Association of Hearing Health with Traffic Accidents among Heavy Vehicle Drivers

Aim: 
Excessive exposure of drivers to traffic noise and the resulting hearing loss could affect safe driving. This study aimed to investigate the hearing status of heavy vehicle drivers and its correlation with traffic accidents.
Materials and Methods: 
This cross-sectional study was conducted on 187 drivers of heavy vehicles (trucks and buses) in Tehran province during 2018. The hearing status of drivers was investigated by the audiometric test method, ISO 6189 (1983). A safety questionnaire and checklist of drivers' demographic variables were used to gather information on accident status and personal characteristics of drivers. SPSS version 24 software was used for the statistical analysis of data. The statistical tests used are Chi-square, Spearman's correlation, paired t-test, and odds ratio.
Results: 
Examining the hearing status of drivers showed that 51.5% were normal and 48.5% of drivers had hearing loss. The highest mean hearing threshold was at a frequency of 4000 Hz. The mean (standard deviation) for the right and left ears was 27.82 ± 15.92 and 18 ± 27.32 dB, respectively. The results of the analysis on drivers' hearing status and accidents showed a significant correlation between the frequency of accidents and the classification of drivers' hearing loss. Thus, a significant relationship with the correlation coefficient of 0.123 and 0.307, respectively, was obtained between the average hearing loss of drivers and having one or five accidents.
Conclusion: 
The findings of the study showed hearing loss in drivers in the left ear, especially at high frequencies. There is also a significant relationship between the number of accidents and the rate of hearing loss of drivers. Hearing loss caused by noise interferes with activities such as driving and negatively affects the safety of drivers and emphasizes the importance of preventing accidents by controlling traffic noise.



Materials and Methods: 
All data and statistics were collected and their seasonal average was calculated. Maps and variables associated with the physical properties of drainage basins were then extracted through ArcGIS. The Schuler diagram was plotted through Chemistry software for all stations and each season to assess the type and chemical quality of the river's drinking water. HEC-RAS model, HEC-GEORAS extension, and ArcGIS were employed for simulation of river flow and calculation and determination of water surface profiles and other hydraulic characteristics of flow including water depth, water flow rate, stream shear stress, and stream power.
Results: 
According to the analyses and results, the improper ecogeomorphological condition of rivers and their low self-purification capacity are directly correlated with the mean river water depth, water flow rate, slope of the river basin, and environmental differences.
Conclusions: 
Within the study area, the highest environmental instability and the least self-purification capacity were observed downstream of the sub-basin in which the mean and maximum depth of water were, respectively, 3.10 m and 8.803 m. Insignificant water flow rate (0.86 m/s on average) and slope of <4% in the area have stagnated water flow in most areas and consequently declined the content of dissolved oxygen and the quality of water. Conclusively, this sub-basin can be reported as a region with an improper ecogeomorphological condition.