Darijan Suton

Evaluating the Responsiveness of Accelerometry to Detect Change in Physical Activity

The responsiveness to change of the Actical and ActiGraph accelerometers was assessed in children and adolescents. Participants (N = 208) aged 6 to 16 years completed two simulated free-living protocols, one with primarily light-to-moderate physical activity (PA) and one with mostly moderate-to-vigorous PA. Time in sedentary, light, moderate, and vigorous PA was estimated using 8 previously developed cut-points (4 for Actical and 4 for ActiGraph) and 5-sec, 15-sec, and 30-sec epochs. Accelerometer responsiveness for detecting differences in PA between protocols was assessed using standardized response means (SRMs). SRM values ≥.8 represented high responsiveness to change. Both accelerometers showed high responsiveness for all PA intensities (SRMs = 1.2–4.7 for Actical and 1.1–3.3 for ActiGraph). All cut-points and epoch lengths yielded high responsiveness, and choice of cut-points and epoch length had little effect on responsiveness. Thus, both the Actical and ActiGraph can detect change in PA in a simulated free-living setting, irrespective of cut-point selection or epoch length.

Physical activity and self-efficacy in normal and over-fat children.

OBJECTIVE To examine the independent and combined association of self-efficacy and fatness with physical activity in 5(th) grade children. METHODS Participants were 281 students (10.4 ± 0.7 years). Physical activity was assessed using a self-report question. Self-efficacy to be physically active was assessed using a 5-point scale. Body fatness was assessed by bioelectrical impedance. Descriptive statistics, ANOVA, and t-tests were used. RESULTS There were no differences in reported days of physical activity between boys and girls, and normal-fat and over-fat children. However, children with high self-efficacy participated in significantly more physical activity compared to their low self-efficacy counterparts (3.4 ± 2.0 days vs. 5.4 ± 1.8 days, respectively, p < .001). CONCLUSIONS Only physical activity self-efficacy was related to physical activity, fatness was not.

Energy Cost of Children's Structured and Unstructured Games.

BACKGROUND Limited data are available on energy cost of common childrens games using measured oxygen consumption. METHODS Children (10.6 ± 2.9 years; N = 37; 26 male, 9 female) performed a selection of structured (bowling, juggling, obstacle course, relays, active kickball) and unstructured (basketball, catch, tennis, clothespin tag, soccer) activities for 5 to 30 minutes. Resting metabolic rate (RMR) was calculated using Schofields age- and sex-specific equation. Children wore a portable metabolic unit, which measured expired gases to obtain oxygen consumption (VO2), youth METs (relative VO2/childs calculated RMR), and activity energy expenditure (kcal/kg/min). Descriptive statistics were used to summarize data. RESULTS Relative VO2 ranged from 16.8 ± 4.6 ml/kg/min (bowling) to 32.2 ± 6.8 ml/kg/min (obstacle course). Obstacle course, relays, active kickball, soccer, and clothespin tag elicited vigorous intensity (>6 METs), the remainder elicited moderate intensity (3-6 METs). CONCLUSIONS This article contributes energy expenditure data for the update and expansion of the youth compendium.

Accelerometer responsiveness to change between structured and unstructured physical activity in children and adolescents

ABSTRACT This study examined if accelerometer-based assessments of physical activity were responsive to changes in physical activity level commensurate with performing structured versus unstructured activity in youth. Youth (6–16 years; N = 206) participated in a simulated after-school program that included structured and unstructured games on four occasions over a 3-year period. Recruitment occurred in 2007/2008 and data collection ended in 2011. Participants wore an Actigraph GT1M accelerometer on the hip. The Evenson cut-points were used to determine the time spent in each physical activity intensity, and standardized response means (SRM) were calculated and converted to standard effect sizes to be interpreted according to Cohen’s guidelines. SRMs ranged from trivial (0.16) to high (2.07), with the majority (75%) being classified as moderate or high. Our findings suggest that accelerometry was sensitive to differences in physical activity associated with structured compared to unstructured play, supporting the utility of accelerometry in evaluating activity-promoting interventions.

Contribution of active videogame play to physical activity among college students.

BACKGROUND Fewer than half of college students meet physical activity (PA) recommendations. Active videogames (AVGs) may increase PA. The contribution that AVGs make to total PA is unknown. This study aimed to examine the contribution of AVG play to total PA and to compare sedentary, light, and moderate- to vigorous-intensity PA (MVPA) on game-days and non-game-days. MATERIALS AND METHODS For 1 week, the PA of 42 students (mean age, 20.4±1.3 years) was assessed by accelerometry. During this week an AVG was played one to three times, for 30 minutes each. The percentage contribution of AVG play to MVPA was calculated. To compare PA on game-days versus non-game-days, t tests were used. RESULTS Students performed an average of 47.2±32.0 minutes of MVPA/day, during the monitored weekdays. MVPA during AVG play contributed 4.8±8.1 percent to total MVPA on game-days. The percentage of time spent in moderate PA was significantly higher on game-days (4.9 percent) than on non-game-days (3.3 percent). CONCLUSIONS This is the first study to examine the contribution of AVG play to daily PA. These data support further investigation of AVGs as a means of increasing health-enhancing PA and reducing sedentary behavior among college students.

The combined association of self-efficacy and fatness on physical activity in low income, minority children

Economy of movement is defmed as the mass related aerobic demand (V02 mL·kg-l·min-l) or energy expenditure required to run or walk at a given submaximal speed (Morgan, 2000). It has been well established that children have a lower economy compared to adults (Rowland and Green, 1988; Rowland et al., 1987; Unnithan and Eston, 1990). This means that at any given walking or running speed, children exhibit a higher weight relative V02compared to that of an adult. The difference in economy between children and adults is thought to be due to differences in stride frequency (SF), leg length, body-surface-area to mass ratio (BSA:M), body mass index (BMI), and ventilatory efficiency (Rowland et al., 1987; Rowland and Green, 1988; Unnithan and Eston, 1990).