Dataset Information

Characteristics and comparison between e-scooters and bicycle-related trauma: a multicentre cross-sectional analysis of data from a road collision registry.

ABSTRACT:

Background

Urban mobility has drastically evolved over the last decade and micromobility rapidly became an expanding segment of contemporary daily transportation routines. E-scooter riders and bicyclists may share similar trauma characteristics, but this has been little explored. The objective was to describe and compare the characteristics of e-scooter and bicycle-related trauma.

Methods

We conducted a cross-sectional analysis of data from the Rhône road collision registry (January 1, 2019 to December 31, 2019). We included all e-scooter or bicycle riders injured in traffic collisions during the study period; there were no exclusion criterion.

Results

A total of 2,779 patients were included; 825 (29.7%) were e-scooter riders and 1,954 (70.3%) were bicyclists. E-scooter riders were younger (median [IQR]: 24 [20-32] vs 29 [20-45] years, p < 0.001) and less frequently male (64.2% vs 73.4%, p < 0.001). Most e-scooter and bicycle road collisions were consequent to a fall or loss of vehicle control (74.2% vs 67.7%, p < 0.001). E-scooter riders were less frequently wearing a helmet at the time of the road collision (6.1% vs 30.7%, p < 0.001) and had more frequently head (24.2% vs 19.9%, p = 0.01) and face (30.6 vs 20.5%, p < 0.001) injuries compared to bicyclists. The median injury severity score was 2 [1-4] in both groups with no significant difference (p = 0.77).

Conclusions

E-scooter and bicycle-related trauma patients were mainly young males with minor injuries and most of them sustained a road collision with no third-party. However, they suffered from different injury patterns; e-scooter riders suffered more frequently face and head injuries than bicycle riders, which may be at least partly the consequence of less frequent helmet use among e-scooter riders compared to bicyclists. Hence the two groups of users should not be considered as a single trauma entity. This issue should be promptly addressed to bring down the incidence of preventable injuries and avoid healthcare costs.

SUBMITTER: Benhamed A

PROVIDER: S-EPMC9520117 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characteristics and comparison between e-scooters and bicycle-related trauma: a multicentre cross-sectional analysis of data from a road collision registry.

Benhamed Axel A Gossiome Amaury A Ndiaye Amina A Tazarourte Karim K

BMC emergency medicine 20220929 1

<h4>Background</h4>Urban mobility has drastically evolved over the last decade and micromobility rapidly became an expanding segment of contemporary daily transportation routines. E-scooter riders and bicyclists may share similar trauma characteristics, but this has been little explored. The objective was to describe and compare the characteristics of e-scooter and bicycle-related trauma.<h4>Methods</h4>We conducted a cross-sectional analysis of data from the Rhône road collision registry (Janua ...[more]

PMID: 36175859

Similar Datasets

Project description:PurposeAn average of 611 deaths and over 47,000 bicyclists are injured in traffic-related crashes in the United States each year. Efforts to increase bicycle safety are needed to reduce and prevent injuries and fatalities, especially as trends indicate that ridership is increasing rapidly. The objective of this study was to evaluate the effect of bicycle-specific roadway facilities (e.g., signage and bicycle lanes) in reducing bicycle crashes.MethodsWe conducted a case site-control site study of 147 bicycle crash-sites identified from the Iowa Department of Transportation crash database from 2007 to 2010 and 147 matched non-crash sites. Control sites were randomly selected from intersections matched to case sites on neighborhood (census block group) and road classification (arterial, feeder, collector, etc.). We examined crash risk by any on-road bicycle facility present and by facility type (pavement markings--bicycle lanes and shared lane arrows, bicycle-specific signage, and the combination of markings and signage), controlling for bicycle volume, motor vehicle volume, street width, sidewalks, and traffic controls.ResultsA total of 11.6% of case sites and 15.0% of controls had an on-road bicycle facility. Case intersections had higher bicycle volume (3.52 vs. 3.34 per 30 min) and motor vehicle volume (248.77 vs. 205.76 per 30 min) than controls. Our results are suggestive that the presence of an on-road bicycle facility decreases crash risk by as much as 60% with a bicycle lane or shared lane arrow (OR=0.40, 95% CI=0.09-1.82) and 38% with bicycle-specific signage (OR=0.62, 95% CI=0.15-2.58).ConclusionsInvestments in bicycle-specific pavement markings and signage have been shown to be beneficial to traffic flow, and our results suggest that they may also reduce the number of bicycle-motor vehicle crashes and subsequent injuries and fatalities. As a relatively low-cost traffic feature, community considerations for further implementation of these facilities are justified.

