replaced by active travel, and the characteristics associated with those trips. Analyses were based on 2,192 Victorian secondary school students aged 12-17 years with 24-h travel diary data in the Victorian Integrated Survey of Travel Activity 2012 − 2016. Feasible distance thresholds for walking and cycling were determined at the 80th percentile of distances of reported walking and cycling trips in the sample. Comparison tests were conducted to assess whether travel patterns differed by sociodemographic characteristics. Multilevel logistic regression analyses identified characteristics of individuals that could replace passive trips with active travel, and characteristics of passive trips that could be replaced by active travel. About 11% of adolescents could feasibly replace at least one of their short passive trips with walking and 48% could feasibly replace at least one of their short passive trips with cycling. Of all the passive trips recorded, about 8% could be replaced with walking and 44% could be replaced with cycling. Trips that commenced within daylight hours, and trips made for shopping and social reasons had higher odds of being replaceable by active travel. The sizable proportion of replaceable passive trips within the cyclable threshold calls for greater emphasis on encouraging cycling.

Background: Evidence for longitudinal associations between childhood weight status and academic achievement remains unclear due to considerable heterogeneity in study design, measures of academic achievement and appropriate categorization of weight status. Objective: To examine longitudinal associations between childhood weight status (underweight, healthy weight, overweight/obese) and academic achievement in the transition from preschool to primary (elementary) school among Australian school children. Methods: Data were from the Healthy Active Preschool and Primary Years study. Height and weight, for calculating BMI were measured at baseline (preschool age 3–5 years; 2008/9) and follow-up (primary school age 6–8 years; 2011/12). Academic achievement was measured at age 9 years. Results: No associations between BMI z-score or weight category in the preschool years and later NAPLAN scores were found for boys. For girls, having a higher BMI z-score (B = −13.68, 95%CI: −26.61, −0.76) and being affected by overweight (B = −33.57, 95%CI: −61.50, −5.24) in preschool was associated with lower language scores. Remaining affected by overweight from preschool to primary school was associated with lower numeracy (B = −25.03, 95%CI: −49.74, −0.33), spelling (B = −33.5, 95%CI: −63.43, −3.58), language (B = −37.89, 95%CI: −72.75, −3.03) and total achievement scores (B = −24.24, 95%CI: −44.85, −3.63) among girls. For boys, becoming affected by overweight was associated with lower spelling (B = −38.76, 95%CI: −73.59, −3.93) and total achievement scores (B = −27.70, 95%CI: −54.81, −0.58). Conclusions: Associations between being affected by overweight/obesity and poorer academic achievement were more pronounced in girls than boys, indicating potentially inequitable impacts of excess weight and highlighting the greater need for intervention among girls. However, stronger study designs are needed to confirm our findings. Refereed/Peer-reviewed

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.

Background A high proportion of adolescents worldwide are not doing enough physical activity for health benefits. Replacing short motorised trips with walking or cycling has the potential to increase physical activity at the population level. This study aimed to estimate the proportion of short distance motorised trips that could be replaced with walking or cycling, and the potential physical activity gains by sociodemographic and trip characteristics. Methods Data were from a subsample of the NEighbourhood Activity in Youth (NEArbY) study conducted among adolescents in Melbourne. A total of 217 adolescents with at least one motorised trip completed a survey and wore a Global Positioning Systems (GPS) device for eight consecutive days. Classification of travel modes were based on speed. GPS data points were geocoded in ArcGIS. Motorised trips within walkable (1.3 km) and cyclable (4.2 km) distances were identified (threshold based on 80th percentile of walking and cycling trip distances among Victorian adolescents), and the additional physical activity minutes that could be accrued by replacing walkable or cyclable motorised trip to active trips were quantified. Multilevel linear regression was used to assess differences in physical activity minutes gain by sociodemographic and trip characteristics. Results A total of 4,116 motorised trips were made. Of these, 17% were walkable and 61% were cyclable. Replacing motorised trips by walking and cycling resulted in estimated gains of six minutes and 15 min of physical activity per day, respectively. Conclusion The sizable proportion of replaceable trips and potential physical activity gains from this shift calls for attention to improve safe and connected infrastructure to support active travel.

Background: This study examined the strength, shape and direction of associations of accelerometer-assessed overall, school- and non-school-based moderate-to-vigorous physical activity (MVPA) and sedentary time (ST) with BMI among adolescents across the world. Second, we examined whether these associations differed by study site and sex. Methods: Cross-sectional data from the IPEN Adolescent study, an observational multi-country study, were used. Participants wore an accelerometer for seven days, reported height and weight, and completed a socio-demographic survey. In total, 4852 adolescents (46.6% boys), aged 11–19 years (mean age = 14.6, SD = 1.7 years) were included in the analyses, using generalized additive mixed models. Results: Adolescents accumulated on average 41.3 (SD = 22.6) min/day of MVPA and 531.8 (SD = 81.1) min/day of ST, and the prevalence of overweight and obesity was 17.2% (IOTF), but these mean values differed by country. Linear negative associations of accelerometer-based MVPA and ST with standardized BMI scores and the likelihood of being overweight/obese were found. School-based ST and non-school-based MVPA were more strongly negatively associated to the outcomes than non-school based ST and school-based MVPA. Study site moderated the associations; adolescent sex did not. No curvilinear associations were found. Conclusions: This multi-country study confirmed the importance of MVPA as a potential protective factor against overweight/obesity in adolescents. Non-school-based MVPA seemed to be the main driver of these associations. Unexpected results were found for ST, calling for further examination in methodologically sound international studies but using inclinometers or pressure sensors to provide more precise ST measures., United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01 HL111378 FWO FWO12/ASP/102, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 306836/2011-4, Grant Agency of the Czech Republic GA14-26896S GA17-24378S, University of Southern Denmark, Health and Medical Research Fund (Food and Health Bureau, Government of the Hong Kong SAR, PR of China) 10111501, Madras Diabetes Research Foundation (MDRF), Chennai, Israel Science Foundation 916/12, Universiti Sains Malaysia International Research Collaboration Grant, Health Research Council of New Zealand HRC12/329, Portuguese Foundation for Science and Technology, Center for Forestry Research & Experimentation (CIEF) GV-2013-087, National Institutes of Health (NIH) - USA R01 HL083454, Future Leader Fellowship from the National Health Foundation of Australia ID100046, Australian Research Council FT140100085, National Health and Medical Research Council (NHMRC) of Australia APP 1176885, National Institutes of Health (NIH) - USA R01 HL111378

Participatory school ground design projects have acknowledged benefits for children’s sense of empowerment, ownership and learning, but the play behaviour outcomes of these school ground projects a...

