Bicyclist fatalities in New York City: 1996-2005

Assessing bicycle safety risks using emerging mobile sensing data

The surge in global electric bicycle ownership has exerted immense pressure on bicycle infrastructure. Theoretically, there's a need to reassess the risk factors associated with multiple bike lane users. Based on this, there's a practical need to re-evaluate the safety and quality of outdated infrastructure. This paper aims to reconsider risk factors related to bicycle infrastructure safety in the context of electric bicycles sharing lanes with traditional bicycles. Moreover, many countries lack precise spatial data concerning bicycle infrastructure. This study introduces a mobile sensing method based on bicycles, aiming to acquire daytime and nighttime bike lane datasets in a cost-effective, efficient, and large-scale manner. A computer vision-based bicycle risk factor assessment model was established, and the distribution of bicycle safety risk factors was visually analyzed. Research data was collected from a representative 59.5-kilometer bicycle lane area in Beijing. The results confirm the significant impact of the surge in electric bicycles, with electric bike users accounting for 72.1% of cyclists, 32.3% wearing helmets, and 8.4% riding against traffic. During the day, the highest-ranking risk factors include the type of bicycle lanes (half lacking dedicated lanes or being shared), roadside parking, and subpar road conditions. At night, insufficient street lighting are notable concerns. The research methodology is easily replicable and can be extended to new multi-user coexistence cycling environments or countries without bicycle spatial data, offering insights for bicycle safety policies and road design.

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Micromobility Vehicles, Obstructions, and Rider Safety Behaviors in New York City Bike Lanes

Micromobility vehicles (MMVs) have become increasingly popular, particularly in urban areas where infrastructure has improved in recent years to facilitate their use. The purpose of this study was to observe protected bike lanes in 10 zones of Manhattan, NYC to: (1) describe the MMVs in bike lanes by type, phone and helmet use; and (2) document MMV users' responses to obstructions. Approximately 1 in 4 of all riders (260/998) were wearing a helmet. Fewer than 2% were observed using a phone while moving. Fewer than 9% of Citi Bike users were wearing a helmet. In contrast, over one-third of non-Citi Bike users were wearing a helmet (228 of 670, 34.03%). This difference was determined to be significant by a chi-squared test (a = 0.05) with a p-value less than 0.0001. Of the 988 MMVs observed in this study, 398 (40.28%) were motorized and 590 (59.72%) were non-motorized. A similar proportion of users of motorized riders versus non-motorized vehicles were wearing a helmet (28.14%, 112/398 versus 24.41%, 144/590). A total of 232 riders (23.50%) encountered an obstruction in their bike lane. Of these obstructions in a bike lane, 82.33% (191/232) were a car/vehicle and 17.67% (41/232) was garbage. A large majority of riders (87.93%) reacted by riding into the traffic lane. These findings suggest that further research and local education, enforcement, and legislative efforts are needed to examine and implement best practices in the safe operation of MMVs, decreasing bike lane obstructions, promoting helmet use, and raising awareness of MMV legislation.

Caught in the blind spot of a truck: A choice model on driver glance behavior towards cyclists at intersections

Vulnerable road users (VRUs) constitute an increasing proportion of the annual road fatalities across Europe. One of the crash types involved in these fatalities are blind spot crashes between trucks and bicyclists. Despite the presence of mandatory blind spot mirrors, truck drivers are often reported to have overlooked the presence of a bicyclist. This raises the question if and when truck drivers check their blind spot mirrors for the presence of bicyclists, and which factors contribute to such glance behavior. The current study presents the results of an analysis of naturalistic glance behavior by 39 truck drivers in 1,903 right-turning maneuvers at urban intersections, where in each maneuver there was a chance of crossing the path of a bicyclist. The descriptive analysis revealed that most often truck drivers did not cast a glance upon their blind spot mirrors as recommended by the examination guidelines. Furthermore, a choice model was developed with the main factors that have an impact on glance behavior. Drivers were more likely to glance with a priority regulation that allowed conflicts, with lower speed limits, with zebra crossings, without cyclist facilities, without a lead vehicle making the same maneuver, in presence of VRUs, without adverse sight conditions, in lower age groups, without certain non-driving related activities, when driving a truck with more direct vision on VRUs, and without a camera providing a view on the blind spot, and with less time between a standstill and starting the maneuver. Three factors did not significantly improve the choice model and were therefore left out, despite showing significant effects in bivariate tests: intersection layout (e.g., three vs. four legs), presence of advanced stopping lanes, and visual obstruction. Implications of the choice model are discussed for driver education (in terms of timely glances, reducing inattention, and hazard anticipation) and vehicle design (in terms of direct vision).

