Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents

Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work.

Contribution to the Investigation of Motorcyclists’ Speed Prediction Equations for Two-Lane Rural Roads

The calculation of speed prediction equations has been the subject of numerous researches in the past. The majority of them present models to predict free-flow speed in terms of the road geometry at the curved road sections and more specifically in terms of the radiuses of the curves. Common characteristic is that none of them approaches the speed behavior of motorcycles since they are excluded from the datasets of the various studies. Instead, the models usually predict operating speed for other vehicle types such as passenger cars, vans, pickups and trucks. The present paper aims to cover this gap by developing speed prediction equations for motorcycles. For this purpose a new methodology is proposed while field measurements were carried out in order to obtain an adequate dataset of free-flow speeds along the curved sections of three different two lane rural roads. The aforementioned field measurements were conducted by two participants incorporating various road conditions (e.g. light conditions, experience level, familiarity with the routes). The ultimate target was the development of speed prediction equations by calculating the optimum regression curves between the curve radius’ and the corresponding velocities for the different road conditions. The research revealed that the proposed methodology could be used as a very useful tool to investigate motorcyclists’ behavior at curved road sections. Moreover it was feasible to draw conclusions correlating the speed adjustment with the various driving conditions.

Spatial analysis of driving accidents leading to deaths related to motorcyclists in Tehran

Purpose: Traffic accidents are one of the main causes of death and disability, causing annual deaths of 1.23 million and tens of millions injured people worldwide. Meanwhile, a significant proportion of the deaths and injuries caused by traffic accidents occur among motorcyclists. According to the world health organization's 2015 report, about 25% of deaths from traffic accidents occur in motorists. In Iran, a significant proportion of deaths and injuries result from traffic accidents among motorcyclists, especially in passages within the cities. According to traffic police, about 25% of deaths and 50% of injuries in traffic accidents of Tehran are reported among motorcyclists. Therefore, due to the importance of this issue, the spatial factors influencing the incidence of motorcycle-related accidents in Tehran were investigated using the geographic information system. Methods: The present work was a cross-sectional and descriptive analysis study. The data necessary for the study were extracted from Tehran traffic police as well as municipality databases. Zoning maps were used to display the distribution of events. In the analytical investigation, Moran index was used to determine the distribution pattern of the events, while Getis-Ord G^* statistics were applied to analyze hot spots. To investigate the role of regional and environmental factors in the frequency of traffic accidents related to motorcyclists in geographic units (Tehran 22 districts), Poisson regression and negative binomial models were used. The geographically weighted regression (GWR) model was used to analyze the relationship between environmental factors and the location of these events. Statistical analyses were performed using SPSS, STATA, ARC-GIS and GWR software. Results: The southern and eastern margins of Tehran are the most vulnerable areas in terms of deaths related to traffic accidents of motorcyclists. Highways are considered the location of most traffic accidents which lead to death of motorcyclists. Getis-Ord General G^*(p < 0.04) indicates that the distribution of high-risk points is statistically significant. The final model showed that in Tehran, the association of different variables including demographic characteristics, pathways network and type of land use with the number of accidents in geographic units was statistically significant. The spatial distribution of traffic accidents leading to deaths of motorcyclists in the center of Tehran varies considerably with changes in population density, length of highways, volume of traffic, and land use in different parts. Conclusion: Most of the traffic accidents leading to deaths of motorcyclists occur in highways. Various environmental variables play a role in determining the distribution pattern of these types of events. Through proper traffic management, controlling environmental risk factors and training people the safety of motorcyclists in Tehran can be improved.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Management of Traumatic Brain Injuries at the Kara Regional Hospital

