Statewide Integrated Traffic Records System Research Articles

Determinants influencing alcohol-related two-vehicle crash severity: A multivariate Bayesian hierarchical random parameters correlated outcomes logit model

Alcohol-related driving remains a significant concern due to its profound association with the likelihood of traffic crashes and the severity of resulting injuries, especially between two vehicles. To investigate the determinants influencing the alcohol-related two-vehicle crash severity, a foundational framework employed was a multinomial logit model. Meanwhile, by incorporating random intercept from individual case and vehicle levels to accommodate unobserved heterogeneity, and covariance matrices to underscore correlated outcomes, a multivariate hierarchical random parameters correlated outcomes logit model was proposed. Additionally, to further explore the potential temporal instability of explanatory variables, a random slope from a per-year indicator was introduced into the model. Crash data from the US Statewide Integrated Traffic Records System (SWITRS) database spanning from January 1, 2016, to December 31, 2021, was used. Three crash injury severity categories were examined, encompassing severe injury, minor injury, and no injury, with characteristics related to the driver, vehicle, road, environment, crash, and time serving as explanatory variables. The model results highlighted significant heterogeneity, with each case and vehicle accounting for 56.9% of the total variance for minor injuries and 50.8% for severe injuries. Furthermore, a significant negative correlation was explicitly exhibited between minor injury and severe injury outcomes at the case level. In terms of potential temporal instability, we provided per-year (2016–2019) parameter estimates and identified significant instability for indicators such as non-intersection, broadside and head-on collisions, cloudy weather conditions, and drivers who had been drinking but were not under the influence. Considering the impact of the COVID-19 pandemic, we divided the accident time into pre-COVID and during-COVID periods, modeling parameter estimates for both periods. This analysis revealed significant instability in several factors influenced by the pandemic. Additionally, noteworthy disparities in the estimated results of explanatory variables emerged in comparison to those general two-vehicle crashes or alcohol-related crashes, providing valuable insights. For instance, drivers who had been drinking but were not under the influence were less likely to sustain severe injuries, but the probability of minor injuries increased. These findings underscore the significance of thorough investigations into the determinants of injury severity in alcohol-impaired two-vehicle crash severity, along with the temporal instability of such factors. They hold important implications for effective traffic safety management and the formulation of prohibitive countermeasures.

Trends and correlates of spatially aggregated alcohol-involved crashes among Whites and Hispanics in California.

This paper examines trends and correlates of alcohol-involved motor vehicle crashes (AMVCs) in California between 2005 and 2016 among Hispanic and non-Hispanic Whites (Whites hereafter). Together these two groups comprise 76% of the state population. The paper also examines whether alcohol outlet density, percentage of Hispanics in census tract populations, and distance to the U.S./Mexico border are related to greater risks for AMVCs. The border is of interest given the greater availability of alcohol in the area. Crash data come from Statewide Integrated Traffic Records System maintained by the California Highway Patrol. Sociodemographic and community characteristics data from the U.S. Census and alcohol outlet density were aggregated to census tracts. Total motor vehicle crashes and AMVCs were related to these characteristics using hierarchical Bayesian Poisson space-time models. There were over two million injury and fatality crashes during the period of analysis, of which 11% were AMVCs. About 1.7% of these crashes had fatalities. The rate of AMVCs increased among both Whites and Hispanics until 2008. After 2008, the rate among Whites declined through 2016 while the rate among Hispanics declined for 2 years (2009 and 2010) and increased thereafter. Crash distance from the border (RR=1.016, 95% CI=1.010 to 1.022) and percent Hispanic population (RR=1.006; 95% CI=1.003 to 1.009) were well-supported results with 95% credible intervals that did not include 1. The percentages of the following: bars/pubs, males, individuals aged 18 to 29 and 40 to 49 years, U.S. born population, individuals below the 150% poverty level, unemployed, housing vacant, and housing owner-occupied were all positively associated with AMVCs and well supported. Between 2005 and 2016 the rate of AMVCs in California declined among Whites but not among Hispanics. Population-level indicators of percent Hispanic population, distance to the U.S. Mexico border, gender, age distribution, and socioeconomic stability were positively associated with crash rates, indicating that important contextual characteristics help determine the level of AMVC rates in communities.