PurposeLittle is known about the experiences of school leaders adopting and implementing real-world, scaled-up physical activity interventions in the Australian educational system. Transform-Us! is a novel physical activity and sedentary behaviour intervention available to all primary schools in Victoria, Australia, since September 2018. This study explored barriers and facilitators experienced by school leaders during the adoption and early implementation phases of Transform-Us!.Design/methodology/approachQualitative study involving seven semi-structured telephone interviews with school leaders implementing Transform-Us! in primary schools in Victoria, Australia. Interview schedules were developed based on the theoretical domains framework (TDF). Interviews were coded using a framework analysis approach.FindingsFour key themes emerged relating to ten of the 14 TDF domains. Themes included: knowledge, goals, implementation factors and leadership. School leaders play a central role in creating a positive implementation environment including the delivery setting (classroom) and a supportive culture (knowledge sharing) in the school. The application of the TDF to the study bridges the gap between theory and practice and identifies potential future implementation strategies which may be further tested in professional practice future studies. Recommendations for increased adoption and sustained implementation related to seven core areas: presence of a school/programme champion(s); collaborative knowledge sharing; online training; school-based workshops; promotion of behavioural and mental health outcomes; teacher autonomy in delivery; and a supportive implementation environment.Originality/valueSchool leaders have a unique scope to influence the adoption and implementation of physical activity and sedentary behaviour interventions. This study outlines specific barriers and facilitators for implementation of a physical activity programme in the Australian educational setting and offers recommendations for programme optimisation.

BACKGROUND: The association between physical activity and adiposity in preschool-aged children is unclear. OBJECTIVE: To assess the cross-sectional association between objectively measured physical activity and body fat in preschool-aged children. METHODS: In the preschool review in an Australian birth cohort study (n = 1074), mean duration and time accumulated in ≥1-min bouts of physical activity at light-intensity (LPA), moderate- to vigorous-intensity (MVPA) and light- to vigorous-intensity (LMVPA) were computed from accelerometer (ActiGraph GT3X+) data. Percent body fat was assessed by bioelectrical impedance. Associations between physical activity and percent body fat were examined by multiple regression, adjusted for accelerometer wear time, MVPA (in analyses of LPA), maternal body mass index (BMI) and maternal education. RESULTS: A total of 450 participants (n = 450) had valid data. There was evidence of associations between physical activity and adiposity: each additional hour of LVPA was associated with 0.6% (CI95 -0.2%, 1.3%) higher body fat; ≥1-min bouts of LPA was associated with 1.0% (CI95 0.1%, 1.9%) higher body fat; each additional hour of MVPA was associated with -0.8% (CI95 -1.6%, -0.1%) less body fat; and ≥1-min bouts of MVPA was associated with -1.3% (CI95 -2.5%, -0.1%) body fat. CONCLUSIONS: Among a cohort of preschool-aged children, there was evidence that more intensive physical activity assessed by an accelerometer is associated with reduced body fat.

Background Little is known about how activity patterns change throughout childhood. This study examined changes and tracking of total volume and bouts of physical activity (PA) and sedentary time (SED) from early to late childhood. Methods Volume and bouts of SED and light-, moderate- and vigorous-intensity PA (LPA, MPA and VPA) were assessed by accelerometry at 3-5y (n = 758), 6-8y (n = 473) and 9-11y (n = 478). Mixed models examined changes and generalized estimating equations assessed tracking (β 0.6=strong), stratified by sex and controlling for baseline age and time between measurements. Results Patterns of SED increased and LPA decreased for both sexes. Total volume of MPA decreased for girls, but time in ≥ 1-min bouts increased for both sexes. Total volume of VPA increased for both sexes, with time spent in ≥ 1-min bouts increasing for boys. All volume and bout variables tracked moderately for boys, except SED bouts ≥15-min, LPA bouts ≥5-min and MPA bouts ≥1-min which tracked weakly. For girls, total SED and bouts ≥1-min tracked strongly, while total volume of LPA, MPA and VPA, ≥5- and ≥10-min SED bouts, and ≥1-min LPA and MPA bouts tracked moderately. Conclusions Activity patterns changed from early to late childhood, with total volumes and short bouts of PA and SED tracking more strongly than longer bouts. Although MVPA increased slightly, total volume and bouts of SED increased considerably more and, of concern, replaced LPA. Key messages Interventions are needed to ensure that young children establish and maintain healthy PA and SED levels from a young age.

Background: Although there is increasing evidence regarding children’s screen time, little is known about children’s sitting. This study aimed to determine the correlates of screen time and sitting in 6- to 8-year-old children. Methods: In 2011–2012, parents in the Healthy Active Preschool and Primary Years (HAPPY) study (n = 498) reported their child’s week/weekend day recreational screen time and potential correlates. ActivPALs™ measured children’s nonschool sitting. In model 1, linear regression analyses were performed, stratified by sex and week/weekend day and controlling for age, clustered recruitment, and activPAL™ wear time (for sitting analyses). Correlates significantly associated with screen time or sitting (P Results: Children (age 7.6 y) spent 99.6 and 119.3 minutes per day on week and weekend days engaging in screen time and sat for 119.3 and 374.6 minutes per day on week and weekend days, respectively. There were no common correlates for the 2 behaviors. Correlates largely differed by sex and week/weekend day. Modifiable correlates of screen time included television in the child’s bedroom and parental logistic support for, encouragement of, and coparticipation in screen time. Modifiable correlates of sitting included encouragement of and coparticipation in physical activity and provision of toys/equipment for physical activity. Conclusions: Interventions may benefit from including a range of strategies to ensure that all identified correlates are targeted.

Improving sedentary measurement is critical to understanding sedentary-health associations in youth. This study assessed agreement between the thigh-worn activPAL and commonly used hip-worn ActiGraph accelerometer methods for assessing sedentary patterns in children. Both devices were worn by 8-12-year-olds (N = 195) for 4.6 +/- 1.9 days. Two ActiGraph cut-points were applied to two epoch durations: 20%. ActiGraph 300c/60s had a better agreement than the other cut-points, but all ICCs were

Objectives To assess the feasibility and efficacy of a 6-week pilot active break program (ACTI-BREAK) on academic achievement, classroom behaviour and physical activity. Design Pilot cluster randomised controlled trial. Methods 374 children in Year 3 and 4 (74% response) were recruited from six schools across Melbourne, Australia. Schools were randomised to the ACTI-BREAK intervention or usual teaching practice. The intervention involved teachers incorporating 3 × 5 min active breaks into their classroom routine daily. Academic achievement was assessed using 1-min tests in reading and mathematics; classroom behaviour at the individual and whole class level was observed by teachers; and physical activity levels were assessed using accelerometers. Multilevel mixed effects linear regression models were conducted using intention to treat (ITT) and per protocol (PP) analyses. Results Significant intervention effects were found for classroom behaviour at the individual level (ITT B = 16.17; 95% CI: 6.58, 25.76); effects were stronger for boys (B = 21.42; 95% CI: 10.34, 32.49) than girls (B = 12.23; 95% CI: 1.52, 22.92). No effect was found for classroom behaviour at the whole class level, reading, math or physical activity. PP findings were similar. Conclusions Implementing active breaks during class time may improve classroom behaviour, particularly for boys. There was no evidence to suggest that implementing active breaks had any adverse effect on academic achievement or classroom behaviour, which may encourage classroom teachers to incorporate active breaks into their routine.

