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Articles

Multidimensional prediction of work traffic crashes among Spanish professional drivers in cargo and passenger transportation

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 20-27 | Published online: 10 Apr 2020
 

Abstract

The aim of this study was to examine the effect of different environmental, mechanical and individual factors associated with fatalities and serious injuries caused by work traffic accidents among cargo and passenger transport drivers (CPTD) in Spain. For this cross-sectional study, national data on work traffic accidents collected in Spain during the last 3 years were analyzed through a regression modeling approach, in order to predict the severity of traffic crashes involving CPTD. Using binary logistic regression analyses, it was found that the type of road and accident, the meteorological, light and vehicle conditions, individual characteristics and risky driving behaviors significantly predict the risk of fatal work traffic accidents and serious injuries. These findings highlight the importance of combining organizational efforts with national road safety policies in order to generate a traffic safety culture among CPTD.

Acknowledgements

The authors thank the Directorate General of Traffic (DGT) (Government of Spain) for providing the data and the analysis tools needed to perform the in-depth research. The authors also wish to thank Dr Ariel Ortiz for his technical support, the INTRAS and PRAX staff for the technical advice provided to the study, and Runa Falzolgher for the professional editing and proofreading of the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

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