The aim of this study was to determine whether changes in fitness performance could be explained by changes in body fatness. Two hundred seventy-nine 10- to 12-year-old children were tested in 1985 as part of a national survey. They were matched for age, sex, body-mass index, and triceps skin-fold thickness with 279 children from a 1997 survey. Average speeds on the 1.6 km walk/run test were compared. Children from the 1997 survey performed significantly worse than their matched peers from the 1985 survey. The decline in performance was evident for boys, girls, and all children. Matching for fatness reduced performance differences by about 61% in boys, and 37% in girls. Declines in fitness performance in this population have not been entirely due to increases in fatness.
Kate Ridley and Tim Olds
Time spent playing video games has been linked to increases in childhood obesity and sedentary behavior. However, “new generation” video games require total body movement and greater physical exertion. The aim of this study was to describe children’s behavior and energy expenditure while visiting video game centers. Observations were undertaken on 134 children’s activity patterns while playing at a video game center. The energy cost of 10 children (5 male and 5 female) aged 12.5 ± 0.5 yr, playing 4 popular video games was then measured. Gross energy cost ranged from 7.6 to 26.5 ml · kg−1 · min−1. Based on our observations, we estimate that the gross energy expenditure during a child’s typical session in a video game center will range from 2.3–2.6 METS.
Kate Ridley, Jim Dollman and Tim Olds
The aim was to develop and trial a computer delivered multimedia 1-day physical activity questionnaire (CDPAQ) and to compare this with an equivalent hard copy version (HC). Thirty male and female subjects (11.96 ± 0.53 years) were used to assess the validity of the questionnaires by comparing Caltrac counts and heart rate (HR) data with physical activity recalls. Pearson product-moment correlations between the CDPAQ and HR and Caltrac counts ranged from r = 0.36 to 0.63 (p < .05). For the HC, correlations ranged from r = 0.25 to 0.48 (p < .05). While the CDPAQ displayed consistently higher validity correlations, the differences failed to reach statistical significance. Both questionnaires demonstrated high test-retest reliability (r = 0.98, p = .0001). The multimedia features of the CDPAQ may assist children in remembering and characterizing physical activity. The data processing features of the CDPAQ also provide considerable time-saving benefits.
Tim Olds, Carol Ann Maher and Kate Ridley
Low physical activity has been associated with increased fatness and deceased fitness. This observational study aimed to describe the magnitude, composition, and time-distribution of moderate-to-vigorous physical activity (MVPA) in Australian children.
A total of 1132 10 to 13 year old schoolchildren completed a 24-h activity recall diary on 2 to 4 occasions. MVPA was defined as any activity requiring ≥3METs, including sport, play, active transport, chores, and other activities.
MVPA was higher in boys than girls (173 vs 140 min/day; P < .0001), higher on nonschool days than school days (166 vs 143 min/day; P < .0001), and decreased with age (9 min/day per year of age). MVPA consisted of structured sport (37%), active transport (26%), unstructured play (24%), and chores/miscellaneous activities (13%). Every hour of MVPA was associated with a reduction in screen time (26.5 min), non-screen-based sedentary pastimes (8 min), and sleep (5.5 min). The least active quartile of children were more likely to be girls (OR = 3.4), have higher screen time, and sleep more. From 4:00−6:30 PM on school days there were large differences in participation between high-active and low-active children.
Findings suggest MVPA interventions should target girls, screen time and focus on the after-school period.
James Dollman, Tim S. Olds, Adrian Esterman and Tim Kupke
The study aimed to establish pedometer step cut points in relation to weight status among 2,071 5–16 year old Australians. Height, weight and waist circumference were measured, and participants wore a pedometer for seven days. Pedometer values were taken as the average number of steps per day and weighted according to the ratio of weekdays to weekends. Receiver operating characteristic (ROC) curves were used to identify the optimal pedometer counts to predict overweight. Analysis of covariance (ANCOVA) was used to compare anthropometric variables across pedometer step quintiles. The ROC model for older females was nonsignificant. Optimal cut points were 12,000 for younger males, 11,000 for older males and 10,000 for younger females. These were largely confirmed by ANCOVA. The cut points were lower than previously reported for equivalent age groups. Cultural and environmental differences may necessitate population-specific guidelines to be established.
