ArticlePloS one2016
The Association between Regional Environmental Factors and Road Trauma Rates: A Geospatial Analysis of 10 Years of Road Traffic Crashes in British Columbia, Canada.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predicting black ice-related accidents with probabilistic modeling using GIS-based Monte Carlo simulation.PloS one · 2024Article
- Spatial and temporal analysis of road traffic crashes and ambulance responses in Lagos state, Nigeria.BMC public health · 2023Article
- Fatal Road Traffic Accidents and Associated Factors in North Shewa Zone, Central Ethiopia: A Cross-Sectional Study.Ethiopian journal of health sciences · 2023Article
- Investigating the Risk Factors Associated with Injury Severity in Pedestrian Crashes in Santiago, Chile.International journal of environmental research and public health · 2022Article
- Road traffic fatalities in rural and remote Australia from 2006 to 2017: The need for targeted action.The Australian journal of rural health · 2022Article
- ASSESSING THE RELATIONSHIP BETWEEN PHYSICIAN AVAILABILITY AND VIRAL LOAD SUPPRESSION IN BRITISH COLUMBIA.The Canadian geographer. Geographe canadien · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundBritish Columbia, Canada is a geographically large jurisdiction with varied environmental and socio-cultural contexts. This cross-sectional study examined variation in motor vehicle crash rates across 100 police patrols to investigate the association of crashes with key explanatory factors.
methodsEleven crash outcomes (total crashes, injury crashes, fatal crashes, speed related fatal crashes, total fatalities, single-vehicle night-time crashes, rear-end collisions, and collisions involving heavy vehicles, pedestrians, cyclists, or motorcyclists) were identified from police collision reports and insurance claims and mapped to police patrols. Six potential explanatory factors (intensity of traffic law enforcement, speed limits, climate, remoteness, socio-economic factors, and alcohol consumption) were also mapped to police patrols. We then studied the association between crashes and explanatory factors using negative binomial models with crash count per patrol as the response variable and explanatory factors as covariates.
resultsBetween 2003 and 2012 there were 1,434,239 insurance claim collisions, 386,326 police reported crashes, and 3,404 fatal crashes. Across police patrols, there was marked variation in per capita crash rate and in potential explanatory factors. Several factors were associated with crash rates. Percent roads with speed limits ≤ 60 km/hr was positively associated with total crashes, injury crashes, rear end collisions, and collisions involving pedestrians, cyclists, and heavy vehicles; and negatively associated with single vehicle night-time crashes, fatal crashes, fatal speeding crashes, and total fatalities. Higher winter temperature was associated with lower rates of overall collisions, single vehicle night-time collisions, collisions involving heavy vehicles, and total fatalities. Lower socio-economic status was associated with higher rates of injury collisions, pedestrian collisions, fatal speeding collisions, and fatal collisions. Regions with dedicated traffic officers had fewer fatal crashes and fewer fatal speed related crashes but more rear end crashes and more crashes involving cyclists or pedestrians. The number of traffic citations per 1000 drivers was positively associated with total crashes, fatal crashes, total fatalities, fatal speeding crashes, injury crashes, single vehicle night-time crashes, and heavy vehicle crashes. Possible explanations for these associations are discussed.
conclusionsThere is wide variation in per capita rates of motor vehicle crashes across BC police patrols. Some variation is explained by factors such as climate, road type, remoteness, socioeconomic variables, and enforcement intensity. The ability of explanatory factors to predict crash rates would be improved if considered with local traffic volume by all travel modes.
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