Continued trends in older driver crash involvement rates in the United States: Data through 2017–2018

Introduction: With the growing older adult population due to the aging baby-boom cohort, there was concern that increases in fatal motor-vehicle crashes would follow. Yet, previous analyses showed this to be untrue. The purpose of this study was to examine current trends to determine if previous declines have persisted or risen with the recent increase in fatalities nationwide. Methods: Trends among drivers ages 70 and older were compared with drivers 35–54 for U.S. passenger vehicle fatal crash involvements per 100,000 licensed drivers from 1997 to 2018, fatal and all police-reported crash involvements per vehicle miles traveled using the 1995, 2001, 2009, and 2017 National Household Travel Surveys, and driver deaths per 1,000 crashes. Results: Since the mid-1990s, fatal crashes per licensed driver trended downward, with greater declines for drivers ages 70 and older than for middle-aged drivers (43% vs. 21%). Fatal crash rates per 100,000 licensed drivers and police-reported crash rates per mile traveled for drivers ages 70–79 are now less than those for drivers ages 35–54, but their fatal crash rates per mile traveled and risk of dying in a crash remain higher as they drive fewer miles. As the economy improved over the past decade, fatal crash rates increased substantially for middle-aged drivers but decreased or remained stable among older driver age groups. Conclusions: Fatal crash involvements for adults ages 70 and older has recently increased, but they remain down from their 1997 peak, even as the number of licensed older drivers and the miles they drive have increased. Health improvements likely contributed to long-term reductions in fatal crash rates. As older drivers adopt vehicles with improved crashworthiness and safety features, crash survivability will improve. Practical Application: Older adults should feel confident that their independent mobility needs pose less risk than previously expected.     

Trends in teen driver licensure,driving patterns and crash involvement in the United States, 2006–2015

IntroductionThe Monitoring the Future (MTF) survey provides nationally-representative annual estimates of licensure and driving patterns among U.S. teens. A previous study using MTF data reported substantial declines in the proportion of high school seniors that were licensed to drive and increases in the proportion of nondrivers following the recent U.S. economic recession.MethodTo explore whether licensure and driving patterns among U.S. high school seniors have rebounded in the post-recession years, we analyzed MTF licensure and driving data for the decade of 2006–2015. We also examined trends in teen driver involvement in fatal and nonfatal injury crashes for that decade using data from the Fatality Analysis Reporting System and National Automotive Sampling System General Estimates System, respectively.ResultsDuring 2006–2015, the proportion of high school seniors that reported having a driver's license declined by 9 percentage points (11%) from 81% to 72% and the proportion that did not drive during an average week increased by 8 percentage points (44%) from 18% to 26%. The annual proportion of black seniors that did not drive was consistently greater than twice the proportion of nondriving white seniors. Overall during the decade, 17- and 18-year-old drivers experienced large declines in fatal and nonfatal injury crashes, although crashes increased in both 2014 and 2015.ConclusionsThe MTF data indicate that licensure and driving patterns among U.S. high school seniors have not rebounded since the economic recession. The recession had marked negative effects on teen employment opportunities, which likely influenced teen driving patterns. Possible explanations for the apparent discrepancies between the MTF data and the 2014 and 2015 increases in crashes are explored.Practical applicationsMTF will continue to be an important resource for clarifying teen driving trends in relation to crash trends and informing strategies to improve teen driver safety.     

Investigating traffic fatality trends and restraint use among rear-seat passengers in the United States, 2000–2016

Introduction: Motor-vehicle crash is one of the leading causes of unintentional injury death in the United States. Previous studies focused on fatalities among drivers and front-seat passengers, with a limited number of studies examining rear-seat passenger fatalities. The objectives of this study were to assess trends in rear-seat passenger motor-vehicle fatalities in the United States from 2000 to 2016 and to identify demographic factors associated with being unrestrained among fatally injured rear-seat passengers. Methods: Rear-seat passenger fatality data were obtained from the Fatality Analysis Reporting System (FARS) database. The fatality rate ratios for overall rear-seat passengers and for different age and sex groups were determined by comparing fatality rates in 2000 and 2016 using random effects models. Risk ratios of being unrestrained for age and sex groups were obtained using general estimating equations. Results: Compared to 2000, the overall rear-seat passenger fatality rate in 2016 decreased by 44% (95% confidence interval [CI]: 39–49%). In particular, the fatality rate among rear-seat passengers decreased more in males than females, and passengers aged 14–19 years experienced a larger decline than all other age groups. Fatally injured male rear-seat passengers had a higher risk of being unrestrained (adjusted risk ratio: 1.06, 95% CI: 1.04–1.07) than their female counterparts, and both youngest (≤13 years) and oldest (65–85 years) passengers were less likely to be unrestrained than those aged 20–64 years. Conclusions: Overall, fatality rates among rear-seat passengers have declined, with differential degrees of improvement by age and sex. Practical Applications: Continued restraint use enforcement campaigns targeted at teenagers and males would further preserve them from fatal injuries and improve traffic safety for the overall population.     

Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle–bicycle crashes

Introduction: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. Method: A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. Results: It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.     

State helmet laws and helmet use among fatally injured moped riders in the United States, 2011–2015

Objective: Research has found that mandatory motorcycle helmet laws increase helmet use and reduce motorcycle-related fatalities. However, the association between state moped helmet laws and helmet use in the United States has not been examined. This study investigated this association among a census of fatally injured moped riders in the United States.

