Traffic exposure, air pollution and children's physical activity at early childhood education and care

BACKGROUND

A significant number of children attend Early Childhood Education and Care (ECEC). ECEC is an important environment and behaviour setting for young children. Time spent outdoors is positively associated with children's physical activity levels, yet increased time spent physically active outdoors may expose young children to traffic-related air pollution, particularly in ECEC centres located in high traffic areas.

METHODS

This study was part of the Play Spaces and Environments for Children's Physical Activity (PLAYCE) study, Perth, Western Australia. Data from 22 ECEC centres and 478 children were collected. Continuous measures of indoor and outdoor fine particulate matter (PM_2.5) were conducted for 48-72 h in each ECEC. Children wore ActiGraph GT3X + accelerometers to measure their physical activity at ECEC. The total length of high traffic roads within a 300m road network service area buffer around each ECEC was used to identify high and low traffic centres.

RESULTS

Outdoor PM_2.5 concentrations peaked in the afternoon (1pm, 2pm and 6pm) at ECEC centres. Outdoor and indoor PM_2.5 concentrations were significantly higher for centres located in high compared with low traffic areas (both p < 0.05). There was no significant association between a centre being located in a high or low traffic area and the time preschoolers spent outdoors or their physical activity levels.

DISCUSSION

Time periods when air pollution concentrations in ECECs are highest correspond with times when preschoolers are likely to be physically active outdoors. Children's potential exposure to traffic-related air pollutants is occurring during a period of rapid lung development. Given there is no evidence of a safe level of exposure to PM_2.5 or a threshold below which no adverse health effects occur, careful planning should be a consideration to avoid locating ECEC centres in high traffic areas.

Study protocol for Healthy Conversations @ Playgroup: a multi-site cluster randomized controlled trial of an intervention to promote healthy lifestyle behaviours in young children attending community playgroups

BACKGROUND

Early childhood is a critical window for preventing obesity and chronic disease. Yet, 1 in 4 Australian children aged 5 years and under are affected by overweight or obesity; and significant proportions of children under 5 years fail to meet guidelines for diet quality, physical activity (PA), screen time, and sleep. Consequently, effective interventions to promote healthy lifestyle behaviors and prevent obesity during early childhood are needed. Community playgroups provide an opportunity for parents, carers, and children to meet in a safe and relaxed environment to play and share information. The structure, low cost and reach of playgroups provide a unique platform to engage parents in a scalable program to promote healthful lifestyle behaviors and prevent childhood obesity. However, the evidence base for the effectiveness of health promotion programs delivered in community playgroup settings is limited and lacking credible evidence from rigorously conducted randomized controlled trials.

METHODS

The Healthy Conversations @ Playgroup randomized controlled trial (RCT) aims to address the underlying behavioral risk factors for obesity by helping parents take effective steps to improve their child's dietary, PA, screen time, and sleep behaviors. The intervention program comprises 10 "healthy conversations" led by a trained peer facilitator, designed to increase parents' behavioral capability and self-efficacy to implement autonomy-supportive parenting practices. The program will be delivered biweekly during regularly scheduled playgroup sessions over 10-weeks. Effectiveness will be tested in a 2-arm cluster RCT involving 60 community playgroups in three states across Australia. After baseline assessments, participating playgroups will be randomly allocated to either intervention or wait-list control conditions. Primary outcomes (vegetable intake, discretionary foods, daily PA, screen time, sleep duration, and body mass index [BMI] z-score) will be assessed at baseline, immediately post-intervention (10-weeks; T2) and 6-months post-intervention (T3). Outcomes will be assessed for differential change at T2 and T3.

DISCUSSION

The Healthy Conversations @ Playgroup trial will rigorously evaluate a novel peer-led intervention program to promote healthful lifestyle behaviors and prevent obesity in children and families attending community playgroups. If effective, the program could be immediately scaled-up and delivered in community playgroups across Australia.

TRIAL REGISTRATION

Trial registered 22nd January 2021 with the Australian and New Zealand Clinical Trials Registry ( ACTRN12621000055808 ).

