Driver injury in near- and far-side impacts: Update on the effect of front passenger belt use

Purpose: This is a study that updates earlier research on the influence of a front passenger on the risk for severe driver injury in near-side and far-side impacts. It includes the effects of belt use by the driver and passenger, identifies body regions involved in driver injury, and identifies the sources for severe driver head injury.

Methods: 1997–2015 NASS-CDS data were used to investigate the risk for Maximum Abbreviated Injury Scale (MAIS) 4 + F driver injury in near-side and far-side impacts by front passenger belt use and as a sole occupant in the driver seat. Side impacts were identified with GAD1 = L or R without rollover (rollover ≤ 0). Front-outboard occupants were included without ejection (ejection = 0). Injury severity was defined by MAIS and fatality (F) by TREATMNT = 1 or INJSEV = 4. Weighted data were determined. The risk for MAIS 4 + F was determined using the number of occupants with known injury status MAIS 0 + F. Standard errors were determined.

Results: Overall, belted drivers had greater risks for severe injury in near-side than far-side impacts. As a sole driver, the risk was 0.969 ± 0.212% for near-side and 0.313 ± 0.069% for far-side impacts (P < .005). The driver's risk was 0.933 ± 0.430% with an unbelted passenger and 0.596 ± 0.144% with a belted passenger in near-side impacts. The risk was 2.17 times greater with an unbelted passenger (NS). The driver's risk was 0.782 ± 0.431% with an unbelted passenger and 0.361% ± 0.114% with a belted passenger in far-side impacts. The risk was 1.57 times greater with an unbelted passenger (P < .10). Seat belt use was 66 to 95% effective in preventing MAIS 4 + F injury in the driver. For belted drivers, the head and thorax were the leading body regions for Abbreviated Injury Scale (AIS) 4+ injury. For near-side impacts, the leading sources for AIS 4+ head injury were the left B-pillar, roof, and other vehicle. For far-side impacts, the leading sources were the other occupant, right interior, and roof (8.5%).

Conclusions: Seat belt use by a passenger lowered the risk of severe driver injury in side impacts. The reduction was 54% in near-side impacts and 36% in far-side impacts. Belted drivers experienced mostly head and thoracic AIS 4+ injuries. Head injuries in the belted drivers were from contact with the side interior and the other occupant, even with a belted passenger.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

Driver and front passenger injury in frontal crashes: Update on the effect of unbelted rear occupants

Purpose: This is a study of the influence of an unbelted rear occupant on the risk of severe injury to the front seat occupant ahead of them in frontal crashes. It provides an update to earlier studies.

Methods: 1997–2015 NASS-CDS data were used to investigate the risk for severe injury (Maximum Abbreviated Injury Score [MAIS] 4+F) to belted drivers and front passengers in frontal crashes by the presence of a belted or unbelted passenger seated directly behind them or without a rear passenger. Frontal crashes were identified with GAD1 = F without rollover (rollover ≤ 0). Front and rear outboard occupants were included without ejection (ejection = 0). Injury severity was defined by MAIS and fatality (F) by TREATMNT = 1 or INJSEV = 4. Weighted data were determined. The risk for MAIS 4+F was determined using the number of occupants with known injury status MAIS 0+F. Standard errors were determined.

Results: The risk for severe injury was 0.803 ± 0.263% for the driver with an unbelted left rear occupant and 0.100 ± 0.039% with a belted left rear occupant. The driver's risk was thus 8.01 times greater with an unbelted rear occupant than with a belted occupant (P <.001). With an unbelted right rear occupant behind the front passenger, the risk for severe injury was 0.277 ± 0.091% for the front passenger. The corresponding risk was 0.165 ± 0.075% when the right rear occupant was belted. The front passenger's risk was 1.68 times greater with an unbelted rear occupant behind them than a belted occupant (P <.001). The driver's risk for MAIS 4+F was highest when their seat was deformed forward. The risk was 9.94 times greater with an unbelted rear occupant than with a belted rear occupant when the driver's seat deformed forward. It was 13.4 ± 12.2% with an unbelted occupant behind them and 1.35 ± 0.95% with a belted occupant behind them.