Bicyclists injured by automobiles: helmet use and the burden of injury

Background

Given the widespread use of bicycles on public roadways, bicyclists injured in automobile collisions present a familiar problem to trauma centers worldwide. The aims of this study are to characterize the current injury patterns and to quantify independent risk factors for preventable injury and death, with a focus on helmet utilization and traumatic brain injuries.

Methods

This is a retrospective study using the American College of Surgeons Trauma Quality Improvement Program database for the period 2010 to 2016. Data were abstracted for bicyclists ≥16 years of age injured by an automobile. The primary outcome of interest was mortality. The secondary outcomes included intracranial, facial, and cervical spine injuries, as well as polytrauma. We used multivariate logistic regression to identify risk factors associated with outcomes.

Results

Of the 980 955 cases in the database, 7159 (0.73%) were bicyclists involved in a collision with an automobile. The median age was 45 years and 85% of patients were male. Polytraumatic occurrences accounted for 58% of injuries. Helmet use was reported in 25.4% of cases, a rate that did not change significantly during the study period. Helmet utilization was higher in those aged >65 years and in patients located in the West and Northeast regions of the USA. Helmet use was associated with an overall lower incidence of all reported forms of intracranial injuries. Overall mortality was 7.4%. Independent risk factors associated with mortality included age >65, lack of helmet use, head injury, and abdominal injury.

Discussion

Bicyclists injured in collisions with an automobile are at high risk of severe injury and mortality. Preventive strategies should target older bicyclists, helmet utilization, and increasing helmet accessibility for all bicyclists using roadways.

Level of evidence

Level IV.

Urban Mid-Block Bicycle Crossings: The Effects of Red Colored Pavement and Portal Overhead Bicycle Crossing Sign

This paper aims to investigate the effectiveness of some mid-block bicycle crossing elements by analyzing the drivers’ behavior, when approaching the bicycle crossings in a real road experiments with 18 participants. The eye-tracking instrument has been used to monitor the driver’s visual behavior during the test in an instrumented vehicle with GPS (global positioning system) and an inertial measurement unit (IMU). In particular, the drivers’ gaze was investigated frame by frame while approaching the mid-block bicycle crossings. The results showed that the red colored pavement increased the visibility of the mid-block crossing zone to 65.3% with respect to zebra crossing 59.6%. The drivers’ visual field was also narrowed by the portal overhead bicycle crossing sign and, consequently, drivers reduced their velocity and looked more to the vertical signs by 28%. The drivers’ speed reduction helped drivers to see the mid-block crossing elements from a greater distance with a higher fixation duration.

Postmortem injury quantification for the fatally injured cyclists in the Osijek-Baranja county over a 21-year period

OBJECTIVE

The objective of this study was to quantify injuries in fatal cyclists' traffic crashes by performing injury analysis and determine injury trends as well as main epidemiological data of the cyclists' fatalities.

METHODS

The study was organized as a cross-sectional retrospective study, which included 125 cyclists' fatalities autopsied at the Clinical Department of Pathology and Forensic Medicine, Clinical Hospital Center Osijek from 1998 to 2018. We applied The Abbreviated Injury Scale (AIS©) classification for all fatally injured cyclists in traffic crashes and determined the severity of injuries by body region from the description of injuries reported in the autopsy report.

RESULTS

The majority of victims in our study (80%) were male and older than 45 (80.8%). A significant majority of cyclists (78.4%) were not wearing a helmet at the time of the fatal crash. For the rest of the cyclists (21.6%) we were not able to establish if they were wearing a helmet at the time of the crash based on the traffic police reports. Most of those who died on the spot or during transport had severe injuries to three or more ISS body regions (26/46 = 54%) and the majority of deceased cyclist had severe injuries to the head and brain, regardless of the time of death. Older cyclists died on the spot with lower injury severity scores (ISS).

