IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i7p5352-d1113044.html
   My bibliography  Save this article

Analysis of Risky Riding Behavior Characteristics of the Related Road Traffic Injuries of Electric Bicycle Riders

Author

Listed:
  • Jiayu Huang

    (School of Public Health, Shantou University, Shantou 515041, China
    These authors contributed equally to this work.)

  • Ziyi Song

    (School of Public Health, Shantou University, Shantou 515041, China
    Injury Prevention Research Center, Shantou University Medical College, Shantou 515041, China
    These authors contributed equally to this work.)

  • Linlin Xie

    (School of Public Health, Shantou University, Shantou 515041, China)

  • Zeting Lin

    (School of Public Health, Shantou University, Shantou 515041, China
    Injury Prevention Research Center, Shantou University Medical College, Shantou 515041, China)

  • Liping Li

    (School of Public Health, Shantou University, Shantou 515041, China
    Injury Prevention Research Center, Shantou University Medical College, Shantou 515041, China)

Abstract

Electric bicycle (EB) riders, being vulnerable road users (VRUs), are increasingly becoming victims of road traffic injuries (RTIs). This study aimed to determine the current status and epidemiological characteristics of RTIs among EB riders through a questionnaire survey and roadside observations in Shantou to provide a scientific basis for the prevention and control of electric bicycle road traffic injuries (ERTIs). A total of 2412 EB riders were surveyed, and 34,554 cyclists were observed in the study. To analyze the relationship between riding habits and injuries among EB riders, chi-square tests and multi-factor logistic regression models were employed. The findings reveal that the prevalence of ERTIs in Shantou was 4.81%, and the most affected group was children under 16 years old, accounting for 9.84%. Risky behavior was widespread among EB riders, such as the infrequent wearing of safety helmets, carrying people on EBs, riding on sidewalks, and listening to music with headphones while bicycling. Notably, over 90% of those who wore headphones while bicycling engaged in this risky behavior. The logistic regression analysis showed that honking the horn (odds ratio (OR): 2.009, 95% CI: 1.245–3.240), riding in reverse (OR: 4.210, 95% CI: 2.631–6.737), and continuing to ride after a fault was detected (OR: 2.010, 95% CI: 1.188–3.402) all significantly increased the risk of ERTIs (all p < 0.05). Risky riding behavior was significantly less observed at traffic intersections with traffic officers than at those without (all p < 0.001).

