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BackgroundCollision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record. On California police reports, relative collision location is recorded using a highway postmile marker or a street intersection. The objective of this study was to create a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies.ResultsGeocoding was completed with a multi-step process. First, pre-processing was performed using a scripting language to clean and standardize street name information. A state highway network with postmile values was then created using a custom tool written in Visual Basic for Applications (VBA) in ArcGIS software. Custom VBA functionality was also used to incorporate the offset direction and distance. Intersection and address geocoding was performed using ArcGIS, StreetMap Pro 2003 digital street network, and Google Earth Pro. A total of 142,007 fatal and severe injury collisions were identified in SWITRS. The geocoding match rate was 99.8% for postmile-coded collisions and 86% for intersection-coded collisions. The overall match rate was 91%.ConclusionsThe availability of geocoded collision data will be beneficial to clinicians, researchers, policymakers, and practitioners in the fields of traffic safety and public health. Potential uses of the data include studies of collision clustering on the highway system, examinations of the associations between collision occurrence and a variety of variables on environmental and social characteristics, including housing and personal demographics, alcohol outlets, schools, and parks. The ability to build maps may be useful in research planning and conduct and in the delivery of information to both technical and non-technical audiences.

Objective:The use of helmets that do not comply with safety standards is common in California. The objective of this study was to describe the use of these nonstandard helmets among San Francisco Bay–area (SFBA) motorcyclists and to identify personal and motorcycle characteristics that are associated with the use of nonstandard helmets. Methods:A survey of 860 SFBA motorcyclists was conducted. Log-binomial regression was used to estimate risk ratios to compare probabilities of nonstandard helmet use. Results:Fifteen percent of motorcyclists reported wearing a nonstandard helmet sometimes or often. BMW riders had the lowest use of nonstandard helmet (5%) and Harley-Davidson riders had the highest use (51%). Among non-Harley-Davidsons, riders of cruiser-style motorcycles were 3.1 times as likely to wear a nonstandard helmet as riders of motorcycles of other styles. African American riders were more than twice as likely to use nonstandard helmets compared to riders with other self-reported race. Discussion:Behavioral countermeasures are needed to improve motorcycle helmet choice in California. This study identified riders of Harley-Davidsons and riders of cruiser-style motorcycles of other brands as potential targets of interventions. [ABSTRACT FROM PUBLISHER]