CONCLUSIONS

Measures against dangerous cycling behavior such as driving under the influence of alcohol and driving without the helmet could lead to reduction of fatal, and probably, non-fatal bicycle crashes. We believe that policy change regarding mandatory helmet usage is of upmost importance. Injury analysis can provide us with valuable information regarding where the focus of treatment should be among severely injured cyclists as well as where the prevention should be targeted. Further injury analysis studies are needed, with studies including both fatal and non-fatal crashes. The Abbreviated Injury Scale represents a valuable system for describing (coding) and quantifying the severity of injuries during autopsies.

Applying fast and frugal tree heuristic algorithm to identify factors influencing crash severity of bicycle-vehicle crashes in Tamilnadu

Though bicycle as a mode of transport has many environmental and societal benefits as well as health benefits, bicyclists are one of the most vulnerable road users. According to the report by the Ministry of Road Transport and Highways (MoRTH, 2017), there is a sharp increase in the number of fatal victims in respect of bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2585 in 2016 to 3559 in 2017, a 37.7% increase. In the present study, we present the analysis of the effect of the crash, geometric, environmental and cyclist characteristics on the bicycle-vehicle involved collisions by using the crash dataset of nine years (2009-2017) from Tamilnadu RADMS (Road Accident Data Management System) database with the application of fast and frugal tree (FFT) heuristic algorithm. The complete dataset (9978 crashes) was divided into two separate datasets: training data (6984 crashes) for the development of model and testing data (2984 crashes) for the performance evaluation. FFT algorithm identifies five major hues or variable attributes that influence the severity of bicycle crashes. The five major hues include the number of lanes, road separation, intersection, colliding vehicle type and road category. From the results of the present study, FFT acts as a complementary tool to other complex machine learning algorithms such as support vector machines, random forest, logistic regression and CART. The findings of the present study provide important insights for reducing the severity of bicycle-involved crashes at the planning and operations levels.

The potential of different countermeasures to prevent injuries with high risk of health loss among bicyclists in Sweden

Objective: As bicyclists account for the largest share of serious injuries in Sweden, focus to improve safety for bicyclists is needed. While knowledge about fatal bicycle crashes is rather extensive, the number of studies that have investigated non-fatal injuries is still rather limited. The aim of this study was to estimate the potential of different countermeasures to reduce crashes resulting in injuries with high risk of health-loss among cyclists in Sweden. A further aim was to describe the residual-that is, crashes that were not considered to be addressed by the analyzed countermeasures.Methods: A sample of individuals with specific injury diagnoses was drawn from the Swedish national crash database Strada. A survey form was used to collect additional information about the crash and the health-related outcomes. The potential of countermeasures currently included in the Swedish Safety Performance Indicators, as well as of countermeasures that could be described as "existing but not fully implemented" was assessed. The overall potential of all countermeasures assessed was calculated, giving a grand total without double counting. Cases that were considered not to be addressed by any of the countermeasures included (i.e., the residual crashes) were described in more detail.Results: The current Swedish Safety Performance Indicators that relate to safe cycling addressed 22% of crashes. Improved maintenance by deicing and removal of snow from bicycle infrastructure was found to have the highest potential (8%), followed by improved crashworthiness of passenger cars (5%) and safer bicycle crossings (4%). The potential for existing but not fully implemented safety improvements was 56%. The greatest potential was found for Autonomous Emergency Braking with cyclist detection for passenger cars (12%), followed by studded winter tyres for bicycles (12%), and improved maintenance on non-bicycle infrastructure (11%). In total, taking double counting into consideration, all safety improvements could address 64% of all crashes. Among the residual crashes, the majority (69%) were single bicycle crashes of which most were related to wheel locking during braking and losing balance at low speed or stationary.Conclusions: Compared with fatal crashes that involve a majority of bicycle-car crashes, the crashes leading to health-loss are mostly single bicycle crashes. Therefore, innovation and development of additional countermeasures to improve safety for bicyclists should focus on single bicycle crashes.

