Unobserved heterogeneity and the effects of driver nationality on crash injury severities in Saudi Arabia

Alogaili, Asim; Mannering, Fred

doi:10.1016/j.aap.2020.105618

Cited by 47 publications

(13 citation statements)

References 27 publications

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“…Ref. [23] revealed that unfamiliar drivers from diverse cultural backgrounds had considerably different injury-severity predictions than their Saudi counterparts. Non-Saudi drivers, for example, are more prone to be involved in fatal singlevehicle crashes in Riyadh, Saudi Arabia.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the Factors Affecting Urban Vehicle-to-Vehicle Crash Severity with Focus on Drivers' Route Familiarity

Saheli¹

2022

CRPASE

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Human factors are usually of paramount importance when it comes to traffic crashes. Drivers' route familiarity or unfamiliarity is a critical human-related factor that has less been considered in the literature. This factor can lead to inattention, distraction, and dangerous behaviors due to familiar drivers' over-confidence or unfamiliar drivers' insufficient knowledge of road geometry and environment. The main objective of this study is to discover the factors affecting the severity of vehicle-to-vehicle crashes in Rasht city (in northern Iran) involving unfamiliar and familiar drivers using a logistic regression model. The results indicate the significant effect of human factors such as driver's familiarity and age, collision type, angle and reason, temporal factors (season and time of day), vehicles involved in the crash, and environmental conditions on the injury severity of vehicle-tovehicle crashes in urban roads. The results of this study can be used by policymakers and implementers to take appropriate measures to reduce the severity of vehicle-to-vehicle crashes in urban areas.

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Section: Literature Reviewmentioning

confidence: 99%

Understanding the Factors Affecting Urban Vehicle-to-Vehicle Crash Severity with Focus on Drivers' Route Familiarity

Saheli¹

2022

CRPASE

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“…Significant heterogeneity among studies was assessed using Cochrane's Q-test and chi-square (I 2 ) (35). A chi-square higher than 50% represents statistically significant heterogeneity (36). According to the analysis, I 2 percentage was higher than 50%, so random effect model (REM) was applied (37).…”

Section: Meta-analysis and Statistical Analysismentioning

confidence: 99%

Global evaluation of potentially harmful elements (PHEs) in potato and carrot irrigated by wastewater: A systematic review, meta-analysis, and health risk assessment

Karimi

Yazdanbakhsh

Atamaleki

et al. 2021

Environ Health Eng Manag

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Background: We aimed to conduct a meta-analysis on the concentration of potentially harmful elements (PHEs) in carrots and potatoes irrigated by wastewater and estimate non-carcinogenic health risks among adult and children consumers. Methods: The health risk of PHEs concentration, including Pb, Cd, total Cr, Ni, Zn, Cu, and Fe, in the edible parts of carrot and potato irrigated by wastewater was investigated by a meta-analysis using a random-effects model (REM). Accordingly, the related articles were screened from international databases such as Scopus, Medline, and Embase. Results: The meta-analysis of 32 papers (38 studies) revealed that the rank order of the most accumulated PHEs in potato was Fe (86.54 mg/kg wet weight) > Zn (30.9 mg/kg wet weight) > Cu (13.7 mg/kg wet weight) > Ni (8.42 mg/kg wet weight) > Pb (5.56 mg/kg wet weight) > Cr (3.45 mg/kg wet weight) > Cd (0.58 mg/kg wet weight). This ranking for carrot was Fe (43.36 mg/kg wet weight) > Zn (36.29 mg/kg wet weight) > Ni (13.49 mg/kg wet weight) > Cu (9.79 mg/kg wet weight) > Pb (1.84 mg/kg wet weight) > Cr (1.05 mg/kg wet weight) > Cd (0.28 mg/kg wet weight). Total hazard quotient (THQ) of PHEs was higher than 1 for potato and carrot; its rank order for potato and carrot was Cu > Pb > Cd > Ni > Fe > Zn > Cr and Cd > Pb > Cu > Ni > Fe > Zn > Cr, respectively. The Cd, Pb, and Cu had also a considerable role for consumer health risk. Conclusion: According to the results, continuous monitor and control of wastewater treatment plants are necessary.

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“…Previous research has classified the severity of crashes either as a binary measure (fatality or injury) [ 11 ], tertiary measures [ 12 ] or categorized into 4 levels such as fatality, serious injury, moderate injury, and mild injury [ 13 ]. Irrespective of the categorization, most studies use measures broadly grouped into environmental, personal, and vehicular characteristics when examining the severity of crashes [ 14 ]. Environmental factors include weather conditions, visibility, illumination, time of the day, road characteristics, or road geometry [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Severity of vehicle-to-vehicle accidents in the UAE: An exploratory analysis using machine learning algorithms

Maghelal,

Ali,

Azar

et al. 2023

Heliyon

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Unobserved heterogeneity and the effects of driver nationality on crash injury severities in Saudi Arabia

Cited by 47 publications

References 27 publications

Understanding the Factors Affecting Urban Vehicle-to-Vehicle Crash Severity with Focus on Drivers' Route Familiarity

Understanding the Factors Affecting Urban Vehicle-to-Vehicle Crash Severity with Focus on Drivers' Route Familiarity

Global evaluation of potentially harmful elements (PHEs) in potato and carrot irrigated by wastewater: A systematic review, meta-analysis, and health risk assessment

Severity of vehicle-to-vehicle accidents in the UAE: An exploratory analysis using machine learning algorithms

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