Drug and alcohol use among drivers admitted to a Level-1 trauma center

The purpose of this research was to determine the incidence and prevalence of drug use, alcohol use, and the combination of drug and alcohol use among motor vehicle crash (MVC) victims admitted to a Level-1 trauma center. In a 90-day study, nearly two-thirds of trauma center admissions were victims of motor vehicle crashes. Blood and urine was collected from 168 MVC victims of whom 108 were identified as the driver in the crash. Toxicology results indicated that 65.7% of drivers tested positive for either commonly abused drugs or alcohol. More than half of the drivers tested positive for drugs (50.9%) other than alcohol, with one in four drivers testing positive for marijuana use. About one-third of those using drugs had also been drinking, but alcohol was detected in only 30.6% of all injured drivers. Within the total MVC patient pool, passenger drug/alcohol use was equivalent to the driver population; however, injured pedestrians had higher rates of alcohol only than other MVC victims. There were no significant differences in drug and alcohol use between MVCs and trauma admissions of other causes. Of the patients with positive toxicology results, less than half (42%) were referred for evaluation for substance abuse disorders.     

The influence of demographic factors on seatbelt use by adults injured in motor vehicle crashes

This study determined demographic factors associated with reported seatbelt use among injured adults admitted to a trauma center. A retrospective chart review was conducted including all patients admitted to a trauma center for injuries from motor vehicle crashes (MVC). E-codes (i.e. ICD-9 external cause of injury codes) were used to identify all patients injured in a MVC between January 1995 and December 1997. Age, sex, race, residence zip code (i.e. a proxy for income based on geographic location of residence), position in the vehicle, and seatbelt use were obtained from the trauma registry. Forward logistic regression was used to identify significant predictors of seatbelt use. Complete data was available for 1366 (82%) patients. Seatbelt use was reported for 45% of patients under age of 25 years, 52% of those 25-60 years, and 68% of those over 60 years. Overall, seatbelt use was reported for 45% of men and 63% of women, as well as for 56% of Caucasians (i.e. Whites) and 34% of African Americans. In addition, seatbelt use was reported for 33% of those earning less than $20,000 per year and 55% of those earning over $20,000. Finally, seatbelt use was reported for 57% of drivers and 43% of passengers. Logistic regression revealed that age, female gender, Caucasian race, natural log of income, and driver were all significant predictors of reported seatbelt use. These results show that seatbelt use was more likely to be reported for older persons, women, Caucasians, individuals with greater incomes, and drivers. Seatbelt use should be encouraged for everyone; however, young people, men, African Americans, individuals with lower incomes, and passengers should be targeted specifically.     

Trends of behavioral risk factors in motor vehicle crashes in Utah, 1992-1997

OBJECTIVE: Measure changes in the prevalence of behavioral factors including police-reported fatigue and alcohol intoxication, as well as self-reported seatbelt use, and assess their effect on hospitalization or death after a motor vehicle crash. METHODS: Probabilistic linkage was used to match drivers in motor vehicle crashes with hospital discharge records for the years 1992-1997. Frequencies of specific behavioral factors were evaluated using the Cochran-Armitage test for trend. Odds ratios and corresponding 95% confidence intervals were calculated using generalized estimating equations (GEEs) with crash and driver characteristics as independent variables and hospitalization or death as the dependent variable. RESULTS: The analysis database consisted of 450,286 crash driver records, which linked to 4219 (0.9%) hospitalizations or deaths. There was an increasing trend for self-reported seatbelt use among crash-involved drivers from 80.5% in 1992 to 89.3% in 1997 (P<0.001). Police-reported alcohol intoxication among crash-involved drivers showed a decreasing trend from 2.4% in 1992 to 1.5% in 1997 (P<0.001). There was no trend for police-reported fatigue-related crashes. Odds ratios of hospitalization or death for seatbelt use, alcohol involvement, and fatigue were significant and did not fluctuate considerably between 1992 and 1997. Seatbelt use offered a protective effect from hospitalization or death, while alcohol intoxication and fatigue contributed to increased likelihood of hospitalization or death. CONCLUSIONS: These results suggest that while some improvement has been made in decreasing seatbelt non-use and driver alcohol intoxication among crash-involved drivers, no improvement has been made in reducing fatigue-related crashes.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Risk factors for fatal crashes in rural Australia