Methods: A logistic regression model was constructed to analyze data extracted from the Fatality Analysis Reporting System (FARS) to examine risk factors for helmet nonuse among 572 moped riders fatally injured between 2011 and 2015.

Results: Fatally injured moped riders in states with universal helmet laws had 69 times the odds of wearing a helmet (P < .001).

Conclusions: Findings suggest that universal moped helmet laws increase helmet use. However, additional research is needed to examine helmet laws and use among nonfatally injured moped riders.     

Are there higher pedestrian fatalities in larger cities?: A scaling analysis of 115 to 161 largest cities in the United States

Objective: In 2012, 4,743 pedestrians were killed in the United States, representing 14% of total traffic fatalities. The number of pedestrians injured was higher at 76,000. Therefore, 36 out of 52 of the largest cities in the United States have adopted a citywide target of reducing pedestrian fatalities. The number of cities adopting the reduction goal during 2011 and 2012 increased rapidly with 8 more cities. We examined the scaling relationship of pedestrian fatality counts as a function of the population size of 115 to 161 large U.S. cities during the period of 1994 to 2011. We also examined the scaling relationship of nonpedestrian and total traffic fatality counts as a function of the population size.

Methods: For the data source of fatality measures we used Traffic Safety Facts Fatality Analysis Reporting System/General Estimates System annual reports published each year from 1994 to 2011 by the NHTSA. Using the data source we conducted both annual cross-sectional and panel data bivariate and multivariate regression models. In the construction of the estimated functional relationship between traffic fatality measures and various factors, we used the simple power function for urban scaling used by Bettencourt et al. (2007 Bettencourt LMA, Lobo J, Helbing D, Kühnert C, West GB. Growth, innovation, scaling and the pace of life in cities. Proc Natl Acad Sci USA. 2007;104:7301–7306.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], 2010 Bettencourt LMA, Lobo J, Strumsky D, West GB. Urban scaling and its deviations: revealing the structure of wealth, innovation and crime across cities. PLoS ONE. 2010;5:e13541.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and the refined STIRPAT (stochastic impacts by regression on population, affluence, and technology) model used in Dietz and Rosa (1994 Dietz T, Rosa EA. Rethinking the environmental impacts of population, affluence and technology. Human Ecology Review. 1994;1:277–300. [Google Scholar], 1997 Dietz T, Rosa EA. Effects of population and affluence on CO₂ emissions. Proc Natl Acad Sci USA. 1997;94:175–179.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and York et al. (2003 York R, Rosa EA, Dietz T. STIRPAT, IPAT and IMPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecol Econ. 2003;46:351–365.[Crossref], [Web of Science ®] , [Google Scholar]).

Results: We found that the scaling relationship display diseconomies of scale or sublinear for pedestrian fatalities. However, the relationship displays a superlinear relationship in case of nonpedestrian fatalities. The scaling relationship for total traffic fatality counts display a nearly linear pattern. When the relationship was examined by the 4 subgroups of cities with different population sizes, the most pronounced sublinear scaling relationships for all 3 types of fatality counts was discovered for the subgroup of megacities with a population of more than 1 million.

Conclusions: The scaling patterns of traffic fatalities of subgroups of cities depend on population sizes of the cities in subgroups. In particular, 9 megacities with populations of more than 1 million are significantly different from the remaining cities and should be viewed as a totally separate group. Thus, analysis of the patterns of traffic fatalities needs to be conducted within the group of megacities separately from the other cities with smaller population sizes for devising prevention policies to reduce traffic fatalities in both megacities and smaller cities.     

State-level seat belt use in the United States, 2011–2016: Comparison of self-reported with observed use and use by fatally injured occupants

Introduction: Despite 49 states and the District of Columbia having seat belt laws that permit either primary or secondary enforcement, nearly half of persons who die in passenger vehicle crashes in the United States are unbelted. Monitoring seat belt use is important for measuring the effectiveness of strategies to increase belt use. Objective: Document self-reported seat belt use by state seat belt enforcement type and compare 2016 self-reported belt use with observed use and use among passenger vehicle occupant (PVO) fatalities. Methods: We analyzed the Behavioral Risk Factor Surveillance System (BRFSS) self-reported seat belt use data during 2011–2016. The Pearson correlation coefficient (r) was used to compare the 2016 BRFSS state estimates with observed seat belt use from state-based surveys and with unrestrained PVO fatalities from the Fatality Analysis Reporting System. Results: During 2011–2016, national self-reported seat belt use ranged from 86–88%. In 2016, national self-reported use (87%) lagged observed use (90%) by 3 percentage points. By state, the 2016 self-reported use ranged from 64% in South Dakota to 93% in California, Hawaii, and Oregon. Seat belt use averaged 7 percentage points higher in primary enforcement states (89%) than in secondary states (82%). Self-reported state estimates were strongly positively correlated with state observational estimates (r = 0.80) and strongly negatively correlated with the proportion of unrestrained PVO fatalities (r = −0.77). Conclusion: National self-reported seat belt use remained essentially stable during 2011–2016 at around 87%, but large variations existed across states. Practical Applications: If seat belt use in secondary enforcement states matched use in primary enforcement states for 2016, an additional 3.98 million adults would have been belted. Renewed attention to increasing seat belt use will be needed to reduce motor-vehicle fatalities. Self-reported and observational seat belt data complement one another and can aid in designing targeted and multifaceted interventions.