A home-based approach to understanding seatbelt use in single-occupant vehicles in Tennessee: Application of a latent class binary logit model

Afghari, Amir Pooyan, Hezaveh, Amin Mohamadi, , & Cherry, Christopher (2020) A home-based approach to understanding seatbelt use in single-occupant vehicles in Tennessee: Application of a latent class binary logit model. Accident Analysis and Prevention, 146, Article number: 105743.

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Although the enforcement of seatbelt use is considered to be an effective strategy in reducing road injuries and fatalities, lack of seatbelt use still accounts for a substantial proportion of fatal crashes in Tennessee, United States. This problem has raised the need to better understand factors influencing seatbelt use. These factors may arise from spatial/temporal characteristics of a driving location, type of vehicle, demographic and socioeconomic attributes of the vehicle occupants, driver behaviours, attitudes, and social norms. However, the above factors may not have the same effects on seatbelt use across different individuals. In addition, the behavioural factors are usually difficult to measure and may not always be readily available. Meanwhile, residential locations of vehicle occupants have been shown to be associated with their behavioural patterns and thus may serve as a proxy for behavioural factors. However, the suitability of geographic and residential locations of vehicle occupants to understand the seatbelt use behaviour is not known to date.

This study aims to fill the above gaps by incorporating the residential location characteristics of vehicle occupants in addition to their demographics and crash characteristics into their seatbelt use while accounting for the varying effects of these factors on individual seatbelt use choices. To achieve this goal, empirical data are collected for vehicular crashes in Tennessee, United States, and the home addresses of vehicle occupants at the time of the crash are geocoded and linked with the census tract information. The resulting data is then used as explanatory variables in a latent class binary logit model to investigate the determinants of vehicle occupants’ seatbelt use at the time of the crash. The latent class specification is employed to capture the unobserved heterogeneity in data. Results show that Tennessean drivers belong to two general categories—conformist and eccentric—with gender, vehicle type, and income per capita determining the likelihood of these categories. Overall, male drivers, younger drivers, and drivers who have consumed drugs are less likely to wear a seatbelt, whereas drivers who come from areas with higher population density, travel time, and income per capita are more likely to wear a seatbelt. In addition, driving during the day and in rainy weather are associated with an increased likelihood of seatbelt use. The findings of this study will help developing effective policies to increase seatbelt use rate and improve safety.

Impact and interest:

16 citations in Scopus
10 citations in Web of Science®
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ID Code: 209112
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Haque, Md Mazharulorcid.org/0000-0003-1016-110X
Measurements or Duration: 8 pages
Keywords: Driving behaviour, Latent class model, Location-based characteristics, Seatbelt use, Transport safety
DOI: 10.1016/j.aap.2020.105743
ISSN: 0001-4575
Pure ID: 76392812
Divisions: Current > Research Centres > Centre for Future Mobility/CARRSQ
Past > QUT Faculties & Divisions > Science & Engineering Faculty
Current > Schools > School of Civil & Environmental Engineering
Current > QUT Faculties and Divisions > Faculty of Health
Copyright Owner: 2020 The Author(s)
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Deposited On: 22 Mar 2021 04:37
Last Modified: 12 May 2024 20:43