Project description:Transportation by motorcycle and bicycle has become popular in Taiwan, this study was designed to investigate the protective effect of helmet use during motorcycle and bicycle accidents by using a propensity score-matched study based on trauma registry system data.Data of adult patients hospitalized for motorcycle or bicycle accidents between January 1, 2009 and December 31, 2015 were retrieved from the Trauma Registry System. These included 7735 motorcyclists with helmet use, 863 motorcyclists without helmet use, 76 bicyclists with helmet use, and 647 bicyclists without helmet use. The primary outcome measurement was in-hospital mortality. Secondary outcomes were the hospital length of stay (LOS), intensive care unit (ICU) admission rate, and ICU LOS. Normally distributed continuous data were analyzed by the unpaired Student t-test, and non-normally distributed data were compared using the Mann-Whitney U-test. Two-sided Fisher exact or Pearson chi-square tests were used to compare categorical data. Propensity score matching (1:1 ratio using optimal method with a 0.2 caliper width) was performed using NCSS software, adjusting for the following covariates: sex, age, and comorbidities. Further logistic regression was used to evaluate the effect of helmet use on mortality rates of motorcyclists and bicyclists, respectively.The mortality rate for motorcyclists with helmet use (1.1%) was significantly lower than for motorcyclists without helmet use (4.2%; odds ratio [OR] 0.2; 95% confidence interval [CI]: 0.17-0.37; p < 0.001). Among bicyclists, there was no significant difference in mortality rates between the patients with helmet use (5.3%) and those without helmet use (3.7%; OR 1.4; 95% CI: 0.49-4.27; p = 0.524). After propensity-score matching for covariates, including sex, age, and comorbidities, 856 well-balanced pairs of motorcyclists and 76 pairs of bicyclists were identified for outcome comparison, showing that helmet use among motorcyclists was associated with lower mortality rates (OR 0.2; 95% CI: 0.09-0.44; p < 0.001). In contrast, helmet use among bicyclists was not associated with a decrease in mortality (OR 1.3; 95% CI: 0.30-5.96; p = 0.706). The hospital LOS was also significantly shorter for motorcyclists with helmet use than for those without (9.5 days vs. 12.0 days, respectively, p < 0.001) although for bicyclists, helmet use was not associated with hospital LOS. Fewer motorcyclists with helmet use were admitted to the ICU, regardless of the severity of injury; however, no significant difference of ICU admission rates was found between bicyclists with and without helmets.Motorcycle helmets provide protection to adult motorcyclists involved in traffic accidents and their use is associated with a decrease in mortality rates and the risk of head injuries. However, no such protective effect of helmet use was observed for bicyclists involved in collisions.

Project description:The aim of this study was to investigate and compare the injury characteristics, severity, and outcome between underweight and normal-weight patients hospitalized for the treatment of all kinds of trauma injury.This study was based on a level I trauma center Taiwan.The detailed data of 640 underweight adult trauma patients with a body mass index (BMI) of <18.5 kg/m and 6497 normal-weight adult patients (25 > BMI ≥ 18.5 kg/m) were retrieved from the Trauma Registry System between January 1, 2009, and December 31, 2014. Pearson's chi-square test, Fisher's exact test, and independent Student's t-test were performed to compare the differences. Propensity score matching with logistic regression was used to evaluate the effect of underweight on mortality.Underweight patients presented a different bodily injury pattern and a significantly higher rate of admittance to the intensive care unit (ICU) than did normal-weight patients; however, no significant differences in the Glasgow Coma Scale (GCS) score, injury severity score (ISS), in-hospital mortality, and hospital length of stay were found between the two groups. However, further analysis of the patients stratified by two major injury mechanisms (motorcycle accident and fall injury) revealed that underweight patients had significantly lower GCS scores (13.8 ± 3.0 vs 14.5 ± 2.0, P = 0.020), but higher ISS (10.1 ± 6.9 vs 8.4 ± 5.9, P = 0.005), in-hospital mortality (odds ratio, 4.4; 95% confidence interval, 1.69-11.35; P = 0.006), and ICU admittance rate (24.1% vs 14.3%, P = 0.007) than normal-weight patients in the fall accident group, but not in the motorcycle accident group. However, after propensity score matching, logistic regression analysis of well-matched pairs of patients with either all trauma, motorcycle accident, or fall injury did not show a significant influence of underweight on mortality.Exploratory data analysis revealed that underweight patients presented a different bodily injury pattern from that of normal-weight patients, specifically a higher incidence of pneumothorax in those with penetrating injuries and of femoral fracture in those with struck on/against injuries; however, the injury severity and outcome of underweight patients varied depending on the injury mechanism.

Dataset Information

Characteristics and comparison between e-scooters and bicycle-related trauma: a multicentre cross-sectional analysis of data from a road collision registry.

Background

Methods

Results

Conclusions

Publications

Characteristics and comparison between e-scooters and bicycle-related trauma: a multicentre cross-sectional analysis of data from a road collision registry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets