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- Title
Injuries With Electric vs Conventional Scooters and Bicycles.
- Authors
Fernandez, Adrian N.; Li, Kevin D.; Patel, Hiren V.; Allen, Isabel Elaine; Ghaffar, Umar; Hakam, Nizar; Breyer, Benjamin N.
- Abstract
Key Points: Question: Are demographic characteristics, injury types, and health care use associated with injuries involving electric scooters or bicycles different from those involving conventional scooters or bicycles? Findings: In a cross-sectional study including 86 623 individuals, electric bicycle injuries increased by nearly 100% and electric scooter injuries increased by more than 45% annually. Injured electric vehicle users were older and less commonly helmeted than those injured from conventional vehicles, with significantly lower odds of hospitalization in individuals who were Black than in those who were White. Meaning: The findings from this study suggest that safer riding infrastructure and rider practices are important to curtail the rise of micromobility injuries. Importance: Micromobility, the use of small vehicles (primarily scooters and bicycles), has become a standard transportation method in the US. Despite broad adoption of electric micromobility vehicles, there is a paucity of data regarding the injury profiles of these vehicles, particularly in the US. Objective: To characterize micromobility injury trends in the US, identify demographic characteristic differences in users of electric and conventional vehicles, and identify factors associated with hospitalization. Design, Setting, and Participants: This cross-sectional study queried the National Electronic Injury Surveillance System, a comprehensive database that collates injury data associated with consumer products from emergency departments across the US to provide national estimates, from calendar year 2017 to 2022. Data on micromobility vehicle injuries (bicycles, scooters, electric bicycles [e-bicycles], and electric scooters [e-scooters]) were obtained. Main Outcomes and Measures: Trends in injury and hospitalization counts, injury characteristics, and factors associated with hospitalization. Results: From 2017 to 2022, the US recorded 2 499 843 bicycle (95% CI, 1 948 539-3 051 147), 304 783 scooter (95% CI, 232 466-377 099), 45 586 e-bicycle (95% CI, 17 684-73 488), and 189 517 e-scooter (95% CI, 126 101-252 932) injuries. The median age of the riders was 28 (IQR, 12-51) years; 72% were male, 1.5% Asian, 13% Black, 12% Hispanic, and 49% White. Annual e-bicycle and e-scooter injuries increased from 751 (95% CI, 0-1586) to 23 493 (95% CI, 11 043-35 944) and injuries increased from 8566 (95% CI, 5522-11 611) to 56 847 (95% CI, 39 673-74 022). Compared with conventional vehicles, electric vehicle accidents involved older individuals (median age, 31 vs 27 years; P <.001) and a higher proportion of Black riders (25% vs 12%; P <.001). Helmet use was less in electric vehicle incidents compared with conventional vehicles (43% vs 52%; P =.02), and injuries were more common in urban settings (83% vs 71%; P =.008). Age-adjusted odds of hospitalization among all Black individuals compared with White individuals was 0.76 (95% CI, 0.59-0.98; P =.04). Conclusions and Relevance: In this cross-sectional study of micromobility vehicles, an increased number of injuries and hospitalizations was observed with electric vehicles compared with conventional vehicles from 2017 to 2022. These findings suggest the need for change in educational policies, infrastructure, and law to recenter on safety with the use of micromobility vehicles. This cross-sectional study examines the number of injuries and hospitalizations associated with electric vs conventional bicycles and scooters from 2017 to 2022.
- Subjects
UNITED States; CYCLING accidents; WOUNDS &; injuries; RISK assessment; CROSS-sectional method; DATA analysis; MOTORCYCLING injuries; HOSPITAL care; EMERGENCY room visits; LOGISTIC regression analysis; DESCRIPTIVE statistics; CHI-squared test; MANN Whitney U Test; STATISTICS; EPIDEMIOLOGY; SOCIODEMOGRAPHIC factors; CONFIDENCE intervals; DATA analysis software; BICYCLES; REGRESSION analysis
- Publication
JAMA Network Open, 2024, Vol 7, Issue 7, pe2424131
- ISSN
2574-3805
- Publication type
Article
- DOI
10.1001/jamanetworkopen.2024.24131