CHAPTER 1: HOW AUSTRALIA IMPROVED HEALTH EQUITY THROUGH ACTION ON THE SOCIAL DETERMINANTS OF HEALTH: Do not think that the social determinants of health equity are old hat. In reality, Australia is very far away from addressing the societal level drivers of health inequity. There is little progressive policy that touches on the conditions of daily life that matter for health, and action to redress inequities in power, money and resources is almost non-existent. In this chapter we ask you to pause this reality and come on a fantastic journey where we envisage how COVID-19 was a great disruptor and accelerator of positive progressive action. We offer glimmers of what life could be like if there was committed and real policy action on the social determinants of health equity. It is vital that the health sector assists in convening the multisectoral stakeholders necessary to turn this fantasy into reality. CHAPTER 2: ABORIGINAL AND TORRES STRAIT ISLANDER CONNECTION TO CULTURE: BUILDING STRONGER INDIVIDUAL AND COLLECTIVE WELLBEING: Aboriginal and Torres Strait Islander peoples have long maintained that culture (ie, practising, maintaining and reclaiming it) is vital to good health and wellbeing. However, this knowledge and understanding has been dismissed or described as anecdotal or intangible by Western research methods and science. As a result, Aboriginal and Torres Strait Islander culture is a poorly acknowledged determinant of health and wellbeing, despite its significant role in shaping individuals, communities and societies. By extension, the cultural determinants of health have been poorly defined until recently. However, an increasing amount of scientific evidence supports what Aboriginal and Torres Strait Islander people have always said - that strong culture plays a significant and positive role in improved health and wellbeing. Owing to known gaps in knowledge, we aim to define the cultural determinants of health and describe their relationship with the social determinants of health, to provide a full understanding of Aboriginal and Torres Strait Islander wellbeing. We provide examples of evidence on cultural determinants of health and links to improved Aboriginal and Torres Strait Islander health and wellbeing. We also discuss future research directions that will enable a deeper understanding of the cultural determinants of health for Aboriginal and Torres Strait Islander people. CHAPTER 3: PHYSICAL DETERMINANTS OF HEALTH: HEALTHY, LIVEABLE AND SUSTAINABLE COMMUNITIES: Good city planning is essential for protecting and improving human and planetary health. Until recently, however, collaboration between city planners and the public health sector has languished. We review the evidence on the health benefits of good city planning and propose an agenda for public health advocacy relating to health-promoting city planning for all by 2030. Over the next 10 years, there is an urgent need for public health leaders to collaborate with city planners - to advocate for evidence-informed policy, and to evaluate the health effects of city planning efforts. Importantly, we need integrated planning across and between all levels of government and sectors, to create healthy, liveable and sustainable cities for all. CHAPTER 4: HEALTH PROMOTION IN THE ANTHROPOCENE: THE ECOLOGICAL DETERMINANTS OF HEALTH: Human health is inextricably linked to the health of the natural environment. In this chapter, we focus on ecological determinants of health, including the urgent and critical threats to the natural environment, and opportunities for health promotion arising from the human health co-benefits of actions to protect the health of the planet. We characterise ecological determinants in the Anthropocene and provide a sobering snapshot of planetary health science, particularly the momentous climate change health impacts in Australia. We highlight Australia's position as a major fossil fuel producer and exporter, and a country lacking cohesive and timely emissions reduction policy. We offer a roadmap for action, with four priority directions, and point to a scaffold of guiding approaches - planetary health, Indigenous people's knowledge systems, ecological economics, health co-benefits and climate-resilient development. Our situation requires a paradigm shift, and this demands a recalibration of health promotion education, research and practice in Australia over the coming decade. CHAPTER 5: DISRUPTING THE COMMERCIAL DETERMINANTS OF HEALTH: Our vision for 2030 is an Australian economy that promotes optimal human and planetary health for current and future generations. To achieve this, current patterns of corporate practice and consumption of harmful commodities and services need to change. In this chapter, we suggest ways forward for Australia, focusing on pragmatic actions that can be taken now to redress the power imbalances between corporations and Australian governments and citizens. We begin by exploring how the terms of health policy making must change to protect it from conflicted commercial interests. We also examine how marketing unhealthy products and services can be more effectively regulated, and how healthier business practices can be incentivised. Finally, we make recommendations on how various public health stakeholders can hold corporations to account, to ensure that people come before profits in a healthy and prosperous future Australia. CHAPTER 6: DIGITAL DETERMINANTS OF HEALTH: THE DIGITAL TRANSFORMATION: We live in an age of rapid and exponential technological change. Extraordinary digital advancements and the fusion of technologies, such as artificial intelligence, robotics, the Internet of Things and quantum computing constitute what is often referred to as the digital revolution or the Fourth Industrial Revolution (Industry 4.0). Reflections on the future of public health and health promotion require thorough consideration of the role of digital technologies and the systems they influence. Just how the digital revolution will unfold is unknown, but it is clear that advancements and integrations of technologies will fundamentally influence our health and wellbeing in the future. The public health response must be proactive, involving many stakeholders, and thoughtfully considered to ensure equitable and ethical applications and use. CHAPTER 7: GOVERNANCE FOR HEALTH AND EQUITY: A VISION FOR OUR FUTURE: Coronavirus disease 2019 has caused many people and communities to take stock on Australia's direction in relation to health, community, jobs, environmental sustainability, income and wealth. A desire for change is in the air. This chapter imagines how changes in the way we govern our lives and what we value as a society could solve many of the issues Australia is facing - most pressingly, the climate crisis and growing economic and health inequities. We present an imagined future for 2030 where governance structures are designed to ensure transparent and fair behaviour from those in power and to increase the involvement of citizens in these decisions, including a constitutional voice for Indigenous peoples. We imagine that these changes were made by measuring social progress in new ways, ensuring taxation for public good, enshrining human rights (including to health) in legislation, and protecting and encouraging an independent media. Measures to overcome the climate crisis were adopted and democratic processes introduced in the provision of housing, education and community development.

Introduction This natural experiment examined the impact of the installation of outdoor fitness equipment and one multi-sports court in a park located in Melbourne, Australia on park visitation and park-based physical activity compared to a control park. Barriers and facilitators to use of this equipment among adult park visitors were also explored. Methods Park visitation and moderate-vigorous physical activity (MVPA) in the two parks were assessed before (T1, 2016) and after the intervention (T2, 2019) using observations of park visitors from children to older adults across four days (7.30am-5.00pm). The relative change in observed counts in visitors from T1-T2 in the intervention park compared to the control park was used to assess the effect of the park refurbishment. Intercept surveys regarding barriers and facilitators were conducted with adult park visitors. Results Over the three-year period, total visitor counts increased by 16% and the number of park visitors observed engaging in MVPA increased by 24% in the intervention park. However, there were no significant intervention effects on total visitor counts (IRR = 0.89, 95%CI: 0.62, 1.30) or MVPA (IRR = 0.80, 95%CI: 0.53, 1.19) relative to the control park. Examples of frequently mentioned facilitators to increase use of the sports court and fitness equipment included having someone to use the facilities with and instructional signage, and common barriers included poor weather and lack of time. Conclusions The impact of the park upgrade on visitation and MVPA was not significant. A better understanding of the broader appeal of outdoor fitness equipment and a multi-sports court among different segments of the population is needed.

Background Physical activity (PA) decreases and sedentary time (SED) increases across childhood, with both behaviours tracking. However, no studies have examined how accumulation patterns of PA and SED (i.e., prolonged bouts, frequency of breaks in sedentary time) change and track over time. The aim of this study was to investigate longitudinal changes in and tracking of total volume and accumulation patterns of SED, light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA) among boys and girls. Methods In 2008/09 (T1), children in HAPPY (3-5y; n = 758) in Melbourne, Australia wore ActiGraph GT1M accelerometers to objectively assess SED, LPA, MPA and VPA. This was repeated at age 6-8y (T2; n = 473) and 9-11y (T3; n = 478). Ten pattern variables were computed: bouts of ≥ 5-, ≥ 10-, ≥ 15- and ≥ 20-min for SED, ≥ 1- and ≥ 5-min for LPA, ≥ 1-min for MPA, ≥ 1- and ≥ 5-min for VPA, and breaks in SED (interruptions of > 25 counts 15 s− 1). Longitudinal mixed models examined changes from T1-3, controlling for T1 age. Generalized estimating equations assessed tracking over the three time points, controlling for T1 age and time between measurements. Analyses were stratified by sex. Results Total volume and bouts of SED and SED breaks increased, while total volume and bouts of LPA decreased for both sexes. There was a small decrease in total volume of MPA for girls, but time spent in ≥ 1-min bouts increased for both sexes. Total volume of VPA increased for both sexes, with time spent in ≥ 1-min bouts increasing for boys only. All volume and pattern variables tracked moderately for boys, except for all SED bouts ≥ 15-min, LPA bouts ≥ 5-min and MPA bouts ≥ 1-min (which tracked weakly). For girls, total SED and SED bouts ≥ 1-min tracked strongly, total volume of LPA, MPA and VPA, ≥ 5- and ≥ 10-min SED bouts, and ≥ 1-min LPA and MPA bouts tracked moderately, and SED breaks, all SED bouts ≥ 15 min, LPA bouts ≥ 5 min and all VPA bouts tracked weakly. Conclusions Patterns of SED and PA change from early to late childhood; with the exception of SED breaks and VPA, changes were detrimental. Total volumes and short bouts tended to track more strongly than longer bouts. Interventions to prevent declines in PA and increases in SED are important from early in life.

Trajectories of physical activity and sedentary time (SED) may differ between subgroups of youth. The aim of this study was to identify group-based dual trajectories of physical activity and SED and explore individual, social, and environmental correlates of these trajectories. Longitudinal data (three time points, baseline 2011-2012) of Spanish youth (n = 1597, mean age = 11.94 ± 2.52, 50.9% boys) were used. Moderate-to-vigorous physical activity (MVPA) and SED were assessed objectively at each time point, and 21 potential correlates were self-reported at baseline. Parallel process growth mixture models identified shared categorical latent groups, adjusting for school and age. Multinomial logistic regression models identified baseline correlates of a given trajectory. Four shared categorical latent groups were identified: (1) stable MVPA and decreasing SED (4%); (2) stable MVPA and increasing SED (3%); (3) consistently higher MVPA (18%); and (4) stable low MVPA and slight increase in SED (75%). Multinomial logistic regression models with group 3 as reference found: negative affect (RRR = 0.90, 95% CI 0.84-0.97), parental screen-time rules (RRR = 1.15, 95% CI 1.00-1.33), and household media equipment (RRR = 1.17, 95% CI 1.05-1.30) predicted likelihood of group 1 membership; cons of reducing SED (RRR = 2.70, 95% CI 1.77-4.10) predicted likelihood of group 2 membership; and co-participation in physical activity with friends (RRR = 0.80, 95% CI 0.69-0.94), fathers' modeling of TV viewing (RRR = 1.22, 95% CI 1.02-1.47), and household media equipment (RRR = 1.16, 95% CI 1.02-1.31) predicted likelihood of group 4 membership. Results suggest that strategies to improve MVPA and SED behaviors among youth may need to be multifaceted, targeting all levels of influence.

BACKGROUND Government responses to managing the COVID-19 pandemic may have impacted the way individuals were able to engage in physical activity. Digital platforms are a promising way to support physical activity levels and may have provided an alternative for people to maintain their activity while at home. OBJECTIVE This study aimed to examine associations between the use of digital platforms and adherence to the physical activity guidelines among Australian adults and adolescents during the COVID-19 stay-at-home restrictions in April and May 2020. METHODS A national online survey was distributed in May 2020. Participants included 1188 adults (mean age 37.4 years, SD 15.1; 980/1188, 82.5% female) and 963 adolescents (mean age 16.2 years, SD 1.2; 685/963, 71.1% female). Participants reported demographic characteristics, use of digital platforms for physical activity over the previous month, and adherence to moderate- to vigorous-intensity physical activity (MVPA) and muscle-strengthening exercise (MSE) guidelines. Multilevel logistic regression models examined differences in guideline adherence between those who used digital platforms (ie, users) to support their physical activity compared to those who did not (ie, nonusers). RESULTS Digital platforms include streaming services for exercise (eg, YouTube, Instagram, and Facebook); subscriber fitness programs, via an app or online (eg, Centr and MyFitnessPal); facilitated online live or recorded classes, via platforms such as Zoom (eg, dance, sport training, and fitness class); sport- or activity-specific apps designed by sporting organizations for participants to keep up their skills (eg, TeamBuildr); active electronic games (eg, Xbox Kinect); and/or online or digital training or racing platforms (eg, Zwift, FullGaz, and Rouvy). Overall, 39.5% (469/1188) of adults and 26.5% (255/963) of adolescents reported using digital platforms for physical activity. Among adults, MVPA (odds ratio [OR] 2.0, 95% CI 1.5-2.7), MSE (OR 3.3, 95% CI 2.5-4.5), and combined (OR 2.7, 95% CI 2.0-3.8) guideline adherence were higher among digital platform users relative to nonusers. Adolescents’ MVPA (OR 2.4, 95% CI 1.3-4.3), MSE (OR 3.1, 95% CI 2.1-4.4), and combined (OR 4.3, 95% CI 2.1-9.0) guideline adherence were also higher among users of digital platforms relative to nonusers. CONCLUSIONS Digital platform users were more likely than nonusers to meet MVPA and MSE guidelines during the COVID-19 stay-at-home restrictions in April and May 2020. Digital platforms may play a critical role in helping to support physical activity engagement when access to facilities or opportunities for physical activity outside the home are restricted.

Parks are places where children can interact with others and engage in physical activity in a natural setting. Park visits can enhance children&rsquo, s social, mental, and physical health. It is therefore important to better understand how parks can be designed to ensure optimal use by children. This qualitative study explored children&rsquo, s perceptions of park features that may influence their park visits, park-based physical activity, and social interaction. Qualitative walk-along interviews were completed with 30 children (mean age 9.7 years (SD 1.3), female n = 16) in nine parks located in varying socioeconomic areas of Melbourne, Australia. As they walked through the park, children shared thoughts regarding characteristics that may influence their visitation, park-based physical activity, and social interactions. Features that would encourage visitation included: challenging and interesting play equipment, a pond and water play area, trees/greenery and shade, and full-sized basketball courts. Features most valued for physical activity included: sports courts, ovals, and equipment, open space, trees to climb, and nature/rocks. Features most valued for social interaction included: a large size, playgrounds, and picnic areas. Children offer unique and important views. Park designers should consider inclusion of these features, when (re)developing parks to support children to lead healthy and active lives.

Background The consequences for youth cardiometabolic risk might depend on whether sedentary time and physical activity are accumulated sporadically (in shorter bouts) or in a sustained pattern (in longer bouts). This study aimed to: 1) describe daily time-use compositions of youth, including time spent in shorter and longer bouts of sedentary behaviour and physical activity; and 2) examine associations between time-use compositions with cardiometabolic biomarkers.Methods Accelerometer and cardiometabolic biomarker data (adiposity, blood pressure, lipids) from 7–13 year olds (mean ± SD: 10.4 ± 1.7) from two Australian studies were pooled (complete cases adiposity n = 772). A time-use composition of nine components was formed using compositional data analysis: time in shorter and longer bouts of sedentary behaviour, light-, moderate- and vigorous-intensity physical activity, and “other time” (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as Results Confounder-adjusted models showed that the overall time-use composition was associated with zBMI, waist circumference, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and a combined cardiometabolic risk score. Specifically, more time in longer relative to shorter bouts of light-intensity physical activity was associated with greater zBMI (β = 1.79, SE = 0.70, p = 0.010) and waist circumference (β = 17.28, SE = 4.87, p Conclusions Accumulating physical activity in frequent short bursts may be beneficial for adiposity compared to engaging in the same amount of these intensities in longer bouts.Trial registration: 'Lifestyle Of Our Kids’ (ACTRN12615000066583 [23/01/2015]) and ‘Transform-Us!’ (ACTRN12609000715279 [19/08/2009], ISRCTN83725066 [30/06/2010]).

Background The design of parks is critical to ensure they are appealing, meet the needs of the community and optimise opportunities for physical activity, relaxation, exposure to nature and social interaction. There is currently a lack of understanding on how research evidence is informing park design and how to reduce the many challenges associated with research-practice-policy translation. Understanding how organisations use evidence for decision-making regarding park design is critical for reducing the research-practice-policy gap and ensuring evidence based strategies inform park design to support healthy active living. This study explored stakeholder perceptions regarding factors that influence the use of research evidence to inform park planning and design, and potential strategies to enhance effective translation of research evidence for optimal park design into policy and practice. Methods One-on-one in-depth interviews were conducted with 23 stakeholders within the park design, planning and management sector. Participants shared experiences regarding: influences on park development and design; current park development policies; ways to facilitate use of evidence; and priorities for future research. Interviews were recorded and transcribed verbatim and content analysis performed using NVivo 12. Results Research evidence is used and considered important for park planning; however, several barriers were highlighted: time and cost constraints; difficulties accessing research; and limited research relevant to specific needs. Developing partnerships between researchers and park developers and providing evidence in a more accessible format such as short summaries/reports, infographics, presentations, research updates and dedicated research databases emerged as key enablers. The main research gaps identified included research into park features to encourage visitation and cost-benefit analyses studies. Conclusions This research is a first step to better understand strategies to promote more effective uptake and use of evidence to inform park planning. Researchers must develop multi-sectoral collaborations and generate policy-relevant research in a readily accessible, timely and user-friendly format to ensure evidence is used to enhance park design and ultimately public health.

The physical environment encompasses natural and built environments. The natural environment refers to the geography and climate of a particular area, such as bodies of water, weather, natural landscapes and topography. This chapter focuses on the links between physical activity and the built environment around the home, commonly known as the neighborhood built environment. The physical environment is an important part of socio-ecological perspectives often used as a theoretical basis to understand and encourage the adoption of a physically active lifestyle. Research on the neighborhood physical environment and physical activity among children and youth has evolved rapidly over the past few decades. A seminal study published in 1990 on children’s independent mobility on school journeys was among the earliest work to explore the role of the environment in shaping children’s physical activity. Audit techniques are typically used to objectively and systematically measure or record features of the physical environment, including features related to community design, streetscapes or routes.

Background: Longitudinal changes in child and adolescent active school transport (AST), and the mediating role of different intensities of daily physical activity (PA) levels in relation to AST and physical fitness and adiposity indicators is unclear. This study aimed to: 1) describe longitudinal changes in AST, light PA (LPA), moderate- to vigorous-intensity PA (MVPA), physical fitness and adiposity indicators over three time-points; and 2) investigate the mediating role of LPA and MVPA levels on associations between AST and physical fitness and adiposity indicators over three time-points among children and adolescents. Methods: This longitudinal study comprised 1646 Spanish children and adolescents (48.8% girls, mean age 12.5 years ±2.5) at baseline, recruited from schools in Cádiz and Madrid. Mode of commuting to school was self-reported at baseline (T0, 2011-12), 1-year (T1) and 2-year follow-up (T2). PA was assessed using accelerometers. Handgrip strength, standing long jump and cardiorespiratory fitness (CRF) assessed physical fitness. Height, weight, body mass index, waist circumference, and triceps and subscapular skinfold thickness were measured. Multilevel linear regression analyses assessed changes in AST, PA levels, physical fitness and adiposity indicators over three time-points (T0-T1-T2). Additionally, longitudinal path analysis (n = 453; mean age [years] 12.6 ± 2.4) was used to test the mediating effects of LPA and MVPA levels on the association between AST and physical fitness and adiposity indicators. Results: Multilevel analyses observed decreases in LPA between T0-T1 (β = - 11.27; p < 0.001) and T0-T2 (β = - 16.27; p < 0.001) and decreases in MVPA between T0-T2 (β = - 4.51; p = 0.011). Moreover, changes over time showed increases in handgrip between T0-T1 (β = 0.78; p = 0.028) and T0-T2 (β = 0.81; p = 0.046). Path analyses showed that AST was directly positively associated with MVPA at T1 (all, β ≈ 0.33; p < 0.001). MVPA at T1 mediated associations between AST and CRF at T2 (β = 0.20; p = 0.040), but not the other outcomes. LPA did not mediate any associations. Conclusions: Results from longitudinal path analysis suggest that participation in more AST may help attenuate declines in MVPA that typically occur with age and improve CRF. Therefore, we encourage health authorities to promote AST, as a way to increase MVPA levels and CRF among youth., This study was supported by the DEP 2010–21662-C04–00 (DEP 2010–21662- C04–01: DEP 2010–21662-C04–02: DEP 2010–21662-C04–03: DEP 2010– 21662-C04–04) grant from the National Plan for Research, Development and Innovation (R + D + i) MICINN. DCM received a scholarship Jose Castillejo scholarship (CAS18/00262) for a brief stay in the Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Australia. JV is supported by an Australian National Heart Foundation Future Leader Fellowship (ID 101928).

Parks are a key setting that can support the health and well-being of older adults through facilitating physical activity and social interaction. However, park use among older adults is low, therefore it is important to better understand which park features are most likely to encourage them to visit and be active and social in parks. This two-phased study examined the relative importance of park features for encouraging park visitation, park-based physical activity, and social interaction among older adults (65+ years). In Phase 1, participants (n = 258; 71.9 + 5.42 years, 52% male) completed an online survey where they rated a selection of images of 42 park features according to the importance of these features for encouraging their park visitation, physical activity and social interaction. The most highly-rated features were included in a new survey for Phase 2, where a new sample (n = 243; 71.5 + 4.91 years, 51% male) completed Adaptive Choice-Based Conjoint analyses tasks to identify relative importance scores of each park feature for all three outcomes. Overall, the two most important features for park visitation were shady trees (conjoint analysis relative importance score 19.6%; 95%CI = 18.3, 20.9) and a peaceful and relaxed setting (19.6%, 95%CI = 18.1, 21.1). The most important feature for physical activity was walking paths (19.6%; 95%CI = 17.1, 22.1) and for social interaction was a peaceful and relaxed setting (14.7%; 95%CI = 12.6, 16.9). Park designers should prioritise shady trees, a peaceful and relaxed setting, and walking paths to ensure that parks meet older adults’ needs and encourage physical activity and social interaction during their park visits.

