A proportional odds model of risk behaviors associated with recurrent road traffic crashes among young adults in Kuwait

Background The aims of this cross-sectional study were to i) assess one-year period prevalence of one, two, three or more road traffic crashes (RTCs) as an ordinal outcome and ii) identify the drivers’ characteristics associated with this ordinal outcome among young adult drivers with propensity to recurrent RTCs in Kuwait. Methods During December 2016, 1465 students, 17 years old or older from 15 colleges of Kuwait University participated in this cross-sectional study. A self-administered questionnaire was used for data collection. One-year period prevalence (95% confidence interval (CI)) of one, two, three or more RTCs was computed. Multivariable proportional odds model was used to identify the drivers’ attributes associated with the ordinal outcome. Results One-year period prevalence (%) of one, two and three or more RTCs respectively was 23.1 (95% CI: 21.2, 25.6), 10.9 (95% CI: 9.4, 12.6), and 4.6 (95% CI: 3.6, 5.9). Participants were significantly (p < 0.05) more likely to be in higher RTCs count category than their current or lower RCTs count, if they habitually violated speed limit (adjusted proportional odds ratio (pORadjusted) = 1.40; 95% Cl: 1.13, 1.75), ran through red lights (pORadjusted = 1.64; 95%CI: 1.30, 2.06), frequently (≥ 3) received multiple (> 3) speeding tickets (pORadjusted = 1.63; 95% CI: 1.12, 2.38), frequently (> 10 times) violated no-parking zone during the past year (pORadjusted = 1.64; 95% CI: 1.06, 2.54) or being a patient with epilepsy (pORadjusted = 4.37; 95% CI: 1.63, 11.70). Conclusion High one-year period prevalence of one, two and three or more RTCs was recorded. Targeted education based on identified drivers’ attributes and stern enforcement of traffic laws may reduce the recurrent RTCs incidence in this and other similar populations in the region.

Short-Term Segment-Level Crash Risk Prediction Using Advanced Data Modeling with Proactive and Reactive Crash Data

Highway crashes, along with the property damage, personal injuries, and fatalities that they cause, continue to present one of the most significant and critical transportation problems. At the same time, provision of safe travel is one of the main goals of any transportation system. For this reason, both in transportation research and practice much attention has been given to the analysis and modeling of traffic crashes, including the development of models that can be applied to predict crash occurrence and crash severity. In general, such models assess short-term crash risks at a given highway facility, thus providing intelligence that can be used to identify and implement traffic operations strategies for crash mitigation and prevention. This paper presents several crash risk and injury severity assessment models applied at a highway segment level, considering the input data that is typically collected or readily available to most transportation agencies in real-time and at a regional network scale, which would render them readily applicable in practice. The input data included roadway geometry characteristics, traffic flow characteristics, and weather condition data. The paper develops, tests, and compares the performance of models that employ Random effects Bayesian Logistics Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Random Forest, and Gradient Boosting Machine methods. The paper applies random oversampling examples (ROSE) method to deal with the problem of data imbalance associated with the injury severity analysis. The models were trained and tested using a dataset of 10,155 crashes that occurred on two interstate highways in New Jersey over a two-year period. The paper also analyzes the potential improvement in the prediction abilities of the tested models by adding reactive data to the analysis. To that end, traffic crashes were classified in multiple classes based on the driver age and the vehicle age to assess the impact of these attributes on driver injury severity outcomes. The results of this analysis are promising, showing that the simultaneous use of reactive and proactive data can improve the prediction performance of the presented models.

Fatality risk and issues of inequity among vulnerable road users in South Africa

Background Contextual effects from the physical and social environment contribute to inequitable protection for a large proportion of road users, especially in low- and middle-income countries like South Africa where distorted urban planning and socio-spatial disparities from the apartheid era prevail. Objectives This paper examines the differentiated risk of road traffic crashes and injuries to vulnerable road users in South Africa, including pedestrians, females and users of some modes of public transport, in relation to characteristics of the crashes that proxy a range of contextual influences such as rurality and socio-economic deprivation. Methods The study is based on a descriptive analysis of 33 659 fatal crashes that occurred in South Africa over a three-year period from 2016–2018. Measures of simple proportion, population-based fatality rate, “impact factor” and crash severity are compared between disaggregated groups using Chi-Square analysis, with the Cramer’s V statistic used to assess effect size. Results and significance Key findings show a higher pedestrian risk in relation to public transport vehicles and area-level influences such as the nature of roads or extent of urbanity; higher passenger risk in relation to public transport vehicles and rurality; and higher risk for female road users in relation to public transport vehicles. The findings have implications for prioritising a range of deprivation-related structural effects. In addition, we present a “User-System-Context” conceptual framework that allows for a holistic approach to addressing vulnerability in the transport system. The findings provide an important avenue for addressing the persistently large burden of road traffic crashes and injuries in the country.

