Download our latest eBook
Clinical Data Capture: Enhancing Conventional Methods with Continuous Digital MeasuresDownload Now
Comparison Of Two Methods Of Estimating Active Commuting In School Children
- Presented on May 30, 2014
Background: Active school travel provides a convenient, daily opportunity to contribute to meeting physical activity guidelines. Accelerometer-based studies of children’s active commuting often use a standardized 60-min estimation method, in which commuting is assumed to occur for an hour before and after school. We developed an individualized method in which school and home arrival time was recorded.
Purpose: To compare the 60-min method to an individualized method for assessing commuting activity in children.
Methods: Children aged 8-10 yr participating in the SE-CAT study (McMinn et al., 2011) wore ActiGraph GT1M accelerometers for 4 weekdays (3 full days and 1 composite day). Each morning, researchers were present to record the school arrival time of each child. Children completed a previously-validated travel diary to report home arrival time. Commuting activity was expressed as total steps and time spent in MVPA. MVPA (4+ METs) was estimated using age-speciﬁc equations (Freedson et al., 1997).
Results: Of 166 participants, 135 met the inclusion criteria for this analysis. The 60-min method gave signiﬁcantly (p<.05) higher mean values for activity during all periods of the daily commute (morning, afternoon, and total commute) compared to the individualized method (Cohen’s d=0.19-0.48). Using Bland-Altman plots, mean and individual inter-method differences were examined and 95% limits of agreement were wide for the total commute (201.51±1036.43 seconds of MVPA and 538±2026 steps). Interestingly, children arrived on average 6 minutes early to school, but individual arrival times were highly variable (range = 74 minutes early to 55 minutes late).
Conclusion: Compared to the individualized method, it appears that the standard 60-min method gives a higher overall estimate of children’s physical activity during the school commute. Additionally, individual differences between the two methods are highly variable. If resources allow, we recommend the individualized method as a more accurate method of determining arrival time, and consequently commuting time. Using newly-available technology such as mobile phone apps, the cost of these recording procedures could be reduced thereby improving feasibility and accuracy in large-scale studies of children’s school travel.