Bicycle Crashes Research Articles

Bicycle safety at roundabouts: a systematic literature review

ABSTRACT As roundabouts become increasingly popular, and as many communities promote bicycle use, the safety of roundabouts for people bicycling is of major concern. Although converting an intersection to a roundabout may reduce crashes overall, some research from northern Europe suggests that roundabouts may actually increase the frequency of bicycle crashes. We perform a systematic literature review on this topic, reviewing 49 different resources with empirical findings (most from Europe, some from Australia/New Zealand, few from the US). Many studies analyse (limited) bicycle crash data or observe driver/cyclist behaviours and interactions, while a few survey cyclists’ safety perceptions. Consistent with design guidance, bicycle safety performance is worse for higher-speed, multilane roundabouts and when on-roadway bike lanes are provided. Crash data and observations suggest that when cyclists “take the lane” and operate as vehicles – as is allowed or even recommended in some current design guidelines – this leads to conflicts and crashes between circulating cyclists and entering drivers who may have “looked but failed to see” (and thus failed to yield to) the cyclist. Providing separated cycle paths around the roundabout seems to be a lower-risk and more comfortable design solution, although care must be taken to encourage appropriate yielding at crossings. Future research should investigate more design features, socio-demographic characteristics, cyclist safety perceptions, and impacts outside of Europe. Studies should continue to explore ways to overcome limited bicycle crash and exposure data and to utilise naturalistic methods, driving simulators, and stated choice experiments.

Socioeconomic Status, Health and Lifestyle Settings as Psychosocial Risk Factors for Road Crashes in Young People: Assessing the Colombian Case.

The social determinants of health influence both psychosocial risks and protective factors, especially in high-demanding contexts, such as the mobility of drivers and non-drivers. Recent evidence suggests that exploring socioeconomic status (SES), health and lifestyle-related factors might contribute to a better understanding of road traffic crashes (RTCs). Thus, the aim of this study was to construct indices for the assessment of crash rates and mobility patterns among young Colombians who live in the central region of the country. The specific objectives were developing SES, health and lifestyle indices, and assessing the self-reported RTCs and mobility features depending on these indices. A sample of 561 subjects participated in this cross-sectional study. Through a reduction approach of Principal Component Analysis (PCA), three indices were constructed. Mean and frequency differences were contrasted for the self-reported mobility, crash rates, age, and gender. As a result, SES, health and lifestyle indices explained between 56.3–67.9% of the total variance. Drivers and pedestrians who suffered crashes had higher SES. A healthier lifestyle is associated with cycling, but also with suffering more bike crashes; drivers and those reporting traffic crashes have shown greater psychosocial and lifestyle-related risk factors. Regarding gender differences, men are more likely to engage in road activities, as well as to suffer more RTCs. On the other hand, women present lower healthy lifestyle-related indices and a less active implication in mobility. Protective factors such as a high SES and a healthier lifestyle are associated with RTCs suffered by young Colombian road users. Given the differences found in this regard, a gender perspective for understanding RTCs and mobility is highly suggestible, considering that socio-economic gaps seem to differentially affect mobility and crash-related patterns.

Modeling bicycle crash costs using big data: A grid-cell-based Tobit model with random parameters