Bike Helmet Usage in the Most Disadvantaged Neighborhoods: A Focused Area for Trauma Prevention

IntroductionThere is a paucity of data to describe how neighborhood socioeconomic disadvantage (NSD) correlates with childhood injuries and outcomes. This study assesses the relationship of NSD to bicycle safety and trauma outcomes among pediatric bicycle versus automobile injuries. MethodsBetween 2008 and 2018, patients ≤18 y old with bicycle versus automobile injuries from a Level I pediatric trauma center were evaluated. Area Deprivation Index (ADI) was used to measure NSD. Patient demographics, injury, clinical data characteristics, and bike safety were analyzed. Traffic scene data from the Statewide Integrated Traffic Records System were matched to clinical records. Multivariate logistic regression was used to assess demographic characteristics related to helmet usage. ResultsAmong 321 patients, 84% were male with a median age of 12 y [interquartile range 9-13], and 44% were of Hispanic ethnicity. Hispanic ethnicity was greater in the most disadvantaged ADI groups (P < 0.001). Mortality occurred in two patients, and most (96%) were discharged home. Of Statewide Integrated Traffic Records System matched traffic records, 81% were at locations without a bike lane. No differences were found in GCS, intensive care unit admission, or length of stay by ADI. Hispanic ethnicity and the highest deprivation group were independently associated with lower odds of wearing a helmet (AOR 0.35, 95% confidence interval 0.1-0.9, P = 0.03; AOR 0.33 95% confidence interval 0.17-0.62; P = 0.001), while patient age and sex were unrelated to helmet usage. ConclusionsOutcomes for bike versus auto trauma remains similar across ADI groups. However, bike helmet usage is significantly lower among Hispanic children and those from neighborhoods with greater socioeconomic disadvantage.

Integrating traffic safety data with area deprivation index: A method to better understand the causes of pediatric pedestrian versus automobile collisions.

The purpose of this study was to identify clinical and traffic factors that influence pediatric pedestrian versus automobile collisions (P-ACs) with an emphasis on health care disparities. A retrospective review was performed of pediatric (18 years or younger) P-ACs treated at a Level I pediatric trauma center from 2008 to 2018. Demographic, clinical, and traffic scene data were analyzed. Area deprivation index (ADI) was used to measure neighborhood socioeconomic disadvantage (NSD) based on home addresses. Traffic scene data from the California Statewide Integrated Traffic Records System were matched to clinical records. Traffic safety was assessed by the streetlight coverage, the proximity of the collision to home addresses, and sidewalk coverage. Descriptive statistics and univariate analysis for key variables and outcomes were calculated using Kruskal-Wallis, Wilcoxon, χ 2 , or Fisher's exact tests. Statistical significance was attributed to p values of <0.05. Among 770 patients, the majority were male (65%) and Hispanic (54%), with a median age of 8 years (interquartile range, 4-12 years). Hispanic patients were more likely to live in more disadvantaged neighborhoods than non-Hispanic patients (67% vs. 45%, p < 0.01). There were no differences in clinical characteristics or outcomes across ADI quintiles. Using the Statewide Integrated Traffic Records System (n = 272), patients with more NSD were more likely injured during dark streetlight conditions (15% vs. 4% least disadvantaged; p = 0.04) and within 0.5 miles from home ( p < 0.01). Pedestrian violations were common (65%). During after-school hours, 25% were pedestrian violations, compared with 12% driver violations ( p = 0.02). A larger proportion of Hispanic children injured in P-ACs lived in neighborhoods with more socioeconomic disadvantage. Hispanic ethnicity and NSD are each independently associated with P-ACs. Poor streetlight conditions and close proximity to home were associated with the most socioeconomically disadvantaged neighborhoods. This research may support targeted prevention programs to improve pedestrian safety in children. Prognostic/Epidemiological; Level IV.