Characteristics of the road infrastructure and injurious cyclist crashes resulting in a hospitalisation

Faced with the current growth and change to Western Australia's road network as well as the promotion and increased uptake of cycling, further investigation into crash, injury and road infrastructure characteristics is necessary. An in-depth study was conducted of 100 cyclists who were injured due to involvement in a crash that occurred on-road and resulted in an admission to a hospital. Information collected included a researcher-administered questionnaire, crash details from the Integrated Road Information System (IRIS), injury information from the State Trauma Registry and a virtual on-line site inspection. Overall, 42 % of crashes involved a motor vehicle and 58 % did not involve a motor vehicle. Twenty-one percent of all crashes involved cyclist loss of control, 18% were crashes with another cyclist, 18% involved hitting an object and 1% involved a pedestrian. . Bicycle crashes were severely under-reported with only 40 percent reported to the Police. Approximately half of crashes occurred at intersections (51 %) and half at midblock (non-intersection) sites (49 %). Fifty-seven percent of crashes that occurred at intersections involved a motor vehicle, whereas only 27% of crashes that occurred at midblocks involved a motor vehicle. The majority of cyclists' injuries were classified as minor according to the Injury Severity Score with the mean number of body regions injured being 4.5 (SD = 2.2). The mean number of days in hospital care was 5.2 days (SD = 5.6, range: 1-33). These findings can be used to guide road infrastructure treatments that reduce the risk of bicycle crashes in Western Australia and insights may inform action in other jurisdictions where cycling is increasing in popularity.

Exploring the severity of bicycle-vehicle crashes using latent class clustering approach in India

INTRODUCTION

Bicyclists are vulnerable users in the shared asset like roadways. However, people still prefer to use bicycles for environmental, societal, and health benefits. In India, the bicycle plays a role in supporting the mobility to more people at lower cost and are often associated with the urban poor. Bicyclists represents one of the road user categories with highest risk of injuries and fatalities. According to the report by the Ministry of Road Transport and Highways (Accidents, 2017) in India, there is a sharp increase in the number of fatal victims for bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2,585 in 2016 to 3,559 in 2017, a 37.7% increase.

METHOD

Few studies have only investigated the crash risk perceived by the bicyclists while interacting with other road users. The present paper investigates the injury severity of bicyclists in bicycle-vehicle crashes that occurred in the state of Tamilnadu, India during the nine year period (2009-2017). The analyses demonstrate that dividing bicycle-vehicle collision data into five clusters helps in reducing the systematic heterogeneity present in the data and identify the hidden relationship between the injury severity levels of bicyclists and cyclists demographics, vehicle, environmental, temporal cause for the crashes.

RESULTS

Latent Class Clustering (LCC) approach was used in the present study as a preliminary tool for the segmentation of 9,978 crashes. Later, logistic regression analysis was used to identify the factors that influence bicycle crash severity for the whole dataset as well as for the clusters that were obtained from the LCC model. Results of this study show that combined use of both techniques reveals further information that wouldn't be obtained without prior segmentation of the data. Few variables such as season, weather conditions, and light conditions were significant for certain clusters that were hidden in the whole dataset. This study can help domain experts or traffic safety researchers to segment traffic crashes and develop targeted countermeasures to mitigate injury severity.