Bicyclists are among the most vulnerable road users in the urban transportation system. It is critical to investigate the contributing factors to bicycle-related crashes and to identify the hotspots for efficient allocation of treatment resources. A grid-cell-based modeling framework was used to incorporate heterogeneous data sources and to explore the overall safety patterns of bicyclists in Manhattan, New York City. A random parameters (RP) Tobit model was developed in the Bayesian framework to correlate transportation, land use, and sociodemographic data with bicycle crash costs. It is worth mentioning that a new algorithm was proposed to estimate bicyclist-involved crash exposure using large-scale bicycle ridership data from 2014 to 2016 obtained from Citi Bike, which is the largest bicycle sharing program in the United States. The proposed RP Tobit model could deal with left-censored crash cost data and was found to outperform the Tobit model by accounting for the unobserved heterogeneity across neighborhoods. Results indicated that bicycle ridership, bicycle rack density, subway ridership, taxi trips, bus stop density, population, and ratio of population under 14 were positively associated with bicycle crash cost, whereas residential ratio and median age had a negative impact on bicycle crash cost. The RP Tobit model was used to estimate the cell-specific potential for safety improvement (PSI) for hotspot ranking. The advantages of using the RP Tobit crash cost model to capture PSI are that injury severity is considered by being converted into unit costs, and varying effects of certain explanatory variables are accounted for by incorporating random parameters. The cell-based hotspot identification method can provide a complete risk map for bicyclists with high resolution. Most locations with high PSIs either had unprotected bicycle lanes or were close to the access points to protected bicycle routes.

The safety of physically separated cycle tracks compared to marked cycle lanes and mixed traffic conditions in Amsterdam

Bicycle infrastructure is utilised to improve cycling safety and encourage bicycle use as a sustainable and healthy transport mode. This study sets out to assess whether providing physically separated cycle tracks along distributor roads, as prescribed in Dutch design guidelines and the Sustainable Safety vision, yields the expected safety benefits for cyclists. Therefore the safety of physically separated cycle tracks is compared to marked or painted cycle lanes and to mixed traffic conditions at distributor roads with a speed limit of 50 km/h in Amsterdam in the Netherlands. The study also includes the presence of the risk factors curbside parking and trams. Since police records are known to underreport single bicycle crashes and other crashes without a motor vehicle involved, ambulance records are used in this study instead. Also, both motor vehicle volumes as well as cyclists counts are taken into account in the crash analysis. By doing so, this study aims to address two weaknesses of previous research, i.e. the lack of control for exposure of cyclists and the use of police recorded crashes which miss the majority of bicycle crashes without motor vehicles. Results show that, controlled for kilometres travelled by bicycle and by motor vehicle, 50-60% less bicycle crashes occur on distributor roads with cycle tracks compared to those with cycle lanes. Curbside parking and trams are related to an increased likelihood of bicycle crashes, a difference of a factor 2 and 1.7-2 respectively. The authors therefore recommend to favour physically separated cycle tracks over cycle lanes and to take out curbside parking from the cross section as this presents the possibility to introduce cycle tracks in existing cross sections and mitigate an important risk factor concurrently.

Beliefs about riding a bicycle when mildly alcohol intoxicated

Alcohol intoxication appears to be a contributing factor to many bicycle crashes with serious consequences. Despite this, there is no specific limit on the blood alcohol concentration permissible when cycling in Sweden, and there is very little knowledge of the perception of sobriety associated with cycling. The aim of this study is therefore to identify the behavioural, normative, and control beliefs underpinning cyclists’ attitude, subjective norm, and perceived behavioural control associated with riding a bicycle when mildly alcohol intoxicated. A total of 34 participants answered questions based on the theory of planned behaviour (Ajzen, 1991). The results indicate that the participants saw great advantages (practical, free, safe, nice, and better than taking the car), but also disadvantages (impaired ability, danger to oneself, and danger to others) from cycling when mildly alcohol intoxicated. Furthermore, they identified both factors making it easier (small amounts of alcohol, bicycle-friendly infrastructure/conditions, poor alternatives, group pressure, and emergency situations) and more difficult (large amounts of alcohol, aggravating circumstances, bicycle-unfriendly infrastructure/conditions, good alternatives, social censure, group resistance, parenthood, and experience) to opt to cycle when mildly alcohol intoxicated. Finally, some participants believed that certain people (e.g. students, people with poor finances, and nearly everyone) think that it is acceptable to cycle when mildly alcohol intoxicated, while others (e.g. parents, responsible people, and nearly no group) think that it is unacceptable. These results support the use of information dissemination/campaigns to reduce the incidence of cycling when alcohol intoxicated and/or the amount of alcohol consumed in connection with cycling. At the same time, they do not support the introduction of a specific limit on the blood alcohol concentration permissible when cycling, and the potential of improved public transport to reduce the number of inebriated cyclists is uncertain.

