Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015–2019

Abstract

Background: Paediatric, pedestrian road traffic injuries (PPRTIs) constitute a major cause of premature death in Iran. Identification of high-risk areas would be the primary step in designing policy intervention for PPRTI reduction because environmental factors play a significant role in these events. The present study aims to determine high-risk areas for PPRTIs at three different geographical scales, including the grid network, the urban neighbourhood and the street levels in Mashhad, Iran during the period 2015-2019. Methods: This cross-sectional retrospective study was based on all pedestrian accidents with motor vehicles involving children (less than 18 years of age) between March 2015 and March 2019 in the city of Mashhad, which is the second-most populous city in Iran. The Anselin Local Moran's I statistic and Getis-Ord Gi* were performed to measure spatial autocorrelation and hotspots of PPRTIs at the geographical grid network and neighbourhood level. Furthermore, a spatial buffer analysis was used to classify the streets according to their PPRTI rate. Results: A total of 7390 PPRTIs (2364 females and 4974 males) were noted during the study period. The children's mean age was 9.7 ± 5.1 years. Out of the total PPRTIs, 43% occurred on or at the sides of the streets, 25 of which labelled high-risk streets. A high-high cluster of PPRTI was discovered in the eastern part of the city, while there was a low-low such cluster in the West. Additionally, in the western part of the city, older children were more likely to become injured, while in the northeastern and southeastern parts, younger children were more often the victims. Conclusions: Spatial analysis of PPRTIs in an urban area was carried out at three different geographical scales: the grid network, the neighbourhood and the street level. The resulting documentation contributes reliable support for the implementation and prioritization of preventive strategies, such as improvement of the highrisk streets and neighbourhoods of the city that should lead to decreasing numbers of PPRTIs.

Comparing spatio‐temporal distribution of the most common human parasitic infections in Iran over two periods 2007 to 2012 and 2013 to 2018: A systematic quantitative literature review

“…is randomly distributed across the study area. 16,28 HH and LL regions are defined as the target area surrounded by areas with similar prevalence rates, while for HL and LH regions, the target area is surrounded by areas with dissimilar prevalence rates. 29 In other words, the HH and LL indicate clusters, while the HL and LH indicate outliers.…”

Mortality rates due to respiratory tract diseases in Tehran, Iran during 2008–2018: a spatiotemporal, cross-sectional study

“…The WGS_1984_UTM_Zone_39N projection system was used for projecting the GIS layers. This projection is a mathematical transformation that transforms spherical coordinates (latitude and longitude) into an XY (planar) coordinate system enabling researchers to create a map that accurately shows distances, areas or directions [49]. WGS_1984_UTM_Zone_39N is suitable for use between 54°E and 60°E, and in the northern hemisphere between the equator and 84°N, onshore and offshore.…”

Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015–2019: a data note

“…Environmental and geographical considerations of the spatial trends of people’s behavior should be taken into account. In this context, we employed a multiple scale spatial analysis and identified high-risk neighbourhoods of the city of Mashhad with particular reference to high-risk streets [ 5 ]. The mentioned analysis is briefly described in the next section.…”