Conclusions: Consistent with prior literature, seat belt use by a rear occupant significantly lowered the risk for severe injury to belted occupants seated in front of them. The reduction was greater for drivers than for front passengers. It was 87.5% for the driver and 40.6% for the front passenger. These results emphasize the need for belt reminders in all seating positions.     

Factors contributing to serious and fatal injuries in belted rear seat occupants in frontal crashes

Abstract

Objectives: Earlier research has shown that the rear row is safer for occupants in crashes than the front row, but there is evidence that improvements in front seat occupant protection in more recent vehicle model years have reduced the safety advantage of the rear seat versus the front seat. The study objective was to identify factors that contribute to serious and fatal injuries in belted rear seat occupants in frontal crashes in newer model year vehicles.

Methods: A case series review of belted rear seat occupants who were seriously injured or killed in frontal crashes was conducted. Occupants in frontal crashes were eligible for inclusion if they were 6 years old or older and belted in the rear of a 2000 or newer model year passenger vehicle within 10 model years of the crash year. Crashes were identified using the 2004–2015 National Automotive Sampling System Crashworthiness Data System (NASS-CDS) and included all eligible occupants with at least one Abbreviated Injury Scale (AIS) 3 or greater injury. Using these same inclusion criteria but split into younger (6 to 12 years) and older (55+ years) cohorts, fatal crashes were identified in the 2014–2015 Fatality Analysis Reporting System (FARS) and then local police jurisdictions were contacted for complete crash records.

Results: Detailed case series review was completed for 117 rear seat occupants: 36 with Maximum Abbreviated Injury Scale (MAIS) 3+ injuries in NASS-CDS and 81 fatalities identified in FARS. More than half of the injured and killed rear occupants were more severely injured than front seat occupants in the same crash. Serious chest injury, primarily caused by seat belt loading, was present in 22 of the injured occupants and 17 of the 37 fatalities with documented injuries. Nine injured occupants and 18 fatalities sustained serious head injury, primarily from contact with the vehicle interior or severe intrusion. For fatal cases, 12 crashes were considered unsurvivable due to a complete loss of occupant space. For cases considered survivable, intrusion was not a large contributor to fatality.

Discussion: Rear seat occupants sustained serious and fatal injuries due to belt loading in crashes in which front seat occupants survived, suggesting a discrepancy in restraint performance between the front and rear rows. Restraint strategies that reduce loading to the chest should be considered, but there may be potential tradeoffs with increased head excursion, particularly in the absence of rear seat airbags. Any new restraint designs should consider the unique needs of the rear seat environment.     

Census Study of Real-Life Near-Side Crashes with Modern Side Airbag-Equipped Vehicles in the United States

Objective: This study aimed to investigate the crash characteristics, injury distribution, and injury mechanisms for Maximum Abbreviated Injury Score (MAIS) 2+ injured belted, near-side occupants in airbag-equipped modern vehicles. Furthermore, differences in injury distribution for senior occupants compared to non-senior occupants was investigated, as well as whether the near-side occupant injury risk to the head and thorax increases or decreases with a neighboring occupant.

Method: National Automotive Sampling System's Crashworthiness Data System (NASS-CDS) data from 2000 to 2012 were searched for all side impacts (GAD L&R, all principal direction of force) for belted occupants in modern vehicles (model year > 1999). Rollovers were excluded, and only front seat occupants over the age of 10 were included. Twelve thousand three hundred fifty-four MAIS 2+ injured occupants seated adjacent to the intruding structure (near-side) and protected by at least one deployed side airbag were studied. To evaluate the injury risk influenced by the neighboring occupant, odds ratio with an induced exposure approach was used.

Result: The most typical crash occurred either at an intersection or in a left turn where the striking vehicle impacted the target vehicle at a 60 to 70° angle, resulting in a moderate change of velocity (delta-V) and intrusion at the B-pillar. The head, thorax, and pelvis were the most frequent body regions with rib fracture the most frequent specific injury. A majority of the head injuries included brain injuries without skull fracture, and non-senior rather than senior occupants had a higher frequency of head injuries on the whole. In approximately 50% of the cases there was a neighboring occupant influencing injury outcome.