Fundamental movement skill proficiency and objectively measured physical activity in children with bronchiectasis: a cross-sectional study

Background

Bronchiectasis is a major contributor to respiratory morbidity and healthcare utilization in children. Children with bronchiectasis exhibit low levels of physical activity (PA) and poor fundamental movement skills (FMS) may be a contributing factor. However, there are no data on FMS’s in this population. The current study assessed FMS proficiency in children with bronchiectasis and examined associations with objectively measured PA.

Methods

Forty-six children with bronchiectasis (mean age 7.5 ± 2.6 year, 63% Male) were recruited from the Queensland Children’s Hospital, Brisbane. PA was measured using the ActiGraph GT3X + accelerometer. Raw accelerometer data were processed into daily time spent in sedentary activities, light-intensity activities and games, walking, running, and moderate-to-vigorous activities and games using a random forest (RF) PA classification algorithm specifically developed for children. Daily MVPA was calculated by summing time spent in walking, running, and moderate-to-vigorous activities and games. FMS were assessed using the Test of Gross Motor Development 2nd Edition (TGMD-2).

Results

Fewer than 5% of children demonstrated mastery in the run, gallop, hop, and leap; while fewer than 10% demonstrated mastery for the two-handed strike, overarm throw, and underarm throw. Only eight of the 46 children (17.4%) achieved their age equivalency for locomotor skills, while just four (8.7%) achieved their age equivalency for object control skills. One-way ANCOVA revealed that children achieving their age equivalency for FMS had significantly higher levels of MVPA than children not achieving their age equivalency (51.7 vs 36.7 min/day). When examined by the five activity classes predicted by the RF algorithm, children achieving their age equivalency exhibited significantly greater participation moderate-to-vigorous intensity activities and games (22.1 vs 10.7 min/day). No significant differences were observed for sedentary activities, light-intensity activities and games, walking, and running.

Conclusion

Children with bronchiectasis exhibit significant delays in their FMS development. However, those who meet their age equivalency for FMS proficiency participate in significantly more daily MVPA than children who do not meet their age-equivalency. Therapeutic exercise programs designed to improve FMS proficiency are thus likely to be beneficial in this population.

Measurement of screen time among young children aged 0-6 years: A systematic review

The impact of screen-based devices on children's health and development cannot be properly understood without valid and reliable tools that measure screen time within the evolving digital landscape. This review aimed to summarize characteristics of measurement tools used to assess screen time in young children; evaluate reporting of psychometric properties; and examine time trends related to measurement and reporting of screen time. A systematic review of articles published in English across three databases from January 2009 to April 2020 was undertaken using PROSPERO protocol (registration: CRD42019132599) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included articles measured screen time as outcome, exposure, or confounder in children 0-6 years. The search identified 35,868 records, 1035 full-text articles were screened for eligibility, and 622 met inclusion criteria. Most measures (60%) consisted of one to three items and assessed duration of screen time on a usual day. Few measures assessed content (11%) or coviewing (7%). Only 40% of articles provided a citation for the measure, and only 69 (11%) reported psychometric properties-reliability n = 58, validity n = 19, reliability and validity n = 8. Between 2009 and 2019, the number of published articles increased from 28 to 71. From 2015, there was a notable increase in the proportion of articles published each year that assessed exposure to mobile devices in addition to television. The increasing number of published articles reflects increasing interest in screen time exposure among young children. Measures of screen time have generally evolved to reflect children's contemporary digital landscape; however, the psychometric properties of measurement tools are rarely reported. There is a need for improved measures and reporting to capture the complexity of children's screen time exposures.

Active Play Network Influences on Physical Activity Among Children Living in Texas Colonias

Physical activity (PA) is beneficial for child health; however, few children meet PA guidelines. Social relationships impact child PA behaviors; however, little is known about this effect in Mexican-heritage populations. This study aims to understand associations between self-reported play networks and PA among Mexican-heritage children. Mexican-heritage children from colonias along the Texas-Mexico border (n = 44; 54.5% girls; mean age = 9.89 years, SD = 0.97) reported information on up to 5 people they played with most often. Linear regression was used to analyze the relationship between composition of children's social network and minutes of moderate- to vigorous-intensity PA (MVPA) and sedentary minutes per day measured by accelerometers. Children who reported a higher percentage of friends as opposed to family members attained significantly more minutes of MVPA per day (β = .27, P = .04). Children who reported playing with individuals in their network more often (β = ‒.28, P = .03) were sedentary for fewer minutes per day. Increasing the connections between children in the neighborhood or community, as well as increasing a child's frequency of active play, may be promising approaches to increasing MVPA and decreasing sedentary behaviors among Mexican-heritage children.

