Introduction: Every year more than 1.2 million people worldwide die due to trauma sustained in road crashes, with an additional number of people injured exceeding 50 million. To a large extent, this applies to so called "unprotected road users", including pedestrians. The risk involved in a traffic crash for pedestrians can result from many factors, one of which is participation in road traffic when under the influence of alcohol. The aim of this study was to analyze the impact of alcohol use among pedestrians as unprotected road traffic participants, and the consequences of them being struck by motor vehicles.
Material And Methods: The source of data was the medical documentation of the Department of Forensic Medicine at the Medical University of Warsaw. The sample for this research consisted of 313 pedestrians who were victims of fatal road crashes resulting from a collision with a mechanical vehicle. The obtained results were subjected to statistical analysis using the STATISTICA version 12.5 program (StatSoft Polska, Cracow, Poland).
Results: Male fatalities constituted the majority of the study sample. Nearly half of the fatal pedestrian victims were found to be under the influence of alcohol. The statistical analysis demonstrated a significant relationship between the gender and age of the victims, as well as between the place of the event, the place of death, the mechanism of the event, and the presence of alcohol in pedestrians.
Conclusions: Among pedestrians, victims of road crashes who were under the influence of alcohol were predominantly drunk young males. Victims under the influence of alcohol were more likely to become fatalities in crashes where the mechanism of the incident was being struck by a passenger car, and when the place of the incident was a rural area, in these cases the rates of death directly at the scene were much more frequent. The eradication of alcohol consumption by all road users should be the overriding objective of all measures aimed at reducing the number of road crashes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6517985 | PMC |
http://dx.doi.org/10.3390/ijerph16081471 | DOI Listing |
Traffic Inj Prev
January 2025
School of Traffic & Transportation Engineering, Changsha University of Science & Technology, Changsha, Hunan, China.
Objective: This study aims to investigate the causes of 2-vehicle collisions involving an autonomous vehicle (AV) and a conventional vehicle (CV). Prior research has primarily focused on the causes of crashes from the perspective of AVs, often neglecting the interactions with CVs.
Method: To address this limitation, the study proposes a classification framework for crash causation patterns in 2-vehicle collisions involving an AV and a CV, considering their interactions.
Cureus
December 2024
Emergency Medicine Department, Aga Khan University, Karachi, PAK.
Background: Road traffic injuries (RTIs) are currently the ninth most common cause of mortality and are expected to increase in the future. RTIs rank in the top three reasons why young people die. Because of the high incidence and mortality risk, proper trauma care has been prioritized for RTI patients who present to the emergency department.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Industrial Engineering, Università degli Studi di Firenze, Via di Santa Marta, 3, 50139, Firenze, Italy.
The rise of Personal Light Electric Vehicles (PLEVs), including electric bicycles and electric kick scooters, represents a relevant trend in current urban mobility. PLEVs offer economic, social, and environmental advantages, making them increasingly attractive for short-distance travel. Despite their benefits, concerns about the safety of PLEVs, particularly related to road accidents, have arisen due to their growing presence in urban areas.
View Article and Find Full Text PDFPLoS One
January 2025
School of Public Health & Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Introduction: Low- and middle-income countries experience high injury-related mortality rates, with road traffic crashes being a significant contributor in Nigeria. Data from trauma registries are crucial for designing and advocating for trauma intervention programmes. However, there is limited research to inform the development of trauma registries in a Nigerian setting.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and network architecture optimization. This paper pioneers the use of the CLIP (Contrastive Language-Image Pre-training) model for fatigue detection.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!