Factors associated with motorcycle traffic crash fatalities among active duty U.S. Army personnel

Objective: Research on factors associated with motorcycle fatalities among active duty U.S. Army personnel is limited. This analysis describes motorcycle crash–related injuries from 1995 through 2014 and assesses the effect of alcohol use and helmet use on the risk of fatal injury among active duty U.S. Army motorcycle operators involved in a traffic crash, controlling for other factors shown to be potentially associated with fatality in this population.

Methods: Demographics, crash information, and injury data were obtained from safety reports maintained in the Army Safety Management Information System. Traffic crashes were defined as crashes occurring on a paved public or private roadway or parking area, including those on a U.S. Army installation. Analysis was limited to motorcycle operators. Odds ratios (ORs) and 95% confidence intervals (95% CIs) from a multivariable analysis estimated the effect of alcohol use and helmet use on the risk of a fatal injury given a crash occurred, controlling for operator and crash characteristics.

Results: Of the 2,852 motorcycle traffic crashes, most involved men (97%), operators aged 20–29 years of age (60%), and operators who wore helmets (95%) and did not use alcohol (92%). Two thirds of reported crashes resulted in injuries requiring a lost workday; 17% resulted in fatality. Controlling for operator and crash characteristics, motorcycle traffic crashes involving operators who had used alcohol had a 3.1 times higher odds of fatality than those who did not use alcohol (OR =3.14; 95% CI, 2.17–4.53). Operators who did not wear a helmet had 1.9 times higher odds of fatality than those who did wear a helmet (OR =1.89; 95% CI, 1.24–2.89).

Conclusions: Among U.S. Army motorcycle operators, alcohol use and not wearing a helmet increased the odds of fatality, given that a crash occurred, and additional modifiable risk factors were identified. Results will help inform U.S. Army motorcycle policies and training.     

Factors associated with higher levels of injury severity in occupants of motor vehicles that were severely damaged in traffic crashes in Kentucky, 2000-2001

OBJECTIVES: The majority of motor vehicle occupants who were killed or hospitalized in crashes in Kentucky in 2000-2001 occupied vehicles that were severely damaged in the crash. Even so, overall only a small percentage of all severely damaged vehicle occupants were killed or hospitalized. The purpose was to identify occupant, vehicle, crash, and roadway/environmental factors that were associated with increased risk of severe injury in crashes where the occupant's vehicle was severely damaged. METHODS: This study probabilistically linked Kentucky's statewide motor vehicle crash and inpatient hospital discharge data files for 2000 and 2001, and selected cases representing occupants of vehicles that were reported by police as having either "severe" or "very severe" damage. For occupants who were identified through data linkage as having been hospitalized, the Injury Severity Score (ISS) was calculated using ICDMAP-90 software, and the scores were stratified into the following categories: critical (>24), severe (15-24), moderate (9-14), and mild (<9). We then created an outcome variable, injury severity level, with five levels: killed; hospitalized with at least moderate injuries (ISS = critical, severe, or moderate); hospitalized with mild injuries (ISS = mild); injured according to the police report but not hospitalized; and no apparent injury according to the police report. We performed a stepwise, ordinal logistic regression of injury severity, using independent variables identified from the existing crash literature. RESULTS: Occupant risk factors for higher levels of injury severity selected by the regression were age (risk increased with age, other factors being equal), female gender, restraint non-use, ejection from the vehicle, and driver impairment (by alcohol and/or drugs). Crash risk factors included head-on collision, collision with a fixed object, vehicle rollover, and vehicle fire. Roadway/environmental factors were federal- or state-maintained roadway and posted speed limit 89 kph (55 mph) or greater. CONCLUSIONS: Many of the identified risk factors are explicitly or implicitly mentioned in the strategic plans of key organizations involved in highway safety and injury prevention in Kentucky. Our analysis provides additional evidence of their importance, and confirms that their mitigation will reduce injury severity in crashes involving severe vehicle damage. Additionally, older occupants and female occupants showed increased risks of serious injury, but to our knowledge these factors are not currently addressed in any state plans. An opportunity exists to clarify the nature of these risks through further studies, which might lead to the identification of countermeasures specific to these populations.     

