Exploring the impact of right-turn safety measures on E-bike-heavy vehicle conflicts at signalized intersections.

A major safety hazard for e-bike riders crossing an intersection is encountering heavy vehicles turning right in the same direction, which often results in severe casualties. Recently, some cities in China have implemented right-turn safety improvement treatments (i.e., right-turn yielding rules and right-turn warning facilities) at intersections to reduce the occurrence of such accidents. However, the risk perception and behavior of e-bike riders and heavy vehicle drivers dynamically change during the right-turn interaction process, and the safety effects of different right-turn safety measures remain unclear. This study aims to investigate the safety effect of right-turn safety measures on E-Bike-Heavy Vehicle (EB-HV) right-turn conflicts at signalized intersections. The right-turn conflicts and potential influencing factors are extracted from aerial video data, including characteristics of right-turn warning facilities, characteristics and behavior of e-bike riders and heavy vehicle drivers, environmental factors, and traffic-related factors. Moreover, traffic conflict indicators such as the Time to Collision (TTC), Post Encroachment Time (PET), and Jerk are selected and calculated. Multinomial and binary logit models are used to estimate and analyze the EB-HV right-turn conflict severity and drivers yielding behavior. The results reveal that: (a) right-turn warning facilities can decrease the probability of slight and severe EB-HV right-turn conflicts, while the presence of law enforcement cameras could prompt heavy vehicle drivers to comply with the yielding rules and adopt more cautious behavior; (b) increased heavy vehicle speed and acceleration before turning right have strong correlation to illegitimate yielding behavior of the driver and higher EB-HV right-turn conflict severity; and (c) aggressive behavior of e-bike rider increases the severe conflict probability, especially at intersections without right-turn warning facilities. Based on the study findings, several practical implications are suggested to reduce the risk of EB-HV right-turn conflicts, enhance the effectiveness of right-turn safety measures, and improve crossing safety for e-bike riders.

Injury severity analysis of e-bike riders in China based on the in-vehicle recording video crash data: a random parameter ordered logit model.

This study investigates the impacts of various factors on e-bike riders' injury severity in crashes with motor vehicles, based on the in-vehicle recording video crash data in China. Variables from human factors, vehicle characteristics, road conditions, and environmental attributes are extracted from the video, especially for drivers and riders' illegal and avoidance behaviour before the crash, and sun shade canopy use. Results of mixed logit models reveal that drivers' speeding, running red lights, slow-down and swerve behaviour, light trucks, heavy trucks, and buses have significantly varied impacts on riders' injury. Moreover, both drivers and riders' illegal behaviour leads to an increased injury, while their avoidance behaviour before crashes can protect riders. In addition, types of visual obstacles, accidents occurring at night, large vehicles' involvement, and the application of sunshade canopies by riders increased the probability of severe injury, while helmet use can protect riders in accidents with motor vehicles.

Riding Towards Danger: A Scoping Review of Burns Associated with Personal Mobility Devices (PMDs), including Electric Bikes (E-bikes) and Electric Scooters (E-scooters).

Burn injuries related to Lithium-Ion batteries from personal mobility devices, such as electric bikes and electric scooters, have emerged as a global concern. By examining the literature, this study aims to provide an overview of the demographics, patterns and outcomes of personal mobility device-associated burns. A Singaporean cohort revealed burns resulting predominantly from fires occurring due to the combustion of unattended personal mobility device batteries during charging. In contrast, an Israeli cohort showed a higher TBSA and highlighted the vulnerability of limbs to burn injuries in such incidents. A Beijing cohort, consisting of paediatric patients, indicated potential child safety concerns regarding personal mobility device usage. Finally, a Shanghai cohort demonstrated the potential dangers of PMD battery chargers. The observed differences between those experiencing burn injuries and the broader population of personal mobility device riders in terms of age and gender suggest that younger males may be at higher risk, perhaps due to risky practices such as leaving personal mobility devices unattended whilst charging. This review emphasises the need for safety education, adherence to regulations, and responsible consumer choices to mitigate burn injuries. Recommendations include promoting child safety measures, using certified personal mobility devices, and cautious handling of DIY conversion kits. Further large-scale studies are essential to gain comprehensive insights and develop effective safety strategies to protect personal mobility device riders from burn injuries.

Accustomed or Regulated: Influencing factors of two-wheeler riders' illegal Lane-Transgressing behavior when overtaking.

