Research Study Abstract

Demographic, Physical Activity, and Route Characteristics Related to School Transportation: An Exploratory Study

  • Presented on February 26 2013

Background and Purpose Active travel to school has been widely promoted as a means to reverse the obesity epidemic. Abundant evidence indicates built environments influence parental decisions on children’s school commuting mode. There has been a growing interest in using portable instruments such as Global Positioning System (GPS) units and accelerometers for capturing more objective and detailed information about the spatial and temporal patterns of physical activity and school commuting behaviors than what can be captured from self-reports especially from children. However, due to the complexity in processing and analyzing the data from these units, empirical studies are still limited.

Objectives By using both the GPS and accelerometer units, the purpose of this study was to investigate the characteristics of children’s home-to-school and school-to-home travels, in terms of demographic, physical activity, and route characteristics. This study assessed the contribution of active travel modes to the overall daily moderate-tovigorous physical activity (MVPA), and variations in school trip characteristics by community settings.

Methods A total of 113 children from 18 elementary schools in the Austin Independent School District in Texas were recruited between fall of 2009 and spring of 2011. Children wore both the GPS watch (Garmin Forerunner) and the accelerometer unit (ActiGraph GT3X) for seven consecutive days and recorded daily travel logs, with parental assistance. Parents completed a survey including school travel, demographic, physical activity, and environmental perception data. From the time-synthesized GPS and accelerometer data, home-school trips were extracted and validated by comparing with the travel log data. All validated trips were then mapped, analyzed, and summarized in Geographic Information System (GIS) software. Minutes of daily MVPA and total accumulated MVPA from active travels were calculated from the accelerometer data. Statistical analyses involved chi-square, ttest, and ANOVA.

Results Demographic Characteristics: The average age was 9.5 years; 50.8% were girls; and 58.3% were of Hispanic origin. Half of the children qualified for the free or reduced price lunch program indicating a lower economic status. Active travel modes were more popular among boys (37% vs. 31%) and Whites (40% vs. 29%), compared with girls and Hispanics. Route/Trip Characteristics: A total of 438 trips from 305 person-days were extracted. Automobiles (private car and school bus) accounted for 61.4% of the total trips, while walking and bicycling accounted for 34.9% and 3.7% respectively. Average trip lengths for driving, walking and bicycling were 2.5, 0.43, and 0.66 miles. Home-to-school trips were more direct and faster (1.38 miles and 7.4 minutes) while school-tohome trips involve more intermediate stops (72% involving at least one stop) and are longer (2.04 miles and 12.1). Common stopping points included a friends’ house, shopping center, grocery store, convenience store, and fast food restaurants. in terms of the route directness (airline distance divided by actual traveled distance between homes and schools), walking trips were more direct than driving trips (0.74 vs. 0.66), and home-to-school trips were more direct than school-to home trips (0.73 vs. 0.64).The 18 study schools were classified into four community settings based on demographic and socioeconomic characteristics of the neighborhood and travel characteristics varied across the settings. Participants from ‘low income, inner-city community’ had a lower share of active travel modes (11%) and longer trips on average (2.36 miles). The ‘urban middle income’ setting included 38% of active trips, were the shortest (1.15 miles), and most direct (0.73). The ‘suburban high income’ setting also had a high share of active modes (35%), despite the longest trip length and duration (2.52 miles and 12.3 minutes). Physical Activity Characteristics: Average daily MVPA was 34.6 minutes, and walkers had 10 more minutes than non-walkers (39.1 vs. 28.7). The average contribution of school travels toward the total daily MVPA was 33.5%, and it was higher among more sedentary children. for example, students with 10 minutes of total daily MVPA had seven minutes (70%) from school travels, while students with one hour of daily MVPA had nine minutes (15%) from school travels.

Conclusions Objective and detailed data from GPS and accelerometer units appear useful in providing information about route/trip characteristics and physical activity implications related to school transportation. Results from these data can guide the future development of policy and environmental interventions, by helping to determine: (a) walkable distances by different settings and student groups, (b) types of attractive destinations (land uses) near school to promote active and efficient trip-chaining behaviors, (c) the contribution of school travel to the overall daily MVPA for assessing health benefits of active school travels, and (d) specific and modifiable built environmental characteristics of the home-school routes that support walking and bicycling. Findings from this exploratory study also suggested that active travel to school is a valuable means to promote physical activity, especially among the sedentary children.

References 1. Cooper, A. R., A. S. Page, B. W. Wheeler, P. Griew, L. Davis, M. Hillsdon & R. Jago (2010) Mapping the walk to school using accelerometry combined with a global positioning system. American Journal of Preventive Medicine, 38, 178-183. 2. Oliver, M., H. Badland, S. Mavoa, M. J. Duncan & S. Duncan (2010) Combining GPS, GIS, and Accelerometry: Methodological Issues in the Assessment of Location and Intensity of Travel Behaviors. Journal of Physical Activity and Health, 7, 102-108.

Support/Funding Source This study was funded by a grant from the Robert Wood Johnson Foundation’s Active Living Research program (Grant ID: 65539).

Presented at

Active Living Research 2013 Annual Conference


, ,