Conclusion: Compared to non-senior occupants, the senior occupants sustained a considerably higher rate of thoracic and pelvis injuries, which should be addressed by improved thorax side airbag protection. The influence on near-side occupant injury risk by the neighboring occupant should also be further evaluated. Furthermore, side airbag performance and injury assessments in intersection crashes, especially those involving senior occupants in lower severities, should be further investigated and side impact dummy biofidelity and injury criteria must be determined for these crash scenarios.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

Injury risk functions for frontal oblique collisions

Objective: The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set.

Method: Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes―a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured).

Results: IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18–64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes.

Conclusions: The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.     

The effect of correct cross-chest clip use on injury outcomes in young children during motor vehicle crashes

Objective: Traffic crashes have high mortality and morbidity for young children. Though many specialized child restraint systems improve injury outcomes, no large-scale studies have investigated the cross-chest clip's role during a crash, despite concerns in some jurisdictions about the potential for neck contact injuries from the clips. This study aimed to investigate the relationship between cross-chest clip use and injury outcomes in children between 0 and 4 years of age.

Methods: Child passengers between 0 and 4 years of age were selected from the NASS-CDS data sets (2003–2014). Multiple regression analysis was used to model injury outcomes while controlling for age, crash severity, crash direction, and restraint type. The primary outcomes were overall Abbreviated Injury Score (AIS) 2+ injury, and the presence of any neck injury.

Results: Across all children aged 0–4 years, correct chest clip use was associated with decreased Abbreviated Injury Scale (AIS) 2+ injury (odds ratio [OR] = 0.44, 95% confidence interval [CI], 0.21–0.91) and was not associated with neck injury. However, outcomes varied by age. In children <12 months old, chest clip use was associated with decreased AIS 2+ injury (OR = 0.09, 95% CI, 0.02–0.44). Neck injury (n = 7, all AIS 1) for this age group only occurred with correct cross-chest clip use. For 1- to 4-year-old children, cross-chest clip use had no association with AIS 2+ injury, and correct use significantly decreased the odds of neck injury (OR = 0.49; 95% CI, 0.27–0.87) compared to an incorrectly used or absent cross-chest clip. No serious injuries were directly caused by the chest clips.

Conclusions: Correct cross-chest clip use appeared to reduce injury in crashes, and there was no evidence of serious clip-induced injury in children in 5-point harness restraints.     

Small female rib cage fracture in frontal sled tests

Objectives: The 2 objectives of this study are to (1) examine the rib and sternal fractures sustained by small stature elderly females in simulated frontal crashes and (2) determine how the findings are characterized by prior knowledge and field data.

Methods: A test series was conducted to evaluate the response of 5 elderly (average age 76 years) female postmortem human subjects (PMHS), similar in mass and size to a 5th percentile female, in 30 km/h frontal sled tests. The subjects were restrained on a rigid planar seat by bilateral rigid knee bolsters, pelvic blocks, and a custom force-limited 3-point shoulder and lap belt. Posttest subject injury assessment included identifying rib cage fractures by means of a radiologist read of a posttest computed tomography (CT) and an autopsy. The data from a motion capture camera system were processed to provide chest deflection, defined as the movement of the sternum relative to the spine at the level of T8.

?A complementary field data investigation involved querying the NASS-CDS database over the years 1997–2012. The targeted cases involved belted front seat small female passenger vehicle occupants over 40 years old who were injured in 25 to 35 km/h delta-V frontal crashes (11 to 1 o'clock).

Results: Peak upper shoulder belt tension averaged 1,970 N (SD = 140 N) in the sled tests. For all subjects, the peak x-axis deflection was recorded at the sternum with an average of ?44.5 mm or 25% of chest depth. The thoracic injury severity based on the number and distribution of rib fractures yielded 4 subjects coded as Abbreviated Injury Scale (AIS) 3 (serious) and one as AIS 5 (critical). The NASS-CDS field data investigation of small females identified 205 occupants who met the search criteria. Rib fractures were reported for 2.7% of the female occupants.

Conclusions: The small elderly test subjects sustained a higher number of rib cage fractures than expected in what was intended to be a minimally injurious frontal crash test condition. Neither field studies nor prior laboratory frontal sled tests conducted with 50th percentile male PMHS predicted the injury severity observed. Although this was a limited study, the results justify further exploration of the risk of rib cage injury for small elderly female occupants.     

Evaluation of developmental metrics for utilization in a pediatric advanced automatic crash notification algorithm

Objective: Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric.

