Moving adolescents for a lifetime of physical activity: shifting to interventions aligned with the third health revolution.

Public health advocates have been calling for an intensified focus on early, middle, and late adolescence health behaviours due to both the short- and long-term health consequences. Hence, both the health-risk (e.g., alcohol consumption) and health-promoting (e.g., physical activity) behaviours of adolescents have been widely studied to better understand the underlying causes or determinants with an eye towards implementing more effective interventions. The success of these interventions, typically grounded in a risk-reduction/prevention-oriented intervention approach has been modest, especially those focused on health-promoting behaviours, such as physical activity. The purposes of this paper are to (1) conduct a conceptual critique of the risk-reduction/prevention-oriented approach underlying traditional adolescent physical activity interventions, and (2) examine the potential usefulness of an emerging person-based, development-oriented (PBDO) approach for enhancing the motivation and sustainability of adolescent physical activity. Within this PBDO perspective, emphasis is on adolescent growth and development as the starting point for initiating and sustaining physical activity. Implications of the PBDO approach for adolescent physical activity interventions are presented.

Prevalence of metabolic syndrome risk factors in high school and NCAA division I football players.

Metabolic syndrome (MetSyn) is a clustering of metabolic and cardiovascular disease risk factors. The purpose of this study was to determine the prevalence of MetSyn risk factors in high school (HS) and college (College) football players and to examine if the prevalence varied according to body fat percent (%Fat). One hundred twenty-three males (height 179.0 ± 6.7 cm; weight 89.4 ± 19.6 kg) from 7 different high schools and 82 males (height 186.2 ± 6.8 cm; weight 99.6 ± 16.8 kg) from one university participated. All testing occurred in the early morning after an overnight fast. %Fat, waist circumference, resting systolic and diastolic blood pressure, fasting triglyceride, high-density lipoprotein (HDL) cholesterol, and blood glucose were determined using standard testing procedures. The MetSyn risk factor levels were determined using American Heart Association criteria. Subjects were grouped by position and playing level (HS, College). Independent t-tests, chi-square analysis, 2-way analysis of variance, and path analytic models were used in the statistical analysis. Significance was set at p < 0.05. 6.8% (n = 14) of the sample met the American Heart Association criteria for MetSyn. Offensive and defensive linemen accounted for 92.3% of the players meeting MetSyn criteria with each playing level (HS, College) having 7 subjects. The MetSyn criteria differed significantly across %Fat. Obese players were more likely to meet the criteria for MetSyn. %Fat was a statistically significant predictor of mean arterial blood pressure, HDL cholesterol, and waist circumference. The MetSyn exists in both HS- and College-level football players, with almost all cases occurring in the athletes with the highest levels of %Fat (offensive/defensive lineman). Strength and conditioning coaches should be aware of the prevalence of MetSyn risk factors in offensive and defensive linemen and take appropriate actions to ensure athlete safety.

The effect of active workstation use on measures of cognition, attention, and motor skill.

BACKGROUND: The purpose of this study was to assess participants' ability to perform tasks requiring attention, short term memory, and simple motor skill while sitting, standing or walking at an active workstation. METHODS: Fifty participants completed the Stroop Color Word test (SCWT), Auditory Consonant Trigram test (ACTT), and Digital Finger Tapping test (DFTT) while sitting, standing and walking 1.6 km/h at an active workstation. RESULTS: A significant difference was found for DFTT, but no differences across conditions were found on ACTT or SCWT. Examination of the linear contrasts and post hoc means comparison tests revealed significant differences in DFTT scores between sitting and walking (t = 2.39 (49) P < .02) and standing and walking (t = 2.28 (49) P < .03). These results indicate that adding the walking task to the ACTT and SCWT conditions results in no decrement in performance on these tasks. Conversely, adding the walking task to the DFTT condition results in reduced performance on the DFTT task. CONCLUSIONS: These results further support the potential of active workstations to increase physical activity in the workplace without compromising cognitive capabilities.

The acute effects of static stretching on the sprint performance of collegiate men in the 60- and 100-m dash after a dynamic warm-up.