Illegal lane-transgressing is a typical aberrant riding behavior of riders of two-wheelers, i.e., motorcycles, bicycles, and e-bikes, which is highly frequent in accident reports. However, there is insufficient attention to this behavior at present. This study aims to explore the socio-psychologic factors that influence the illegal lane-transgressing behavior of two-wheeler riders when overtaking. For this purpose, a questionnaire was first composed. The questionnaire included the behavioral intention of two-wheeler riders towards illegal overtaking behavior and five influencing factors: safety knowledge, descriptive norms, injunctive norms, perceived behavior control, and risk perception. Second, a survey was conducted on different two-wheeler riders in Xi'an. Third, various types of two-wheelers were analyzed jointly and separately by structural equation models and analyses of variance. Results show that e-bike riders were more similar to motorcycle riders in behavioral intentions, with their risk perception weaker than other riders. Descriptive norms and perceived behavior control played the most significant roles in the structural equation model. It was also found that two-wheeler riders with a car license had better traffic safety performance. Based on the above results, it is recommended that attention be paid to illegal lane-transgression in the process of law enforcement and education, and a higher level of safety training should be provided for two-wheeler riders.

Factors affecting the intention to wear helmets for e-bike riders: the case of Chinese college students.

As the popularity of electric bicycles (e-bikes) continues to surge, the number of accidents involving them has commensurately increased. A significant factor contributing to the high fatality rate in these accidents is the low usage of helmets among e-bike riders. Helmets have been proven to reduce the severity of injuries, yet their usage remains unexpectedly low. This issue is particularly pronounced among college students, the primary buyer group for e-bikes. Regrettably, there is a lack of research exploring their intentions to wear helmets. Understanding determinants of their intentions to wear helmets is crucial in promoting safe e-bike travel. Therefore, the present study aims to develop an integrated theoretical model that combines the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM) to examine the factors influencing e-bike riders' helmet-wearing intentions among college students. Additionally, two variables-descriptive norms and law enforcement-are incorporated. The results indicate that the integrated model accounts for 76% of the variance in helmet-wearing intention, surpassing single-theory models. Specifically, the TPB accounts for 65%, while the HBM explains 53%. Notably, law enforcement emerges as the most influential factor, highlighting the crucial role of enforcing regulations and promoting awareness. Other significant factors include subjective and descriptive norms, attitudes, perceived benefits, perceived susceptibility, perceived barriers, and perceived severity. These findings provide valuable insights for policy development and targeted interventions aimed at improving helmet wear rates among e-bike riders, especially among the college student population.

Cranio-cervical and traumatic brain injury patterns-do they differ between electric bicycle, bicycle, and motorcycle-induced accidents?

PURPOSE: With the growing technical options of power transmission and energy-saving options in electric drives, the number of E-bike-related accidents especially in an elderly population has increased. The aim of the current study was to compare if the increased velocity in comparison to conventional bikes translates into different injury patterns in the cranio-cervical and head region. METHODS: A retrospective cohort study was performed in patients admitted to our level one trauma center between 2009 and 2019 after being involved in an accident with either an E-bike, bicycle, or motorcycle and suffered cranio-cervical or traumatic brain injury. OUTCOMES: cranio-cervical/intracranial injury pattern. Data interpretation was conducted in an interdisciplinary approach. RESULTS: From 3292 patients treated in this period, we included 1068 patients. E-bikers were significantly older than bicyclists (or motorcyclists) and lay between the other two groups in terms of helmet use. Overall injury patterns of E-bikers resembled those found in motorcyclists rather than in bicyclists. E-bikers had a higher incidence of different cerebral bleedings, especially if no helmet was worn. Helmet protection of E-bikers resulted in a comparable frequency of intracranial bleeding to the helmeted bicyclists. CONCLUSION: The overall pattern of head and cervical injuries in E-bikers resembles more to that of motorcyclists than that of bicyclists. As they are used by a more senior population, multiple risk factors apply in terms of complications and secondary intracranial bleeding. Our study suggests that preventive measures should be reinforced, i.e., use of helmets to prevent from intracranial injury.

Exploring the spatial relationship of e-bike and motorcycle crashes: Implications for risk reduction.

