Seatbelt Use and Related Factors Among Drivers Involved in Road Crashes in Southeast Iran

The prevalence of seat belt use among drivers and passengers: a systematic review and meta-analysis

BACKGROUND

Seat belts might save people's lives in car accidents by preventing severe collision damage and keeping passengers safe from critical injuries. This meta-analysis was performed to assess the prevalence of seat belt use among drivers and passengers.

METHODS

The databases of PubMed, Web of Science (WOS), and Google Scholar were searched from the beginning of 2000 to late December 2020 to identify studies that investigated the prevalence of seat belt use among drivers and passengers. The pooled prevalence was calculated using a random-effects model. The STATA-v14 software was used to perform data analysis.

RESULTS

Sixty-eight studies that met the inclusion criteria and were suitable for this meta-analysis were identified. The pooled prevalence of seat belt use was 43.94% (95% CI: 42.23-45.73) among drivers, 38.47% (95% CI: 34.89-42.42) among front-seat passengers, and 15.32% (95% CI: 12.33-19.03) among rear-seat passengers. The lowest seat belt use among drivers and passengers was observed in Asia, the Middle East, and Africa, while the highest use was reported in Europe and America. Moreover, the prevalence of seat belt use was higher among women drivers [51.47% (95% CI: 48.62-54.48)] than men drivers [38.27% (95% CI: 34.98-41.87)] (P < 0.001). Furthermore, the highest prevalence of seat belt use was seen among drivers (68.9%) and front-seat passengers (50.5%) of sports utility vehicles (SUVs); in contrast, the lowest prevalence was observed among drivers and passengers of public vehicles such as buses, minibuses, and taxis.

CONCLUSIONS

In general, the prevalence of seat belt use was not high among drivers and was even lower among passengers. Moreover, drivers and passengers in Asia, the Middle East, and Africa had the lowest prevalence of seat belt usage. Additionally, drivers and passengers of public transportation (buses, minibuses, and taxis) had a lower rate of seat belt use, especially among men. Therefore, effective interventional programs to improve seat belt use should be designed and implemented, particularly among these at-risk populations in Asia, the Middle East, and Africa.

A Hybrid of Random Forests and Generalized Path Analysis: A Causal Modeling of Crashes in 52,524 Suburban Areas

BACKGROUND

Determining suburban area crashes' risk factors may allow for early and operative safety measures to find the main risk factors and moderating effects of crashes. Therefore, this paper has focused on a causal modeling framework.

STUDY DESIGN

A cross-sectional study.

METHODS

In this study, 52524 suburban crashes were investigated from 2015 to 2016. The hybrid-random-forest-generalized-path-analysis technique (HRF-gPath) was used to extract the main variables and identify mediators and moderators.

RESULTS

This study analyzed 42 explanatory variables using a RF model, and it was found that collision type, distinct, driver misconduct, speed, license, prior cause, plaque description, vehicle maneuver, vehicle type, lighting, passenger presence, seatbelt use, and land use were significant factors. Further analysis using g-Path demonstrated the mediating and predicting roles of collision type, vehicle type, seatbelt use, and driver misconduct. The modified model fitted the data well, with statistical significance ( χ230 =81.29, P<0.001) and high values for comparative-fit-index and Tucker-Lewis-index exceeding 0.9, as well as a low root-mean-square-error-of-approximation of 0.031 (90% confidence interval: 0.030-0.032).

CONCLUSION

The results of our study identified several significant variables, including collision type, vehicle type, seatbelt use, and driver misconduct, which played mediating and predicting roles. These findings provide valuable insights into the complex factors that contribute to collisions via a theoretical framework and can inform efforts to reduce their occurrence in the future.

Use of seat belts among public transport drivers in Tacna, Peru: Prevalence and risk factors

INTRODUCTION

There are individuals who still refuse to wear seat belts, despite its effectiveness in reducing morbidity and mortality in road traffic accidents. We aimed to determine the prevalence and risk factors according to the use of seat belts among public transport drivers in Tacna, Peru.

METHODOLOGY

This analytical transversal study was carried out among public transport drivers (buses and taxis) in a Peruvian city. Questionnaires were used to evaluate the general and occupational characteristics and the use of seat belts (observed). Descriptive statistics and risk factors were obtained, these latter through generalized linear models.

RESULTS

Of the 460 drivers, 77% used their seat belts, with a difference in use depending on the type of public transport (p<0.001). In the multivariate model, the risk of not using the belt was associated with the following: older age (p<0.001), having complete studies (p<0.001), a higher level/category of driving license (3 categories had p<0.001), having a higher number of previous road traffic accidents (p = 0.011), and received medical attention in that accident (p<0.001), those who reported using a cell phone while driving (p = 0.005), if the co-driver's belt had 3 anchorage points (p<0.001), and working for > 5 hours that day (p = 0.002). However, male drivers and those who had their belt with 3 anchorage points had greater use (both p<0.001).

CONCLUSIONS

One in five drivers did not use a seat belt, and important characteristics of those who did not comply with this traffic law were evaluated to generate control and intervention measures.

Latent Class Model with Heterogeneous Decision Rule for Identification of Factors to the Choice of Drivers’ Seat Belt Use

The choice of not buckling a seat belt has resulted in a high number of deaths worldwide. Although extensive studies have been done to identify factors of seat belt use, most of those studies have ignored the presence of heterogeneity across vehicle occupants. Not accounting for heterogeneity might result in a bias in model outputs. One of the main approaches to capture random heterogeneity is the employment of the latent class (LC) model by means of a discrete distribution. In a standard LC model, the heterogeneity across observations is considered while assuming the homogeneous utility maximization for decision rules. However, that notion ignores the heterogeneity in the decision rule across individual drivers. In other words, while some drivers make a choice of buckling up with some characteristics, others might ignore those factors while making a choice. Those differences could be accommodated for by allowing class allocation to vary based on various socio-economic characteristics and by constraining some of those rules at zeroes across some of the classes. Thus, in this study, in addition to accounting for heterogeneity across individual drivers, we accounted for heterogeneity in the decision rule by varying the parameters for class allocation. Our results showed that the assignment of various observations to classes is a function of factors such as vehicle type, roadway classification, and vehicle license registration. Additionally, the results showed that a minor consideration of the heterogeneous decision rule resulted in a minor gain in model fits, as well as changes in significance and magnitude of the parameter estimates. All of this was despite the challenges of fully identifying exact attributes for class allocation due to the inclusion of high number of attributes. The findings of this study have important implications for the use of an LC model to account for not only the taste heterogeneity but also heterogeneity across the decision rule to enhance model fit and to expand our understanding about the unbiased point estimates of parameters.

The relationship between driver and passenger's seatbelt use: a bivariate probit analysis

Vehicle seatbelt has been shown to have a beneficial impact on occupants. However, some occupants do not use the seatbelt when inside a moving vehicle. Despite the numerous investigation on the risk factors associated with seatbelt use by occupants, little is known about the relationship between driver and passenger seatbelt use. This gap is analyzed with road side observational survey data on driver and front-right seat passenger's seatbelt use behaviour using bivariate probit model. The use of the bivariate probit model is based on the premise that the front-right passenger's seatbelt use is endogenously related to that of the driver. Out of the 5,433 vehicles observed, the prevalence rate of driver and front-right passengers' seatbelt use were 81% and 33%, respectively. In addition, there is a positive relationship between driver and passenger's seatbelt use with correlation coefficient of 0.53. Thus, the unobserved factors that influence the probability of a driver seatbelt use also influence their front-right passenger's seatbelt use propensity.