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Population based case–control study of serious non-fatal motorcycle crashes

BACKGROUND: Motorcycle sales, registration and use are increasing in many countries. The epidemiological literature on risk factors for motorcycle injury is becoming outdated, due to changes in rider demography, licensing regulations, traffic mix and density, road environments, and motorcycle design...

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Detalles Bibliográficos
Autores principales: Day, Lesley, Lenné, Michael G, Symmons, Mark, Hillard, Peter, Newstead, Stuart, Allen, Trevor, McClure, Rod
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599456/
https://www.ncbi.nlm.nih.gov/pubmed/23351603
http://dx.doi.org/10.1186/1471-2458-13-72
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author Day, Lesley
Lenné, Michael G
Symmons, Mark
Hillard, Peter
Newstead, Stuart
Allen, Trevor
McClure, Rod
author_facet Day, Lesley
Lenné, Michael G
Symmons, Mark
Hillard, Peter
Newstead, Stuart
Allen, Trevor
McClure, Rod
author_sort Day, Lesley
collection PubMed
description BACKGROUND: Motorcycle sales, registration and use are increasing in many countries. The epidemiological literature on risk factors for motorcycle injury is becoming outdated, due to changes in rider demography, licensing regulations, traffic mix and density, road environments, and motorcycle designs and technologies. Further, the potential contribution of road infrastructure and travel speed has not yet been examined. METHODS/DESIGN: A population based case–control study together with a nested case-crossover study is planned. Cases will be motorcycle riders who are injured but not killed in a motorcycle crash on a public road within 150 km radius of Melbourne, Australia, and admitted to one of the study hospitals. Controls will be motorcycle riders who ride through the crash site on the same type of day (weekday or weekend) within an hour of the crash time. Data on rider, bike, and trip characteristics will be collected from the participants by questionnaire. Data on crash site characteristics will be collected in a structured site inspection, and travel speed for the cases will be estimated from these data. Travel speed for the controls will be measured prior to recruitment with a radar traffic detection device as they ride through the crash site. Control sites for the case-crossover study will be selected 1 km upstream from the crash site and matched on either intersection status or road curvature (either straight or cornered). If the initial site selected does not match the case site on these characteristics, then the closest matching site on the case route will be selected. Conditional multivariate logistic regression models will be used to compare risk between the matched case and control riders and to examine associations between road infrastructure and road environment characteristics and crash occurrence. Interactions between type of site and speed will be tested to determine if site type is an effect modifier of the relationship between speed and crash risk. The relationship between rider factors and travel speed generally will be assessed by multivariate regression methods. DISCUSSION: In the context of the changing motorcycling environment, this study will provide evidence on contemporary risk factors for serious non-fatal motorcycle crashes.
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spelling pubmed-35994562013-03-17 Population based case–control study of serious non-fatal motorcycle crashes Day, Lesley Lenné, Michael G Symmons, Mark Hillard, Peter Newstead, Stuart Allen, Trevor McClure, Rod BMC Public Health Study Protocol BACKGROUND: Motorcycle sales, registration and use are increasing in many countries. The epidemiological literature on risk factors for motorcycle injury is becoming outdated, due to changes in rider demography, licensing regulations, traffic mix and density, road environments, and motorcycle designs and technologies. Further, the potential contribution of road infrastructure and travel speed has not yet been examined. METHODS/DESIGN: A population based case–control study together with a nested case-crossover study is planned. Cases will be motorcycle riders who are injured but not killed in a motorcycle crash on a public road within 150 km radius of Melbourne, Australia, and admitted to one of the study hospitals. Controls will be motorcycle riders who ride through the crash site on the same type of day (weekday or weekend) within an hour of the crash time. Data on rider, bike, and trip characteristics will be collected from the participants by questionnaire. Data on crash site characteristics will be collected in a structured site inspection, and travel speed for the cases will be estimated from these data. Travel speed for the controls will be measured prior to recruitment with a radar traffic detection device as they ride through the crash site. Control sites for the case-crossover study will be selected 1 km upstream from the crash site and matched on either intersection status or road curvature (either straight or cornered). If the initial site selected does not match the case site on these characteristics, then the closest matching site on the case route will be selected. Conditional multivariate logistic regression models will be used to compare risk between the matched case and control riders and to examine associations between road infrastructure and road environment characteristics and crash occurrence. Interactions between type of site and speed will be tested to determine if site type is an effect modifier of the relationship between speed and crash risk. The relationship between rider factors and travel speed generally will be assessed by multivariate regression methods. DISCUSSION: In the context of the changing motorcycling environment, this study will provide evidence on contemporary risk factors for serious non-fatal motorcycle crashes. BioMed Central 2013-01-25 /pmc/articles/PMC3599456/ /pubmed/23351603 http://dx.doi.org/10.1186/1471-2458-13-72 Text en Copyright ©2013 Day et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Study Protocol
Day, Lesley
Lenné, Michael G
Symmons, Mark
Hillard, Peter
Newstead, Stuart
Allen, Trevor
McClure, Rod
Population based case–control study of serious non-fatal motorcycle crashes
title Population based case–control study of serious non-fatal motorcycle crashes
title_full Population based case–control study of serious non-fatal motorcycle crashes
title_fullStr Population based case–control study of serious non-fatal motorcycle crashes
title_full_unstemmed Population based case–control study of serious non-fatal motorcycle crashes
title_short Population based case–control study of serious non-fatal motorcycle crashes
title_sort population based case–control study of serious non-fatal motorcycle crashes
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599456/
https://www.ncbi.nlm.nih.gov/pubmed/23351603
http://dx.doi.org/10.1186/1471-2458-13-72
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