T. Okely

Mastery of fundamental motor skills among New South Wales school students: prevalence and sociodemographic distribution

Mastery of fundamental motor skills among children and adolescents is a potentially important contribution to satisfying participation in sports, games and other physical activities and may enhance the development of an active lifestyle. However, few attempts have been made to determine the prevalence of fundamental motor skill mastery among young Australians. The NSW Schools Fitness and Physical Activity Survey, 1997 (N = 5518) randomly selected schools proportionally from all three education sectors and selected students in Years 4, 6, 8 and 10. Performance on six fundamental motor skills (run, vertical jump, catch, overhand throw, forehand strike and kick) was assessed qualitatively. The prevalence of mastery and near mastery of each skill and mastery of each skill component is reported for boys and girls in each school year. The findings indicate that the prevalence of mastery and near mastery of each of the fundamental motor skills was generally low. There were no differences between students from urban or rural schools and the prevalence of skill mastery was directly associated with socioeconomic status more consistently among girls than among boys. Greater curriculum time and resourcing and training of teachers is required to increase the proportion of students who have mastered the skills fundamental to common sports, games and other physical activities.

Methods of the NSW Schools Fitness and Physical Activity Survey, 1997.

Physical fitness, participation in physical activity, fundamental motor skills and body composition are important contributors to the health and the development of a healthy lifestyle among children and youth. The New South Wales Schools Fitness and Physical Activity Survey, 1997, was conducted to fill some of the gaps in our knowledge of these aspects of the lives of young people in New South Wales. The survey was conducted in February and March, 1997 and collected data on a randomly-selected sample of students (n=5518) in Years 2, 4, 6, 8 and 10. Measures were taken on body composition (height and weight, waist and hip girths, skinfolds), health-related fitness (aerobic capacity, muscular strength, muscular endurance, flexibility), fundamental motor skills (run, vertical jump, catch, overhand throw, forehand strike and kick), self-reported physical activity, time spent in sedentary recreation, and physical education (PE) classes. The methods are described to assist in the development of surveys of other populations and to provoke debate relevant to the development and dissemination of standard approaches to monitoring the fitness, physical activity habits and body composition of Australian children and youth. Finally, we offer comments on some of the strengths and limitations of the methods employed.

Results from Australia’s 2014 Report Card on Physical Activity for Children and Youth

BACKGROUND Like many other countries, Australia is facing an inactivity epidemic. The purpose of the Australian 2014 Physical Activity Report Card initiative was to assess the behaviors, settings, and sources of influences and strategies and investments associated with the physical activity levels of Australian children and youth. METHODS A Research Working Group (RWG) drawn from experts around Australia collaborated to determine key indicators, assess available datasets, and the metrics which should be used to inform grades for each indicator and factors to consider when weighting the data. The RWG then met to evaluate the synthesized data to assign a grade to each indicator. RESULTS Overall Physical Activity Levels were assigned a grade of D-. Other physical activity behaviors were also graded as less than average (D to D-), while Organized Sport and Physical Activity Participation was assigned a grade of B-. The nation performed better for settings and sources of influence and Government Strategies and Investments (A- to a C). Four incompletes were assigned due to a lack of representative quality data. CONCLUSIONS Evidence suggests that physical activity levels of Australian children remain very low, despite moderately supportive social, environmental and regulatory environments. There are clear gaps in the research which need to be filled and consistent data collection methods need to be put into place.

Dietary outcomes of the healthy dads healthy kids randomised controlled trial

ABSTRACT Fathers have not been exclusively targeted in family-based lifestyle programmes. The aim was to determine whether dietary intakes of fathers and children can be improved, following an intervention targeting fathers. Overweight and obese fathers (n = 50, 21–65 years, body mass index [mean ± standard deviation] 33.3 ± 4.1) and their children (5–12 years) were recruited. Dietary intake was assessed at baseline and 6 months (n = 35) by food frequency questionnaire. Linear mixed models determined differences by time. Fathers significantly reduced portion size (P = 0.03) but not energy intakes, whereas children reduced energy intakes (kJ) (P = 0.02). There is an opportunity to target fathers as to improve child intakes.

Evaluation of Actical equations and thresholds to predict physical activity intensity in young children

Abstract This study examined the validity of current Actical activity energy expenditure (AEE) equations and intensity cut-points in preschoolers using AEE and direct observation as criterion measures. Forty 4–6-year-olds (5.3 ± 1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary behaviours (SBs), light intensity physical activities (LPAs) and moderate-to-vigorous intensity physical activities (MVPAs). AEE and/or physical activity intensity were calculated using Actical equations and cut-points by Adolph, Evenson, Pfeiffer and Puyau. Predictive validity was examined using paired sample t-tests. Classification accuracy was evaluated using weighted kappas, sensitivity, specificity and area under the receiver operating characteristic curve. The Pfeiffer equation significantly overestimated AEE during SB and underestimated AEE during LPA (P < 0.0125 for both). There was no significant difference between measured and predicted AEEs during MVPA. The Adolph cut-point showed significantly higher accuracy for classifying SB, LPA and MVPA than all others. The available Actical equation does not provide accurate estimates of AEE across all intensities in preschoolers. However, the Pfeiffer equation performed reasonably well for MVPA. Using cut-points of ≤6 counts · 15 s−1, 7–286 counts · 15 s−1 and ≥ 287 counts · 15 s−1 when classifying SB, LPA and MVPA, respectively, is recommended.