Spatial analysis of mortality rate of pedestrian accidents in Iran during 2012–2013

Abstract

Objectives: Considering the high mortality rate of pedestrians in traffic accidents in Iran, the present study aimed to determine the high-risk and low-risk areas of accidents resulting in pedestrian deaths and the spatial analysis of their mortality rates.

Methods: This cross-sectional study included 4,371 deceased pedestrians reported by the Legal Medicine Organization in Iran from March 2012 to March 2013. For spatial analysis, the collected data were entered into ArcGIS software version 10.2 and a spatial map of the mortality rate was drawn according to the distribution of data in the provinces. Using this software, high-risk and low-risk areas were identified by calculating the spatial autocorrelation of the data. The Moran’s index of road accident patterns was surveyed and high-risk and low-risk points were identified using the local Getis index.

Results: The age-standardized incidence rate was 6.8 per 100,000. After analyzing the data using ArcGIS software, the local Moran’s index showed a cluster pattern with a high mortality rate in 3 provinces of Mazandaran, Gilan, and Qazvin. In identifying high-risk and low-risk points, the local Getis index showed 3 hot spots with a confidence interval of 99% in Qom, Qazvin, and Mazandaran and 5 hot spots with a 95% confidence interval in Markazi, Tehran, Zanjan, Gilan, and Golestan provinces.

Conclusions: According to the cluster pattern of accidents in the 3 provinces and the presence of hot spots in 9 provinces, it is necessary to identify factors that increase the risk of death in the study provinces in order to reduce the mortality rate among pedestrians due to traffic accidents. Therefore, to reduce the pedestrian mortality rate, especially in high-risk provinces, some studies need to be conducted to determine the risk factors in pedestrian mortality.

Keywords:

• Spatial analysis
• pedestrians
• road accidents
• Iran

Notes

1 The quintiles were used to categorize the incidence rate. A quintile is a statistical value of a data set that represents 20% of a given population; therefore, the first quintile represents the lowest fifth of the data (1–20%); the second quintile represents the second fifth (21–40%), and so on.

2 Values lower than the upper limit are included in the range.