In Colombia, Treading the Border between Memory and Magic: A Conversation with Ingrid Rojas Contreras

Days after a bicycle crash that would erase her memory for two months, Ingrid Rojas Contreras answered her phone and heard the voice of a woman she presumably didn't know, but who sounded oddly familiar—her mother. Curiously, her mother had suffered a similar physical accident and extended memory loss decades earlier in Colombia and, as she recovered, began to see ghosts, empowering her to join a previously all-male family line of curanderos, or indigenous healers. This story, tinged with a García Márquez–like magical realism, lies along a border between fictional truth and documentable mystery that Rojas Contreras is now exploring in her memoir-in-progress, The Man Who Could See Clouds, which centers on her curandero grandfather. Her 2018 novel Fruit of the Drunken Tree also treads that border, drawing on her family's life in Bogotá against the backdrop of Colombia's politically tumultuous 1980s and '90s. In a December 2020 Zoom conversation, we compared how truth and fiction play together between memoir and novel.

Enlightening cyclists: an evaluation study of a bicycle light communication system aimed to support older cyclists in traffic interactions

In the Netherlands, older cyclists run an increased risk of bicycle crashes. Critical factors are low-speed interactions, stopping, (dis)mounting, and potentially misjudging riding speeds. A Bicycl...

TIPP—Bicycle Safety: Myths and Facts

Patient Education| 2021 TIPP—Bicycle Safety: Myths and Facts Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation TIPP—Bicycle Safety: Myths and Facts. Pediatric Patient Education 2021; 10.1542/peo_document311 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search nav search search input Search input auto suggest search filter All AAP SitesAll PublicationsPediatric Patient Education Search Advanced Search Subjects: TIPP - The Injury Prevention Program Topics: bicycle safety, misconceptions, protective helmet, teaching Learning to ride a bike is a developmental milestone in the life of a child. Yet all too often children are seriously injured, or even killed, when they do not follow basic bicycle safety rules. Following is a list of common bicycle safety myths, coupled with the correct information you need to teach your children about safe bike riding. These facts will help you and your children make every bike ride safe. Myth: My child doesn’t need to wear a helmet on short rides around the neighborhood. Fact: Your child needs to wear a helmet on every bike ride, no matter how short or how close to home. Many injuries happen in driveways, on sidewalks, and on bike paths, not just on streets. In fact, most bike crashes happen near home. A helmet protects your child from serious injury and should... © 2020 American Academy of Pediatrics. All rights reserved. You do not currently have access to this content.

Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data

Pedestrian and bicycle safety is a key component in traffic safety studies. Various studies were conducted to address pedestrian and bicycle safety issues for intersections, road segments, etc. However, only a few studies investigated pedestrian and bicycle safety for bus stops, which usually have a relatively larger volume of pedestrians and bicyclists. Moreover, traditional reactive safety approaches require a significant number of historical crashes, while pedestrian and bicycle crashes are usually rare events. Alternatively, surrogate safety measures could proactively evaluate traffic safety status when crash data are rare or unavailable. This paper utilized critical bus driving events extracted from GPS trajectory data as pedestrian and bicycle surrogate safety measures for bus stops. A city-wide trajectory data from Orlando, Florida was used, which contains around 300 buses, 6,700,000 GPS records, and 1300 bus stops. Three critical driving events were identified based on the buses’ acceleration rates and stop time; hard acceleration, hard deceleration, and long stop. The relationships between critical driving events and crashes were examined using Spearman’s rank correlation coefficient. All three events were positively correlated with pedestrian and bicycle crashes. Long stop event has the highest correlation coefficient, followed by hard acceleration and hard deceleration. A Bayesian negative binomial model incorporating spatial correlation (Bayesian NB-CAR) was built to estimate the pedestrian and bicycle crash frequency using the generated events. The results were consistent with the correlation estimation. For example, hard acceleration and long stop events were both positively related to pedestrian and bicycle crashes. Moreover, model evaluation results indicated that the proposed Bayesian NB-CAR outperformed the standard Bayesian negative binomial model with lower Watanabe-Akaike Information Criterion (WAIC) and Deviance Information Criteria (DIC) values. In conclusion, this paper suggests the use of critical bus driving events as surrogate safety measures for pedestrian and bicycle crashes, which could be implemented in a proactive traffic safety management system.

