It has been theorized that physical literacy is associated with physical activity and health. The purpose of this study is to investigate the associations between physical literacy and health, and if this relationship is mediated by moderate-to-vigorous physical activity (MVPA). Two hundred and twenty-two children (113 girls, 10.7 ± 1.0 years old) participated in this cross-sectional study. A physical literacy composite score was computed from measures of PLAYfun, PLAYparent, and PLAYself. Physical activity was measured over seven days with accelerometers, expressed as MVPA (min/day). Health indicators included: body composition (percent body fat), aerobic fitness (treadmill time and 60s heart rate recovery), resting systolic blood pressure, and quality of life. Physical literacy was significantly associated (p < 0.001) with percent body fat (R2 = 0.23), treadmill time (R2 = 0.21), 60 s heart rate recovery (R2 = 0.36), systolic blood pressure (R2 = 0.11), and quality of life (R2 = 0.11). The relationships between physical literacy and aerobic fitness, but not other health indicators, were directly mediated by MVPA. Higher physical literacy in children is associated with favorable health indicators, and the relationships between physical literacy and aerobic fitness were influenced by MVPA. Future work should examine these relationships longitudinally and determine if changes in physical literacy leads to changes in health.

The Physical Literacy Assessment for Youth (PLAY) Tools are a suite of tools to assess an individual’s physical literacy. The purpose of this study is to examine the psychometric properties of the PLAY Tools, including inter-rater reliability, internal consistency, validity and the associations between the tools. In this study, 218 children and youth (8.4- to- 13.7-years old) and a parent/ guardian completed the appropriate physical literacy assessments (i.e., PLAYbasic, PLAYfun, PLAYparent and PLAYself) and the Bruiniks-Oseretsky Test of Motor Proficiency (BOT-2). Inter-rater reliability for PLAYfun was excellent (ICC=0.94). The PLAYbasic, PLAYfun total, running and object control scores, and PLAYparent motor competence domain were higher in males than females, and PLAYfun locomotor skills were lower in males than females (p<0.05). Age was positively correlated with PLAYbasic and PLAYfun (r=0.14-0.32, p<0.05). BOT-2 was positively correlated with PLAYfun and PLAYbasic (r=0.19-0.59, p<0.05). PLAYbasic is a significant predictor of PLAYfun (R²=0.742, p<0.001). PLAYfun, PLAYparent and PLAYself were moderately correlated with one another. PLAYfun, PLAYparent and PLAYself demonstrated acceptable internal consistency (α=0.74-0.87, ω=0.73-0.87). The PLAY Tools demonstrated moderate associations between one another, strong inter-rater reliability and good construct and convergent validity. Continued evaluation of these tools with other populations, such as adolescents, is necessary. •In school-age children, the PLAY Tools demonstrated strong inter-rater reliability, moderate associations with one another, acceptable internal consistency and good construct and convergent validity.•The results suggest that that PLAY Tools are an acceptable method of evaluation for physical literacy in school-age children.

The early years are characterized by rapid physical growth and the development of behaviours such as physical activity. The objectives of this study were to assess the 12-month changes in and the tracking of physical activity and fitness in 400 preschoolers (201 boys, 4.5 ± 0.9 years of age). Physical activity data, expressed as minutes per day and as the percentage of time spent at various intensities while wearing an accelerometer, were collected in 3-s epochs for 7 days. Short-term muscle power, assessed with a 10-s modified Wingate Anaerobic Test, was expressed as absolute (W) and relative (W/kg) peak power (PP) and mean power (MP). Aerobic fitness, assessed with the Bruce Protocol progressive treadmill test, was expressed as maximal treadmill time and heart rate recovery (HRR). Light physical activity decreased by 3.2 min/day (p < 0.05), whereas vigorous physical activity increased by 3.7 min/day (p < 0.001), from year 1 to year 2. Physical activity exhibited moderate tracking on the basis of Spearman correlations (r = 0.45-0.59, p < 0.001) and fair tracking on the basis of κ statistics (κ = 0.26-0.38). PP and MP increased from year 1 (PP, 94.1 ± 37.3 W; MP, 84.1 ± 30.9 W) to year 2 (PP, 125.6 ± 36.2 W; MP, 112.3 ± 32.2 W) (p < 0.001) and tracked moderately to substantially (PP, r = 0.89, κ = 0.61; MP, r = 0.86, κ = 0.56). Time to exhaustion on the treadmill increased from 9.4 ± 2.3 min to 11.8 ± 2.3 min (p < 0.001) and tracked strongly (r = 0.82, κ = 0.56). HRR was unchanged at 65 ± 14 beats/min (p = 0.297) and tracked fairly (r = 0.52, κ = 0.23). The findings indicate that fitness tracks better than physical activity over a 12-month period during the early years.