This study examined cross-sectional and prospective associations between typologies of neighbourhood food environment and dietary patterns among 10-12 year-old children. Baseline data were collected in 2003 and follow-up data in 2006 from children in Melbourne or Geelong. Parents completed a food frequency questionnaire at both time points. 'Healthful' and 'energy-dense' dietary pattern scores were computed. A Geographic Information System was used to determine the presence or absence of food outlets (cafés/restaurant; fast food; supermarkets/grocery stores; convenience store; greengrocer; and butcher, seafood or poultry retailer) within an 800 m road network buffer of home. Three typologies were identified: 1-variety of food outlets, including those selling core/fresh foods (n = 96); 2-café/restaurant and convenience (n = 160); 3-few types of outlets (n = 208). Latent class analysis was used to identify underlying unobservable typologies of neighbourhood food outlet availability. Linear mixed models were fitted to determine cross-sectional (n = 439) and longitudinal (n = 173) associations between the three identified neighbourhood typologies and each (log-transformed) dietary pattern, accounting for clustering within families and schools. There was little evidence of cross-sectional associations. The longitudinal analyses showed that compared to those with a variety of food outlets, those with few types had 25% lower scores for the healthful dietary pattern (p 0.05) three years later. For optimal dietary patterns, availability of a variety of food outlets close to home, particularly those where core/fresh foods are available, may be important.

ObjectiveThe purpose of the current study was to examine associations of individual and aggregated screen-based behaviours, and total sitting time, with healthy and unhealthy dietary intakes among adolescents.DesignCross-sectional study of adolescents. Participants self-reported durations of television viewing, computer use, playing electronic games (e-games), total sitting time, daily servings of fruits and vegetables, and frequency of consumption of sugar-sweetened beverages (SSB), diet beverages, fast foods and discretionary snacks. Logistic regression models were conducted to identify associations of screen-based behaviours, total screen time and total sitting time with dietary intakes.SettingVictoria, Australia.SubjectsAdolescents (n 939) in School Year 11 (mean age 16·8 years).ResultsThe results showed that watching television (≥2 h/d) was positively associated with consuming SSB and diet beverages each week and consuming discretionary snacks at least once daily, whereas computer use (≥2 h/d) was inversely associated with daily fruit and vegetable intake and positively associated with weekly fast-food consumption. Playing e-games (any) was inversely associated with daily vegetable intake and positively associated with weekly SSB consumption. Total screen (≥2 h/d) and sitting (h/d) times were inversely associated with daily fruit and vegetable consumption, with total screen time also positively associated with daily discretionary snack consumption and weekly consumption of SSB and fast foods.ConclusionsIndividual and aggregated screen-based behaviours, as well as total sitting time, are associated with a number of indicators of healthy and unhealthy dietary intake. Future research should explore whether reducing recreational screen time improves adolescents’ diets.

This study aimed to understand differences in leisure, educational/work and social screen time behaviours experienced by parents and children due to COVID-19 lockdown restrictions, which may inform behaviour change strategies and policy in the transition to a COVID-normal life. Participants in the “Our Life at Home” study (n = 218 parents from Australia, 43.4 ± 6.8 years, 88% female) completed a cross-sectional online survey in April/May 2020. Parents recalled their own and their child (8.7 ± 2.0 years, 42% female) or adolescents (15.0 ± 1.5 years, 50% female) participation in nine screen time behaviours in the past month (during lockdown) and retrospectively for February 2020 (pre-lockdown), providing data on 436 individuals. Screen time behaviours included leisure (computer/laptop and tablet/smartphone for leisure, TV/videos/DVDs and game consoles), education/work (computer/laptop and tablet/smartphone for work/education), and social screen time (computer/tablet/smartphone for social communication with friends, family and work (parents only)). Wilcoxon signed-rank tests and effect sizes (r) compared the time spent in each behaviour pre-lockdown and during lockdown. Large differences were observed in social (parents: r = 0.41–0.57, children: r = 0.55–0.65, adolescents: r = 0.28–0.43) and education (children: r = 0.50–0.65 and adolescents: r = 0.25–0.37) behaviours. There were small or no differences in leisure time screen use. COVID-19 lockdown restrictions have impacted parent’s and children’s screen time, and future research and policy should consider strategies to support families to manage screen time.

Background Recommendations to define eating occasions (EO) currently exist for research in adults, but not for children or adolescents. We examined how varying EO definitions affect the characterization of eating patterns in children and adolescents. Methods Cross-sectional dietary data collected using a 24-h recall data during the 2011–12 Australian National Nutrition and Physical Activity Survey (1364 boys and 1337 girls aged 2–18 years) were analyzed. Eight definitions were applied: participant-identified, time-of-day, and 6 neutral definitions (EO separated by 15- or 60-min and/or an additional energy criterion of 21 or 210 kJ). Frequency of and total energy intake from meals, snacks, and all EO were estimated. F tests stratified by gender and age-group, were used to assess differences between definitions. Agreement between definitions of meal and snack frequencies was assessed using intraclass correlation coefficients (ICC). Linear regression was used to estimate the proportion of variance in total energy intake (kJ) and BMI z-score predicted by each definition. Results Mean frequencies of meals and snacks differed between the participant-identified and time-of-day definitions, in boys and girls and for all age groups (P P 2 range = 8.1–34.8). Definitions that delineated meals and snacks better predicted variance in BMI z-score, when compared to the neutral definitions. Conclusions How eating patterns are characterized vary depending on the EO definitions employed, particularly in young children. Variance in total energy intake was best predicted by a variation of the neutral definition whereas definitions that delineated meals and snacks performed better in relation to predicting BMI variance. Further international research that compares EO definitions in children will help inform a standard approach.

This study examined how children's physical activity levels during recess and lunchtime and the contribution of recess and lunchtime to daily physical activity differed across seasons. Three hundred and twenty-six children aged 8-11years from Australia participated. Physical activity was measured every 15-seconds using hip-mounted ActiGraph accelerometers for 7 consecutive days during the winter (n=246), spring (n=211), summer (n=161) and autumn terms (n=139). Data were collected 2012-2013. Time spent in light- (LPA) moderate- (MPA), vigorous- (VPA), and moderate- to vigorous-intensity physical activity (MVPA) during recess and lunchtime were calculated. Longitudinal data were analysed using multilevel analyses and adjusted for potential confounders. The results showed that compared to winter, children engaged in significantly less MVPA and VPA in spring and summer during lunchtime (p

Refereed/Peer-reviewed Little is known about whether physical activity compensation occurs and, if so, what are potential moderators of such responses. This study examined whether children's physical activity, sedentary time and energy expenditure on one day was associated with these behaviours the following day, and what factors may moderate observed associations. One hundred and twenty-seven children (8-11 years) wore an ActiGraph accelerometer for eight days. Time spent in sedentary time and physical activity was obtained. Daily energy expenditure was also assessed using a SenseWear Armband (n=98). Moderators examined were sex, age, BMI, fitness, and fundamental movement skills (FMS). Multilevel analyses were conducted using generalized mixed models. On any given day, every additional 10 minutes spent in moderate-to-vigorous physical activity (MVPA) was associated with 9.3 minutes less MVPA the following day. Every additional 10kcal expended on one day was associated with 2.9 fewer kcal expended the following day. Additional time spent sedentary on any given day was associated with less light physical activity the following day in children with lower FMS. The results are largely consistent with the compensation hypothesis, with children appearing to compensate their activity between days. Strategies to minimise potential compensatory changes may be needed for children overall rather than for specific population sub-groups. usc