Improving knowledge of cyclist crashes based on hospital data including crash descriptions from open text fields

Introduction: In this study we explore the added value of bicycle crash descriptions from open text fields in hospital records from the Aarhus municipality in Denmark. We also explore how bicycle crash data from the hospital complements crash data registered by the police in the same area and time period. Method: The study includes 5,313 Danish bicycle crashes, of which 4,205 were registered at the hospital and 1,078 by the police. All crashes occurred from 2010 to 2015. We performed an in-depth analysis of the open text fields on hospital records to identify factors associated with each crash using four categories: bicyclist, road, bicycle, and the other party. We employed the chi-squared test to compare the distribution of variables between crashes registered at the hospital and by the police. A binary logit model was used to estimate the probability that a crash factor is identified, and that each crash factor is associated with a single-bicycle crash. Results: The open-ended text fields in hospital records provide detailed information about crash factors not available in police records, including riding speed, inattention, clothing, specific road conditions, and bicycle defects. The factors alcohol and curb had the highest odds of being identified in relation to a single-bicycle crash. Crash data registered at the hospital included a larger number of bicycle crashes, particularly single-bicycle crashes and crashes with slight injuries only. Conclusion: Crash information registered at the hospital in Aarhus Municipality contributes to a better understanding of bicycle crashes due to detailed information about crash-associated factors as well as information about a larger number of bicycle crashes, particularly single-bicycle crashes. Practical implication: Efforts to improve access to detailed information about bicycle crashes are needed to provide a better basis for bicycle crash prevention.

Factors influencing the injury severity of single-bicycle crashes

The majority of research on bicyclist injury severity relates to bicycle-motor vehicle crashes, even though single-bicycle crashes make up more than half of bicycle crashes. This study explores the factors related to the injury severity outcome of single-bicycle crashes. We use single-bicycle crash data obtained from medical records collected in the period 2010–2015 combined with road maintenance data. The data includes three injury severity categories: ‘severe injury’, ‘slight injury’, ‘no injury’.The relation between the factors surrounding single-bicycle crashes and the resulting injury severity is estimated using a latent class ordered probit model. The model estimation identifies three latent classes where the likelihood of cyclist membership depends on the bicyclist's age and gender. Furthermore, several factors appear to affect the likelihood of injuries in single-bicycle crashes. These are the road geometry (i.e. if the crash occurred on a bicycle lane or a road section), maintenance level, and the interaction between road geometry and maintenance level. The findings suggest that single-bicycle crashes on road sections result in more severe injuries than single-bicycle crashes on bicycle lanes. The largest effect is seen when a single-bicycle crash occurs on a road section with a poorly maintained bicycle lane being available. Crashes on low volume roads with few bicyclists are also related to an increased probability of severe injury as well as crashes occurring after dark.