Enhancing trauma registries by integrating traffic records and geospatial analysis to improve bicyclist safety.

Trauma registries are used to identify modifiable injury risk factors for trauma prevention efforts. However, these may miss factors useful for prevention of bicycle-automobile collisions, such as vehicle speeds, driver intoxication, street conditions, and neighborhood characteristics. We hypothesize that (GIS) analysis of trauma registry data matched with a traffic accident database could identify risk factors for bicycle-automobile injuries and better inform injury prevention efforts. The trauma registry of a US Level I trauma center was used retrospectively to identify bicycle-motor vehicle collision admissions from January 1, 2010, to December 31, 2018. Data collected included demographics, vitals, injury severity scores, toxicology, helmet use, and mortality.Matching with the Statewide Integrated Traffic Records System was done to provide collision, victim and GIS information. The GIS mapping of collisions was done with census tract data including poverty level scoring. Incident hot spot analysis to identify statistically significant incident clusters was done using the Getis Ord Gi* statistic. Of 25,535 registry admissions, 531 (2.1%) were bicyclists struck by automobiles, 425 (80.0%) were matched to Statewide Integrated Traffic Records System. Younger age (odds ratio [OR], 1.026; 95% confidence interval [CI], 1.013-1.040, p < 0.001), higher census tract poverty level percentage (OR, 0.976; 95% CI, 0.959-0.993, p = 0.007), and high school or less education (OR, 0.60; 95 CI, 0.381-0.968; p = 0.036) were predictive of not wearing a helmet. Higher census tract poverty level percentage (OR, 1.019; 95% CI, 1.004-1.034; p = 0.012) but not educational level was predictive of toxicology positive-bicyclists in automobile collisions. Geographic information systems analysis identified hot spots in the catchment area for toxicology-positive bicyclists and lack of helmet use. Combining trauma registry data and matched traffic accident records data with GIS analysis identifies additional risk factors for bicyclist injury. Trauma centers should champion efforts to prospectively link public traffic accident data to their trauma registries. Prognostic and Epidemiological, level III.

Space-Time Analyses of Alcohol Outlets and Related Motor Vehicle Crashes: Associations at City and Census Block-Group Levels.

Past research has linked alcohol outlet densities to drinking, drunken driving, and alcohol-related motor vehicle crashes (MVCs). Because impaired drivers travel some distances from drinking places to crash locations, spatial relationships between outlets and crashes are complex. We investigate these relationships at 3 geographic levels: census block groups (CBGs), adjacent (nearby) areas, and whole cities. We examined risks of all injury MVCs as well as "had been drinking" (HBD) and single-vehicle-nighttime (SVN) subgroups using data from the Statewide Integrated Traffic Records System across CBGs among 50 California cities from 2001 to 2008. Relationships between outlet densities at the city level, within CBGs, and in adjacent CBGs and crashes were examined using Bayesian Poisson space-time analyses controlling for population size income and other demographics (all as covariates). All injury MVCs were positively related to adjacent CBG population size (relative rate [RR]=1.008, 95% credible interval (CI)=1.004, 1.012), and outlet densities at CBG (RR=1.027, CI=1.020, 1.035), nearby area (RR=1.084, CI=1.060, 1.106) and city levels (RR=1.227, CI=1.147, 1.315), and proportion of bars or pubs at the city level (RR=2.257, CI=1.187, 4.125). HBD and SVN crashes were comparatively less frequent in high outlet density CBG (RR=0.993, CI=0.987, 0.999; RR=0.963, CI=0.951, 0.975) and adjacent areas (RR=0.979, CI=0.962, 0.996; RR=0.909, CI=0.883, 0.936), but positively associated with city-level proportions of bars (RR=3.373, CI=0.736, 15.644; RR=10.322, CI=1.704, 81.215). Overall, a 10% increase in alloutlets was related to 2.8% more injury crashes (CI=2.3, 3.3) and 2.5% more HBDs (CI=1.7, 3.3). A10% increase in bars was related to 1.4% more crashes, 4.3% more HBDs, and 10.3% more SVNs. Population size and densities of bars or pubs were found to be associated with crash rates, with population effects appearing across cities and outlet effects appearing within dense downtown areas. Summary estimates of outlet and population impacts on MVCs must consider varying contributions at multiple spatial scales.