Parks provide opportunities for people of all ages to engage in physical activity, connect socially with family and friends, and have contact with nature. Despite these benefits, park visitation among adolescents is particularly low; however, little is known about what attributes would attract adolescents to visit parks. This study examined the relative importance of park features that might influence their decision to visit a park. Adolescents were recruited in 2014–5 from four secondary schools located in Melbourne, Australia. Participants completed an adaptive choice based conjoint (ACBC) task during one school class-lesson. This methodology makes it possible to identify the relative importance of individual park features. Ten park attributes were included in the survey and part-worth utility and importance scores were estimated for each attribute with Hierarchical Bayes analyses using Sawtooth Software. Participants (n = 92) had a mean age of 14.7 years (SD = 1.0) and 57% were female. Importance scores showed that playground slides (particularly long steep slides) were the most important attribute for park visitation (16.1%; 95% CI = 15.0, 17.2), followed by an absence of rubbish/graffiti (13.0%; 95% CI = 11.2, 14.8), and the presence of swings (12.4%; 95% CI = 11.4, 13.3), walking/cycling paths (12.1%; 95% CI = 11.0, 13.2) and BMX tracks/skate bowls (10.6%; 95% CI = 9.3, 11.9). These findings can assist those involved in designing parks to identify attributes that should be prioritised to ensure visitation by adolescents is maximised. The novel methodology utilised may be transferable to other studies of the built environment among other population groups.

Physical inactivity and overweight and obesity are more prevalent among rural than urban populations. This study aimed to review published evidence of the effectiveness of interventions to increase physical activity (PA) and/or decrease sedentary behaviour (SB) among rural adults and to identify factors associated with effectiveness. Seven electronic databases were searched for controlled trials of a PA or SB intervention. Meta-analysis was conducted using random effects models and meta-regression. Thirteen studies were included in the qualitative synthesis (n = 4,848 participants) and 12 in the meta-analysis (n = 4,820). All studies were interventions to increase PA. Overall, there was no effect on PA (standardized mean difference [SMD] 0.11; 95% confidence interval [CI] −0.04, 0.25) or SB (SMD 0.07; 95% CI −0.33, 0.20). In PA subgroup analyses, studies employing objective outcome measures demonstrated effects in favour of the intervention (SMD 0.65, 95% CI 0.30, 1.00), while those using self-reported measures did not (SMD 0.00; 95% CI −0.11, 0.10). This review highlights significant gaps in our understanding of how best to promote PA and reduce SB among rural adults. Future studies should use objective measures of PA as study outcomes. The absence of interventions to decrease SB is of concern, with immediate action required to address this large knowledge gap.

Background:Little is known about the associations of preschoolers’ health behaviors with their later psychosocial wellbeing. This study investigates the association of 3- to 5-year-old children’s physical activity and electronic media use with their later social-emotional skills (6-8 years).Methods:Data were collected in 2008–2009 and 2011–2012 for the Healthy Active Preschool and Primary Years (HAPPY) Study in metropolitan Melbourne. Participants were a random subsample (n = 108) of the 567 children at follow-up. Physical activity was objectively measured using ActiGraph GT1M accelerometers; electronic media use (television viewing, sedentary electronic games and active electronic games) was parent proxy-reported. Social and emotional skills were child-reported using the Bar-On Emotional Quotient Inventory—Youth Version. Regression analyses controlled for sex, clustering by center of recruitment, and accelerometer wear time (for physical activity analyses).Results:Sedentary electronic games were positively associated with intrapersonal and stress management skills and total emotional quotient. Computer/internet use was inversely associated with interpersonal, and positively associated with stress management, skills.Conclusions:Findings suggest that physical activity is not associated with children’s psychosocial health while some types of electronic media use are. Future research should investigate the contexts in which preschoolers participate in these behaviors and potential causal mechanisms of associations.

Background: Some evidence suggests that higher energy intake (EI) later in the day is associated with poor diet quality and obesity. However, EI at one eating occasion (EO) is also dependent on EI at surrounding EOs. Studies that examine the distribution of EOs across the day are rare.Objective: The aim of this study was to examine associations between temporal eating patterns, nutrient intakes, diet quality, and measures of adiposity in a representative sample of Australian adults.Design: Dietary data from two 24-h recalls collected during the cross-sectional 2011-2012 Australian National Nutrition and Physical Activity Survey were analyzed (n = 4544 adults, aged ≥19 y). Temporal eating patterns, based on the distribution of EOs across the day, were determined by using latent class analysis. Diet quality estimated adherence to healthy eating recommendations and was assessed by using the 2013 Dietary Guidelines Index (DGI). Multivariate regression models assessed associations between temporal eating patterns, nutrient intakes, diet quality, and adiposity (body mass index, waist circumference, weight status, and central weight status). Models were adjusted for potential confounders and energy misreporting.Results: Three patterns, labeled "conventional," "later lunch," and "grazing," were identified. Compared with a "conventional" or "later lunch" pattern, men and women with a "grazing" pattern had lower DGI scores and higher intakes of discretionary (noncore) foods (P < 0.05). Among women, the "grazing" pattern was associated with overweight or obesity (OR: 1.57; 95% CI: 1.15, 2.13) and central overweight or obesity (OR: 1.73; 95% CI: 1.19, 2.50). These associations were attenuated after the exclusion of energy misreporters and adjustment for total EI.Conclusions: This study found that a "grazing" temporal eating pattern was modestly but significantly associated with poorer diet quality and adiposity among women, after adjustment for covariates and energy misreporting. Future research should consider the impact of energy misreporting on the relation between temporal eating patterns and adiposity. This secondary analysis was registered at anzctr.org.au as ACTRN12617001029381.

This study examined two year changes in children's active transport and independent mobility and prospective associations between individual, social and physical environmental predictors of interest and these behaviors two years later. Overall, 43.5% of children (12.0 ± 2.1 years) used active transport on the school journey at T1 and at T2 (p=0.77), and 35.3% engaged in independent mobility on the school journey at T1 and 29.6% at T2 (p=0.07). Enjoyment, parental safety concerns, and proximity to walking tracks were associated with independent mobility on the school journey. Road safety and social norms were associated with active transport and independent mobility to local destinations. These factors provide potential targets for interventions.