Jim Dollman, Tim Olds, Kevin Norton and David Stuart
There is evidence that fitness has been declining and fatness increasing in Australian schoolchildren over the last generation. This study reproduced the methods of a national survey of Australian schoolchildren conducted in 1985. Anthropometric and performance tests were administered to 1,463 10- and ll-year-old South Australians. Compared to the 1985 sample, the 1997 children were heavier (by 1.4−2.9 kg), showed greater weight for height (by 0.13−0.30 kg · m−2.85), and were slower over 1.6 km (by 38−48.5 s). Furthermore, the distribution of values was markedly more skewed in the 1997 data. While there was little difference between the fittest and leanest quartiles in 1997 and their 1985 counterparts, the least fit and fattest quartiles were markedly worse in 1997. This suggests that the decline in fitness of Australian schoolchildren is not homogeneous and that interventions should target groups where the decline is most marked.
Tim S. Olds, Kate Ridley, James Dollman and Carol A. Maher
This study examined the convergent validity of a computerized use of time diary (MARCA) relative to pedometry. Participants aged 9–16 years wore a pedometer and completed the MARCA. Comparing pedometer data and self-report data collected for the same day (n = 297 participants), the correlation (Spearman’s rho) with PAL was 0.54 and with MVPA was 0.50. Comparing mean daily step counts over 6–7 days with averaged self-report data collected on different days (n = 1713 participants) Spearman’s rho for PAL was 0.45 and for MVPA was 0.44. Thus, the MARCA showed validity similar or superior to most self-report instruments for young people.
Jocelyn Kernot, Lucy Lewis, Tim Olds and Carol Maher
Background: Facebook has over 1.8 billion users and offers unique opportunities for health intervention delivery due to its popularity, flexibility, high engagement, and social connectedness. Methods: This study aimed to determine the effectiveness of the Mums Step It Up (MSIU) Facebook app, a team-based, 50-day physical activity intervention for postpartum women. A total of 120 postpartum women were recruited and randomly allocated to 1 of 3 conditions: MSIU (n = 41), pedometer only (n = 39), and control (n = 40). Assessments were completed at baseline, 6 weeks, and 6 months. Primary outcomes were accelerometer moderate to vigorous physical activity and self-reported walking. Analyses were undertaken on an intention to treat basis using random effects mixed modeling (P ≤ .05). Compliance and engagement with the MSIU app were analyzed, descriptively. Results: There were no significant differences in changes in moderate to vigorous physical activity (P = .81, 6 wk; P = .91, 6 mo) or self-reported walking (P = .55, 6 wk; P = .90, 6 mo) across the 3 conditions. High engagement with the MSIU app was evident, with participants on average visiting the app 26 times and logging steps for 48/50 days. Conclusion: Although engagement with the MSIU app was promising, the nonsignificant results suggest that further work needs to be done to enhance efficacy for postpartum women.
Katia Ferrar, Carol Maher, John Petkov and Tim Olds
To date, most health-related time-use research has investigated behaviors in isolation; more recently, however, researchers have begun to conceptualize behaviors in the form of multidimensional patterns or clusters.
The study employed 2 techniques: radar graphs and centroid vector length, angles and distance to quantify pairwise time-use cluster similarities among adolescents living in Australia (N = 1853) and in New Zealand (N = 679).
Based on radar graph shape, 2 pairs of clusters were similar for both boys and girls. Using vector angles (VA), vector length (VL) and centroid distances (CD), 1 pair for each sex was considered most similar (boys: VA = 63°, VL = 44 and 50 units, and CD = 48 units; girls: VA = 23°, VL = 65 and 85 units, and CD = 36 units). Both methods employed to determine similarity had strengths and weaknesses. Conclusions: The description and quantification of cluster similarity is an important step in the research process. An ability to track and compare clusters may provide greater understanding of complex multidimensional relationships, and in relation to health behavior clusters, present opportunities to monitor and to intervene.
Sarah Edney, Tim Olds, Jillian Ryan, Ronald Plotnikoff, Corneel Vandelanotte, Rachel Curtis and Carol Maher
Background: Homophily is the tendency to associate with friends similar to ourselves. This study explored the effects of homophily on team formation in a physical activity challenge in which “captains” signed up their Facebook friends to form teams. Methods: This study assessed whether participants (n = 430) were more similar to their teammates than to nonteammates with regard to age, sex, education level, body mass index, self-reported and objectively measured physical activity, and negative emotional states; and whether captains were more similar to their own teammates than to nonteammates. Variability indices were calculated for each team, and a hypothetical variability index, representing that which would result from randomly assembled teams, was also calculated. Results: Within-team variability was less than that for random teams for all outcomes except education level and depression, with differences (SDs) ranging from +0.15 (self-reported physical activity) to +0.47 (age) (P < .001 to P = .001). Captains were similar to their teammates except in regard to age, with captains being 2.6 years younger (P = .003). Conclusions: Results support hypotheses that self-selected teams are likely to contain individuals with similar characteristics, highlighting potential to leverage team-based health interventions to target specific populations by instructing individuals with risk characteristics to form teams to help change behavior.