This paper presents findings from the rural and remote road safety study, conducted in Queensland, Australia, from March 2004 till June 2007, and compares fatal crashes and non-fatal but serious crashes in respect of their environmental, vehicle and operator factors. During the study period there were 613 non-fatal crashes resulting in 684 hospitalised casualties and 119 fatal crashes resulting in 130 fatalities. Additional information from police sources was available on 103 fatal and 309 non-fatal serious crashes. Over three quarters of both fatal and hospitalised casualties were male and the median age in both groups was 34 years. Fatal crashes were more likely to involve speed, alcohol and violations of road rules and fatal crash victims were 2½ times more likely to be unrestrained inside the vehicle than non-fatal casualties, consistent with current international evidence. After controlling for human factors, vehicle and road conditions made a minimal contribution to the seriousness of the crash outcome. Targeted interventions to prevent fatalities on rural and remote roads should focus on reducing speed and drink driving and promoting seatbelt wearing.     

Predicting severe head injury after light motor vehicle crashes: implications for automatic crash notification systems

Motor vehicle crashes (MVC) are a leading public health problem. Improving notification times and the ability to predict which crashes will involve severe injuries may improve trauma system utilization. This study was undertaken to develop and validate a model to predict severe head injury following MVC using information readily incorporated into an automatic crash notification system. A cross-sectional study with derivation and validation sets was performed. The cohort was drawn from drivers of vehicles involved in MVC obtained from the National Automotive Sampling System (NASS). Independent multivariable predictors of severe head injury were identified. The model was able to stratify drivers according to their risk of severe head injury indicating its validity. The areas under the receiver-operating characteristic (ROC) curves were 0.7928 in the derivation set and 0.7940 in the validation set. We have developed a prediction model for head injury in MVC. As the development of automatic crash notification systems improves, models such as this one will be necessary to permit triage of what would be an overwhelming increase in crash notifications to pre-hospital responders.     

Investigating driver injury severity patterns in rollover crashes using support vector machine models

Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.     

Acute healthcare utilization by children after motor vehicle crashes

This study, describing the overall patterns of acute healthcare resource utilization by child crash victims (age 15 years and younger), was conducted between 28 July 1999 and 30 November 2000 as part of an on-going large-scale, child-specific crash surveillance system, Partners for Child Passenger Safety: insurance claims from 15 states and the District of Columbia function as the source of subjects, with telephone survey and on-site crash investigations serving as the primary sources of data. A probability sample of 4862 eligible crashes with 7368 child occupants formed the study sample. Our results suggest that for every 1000 children involved in crashes, 3 are hospitalized; 108 are treated and released from an emergency department (ED); 48 are evaluated in a physician's office, urgent care center, or other facility; and 841 receive no care at all. Comprehensive surveillance systems for motor vehicle crashes must capture children treated in physicians' offices, emergency departments, and other healthcare facilities in order to provide accurate estimates of the impact on the health care system related to motor vehicle trauma.     

Costs of alcohol-related crashes: New Zealand estimates and suggested measures for use internationally

This paper presents policy-oriented measures of alcohol-related crash incidence and costs in New Zealand (N.Z.). Costs of crashes, where alcohol probably was a contributing factor were computed from official crash costs and police-reported crash/injury counts adjusted for under-reporting of crashes and of alcohol involvement. Alcohol-related crashes cost an estimated $1.2 billion in N.Z. in 1996. They equate to an estimated $0.75 per drink consumed, $17.80 per km driven above the legal limit of 0.08, and $1100 per heavy drinker. People other than the drinkers, who caused the crashes, paid half the costs. An estimated one in 90 drunk-driving trips resulted in a crash (and often a drunk driving conviction) while one in 375 crash-free drunk driving trips also resulted in a drunk-driving conviction. Ten measures of alcohol-related crash incidence and costs are recommended for international use. They include number of alcohol-related deaths and injuries; innocent victims and children harmed in crashes caused by drinkers; annual costs and costs paid by people other than the drinker who caused the crash; crash costs per drink consumed, per heavy drinker, per kilometer driven drunk versus sober; probabilities of crash and of drunk-driving conviction.     

Investigation of pulmonary contusion extent and its correlation to crash,occupant, and injury characteristics in motor vehicle crashes

Background

Pulmonary contusion (PC) is a leading injury in blunt chest trauma and is most commonly caused by motor vehicle crashes (MVC). To improve understanding of the relationship between insult and outcome, this study relates PC severity to crash, occupant, and injury parameters in MVCs.