Introduction: Traumatic Brain Injury (TBI) is a major public health problem causing significant morbidity and mortality in young adults. This study aimed to describe the epidemiological, diagnostic, therapeutic, and evolutionary aspects of TBI. Materials and Methods: This was a prospective, descriptive study conducted from 1 April 2022 to 31 March 2023 on patients admitted to and treated for cranioencephalic trauma in the General Surgery department of Kara Regional Hospital. Results: Eighty-three (83) patients with cranioencephalic trauma were managed out of 773 patients admitted to the department during the study period. The mean age was 34 ± 14.98 years and the sex ratio was 3.6 in favour of men. Motorbike taxi drivers were the social group most affected (n = 33, 40%). The causes of trauma were dominated by public road accidents (n = 80;96%). TBI was mild (n = 40;48%), moderate (n = 35;42%) and severe (n = 8;10%). Cerebral CT scans were performed in 19 patients (23%). Cerebral contusion (n = 4) was the most frequent cerebral lesion. Six patients (7%) with severe head injuries were transferred to Kara University Hospital. Six deaths (7%) occurred in patients with severe head injuries. The main sequelae were intermittent headaches in all patients reviewed, and memory problems (6%). Conclusion: Traumatic brain injuries are common at Kara Regional Hospital. Severe cranial trauma is less frequent but leads to death because of financial difficulties and limited technical facilities.

The Association of World Health Organisation (WHO) Safe Community Programme with Death Rate from Motorcycle Accidents in Iran

Background: Many developing countries are facing the problem of rapidly rising death rate from fatal accidents involving motorcycles. Objective: To determine the effect of participation and implementation of the World Health Organization (WHO) Safe Community Programme on death rate from fatal motorcycle accidents. Methods: Motorcycle’ fatal accident data were obtained from forensic medicine departments and hospital records in 11 cities located in three provinces in Iran during 2006-2007. Data were analyzed using chi-square and ANOVA tests. Fidelity of the data was safeguarded by using national security coding for each individual involved in the accident. Results: The highest death rate was found in the Fars province followed by Khorasan and Bushehr provinces. In Fars province, the highest mortality rate was found in Niriz city, which did not implement the Safe Community Programme and the lowest death rate was reported from Arsanjan city participating in Safe Community. Similar results were found in the Khorasan province. In Busher province, the highest death rate was found in Busher city participating in the program and the lowest in Genaveh city—not participating in the program. Among sex and age groups, males aged 19 - 39 years old had a highest death rate. Half of the death occurred at the accident scene—25% during a transfer to the hospital and 25% of death occurred at the hospital. Conclusions: The Safe Community Programme is a promising model to prevent death from fatal motorcycle accidents in urban areas in Iran.

Disability to Admit as a Change of Life after a Road Crash: Estimates and Related Factors in Benin for Prevention

Background: Disability is an underestimated issue in public health, with road crashes as leading cause. In Africa, motorcyclists disproportionately bear the burden of road crash injuries, including disability. To contribute to decision-making for disability prevention, this study aims to determine the prevalence and factors associated with disability at 12 months among motorcyclists involved in road crashes in Benin. Methods: This is a prospective, cross-sectional, analytical study based on 12-month follow-up data from a cohort of road crash victims set up in five hospitals in Benin. Data were collected from November 2020 to January 2021. Sample used for this analysis size was 297 motorcyclists. Disability was assessed using the Washington Group on Disabilities Statistics question set. Logistic regression analysis was used to identify risk factors for disability in victims 12 months after the crash. Results: The prevalence of disability was 12.5% 95% CI (9.2 - 16.7). Disability occurrence was associated with being over 45 years old (OR = 3.1;95% CI = 1.5 - 6.6), severity of initial injury (OR = 3.3;95% CI = 1.5 - 7.3) and hospitalisation of the victim (OR = 6.9;95% CI = 2.0 - 24). Conclusion: Age over 45 years, severity of initial injuries and hospitalisation of the victim were risk factors for the occurrence of disability among motorcyclists who were victims of road crashes in Benin. User awareness, law enforcement, holistic and early management of road crash victims could contribute to reducing the prevalence of disability among victims in Benin.