Motorcyclist injury severity in angle crashes at T-junctions: Identifying significant factors and analysing what made motorists fail to yield to motorcycles

Evidence in literature suggested that motorists’ failure to give way to motorcycles at junctions is the main contributory factor to motorcycle–car accidents that involve gap acceptance (i.e., approach-turn and angle crashes). This paper attempts to examine how motorist’s failure to give way affects motorcyclist injury severity in angle crashes at T-junctions, while controlling for other factors (demographic, vehicle, crash, and environmental factors). Binary logistic models of motorcyclist injury severity were estimated using the data extracted from the Stats19 accident injury database (1991–2004). Angle collisions were classified into several sub-crashes based on the manoeuvres motorcycles and cars were making prior to the accidents. The modelling results showed that injuries were greatest when a travelling-straight motorcycle on the main road crashed into a right-turn car from the minor road, particularly at stop-/yield-controlled junctions. Such crash pattern was assumed to be an accident involving right-of-way violation. Using binary logistic models, factors determining the likelihood of motorist’s failure to yield to motorcycles were also examined. The implications of the research findings of this present study were provided.     

A multinomial logit analysis of factors associated with severity of motorcycle crashes in Ghana

Objective: The objective of this study was to explore the factors affecting motorcycle crash severity in Ghana.

Methods: A retrospective analysis of motorcycle crash data between 2011 and 2015 was conducted using a motorcycle crash data set extracted from the National Road Traffic Crash Database at the Building and Road Research Institute (BRRI) in Ghana. Injury severity was classified into 4 categories: Fatal, hospitalized, injured, and damage only. A multinomial logit modeling framework was used to identify the possible determinants of motorcycle crash severity.

Results: During the study period, a total of 8,516 motorcycle crashes were recorded, of which 22.9% were classified as fatal, 42.1% were classified as hospitalized injuries, 29.4% were classified as slight injuries, and 5.6% were classified as damage-only crashes. The estimation results indicate that the following factors increase the probability of fatal injuries: At a junction; weekend; signage; poor road shoulder; village settlement; tarred and good road surface; and collision between motorcycle and heavy goods vehicle (HGV). Motorcycle crashes occurring during the daytime and on the weekend increases the probability of hospitalized injury. The results also suggest that motorcycle crashes occurring during the daytime, in curves or inclined portions of roads, or in unclear weather conditions decrease the probability of fatal injury.

Conclusions: This study provides further empirical evidence to support motorcycle crash modeling research, which is lacking in developing countries. The ability to understand the various factors that influence motorcycle crash severity is a step forward in providing an appropriate basis upon which informed motorcycle crash policies can be developed. Particular attention should be given to the provision of road signage at junctions and speed humps and controlling traffic during the weekend. In addition, road maintenance should be carried out periodically to address motorcycle safety in Ghana.     

An analysis of motorcycle injury and vehicle damage severity using ordered probit models

Problem: Motorcycles constitute about 19% of all motorized vehicles in Singapore and are generally overrepresented in traffic accidents, accounting for 40% of total fatalities. Method: In this paper, an ordered probit model is used to examine factors that affect the injury severity of motorcycle accidents and the severity of damage to the vehicle for those crashes. Nine years of motorcycle accident data were obtained for Singapore through police reports. These data included categorical assessments of the severity of accidents based on three levels. Damage severity to the vehicle was also assessed and categorized into four levels. Categorical data of this type are best analyzed using ordered probit models because they require no assumptions regarding the ordinality of the dependent variable, which in this case is the severity score. Various models are examined to determine what factors are related to increased injury and damage severity of motorcycle accidents. Results: Factors found to lead to increases in the probability of severe injuries include the motorcyclist having non-Singaporean nationality, increased engine capacity, headlight not turned on during daytime, collisions with pedestrians and stationary objects, driving during early morning hours, having a pillion passenger, and when the motorcyclist is determined to be at fault for the accident. Factors leading to increased probability of vehicle damage include some similar factors but also show some differences, such as less damage associated with pedestrian collisions and with female drivers. In addition, it was also found that both injury severity and vehicle damage severity levels are decreasing over time.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