Methods

Twenty-nine subjects with PC were selected from the Crash Injury Research and Engineering Network (CIREN) database, which contains detailed crash and medical information on MVC occupants. Computed tomography scans of these subjects were segmented using a semi-automated protocol to quantify the volumetric percentage of injured tissue in each lung. Techniques were used to quantify the geometry and location of PC, as well as the location of rib fractures. Injury extent including percent PC volume and the number of rib fractures was analyzed and its relation to crash and occupant characteristics was explored.

Results

Frontal and near-side crashes composed 72% of the dataset and the near-side door was the component most often associated with PC causation. The number of rib fractures increased with age and fracture patterns varied with crash type. In near-side crashes, occupant weight and BMI were positively correlated with percent PC volume and the number of rib fractures, and the impact severity was positively correlated with percent PC volume in the lung nearest the impact.

Conclusions

This study quantified PC morphology in 29 MVC occupants and examined the relationship between injury severity and crash and occupant parameters to better characterize the mechanism of injury. The results of this study may contribute to the prevention, mitigation, and treatment of PC.     

Consideration of driver home county prohibition and alcohol-related vehicle crashes

This study examines the characteristics of alcohol-related crashes in wet versus dry counties in the state of Kentucky, USA and incorporates the location of driver residences through use of geographic information system (GIS) analysis. Between 1991 and 1997, 39344 alcohol-related crashes by Kentucky residents on Kentucky State roads were reported. The location of the crash and the home ZIP code from the driver's address were used to consider distance from home in the GIS. Analysis of the crash data revealed that a similar proportion of crashes in wet and dry counties are alcohol-related but that a higher proportion of dry counties residents are involved in an alcohol-related crash. However, when the distance from home variable is considered, several results suggest that dry county residents may be driving further when consuming alcohol. In part due to the rural nature of dry counties, drivers from dry counties have both alcohol-related and non-alcohol related crashes farther from their homes than residents from wet counties. Alcohol-related crashes by dry county residents in wet counties are the greatest average distance from home while crashes by wet county residents in wet counties are the smallest average distance. Drivers from dry counties over 21 years of age have alcohol-related crashes significantly farther from home than those under 21 who would not legally be admitted to drinking establishments in the wet counties. Furthermore, residents from dry counties that do not border wet counties have alcohol-related crashes on average farther from home than the border county residents. These last three results provide circumstantial evidence that some dry county drivers may be driving to wet counties to consume alcohol thus increasing impaired driving exposure. In conclusion, by considering crash location and driver residence, these findings indicate that county-level prohibition is not necessarily effective in improving highway safety.     

The odds of wrong-way crashes and resulting fatalities: A comprehensive analysis

The United States of America and other nations are grappling with the incidence of wrong-way driving (WWD). The issue is as important today (NTSB, 2012) as it was a half-century ago (Hulbert and Beers, 1966). In the absence of a comprehensive analysis, any effort to implement WWD countermeasures can be counterproductive. Hence, this effort began with the express intent to identify the factors that cause WWD crashes and fatalities. This work is sizeable in that it evaluated one million complete crash records from Florida. The methodology comprised (a) administering a survey on the perceptions about WWD; (b) developing binomial logistic models for computing the odds of WWD crashes, and of fatal crashes within the WWD space; (c) analyzing the contributing variables; and (d) comparing perceptions with crash analysis results. The study parameters included driver's age, gender, licensing state, physical defect, blood alcohol concentration, vehicle use, seatbelt compliance, day and time of crash, roadway lighting, facility type, weather conditions, road geometrics, and traffic volumes. Individual variable analysis of 23 parameters and the model development process included the determination of odds ratios and statistical tests for the predictive power and goodness-of-fit. The results of this work are generally consistent with expectation, yet surprising at times. This work concludes with decision-making inputs to the scientist, policy-maker and practitioner on the need for effectively engineering the roads, actively educating people about wrong-way driving, and strictly enforcing traffic laws, rules and regulations.     

