Trauma Surgeon-Led and Funded Injury Prevention Program Decreases Admission for Motorcycle Crash Injuries

Background Unhelmeted motorcyclists injured in states with lax or poorly enforced helmet safety laws are frequently seen in rural trauma centers. A trauma surgeon started a comprehensive injury prevention and research fund with outreach to a three-state trauma center catchment area promoting injury prevention at area high schools and local communities. We hypothesized that unhelmeted riders would have more severe head injuries and fatalities than helmeted riders. Methods A trauma registry review of 708 injured motorcycle riders over an 11-year period examined demographics, helmet use, and clinical outcomes of helmeted and unhelmeted riders. A full-time injury prevention coordinator collaborating with law enforcement provided electronic and mechanical simulations with discussions regarding helmet use, alcohol avoidance, and responsible motorcycle riding for area high school students. This program coincided with the second half of our 11-year study. Multiple regression analysis evaluated predictors for head injury and death. Results Unhelmeted motorcyclists suffered worse head injuries, (OR 8.8, CI 1.6-2.4, P < .001), more severe overall injury (OR 10, CI 12.7-18.6, P < .001), and higher mortality (OR 2.7, CI .02-.15, P < .001). Local motorcycle-related trauma center admissions and deaths have stabilized in recent years while statewide motorcycle crashes have increased ( P < .05). Discussion Unhelmeted motorcyclists suffer worse head injuries and mortality rates. Physician-led outreach efforts for injury prevention may be effective. Trauma surgeons have ongoing opportunities to promote responsible motorcycle riding for schools and local communities.

Exploring the Relationship of Rush Hour Period and Fatal and Non-Fatal Crash Injuries In The U.S.: A Systematic Review and Meta-Analysis

Road crashes are preventable causes of morbidity and mortality. In the U.S., substantial crashes occur during the rush hour period. The rush hour represents the period of the day during which the density of humans and vehicles in the road environment is highest. In the U.S., the rush hour period is bi-modal, occurring in the morning and the afternoon, at times that vary by state and urban-rural status. This systematic review and meta-analysis aimed to evaluate the association between the rush hour period and fatal and non-fatal crash injuries. Selected articles were limited to peer-reviewed full-text articles that measured crash injury as an outcome and rush hour as either a predictor, covariate, stratification, or a control variable. A total of 13 articles were identified for systematic review and seven articles were included in the meta-analysis. Across the selected studies, the rush-hour period signified the period of "peak traffic flow." During the rush hour period, aggressive driving behavior, truck driving, bicycle riding, and precipitation were associated with increased crash events or crash injuries. Across the seven studies included in the meta-analysis, the effective sample size was 220,471. The rush-hour period was associated with a 41% increased risk of fatal crash injury (Pooled RR: 1.41; 95% CI: 1.35 - 1.48). The morning and afternoon rush hour periods were associated with 40% (Pooled RR: 1.40; 95% CI: 1.13-1.67) and 27% (Pooled RR:1.27; 95% CI: 1.10-1.44) increased crash injury risk, respectively. The rush hour period, though less commonly studied as a predictor of fatal and non-fatal crash injuries, represents an important domain in need of crash injury prevention attention. The knowledge of the pattern of crash injuries, as it varies across countries, states, regions, and county can inform policy and intervention, in the presence of competing public health needs.

Investigating Head-On Crash Severity Involving Commercial Motor Vehicles in Kentucky

This study examines various features affecting the severity associated with commercial motor vehicle (CMV, i.e., large truck and bus) head-on collisions on Kentucky highways. Recent five-year (2015–2019) crash data and variables rarely explored before (e.g., presence of centerline rumble strips, type of passing zone, and terrain type) were collected and prepared using Google Maps. A total of 378 CMV-related head-on collisions were analyzed. The generalized ordered probit (GOP) model was employed to identify the significant factors affecting the severity level resulting from CMV head-on collisions. The model allows the coefficients to vary across the injury severity categories for reliable parameter estimations. From the preliminary investigation, rolling terrains had the highest share of severe CMV head-on crashes (62% and 71% for multilane and two-lane roadways, respectively). The presence of centerline rumble strips could reduce severe crash outcomes along multilane and two-lane facilities. The GOP model identified various significant predictors of minor and severe injuries from CMV head-on crashes. Occupants wearing seatbelt were 39.3% less likely to sustain severe head-on crash injuries. From the roadway characteristics, presence of median cable and concrete barriers could significantly reduce the probability of severe head-on crash injuries, with median cables being more effective. With regard to the driver characteristics, drug impairment and speeding increased the risk of sustaining fatal/serious injuries by 39.5% and 26.4%, respectively. Necessary safety recommendations are proposed to reduce the severity of CMV head-on-related collisions. One example is installing median cable barriers along roadway stretches with a history of head-on CMV-related crashes.

Fail to Yield? An Analysis of Ambulance Crashes in Taiwan

Introduction—Medical emergency vehicles help patients get to the hospital quickly. However, there were more and more ambulance crashes on the road in Taiwan during the last decade. This study investigated the characteristics of medical emergency vehicle crashes in Taiwan from January 2003 to December 2016. Methods—The ordered logit (OL) model, multinominal logit (MNL) model, and partial proportional odds (PPO) model were applied to investigate the relationship between the severity of ambulance crash injuries and its risk factors. Results—We found the various factors have different effects on the overall severity of ambulance crashes, such as ambulance drivers’ characteristics and road and weather conditions. When another car was involved in ambulance crashes, there was a disproportionate effect on the different overall severity, as found by the PPO model. Conclusions—The results showed that male ambulance drivers and car drivers who failed to yield to an ambulance had a higher risk of severe injury from ambulance crashes. Ambulance crashes are an emerging issue and need further policies and public education regarding Taiwan’s ambulance transportation safety.

Evaluating the Effects of Holidays on Road Crash Injuries in the United Kingdom

Background: Research suggests that drivers tend to engage in risk-taking behaviours on public holidays. Studies that examined the association between holidays (or other special days) and fatal injuries are inconsistent. This study used UK STATS19 data to investigate the associations of nine public holidays on road crash casualties. Methods: This retrospective study assessed UK STATS19 crash data for 1990–2017. All casualties from two vehicle crashes were initially considered; subsequently, casualties with missing data were excluded. Multiple logistic regression was estimated to explore the associations of potential risk factors with the likelihood of killed or seriously injured (KSI) casualties and to calculate adjusted odds ratios (AORs). Results: In total, 3,751,998 casualties from traffic accidents in the United Kingdom during 1990–2017 were included in the final data set; among these, 410,299 (10.9%) were KSI casualties, and 3,341,699 (89.1%) were slight injuries. Crashes on public holidays were 16% (AOR = 1.16; 95% confidence interval [CI] = 1.13–1.19) more likely to involve KSI casualties than were crashes on non-holidays. With other factors controlled for, crashes during the Queen’s 2002 Golden Jubilee and on New Year’s Day were 48% (AOR = 1.48; 95% CI = 1.06–2.07) and 36% (AOR = 1.36; 1.26–1.48) more likely to lead to KSIs, respectively. Conclusions: The proportion of crashes resulting in KSI casualties on public holidays was higher than that on non-holidays. Furthermore, crashes during the Queen’s 2002 Golden Jubilee had the highest risk of KSI casualties followed by New Year’s Day.