Injury severity analysis of rollover crashes for passenger cars and light trucks considering temporal stability: A random parameters logit approach with heterogeneity in mean and variance

Problem: The rollover crash is a serious crash type that often causes higher injury severities. Moreover, factors that contribute to the injury severities of rollover crashes may show instabilities in different vehicle types and time periods, which requires further investigations. This study utilizes the rollover crash data in North Carolina from Highway Safety Information System (HSIS) to study the effect instabilities of factors in vehicle type and time periods in rollover crashes. Methods: The injury severities of drivers are estimated using the random parameters logit (RPL) model with heterogeneity in means and variances. Available factors in HSIS have been categorized into three groups, which are drivers, road, and environment, respectively. This study also justifies the segmentations through transferability tests. The effects of identified significant factors are evaluated using marginal effects. Results: Factors such as FWP (farm, wood, and pasture areas), unhealthy physical condition, impaired physical condition, road adverse, and so forth have shown instabilities in marginal effects among vehicle types and time periods. Practical Applications: The finding of this research could provide important references for policy makers and automobile manufactures to help mitigate the injury severity of rollover crashes.     

Ordered logistic models of influencing factors on crash injury severity of single and multiple-vehicle downgrade crashes: A case study in Wyoming

Introduction: The state of Wyoming, like other western United States, is characterized by mountainous terrain. Such terrain is well noted for its severe downgrades and difficult geometry. Given the specific challenges of driving in such difficult terrain, crashes with severe injuries are bound to occur. The literature is replete with research about factors that influence crash injury severity under different conditions. Differences in geometric characteristics of downgrades and mechanics of vehicle operations on such sections mean different factors may be at play in impacting crash severity in contrast to straight, level roadway sections. However, the impact of downgrades on injury severity has not been fully explored in the literature. This study is thus an attempt to fill this research gap. In this paper, an investigation was carried out to determine the influencing factors of crash injury severities of downgrade crashes. Method: Due to the ordered nature of the response variable, the ordered logit model was chosen to investigate the influencing factors of crash injury severities of downgrade crashes. The model was calibrated separately for single and multiple-vehicle crashes to ensure the different factors influencing both types of crashes were captured. Results: The parameter estimates were as expected and mostly had signs consistent with engineering intuition. The results of the ordered model for single-vehicle crashes indicated that alcohol, gender, road condition, vehicle type, point of impact, vehicle maneuver, safety equipment use, driver action, and annual average daily traffic (AADT) per lane all impacted the injury severity of downgrade crashes. Safety equipment use, lighting conditions, posted speed limit, and lane width were also found to be significant factors influencing multiple-vehicle downgrade crashes. Injury severity probability plots were included as part of the study to provide a pictorial representation of how some of the variables change in response to each level of crash injury severity. Conclusion: Overall, this study provides insights into contributory factors of downgrade crashes. The literature review indicated that there are substantial differences between single- and multiple vehicle crashes. This was confirmed by the analysis which showed that mostly, separate factors impacted the crash injury severity of the two crash types. Practical applications: The results of this study could be used by policy makers, in other locations, to reduce downgrade crashes in mountainous areas.     

