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Road environment characteristics and fatal crash injury during the rush hour period in the U.S.: Model testing and nested analytical study
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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 - 2017) data from the Fatality Analysis Reporting System. We limited the data to crashes during the rush hour period (6–9 am; 3– 7 pm). The outcome variable was the counts of fatal crashes per county. The predictor variables were road design (intersection, driveway, ramp, work-zone), 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.
Title: Road environment characteristics and fatal crash injury during the rush hour period in the U.S.: Model testing and nested analytical study
Description:
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 - 2017) data from the Fatality Analysis Reporting System.
We limited the data to crashes during the rush hour period (6–9 am; 3– 7 pm).
The outcome variable was the counts of fatal crashes per county.
The predictor variables were road design (intersection, driveway, ramp, work-zone), 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.
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