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Cycling injury risk in London: A case-control study exploring the impact of cycle volumes, motor vehicle volumes, and road characteristics including speed limits.

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journal contribution
posted on 25.07.2019, 15:08 by Rachel Aldred, Anna Goodman, John Gulliver, James Woodcock
Cycling injury risk is an important topic, but few studies explore cycling risk in relation to exposure. This is largely because of a lack of exposure data, in other words how much cycling is done at different locations. This paper helps to fill this gap. It reports a case-control study of cycling injuries in London in 2013-2014, using modelled cyclist flow data alongside datasets covering some characteristics of the London route network. A multilevel binary logistic regression model is used to investigate factors associated with injury risk, comparing injury sites with control sites selected using the modelled flow data. Findings provide support for 'safety in numbers': for each increase of a natural logarithmic unit (2.71828) in cycling flows, an 18% decrease in injury odds was found. Conversely, increased motor traffic volume is associated with higher odds of cycling injury, with one logarithmic unit increase associated with a 31% increase in injury odds. Twenty-mile per hour compared with 30mph speed limits were associated with 21% lower injury odds. Residential streets were associated with reduced injury odds, and junctions with substantially higher injury odds. Bus lanes do not affect injury odds once other factors are controlled for. These data suggest that speed limits of 20 mph may reduce cycling injury risk, as may motor traffic reduction. Further, building cycle routes that generate new cycle trips should generate 'safety in numbers' benefits.

Funding

JW, AG, and JG were partially supported on this work by the METAHIT project funded by the Medical Research Council (MR/P02663X/1). JW and AG’s work occurred under the auspices of the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence funded by the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research (NIHR), Health Research (NIHR) and the Wellcome Trust (MR/K023187/1).

History

Citation

Accident Analysis and Prevention, 2018, 117, pp. 75-84

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/School of Geography, Geology and the Environment

Version

VoR (Version of Record)

Published in

Accident Analysis and Prevention

Publisher

Elsevier, Association for the Advancement of Automative Medicine

eissn

1879-2057

Acceptance date

01/03/2018

Copyright date

2018

Available date

25/07/2019

Publisher version

https://www.sciencedirect.com/science/article/pii/S0001457518301076?via=ihub

Language

en