Sequence analysis of sickness absence and disability pension in the year before and the three years following a bicycle crash; a nationwide longitudinal cohort study of 6353 injured individuals

BackgroundBicyclists are the road user group with the highest number of severe injuries in the EU, yet little is known about sickness absence (SA) and disability pension (DP) following such injuries.AimsTo explore long-term patterns of SA and DP among injured bicyclists, and to identify characteristics associated with the specific patterns.MethodsA longitudinal register-based study was conducted, including all 6353 individuals aged 18–59 years and living in Sweden in 2009, who in 2010 had incident in-patient or specialized out-patient healthcare after a bicycle crash. Information about sociodemographic factors, the injury, SA (SA spells > 14 days), and DP was obtained from nationwide registers. Weekly SA/DP states over 1 year before through 3 years after the crash date were used in sequence and cluster analyses. Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for factors associated with each identified sequence cluster.ResultsSeven clusters were identified: “No SA or DP” (58.2% of the cohort), “Low SA or DP” (7.4%), “Immediate SA” (20.3%), “Episodic SA” (5.9%), “Long-term SA” (1.7%), “Ongoing part-time DP” (1.7%), and “Ongoing full-time DP” (4.8%). Compared to the cluster “No SA or DP”, all other clusters had higher ORs for women, and higher age. All clusters but “Low SA and DP” had higher ORs for inpatient healthcare. The cluster “Immediate SA” had a higher OR for: fractures (OR 4.3; CI 3.5–5.2), dislocation (2.8; 2.0–3.9), sprains and strains (2.0; 1.5–2.7), and internal injuries (3.0; 1.3–6.7) compared with external injuries. The cluster “Episodic SA” had higher ORs for: traumatic brain injury, not concussion (4.2; 1.1–16.1), spine and back (4.5; 2.2–9.5), torso (2.5; 1.4–4.3), upper extremities (2.9; 1.9–4.5), and lower extremities (3.5; 2.2–5.5) compared with injuries to the head, face, and neck (not traumatic brain injuries). The cluster “Long-term SA” had higher ORs for collisions with motor vehicles (1.9;1.1–3.2) and traumatic brain injury, not concussion (18.4;2.2–155.2).ConclusionSequence analysis enabled exploration of the large heterogeneity of SA and DP following a bicycle crash. More knowledge is needed on how to prevent bicycle crashes and especially those crashes/injuries leading to long-term consequences.

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.

Design, Implementation and Testing of a New Multi-Sensor Mobile Device as a Tool for Cycling Data Collection in Highly Congested Urban Streets

The number of bicycle riders in New York City (NYC) has been increasing steadily in the past few years. These numbers include private and shared bicycles. The NYC bicycle network has been expanded to accommodate the needs of the increasing number of riders. Although the new infrastructure has reduced the number of cyclists killed or seriously injured (KSI) in some areas, in other areas similar improvements were not observed. A data-driven approach to study the possible effects of this type of infrastructure inconsistency on the variation of the number of bicycle crashes from one region to another in the city is the primary motivation of this paper. A highly portable and inexpensive sensing device for measuring the distance between a bicycle and lateral objects is designed and developed from scratch. The developed mobile sensing device can also map bicycle trajectories to highlight critical segments where the safe distance from passing vehicles is not respected. This mobile device is powered by a portable power source and it is comprised of two ultrasonic sensors, a Global Positioning System (GPS) receiver, and a real-time clock (RTC). The sensor is secured inside a custom design 3D printed case. The case can be easily attached to any bicycle including shared bikes for testing. The final prototype is entirely functional and used to collect sample data to demonstrate its effectiveness to address safety-related problems mentioned above. Finally, a dashboard is created to display collected key information. This key information can be used by researches and agencies for a better understanding of the factors contributing to the safety of bicycle routes.

Use of Spatial Analysis Techniques to Identify Statistically Significant Crash Hot Spots in Metropolitan Melbourne

Understanding where, when, what type and why crashes are occurring can help determine the most appropriate initiatives to reduce road trauma. Spatial statistical analysis techniques are better suited to analysing crashes than traditional statistical techniques as they allow for spatial dependency and non-stationarity. For example, crashes tend to cluster at specific locations (spatial dependency) and vary from one location to another (non-stationarity). Several spatial statistical methods were used to examine crash clustering in metropolitan Melbourne, including Global Moran’s I statistic, Kernel Density Estimation and Getis-Ord Gi* statistic. The Global Moran’s I statistic identified statistically significant clustering on a global level. The Kernel Density Estimation method showed clustering but could not identify the statistical significance. The Getis-Ord Gi* method identified local crash clustering and found that 15.7 per cent of casualty crash locations in metropolitan Melbourne were statistically significant hot spots at the 95 per cent confidence level. The degree, location and extent of clustering was found to vary for different crash categories, with fatal crashes exhibiting the lowest level of clustering and bicycle crashes exhibiting the highest level of clustering. Temporal variations in clustering were also observed. Overlaying the results with land use and road classification data found that hot spot clusters were in areas with a higher proportion of commercial land use and with a higher proportion of arterial and sub-arterial roads. Further work should investigate network based hot spot analysis and explore the relationship between crash clusters and influencing factors using spatial techniques such as Geographically Weighted Regression.

Journey Attributes, E-Bike Use, and Perception of Driving Behavior of Motorists as Predictors of Bicycle Crash Involvement and Severity

Previous studies have revealed the relevance of e-bike use, perception of driving behavior of motorists, and instrumental and affective factors in work and leisure journeys among regular cyclists. However, the importance of these factors as predictors of bicycle crash involvement and severity is less well-known. The aim of the present study was to investigate the role of journey attributes, e-bike use, and perception of driving behavior of motorists in predicting bicycle crash involvement and severity, while controlling for sociodemographic factors, cycling levels, cycling environment, and purposes of cycling. We collected data from an online panel of 2,389 respondents from six European countries (Sweden, Netherlands, United Kingdom, Hungary, Italy, Spain). Using the generalized linear model, we found that both bicycle crash involvement and severity were related to lower age, being employed, using the bicycle for traveling to or from college/university, not using the bicycle for leisure/training, and using an e-bike. Bicycle crash severity was associated with lower affective attributes, higher instrumental attributes, and the perception of good driving behavior of motorists.

Effect of London cycle hire scheme on bicycle safety

This study evaluates the effect of London Cycle Hire scheme (LCH) on bicycle crashes, based on the data from 333 Lower Layer Super Output Areas (LSOAs) in the period 2011–2012. The Propensity Score Matching method (PSM) is applied to evaluate the effects of policy interventions (‘treatment’) on bicycle safety, with which the effects of confounding factors on the treatment effects are accounted, using the systematically established untreated groups. Covariates including land use, traffic and population characteristics are considered when selecting the untreated group for each treated unit. Results of PSM indicated that numbers of overall and slight injury bicycle crashes increased by 37.7% and 31.8% when LCH was introduced. Additionally, the interaction by another transport management policy – London Congestion Charging scheme (LCC) – on the effects of LCH on bicycle crash was estimated. Numbers of overall and slight injury bicycle crash further increased by 59.1% and 57.8% because of the implementation of LCC. For the killed or seriously injured (KSI) bicycle crashes, increases were observed in both cases (i.e. 81% for LCH and 66% for LCC), despite that they are not statistically significant. Results are indicative to the design and planning of bicycle infrastructure that could enhance the overall bicycle safety in London.

Safety of e-bikes compared to conventional bicycles: What role does cyclists’ health condition play?

IntroductionThe rising use of e-bikes (EBs) presents an opportunity to increase active transportation but may compromise road safety due to increased travel speed and weight compared to conventional bicycle (CBs). Evidence comparing the safety of EBs and CBs is limited while the influence of cyclists’ health status has been neglected. MethodsThis cross-sectional case-control study compared EB and CB users in the Netherlands. Data were gathered 1) through a survey among crash casualties treated at emergency departments aged >16 (N = 2383) and 2) control group data were collected among cyclists without any known crash experience, randomly drawn from a panel of the Dutch population (N = 1860). Using logistic regressions, we assessed the likelihood of crashes and crash severity while adjusting for bicycle use and health status. ResultsEB users had poorer health than CB users, but they were not more likely to be involved in a crash or to sustain more severe injuries. However, older female cyclists did have an elevated risk on EBs and sustained more severe injuries. Health-related factors such as the presence of morbid conditions, medication use, and the body mass index were neither associated with crash likelihood nor associated with injury severity and accordingly did not explain the findings for older females. However, balance and coordination problems, and the use of anti-epileptic drugs were associated with crashes. ConclusionOur findings provide support that EB users have a poorer health status than CB users, while general health status is unrelated to the likelihood and severity of bicycle crashes. EBs enable more vulnerable groups to cycle or keep cycling but, after controlling for bicycle use, EB users are not more likely to be involved in a crash or to sustain severe injuries. As older females run a higher risk on an EB and are more likely to fall while (dis)mounting, we recommend to promote EBs enabling safer (dis)mounting such as by reduced saddle height.

A jughandle design will virtually eliminate single bicycle crashes at a railway crossing

IntroductionBicycling provides many positive outcomes at individual- and population-levels, from increased physical activity to reduced congestion. One of the main barriers to increased levels of bicycling is safety and injury risk from motor vehicles and from single-bicycle crashes. One known hazard is bicycle crashes at rail crossings where the bicycle wheel is caught in the flangeway causing loss of control. MethodsThis study evaluates two realignments, or “jughandle” designs to increase the angle of a skewed crossing in an urban environment. Using continuous video analysis over two 2-month periods, this is the first empirical analysis of safety performance of this infrastructure. ResultsThe realignment reduced crash risk by 98% (C.I. 86.3%–99.7%), from 4.0 to 0.1 crashes per 1000 crossings (or 53 crashes before to 1 crash after). Bicycling across at more than 30° eliminates almost all risk by reducing the severity of the crash. There were 19 crashes with minor injury and one was severe out of 32 observed crashes before the jughandle design, while only one non-injury crash was observed after the treatment. More than 90% of riders complied with the new design, following the desired path. ConclusionThe study shows that the “jughandle” realignment of bicycle crossings at the railway can virtually eliminate the risk of single bicycle crashes. Most of the riders complied with the realigned path by the use of low-cost implementation of pavement marking. However, we can expect better compliance rate and, subsequently, lower crash rate by the application of prominent mitigation techniques such as bollards and surface treatment.

Helmet Usage Reduces Serious Head Injury Without Decreasing Concussion After Bicycle Riders Crash

BackgroundThe importance of bicycle helmets in reducing injuries is unclear. Our center receives a disproportionate number of bicycle crash victims. We sought to evaluate the types of injuries observed and the role of helmets in reducing head injuries. Materials and methodsWe evaluated demographic data and compared injuries between bicycle riders that crashed with and without helmets over a 9-year period. Categorical variables were compared using linear regression methods and nominal variables using ANOVA. Differences were considered significant for P ≤ 0.05. ResultsThere were 906 patients evaluated, 701 with helmets (77%) and 205 (23%) without helmets. The mean Injury Severity Score was 9.3 ± 6.4. The most common injuries were concussion (n = 385), rib fractures (n = 154), clavicle fractures (n = 139), facial fractures (n = 102), and cervical spine fractures (n = 89). There was no significant difference in the number of patients with a concussion in riders with or without helmets, [299/701, 42.6% versus 86/205, 42.0%, respectively, (P = NS)]. In helmet versus no helmet riders, there were significantly fewer patients with facial fractures, [67/701, 9.5%, versus 35/205, 17.0%, respectively, (P = 0.003)], skull fractures [8/701, 1.1% versus 9/205, 4.4%, respectively, (P = 0.003)], and serious head injuries [6/701, 0.85% versus 8/205, 3.9%, respectively, (P = 0.002)]. ConclusionsHelmeted patients involved in bicycle crashes are less likely to sustain a serious head injury, a skull fracture, or facial fractures compared to riders without helmets. The most common injury in patients with a bicycle crash is a concussion. Helmets did not prevent concussion after bicycle rider’s crash in our patient population.