Cannabis and crash responsibility while driving below the alcohol per se legal limit

There is a growing interest in how extensively the use of marijuana by drivers relates to crash involvement. While cognitive, lab-based studies are consistent in showing that the use of cannabis impairs driving tasks, epidemiological, field-based studies have been inconclusive regarding whether cannabis use causes an increased risk of accidents. There is ample evidence that the presence of cannabis among drivers with a BAC≥0.08g/dL highly increases the likelihood of a motor vehicle crash. Less clear, however, is the contribution of cannabis to crash risk when drivers have consumed very little or no alcohol. This effort addresses this gap in knowledge. We took advantage of a unique database that merged fatal crashes in the California Statewide Integrated Traffic Records System (SWITRS) and the Fatality Analysis Reporting System (FARS), which allows for a precise identification of crash responsibility. To account for recent increase in lab testing, we restricted our sample to cover only the years 1993–2009. A total of 4294 drivers were included in the analyses. Descriptive analyses and logistic regressions were run to model the contribution of alcohol and drugs to the likelihood of being responsible in a fatal crash. We found evidence that compared with drivers negative for alcohol and cannabis, the presence of cannabis elevates crash responsibility in fatal crashes among drivers at zero BACs (OR=1.89) and with 0<BAC<0.05g/dL (OR=3.42), suggesting that emphasis on curbing impaired driving should not be solely focused on heavy-drinking drivers. Data limitations however caution about the generalizability of study findings. Special efforts to understand the effect of cannabis on fatal crashes, in particular in the absence of alcohol, are needed.

A52 Trends in inpatient admissions for pedal cycle injuries for the state of California: 2005-2011

Abstract Background In the United States, cycling has grown substantially in popularity in recent years. It is unclear, however, whether pedal cycling safety, such as use of helmets, have kept pace with this rapid growth. We use administrative records of pedal cyclist crashes and hospitalizations to explore trends in injuries and fatalities among pedal cyclists in the state of California. Methods We perform a retrospective analysis of the Statewide Integrated Traffic Records System (SWITRS), the State Emergency Department Database (SEDD), and the State Inpatient Database (SID) for the state of California in 2005 to 2011. SWITRS contains all motor vehicle crash records reported to law enforcement in California and is maintained by the California Highway Patrol. SEDD/SID provide records on all emergency department (ED) and inpatient admissions in community hospitals for California. Pedal cyclist injury records were selected using Clinical Classification Software codes (External Causes of Injury code 2608 “Pedal Cyclist, not MVT”). We examine patient characteristics related to pedal cyclist injuries including age, gender, insurance status, race, disposition status and all related bodily injuries. Trends in number of bicycle-related injuries on public roads, and ED visits and inpatient admissions (number and per capita) are presented. Cost-to-charge ratios provided by HCUP are used to calculate costs of treatment for injured bicyclists. Results During the 7-year period from 2005 to 2011, there were 275,845 ED visits and 24,281 pedal cyclist-related inpatient admissions in the state of California. Number of ED visits per 100,000 population increased from 95.1 to 122.6 in 2005-11—a 29% increase. Much of this increase was driven by older pedal cyclists. The average age of a cyclist increased by 3.4 years in the study period, and the proportion aged 45 and older increased from 15.9% to 22.1%. For inpatient admissions, this proportion increased from 39.1% to 50.4%. Upper limb fractures and intracranial injuries were the most common types of injuries sustained by hospitalized pedal cyclists. Median inpatient costs of treatment were $11,264 per case, and totaled $59.7 million in 2011. Conclusions In an average week in California, there are about 26.5 million pedal cycling trips. Although pedal cycling is associated with a number of important cardiovascular and other health benefits, our study suggests that injuries have increased substantially as pedal cycling has become more popular. These results call for the need to examine pedal cycling safety efforts, especially among older riders who are at risk for serious injury.

