Analytic Methods in Accident Research, volume 36, pages 100249
Evaluating gender differences in injury severities of non-helmet wearing motorcyclists: Accommodating temporal shifts and unobserved heterogeneity
Chenzhu Wang
1
,
Muhammad Ijaz
2
,
Fei Chen
1
,
Yu Zhang
3
,
Jianding Cheng
1
,
Muhammad Zahid
4
Publication type: Journal Article
Publication date: 2022-12-01
scimago Q1
SJR: 5.020
CiteScore: 22.1
Impact factor: 12.5
ISSN: 22136657, 22136665
Safety Research
Transportation
Abstract
• Differences in factors contributing to injury severity in male and female non-helmet wearing motorcyclist crashes were investigated over a three-year period. • Statistically significant temporal instability and non-transferability of contributors determining male and female non-helmet wearing motorcyclist crashes were revealed. • Out-of-sample prediction was conducted to further examine the temporal instability and non-transferability. With rapid growth in motorcycle use and relatively low helmet-wearing usage rates, injuries and fatalities resulting from motorcycle crashes in Pakistan are a critical concern. To investigate possible temporal instability and differences in the factors that determine resulting injury severities between male and female non-helmet wearing motorcyclists, this study estimated male and female injury severity models using a random parameter logit approach with heterogeneity in means and variances. Motorcycle crash data between 2017 and 2019 from Rawalpindi, Pakistan, were used for the model estimation. With four possible crash injury severity outcomes (injury, minor injury, severe injury, and fatal injury), a wide variety of explanatory variables were considered, including the characteristics of riders, vehicles, roadways, environments, crashes, and temporal considerations. Temporal shifts in the effects of explanatory variables were confirmed using a series of likelihood ratio tests. While the effects of several explanatory variables are relatively temporally stable, those of most variables vary considerably across the years. In addition, out-of-sample simulations underscore the temporal shifts from year to year and the differences between male and female motorcyclist-injury severity. The findings suggest that factors such as effective enforcement countermeasures and relevant educational campaigns can be implemented to reduce injury severity. The statistically significant differences between male and female non-helmeted injury severity models underscore the importance of policies that separately target male and female motorcycle rider safety.
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