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Articles

Multilevel analysis of injury severity of elderly motorcycle riders: The role of regional transport development

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Pages 102-106 | Received 24 Mar 2021, Accepted 07 Jan 2022, Published online: 04 Feb 2022
 

Abstract

Objective

Research specifically focusing on the elderly segment of motorcycle riders remains largely scarce, which represents a serious lack in understanding given the fast-growing trend of aging societies around the world. This article examines factors affecting the injury severity of elderly motorcycle riders in Taiwan using a multilevel model consisting of both individual and municipality levels. In particular, this study emphasized the role of municipality-level factors closely related to the municipality characteristics and policy considerations in directing local governments’ policies and implementing crash-prevention strategies and measures.

Methods

A multilevel logistic regression model was specified and estimated by using crash data of elderly motorcycle riders across 20 municipalities in Taiwan between 2012 and 2018. Principal component analysis was employed to identify the municipality-level factors.

Results

Individual-level factors such as being male, old age, no valid license, drunk driving, not wearing a helmet, turning or overtaking others, early morning and evening riding, errors in traffic signaling, and exceeding the speed limit have significant effects on injury severity. The highlighted municipality-level factor, the transport development index, demonstrates its significant effect on mitigating injury severity across municipalities.

Conclusions

Apart from considering individual factors such as driver-related, vehicle-related and road-side-related variables, this paper shed light on the role of transport development level of a municipality in analyzing the injury severity of elderly motorcycle riders. Policy implications in directing local governments’ policies and implementing crash-prevention strategies and measures are discussed and provided.

Additional information

Funding

This study was funded by Ministry of Science and Technology, Taiwan (MOST 108-2410-H-006-080-MY2).

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