INTRODUCTION: Electric bicycles, or e-bikes, have become very popular over the past decade. In order to reduce the risk of crashes, it is necessary to understand the contributing factors. While several researchers have examined these elements, few have considered the spatial heterogeneity between crashes and environmental variables, such as Points of Interest (POI). In addition, there is a scarcity of studies comparing the crash-related factors of e-bikes and motorcycles. Despite their differing speed and range capabilities, different POIs also tend to impact area/bandwidths differently because e-bikes cannot cover the same range that motorcycles can. METHOD: In this study, we compared e-bike and motorcycle crashes at 11 different types of POIs in Taipei from 2016 to 2020. Since crashes are sparse events and easily affected by the Modifiable Areal Unit Problem (MAUP), Kernel Density Estimation (KDE) was employed to transform crash points (count data) to crash risk surfaces (continuous data). Additionally, an advanced variant of Geographical Weighted Regression (GWR), Multiscale Geographically Weighted Regression (MGWR) utilized to predict crash risk because each predictor is allowed to have a different bandwidth. RESULTS: The results showed: (a) For e-bike crashes, the MGWR model outperformed the GWR and OLS models in terms of AIC values, while the MGWR and GWR performed similarly with regard to motorcycle crashes; (b) The analysis revealed e-bike and motorcycle crash risk to be associated with various types of POIs. E-bike crashes tended to occur more frequently in areas with more schools, supermarkets, intersections, and elderly people. Meanwhile, motorcycle crashes were more likely to occur in areas with a high number of restaurants and intersections. The search bandwidths of e-bikes are inconsistent and narrower than those of motorcycles.

Secular trends in the incidence and severity of injuries sustained by riders of electric bikes and powered scooters: The experience of a level 1 adult trauma center.

BACKGROUND: The incidence of injuries caused by electric bicycles (E-bikes) and powered scooters (P-scooters) continues to increase. Data on the severity of those injuries is conflicting. The purpose of this study was to explore secular trends in the incidence and severity characteristics of patients following E-bike and P-scooter injuries and predictors for major trauma. METHODS: A retrospective cohort study of patients aged ≥16 years following E-bike and P-scooter injuries was performed at a level 1-trauma center between 2017 and 2022. We explored secular trends in major trauma cases (primary outcome), emergency department (ED) visits, hospitalizations, and surgical interventions (secondary outcomes). Major trauma was defined by either an injury severity score (ISS) >15 or the patient's need for acute care, defined by any of the following: Intensive care unit admission, direct disposition to the operating room, acute interventions performed in the trauma room, and in-hospital death. Primary and secondary outcomes were compared between two time frames (2017-2018 vs.2019-2022). RESULTS: In total, 9748 patients were presented following P-scooter and E-bike injuries. Of them, 1183 patients (12.1%) were hospitalized (854 males [72.2%],median age 33 years, median ISS 9).During the study period, the number of ED visits increased by 21-fold, with a parallel increase hospitalizations and surgical interventions numbers, which increased by 3.4-and 3.8-fold, respectively. Numbers of patients with ISSs >15 and patients who required acute care sharply increased during the study period, but no significant differences were found in the percentages of patients with ISSs >15 (p = 0.78) or patients' need for acute care (p = 0.32) between early and late periods. A severity analysis revealed that male sex (adjusted odds ratio [aOR] 1.7 [95% confidence interval (CI): 1.2-2.4], p = 0.001) and E-bike riders compared to P-scooter riders (aOR 1.5 [95% CI:1.1-2.0], p = 0.005) were independent predictors for severe trauma. CONCLUSIONS: The incidence of E-bike and P-scooter injuries sharply increased over time, with a parallel elevation in numbers of hospitalizations, surgical interventions, and major trauma cases. Major trauma percentages did not increase during the study period. Male sex and E-bikes emerged as independent predictors for major trauma.

[Bicycle accidents in the course of time in Münster, Germany : Analysis of changes in bicycle accidents over the past 10 years]. / Münsteraner Fahrradunfälle im Wandel der Zeit : Analyse der Entwicklung der Fahrradunfälle in den letzten 10 Jahren.