Young children's activity and sedentary time were simultaneously measured via the Actical method (i.e., Actical accelerometer and specific cut-points) and the ActiGraph method (i.e., ActiGraph accelerometer and specific cut-points) at both 15-s and 60-s epochs to explore possible differences between these 2 measurement approaches. For 7 consecutive days, participants (n = 23) wore both the Actical and ActiGraph side-by-side on an elastic neoprene belt. Device-specific cut-points were applied. Paired sample t tests were conducted to determine the differences in participants' daily average activity levels and sedentary time (min/h) measured by the 2 devices at 15-s and 60-s time sampling intervals. Bland-Altman plots were used to examine agreement between Actical and ActiGraph accelerometers. Regardless of epoch length, Actical accelerometers reported significantly higher rates of sedentary time (15 s: 42.7 min/h vs 33.5 min/h; 60 s: 39.4 min/h vs 27.1 min/h). ActiGraph accelerometers captured significantly higher rates of moderate-to-vigorous physical activity (15 s: 9.2 min/h vs 2.6 min/h; 60 s: 8.0 min/h vs 1.27 min/h) and total physical activity (15 s: 31.7 min/h vs 22.3 min/h; 60 s: = 39.4 min/h vs 25.2 min/h) in comparison with Actical accelerometers. These results highlight the present accelerometry-related issues with interpretation of datasets derived from different monitors.

Introduction/PurposeTo determine personal, environmental, and participation factors that predict children’s physical activity (PA) trajectories from preschool through to school years.MethodsTwo hundred seventy-nine children (4.5 ± 0.9 yr, 52% boys) were included in this study. Physical activity was collected via accelerometry at six different timepoints over 6.3 ± 0.6 yr. Time-stable variables were collected at baseline and included child’s sex and ethnicity. Time-dependent variables were collected at six timepoints (age, years) and included household income (CAD), parental total PA, parental influence on PA, and parent-reported child’s quality of life, child’s sleep, and child’s amount of weekend outdoor PA. Group-based trajectory modeling was applied to identify trajectories of moderate-to-vigorous PA (MVPA) and total PA (TPA). Multivariable regression analysis identified personal, environmental, and participation factors associated with trajectory membership.ResultsThree trajectories were identified for each of MVPA and TPA. Group 3 in MVPA and TPA expressed the most PA over time, with increased activity from timepoints 1 to 3, and then declining from timepoints 4 to 6. For the group 3 MVPA trajectory, male sex (β estimate, 3.437; P = 0.001) and quality of life (β estimate, 0.513; P < 0.001) were the only significant correlates for group membership. For the group 3 TPA trajectory, male sex (β estimate, 1.970; P = 0.035), greater household income (β estimate, 94.615; P < 0.001), and greater parental total PA (β estimate, 0.574; P = 0.023) increased the probability of belonging to this trajectory group.ConclusionsThese findings suggest a need for interventions and public health campaigns to increase opportunities for PA engagement in girls starting in the early years. Policies and programs to address financial inequities, positive parental modeling, and improving quality of life are also warranted.