Uncovering the patterns and drivers of children’s active travel through GPS, accelerometer, and GIS integration

Background: The use of time-matched Geographic Positioning Systems (GPS) and accelerometry data holds great promise for better understanding the micro-level environmental factors (street-level features) that influence active travel in populations. However, processing and analyzing these data in ways that yield meaningful insights for answering health and place questions, and inform built environment policy and action, remains challenging.

Purpose: To develop an open-source code that integrates GPS and accelerometer data for exploring the patterns of active travel to/from schools, and associated geospatial factors.

Methods: We developed an open-source, Python-based code integrating QTravel BT-10000 GPS and GT3X-wBT Actigraph device data via temporal matching and used it to process data from the STREETS study, a natural experiment assessing the impact of a Safe Routes to School intervention in Austin, Texas, USA, on active-travel-to-school among elementary school (9-10 years) children living within walking distance of school. Parental surveys and child accelerometer counts were used to calibrate travel mode detection. Routes were geocoded using ArcGIS.

Results: GPS and accelerometer data were processed for 326 participants at baseline, of which 28.2% engaged in at least one walking or cycling trip to/from school during the assessment week. GIS analysis is underway. Preliminary findings suggest that most walking and cycling trips to/from school do not happen in the “fastest/nearest route”, and occur more frequently along routes with high tree canopy and sidewalk coverage, and built-up areas.

Conclusions: This open-source tool provides a novel and valid approach to comprehensively examine children’s interaction patterns with their neighborhood environment while actively commuting to school, and how these interactions influence physical activity and health outcomes.

Practical Implications: This tool and analysis framework can be used to inform urban design standards near school areas to provide all children the opportunity to safely, comfortably, and enjoyably walk or cycle to school.

Funding: NIH R01HD097669.