BACKGROUND: Bicycles have been a popular means of transport for many years. Especially in times of increased climate discussion, the bicycle has moved further into focus as an environmentally friendly and cost-effective means of transport. Bike lanes and roads are becoming more crowded and new means of transport such as pedelecs or e­scooters are emerging. METHODS: A total of four studies by Münster University Hospital on bicycle accidents and the official accident statistics of the Münster police were compared. In the period from 2009 to 2019, three studies were conducted that considered all bicycle accidents and one study that only considered pedelec riders separately. RESULTS: The age distribution as well as main causes of accidents remained almost the same over the years. The number of pedelec accidents has increased. Pedelec riders have a higher average age and a higher proportion of intensive care stays; however, this cohort also has a high rate of helmet wearers. Overall, the willingness to wear a helmet seems to have increased. CONCLUSION: It should be considered that with increasing bicycle traffic, safety measures must be increased accordingly. In this respect, accident prevention should focus on three major areas, engineering, education and enforcement.

Development of German pedelec (and bicycle) crashes between 2013 and 2021.

INTRODUCTION: The continuous growth in the use of e-bikes (in Germany mostly pedelecs that support pedaling up to 25 km/h) raises questions about the use of historic crash data for the development of road safety measures. The aim of this study was to address this issue, by conducting a longitudinal analysis of pedelec and bicycle crash data over a period of nine years to identify trends and to clarify whether such trends are specific to pedelecs. METHOD: We analyzed 95,338 police reported pedelec and bicycle injury crashes from 2013 through 2021. The dataset consisted of crashes from three federal states of Germany: Brandenburg, Hesse and Saxony. Data were analyzed with respect to sex and age distribution, time, location and type of accident, conflict partner, cause of crash and injury severity. RESULTS: Many of the analyzed variables showed a considerable degree of temporal stability, with differences as well as similarities between the two bicycle types staying quite consistent over the years. One notable difference was the mean age of the involved riders, with crashed pedelec riders being significantly older than conventional cyclists. At the same time, however, the mean age of these pedelec riders has decreased by eight years over time. Single vehicle crashes were consistently more common for pedelec riders than for cyclists. Similarly, pedelec rider crashes went with a higher injury severity over all the years. CONCLUSIONS AND PRACTICAL APPLICATIONS: While, on a more detailed level, we found differences between the two bicycle types, overall crash characteristics were remarkably similar and consistent over time. Our findings provide no clear argument for road safety measures that are specifically designed to target pedelecs. Instead, the stable crash total, and the increases in ridership of both bicycles and pedelecs, highlight the demand for new, innovative solutions to improve cycling safety in general.

Torque Measurement and Control for Electric-Assisted Bike Considering Different External Load Conditions.

This paper proposes a novel torque measurement and control technique for cycling-assisted electric bikes (E-bikes) considering various external load conditions. For assisted E-bikes, the electromagnetic torque from the permanent magnet (PM) motor can be controlled to reduce the pedaling torque generated by the human rider. However, the overall cycling torque is affected by external loads, including the cyclist's weight, wind resistance, rolling resistance, and the road slope. With knowledge of these external loads, the motor torque can be adaptively controlled for these riding conditions. In this paper, key E-bike riding parameters are analyzed to find a suitable assisted motor torque. Four different motor torque control methods are proposed to improve the E-bike's dynamic response with minimal variation in acceleration. It is concluded that the wheel acceleration is important to determine the E-bike's synergetic torque performance. A comprehensive E-bike simulation environment is developed with MATLAB/Simulink to evaluate these adaptive torque control methods. In this paper, an integrated E-bike sensor hardware system is built to verify the proposed adaptive torque control.

Electric bicycles (e-bikes) are an increasingly common pediatric public health problem.

Purpose: Electric bicycles (e-bikes) achieve higher speeds than pedal bicycles, but few studies have investigated the impact on injury rates specific to the pediatric population. Utilizing the National Electronic Injury Surveillance System (NEISS), we compared rates of pediatric injury for e-bikes, bicycles, and gas-engine bicycles (mopeds) from 2011 to 2020. Methods: Descriptive and bivariate inferential analyses were performed upon NEISS estimates of e-bike, bicycle, and moped injuries in children aged 2-18 years. Analyses were stratified by patient age and helmet usage. The Mann-Kendall test of trends was used. Results: We identified 3945 e-bike, 23,389 moped, and 2.05 million bicycle injuries. Over time, the incidence of injury increased for e-bikes (Kendall's τ=0.73, p = 0.004), decreased for pedal bicycles (Kendall's τ= - 0.91, p = 0.0003), and did not change for mopeds (Kendall's τ = 0.06, p = 0.85). Males accounted for 82.5 % of e-bike injuries. The age group most commonly affected by e-bike injury (44.3 %) was 10-13 years old. The proportion of injuries requiring hospitalization was significantly higher for e-bikes (11.5 %), compared to moped and bicycle (7.0 and 4.8 %, respectively, p < 0.0001). In cases where helmet use or absence was reported, 97.3 % of e-bike riders were without a helmet at the time of injury, compared to 82.1 % of pedal bicycle riders and 87.2 % of moped riders. Conclusions: The rate of pediatric e-bike injuries increased over the study period. Compared to riders on pedal bicycles or mopeds, children on e-bikes had infrequent helmet use and increased rate of hospitalization. These findings suggest that attention to e-bike safety and increasing helmet usage are important to public health among the pediatric population. Level of evidence: IV.