Psychometric properties of instruments to measure parenting practices and children's movement behaviors in low-income families from Brazil

Background

Childhood obesity has increased remarkably in low and middle-income (LMIC) countries. Movement behaviors (physical activity, screen time, and sleep) are crucial in the development of overweight and obesity in young children. Yet, few studies have investigated the relationship between children’s movement behaviors and parenting practices because validated measures for use among families from LMIC are lacking. This study evaluated the psychometric properties of previously validated measures of young children’s physical activity, screen time, and sleep and parenting practices, translated and culturally adapted to Brazilian families.

Methods

A total of 78 parent-child dyads completed an interviewer-administered survey twice within 7 days. Child physical activity, sedentary time and sleep were concurrently measured using a wrist-worn accelerometer. Internal consistency and test-retest reliability was assessed using McDonald’s Omega and Intraclass Correlation Coefficients (ICC’s). Concurrent validity was evaluated by calculating Spearman correlations between parent reported child behaviors and accelerometer measured behaviors.

Results

Seventeen of the 19 parenting practices scales exhibited acceptable internal consistency reliability (Ω ≥ 0.70). Test-retest reliability ICC’s were acceptable and ranged from 0.82 - 0.99. Parent reported child physical activity was positively correlated with objectively measured total movement (rho= 0.29 - 0.46, p < .05) and energetic play (rho= 0.29 – 0.40, p < .05). Parent reported child screen time was positively correlated with objectively measured sedentary time; (rho = 0.26, p < .05), and inversely correlated with total movement (rho = - 0.39 – - 0.41, p < .05) and energetic play (rho = - 0.37 – - 0.41, p < .05). Parent reported night-time sleep duration was significantly correlated with accelerometer measured sleep duration on weekdays (rho = 0.29, p < .05), but not weekends.

Conclusions

Measurement tools to assess children’s movement behaviors and parenting practices, translated and culturally adapted for use in Brazilian families, exhibited acceptable evidence of concurrent validity, internal consistency, and test-retest reliability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01320-y.

Exploring the effect of a school-based cluster-randomised controlled trial to increase the scheduling of physical activity for primary school students on teachers' physical activity

BACKGROUND

To determine if a school-based physical activity (PA) intervention that supported primary school teachers to schedule PA during school hours impacted their own PA.

METHODS

A 2x2 factorial group cluster-randomised controlled trial was undertaken in 12 Australian primary schools. The nine-month intervention supported classroom teachers to increase scheduled weekly PA for their class via physical education, sport, Energisers and integrated lessons. Teachers' PA (n = 76) was measured at follow-up only using accelerometers (Actigraph GT3X or GT9X). Linear mixed models were used to estimate between-group differences in teachers' mean minutes of sedentary, light, moderate-to-vigorous-intensity physical activity (MVPA) across the school day and during class-time.

RESULTS

At follow-up, there were non-significant between-group differences favouring intervention teachers, compared to controls, for light PA (4.9 minutes, 95% CI: -6.3, 16.0; P = .33) and MVPA (0.4 minutes, 95% CI: -10.9, 11.6; P = .94) across the school day; although not favouring the intervention for sedentary behaviour (5.1 minutes, 95% CI: -11.4, 21.7; P = .48). Similar patterns were seen during class-time for light PA and sedentary time, but not for MVPA.

CONCLUSIONS

Supporting teachers with the scheduling of PA for their class may impact on their own PA. Fully powered studies are needed to better understand the impact of the intervention on teachers' PA.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12616001228471 (http://www.anzctr.org.au/).

