Article Text
Abstract
Background Few studies have explored the impact of environmental change on walking using controlled comparisons. Even fewer have examined whose behaviour changes and how. In a natural experimental study of new walking and cycling infrastructure, we explored changes in walking, identified groups who changed in similar ways and assessed whether exposure to the infrastructure was associated with trajectories of walking.
Methods 1257 adults completed annual surveys assessing walking, sociodemographic and health characteristics and use of the infrastructure (2010–2012). Residential proximity to the new routes was assessed objectively. We used latent growth curve models to assess change in total walking, walking for recreation and for transport, used simple descriptive analysis and latent class analysis (LCA) to identify groups who changed in similar ways and examined factors associated with group membership using multinomial regression.
Results LCA identified five trajectories, characterised by consistently low levels; consistently high levels; decreases; short-lived increases; and sustained increases. Those with lower levels of education and lower incomes were more likely to show both short-lived and sustained increases in walking for transport. However, those with lower levels of education were less likely to take up walking. Proximity to the intervention was associated with both uptake of and short-lived increases in walking for transport.
Conclusions Environmental improvement encouraged the less active to take up walking for transport, as well as encouraging those who were already active to walk more. Further research should disentangle the role of socioeconomic characteristics in determining use of new environments and changes in walking.
- Epidemiological methods
- Health inequalities
- Neighborhood/place
- PHYSICAL ACTIVITY
- PUBLIC HEALTH
This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
Statistics from Altmetric.com
Footnotes
Contributors JP and DO designed the analysis. JP analysed the data. Both interpreted the data, drafted the article and revised it critically for important intellectual content, and approved the final version of the submitted manuscript.
Funding This paper was written on behalf of the iConnect consortium (http://www.iconnect.ac.uk; Christian Brand, Fiona Bull, Ashley Cooper, Andy Day, Nanette Mutrie, David Ogilvie, Jane Powell, John Preston and Harry Rutter). The iConnect consortium was funded by the Engineering and Physical Sciences Research Council (grant reference EP/G00059X/1). DO and JP are supported by the Medical Research Council (Unit Programme number MC_UU_12015/6). JP's contribution to this study was supported by an NIHR Post-Doctoral Research Fellowship (PDF-2012-05-157). The views and opinions expressed in this article are those of the authors and do not necessarily reflect those of the EPSRC, NIHR, Department of Health or other funders, which had no role in the conduct of the study or in the writing of the report.
Competing interests None declared.
Ethics approval The University of Southampton Research Ethics Committee granted ethical approval (CEE200809-15).
Provenance and peer review Not commissioned; externally peer reviewed.