Evaluating alternate discrete outcome frameworks for modeling riders' red light running behavior.

This paper aims to empirically evaluate the ordered and unordered discrete outcome frameworks to approach riders' red-light running (RLR) decisions and compare the differences in influencing factors between riders' risk-taking and opportunistic RLR behaviors. A total of 2057 cyclist samples approaching the intersections during red signals were observed by video in Beijing, China. To better capture the unobserved heterogeneity, apart from the traditional models, three advanced models including the random thresholds random parameters hierarchical ordered logit (RTRPHOL) model, the random parameters logit model with heterogeneity in means and variances (RPLHMV) model, and the correlated random parameters logit model with heterogeneity in means (CRPLHM), are developed. Results show that: 1) the unordered framework statistically outperformed its ordered counterparts, and the RPLHMV and CRPLHM models are statistically better than others. 2) The female and e-bicycle indicators produce a heterogeneity-in-means effect, and the low-volume and left-side indicators produce a heterogeneity-in-variances effect. 3) e-bike riders and riders from the right side are more inclined to have risk-taking behavior than opportunistic behavior, and both RLR behaviors of cyclists are most susceptible to the number of violating individual indicator. Findings illustrate that multilayer unobserved heterogeneity should be adequately considered in developing precise micro-simulation and practical guidance in traffic safety.

Mobile phone use while cycling among e-bikers in China: Reasoned or social reactive?

INTRODUCTION: China has the largest number of e-bikers in the world, and e-bike crashes cause thousands of fatalities and tens of thousands of serious injuries annually. Mobile phone use while e-biking is a violation of Chinese law and associated with increased crash risk. The current study investigated mobile phone use behavior while cycling among Chinese e-bikers and the psychological factors surrounding why individuals might choose to engage in this risk-taking behavior. METHOD: In particular, this study investigates whether the decision to use a mobile phone while cycling is explained through reasoned decision making or is a social reactive decision, or both, as defined by the prototype willingness model (PWM). Questionnaire data were collected from 784 Chinese adults with e-bike experience. RESULTS: Results showed that 40.2 % of the participants reported mobile phone use while cycling e-bikes in the past month. Both behavioral intention and behavioral willingness were predictors of mobile phone while using e-bikes, and they were approximately equal in their magnitude of predictive power (ßBI = 0.25; ßBW = 0.26). E-bikers' attitudes, perceived behavioral control, and perception of prototype similarity and favorability were strong predictors of intention, willingness, and self-reported behavior to use mobile phones while e-biking. CONCLUSIONS: Both social reactive decision-making and reasoned decision-making contribute to decisions to use a mobile phone while riding an e-bike. PRACTICAL APPLICATIONS: Results have implications for guiding development of interventions to prevent and reduce mobile phone use when e-bike cycling.

Design and Validity of a Smart Healthcare and Control System for Electric Bikes.

This paper presents the development of an electronic system that converts an electrically assisted bicycle into an intelligent health monitoring system, allowing people who are not athletic or who have a history of health issues to progressively start the physical activity by following a medical protocol (e.g., max heart rate and power output, training time). The developed system aims to monitor the health state of the rider, analyze data in real-time, and provide electric assistance, thus diminishing muscular exertion. Furthermore, such a system can recover the same physiological data used in medical centers and program it into the e-bike to track the patient's health. System validation is conducted by replicating a standard medical protocol used in physiotherapy centers and hospitals, typically conducted in indoor conditions. However, the presented work differentiates itself by implementing this protocol in outdoor environments, which is impossible with the equipment used in medical centers. The experimental results show that the developed electronic prototypes and the algorithm effectively monitored the subject's physiological condition. Moreover, when necessary, the system can change the training load and help the subject remain in their prescribed cardiac zone. This system allows whoever needs to follow a rehabilitation program to do so not only in their physician's office, but whenever they want, including while commuting.