Validity of the Apple Watch® for monitoring push counts in people using manual wheelchairs

Objective: A recent Apple Watch® activity-monitoring innovation permits manual wheelchair users to monitor daily push counts. This study evaluated the validity of the Apple Watch® push count estimate.Design: Criterion validity.Setting: Southern Finland and Southeast Queensland, Australia.Participants: Twenty-six manual wheelchair users from Finland and Australia were filmed completing a standardized battery of activities while wearing the Apple Watch® (dominant wrist).Outcome Measures: Wheelchair pushes as determined by the Apple Watch® were compared to directly observed pushes.Results: Agreement between Apple Watch® push counts and directly observed pushes was evaluated using Intraclass correlation coefficients (ICC), Pearson correlations and Bland-Altman analyses. Apple Watch® pushes and directly observed push counts were strongly correlated (ICC = 0.77, P < 0.01) (r = 0.84, P < 0.01). Bland Altman plots indicated that the Apple Watch® underestimated push counts (M = -103; 95% ULoA = 217; LLoA = -423 pushes). Mean absolute percentage error was 13.5% which is comparable to studies evaluating agreement between pedometer-based step counts and directly observed steps.Conclusion: Apple Watch® push-count estimates are acceptable for personal, self-monitoring purposes and for research entailing group-level analyses, but less acceptable where accurate push-count measures for an individual is required.

Physical ACTivity in Survivorship (PACTS): study protocol for a randomized controlled trial evaluating a goal-directed therapeutic exercise program in pediatric posterior fossa brain tumor survivors

BACKGROUND

Posterior fossa brain tumors (PFBT) are the most common solid tumor in children. Recent increases in survival rates are encouraging; however, survivors may experience a plethora of disease- and treatment-related complications that can persist into adulthood. Therapeutic exercise interventions have been shown to improve quality of survivorship in other pediatric cancer diagnoses. There is also evidence that goal-directed interventions are effective at improving motor activities, function, and self-care in children with complex health conditions. Yet, there is currently no evidence on the efficacy of goal-directed therapeutic exercise in pediatric PFBT survivors. The Physical ACTivity in Survivorship (PACTS) study aims to investigate the effects of a novel goal-directed therapeutic exercise program on cardiorespiratory fitness and physical activity-related goal attainment in pediatric survivors of PFBT.

METHOD

PFBT survivors, aged five to 17 years, who underwent surgery at least 12 months earlier and completed radiation therapy and/or chemotherapy at least 6 months prior will be recruited from the Queensland Children's Hospital (Brisbane, Australia) (target n = 48). Following baseline assessment, participants are randomized into either the intervention or usual care group. The intervention group will receive weekly individualized, goal-directed exercise therapy delivered face-to-face for 12 weeks, along with an accompanying home-based program (three sessions per week). Outcomes will be assessed at baseline, immediately post-intervention, and at 6- and 12-months post-intervention. The primary outcomes are cardiorespiratory fitness (Peak VO2) and physical activity-related goal attainment. Secondary outcomes are cardiorespiratory endurance, high-level mobility skills, functional muscle strength, habitual physical activity, gait, balance, quality of life, fatigue, participation, perceived movement skill competence and parameters of body composition.

DISCUSSION

PACTS is the first study to investigate the efficacy of goal-directed therapeutic exercise in children with PFBT and provide evidence needed to inform clinical practice recommendations for managing quality of survivorship in PFBT survivors.

TRIAL REGISTRATION

ACTRN12619000841178 .

Free-living Evaluation of Laboratory-based Activity Classifiers in Preschoolers

Machine learning classification models for accelerometer data are potentially more accurate methods to measure physical activity in young children than traditional cut point methods. However, existing algorithms have been trained on laboratory-based activity trials, and their performance has not been investigated under free-living conditions.

PURPOSE

This study aimed to evaluate the accuracy of laboratory-trained hip and wrist random forest and support vector machine classifiers for the automatic recognition of five activity classes: sedentary (SED), light-intensity activities and games (LIGHT_AG), walking (WALK), running (RUN), and moderate to vigorous activities and games (MV_AG) in preschool-age children under free-living conditions.

METHODS

Thirty-one children (4.0 ± 0.9 yr) were video recorded during a 20-min free-living play session while wearing an ActiGraph GT3X+ on their right hip and nondominant wrist. Direct observation was used to continuously code ground truth activity class and specific activity types occurring within each class using a bespoke two-stage coding scheme. Performance was assessed by calculating overall classification accuracy and extended confusion matrices summarizing class-level accuracy and the frequency of specific activities observed within each class.