Hierarchical Bayesian random intercept model-based cross-level interaction decomposition for truck driver injury severity investigations

Traffic crashes occurring on rural roadways induce more severe injuries and fatalities than those in urban areas, especially when there are trucks involved. Truck drivers are found to suffer higher potential of crash injuries compared with other occupational labors. Besides, unobserved heterogeneity in crash data analysis is a critical issue that needs to be carefully addressed. In this study, a hierarchical Bayesian random intercept model decomposing cross-level interaction effects as unobserved heterogeneity is developed to examine the posterior probabilities of truck driver injuries in rural truck-involved crashes. The interaction effects contributing to truck driver injury outcomes are investigated based on two-year rural truck-involved crashes in New Mexico from 2010 to 2011. The analysis results indicate that the cross-level interaction effects play an important role in predicting truck driver injury severities, and the proposed model produces comparable performance with the traditional random intercept model and the mixed logit model even after penalization by high model complexity. It is revealed that factors including road grade, number of vehicles involved in a crash, maximum vehicle damage in a crash, vehicle actions, driver age, seatbelt use, and driver under alcohol or drug influence, as well as a portion of their cross-level interaction effects with other variables are significantly associated with truck driver incapacitating injuries and fatalities. These findings are helpful to understand the respective or joint impacts of these attributes on truck driver injury patterns in rural truck-involved crashes.     

Evaluation of effectiveness of safety seatbelt legislation in the United Arab Emirates

Seatbelt legalisation was implemented in the United Arab Emirates (UAE) in January 1999. This provided the opportunity to evaluate the effectiveness of the legislation in the Eastern District of Abu Dhabi Emirate in the UAE by establishing levels of injury severity from motor vehicle crashes (MVC) before and after the legislation and the rate of compliance with the legislation. Data were obtained from a major hospital in the Eastern District of Abu Dhabi Emirate, UAE. Subjects were a systematic sample of MVC victims who arrived alive at hospital in either the pre-implementation period (January-June 1998) or the post-implementation period (February-August 2000). The main measures of outcome were injury severity codes, numbers of hospital bed days and rates of admission and discharge at hospital. The analysis of injury severity from MVCs, from the pre- to the post-implementation period, revealed a significant declining trend (chi-square = 77.68, P < 0.001). While the proportion of minor injuries increased from 42% (95% CI: 36-48%) in the pre-implementation period to 77% (95% CI: 71-83%) in the post-implementation period, the proportion of "moderate to fatal injuries" declined from 54% (95% CI: 48-60%) to 17% (P = 0.001) and the median number of hospital bed days declined from 5 days (25% = 2; 75% = 8 ) to 3 days (25% = 1; 75% = 4 ). The rate of seatbelt compliance reported by occupants involved in MVCs in the post-implementation period was 59% (95% CI: 52-67%). The implementation of the seatbelt legislation in the Eastern District of Abu Dhabi Emirate was associated with statistically significant reduction in morbidity in those arriving alive at hospital following MVC, including reduced severity of injury, admission rate to hospital and the duration of hospital stay. More active implementation of seatbelt law would most likely further reduce severity of MVC injuries and fatalities in the Eastern District of Abu Dhabi Emirate, UAE.     

The effects of age,gender, and crash types on drivers’ injury-related health care costs

There are many studies that evaluate the effects of age, gender, and crash types on crash related injury severity. However, few studies investigate the effects of those crash factors on the crash related health care costs for drivers that are transported to hospital. The purpose of this study is to examine the relationships between drivers’ age, gender, and the crash types, as well as other crash characteristics (e.g., not wearing a seatbelt, weather condition, and fatigued driving), on the crash related health care costs. The South Carolina Crash Outcome Data Evaluation System (SC CODES) from 2005 to 2007 was used to construct six separate hierarchical linear regression models based on drivers’ age and gender. The results suggest that older drivers have higher health care costs than younger drivers and male drivers tend to have higher health care costs than female drivers in the same age group. Overall, single vehicle crashes had the highest health care costs for all drivers. For males older than 64-years old sideswipe crashes are as costly as single vehicle crashes. In general, not wearing a seatbelt, airbag deployment, and speeding were found to be associated with higher health care costs. Distraction-related crashes are more likely to be associated with lower health care costs in most cases. Furthermore this study highlights the value of considering drivers in subgroups, as some factors have different effects on health care costs in different driver groups. Developing an understanding of longer term outcomes of crashes and their characteristics can lead to improvements in vehicle technology, educational materials, and interventions to reduce crash-related health care costs.     