Using data mining techniques to predict the severity of bicycle crashes

To investigate the factors predicting severity of bicycle crashes in Italy, we used an observational study of official statistics. We applied two of the most widely used data mining techniques, CHAID decision tree technique and Bayesian network analysis. We used data provided by the Italian National Institute of Statistics on road crashes that occurred on the Italian road network during the period ranging from 2011 to 2013. In the present study, the dataset contains information about road crashes occurred on the Italian road network during the period ranging from 2011 to 2013. We extracted 49,621 road accidents where at least one cyclist was injured or killed from the original database that comprised a total of 575,093 road accidents. CHAID decision tree technique was employed to establish the relationship between severity of bicycle crashes and factors related to crash characteristics (type of collision and opponent vehicle), infrastructure characteristics (type of carriageway, road type, road signage, pavement type, and type of road segment), cyclists (gender and age), and environmental factors (time of the day, day of the week, month, pavement condition, and weather). CHAID analysis revealed that the most important predictors were, in decreasing order of importance, road type (0.30), crash type (0.24), age of cyclist (0.19), road signage (0.08), gender of cyclist (0.07), type of opponent vehicle (0.05), month (0.04), and type of road segment (0.02). These eight most important predictors of the severity of bicycle crashes were included as predictors of the target (i.e., severity of bicycle crashes) in Bayesian network analysis. Bayesian network analysis identified crash type (0.31), road type (0.19), and type of opponent vehicle (0.18) as the most important predictors of severity of bicycle crashes.

Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining

The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type), road user (i.e., opponent vehicle and cyclist's maneuver, type of collision, age and gender of the cyclist), vehicle (type of opponent vehicle), and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather). To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types.

The role of intersection and street design on severity of bicycle-motor vehicle crashes

Background

Safety concerns are a major barrier to cycling. Intersection and street design variables such as intersection angles and street width might contribute to the severity of crashes and the safety concerns. In this study we examined whether these design variables were associated with bicycle-motor vehicle crashes (BMVC) severity.

Methods

Using the geographical information system and latitudes/longitudes recorded by the police using a global positioning device, we extracted intersection angles, street width, bicycle facilities, posted speed limits and annual average daily traffic from 3266 BMVC data from New York City police records. Additional variables about BMVC, including age and sex of the bicyclist, time of the day, road surface conditions, road character, vehicle type and injury severity, were obtained from police reports. Injury severity was classified as severe (incapacitating or killed) or non-severe (non-incapacitating, possible injury). The associations between injury severity and environment design variables were examined using multivariate log-binomial regression model.

Findings

Compared with crashes at orthogonal intersections, crashes at non-orthogonal intersections had 1.37 times (95% CI 1.05 to 1.80) and non-intersection street segments had 1.31 times (95% CI 1.01 to 1.70) higher risk of a severe injury. Crashes that involved a truck or a bus were twice as likely to result in a severe injury outcome; street width was not significantly associated with injury severity.

Conclusion

Crashes at non-orthogonal intersections and non-intersection segments are more likely to result in higher injury severity. The findings can be used to improve road design and develop effective safety interventions.

Injury severity of pedestrians, bicyclists and motorcyclists resulting from crashes with reversing cars

OBJECTIVE

Pedestrians, bicyclists and motorcyclists can suffer serious injury in road traffic crashes. To date, no studies examine the injury severity within this vulnerable cohort following collisions with reversing cars.

MATERIAL AND METHODS

Our institution prospectively maintains a database including medical and technical information regarding traffic accidents in our area, including urban and suburban regions. In a retrospective review of this database, the authors describe the injury severity of pedestrians, bicyclists and motorcyclists following traffic crashes involving reversing cars. Injury severity was described using the abbreviated injury scale (AIS) as well as the maximum abbreviated injury scale (MAIS).

RESULTS

This study included 234 crashes occurring between 1999 and 2012. The lower extremity was injured most often while also suffering more severe injuries with a median AIS of 1 compared to 0 in all other documented body regions. The upper extremity was injured second most often. AIS ranging from 4 to 6 were infrequent. AIS 3 however, was documented for the legs in 4.3% of patients. MAIS 0, 1, 2, 3, 5 and 9 were found in 1, 164, 46, 14, 1, and 8 patients in the study cohort, respectively. Pedestrians and motorcyclists were seriously injured in 9.1% and 9.6% of cases, respectively. In contrast, no bicyclists suffered serious injuries. As to the zone of impact, most collisions occurred at the rear center of the vehicle (35%) followed by rear left (26%), rear right (20%), side rear (11%), side center (4%) and side front (3%). 204 (87.2%) collisions occurred during the day, 19 (8.1%) at night and 11 (4.7%) at twilight. Speed was similar in crashes involving pedestrians, bicyclists and motorcyclists, being as high as 7.0±3.6, 7.0±4.0 and 7.9±4.2km/h respectively.

