Aim: To investigate the frequency of eye disorders in heavy vehicle drivers.
Methods: A cross-sectional type study was conducted between November 2004 and September 2006 in 200 driver and 200 non-driver persons. A complete ophthalmologic examination was performed, including visual acuity, and dilated examination of the posterior segment. We used the auto refractometer for determining refractive errors.
Results: According to eye examination results, the prevalence of the refractive error was 21.5% and 31.3% in study and control groups respectively (P<0.05). The most common type of refraction error in the study group was myopic astigmatism (8.3%) while in the control group simple myopia (12.8%). Prevalence of dyschromatopsia in the rivers, control group and total group was 2.2%, 2.8% and 2.6% respectively.
Conclusion: A considerably high number of drivers are in lack of optimal visual acuity. Refraction errors in drivers may impair the traffic security.
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http://dx.doi.org/10.3980/j.issn.2222-3959.2011.03.23 | DOI Listing |
PLoS One
January 2025
Graduate Institute of Injury Prevention and Control, College of Public Health, Taipei Medical University, Taipei City, Taiwan.
Background And Objective: Relevant research has provided valuable insights into risk factors for bicycle crashes at intersections. However, few studies have focused explicitly on three common types of bicycle crashes on road segments: overtaking, rear-end, and door crashes. This study aims to identify risk factors for overtaking, rear-end, and door crashes that occur on road segments.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Center for Environmental Research and Technology (CE-CERT), Bourns College of Engineering, University of California, 1084 Columbia Avenue, Riverside, California 92507, United States.
We assessed the real-world particulate emissions of a goods movement diesel vehicle, with an emphasis on total particle number and solid particle number emissions at different cutoff sizes. The vehicle was tested on routes in the South Coast Air Basin (SCAB) of California, representative of typical goods movement operation between the ports to warehouses and logistic centers with a mixture of urban and highway driving, as well as elevation change. We evaluated emissions during normal vehicle operation and diesel particulate filter (DPF) active regeneration events.
View Article and Find Full Text PDFArch Environ Occup Health
January 2025
School of Medicine, Vision and Eye Research Institute, Anglia Ruskin University, Cambridge, UK.
Lower back pain (LBP) is a prevalent issue affecting individuals globally. This study explored factors associated with LBP among rickshaw pullers in Dhaka, Bangladesh. A cross-sectional study was conducted with 299 bicycle rickshaw pullers in Mirpur from July to November 2019.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Civil and Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
Jharkhand is a minerally prosperous state with geogenic and industrial origins of metals. This study assesses the seasonal variation of pseudo-total metal contents (Cr, Ni, Pb, Zn, Mn, Cu, Fe, Mg, Al) and related contamination and risks in indoor dust, street dust, and soils of four major cities of Jharkhand. Across cities and seasons, Zn, Cu, and Pb were the most common pollutants.
View Article and Find Full Text PDFAccid Anal Prev
December 2024
School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China.
There has been an increase in the use of the extreme value theory (EVT) approach for conflict-based crash risk estimation and its application such as conducting the evaluation of safety countermeasures. This study proposes a cross-sectional approach for evaluating the effectiveness of a right-turn safety treatment using a conflict-based EVT approach. This approach combines traffic conflicts of different sites at the same period and develops the generalized extreme value (GEV) models.
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