Nationwide risk factors for hospital readmission for subsequent injury after motor vehicle crashes

Abstract

Objective: Some drivers involved in motor vehicle crashes across the United States may be identified as at risk of subsequent injury by a similar mechanism. The purpose of this study was to perform a national review of the risk factors for hospitalization for a new injury due to a subsequent motor vehicle crash. It was hypothesized that presenting to a different hospital after subsequent injury would result in worse patient outcomes when compared to presentation at the same hospital.

Methods: The Nationwide Readmissions Database for 2010–2014 was queried for all inpatient hospitalizations with injury related to motor vehicle traffic. The primary patient outcome of interest was subsequent motor vehicle crash–related injury within 1 year. The secondary patient outcomes were different hospital subsequent injury presentation, higher Injury Severity Score (ISS), longer length of stay (LOS), and in-hospital death after subsequent injury. The analysis of secondary patient outcomes was performed only on patients who were reinjured. Univariable analysis was performed for each outcome using all variables during the index admission. Multivariable logistic regression was performed using all significant (P < .05) variables on univariate analysis. Results were weighted for national estimates.

Results: During the study period, 1,008,991 patients were admitted for motor vehicle–related injury; 12,474 patients (1.2%) suffered a subsequent injury within 1 year. From the reinjured patients, 32.9% presented to a different hospital, 48.9% had a higher ISS, and 22.1% had a longer LOS. The in-hospital mortality rate after subsequent injury was 1.1%. Presentation to a different hospital for subsequent injury was associated with a longer LOS (odds ratio [OR]?=?1.32; 95% confidence interval [CI], 1.20–1.45; P < .01) and a higher ISS (OR?=?1.38; 95% CI, 1.27–1.49; P < .01). Motorcyclists were more likely to suffer subsequent injury (OR?=?1.39; 95% CI, 1.32–1.46; P < .01) and motorcycle passengers were more likely to present to a different hospital with a subsequent injury (OR?=?2.49; 95% CI, 1.73–3.59; P < .01). Alcohol abuse was associated with subsequent injury (OR?=?1.12; 95% CI, 1.07–1.18; P < .01).

Conclusions: Nearly a third of patients suffering subsequent motor vehicle crash–related injury after an initial motor vehicle crash in the United States present to a different hospital. These patients are more likely to suffer more severe injuries and longer hospitalizations due to their subsequent injury. Future efforts to prevent these injuries must consider the impact of this fragmentation of care and the implications for quality and cost improvements.     

Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou,China

Introduction: With the rapid development of transportation infrastructures in precipitous areas, the mileage of freeway tunnels in China has been mounting during the past decade. Provided the semi-constrained space and the monotonous driving environment of freeway tunnels, safety concerns still remain. This study aims to investigate the uniqueness of the relationships between crash severity in freeway tunnels and various contributory factors. Method: The information of 10,081 crashes in the entire freeway network of Guizhou Province, China in 2018 is adopted, from which a subset of 591 crashes in tunnels is extracted. To address spatial variations across various road segments, a two-level binary logistic approach is applied to model crash severity in freeway tunnels. A similar model is also established for crash severity on general freeways as a benchmark. Results: The uniqueness of crash severity in tunnels mainly includes three aspects: (a) the road-segment-level effects are quantifiable with the environmental factors for crash severity in tunnels, but only exist in the random effects for general freeways; (b) tunnel has a significantly higher propensity to cause severe injury in a crash than other locations of a freeway; and (c) different influential factors and levels of contributions are found to crash severity in tunnels compared with on general freeways. Factors including speed limit, tunnel length, truck involvement, rear-end crash, rainy and foggy weather and sequential crash have positive contributions to crash severity in freeway tunnels. Practical applications: Policy implications for traffic control and management are advised to improve traffic safety level in freeway tunnels.     

Correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists in single-vehicle crashes

Objectives: In order to improve motorcycle safety, this article examines the correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists, under multiple precrash conditions. Method: Ten-year crash data for single-vehicle motorcycle crashes from the General Estimates Systems (GES) were analyzed, using partial proportional odds models (i.e., generalized ordered logit models). Results: The modeling results show that “braking (no lock-up)” is associated with a higher probability of increased severity, whereas “braking (lock-up)” is associated with a higher probability of decreased severity, under all precrash conditions. “Steering” is associated with a higher probability of reduced injury severity when other vehicles are encroaching, whereas it is correlated with high injury severity under other conditions. “Braking and steering” is significantly associated with a higher probability of low severity under “animal encounter and object presence,” whereas it is surprisingly correlated with high injury severity when motorcycles are traveling off the edge of the road. The results also show that a large number of motorcyclists did not perform any crash avoidance maneuvers or conducted crash avoidance maneuvers that are significantly associated with high injury severity. Conclusions: In general, this study suggests that precrash maneuvers are an important factor associated with motorcyclists' injury severity. To improve motorcycle safety, training/educational programs should be considered to improve safety awareness and adjust driving habits of motorcyclists. Antilock brakes and such systems are also promising, because they could effectively prevent brake lock-up and assist motorcyclists in maneuvering during critical conditions. This study also provides valuable information for the design of motorcycle training curriculum.     

Exploring factors contributing to crash injury severity on rural two-lane highways

ObjectiveCrash injury results from complex interaction among factors related to at-fault driver's behavior, vehicle characteristics, and road conditions. Identifying the significance of these factors which affect crash injury severity is critical for improving traffic safety. A method was developed to explore the relationship based on crash data collected on rural two-lane highways in China.MethodsThere were 673 crash records collected on rural two-lane highways in China. A partial proportional odds model was developed to examine factors influencing crash injury severity owing to its high ability to accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of each contributing factor.ResultsThe results show that nine explanatory variables, including at-fault driver's age, at-fault driver having a license or not, alcohol usage, speeding, pedestrian involved, type of area, weather condition, pavement type, and collision type, significantly affect injury severity. In addition to alcohol usage and pedestrian involved, others violate the proportional odds assumption. At-fault driver's age of 25–39 years, alcohol usage, speeding, pedestrian involved, pavement type of asphalt, and collision type of angle are found to be increased crash injury severity.Practical ApplicationsThe developed logit model has demonstrated itself efficient in identifying the effect of contributing factors on the crash injury severity.     

The effect of motorcyclists’ age on injury severities in single-motorcycle crashes with unobserved heterogeneity

Introduction: Due to the myriad of unique characteristics associated with motorcycle operation, motorcycle safety is a public health concern as complex as it is serious. National crash data suggest motorcyclists are 28 times more likely to be killed when compared to passenger car occupants. In the state of Florida, motorcycle crashes are 1.5 times more likely to result in the death of the rider, placing Florida among the top deadliest states for motorcyclists in the nation. Using police-reported data from 2016, this study addresses the complex and interconnected nature of the many characteristics associated with motorcycle operation by investigating the effect of age on motorcyclists’ riding behavior as it relates to injury severity for single-motorcycle crashes in the state of Florida. Method: To account for unobserved heterogeneity in the crash data, mixed logit models with heterogeneity in means and variances were estimated to model three injury severity outcomes (non-visible, severe, and fatal) for three age groups (under 30, 30–49, and 50 and above). Results: Model results indicate that age affects motorcyclists’ safety perception and ability to assess risks, thereby influencing their involvement in risky behaviors. Characteristics unique to motorcycle operation—spatial characteristics, speed, motorcycle type, time of day, helmet usage, alcohol consumption, ejection from motorcycle, passenger presence, endorsement status, and lighting—are further complicated by their dependency on the characteristics of the individual motorcyclist. Age of motorcyclist indicates a relationship between motorcyclists’ behavior and perceived safety. Conclusion: The model results indicated that statistically significant parameters constituted different models and they were not equal across the age groups of motorcyclists: aged under 30, aged 30–49, and aged 50 and above. Through advanced econometric modeling, this study fills a gap in the existing literature and assists the safety professionals, motorcycle trainers, policymakers, law enforcement agencies, and roadway designers in developing countermeasures.     