RESULTS

Accuracy values for the hip and wrist random forest algorithms were 69.4% and 59.1%, respectively. Accuracy values for hip and wrist support vector machine algorithms were 66.4% and 59.3%, respectively. Compared with the laboratory cross validation, accuracy decreased by 11%-15% for the hip classifiers and 19%-21% for the wrist classifiers. Classification accuracy values were 72%-78% for SED, 58%-79% for LIGHT_AG, 71%-84% for MV_AG, 9%-15% for WALK, and 66%-75% for RUN.

CONCLUSION

The accuracy of laboratory-based activity classifiers for preschool-age children was attenuated when tested on new data collected under free-living conditions. Future studies should train and test machine learning activity recognition algorithms using accelerometer data collected under free-living conditions.

Associations between in-school-hours physical activity and child health-related quality of life: A cross-sectional study in a sample of Australian primary school children

The aim of the current study was to examine the association between Australian primary school children's objectively measured in-school-hours weekly physical activity (PA) and their health-related quality of life (HRQoL). A cross-sectional study of 1128 Grade 2 and 3 children, aged 7-9 years, from 62 primary schools was conducted in New South Wales, Australia between October 2017 and April 2018. Children's PA was assessed via an accelerometer worn for five days during school hours. Their parents completed a telephone interview, answering demographic, child HRQoL and out-of-school-hours PA questions. Children's in-school-hours PA was classified as total PA and moderate-to-vigorous PA (MVPA). HRQoL scores were aggregated and reported at the high construct level domains (Total Quality of Life (Total HRQoL), Physical and Psychosocial Health Summary Scores). Multiple linear mixed regression analyses accounting for clustering were conducted to evaluate the association between children's in-school-hours weekly PA and their HRQoL. After adjusting for potential confounders, significant positive associations were found between children's in-school-hours weekly total PA and Total HRQoL (0.62 units, 95% CI: 0.29; 0.94, p < 0.001), Physical (0.71 units, 95% CI: 0.38; 1.04, p ≤ 0.001) and Psychosocial (0.58 units, 95% CI: 0.19; 0.97, p = 0.004) scores, with a stronger association observed between average weekly MVPA than average weekly total PA. There were also positive associations between PA and HRQoL for each sex when analysed separately. Our findings demonstrate a positive association between children's objectively-measured in-school-hours PA and parent-reported child HRQoL, strengthening evidence supporting the continued implementation of school-based PA programs for broader health outcomes.

Development of physical activity policy and implementation strategies for early childhood education and care settings using the Delphi process

BACKGROUND

The aim of this study was to gain consensus on an evidence informed physical activity policy template for early childhood education and care (ECEC) and determine best-practice dissemination and implementation strategies using the Delphi process.

METHODS

Three-round modified Delphi methodology. During round one an expert working group developed an evidence informed ECEC specific physical activity policy template. Rounds two and three involved national online surveys to seek insight from a group of experts on the draft physical activity policy template.

RESULTS

Ninety per cent of experts reported ECEC services are fully responsible for having a physical activity policy. There was consensus on the components of the policy and key physical activity and sedentary behaviour statements and recommendations. The most effective methods for disseminating a physical activity policy to ECEC providers included online (websites, social and electronic media), ECEC targeted launch events, direct mail outs and via professional associations. Twenty five key strategies related to management, supervisors and educators; the ECEC physical environment; communicating with families; and accreditation, monitoring and review, were identified as necessary for the successful implementation of physical activity policy in ECEC. Experts reached consensus on nine of these strategies indicating they were both easy to implement and likely to have a high level of influence. Key barriers and enablers to implementing ECEC-specific physical activity were also identified.

CONCLUSIONS

This evidence informed physical activity policy template for ECEC provides recommendations on the amount of physical activity and sedentary time (including screen time) children should have whilst attending ECEC and aligns with national/international guidelines. A number of effective physical activity policy implementation strategies for ECEC were identified. An important next step is advocating for the introduction of legislative requirements for services to have and implement a physical activity policy.

Machine learning to quantify habitual physical activity in children with cerebral palsy

AIM

To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by children and adolescents with cerebral palsy (CP) who use mobility aids for ambulation.