The relationship between gasoline price and patterns of motorcycle fatalities and injuries

ObjectiveEconomic factors such as rising gasoline prices may contribute to the crash trends by shaping individuals’ choices of transportation modalities. This study examines the relationship of gasoline prices with fatal...

Estimating the over-involvement of suspended, revoked, and unlicensed drivers as at-fault drivers in California fatal crashes

Introduction and MethodQuasi-induced exposure analysis was used to estimate annual fatal crash involvement rates for validly licensed, suspended or revoked (S/R), and unlicensed drivers in California from 1987 through 2009 using fatal crash data obtained from the National Highway Traffic Safety Administration's Fatality Analysis Reporting System and crash culpability determinations from the California Highway Patrol's Statewide Integrated Traffic Records System. ResultsAlthough there was some year-to-year fluctuation in the annual estimates, S/R and unlicensed drivers were over-involved as at-fault drivers in fatal crashes during every year of the 23-year time period relative to validly licensed drivers. The fatal crash involvement ratios combined across all years were 0.86 for validly licensed drivers, 2.23 for S/R drivers, and 2.34 for unlicensed drivers. Hence, compared to validly licensed drivers, the odds of being at-fault for a fatal crash were 160% higher for S/R drivers (involvement ratio=2.60) and 173% higher for unlicensed drivers (involvement ratio=2.73). The excess risks of S/R and unlicensed drivers are somewhat lower than estimates found in a prior study using the same technique, but the results nonetheless provide evidence that S/R and unlicensed drivers are much more hazardous on the road than are validly licensed drivers and emphasize the importance of using strong countermeasures—including vehicle impoundment—to reduce their high crash risk. These findings support interventions to help reduce driving among S/R and unlicensed drivers.

A Geographic Analysis of Collisions Involving Child Pedestrians in a Large Southern California County

Objectives: The goal of this study is to explore the relationship between child pedestrian injuries and socioeconomic characteristics of neighborhoods in the context of local traffic volume. Methods: Child pedestrian collisions were identified in the data of the California Statewide Integrated Traffic Records System (SWITRS). Nine hundred sixty crashes over a 5-year period were identified, geocoded, and mapped to Orange County census tracts. Census data from 2000 were used to identify tracts, population, and population characteristics in the county of approximately 3,000,000 individuals. Pedestrian collision maps were merged with census characteristics and analyzed using STATA (Version 10.1, Stata Corp, College Station, IX) to determine correlations between socioeconomic factors and collision rates within census tracts. Results: The percentage of the population living in households with low income (less than 185% of the federal poverty level) was the strongest predictor of pedestrian injuries. One fourth of census tracts had less than 9 percent of residents with low income and averaged 6 per 100,000 child pedestrian crashes annually. One fourth of the census tracts had more than 32 percent of residents with low income and an average of 56 child pedestrian crashes per 100,000 annually. These data indicate an 8.8-fold increase in collision frequency in the lowest income quartile over the highest income quartile. Other socioeconomic correlates strongly associated with increased child collisions include population density, proportion of population speaking English less than very well, lack of high school education, number of multifamily residences, and Latino ethnicity. Conclusions: Our study showed that child pedestrian collisions are nearly 9 times more frequent in the poorest quartile of neighborhoods than in the richest quartile. Other factors associated with increased pediatric collision risk include increased neighborhood crowding, low levels of education and English speaking ability, and Latino ethnicity.