Refereed/Peer-reviewed The directionality of the relationship between children's physical activity and sleep is unclear. This study examined the temporal and bidirectional associations between objectively measured physical activity, energy expenditure, and sleep in primary school-aged children. A subgroup of children (n = 65, aged 8-11 years) from the Fitness, Activity and Skills Testing Study conducted in Melbourne, Australia, had their sleep and physical activity assessed using the SenseWear Pro Armband for 8 consecutive days. Outcome measures included time spent in light-intensity physical activiy (LPA), moderate-to vigorousintensity physical activity (MVPA), activity energy expenditure (AEE), time in bed, total sleep time, and sleep efficiency. Multilevel analyses were conducted using generalized linear latent mixed models to determine whether physical activity on 1 day was associated with sleep outcomes that night, and whether sleep during 1 night was associated with physical activity the following day. No significant associations were observed between time in bed, total sleep time, and sleep efficiency with LPA, MVPA, and AEE in either direction. This study found no temporal or bidirectional associations between objectively measured physical activity, AEE, and sleep. Future research is needed to understand other sleep dimensions that may impact on or be influenced by physical activity to provide potential intervention targets to improve these outcomes. usc

Objectives: To identify the number of hours and days or nights of monitoring required to reliably estimate energy expenditure (EE), steps, waking sedentary time, light- (LPA), moderate- (MPA), vigorous- (VPA), moderate- to vigorous-intensity physical activity (MVPA), time in bed and total sleep time using the SenseWear Armband.Design: Cross-sectional study.Methods: One hundred and two children (50% boys) aged 8-11 years from six schools wore a SenseWear Armband (BodyMedia Inc, USA) for eight consecutive days (seven consecutive nights). Hourly increments of valid day wear time criteria were examined (days/week; 8h/day-14h/day). Intra-class correlation coefficients estimated the reliability for any individual day for each wear time criteria. The Spearman-Brown prophecy formula was used to determine the number of days/nights of monitoring needed to achieve reliability estimates of 0.7, 0.8 and 0.9.Results: Fewer monitoring days were needed as the valid day criteria became more stringent. For example, at least 12 h of wear time on at least 2 days was required to achieve a reliability of 0.7 for EE. In contrast, at least 8 h/day on 5 days resulted in reliable estimates (0.7) for MPA, VPA and MVPA. Between 6 and 7 nights of monitoring were required to reliably estimate children's time in bed and total sleep time, respectively.Conclusions: A 7-day monitoring protocol in primary school-aged children would provide acceptable reliability for the assessment of EE, waking sedentary time, LPA, MPA, VPA, MVPA, time in bed and total sleep time, as assessed by the SenseWear Armband. (C) 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved. usc Refereed/Peer-reviewed

Purpose This quasi-experimental study examined the impact of height-adjustable desks in combination with prompts to break up prolonged sitting time during class time and identified social and motivational factors associated with breaking up sitting time among adolescents. Teachers’ perceptions of strategies were also examined. Methods Over 17 weeks, 1 classroom in a government secondary school in Melbourne, Australia, was equipped with 27 height-adjustable desks and prompts (posters and desk stickers) to break up classroom sitting time. Teachers received professional development in the use of the desks and prompts. One group of adolescents (n = 55) had 2–5 lessons/week using the height-adjustable desks in an intervention classroom, and a comparison group matched by year level and subject (n = 50) was taught in traditional “seated” classrooms. Adolescents wore an activPAL monitor at baseline (T0), 4 weeks (T1), and 17 weeks (T2) and completed a survey at T0 and T2. Six teachers participated in interviews at T2. Effect sizes were calculated (d). Results Linear mixed models found that, compared to the traditional “seated” classrooms, the adolescents in the intervention classroom had significantly lower sitting time (T1: –9.7 min/lesson, d = –0.96; T2: –6.7 min/lesson, d = –0.70) and time spent in sitting bouts >15 min (T2: –11.2 min/lesson, d = –0.62), and had significantly higher standing time (T1: 7.3 min/lesson, d = 0.84; T2: 5.8 min/lesson, d = 0.91), number of breaks from sitting (T1: 1.3 breaks/lesson, d = 0.49; T2: 1.8 breaks/lesson, d = 0.67), and stepping time (T1: 2.5 min/lesson, d = 0.66). Intervention classroom adolescents reported greater habit strength (d = 0.58), self-efficacy for breaking up sitting time (d = 0.75), and indicated that having a teacher/classmate remind them to stand as helpful (d = 0.50). Conclusion This intervention shows promise for targeting sitting behaviors in the classroom and indicates that incorporating social and motivational strategies may further enhance outcomes.

Objective: Little is known about how the physical environment impacts physical activity behaviour among rural populations, who are typically less active and at higher risk of chronic disease than urban dwellers. The lack of individual-level instruments to assess the physical environment in rural areas limits advancement of this field. Among rural adults, this study aimed to evaluate (a) the test-retest reliability of a self-reported questionnaire of individual-level perceptions of the physical activity environment, and (b) the stability of a self-reported physical activity questionnaire. Design: Cross-sectional questionnaire repeated twice, 2 weeks apart. The questionnaire included 94 items relating to the perceived physical environment (representing nine summary scores), demographic characteristics and physical activity. Setting: Rural Australia. Participants: Rurally residing adults (≥18 years) across three Australian states.Main outcome measures: Test-retest reliability evaluated by weighted Kappa statistics(individual items) and intra-class correlations (summary scores). Results: A total of 292 participants (20% men) completed both questionnaires, on average22 days apart. Test-retest reliability of individual items ranged from weighted Kappa 0.37-0.85 (median: 0.59). Internal reliability for five summary scores was good to excellent (Cronbach's alpha: 0.81-0.97). Test-retest reliability was good to excellent for six summary scores (intra-class correlations: 0.67-0.77). Conclusions: The findings indicated good to excellent test-retest reliability for most items, particularly “fixed” constructs for this new questionnaire measuring the perceived physical environment in rural populations. This study represents an important step towards improving measurement of physical activity environments in rural populations, potentially leading to better tailored interventions to promote active and healthy living in rural areas. Refereed/Peer-reviewed

BackgroundGlobally, many children fail to meet the World Health Organization’s physical activity and sedentary behaviour guidelines. Schools are an ideal setting to intervene, yet despite many interventions in this setting, success when delivered under real-world conditions or at scale is limited. This systematic review aims to i) identify which implementation models are used in school-based physical activity effectiveness, dissemination, and/or implementation trials, and ii) identify factors associated with the adoption, implementation and sustainability of school-based physical activity interventions in real-world settings.MethodsThe review followed PRISMA guidelines and included a systematic search of seven databases from January 1st, 2000 to July 31st, 2018: MEDLINE, EMBASE, CINAHL, SPORTDiscus, PsycINFO, CENTRAL, and ERIC. A forward citation search of included studies using Google Scholar was performed on the 21st of January 2019 including articles published until the end of 2018. Study inclusion criteria: (i) a primary outcome to increase physical activity and/or decrease sedentary behaviour among school-aged children and/or adolescents; (ii) intervention delivery within school settings, (iii) use of implementation models to plan or interpret study results; and (iv) interventions delivered under real-world conditions. Exclusion criteria: (i) efficacy trials; (ii) studies applying or testing school-based physical activity policies, and; (iii) studies targeting special schools or pre-school and/or kindergarten aged children.Results27 papers comprising 17 unique interventions were included. Fourteen implementation models (e.g., RE-AIM, Rogers’ Diffusion of Innovations, Precede Proceed model), were applied across 27 papers. Implementation models were mostly used to interpret results (n = 9), for planning evaluation and interpreting results (n = 8), for planning evaluation (n = 6), for intervention design (n = 4), or for a combination of designing the intervention and interpreting results (n = 3). We identified 269 factors related to barriers (n = 93) and facilitators (n = 176) for the adoption (n = 7 studies), implementation (n = 14 studies) and sustainability (n = 7 studies) of interventions.ConclusionsImplementation model use was predominately centered on the interpretation of results and analyses, with few examples of use across all study phases as a planning tool and to understand results. This lack of implementation models applied may explain the limited success of interventions when delivered under real-world conditions or at scale.Trial registrationPROSPERO (CRD42018099836).