Previous research has shown that static stretching has an inhibitory effect on sprinting performances up to 50 m. The purpose of this study was to see what would happen to these effects at longer distances such as those seen in competition. This study used a within-subjects design to investigate the effects of passive static stretching vs. no stretching on the 60- and 100-m sprint performance of college track athletes after a dynamic warm-up. Eighteen male subjects completed both the static stretching and the no stretching conditions in counterbalanced order across 2 days of testing. On each day, all subjects first completed a generalized dynamic warm-up routine that included a self-paced 800-m run, followed by a series of dynamic movements, sprint, and hurdle drills. At the end of this generalized warm-up, athletes were assigned to either a static stretching or a no-stretching condition. They then immediately performed 2 100-m trials with timing gates set up at 20, 40, 60, and 100 m. Results revealed a significant slowing in performance with static stretching (p < 0.039) in the second 20 (20-40) m of the sprint trials. After the first 40 m, static stretching exhibited no additional inhibition of performance in a 100-m sprint. However, although there was no additional time loss, athletes never gained back the time that was originally lost in the first portion of the trials. Therefore, in strict terms of performance, it seems harmful to include static stretching in the warm-up protocol of collegiate male sprinters in distances up to 100 m.

The effect of ball-carrying technique and experience on sprinting in rugby union.

There are several ways of carrying the ball in rugby union, which could influence the speed at which a player can run. We assessed 52 rugby players (34 males, 18 females) during a maximum sprint over 30 m without the ball, with the ball under one arm, and with the ball in both hands. Timing gates were used to measure time over the initial 10 m and the last 20 m. It has previously been reported (Grant et al., 2003) that running with the ball produces a slower sprinting speed than running without the ball. We hypothesized that the decrease in speed caused by carrying the ball would become less marked with the experience of the player. The male and female players were each divided into two groups: a "beginner" group that consisted of players in their first or second season and an "experienced" group that was composed of players who had played for more than two seasons. A 2 x 3 mixed-model analysis of variance was used to identify differences (P < 0.01) between the beginner and experienced groups in the three sprinting conditions. The times for the males for the first 10 m sprints without the ball, with the ball under one arm, and with the ball in both hands were 1.87 +/- 0.08 s, 1.87 +/- 0.08 s, and 1.91 +/- 0.1 s for the beginners, and 1.87 +/- 0.1, 1.88 +/- 0.1 and 1.88 +/- 0.12 for the more experienced players respectively. The times for the females for the first 10 m without the ball, with the ball under one arm, and with the ball in both hands were 2.13 +/- 0.16 s, 2.19 +/- 0.17 s, and 2.20 +/- 0.16 s for the beginners, and 2.03 +/- 0.12 s, 2.03 +/- 0.09 s, and 2.04 +/- 0.1 s for the more experienced players respectively. For the last 20 m of the 30-m sprint, there were differences between the different sprint conditions (P < 0.001) but no differences that were attributable to experience (P = 0.297). The times for the males over the last 20 m without the ball, with the ball under one arm, and with the ball in both hands were 2.58 +/- 0.19 s, 2.61 +/- 0.12 s, and 2.65 +/- 0.12 s for the beginners, and 2.59 +/- 0.12, 2.62 +/- 0.23, and 2.65 +/- 0.18 s for the more experienced players respectively. The times for the females over the last 20 m without the ball, with the ball under one arm, and with the ball in both hands were 3.25 +/- 0.38 s, 3.35 +/- 0.42 s, and 3.40 +/- 0.46 s for the beginners, and 3.04 +/- 0.32 s, 3.06 +/- 0.22 s, and 3.13 +/- 0.27 s for the more experienced players respectively. No gender-specific differences were detected. The results of this study suggest that practising sprints while carrying a ball benefits the early phase of sprinting while carrying the ball.

Heart rate monitoring as a measure of physical activity in children.

PURPOSE: Using a larger sample and broader range of activities than most previous investigations of HR monitoring, this study examined the need for individual calibration of the HR-VO2 prediction equation, the effect of including low-intensity activities when establishing the HR-VO2 equation, comparisons of different methods for calculating HR-VO2 prediction equations for maximum energy expenditure (EE) variance, and the effect of these different methods when applied to free-living HR data. METHODS: Forty-three children ages 8 to 12 completed laboratory assessments of the relationship between HR and VO2. Different methods of estimating daily EE were applied to free-living HR data collected from 37 of these children. RESULTS: There was significant individual variation in the HR-VO2 prediction equations. HR monitoring predicted VO2 during low-intensity activities, below most established cut points. Individual differences persisted during both high- and low-intensity activities. Although a HR-VO2 prediction equation generated from the group accounted for 85% of the variance in EE, significant improvements in prediction were achieved with individualized HR-VO2 prediction equations that took into account low-intensity activity levels. CONCLUSION: Generic equations derived from group data may be suitable for some applications. However, for investigators requiring more precision, individual HR-VO2 equations significantly improve prediction.