METHOD

Eleven participants (mean age 11y [SD 3y]; six females, five males) classified in Gross Motor Function Classification System (GMFCS) levels III and IV, completed six physical activity trials wearing a tri-axial accelerometer on the wrist, hip, and thigh. Trials included supine rest, upper-limb task, walking, wheelchair propulsion, and cycling. Three supervised learning algorithms (decision tree, support vector machine [SVM], random forest) were trained on features in the raw-acceleration signal. Model-performance was evaluated using leave-one-subject-out cross-validation accuracy.

RESULTS

Cross-validation accuracy for the single-placement models ranged from 59% to 79%, with the best performance achieved by the random forest wrist model (79%). Combining features from two or more accelerometer placements significantly improved classification accuracy. The random forest wrist and hip model achieved an overall accuracy of 92%, while the SVM wrist, hip, and thigh model achieved an overall accuracy of 90%.

INTERPRETATION

Models trained on features in the raw-acceleration signal may provide accurate recognition of clinically relevant physical activity behaviours in children and adolescents with CP who use mobility aids for ambulation in a controlled setting.

WHAT THIS PAPER ADDS

Machine learning may assist clinicians in evaluating the efficacy of surgical and therapy-based interventions. Machine learning may help researchers better understand the short- and long-term benefits of physical activity for children with more severe motor impairments.

Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children

Machine learning (ML) activity classification models trained on laboratory-based activity trials exhibit low accuracy under free-living conditions. Training new models on free-living accelerometer data, reducing the number of prediction windows comprised of multiple activity types by using shorter windows, including temporal features such as standard deviation in lag and lead windows, and using multiple sensors may improve the classification accuracy under free-living conditions. The objective of this study was to evaluate the accuracy of Random Forest (RF) activity classification models for preschool-aged children trained on free-living accelerometer data. Thirty-one children (mean age = 4.0 ± 0.9 years) completed a 20 min free-play session while wearing an accelerometer on their right hip and non-dominant wrist. Video-based direct observation was used to categorize the children’s movement behaviors into five activity classes. The models were trained using prediction windows of 1, 5, 10, and 15 s, with and without temporal features. The models were evaluated using leave-one-subject-out-cross-validation. The F-scores improved as the window size increased from 1 to 15 s (62.6%–86.4%), with only minimal improvements beyond the 10 s windows. The inclusion of temporal features increased the accuracy, mainly for the wrist classification models, by an average of 6.2 percentage points. The hip and combined hip and wrist classification models provided comparable accuracy; however, both the models outperformed the models trained on wrist data by 7.9 to 8.2 percentage points. RF activity classification models trained with free-living accelerometer data provide accurate recognition of young children’s movement behaviors under real-world conditions.

Machine Learning to Quantify Physical Activity in Children with Cerebral Palsy: Comparison of Group, Group-Personalized, and Fully-Personalized Activity Classification Models

Pattern recognition methodologies, such as those utilizing machine learning (ML) approaches, have the potential to improve the accuracy and versatility of accelerometer-based assessments of physical activity (PA). Children with cerebral palsy (CP) exhibit significant heterogeneity in relation to impairment and activity limitations; however, studies conducted to date have implemented “one-size fits all” group (G) models. Group-personalized (GP) models specific to the Gross Motor Function Classification (GMFCS) level and fully-personalized (FP) models trained on individual data may provide more accurate assessments of PA; however, these approaches have not been investigated in children with CP. In this study, 38 children classified at GMFCS I to III completed laboratory trials and a simulated free-living protocol while wearing an ActiGraph GT3X+ on the wrist, hip, and ankle. Activities were classified as sedentary, standing utilitarian movements, or walking. In the cross-validation, FP random forest classifiers (99.0–99.3%) exhibited a significantly higher accuracy than G (80.9–94.7%) and GP classifiers (78.7–94.1%), with the largest differential observed in children at GMFCS III. When evaluated under free-living conditions, all model types exhibited significant declines in accuracy, with FP models outperforming G and GP models in GMFCS levels I and II, but not III. Future studies should evaluate the comparative accuracy of personalized models trained on free-living accelerometer data.