CONCLUSIONS

This is the first study that analyzes injury severity among these vulnerable road users following collisions with reversing vehicles. The majority of collisions occur at low impact speed during the day. Most injuries resulting from these collisions are not serious, however pedestrians are at greatest risk of severe injury to any body region. The lower extremities suffer the most serious and frequent injuries within this cohort.

Alcohol use by urban bicyclists is associated with more severe injury, greater hospital resource use, and higher mortality

Alcohol use is a risk factor for severe injury in pedestrians struck by motor vehicles. Our objective was to investigate alcohol use by bicyclists and its effects on riding behaviors, medical management, injury severity, and mortality within a congested urban setting. A hospital-based, observational study of injured bicyclists presenting to a Level I regional trauma center in New York City was conducted. Data were collected prospectively from 2012 to 2014 by interviewing all bicyclists presenting within 24 h of injury and supplemented with medical record review. Variables included demographic characteristics, scene-related data, Glasgow Coma Scale (GCS), computed tomography (CT) scans, and clinical outcomes. Alcohol use at the time of injury was determined by history or blood alcohol level (BAL) >0.01 g/dL. Of 689 bicyclists, 585 (84.9%) were male with a mean age of 35.2. One hundred four (15.1%) bicyclists had consumed alcohol prior to injury. Alcohol use was inversely associated with helmet use (16.5% [9.9-25.1] vs. 43.2% [39.1-47.3]). Alcohol-consuming bicyclists were more likely to fall from their bicycles (42.0% [32.2-52.3] vs. 24.2% [20.8-27.9]) and less likely to be injured by collision with a motor vehicle (52.0% [41.7-62.1] vs. 67.5% [63.5-71.3]). 80% of alcohol-consuming bicyclists underwent CT imaging at presentation compared with 51.5% of non-users. Mortality was higher among injured bicyclists who had used alcohol (2.9% [0.6-8.2] vs. 0.0% [0.0-0.6]). Adjusted multivariable analysis revealed that alcohol use was independently associated with more severe injury (Adjusted Odds Ratio 2.27, p = 0.001, 95% Confidence Interval 1.40-3.68). Within a dense urban environment, alcohol use by bicyclists was associated with more severe injury, greater hospital resource use, and higher mortality. As bicycling continues to increase in popularity internationally, it is important to heighten awareness about the risks and consequences of bicycling while under the influence of alcohol.

Circumstances and causes of fatal cycling crashes in the Czech Republic

OBJECTIVES

The circumstances and causes of death of 129 cyclists registered in the Olomouc and the Zlín regions, the Czech Republic, between 2005 and 2013 were the subject of this study.

METHODS

We analyzed the autopsy reports, where the principal cause of death was stated, and obtained a detailed description of the circumstances recorded by the police officers.

RESULTS

Eighty-three cases (64.3% of the set) were collisions involving a motor vehicle. The driver was the guilty party in 57 cases (68.7%) and the cyclist in the remaining 26 cases (31.3%). The most frequent cause of the crash was connected with right of way (29 cases). Cars were involved in 52 cases; heavy vehicles, including buses, in 26 cases; and motorcycles in 5 cases. Single-vehicle crashes consisted of 43 (33.3%) cases. We divided this group into 3 subgroups based on whether the particular case could be attributed to a cyclist having lost control of the bicycle (31 cases) or to other particular causes. Sixty-eight cases (52.7%) of fatal outcomes were directly linked to intracranial injuries. Multiple injuries were the principal cause of death in 19 cases (14.7%), followed by hemorrhagic traumatic shock (12 cases, 9.3%). Seventy-two (55.8%) cyclists died immediately after the crash and 23 (17.8%) cyclists died within a day of the accident.

CONCLUSIONS

Trucks were more dangerous to cyclists than cars at intersections, whereas cars were more dangerous on straight sections. The most important pattern was identified as a motor vehicle hitting a cyclist from behind on a straight road section. We identified a strong underestimation of natural death as a cause of cycling fatalities in the official police reports.

