Abstract
The increase in average distance from home to secondary school over recent decades has been accompanied by a significant growth in the proportion of pupils travelling to school by motorized means as opposed to walking or cycling. More recently this switch in travel mode has received considerable attention as declining levels of physical activity, growing car dependence and the childhood obesity “crisis” have pushed concerns about the health of future generations up the public health agenda, particularly in the U.S., but also in the UK and Europe. This has led to a proliferation of international studies researching a variety of individual, school and spatial characteristics associated with children's active travel to school which has been targeted by some governments as a potential silver bullet to reverse the trend. However, to date national pupil census data, which comprises annual data on all English pupils, including a mode of travel to school variable, has been under-utilised in the analysis of how pupils commute to school. Furthermore, methodologically, the grouped nature of the data with pupils clustered within both schools and residential neighbourhoods has often been ignored - an omission which can have considerable consequences for the statistical estimation of the model. The research presented here seeks to address both of these points by analysing pupil census data on all 26,709 secondary pupils (aged 11–16) who attended schools in Sheffield, UK during the 2009–10 school year. Individual pupil data is grouped within school, and neighbourhood, within a cross-classified multilevel model of active versus motorised modes of commuting to school. The results support the findings of other research that distance to school is key, but suggest that sociospatial clustering within neighbourhoods and schools is also critical. A further finding is that distance to school varies significantly by ethnicity, with white British pupils travelling the shortest distance of all ethnic groups. The implications of these findings for education and transport policy are discussed.
Highlights
In the mid-1980s the mean distance travelled to school by 11-16 year olds in the UK was just over 2 miles; by 2013 this had almost doubled, increasing to 3.7 miles (Department for Transport, 2013)
For pupils living less than one mile from school, 82% walked, this represents a very substantial decline over the last three decades, comparing to over 94% of high school pupils aged 11-17 in 1975/6 (Rigby, 1979)
This finding highlights the high levels of autocorrelation that exist across residential space as well as within educational institutions, and the consequent importance of taking the sociospatial clustering of individual pupils into account in any examination of school travel patterns
Summary
In the mid-1980s the mean distance travelled to school by 11-16 year olds in the UK was just over 2 miles; by 2013 this had almost doubled, increasing to 3.7 miles (Department for Transport, 2013). This lengthening of the high school commute has been influenced by some of the urban-structural processes which have occurred over the past 50 years. The suburbanisation and decentralisation in many cities have dispersed some school-aged children to family housing in low density new-build housing estates on the outskirts of cities (Hoare, 1975), which involves both longer travel distances and an urban form that favours car use (Dieleman et al, 2002, Newman and Kenworthy, 2006). In recent studies it has been estimated that less than half of all school-age children attend their nearest school (Allen, 2007, Ferrari and Green, 2013)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