Exploring motorcyclist injury severity resulting from various crash configurations at T-junctions in the United Kingdom--an application of the ordered probit models

OBJECTIVES: The fact that motorcycle users tend to be more vulnerable to injuries than those using other motorized vehicles may act synergistically with the complexity of conflicting movements between vehicles and motorcycles to increase injury severity in a junction-type accident. A junction-type collision tends to be more severe than a non-junction case due to the fact that some of the injurious crashes such as angle-collision commonly occur. Existing studies have applied several statistical modeling techniques to examine influential factors on the occurrences of different crashes among motorized vehicles but surprisingly very little has empirically explored whether a particular crash type, resulting from a junction-type accident, is more injurious to motorcyclists. This article attempts to investigate whether a particular collision is more deadly to motorcyclists conditioned on crash occurrence at T-junctions in the U.K., while controlling for environment, vehicle, and demographic factors. METHODS: The statistical modeling technique employed is the ordered probit models using the data extracted from the STATS19 accident injury database (1999-2004). RESULTS: The modeling found determinants of injury severity among motorcyclists at T-junctions in the U.K. For example, an approach-turn/head-on collision is much more injurious to motorcyclists; and, those riding in early morning (i.e., 0000-0659) are more likely to be severely injured. CONCLUSIONS: This study offers a guideline for future research, as well as insight into potential prevention strategies that might help moderate motorcyclist injuries.     

Risky driving and the perception of motorcycle accident causes among chinese motorcyclists in Hong Kong

Objective: The primary purposes of this study were to explore the relationship between risk-taking acts while driving motorcycles and perceived causes of motorcycle accidents, as well as their contribution to active involvement in traffic accidents among Chinese motorcyclists in Hong Kong. Active involvement means the riders was likely at fault for the crash. Methods: A total of 774 motorcyclists were recruited, of whom 292 had been involved in active motorcycle accident in the previous 3?years. All were asked to fill in a questionnaire, which was developed to assess their risk-taking acts while driving a motorcycle and perception of motorcycle accident causes. Results: The results of the study revealed 3 dimensions of accident causes, namely, driving-related, environment-related, and belief-related causes. These motorcycle accident causes were correlated with risk-taking acts while driving a motorcycle. A multivariate logistic regression analysis showed that risk-taking acts while driving motorcycles (adjusted odds ratio [OR]: 1.036, 95% confidence interval [CI]: 1.020-1.052), perception of driving-related cause (adjusted OR: 0.941, 95% CI: 0.916-0.967), and belief-related cause (adjusted OR: 1.134, 95% CI: 1.088-1.182) were significant factors contributing to involvement in active traffic accidents by motorcycle riders after controlling for concurrent demographic variables. Conclusions: The study highlights that perceived causes of motorcycle accidents are multidimensional, including those areas related to driving, the environment, and beliefs. It substantiates previous studies that a higher degree of driving-related risk perception is related to a lower degree of risk-taking acts while driving. Further research is needed to understand why belief-related causes, sometimes called superstitions, lead riders to believe that it is beyond their ability to affect accident causation and prevention.     

Highway safety assessment and improvement through crash prediction by injury severity and vehicle damage using Multivariate Poisson-Lognormal model and Joint Negative Binomial-Generalized Ordered Probit Fractional Split model

Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to severe highway crashes, and assisting the practitioners in allocating safety improvement resources. Methods: This paper uses urban and suburban intersection data in Connecticut, along with two sophisticated modeling approaches, i.e. a Multivariate Poisson-Lognormal (MVPLN) model and a Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) model to assess the methodological rationality and accuracy by accommodating for the unobserved factors in predicting crash counts by severity level. Furthermore, crash prediction models based on vehicle damage level are estimated using the same two methodologies to supplement the injury severity in estimating crashes by severity when the sample mean of severe injury crashes (e.g., fatal crashes) is very low. Results: The model estimation results highlight the presence of correlations of crash counts among severity levels, as well as the crash counts in total and crash proportions by different severity levels. A comparison of results indicates that injury severity and vehicle damage are highly consistent. Conclusions: Crash severity counts are significantly correlated and should be accommodated in crash prediction models. Practical application: The findings of this research could help select sound and reliable methodologies for predicting highway accidents by injury severity. When crash data samples have challenges associated with the low observed sampling rates for severe injury crashes, this research also confirmed that vehicle damage can be appropriate as an alternative to injury severity in crash prediction by severity.     

Etiology of fatal thoracic aortic injuries: Secondary data analysis

Objectives: Motor vehicle crashes remain a leading cause of death in the United States (US). Thoracic aortic dissection due to blunt trauma remains a major injury mechanism, and up to 90% of these injuries result in death on the scene. The objective of this study is to understand the modern risk factors and etiology of fatal thoracic aortic injuries in the current US fleet.

Methods: Using a unique, linked, Fatality Analysis Reporting System (FARS) and Multiple Cause of Death (MCOD) database from 2000–2010, 144,169 drivers over 16 years of age who suffered fatal injuries were identified. The merged database provides an unparalleled fidelity for identifying thoracic aortic injuries due to motor vehicle accidents. Thoracic aortic injuries were defined by ICD-10 codes S250. Univariate and multivariate logistic regression models for presence of any thoracic aortic injuries were fitted. Age, gender, BMI weight categories, vehicle class, model year, crash type/direction, severity of crash damage, airbag deployment location, and seatbelt use, fatal injury codes, and location of injury were considered. Odds ratios (OR) and corresponding 95% confidence intervals (95%CI) are calculated.

Results: There were 2953 deaths (2.10%) related to thoracic aortic injuries that met the inclusion criteria. Nearside crashes were associated with an increased odds (OR = 1.42, 1.1-1.83), while rollover crashes (OR =.44,.29-.66) were associated with a reduced odds of fatal thoracic aortic injury. Using backward selection on the full multivariate model, the only significant model effects that remained were vehicle type, crash type, body region, and injury type.

Conclusions: The increased prevalence of fatal thoracic aortic injury in nearside crashes, increasing age, and vehicle type provide some insight into the current US fleet. Important factors, including model year, had significantly lower levels of the injury in univariate analysis, demonstrating the effect of safety improvements in newer model vehicles. Further study of this fatal injury is warranted, including comparisons of those who survive the injury.     

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers. Methods: A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China. Results: The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty. Conclusions: Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.     

Issues with using police citations to assign responsibility in quasi-induced exposure

Crash fault determination is one of the most critical issues in applications of quasi-induced exposure. Traditionally, the driver citation issued by the investigating police officer is the primary source to assign responsibility for motor vehicle crashes. Such citations are based on the “evidence” or observation of a moving violation (such as engaged hazardous actions) in combination with non-moving violations (such as suspended driver license) prior to the crash. The objective here is to identify the contributing factors that may lead to driver citations in two-vehicle crashes in addition to the hazardous action. Multivariate binary logistic regression modeling is employed to explore the behavior of the investigating police officer in terms of issuing citation at the crash scene. A series of explanatory parameters including roadway characteristics, environmental factors, and driver and vehicle attributes is assessed. The results show that whether the crash type was a hit-and-run, alcohol and illegal drug use, driver gender, driver age, and injury severity all appear to have significant impacts on the investigating officer’s decision-making. Specific examples are given to demonstrate how two factors hit-and-run and drinking status can skew the exposure estimates in the context of quasi-induced exposure. The findings will help to serve as a basis to select appropriate parameters in assigning crash responsibility in quasi-induced exposure applications; and we make recommendations to modify existing crash database for better safety research in the future.