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Quantifying the influence of safe road systems and legal licensing age on road mortality among young adolescents :  steps towards system thinking

In: Accident analysis & prevention. Volume 74, (January 2015), pages 306–313

Authors: Divera Twisk, Jacques J.F. Commandeur, Niels Bos, Jean T. Shopeb, Gerjo Kok

Based on existing literature, a system thinking approach was used to set up a conceptual model on the interrelationships among the components influencing adolescent road mortality, distinguishing between components at the individual level and at the system level. At the individual level the role of risk behaviour (sometimes deliberate and sometimes from inexperience or other non-deliberate causes) in adolescent road mortality is well documented. However, little is known about the extent to which the ‘road system’ itself may also have an impact on younger adolescents’ road mortality. This, by providing a safe or unsafe road environment for all road users (System-induced exposure) and by allowing access to high-risk vehicles at a young or older age through the legal licensing age. This study seeks to explore these relationships by analysing the extent to which the road mortality of 10 to 17 year olds in various jurisdictions can be predicted from the System-induced Exposure (SiE) in a jurisdiction and from its legal licensing age to drive motor vehicles. SiE was operationalized as the number of road fatalities per 105 inhabitants/all ages together, but excluding the 10 to 17 year olds. Data on road fatalities during the years 2001 through 2008 were obtained from the OECD International Road Traffic Accident Database (IRTAD) and from the USA NHTSA's Fatality Analysis Reporting System (FARS) database for 29 early and 10 late licensing jurisdictions. Linear mixed models were fitted with annual ‘Adolescent road mortality per capita’ for 2001 through 2008 as the dependent variable, and time-dependent ‘SiE’ and time-independent ‘Licensing system’ as predictor variables. To control for different levels of motorisation, the time-dependent variable ‘Annual per capita vehicle distance travelled’ was used as a covariate.