Evidence map›Paper›PMID 32430028›Full record

ArticleBMC public health2020

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

Hamidreza Shabanikiya, Soheil Hashtarkhani, Robert Bergquist, Nasser Bagheri, Reza VafaeiNejad, Malihe Amiri-Gholanlou, Toktam Akbari, Behzad Kiani

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. A decision support system for prioritised COVID-19 two-dosage vaccination allocation and distribution.Transportation research. Part E, Logistics and transportation review · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hamidreza ShabanikiyaSocial Determinants of Health Research Centre, Mashhad University of Medical Sciences, Mashhad, Iran.
Soheil HashtarkhaniDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Robert BergquistIngerod, 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 BagheriVisualization 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 VafaeiNejadCenter for Accident and Emergency Medicine Management, Mashhad University of Medical Sciences, Mashhad, Iran.
Malihe Amiri-GholanlouStudent Research Committee, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Toktam AkbariStudent Research Committee, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Behzad KianiDepartment of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. KianiB@mums.ac.ir.ORCID http://orcid.org/0000-0002-8816-328X

Funding

Mashhad University of Medical Sciences 970733
6 · The paper itself

Abstract

backgroundPaediatric, 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.

methodsThis 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.

resultsA 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.

conclusionsSpatial 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.

Indexed as

Accidents, TrafficAdolescentChildChild, PreschoolCross-Sectional StudiesFemaleGeographyHumansIranMalePedestriansResidence CharacteristicsRetrospective StudiesSpatial AnalysisWounds and InjuriesCluster analysisGeographical information systemIranPaediatricPedestrian accidentRoad traffic injuriesSpatial analysis

Identifiers

PMID32430028
PMCPMC7236119

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.