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RSS FeedsSafety in numbers for cyclists beyond national-level and city-level data: a study on the non-linearity of risk within the city of Hong Kong (Injury Prevention)

 
 

22 november 2016 17:30:27

 
Safety in numbers for cyclists beyond national-level and city-level data: a study on the non-linearity of risk within the city of Hong Kong (Injury Prevention)
 


Objective This paper examines the relationship between bicycle collisions and the amount of cycling at the local level. Most previous research has focused on national and city comparisons, little is known about differences within a city (the mesoscale). Methods This study mainly used three types of data sets relating to bicycle collisions, use of bicycles and local neighbourhood characteristics in Hong Kong. In particular, bicycle usage, measured as bicycle-kilometres travelled, was estimated from travel surveys following the activity-based approach. Negative binomial regression models were established to model the relationship between the amount of cycling and the occurrence of bicycle collisions at the spatial scale of the Tertiary Planning Unit, which is the smallest planning unit of the city. Results The numbers of bicycle collisions went up with the increasing use of bicycles, but the increase in the number of collisions in a given community was less than a linear proportion of the bicycle flow. When other local neighbourhood variables are controlled, the amount of cycling is a statistically significant variable in accounting for the number of collisions. Conclusions Even in a highly motorised city where bicycles are a minor transport mode, cyclists are less likely to be involved in road collisions in communities with higher cycling volume. Since cycling activities are likely to vary within a city, a more local-based approach in promoting cycling is needed. In particular, the higher safety risks in neighbourhoods of low bicycle usage, especially at an initial stage of promoting cycling, need to be addressed properly.


 
124 viewsCategory: Medicine, Pathology
 
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