Peter Collins, Yahya Al-Nakeeb and Mark Lyons
Active school commuting is widely regarded as a key opportunity for youth to participate in physical activity (PA). However, the accurate measurement of the commute home from school and its contribution to total free-living moderateto- vigorous PA (MVPA) is relatively unexplored.
Seventy-five adolescents (38 males, 37 females) wore an integrated GPS and heart rate device during after-school hours for 4 consecutive weekdays.
Active commuters were significantly more active (11.72 minutes MVPA) than passive commuters (3.5 minutes MVPA) during their commute home from school (P = .001). The commute home of walkers and cyclists on average contributed 35% of their total free-living PA. However, there was no significant difference in the overall free-living PA levels of passive and active commuters (P > .05). A total 92.7% of the youth living within 1.5 miles of the school actively commuted, compared with 16.7% of the youth who lived further away. Socioeconomic differences in commuting patterns were also evident.
The findings highlighted the significant proportion of total free-living PA that was attributed to active commuting home from school. The study demonstrates the usefulness of utilizing GPS and heart rate data to accurately track young people’s after-school PA. Demographic influences and implications for future research are discussed.
Peter Brubaker, Cemal Ozemek, Alimer Gonzalez, Stephen Wiley and Gregory Collins
Underwater treadmill (UTM) exercise is being used with increased frequency for rehabilitation of injured athletes, yet there has been little research conducted on this modality.
To determine the cardiorespiratory responses of UTM vs land treadmill (LTM) exercise, particularly with respect to the relationship between heart rate (HR) and oxygen consumption (VO2).
Design and Setting:
This quantitative original research took place in sports medicine and athletic training facilities at Wake Forest University.
11 Wake Forest University student athletes (20.8 ± 0.6 y, 6 women and 5 men).
All participants completed the UTM and LTM exercise-testing protocols in random order. After 5 min of standing rest, both UTM and LTM protocols had 4 stages of increasing belt speed (2.3, 4.9, 7.3, and 9.6 km/h) followed by 3 exercise stages at 9.6 km/h with increasing water-jet resistance (30%, 40%, and 50% of jet capacity) or inclines (1%, 2%, and 4% grade).
Main Outcome Measures:
A Cosmed K4b2 device with Polar monitor was used to collect HR, ventilation (Ve), tidal volume (TV), breathing frequency (Bf), and VO2 every minute. Ratings of perceived exertion (RPE) were also obtained each minute.
There was no significant difference between UTM and LTM for VO2 at rest or during any stage of exercise except stage 3. Furthermore, there were no significant differences between UTM and LTM for HR, Ve, Bf, and RPE on any exercise stage. Linear regression of HR vs VO2, across all stages of exercise, indicates a similar relationship in these variables during UTM (r = .94, y = .269x − 10.86) and LTM (r = .95, y = .291x − 12.98).
These data indicate that UTM and LTM exercise elicits similar cardiorespiratory responses and that HR can be used to guide appropriate exercise intensity for college athletes during UTM.
Stephen Zwolinsky, James McKenna, Andy Pringle, Paul Widdop, Claire Griffiths, Michelle Mellis, Zoe Rutherford and Peter Collins
Increasingly the health impacts of physical inactivity are being distinguished from those of sedentary behavior. Nevertheless, deleterious health prognoses occur when these behaviors combine, making it a Public Health priority to establish the numbers and salient identifying factors of people who live with this injurious combination.
Using an observational between-subjects design, a nonprobability sample of 22,836 participants provided data on total daily activity. A 2-step hierarchical cluster analysis identified the optimal number of clusters and the subset of distinguishing variables. Univariate analyses assessed significant cluster differences.
High levels of sitting clustered with low physical activity. The Ambulatory & Active cluster (n = 6254) sat for 2.5 to 5 h·d−1 and were highly active. They were significantly younger, included a greater proportion of males and reported low Indices of Multiple Deprivation compared with other clusters. Conversely, the Sedentary & Low Active cluster (n = 6286) achieved ≤60 MET·min·wk−1 of physical activity and sat for ≥8 h·d−1. They were the oldest cluster, housed the largest proportion of females and reported moderate Indices of Multiple Deprivation.
Public Health systems may benefit from developing policy and interventions that do more to limit sedentary behavior and encourage light intensity activity in its place.