Methods: A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000–2011 was performed. R² values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side).

Results: NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0–4 years, 5–9 years, 10–14 years, and 15–18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries.

Conclusions: The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.     

Real-World Rib Fracture Patterns in Frontal Crashes in Different Restraint Conditions

Objective: The purpose of this study was to use the detailed medical injury information in the Crash Injury Research and Engineering Network (CIREN) to evaluate patterns of rib fractures in real-world crash occupants in both belted and unbelted restraint conditions. Fracture patterns binned into rib regional levels were examined to determine normative trends associated with belt use and other possible contributing factors.

Methods: Front row adult occupants with Abbreviated Injury Scale (AIS) 3+ rib fractures, in frontal crashes with a deployed frontal airbag, were selected from the CIREN database. The circumferential location of each rib fracture (with respect to the sternum) was documented using a previously published method (Ritchie et al. 2006) and digital computed tomography scans. Fracture patterns for different crash and occupant parameters (restraint use, involved physical component, occupant kinematics, crash principal direction of force, and occupant age) were compared qualitatively and quantitatively.

Results: There were 158 belted and 44 unbelted occupants included in this study. For belted occupants, fractures were mainly located near the path of the shoulder belt, with the majority of fractures occurring on the inboard (with respect to the vehicle) side of the thorax. For unbelted occupants, fractures were approximately symmetric and distributed across both sides of the thorax. There were negligible differences in fracture patterns between occupants with frontal (0°) and near side (330° to 350° for drivers; 10° to 30° for passengers) crash principal directions of force but substantial differences between groups when occupant kinematics (and contacts within the vehicle) were considered. Age also affected fracture pattern, with fractures tending to occur more anteriorly in older occupants and more laterally in younger occupants (both belted and unbelted).

Conclusions: Results of this study confirmed with real-world data that rib fracture patterns in unbelted occupants were more distributed and symmetric across the thorax compared to belted occupants in crashes with a deployed frontal airbag. Other factors, such as occupant kinematics and occupant age, also produced differing patterns of fractures. Normative data on rib fracture patterns in real-world occupants can contribute to understanding injury mechanisms and the role of different causation factors, which can ultimately help prevent fractures and improve vehicle safety.     

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics

Objective: Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity.

Methods: The NASS-CDS 2000–2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0–4, 5–9, 10–14, and 15–18 years. Next, the National Trauma Databank 2002–2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MR_MAIS) for each injury within 6 age groups: 0–4, 5–9, 10–14, 15–18, 0–18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated.

Results: MR and MR_MAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MR_MAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MR_MAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MR_MAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.

Conclusions: Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.     

Association Between NCAP Ratings and Real-World Rear Seat Occupant Risk of Injury

Objective: Several studies have evaluated the correlation between U.S. or Euro New Car Assessment Program (NCAP) ratings and injury risk to front seat occupants, in particular driver injuries. Conversely, little is known about whether NCAP 5-star ratings predict real-world risk of injury to restrained rear seat occupants. The NHTSA has identified rear seat occupant protection as a specific area under consideration for improvements to its NCAP. In order to inform NHTSA's efforts, we examined how NCAP's current 5-star rating system predicts risk of moderate or greater injury among restrained rear seat occupants in real-world crashes.

Methods: We identified crash-involved vehicles, model year 2004–2013, in NASS-CDS (2003–2012) with known make and model and nonmissing occupant information. We manually matched these vehicles to their NCAP star ratings using data on make, model, model year, body type, and other identifying information. The resultant linked NASS-CDS and NCAP database was analyzed to examine associations between vehicle ratings and rear seat occupant injury risk; risk to front seat occupants was also estimated for comparison. Data were limited to restrained occupants and occupant injuries were defined as any injury with a maximum Abbreviated Injury Scale (AIS) score of 2 or greater.

Results: We linked 95% of vehicles in NASS-CDS to a specific vehicle in NCAP. The 18,218 vehicles represented an estimated 6 million vehicles with over 9 million occupants. Rear seat passengers accounted for 12.4% of restrained occupants. The risk of injury in all crashes for restrained rear seat occupants was lower in vehicles with a 5-star driver rating in frontal impact tests (1.4%) than with 4 or fewer stars (2.6%, P =.015); results were similar for the frontal impact passenger rating (1.3% vs. 2.4%, P =.024). Conversely, side impact driver and passenger crash tests were not associated with rear seat occupant injury risk (driver test: 1.7% for 5-star vs. 1.8% for 1–4 stars; passenger test: 1.6% for 5 stars vs 1.8% for 1–4 stars).

