Trends of Fatal Road Traffic Injuries in Iran (2004–2011)

Abstract

Road traffic injuries (RTIs) leading to death need the most essential concern for low, middle and high income societies. Mortality rate due to traffic injuries is considerable in Iran particularly during the last decade along with the industrialization process. The present study considered the trend of traffic injuries leading to death in Iran for a period of seven-years which started from March 2004 to March 2011. The formal merged Iranian database provided by the Ministry of Roads, the Legal Medicine Organization, the Traffic Police (NAJA), and the Ministry of Health covering 146, 269 deaths due to traffic injuries between 2004 and 2011 was analyzed. The time series method was carried out to determine the death trends of RTIs in the whole country. The Poisson regression model was used to estimate the changes in the frequency of events over time adjusting for associated known risk factors. The SARIMA (0, 1, 1)×(0, 1, 1)12 model was used for fitting to the time series of death rate. The death rate due to RTIs in Iran has statistically declined from 38 in 2004 to 31 per 100,000 populations in 2011. Based on the number of vehicles, the mortality rate has also declined from 38 to 12 cases per 10,000 vehicles from 2004 to 2011 respectively. However, the mortality rate was increased from 51 to 65 cases per 1000 accidents from 2004 to March 2011 respectively. Despite minor variations in mortality trends of RTIs in Iran according to different criteria, an annual average of 21,000 deaths is considerable and needs serious attentions. Modification of traffic laws, enhancement of police controls, improving transport infrastructure, holding education courses for drivers and providing optimal healthcare services are recommended.

Time Series Analysis of Mortalities Resulting from Car Accidents in the Injured Individuals Hospitalized in Shiraz Shahid Rajaee Hospital During 2010 - 2016

“…Accordingly, the mortalities caused by car accidents followed an increasing trend. The auto regressive integrated moving average (ARIMA) model with AR = 4, MA = 1, and Akaike information criterion statistics (AIC) = 125 was used for the prediction of mortalities caused by car accidents (1,1,4).…”

“…Accordingly, mortality followed an ascending trend in both males and females. In order to predict the mortality resulting from car accidents, the ARIMA model was used which showed AR = 1, MA = 11, and AIC = 236 for males (1,1,11), and AR = 6, MA = 1, and AIC = 284 for females (1, 1, 6).…”

“…Accordingly, mortality had a relatively fixed trend in the individuals below 30 years of age, an increasing trend in the individuals between 30 and 45 years old, and a steeper slope in those above 45 years of age. In order to predict the age groups, the ARIMA model was used, which showed AR = 2, MA = 1, and AIC = 278 for below-30-year-old individuals (1, 1, 2), AR = 10, MA = 0, and AIC = 380 for those between 30 and 45 years old (0, 1, 10), and AR = 5, MA = 2, and AIC = 260 for those above 45 years of age (2,1,5).…”

“…At least one vehicle is involved in an accident (1). Nowadays road traffic injuries (RTIs) are a major public health challenge (2).…”

Health impacts of the M74 urban motorway extension: a mixed-method natural experimental study

“…Taking both observations into account, we therefore elected to apply the time series models to the accident count data only. [107][108][109] An evaluation conducted for Transport Scotland 16 weeks after the opening of the new motorway identified small decreases in traffic for some local streets, increases in traffic on the main feeder roads for the new motorway and 'satisfactory' traffic flow on the new motorway itself. 110 Results Table 28 presents the results from the ITS models for (1) all accidents and (2) serious and fatal accidents only.…”