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


Journal

BMC public health
ISSN: 1471-2458
Titre abrégé: BMC Public Health
Pays: England
ID NLM: 100968562

Informations de publication

Date de publication:
19 May 2020
Historique:
received: 18 12 2019
accepted: 13 05 2020
entrez: 21 5 2020
pubmed: 21 5 2020
medline: 10 10 2020
Statut: epublish

Résumé

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. 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. 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 north-eastern and south-eastern parts, younger children were more often the victims. 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 high-risk streets and neighbourhoods of the city that should lead to decreasing numbers of PPRTIs.

Sections du résumé

BACKGROUND 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 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 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 north-eastern and south-eastern parts, younger children were more often the victims.
CONCLUSIONS 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 high-risk streets and neighbourhoods of the city that should lead to decreasing numbers of PPRTIs.

Identifiants

pubmed: 32430028
doi: 10.1186/s12889-020-08911-2
pii: 10.1186/s12889-020-08911-2
pmc: PMC7236119
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

722

Subventions

Organisme : Mashhad University of Medical Sciences
ID : 970733

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Auteurs

Hamidreza Shabanikiya (H)

Social Determinants of Health Research Centre, Mashhad University of Medical Sciences, Mashhad, Iran.

Soheil Hashtarkhani (S)

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

Robert Bergquist (R)

Ingerod, Brastad, Sweden (formerly with the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases, World Health Organization), Geneva, Switzerland.

Nasser Bagheri (N)

Visualization and Decision Analytics (VIDEA) lab, Centre for Mental Health Research, Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia.

Reza VafaeiNejad (R)

Center for Accident and Emergency Medicine Management, Mashhad University of Medical Sciences, Mashhad, Iran.

Malihe Amiri-Gholanlou (M)

Student Research Committee, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.

Toktam Akbari (T)

Student Research Committee, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.

Behzad Kiani (B)

Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. KianiB@mums.ac.ir.

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