Literature DB >> 32253257

How does mode of travel affect risks posed to other road users? An analysis of English road fatality data, incorporating gender and road type.

Rachel Aldred1, Rob Johnson2, Christopher Jackson3, James Woodcock4.   

Abstract

BACKGROUND: Most analysis of road injuries examines the risk experienced by people using different modes of transport, for instance, pedestrian fatalities per-head or per-km. A small but growing field analyses the impact that the use of different transport modes has on other road users, for instance, injuries to others per-km driven.
METHODS: This paper moves the analysis of risk posed to others forward by comparing six different vehicular modes, separating road types (major vs minor roads in urban vs rural settings). The comparison of risk posed by men and women for all these modes is also novel.
RESULTS: Per-vehicle kilometre, buses and lorries pose much the highest risk to others, while cycles pose the lowest. Motorcycles pose a substantially higher per-km risk to others than cars. The fatality risk posed by cars or vans to ORUs per km is higher in rural areas. Risk posed is generally higher on major roads, although not in the case of lorries, suggesting a link to higher speeds. Men pose higher per-km risk to others than women for all modes except buses, as well as being over-represented among users of the most dangerous vehicles.
CONCLUSIONS: Future research should examine more settings, adjust for spatial and temporal confounders, or examine how infrastructure or route characteristics affect risk posed to others. Although for most victims the other vehicle involved is a car, results suggest policy-makers should also seek to reduce disproportionate risks posed by the more dangerous vehicles, for instance, by discouraging motorcycling. Finally, given higher risk posed to others by men across five of six modes analysed, policy-makers should consider how to reduce persistent large gender imbalances in jobs involving driving. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Entities:  

Keywords:  bicycle; cross sectional study; driver; motor vehicle occupant; passenger; pedestrian

Mesh:

Year:  2020        PMID: 32253257      PMCID: PMC7848050          DOI: 10.1136/injuryprev-2019-043534

Source DB:  PubMed          Journal:  Inj Prev        ISSN: 1353-8047            Impact factor:   2.399


  11 in total

1.  Risks older drivers face themselves and threats they pose to other road users.

Authors:  L Evans
Journal:  Int J Epidemiol       Date:  2000-04       Impact factor: 7.196

2.  Age and gender differences in risk-taking behaviour as an explanation for high incidence of motor vehicle crashes as a driver in young males.

Authors:  Cathy Turner; Rod McClure
Journal:  Inj Control Saf Promot       Date:  2003-09

3.  Risks older drivers pose to themselves and to other road users.

Authors:  Brian C Tefft
Journal:  J Safety Res       Date:  2008-11-24

4.  Crash risk: How cycling flow can help explain crash data.

Authors:  Marco Dozza
Journal:  Accid Anal Prev       Date:  2016-05-12

5.  Analysis of factors that increase motorcycle rider risk compared to car driver risk.

Authors:  Michael D Keall; Stuart Newstead
Journal:  Accid Anal Prev       Date:  2011-07-28

6.  Deaths of cyclists in London: trends from 1992 to 2006.

Authors:  Andrei S Morgan; Helen B Dale; William E Lee; Phil J Edwards
Journal:  BMC Public Health       Date:  2010-11-15       Impact factor: 3.295

7.  How exposure information can enhance our understanding of child traffic "death leagues".

Authors:  Nicola Christie; Sally Cairns; Elizabeth Towner; Heather Ward
Journal:  Inj Prev       Date:  2007-04       Impact factor: 2.399

8.  Gender Effects in Young Road Users on Road Safety Attitudes, Behaviors and Risk Perception.

Authors:  Pierluigi Cordellieri; Francesca Baralla; Fabio Ferlazzo; Roberto Sgalla; Laura Piccardi; Anna Maria Giannini
Journal:  Front Psychol       Date:  2016-09-27

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

Authors:  Rachel Aldred; Anna Goodman; John Gulliver; James Woodcock
Journal:  Accid Anal Prev       Date:  2018-04-13

10.  Health impact modelling of active travel visions for England and Wales using an Integrated Transport and Health Impact Modelling Tool (ITHIM).

Authors:  James Woodcock; Moshe Givoni; Andrei Scott Morgan
Journal:  PLoS One       Date:  2013-01-09       Impact factor: 3.240

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  3 in total

1.  Fatality risk and issues of inequity among vulnerable road users in South Africa.

Authors:  Anesh Sukhai; Rajen Govender; Ashley van Niekerk
Journal:  PLoS One       Date:  2021-12-31       Impact factor: 3.240

2.  Dizziness and Driving From a Patient Perspective.

Authors:  Roeland B van Leeuwen; Tjard R Schermer; Carla Colijn; Tjasse D Bruintjes
Journal:  Front Neurol       Date:  2021-07-01       Impact factor: 4.003

3.  Health, environmental and distributional impacts of cycling uptake: The model underlying the Propensity to Cycle tool for England and Wales.

Authors:  James Woodcock; Rachel Aldred; Robin Lovelace; Tessa Strain; Anna Goodman
Journal:  J Transp Health       Date:  2021-09
  3 in total

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