Correlates of physical activity in fifth-grade students in Ho Chi Minh City, Vietnam

Studies investigating correlates of physical activity (PA) using objective PA measurements among primary school-aged children are limited in Asia, particularly Vietnam. This study examined psychosocial and environmental factors associated with PA among fifth-grade students in eight primary schools in Ho Chi Minh city, Vietnam. Bivariate analyses showed that for every month increase in students’ age, an increase of 66 steps/day (p<0.05) was found; boys had 1442 more steps/day than girls (p<0.001); and students from lower income households had 1169 steps/day less than those from higher income households (p<0.01). For every unit increase in self-efficacy, perceived social influences, intention to be physically active, and parental support for PA, an increase of 220, 200, 522, and 117 steps/day (p<0.01) was found respectively. In multivariable analysis, only intention and parental support for PA remained significant (p<0.01). About 21% of variation in daily steps was explained by demographic characteristics and an additional 13% by psychosocial influences. In conclusion, intention to be physically active and parental support are important factors and should be considered when designing PA interventions in school/community-based settings.

'Jump start' childcare-based intervention to promote physical activity in pre-schoolers: six-month findings from a cluster randomised trial

BACKGROUND

Participation in adequate levels of physical activity during the early years is important for health and development. We report the 6-month effects of an 18-month multicomponent intervention on physical activity in early childhood education and care (ECEC) settings in low-income communities.

METHODS

A cluster randomised controlled trial was conducted in 43 ECEC settings in disadvantaged areas of New South Wales, Australia. Three-year-old children were recruited and assessed in the first half of 2015 with follow-up 6 months later. The intervention was guided by Social Cognitive Theory and included five components. The primary outcome was minutes per hour in total physical activity during ECEC hours measured using Actigraph accelerometers. Intention-to-treat analysis of the primary outcome was conducted using a generalized linear mixed model.

RESULTS

A total of 658 children were assessed at baseline. Of these, 558 (85%) had valid accelerometer data (mean age 3.38y, 52% boys) and 508 (77%) had valid accelerometry data at 6-month follow-up. Implementation of the intervention components ranged from 38 to 72%. There were no significant intervention effects on mins/hr. spent in physical activity (adjusted difference = - 0.17 mins/hr., 95% CI (- 1.30 to 0.97), p = 0.78). A priori sub-group analyses showed a greater effect among overweight/obese children in the control group compared with the intervention group for mins/hr. of physical activity (2.35mins/hr., [0.28 to 4.43], p = 0.036).

CONCLUSIONS

After six-months the Jump Start intervention had no effect on physical activity levels during ECEC. This was largely due to low levels of implementation. Increasing fidelity may result in higher levels of physical activity when outcomes are assessed at 18-months.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry  ACTRN12614000597695.

Patterns and Correlates of Sedentary Behavior in Children Attending Family Child Care

Public health authorities recommend young children should not be sedentary for more than one hour at a time. This study assessed the frequency and duration of sedentary bouts in children attending family child care homes (FCCHs); and examined associations with FCCH provider practices related to sedentary behaviors. Overall, 127 children (aged 3.5 ± 1.1 years) from 41 FCCHs participated in the study. Sedentary bouts were measured using an accelerometer worn for the duration of FCCHs attendance over a randomly selected week. Provider practices were assessed using the Nutrition and Physical Activity Self-Assessment for Child Care self-assessment instrument. Children attending FCCHs mostly accumulated short sedentary bouts (<5 min) with very few lasting more than 10 min. Boys exhibited significantly fewer sedentary bouts, and significantly less sedentary time in bouts than girls. Children attending FCCHs that met or exceeded childcare standards for outdoor active play, had portable play equipment, offered a variety of fixed play equipment, and/or adequate indoor play space exhibited significantly fewer sedentary bouts and significantly less sedentary time accumulated in short and medium length bouts. Programs encouraging FCCHs to adopt physical activity promoting practices could potentially reduce child sedentary time while in care.