Nilsson's Power Model connecting speed and road trauma: Applicability by road type and alternative models for urban roads

Nilsson (1981) proposed power relationships connecting changes in traffic speeds with changes in road crashes at various levels of injury severity. Increases in fatal crashes are related to the 4^th power of the increase in mean speed, increases in serious casualty crashes (those involving death or serious injury) according to the 3^rd power, and increases in casualty crashes (those involving death or any injury) according to the 2^nd power. Increases in numbers of crash victims at cumulative levels of injury severity are related to the crash increases plus higher powers predicting the number of victims per crash. These relationships are frequently applied in OECD countries to estimate road trauma reductions resulting from expected speed reductions. The relationships were empirically derived based on speed changes resulting from a large number of rural speed limit changes in Sweden during 1967-1972. Nilsson (2004) noted that there had been very few urban speed limit changes studied to test his power model. This paper aims to test the assumption that the model is equally applicable in all road environments. It was found that the road environment is an important moderator of Nilsson's power model. While Nilsson's model appears satisfactory for rural highways and freeways, the model does not appear to be directly applicable to traffic speed changes on urban arterial roads. The evidence of monotonically increasing powers applicable to changes in road trauma at increasing injury severity levels with changes in mean speed is weak. The estimated power applicable to serious casualties on urban arterial roads was significantly less than that on rural highways, which was also significantly less than that on freeways. Alternative models linking the parameters of speed distributions with road trauma are reviewed and some conclusions reached for their use on urban roads instead of Nilsson's model. Further research is needed on the relationships between serious road trauma and urban speeds.     

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention.     

Pedestrian- and driver-related factors associated with the risk of causing collisions involving pedestrians in Spain

This study aimed to quantify the association between pedestrian- and driver-related factors and the risk of causing road crashes involving pedestrians in urban areas in Spain between 1993 and 2011. From the nationwide police-based registry of road crashes with victims in Spain, we analyzed all 63,205 pairs of pedestrians and drivers involved in crashes in urban areas in which only the pedestrian or only the driver was at fault. Logistic regression models were used to obtain adjusted odds ratios to assess the strength of association between each individual-related variable and the pedestrian’s odds of being at fault for the crash (and conversely, the driver’s odds of not being at fault).The subgroups of road users at high risk of causing a road crash with a pedestrian in urban areas were young and male pedestrians, pedestrians with psychophysical conditions or health problems, the youngest and the oldest drivers, and drivers with markers of high-risk behaviors (alcohol use, nonuse of safety devices, and driving without a valid license). These subgroups should be targeted by preventive strategies intended to decrease the rate of urban road crashes involving pedestrians in Spain.     

Severity of motorcycle crashes in Calgary

Motorcycle riders would be more vulnerable in the event of a crash because of their lack of protection which would often result in them suffering more severe injuries than car drivers. This paper estimated three crash severity models to identify factors that contributed to increasing the severity of motorcycle involved crashes in the Canadian City of Calgary. We found that results from the ordered logit model, heterogeneous choice model and partially constrained generalized ordered logit model produced estimates that were very similar which attested to their robustness. Injury severity tended to increase in neighborhoods with loops and lollipops types of streets or involved right-angle and left-turn-across-path crashes, a truck, unsafe speed or alcohol use but tended to decrease if the crash occurred in parking lots or during winter, involved a van or male rider, or a rider following-too-closely to the vehicle in front.     

Identification of vehicle components associated with severe thoracic injury in motor vehicle crashes: a CIREN and NASS analysis

INTRODUCTION: Thoracic trauma secondary to motor vehicle crashes (MVC) continues to be a major cause of morbidity and mortality. Specific vehicle features may increase the risk of severe thoracic injury when striking the occupant. We sought to determine which vehicle contact points were associated with an increased risk of severe thoracic injury in MVC to focus subsequent design modifications necessary to reduce thoracic injury. METHODS: The National Automotive Sampling System (NASS) databases from 1993 to 2001 and the Crash Injury Research and Engineering Network (CIREN) databases from 1996 to 2004 were analyzed separately using univariate and multivariate logistic regression stratified by restraint use and crash direction. The risk of driver thoracic injury, defined as an abbreviated injury scale (AIS) of score > or =3, was determined as it related to specific points of contact between the vehicle and the driver. RESULTS: The incidence of severe chest injury in NASS and CIREN were 5.5% and 33%, respectively. The steering wheel, door panel, armrest, and seat were identified as contact points associated with an increased risk of severe chest injury. The door panel and arm rest were consistently a frequent cause of severe injury in both the NASS and CIREN data. CONCLUSIONS: Several vehicle contact points, including the steering wheel, door panel, armrest and seat are associated with an increased risk of severe thoracic injury when striking the occupant. These elements need to be further investigated to determine which characteristics need to be manipulated in order to reduce thoracic trauma during a crash.