Conclusions: Current frontal impact test procedures provide some degree of discrimination in real-world rear seat injury risk among vehicles with 5 compared to fewer than 5 stars. However, there is no evidence that vehicles with a 5-star side impact passenger rating, which is the only crash test procedure to include an anthropomorphic test dummy (ATD) in the rear, demonstrate lower risks of injury in the rear than vehicles with fewer than 5 stars. These results support prioritizing modifications to the NCAP program that specifically evaluate rear seat injury risk to restrained occupants of all ages.     

Epidemiology of injury patterns for 4- to 10-year-olds in side and oblique impacts

Abstract

Objectives: With regard to the pediatric population involved in vehicle side impact collisions, epidemiologic data can be used to identify specific injury-producing conditions and offer possible safety technology effectiveness through population-based estimates. The objective of the current study was to perform a field data analysis to investigate injury patterns and sources of injury to 4- to 10-year-olds in side and oblique impacts to determine the potential effect of updated side impact regulations and airbag safety countermeasures.

Methods: The NASS-CDS, years 1991 to 2014, was analyzed in the current study. The Abbreviated Injury Scale (AIS) 2005–Update 2008 was used to determine specific injuries and injury severities. Injury distributions were examined by body region as specified in the AIS dictionary and the Maximum AIS (MAIS). Children ages 4 to 10 were examined in this study. All occupant seating locations were investigated. Seating positions were designated by row and as either near side, middle, or far side. Side impacts with a principal direction of force (PDOF) between 2:00 and 4:00 as well as between 8:00 and 10:00 were included. Restraint use was documented only as restrained or unrestrained and not whether the restraint was being used properly. Injury distribution by MAIS, body region, and source of injury were documented. Analysis regarding occupant injury severity, body region injured, and injury source was performed by vehicle model year to determine the effect of updated side impact testing regulation and safety countermeasures. Because the aim of the study was to identify the most common injury patterns and sources, only unweighted data were analyzed.

Results: Main results obtained from the current study with respect to 4- to 10-year-old child occupants in side impact were that a decrease was observed in frequency of MAIS 1–3 injuries; injuries to the head, face, and extremities; as well as injuries caused by child occupant interaction with the vehicle interior and seatback support structures in 1998 model year passenger cars and newer.

Conclusions: Results from this study could be useful in design advances of pediatric anthropomorphic test devices, child restraints, as well as vehicles and their safety countermeasure systems.     

Improving the Chest Protection of Elderly Occupants in Frontal Crashes Using SMART Load Limiters

Objective: To determine whether varying the seat belt load limiter (SBL) according to crash and occupant characteristics could have real-world injury reduction benefits in frontal impacts and, if so, to quantify those benefits.

Methods: Real-world UK accident data were used to identify the target population of vehicle occupants and frontal crash scenarios where improved chest protection could be most beneficial. Generic baseline driver and front passenger numerical models using a 50th percentile dummy were developed with MADYMO software. Simulations were performed where the load limiter threshold was varied in selected frontal impact scenarios. For each SBL setting, restraint performance, dummy kinematics, and injury outcome were studied in 5 different frontal impact types. Thoracic injury predictions were converted into injury probability values using Abbreviated Injury Scale (AIS) 2+ age-dependent thoracic risk curves developed and validated based on a methodology proposed by Laituri et al. (2005). Real-world benefit was quantified using the predicted AIS 2+ risk and assuming that an appropriate adaptive system was fitted to all the cars in a real-world sample of recent frontal crashes involving European passenger cars.

