Bicyclist injury severities in bicycle-motor vehicle accidents.

Washington University in St. Louis, Department of Civil Engineering, Campus Box 1130, One Brookings Drive, St. Louis, MO 63130-4899, USA.
Accident Analysis & Prevention (Impact Factor: 1.87). 04/2007; 39(2):238-51. DOI: 10.1016/j.aap.2006.07.002
Source: PubMed

ABSTRACT This research explores the factors contributing to the injury severity of bicyclists in bicycle-motor vehicle accidents using a multinomial logit model. The model predicts the probability of four injury severity outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. The analysis is based on police-reported accident data between 1997 and 2002 from North Carolina, USA. The results show several factors which more than double the probability of a bicyclist suffering a fatal injury in an accident, all other things being kept constant. Notably, inclement weather, darkness with no streetlights, a.m. peak (06:00 a.m. to 09:59 a.m.), head-on collision, speeding-involved, vehicle speeds above 48.3 km/h (30 mph), truck involved, intoxicated driver, bicyclist age 55 or over, and intoxicated bicyclist. The largest effect is caused when estimated vehicle speed prior to impact is greater than 80.5 km/h (50 mph), where the probability of fatal injury increases more than 16-fold. Speed also shows a threshold effect at 32.2 km/h (20 mph), which supports the commonly used 30km/h speed limit in residential neighborhoods. The results also imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault.

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    ABSTRACT: To examine the relationship between cycling injury severity and personal, trip, route and crash characteristics. Data from a previous study of injury risk, conducted in Toronto and Vancouver, Canada, were used to classify injury severity using four metrics: (1) did not continue trip by bike; (2) transported to hospital by ambulance; (3) admitted to hospital; and (4) Canadian Triage and Acuity Scale (CTAS). Multiple logistic regression was used to examine associations with personal, trip, route and crash characteristics. Of 683 adults injured while cycling, 528 did not continue their trip by bike, 251 were transported by ambulance and 60 were admitted to hospital for further treatment. Treatment urgencies included 75 as CTAS=1 or 2 (most medically urgent), 284 as CTAS=3, and 320 as CTAS=4 or 5 (least medically urgent). Older age and collision with a motor vehicle were consistently associated with increased severity in all four metrics and statistically significant in three each (both variables with ambulance transport and CTAS; age with hospital admission; and motor vehicle collision with did not continue by bike). Other factors were consistently associated with more severe injuries, but statistically significant in one metric each: downhill grades; higher motor vehicle speeds; sidewalks (these significant for ambulance transport); multiuse paths and local streets (both significant for hospital admission). In two of Canada's largest cities, about one-third of the bicycle crashes were collisions with motor vehicles and the resulting injuries were more severe than in other crash circumstances, underscoring the importance of separating cyclists from motor vehicle traffic. Our results also suggest that bicycling injury severity and injury risk would be reduced on facilities that minimise slopes, have lower vehicle speeds, and that are designed for bicycling rather than shared with pedestrians. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to
    BMJ Open 01/2015; 5(1):e006654. · 2.06 Impact Factor
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    ABSTRACT: Purpose To identify how person, crash, environment, and population characteristics differ between bicycle-motor vehicle crashes that occur at intersections and non-intersections. Methods The Iowa Department of Transportation crash database for the years 2001 through 2011 was used to identify bicycle-motor vehicle (BMV) crashes and associated person, crash, and environment characteristics. Population-level data were drawn from the 2010 U.S. Census and the 2010 American Community Survey. Descriptive statistics, GIS mapping, and multivariable logistic regression were used to examine factors associated with crash risk and crash location. Results Compared to intersections, non-intersection BMV crashes had higher odds of involving young bicyclists (<10 years old; OR: 1.8, 95%CI: 1.2–2.6), location outside city limits (OR: 5.7, 95%CI: 3.9–8.3), with driver vision obscured (OR: 1.5, 95% CI: 1.2–1.8), reduced lighting on roadway (OR: 1.9, 95% CI: 1.5–2.4), and lower odds when the bicyclist (OR: 0.4, 95% CI: 0.3–0.6) or motorist (OR: 0.6, 95% CI: 0.4–0.8) failed to yield right of way. Conclusions Environmental factors, as well as developmental (age) and behavioral factors of bicycle-motor vehicle crashes vary by location (intersection/non-intersection). Results from this study can be used to tailor and target multiple intervention approaches, such as making infrastructure changes, increasing safety behavior among both motorists and bicyclists, and identifying which age groups and locations would most benefit from intervention.
    Journal of Transport & Health. 09/2014;
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    ABSTRACT: Use of electrically assisted bicycles with a maximum speed of 25 km/h is rapidly increasing. This growth has been particularly rapid in the Netherlands, yet very little research has been conducted to assess the road safety implications. This case–control study compares the likelihood of crashes for which treatment at an emergency department is needed and injury consequences for electric bicycles to classic bicycles in the Netherlands among users of 16 years and older. Data were gathered through a survey of victims treated at emergency departments. Additionally, a survey of cyclists without any known crash experience, drawn from a panel of the Dutch population acted as a control sample. Logistic regression analysis is used to compare the risk of crashes with electric and classical bicycles requiring treatment at an emergency department. Among the victims treated at an emergency department we compared those being hospitalized to those being send home after the treatment at the emergency department to compare the injury consequences between electric and classical bicycle victims. The results suggest that, after controlling for age, gender and amount of bicycle use, electric bicycle users are more likely to be involved in a crash that requires treatment at an emergency department due to a crash. Crashes with electric bicycles are about equally severe as crashes with classic bicycles. We advise further research to develop policies to minimize the risk and maximize the health benefits for users of electric bicycles.
    Accident Analysis & Prevention 09/2014; 73:174-180. · 1.87 Impact Factor


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