OBJECTIVES: According to Traffic Police, about 35% of deaths and more than 50% of injuries caused by traffic collision in the roads of Tehran are among drivers and car occupants. This study was conducted to determine areas with the highest number of traffic collisions and perform spatial analysis of traffic collisions involving drivers in Tehran during April 2014 to March 2017. METHODS: The present study was a cross-sectional and descriptive-analytic research. In this study, all traffic collision that driver was accounted (100 percent or less) for crash occurrence which resulted in the death of at least one person (driver, pedestrian or passenger) were included in the analyses. Geographic information system software was used to show spatial distribution of events from zoning maps. Moran index was used in the mathematical analysis in order to determine the distribution pattern of the events from and Getis-Ord G statistics was applied to analyze the hot spots (high risk points). RESULTS: A total number of 519 traffic collisions were investigated in this study. Moreover, 283 cases (54.5%) of the incidents took place in direct routes and 236 cases (45.5%) occurred at intersections. The most frequent events were in the region 4 (57 cases) and the least frequent events were reported in the region 10 (6 cases). Moran statistics show that the distribution of the studied events significantly follows the cluster pattern (p<0.001). CONCLUSIONS The northeastern and northwest margins of Tehran are the most prone areas for drivers involved with traffic collisions leading to death. Most traffic collisions leading to death take place at highways located at the entrance and exit points of Tehran and highways in regions 2 and 5.

OBJECTIVES: According to Traffic Police, about 35% of deaths and more than 50% of injuries caused by traffic collision in the roads of Tehran are among drivers and car occupants. This study was conducted to determine areas with the highest number of traffic collisions and perform spatial analysis of traffic collisions involving drivers in Tehran during April 2014 to March 2017. METHODS: The present study was a cross-sectional and descriptive-analytic research. In this study, all traffic collision that driver was accounted (100 percent or less) for crash occurrence which resulted in the death of at least one person (driver, pedestrian or passenger) were included in the analyses. Geographic information system software was used to show spatial distribution of events from zoning maps. Moran index was used in the mathematical analysis in order to determine the distribution pattern of the events from and Getis-Ord G statistics was applied to analyze the hot spots (high risk points). RESULTS: A total number of 519 traffic collisions were investigated in this study. Moreover, 283 cases (54.5%) of the incidents took place in direct routes and 236 cases (45.5%) occurred at intersections. The most frequent events were in the region 4 (57 cases) and the least frequent events were reported in the region 10 (6 cases). Moran statistics show that the distribution of the studied events significantly follows the cluster pattern (p<0.001). CONCLUSIONS The northeastern and northwest margins of Tehran are the most prone areas for drivers involved with traffic collisions leading to death. Most traffic collisions leading to death take place at highways located at the entrance and exit points of Tehran and highways in regions 2 and 5.

PURPOSETo identify and appraise the published studies assessing interventions accounting for reducing fatigue and sleepiness while driving.

METHODSThis systematic review searched the following electronic databases: Medline, Science direct, Scopus, EMBASE, PsycINFO, Transport Database, Cochrane, BIOSIS, ISI Web of Knowledge, specialist road injuries journals and the Australian Transport and Road Index database. Additional searches included websites of relevant organizations, reference lists of included studies, and issues of major injury journals published within the past 15 years. Studies were included if they investigated interventions/exposures accounting for reducing fatigue and sleepiness as the outcome, measured any potential interventions for mitigation of sleepiness and were written in English. Meta-analysis was not attempted because of the heterogeneity of the included studies.

RESULTSOf 63 studies identified, 18 met the inclusion criteria. Based on results of our review, many interventions in the world have been used to reduce drowsiness while driving such as behavioral (talking to passengers, face washing, listening to the radio, no alcohol use, limiting the driving behavior at the time of 12 p.m. - 6 a.m. etc), educational interventions and also changes in the environment (such as rumble strips, chevrons, variable message signs, etc). Meta-analysis on the effect of all these interventions was impossible due to the high heterogeneity in methodology, effect size and interventions reported in the assessed studies.

CONCLUSIONResults of present review showed various interventions in different parts of the world have been used to decrease drowsy driving. Although these interventions can be used in countries with high incidence of road traffic accidents, precise effect of each intervention is still unknown. Further studies are required for comparison of the efficiency of each intervention and localization of each intervention according to the traffic patterns of each country.

PURPOSE: Traffic accidents are one of the main causes of death and disability, causing annual deaths of 1.23 million and tens of millions injured people worldwide. Meanwhile, a significant proportion of the deaths and injuries caused by traffic accidents occur among motorcyclists. According to the world health organization's 2015 report, about 25% of deaths from traffic accidents occur in motorists. In Iran, a significant proportion of deaths and injuries result from traffic accidents among motorcyclists, especially in passages within the cities. According to traffic police, about 25% of deaths and 50% of injuries in traffic accidents of Tehran are reported among motorcyclists. Therefore, due to the importance of this issue, the spatial factors influencing the incidence of motorcycle-related accidents in Tehran were investigated using the geographic information system. METHODS: The present work was a cross-sectional and descriptive analysis study. The data necessary for the study were extracted from Tehran traffic police as well as municipality databases. Zoning maps were used to display the distribution of events. In the analytical investigation, Moran index was used to determine the distribution pattern of the events, while Getis-Ord G * statistics were applied to analyze hot spots. To investigate the role of regional and environmental factors in the frequency of traffic accidents related to motorcyclists in geographic units (Tehran 22 districts), Poisson regression and negative binomial models were used. The geographically weighted regression (GWR) model was used to analyze the relationship between environmental factors and the location of these events. Statistical analyses were performed using SPSS, STATA, ARC-GIS and GWR software. RESULTS: The southern and eastern margins of Tehran are the most vulnerable areas in terms of deaths related to traffic accidents of motorcyclists. Highways are considered the location of most traffic accidents which lead to death of motorcyclists. Getis-Ord General G * (p < 0.04) indicates that the distribution of high-risk points is statistically significant. The final model showed that in Tehran, the association of different variables including demographic characteristics, pathways network and type of land use with the number of accidents in geographic units was statistically significant. The spatial distribution of traffic accidents leading to deaths of motorcyclists in the center of Tehran varies considerably with changes in population density, length of highways, volume of traffic, and land use in different parts. CONCLUSION Most of the traffic accidents leading to deaths of motorcyclists occur in highways. Various environmental variables play a role in determining the distribution pattern of these types of events. Through proper traffic management, controlling environmental risk factors and training people the safety of motorcyclists in Tehran can be improved.
Accidents, Traffic ; prevention & control ; statistics & numerical data ; Automobile Driving ; statistics & numerical data ; Cross-Sectional Studies ; Environment ; Geographic Information Systems ; Geography ; Humans ; Incidence ; Iran ; epidemiology ; Motorcycles ; statistics & numerical data ; Regression Analysis ; Risk Factors ; Wounds and Injuries ; epidemiology ; etiology ; mortality ; prevention & control