Results: From the accident data sample the chest was the most frequently injured body region at an AIS 2+ level in frontal impacts (7% of front seat occupants). The proportion of older vehicle front seat occupants (>64 years) with AIS 2+ injury was also greater than the proportion of younger occupants. Additionally, older occupants were more likely to sustain seat belt–induced serious chest injury in low- and moderate-speed frontal crashes. In both front seating positions, the low SBL provided the best chest injury protection, without increasing the risk to other body regions. In severe impacts, the low SBL allowed the driver to move dangerously close to the steering wheel. Compared to the driver side, greater ride-down space on the passenger side gave a higher potential for using the low SBLs. When applying the AIS 2+ risk reduction findings to the weighted accident data sample, the risk of sustaining an AIS 2+ seat belt injury changed to 0.9, 4.9, and 8.1% for young, mid, and older occupants, respectively, from their actual injury risk of 1.3, 7.6, and 13.1%.

Conclusions: These results suggest the potential for improving the safety of older occupants with the development of smarter restraint systems. This is an important finding because the number of older users is expected to increase rapidly over the next 20 years. The greatest benefits were seen at lower crash severities. This is also important because most real-world crashes occur at lower speeds.     

Rollover injury: effects of near- and far-seating position, belt use, and number of quarter rolls

PURPOSE: Vehicle and occupant responses in rollovers are complex since many factors influence both. This study analyzes the following factors: 1) belt use, 2) seated position with respect to the lead side in the rollover, 3) another front occupant in the crash, and 4) number of quarter rolls. The aim was to improve our understanding of rollover injury mechanisms. METHOD: Rollover accidents were analyzed using 1992-2004 NASS-CDS data. The sample included adult drivers and right-front passengers. All occupants were evaluated and then a subset of non-ejected occupants was analyzed. Using roll direction and seating position, the sample was divided into near- and far-seated occupants. Injury and fatality risks were determined by seatbelt use, occupancy, rollover direction, and number of quarter rolls. Risk was defined as the number of injured (e.g., MAIS 3+) divided by the number of exposed occupants (MAIS 0-6). Significance in differences was determined. A matched-pair analysis was used to determine the risk of serious injury for near- and far-seated occupants who were either belted or unbelted in the same crash. RESULTS: For all occupants, serious injury risks were highest for far-seated, unbelted occupants at 18.1% +/- 4.8%, followed by near-seated unbelted occupants at 12.0% +/- 3.5%. However, the difference was not statistically significant. Belted near- and far-seated occupants had a similar injury risk of 4.3% +/- 1.2% and 4.0% +/- 1.2%, respectively. For non-ejected occupants, serious injury risk was 9.5% +/- 3.2% for far-seated unbelted occupants and 4.9% +/- 2.1% for near-seated unbelted occupants, not a statistically significant difference. Serious injury risk was similar for belted near- and far-seated non-ejected occupants, at 3.6% +/- 1.1%. Seatbelts were 64.2%-77.9% effective in preventing serious injury for all occupants and 62.1%-26.5% for far- and near-seated, non-ejected occupants, respectively. Based on the matched pairs, seatbelts were less effective for near-seated (5.0%) compared to far-seated (2.8%) occupant MAIS 3+F risks. This was similar for non-ejected occupants. An unbelted near-seated occupant increased the risk for a belted far-seated occupant by 2.2 times, whereas an unbelted far-seated occupant increased the risk for a belted near-seated occupant by 10.2 times. For all occupants, the risk of serious injury increased with the number of quarter rolls, irrespective of seated position. For near-seated occupants, seatbelt effectiveness was higher in < or =1 roll than 1+ roll, at 72.3% compared to 28.3%. For far-seated occupants, seatbelt effectiveness was similar in < or =1 and 1+ roll samples at 78.3% and 76.8%, respectively. Near-seated occupants had the lowest serious injury risk when they were the sole occupant in the vehicle. This was also true for non-ejected occupants. However, far-seated occupants had a lower injury risk when another occupant was involved in the crash. CONCLUSIONS: The effect of carrying another occupant appears to reduce the risk of serious injury to far-seated occupants. However, near-seated occupants are better off being the sole occupant in the vehicle. Seatbelt effectiveness was lowest at 28.3% for non-ejected, near-seated occupants in 1+ rolls. This finding deserves further evaluation in an effort to improve seatbelt effectiveness in rollovers. For belted drivers alone in a rollover, fatality risks are 2.24 times higher for the far- versus near-seated position. Analysis of rollovers by quarter turns indicates that occupants are both far-side and near-side in rollovers. The extent to which this confounds the relationship between roll direction, seating position, and injury risk is unknown.