Mental health and behavioural factors involved in road traffic crashes by young adults: analysis of the Raine Study

BackgroundRoad traffic crashes (RTC) are a leading cause of mortality and morbidity in young people. Severe mental health and behavioural conditions increase the likelihood of RTC, as do a range of driving-risk activities.MethodWe used data from the Raine Study, a prebirth cohort from Perth, Australia, to assess the relationship between measures of common mental health or behavioural conditions (Child Behavior Checklist Internalising and Externalising scores) at age 17 and subsequent RTC by 27 years, controlling for substance use and driving-risk activities.ResultsBy 27 years of age, of 937 participants, 386 (41.2%) reported zero crashes and 551 (58.8%) reported ≥1 crashes. In the baseline Poisson model, increased Externalising scores (eg, aggression and delinquency) were associated with increased RTC (incidence rate ratio (IRR)=1.02, 95% CI 1.01 to 1.02): increased Internalising scores (eg, anxiety and depression) were associated with fewer RTC (IRR=0.99, 95% CI 0.98 to 1.00). In the fully adjusted model, the mental health measures were not significant (Externalising IRR=1.01, 95% CI 0.99 to 1.02: Internalising IRR=0.99, 95% CI 0.99 to 1.00). Risky driver activities, such as falling asleep while driving (IRR=1.34), more frequent use of a hands-free telephone (IRR=1.35) and more frequent hostility towards other drivers (IRR=1.30) increased the rate of RTC.ConclusionMeasures of mental health scores at age 17 were not predictive of subsequent RTC, after adjusting for measures of driving-risk activities. We need to better understand the determinants of externalising and risky driving behaviours if we are to address the increased risk of RTC.

Epidemiology, Incidence and Trend of Injuries in Iran: A National Study

Background: Injuries are one of the well-known leading causes of disability and mortality in all societies. This study aims to determine the incidence and trend of injuries and their epidemiologic characteristics in Iran.Methods: In a cross sectional study, injuries fatality data from 2006 to 2016 were obtained from the registry of the Ministry of Health and Medical Education (Iran) and analyzed to determine the epidemiological pattern of injuries. Data were analyzed using descriptive analysis. Excel and statistical package of SPSS version 22 were used for data analysis. The P value of ≤ 0.05 was considered significant. Results: The highest incidence of injuries was related to traffic injuries with 546.4 per 100000 populations, followed by trauma and falls from heights with 497.7 and 195.2 per 100000 population, respectively. The highest incidence of traffic injuries in Iran had occurred in the year 2011 with 628.1 per 100000 population.Conclusion: Regarding the high incidence of injuries, especially traffic crashes, traumas and falls the priorities for close monitoring of these injuries during the high-risk periods in order to decrease and control of the rate of the injuries strongly felt.

OPTIMISING ROAD LIGHTING TO REDUCE ROAD TRAFFIC CRASHES

Pedestrians and motorcyclists are vulnerable road users, being over represented in road traffic collisions (RTCs). One assumed benefit of road lighting is a reduction in RTCs after dark by countering the impairment to the visual detection of hazards that occur after dark. One way to optimise the use of road lighting is to light only those sections of road where light level, and hence visibility, is an important factor. The current study used change in ambient light level on RTCs to investigate those situations where improved vision is likely to have significant impact, and therefore the situations where road lighting is of better cost-benefit effectiveness. For both motorcyclist and pedestrian RTCs there was a significant increase in overall RTC risk in darkness compared to daylight, indicating that there may be an overall benefit of road lighting. While darkness was a particular detriment at junctions for motorcyclists and on high-speed roads for pedestrians, road lighting may not be effective mitigation in either case and therefore alternative ways of increasing conspicuity should be considered.