Direct observations of active school transportation and stroller use in kindergarten children

Patterns of Active Commuting to School in Spanish Preschool Children and Its Associations with Socio-Economic Factors: The PREFIT Project

The aims of this study were to describe patterns of active commuting to school (ACS) of preschool children, and to analyse the relationship between ACS and family socio-economic factors. A total of 2636 families of preschoolers (3-to-5 years old) were asked to complete a questionnaire at home about the mode of commuting to school of their children and marital status, educational level, and profession of both father and mother. Chi-square analyses were applied to compare ACS between school grades and gender of the children. To analyse the association of ACS with socio-economic factors, logistic regression analyses were performed. Almost 50% of participants reported ACS of their offspring, with a higher rate in 3rd preprimary grade (5 years old) than in 1st and 2nd preprimary grades (3- and 4-years old. All, p < 0.05). Those preschool children who had parents with lower educational level and no managerial work had higher odds to ACS than those who had parents with higher educational level and managerial work (all, p ≤ 0.001). Around half of the Spanish preschool children included in this study commuted actively to school and families with lower educational levels or worse employment situation were related to active commuting to school.

Getting at Mode Share: Comparing 3 Methods of Travel Mode Measurement for School Travel Research

BACKGROUND

Mode share is an important metric for active school travel programs. Common methods for measuring mode share include Hands Up surveys and family surveys, but these require teacher and parental involvement. We used these methods as part of an evaluation of a school-based bicycle training program, and added a novel observational count approach. This paper compares mode share results across the 3 methods.

METHODS

We collected data over 2015-2017 at 16 elementary schools. Our outcome of interest was mode share (walk, drive, and bicycle).

RESULTS

We found variations in travel mode estimates between methods and across schools. Overall most school journeys were made by walking (55.7% by observational counts, 46.3% by Hands Up surveys, and 51.5% by family surveys) or car (42.5%, 51.4%, and 46.2%, respectively), and a small proportion by bicycle (1.8%, 2.3%, and 2.2%, respectively). At individual schools, Hands Up and family survey results were similar; there was less agreement between these and observational counts.

CONCLUSION

School travel practitioners face pragmatic choices in data collection. Observational counts are a nonintrusive method suited for school-wide travel patterns. Hands up and family surveys may be more appropriate for assessing differences between classrooms, ages, or family characteristics.