Suggested Citation

  • Jiayu Huang & Ziyi Song & Linlin Xie & Zeting Lin & Liping Li, 2023. "Analysis of Risky Riding Behavior Characteristics of the Related Road Traffic Injuries of Electric Bicycle Riders," IJERPH, MDPI, vol. 20(7), pages 1-12, March.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:7:p:5352-:d:1113044
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/7/5352/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/7/5352/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Changxi Ma & Dong Yang & Jibiao Zhou & Zhongxiang Feng & Quan Yuan, 2019. "Risk Riding Behaviors of Urban E-Bikes: A Literature Review," IJERPH, MDPI, vol. 16(13), pages 1-18, June.
    2. Zhaohao Zhong & Zeting Lin & Liping Li & Xinjia Wang, 2022. "Risk Factors for Road-Traffic Injuries Associated with E-Bike: Case-Control and Case-Crossover Study," IJERPH, MDPI, vol. 19(9), pages 1-12, April.
    3. Tao Wang & Sihong Xie & Xiaofei Ye & Xingchen Yan & Jun Chen & Wenyong Li, 2020. "Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model," IJERPH, MDPI, vol. 17(13), pages 1-18, July.
    4. Keila González-Gómez & María Castro, 2019. "Evaluating Pedestrians’ Safety on Urban Intersections: A Visibility Analysis," Sustainability, MDPI, vol. 11(23), pages 1-16, November.
    5. Ping Yuan & Guojia Qi & Xiuli Hu & Miao Qi & Yanna Zhou & Xiuquan Shi, 2023. "Characteristics, likelihood and challenges of road traffic injuries in China before COVID-19 and in the postpandemic era," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    2. Manuel Rey-Moreno & Rafael Periáñez-Cristóbal & Arturo Calvo-Mora, 2022. "Reflections on Sustainable Urban Mobility, Mobility as a Service (MaaS) and Adoption Models," IJERPH, MDPI, vol. 20(1), pages 1-14, December.
    3. Lei Zhang & Shengrui Zhang & Bei Zhou & Yan Huang & Dan Zhao & Shuaiyang Jiao, 2022. "Exploring Unobserved Heterogeneity in Cyclists’ Occupying Motorized Vehicle Lane Behaviors at Different Bike Facility Configurations," IJERPH, MDPI, vol. 19(2), pages 1-22, January.
    4. Bichen Wang & Peng Jing & Chengxi Jiang, 2023. "Combining SEM, fsQCA and BNs to Explore E-Bike Riders’ Helmet Wearing Intentions under the Impact of Mandatory Policies: An Empirical Study in Zhenjiang," Sustainability, MDPI, vol. 15(24), pages 1-25, December.
    5. Cheng Wang & Liyang Wei & Kun Wang & Hongya Tang & Bo Yang & Mengfan Li, 2022. "Investigating the Factors Affecting Rider’s Decision on Overtaking Behavior: A Naturalistic Riding Research in China," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    6. Tao Wang & Sihong Xie & Xiaofei Ye & Xingchen Yan & Jun Chen & Wenyong Li, 2020. "Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model," IJERPH, MDPI, vol. 17(13), pages 1-18, July.
    7. Lining Liu & Xiaofei Ye & Tao Wang & Xingchen Yan & Jun Chen & Bin Ran, 2022. "Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network," IJERPH, MDPI, vol. 19(10), pages 1-17, May.
    8. Piotr Kędziorek & Zbigniew Kasprzyk & Mariusz Rychlicki & Adam Rosiński, 2023. "Analysis and Evaluation of Methods Used in Measuring the Intensity of Bicycle Traffic," Energies, MDPI, vol. 16(2), pages 1-18, January.
    9. Marjolein van der Vlegel & Juanita A. Haagsma & Leonie de Munter & Mariska A. C. de Jongh & Suzanne Polinder, 2020. "Health Care and Productivity Costs of Non-Fatal Traffic Injuries: A Comparison of Road User Types," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    10. Matteo della Mura & Serena Failla & Nicolò Gori & Alfonso Micucci & Filippo Paganelli, 2022. "E-Scooter Presence in Urban Areas: Are Consistent Rules, Paying Attention and Smooth Infrastructure Enough for Safety?," Sustainability, MDPI, vol. 14(21), pages 1-36, November.
    11. Luís Pádua & José Sousa & Jakub Vanko & Jonáš Hruška & Telmo Adão & Emanuel Peres & António Sousa & Joaquim J. Sousa, 2020. "Digital Reconstitution of Road Traffic Accidents: A Flexible Methodology Relying on UAV Surveying and Complementary Strategies to Support Multiple Scenarios," IJERPH, MDPI, vol. 17(6), pages 1-24, March.
    12. Jibiao Zhou & Xinhua Mao & Yiting Wang & Minjie Zhang & Sheng Dong, 2019. "Risk Assessment in Urban Large-Scale Public Spaces Using Dempster-Shafer Theory: An Empirical Study in Ningbo, China," IJERPH, MDPI, vol. 16(16), pages 1-28, August.
    13. Jenkins, Michael & Lustosa, Lucio & Chia, Victoria & Wildish, Sarah & Tan, Maria & Hoornweg, Daniel & Lloyd, Meghann & Dogra, Shilpa, 2022. "What do we know about pedal assist E-bikes? A scoping review to inform future directions," Transport Policy, Elsevier, vol. 128(C), pages 25-37.
    14. Anat Meir, 2022. "Can Complete-Novice E-Bike Riders Be Trained to Detect Unmaterialized Traffic Hazards in the Urban Environment? An Exploratory Study," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    15. David Kohlrautz & Tobias Kuhnimhof, 2023. "E-Bike Charging Infrastructure in the Workplace—Should Employers Provide It?," Sustainability, MDPI, vol. 15(13), pages 1-11, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:7:p:5352-:d:1113044. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.