E-scooter and E-bike injury pattern profile in an inner-city trauma center in upper Manhattan.

BACKGROUND: Electric bikes and scooters are becoming popular means of short-distance transportation in major cities. Regulations for safe riding established by ride-sharing companies and local governments have not been effectively implemented. Inner-city hospitals are at the frontline of receiving traumas related to e-bikes and e-scooters and are receiving an increasing number of injuries. The works of literature reporting these injuries are limited. METHOD: This study reviewed all the trauma activations at a major trauma center in NYC from 04/2019 to 08/2021. Patients with e-bike and e-scooter injuries were included in the study. Socio-demographics of riders, passengers, injury patterns, and outcomes were reviewed. Logistics regression was used to analyze the factors associated with Injury Severity Scale. RESULTS: We reviewed 1979 patient charts of trauma activation in the Emergency Department. We included 88 scooters, 24 E-bike, and 5 nonrider scooter injuries. 91% were male and 9% were Female victims. The majority were African American patients (34%) and Hispanic patients (46%). 87% belonged to the 18-50 years age group, and 13% were above 50 years and below 18 years were excluded from the study. 36% of victims were under the influence of drugs or alcohol and only 25% of riders wore helmets. 58% of patients were discharged from the ED, 42% required hospital admission, and 14% required ICU care. Odds of non-mild injury (moderate to critical injury) in comparison to mild injury were significantly greater with increasing age. CONCLUSIONS: The use of e-bikes and e-scooters is increasing as a means of affordable short-distance transportation but with evidence of significant injuries with varying severity. These findings suggest a need to review public policy regarding e-bike and electric scooter use regulations for the safety of riders and pedestrians; Driving While Intoxicated (DWI) law enforcement, mandatory helmet, education, speed control, creation of special lanes, and no car zones.

Safer cycling in older age (SiFAr): effects of a multi-component cycle training. a randomized controlled trial.

BACKGROUND: The risk of older adults being injured or killed in a bicycle accident increases significantly due to the age-related decline of physical function. Therefore, targeted interventions for older adults to improve safe cycling competence (CC) are urgently needed. METHODS: The "Safer Cycling in Older Age" (SiFAr) randomized controlled trial investigated if a progressive multi-component training program related to cycling improves CC of older adults. Between June 2020 and May 2022, 127 community-dwelling persons living in the area Nürnberg-Fürth-Erlangen, Germany aged 65 years and older were recruited, who are either (1) beginners with the e-bike or (2) feeling self-reported unsteadiness when cycling or (3) uptaking cycling after a longer break. Participants were either randomized 1:1 to an intervention group (IG; cycling exercise program, 8 sessions within 3 months) or an active control group (aCG; health recommendations). The CC as primary outcome was tested not blinded in a standardized cycle course prior and after the intervention period and after 6-9 months, which consists of variant tasks requiring skills related to daily traffic situations. Regression analyses with difference of errors in the cycling course as dependent variable and group as independent variable adjusted for covariates (gender, number of errors at baseline, bicycle type, age and cycled distance) were performed. RESULTS: 96 participants (73.4 ± 5.1 years; 59.4% female) were analyzed for primary outcome. Compared to the aCG (n = 49), the IG (n = 47) made an average of 2.37 fewer errors in the cycle course after the 3 months intervention period (p = 0.004). People with more errors at baseline had higher potential for improvement (B=-0.38; p < 0.001). Women on average made 2.31 (p = 0.016) more errors than men, even after intervention. All other confounders had no significant effect on the difference in errors. The intervention effect was very stable until 6-9 months after the intervention (B=-3.07, p = 0.003), but decreased with a higher age at baseline in the adjusted model (B = 0.21, p = 0.0499). CONCLUSION: The SiFAr program increases cycling skills among older adults with self-perceived needs for improvement in CC and could easily be made available to a broad public due to its standardized structure and a train-the-trainer approach. TRIAL REGISTRATION: This study was registered with clinicaltrials.gov: NCT04362514 (27/04/2020), https://clinicaltrials.gov/ct2/show/NCT04362514 .

Does a bicycle accident as the cause of proximal femur fracture indicate that geriatric co-management is superfluous? A retrospective cohort study.