The Effect of Upgrades to Childcare Outdoor Spaces on Preschoolers' Physical Activity: Findings from a Natural Experiment

Physical inactivity is a significant risk factor for childhood obesity. Preventing obesity in the early years reduces the risk of developing chronic health conditions later. Early childhood education and care (ECEC) services are important settings to establish good preschooler physical activity behaviors. This natural experiment investigated the influence of ECEC outdoor physical environment upgrade on preschoolers' physical activity (aged 2-5 years). Centers implemented upgrades without researcher input. Physical activity was measured by 7-day accelerometry for intervention (n = 159; 6 centers) and control (n = 138; 5 centers) groups. ECEC outdoor space was assessed using a modified Environment and Policy Assessment and Observation (EPAO) Instrument. Key outcomes were measured at baseline and 6-12 months follow-up. Fixed sandboxes, balls, portable slides, portable floor play equipment (e.g., tumbling mats), and natural grassed areas were positively associated with activity levels; fixed tunnels and twirling equipment were negatively associated with activity levels (all p < 0.05). Post-upgrade portable play equipment (balls, twirling equipment, slides, floor play equipment) increased intervention preschoolers' moderate-vigorous physical activity (MVPA) levels compared to control (p < 0.05). Intervention preschoolers were more active than control at follow-up (58.09 vs. 42.13 min/day increase in total physical activity; 30.46 vs. 19.16 min/day increase in MVPA (all p < 0.001)). Since few preschoolers meet daily activity recommendations while at ECEC, the findings may help ECEC providers to optimize outdoor physical environments and encourage more active play among preschoolers.

Supporting healthy lifestyle behaviours in families attending community playgroups: parents' perceptions of facilitators and barriers

BACKGROUND

Establishing healthy nutrition, activity, and sleep behaviours early in life is a key strategy in childhood obesity prevention. Parents are the primary influence on the development and establishment of obesity-related behaviours in young children. There is evidence that autonomy supporting parenting practices are crucial for the development of self-regulation and the internalisation of healthy behaviours in children. It is therefore imperative that parenting practices are targeted as part of an obesity prevention intervention. However, there is limited understanding of barriers and facilitators to parents using autonomy supporting parenting practices with their children aged 0-5 years. Therefore, the aim of the study was to identify barriers and facilitators to using autonomy supporting parenting practices. A secondary aim was to determine parent preferences in respect to an intervention program to be delivered in community playgroups.

METHODS

Parents were recruited through Playgroup Queensland (PGQ), a not-for-profit organisation in Brisbane, Australia, to attend a focus group during their usual playgroup session. The focus group interview guide was designed to promote discussion among the participants in respect to their shared experiences as parents of young children. The focus group transcripts were coded and analysed using qualitative content analysis. Five focus groups with parents (n = 30) were conducted in May 2018. Most of the participants were mothers [1], and the majority (76%) had a child at playgroup aged between 2 and 4 years.

RESULTS

The support and guidance received from other parents at playgroup was a facilitator to autonomy supporting parenting practices. Barriers included beliefs around the need to use rewards to encourage child eating, beliefs around the need for screens as babysitters, and feeling disempowered to change sleep behaviours. Parents were enthusiastic about a potential program that would leverage off the existing playgroup support networks, but they did not want to be "educated", or to lose their "playgroup time" to an intervention. Rather they wanted strategies and support to deal with the frustrations of food, screen and sleep parenting.

CONCLUSION

These results will be used to inform the development of a childhood obesity prevention intervention to be delivered in a community playgroup setting.

Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data

Detection of non-wear periods is an important step in accelerometer data processing. This study evaluated five non-wear detection algorithms for wrist accelerometer data and two rules for non-wear detection when non-wear and sleep algorithms are implemented in parallel. Non-wear algorithms were based on the standard deviation (SD), the high-pass filtered acceleration, or tilt angle. Rules for differentiating sleep from non-wear consisted of an override rule in which any overlap between non-wear and sleep was deemed non-wear; and a 75% rule in which non-wear periods were deemed sleep if the duration was < 75% of the sleep period. Non-wear algorithms were evaluated in 47 children who wore an ActiGraph GT3X+ accelerometer during school hours for 5 days. Rules for differentiating sleep from non-wear were evaluated in 15 adults who wore a GeneActiv Original accelerometer continuously for 24 hours. Classification accuracy for the non-wear algorithms ranged between 0.86-0.95, with the SD of the vector magnitude providing the best performance. The override rule misclassified 37.1 minutes of sleep as non-wear, while the 75% rule resulted in no misclassification. Non-wear algorithms based on the SD of the acceleration signal can effectively detect non-wear periods, while application of the 75% rule can effectively differentiate sleep from non-wear when examined concurrently.