The epidemiology of fatal cyclist crashes over a 14-year period in Alberta, Canada

Background

Cycling is a popular recreational activity and a common transportation option; however, cycling-related injuries can be fatal. There are few studies of cycling fatalities in Canada and none in a region as sparsely populated as Alberta.

Methods

A chart review was conducted of cyclists involved in fatal crashes. Charts for deaths that occurred between 1998 and 2011 (inclusive) were identified and abstracted onto standardized forms. Personal characteristics and crash circumstances, including motor vehicle involvement, were collected; mechanisms of fatally injured cyclists across age groups were compared. Census data were used to calculate region-specific and provincial age-specific cycling fatality rates.

Results

Charts from 101 deaths over 14 years were reviewed. Events mainly occurred during the summer. There were more fatalities in urban (64 [63 %]) than in rural settings. Collisions with motor vehicles and cyclist-only crashes accounted for 68 and 15 % of cycling fatalities, respectively. Most (87 %) deceased cyclists were male, and the median age was 47 years (inter-quartile range: 25, 58). The population-based fatality rate over the study period was highest among deceased cyclists older than 65. Helmet use was reported in 26 (26 %) cases and increased with age. Alcohol use was detected in 25 (25 %) cases.

Conclusions

Fatal cycling crashes in Alberta typically involve adults riding on urban roads and collisions with motor vehicles. While helmet legislation has reduced non-fatal cycling head injuries, deaths may be further prevented by physical separation of cyclists and motor vehicles and avoidance of substance use while operating bicycles.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-015-2476-9) contains supplementary material, which is available to authorized users.

Injury patterns and features of cycling fatalities in South Australia

There has been an increase in cycling in Australia. This means that more cyclists are at risk of injuries, which account for a proportion of transport-related fatalities. In this study, all cyclist fatalities from 2002 to 2013 in South Australia where post-mortem examinations were performed were investigated. There were 42 deaths representing 3% of the total road fatalities over the same time. Of this total number of cases, 13 deaths (31%) involved collapse (mostly natural causes from an underlying medical condition) and 29 (69%) resulted from trauma. There were no cases of hyperthermia. Of the decedents 95% were male, and the mean age at death was 47 years. Fatal incidents were more likely to occur during April and November, and on a Monday. However, statistical analysis was not possible due to the small number of cases. Fatalities (traumatic and collapse) predominantly occurred whilst the cyclist was riding (86%). The majority of riding fatalities were as a result of collision with vehicles (81%). Drugs (including alcohol) were detected in two (15%) of the 13 cases of the collapses, and in seven (26%) of the 27 trauma cases tested. In trauma cases, death was most often due to multiple injuries. The most frequent area for injury was the head (found in 90% of traumatic deaths). Despite the increasing numbers of cyclists on South Australian roads over the last decade, death rates have trended downwards suggesting that road safety campaigns and the provision of more dedicated bicycle lanes have had a positive outcome.

The relation between speed environment, age and injury outcome for bicyclists struck by a motorized vehicle - a comparison with pedestrians

This study analyzes (a) the relation between injury severities, the age of the bicyclist and the speed environment at accident locations (mean travel speed of the traffic flow involved in the accident) where a bicyclist was struck by a motorized vehicle and (b) how these relations differ from those for struck pedestrians. Accident data from Sweden for the years 2004-2008 was used to identify accident locations to analyze the relations between speed environment, age and injury outcome. Seventy-seven accident sites were used for field measurements and further analysis. The results show that both speed environment and age have considerable correlation with injury severity. There was a statistically significant relation between injury severity and the speed environment, and large proportion of the serious bicycle accidents occur at locations with speeds below 30km/h. Also, the risk of serious injuries or fatalities seems to increase after the age of 45. To our knowledge this is the first study that uses the mean travel speed in this manner for analyzing injury severity of struck bicyclists.

