Tunnel driving occupational environment and hearing loss in train drivers in China.

OBJECTIVE: Hearing loss caused by high levels of noise is a potential occupational health disorder among train drivers around the world. This study aims to investigate the relationship between tunnel driving occupational environment and hearing loss in train drivers, to provide some insights into helping reduce hearing loss among train drivers. METHODS: This study analysed cross-sectional data for 1214 train drivers who work at China Railway Guangzhou Group. Health examination was taken by physicians with professional licences, and audiometric testing was performed by health technicians in a sound-isolated room. T/R is defined as the ratio of the length of the tunnels to the length of the railway along drivers' work routes. Different multivariate models and stratified models were established for sensitivity analysis. A multivariable logistic regression model was used to estimate the ORs of hearing loss associated with tunnel driving occupational environment. RESULTS: The adjusted OR for high-frequency hearing loss in association with the highest T/R levels (30%-45%) versus the lowest T/R levels (<15%) was 3.72 (95% CI 1.43 to 9.69). The corresponding OR for speech-hearing loss was 1.75 (95% CI 0.38 to 8.06). The sensitivity analysis shows our results are suitable for various alternative models. CONCLUSIONS: This study found that there was a significant association between tunnel driving occupational environment and hearing loss. Train drivers who work in a higher T/R environment have worse hearing loss.

An investigation on fatality of drivers in vehicle-fixed object accidents on expressways in China: Using multinomial logistic regression model.

This study aims to identify the effects of characteristics of vehicle, roadway, driver, and environment on fatality of drivers in vehicle-fixed object accidents on expressways in Changsha-Zhuzhou-Xiangtan district of Hunan province in China by developing multinomial logistic regression models. For this purpose, 121 vehicle-fixed object accidents from 2011-2017 are included in the modeling process. First, descriptive statistical analysis is made to understand the main characteristics of the vehicle-fixed object crashes. Then, 19 explanatory variables are selected, and correlation analysis of each two variables is conducted to choose the variables to be concluded. Finally, five multinomial logistic regression models including different independent variables are compared, and the model with best fitting and prediction capability is chosen as the final model. The results showed that the turning direction in avoiding fixed objects raised the possibility that drivers would die. About 64% of drivers died in the accident were found being ejected out of the car, of which 50% did not use a seatbelt before the fatal accidents. Drivers are likely to die when they encounter bad weather on the expressway. Drivers with less than 10 years of driving experience are more likely to die in these accidents. Fatigue or distracted driving is also a significant factor in fatality of drivers. Findings from this research provide an insight into reducing fatality of drivers in vehicle-fixed object accidents.