The Relationship of Pedestrian Injuries to Socioeconomic Characteristics in a Large Southern California County

Objectives: The goal of this study is to explore the relationship between pedestrian injuries and socioeconomic characteristics. Methods: Pedestrian collisions were identified in the data of the California Statewide Integrated Traffic Records System (SWITRS), which is assembled from police crash reports by the California Highway Patrol Information Services Unit. Four thousand crashes were identified and geocoded within the census tracts in a county population of 2,846,289 over a 5-year period. Population and population characteristics for census tracts were obtained from the 2000 U.S. Census. Results: The percentage of the population living in households with low income (less than 185% of the federal poverty level) was the strongest predictor of pedestrian injuries. One fourth of census tracts had less than 8.7 percent of residents with low income and averaged 11 per 100,000 pedestrian crashes annually. One fourth of the census tracts had more than 32.2 percent of residents with low income and an average of 44 pedestrian crashes per 100,000 annually. Negative binomial regression showed that with each 1 percent increase in the percentage of residents with low income was associated with a 2.8 percent increase in pedestrian crashes. The percentage of residents age 14 years or less, adult residents who had not completed high school, residents who spoke English less than “very well” and spoke another language at home, and the population density were each associated with a higher frequency of pedestrian crashes. However, when low income was added to these 4 regression models, the relationship between low income and pedestrian crashes increased. Conclusions: Our study showed that pedestrian crashes are 4 times more frequent in poor neighborhoods and that neither age of the population, education, English language fluency, nor population density explained the effect of poverty.

Socioeconomic disparities in pedestrian injuries

Pedestrian injuries are an important component of motor vehicle injuries, especially for children. We examined the association between pedestrian collisions and the social environment using data from a large suburban...

Geocoding police collision report data from California: a comprehensive approach

BackgroundCollision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record. On California police reports, relative collision location is recorded using a highway postmile marker or a street intersection. The objective of this study was to create a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies.ResultsGeocoding was completed with a multi-step process. First, pre-processing was performed using a scripting language to clean and standardize street name information. A state highway network with postmile values was then created using a custom tool written in Visual Basic for Applications (VBA) in ArcGIS software. Custom VBA functionality was also used to incorporate the offset direction and distance. Intersection and address geocoding was performed using ArcGIS, StreetMap Pro 2003 digital street network, and Google Earth Pro. A total of 142,007 fatal and severe injury collisions were identified in SWITRS. The geocoding match rate was 99.8% for postmile-coded collisions and 86% for intersection-coded collisions. The overall match rate was 91%.ConclusionsThe availability of geocoded collision data will be beneficial to clinicians, researchers, policymakers, and practitioners in the fields of traffic safety and public health. Potential uses of the data include studies of collision clustering on the highway system, examinations of the associations between collision occurrence and a variety of variables on environmental and social characteristics, including housing and personal demographics, alcohol outlets, schools, and parks. The ability to build maps may be useful in research planning and conduct and in the delivery of information to both technical and non-technical audiences.

Measuring the impact of passenger restrictions on new teenage drivers

Passenger restrictions for new teenage drivers that became law in 1998 in California provide an opportunity to study the effectiveness of such laws in reducing the number of passengers as well as the influence of teenage passengers on novice drivers. Using fatal and injury crash data from California’s Statewide Integrated Traffic Records System, this study found that teenage passengers are a causal factor in crashes of 16-year-old drivers and that in the three years following implementation of the new law, the average number of teenage passengers carried by 16-year-olds decreased by approximately 25%. Without considering the beneficial effect of a decrease in the crash rate, the decrease in the number of teenage passengers in actual crashes resulted in an estimated saving of eight lives and the prevention of 684 injuries over a three-year period.