Highlights A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police. A multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. Non-fatal accidents mostly involve private vehicles or occur on local city streets. Control characteristics are not generally effective on decreasing the fatal injuries. This study is the first attempt to use an unordered response model to analyze traffic injuries in Turkey.

    Abstract A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.


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    Titel :

    A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey


    Beteiligte:
    Çelik, Ali Kemal (Autor:in) / Oktay, Erkan (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2014-06-17


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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