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social, economic and demographic characteristics of neighbourhoods where  road users live

               (Warsh et al., 2009; Cottrill and Thakuriah, 2010; Schneider et al., 2010).


               The socioeconomic status (SES) of a person is one of the most fundamental determinants of
               his or her health outcomes. The importance of social, physical, economic and environmental

               factors in determining health outcomes has been identified in many studies (National Health
               Committee,  1988;  Carroll  et  al.,  1993;  Link  and  Phelan,  1995).  The  social  influences

               examined include a range of inter-related factors, such as education, employment, occupation

               and  working  conditions,  income,  and  housing.  However,  the  influence  of  SES  on  health
               outcomes of traffic accidents has been examined in only a few studies  and only a limited

               number of factors have been explored.


               Therefore, the objective of this research is to identify factors contributing to the severity of

               crashes  involving  heavy  vehicles.  In  addition  to  the  usual  contributing  factors,  such  as
               roadway, environment, road user and vehicle factors, this study examines the influence of

               social and demographic characteristics of the neighbourhood where road users live and where
               crashes  occur  in  the  State  of  Victoria,  Australia,  using  the  multinomial  logit  model.  This

               study will contribute to advancing knowledge in the field, as little research has been done on

               the contribution of the socio-demographic characteristics of the neighbourhoods where road
               users live and where crashes occur.


               The  remaining  chapter  is  organised  as  follows.  In  the  next  section,  the  data  used  in  this

               research and the estimation model are presented. The results are discussed in Section 4.3, and
               the last section provides some concluding remarks.



               4.2     Methods



               4.2.1  Data



               The primary data used in this study were provided by VicRoads and contained information

               on  all  police-reported  collisions  in  Victoria,  Australia.  The  data  provided  included
               information  on  environmental,  temporal,  road  user,  road,  and  vehicle  characteristics.  In



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