An epidemiological study of the risk of cycling in the dark: the role of visual perception, conspicuity and alcohol use

To curtail the rising numbers of cyclists seriously injured in road crashes, more insights are needed into the factors that contribute to these crashes. For instance, darkness is known to be associated with higher injury rates, but little is known about the relative influence of factors such as poor conspicuity, impaired perception and alcohol use among cyclists. To examine these factors, the present study analyzed the epidemiological crash data for three meteorological light conditions: daylight, late evening darkness and early morning darkness; for two crash types: crashes with (M-crashes) and without motorized traffic (NM-crashes); and for different age groups. The relative injury rates (injury risk per distance travelled in darkness corrected for daylight injury risks for each age group) confirmed findings from earlier studies that cycling in late evening darkness is associated with higher injury rates than cycling in daylight conditions. This is the case for both crash types with only small differences between the age groups suggesting that poor conspicuity (M-crashes) and impaired perception (NM-crashes) may play a role. In comparison to late evening darkness, relative injury rates in early morning darkness are much higher. This is the case for both crash types with large differences among the age groups, suggesting that in addition to the absence of daylight also age related risk factors are at play. Support for this hypothesis was found from the analyses of hospital records, showing that the proportion of seriously injured cyclists who have been drinking is highest in early morning darkness and has strongly increased over the last decades. These insights provide input for the selection of countermeasures such as improved lighting (both street and bicycle lights) and interventions targeting alcohol use among cyclists.

Severe street and mountain bicycling injuries in adults: a comparison of the incidence, risk factors and injury patterns over 14 years

BACKGROUND

Street and mountain bicycling are popular recreational activities and prevalent modes of transportation with the potential for severe injury. The purpose of this investigation was to compare the incidence, risk factors and injury patterns among adults with severe street versus mountain bicycling injuries.

METHODS

We conducted a retrospective cohort study using the Southern Alberta Trauma Database of all adults who were severely injured (injury severity score [ISS] ≥ 12) while street or mountain bicycling between Apr. 1, 1995, and Mar. 31, 2009.

RESULTS

Among 11 772 severely injured patients, 258 (2.2%) were injured (mean ISS 17, hospital stay 6 d, mortality 7%) while street (n = 209) or mountain bicycling (n = 49). Street cyclists were often injured after being struck by a motor vehicle, whereas mountain bikers were frequently injured after faulty jump attempts, bike tricks and falls (cliffs, roadsides, embankments). Mountain cyclists were admitted more often on weekends than weekdays (61.2% v. 45.0%, p = 0.040). Injury patterns were similar for both cohorts (all p > 0.05), with trauma to the head (67.4%), extremities (38.4%), chest (34.1%), face (26.0%) and abdomen (10.1%) being common. Spinal injuries, however, were more frequent among mountain cyclists (65.3% v. 41.1%, p = 0.003). Surgical intervention was required in 33.3% of patients (9.7% open reduction internal fixation, 7.8% spinal fixation, 7.0% craniotomy, 5.8% facial repair and 2.7% laparotomy).

CONCLUSION

With the exception of spine injuries, severely injured cyclists display similar patterns of injury and comparable outcomes, regardless of style (street v. mountain). Helmets and thoracic protection should be advocated for injury prevention.

Risk factors for causing road crashes involving cyclists: An application of a quasi-induced exposure method

A quasi-induced exposure approach was applied to the Spanish Register of Traffic Crashes to identify driver- and vehicle-related factors associated with the risk of causing a road crash involving a cyclist in Spain from 1993 to 2009. We analyzed 19,007 collisions between a bicycle and another vehicle in which only one of the drivers committed an infraction, and 13,540 records that included the group of non-infractor cyclists in the above collisions plus cyclists involved in single-bicycle crashes. Adjusted odds ratios were calculated for being responsible for each type of crash for each factor considered. Age from 10 to 19 years, male sex, alcohol or drug consumption and non-helmet use were cyclist-related variables associated with a higher risk of crash, whereas cycling more than 1h increased only the risk of single crashes. Bicycles with brake defects and ridden by two occupants were also at higher risk of involvement in a crash, whereas light defects were associated only with collisions with another vehicle. For drivers of the other vehicle, age more than 60 years, alcohol, not using safety devices and nonprofessional drivers were at higher risk. The risk of colliding with a bicycle was higher for mopeds than for passenger cars.

Protecting vulnerable road users from injury

Aymery Constant and Emmanuel Lagarde discuss policies to protect pedestrians, and pedal and motor cyclists, from injury.