Road environment characteristics and fatal crash injury during the rush hour period in the U.S.: Model testing and nested analytical study

Abstract

Background: A substantial proportion of crash injuries occur during the rush hour period. This study aims to assess the relationship between county level road environmental characteristics and fatal road crash counts during the rush hour period. Method: We merged eight-year (2010 to 2017) data from the Fatality Analysis Reporting System. We limited the data to crashes during the rush hour period (6 to 9 am; 3 to 7 pm). The outcome variable was the counts of fatal crashes per county. The predictor variables were road design (intersection, driveway, ramp, workzone), road type (interstate, highways, roads/streets), and inclement weather factors (rain, fog, snow). A nested spatial negative binomial regression model was used to estimate the rate ratio of fatal crash injury during the rush hour period, with estimated county population sizes used as the offset variable. Small area estimates, adjusted crash fatality rates, clusters, and outliers were visualized using choropleths maps. Results: The median prevalence of rush hour related fatal crashes was 7.3 per 100,000 population. Case specific fatality rates from interstates, highways, roads, streets, intersections, rain, fog, and snow were higher than the median fatality rates. Also, the median crash fatality rates were significantly higher in rural counties as compared to urban counties. During the rush hour period, fatal crash injury rates were significantly elevated on interstates, highways, roads and streets, intersections, driveways, and work zones. Further, rain and fog were significantly associated with elevated fatal crash rates during the rush-hour period. Spatial clusters of fatal crash injuries were found in counties located in Idaho, Montana, Nevada, California, Wyoming, Utah, and across a few states in the Southeast. Conclusion: Certain built, and natural road environment factors may influence crash injury rates during the rush hour period.

Social Determinants of Health and Fatal Crashes Involving US Geriatric and Non-Geriatric Road Users

“…This observed finding may suggest the disproportionate distribution of non-geriatric road users in metropolitan urban areas and the impact of risky driving behaviors associated with young and middleaged drivers. Earlier studies have reported that non-geriatric road users are more likely to drive while under the influence of drugs and alcohol, 9,55,56 and engage in phone-related distracted driving. [57][58][59][60] These unique characteristics may account for the observed elevated fatal crash rate ratio in nongeriatric road users.…”

“…Poverty, an exemplar of economic stability, predicts substance use, injury, and adverse events from chronic diseases. 4 Similarly, rurality, an exemplar of neighborhood and built environment is associated with increased hospital closure, [5][6][7] longer emergency medical service response and hospital transit time, [8][9][10][11] , and increased deaths without resuscitation. 10 Understanding the relationship between SDoH and fatal crash counts will further highlight the importance of improving measures of SDoH.…”

Substance use and pre-hospital crash injury severity among U.S. older adults: A five-year national cross-sectional study

“…Earlier studies have reported increased speeding behavior among road users in rural areas [74] and non-use of seat belts among older adult drivers [75]. Rural areas also experience significantly prolonged response times [24,26], increased deaths at the crash scene [26], and increased proportions of crash fatalities [76][77][78]. Additionally, the impact of hospital closures in rural areas may further explain the rural-urban disparity in crash outcomes since hospital closures is directly linked with reduced availaibility of healthcare professionals and reduced access to healthcare [79][80][81][82].…”