BACKGROUND: Deployment of geriatric care would be more sustainable if we could limit geriatric co-management to older hip fracture patients who benefit most from it. We assumed that riding a bicycle is a proxy of good health and hypothesized that older patients with a hip fracture due to a bicycle accident have a more favorable prognosis than patients whose hip fracture was caused by another type of accident. METHODS: Retrospective cohort study of hip fracture patients ≥ 70 years admitted to hospital. Nursing home residents were excluded. Primary outcome was length of hospital stay (LOS). Secondary outcomes were delirium, infection, blood transfusion, intensive care unit stay and death during hospitalization. The group with a bicycle accident (BA) was compared to the non-bicycle accident (NBA) group using linear and logistic regression  models, with correction for age and sex. RESULTS: Of the 875 patients included, 102 (11.7%) had a bicycle accident. BA patients were younger (79.8 versus 83.9 years, p < 0.001), less often female (54.9 versus 71.2%, p = 0.001) and lived independently more often (100 versus 85.1%, p < 0.001). Median LOS in the BA group was 0.91 times the median LOS in the NBA group (p = 0.125). For none of the secondary outcomes the odds ratio favored the BA group, except for infection during hospital stay (OR = 0.53, 95%CI 0.28-0.99; p = 0.048). CONCLUSIONS: Although older hip fracture patients who had a bicycle accident appeared more healthy than other older hip fracture patients, their clinical course was not more favorable. Based on this study, a bicycle accident is not an indicator that geriatric co-management can be omitted.

Characteristics of older cyclists with self-perceived needs for improvement in cycling competence: SiFAr trial.

BACKGROUND: Older cyclists are in great risk of being injured or killed in a traffic-related accident and their needs should find more consideration in safety guidelines, urban planning, and future intervention programs. OBJECTIVE: The aim for this cross-sectional analysis was to comprehensively explore characteristics of community-dwelling cyclists aged 65 years and older with a self-perceived need to increase cycle competence. METHODS: 118 older adults (mean age 73.3 ± 5.2 years, 61% women) performed a standardized cycle course representing specific cycling skills. Additionally, health and functional assessments were carried out and characteristics regarding demographic, health, falls, bicycle equipment/type and cycling biography/behavior were obtained. RESULTS: The majority (67.8%) of this community-dwelling adults reported being unsafe when cycling and 41.3% had a bicycle fall in the past year. More than half of the participants showed at least one limitation in each of the measured cycling skills. Women significantly had more frequent limitations in four of the cycling skills measured (p ≤ 0.001) compared to men. While no significant differences were found for falls, health and functional characteristics, women and men differed significantly in terms of bicycle type, equipment, and perceived safety (p < 0.001). CONCLUSION: Limitations in cycling should be compensated by preventive bicycle training and a safe cycling infrastructure. Bicycle fit, the wearing of bicycle helmets and promotion of a sense of security while cycling can further reduce accident risk and must find recognition in safety guidelines. In addition, educational initiatives have to dismantle gender-related bicycle stereotypes.

Fractures of the Lower Extremity after E-Bike, Bicycle, and Motorcycle Accidents: A Retrospective Cohort Study of 624 Patients.

Electric bicycles (e-bikes) have gained enormous popularity in recent years, and as a result, they have successively become more involved in traffic accidents. The aim of the present study was to assess differences in severity and localization of injuries to the lower extremities after accidents with e-bikes, conventional bicycles, and motorcycles. A retrospective cohort-analysis of patients who sustained traumatic accidents with two-wheeled vehicles transferred to a level 1 trauma center in Switzerland was performed. We assessed patient demographics, injury pattern, and trauma severity (ISS), with a subgroup analysis of outcomes stratified by vehicle. In total, 624 patients (71% male) with injuries to the lower extremities after bicycle (n = 279), electric bike (n = 19), and motorcycle (n = 326) accident were included. The mean age of all assessed patients was 42.4 years (SD 15.8), with a significantly higher age in the e-bike cohort (p = 0.0001). High-velocity injuries were found significantly more often in the motorcycle and e-bike group. The motorcycle group had a significantly higher mean ISS (17.6) than the other groups (p = 0.0001). E-bike accidents produce a different injury profile to the lower extremities compared to motorcycle or bicycle accidents. Higher age, higher velocity, and different protective equipment seem to have an impact on these fracture patterns.