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

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          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 north-eastern and south-eastern 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 high-risk streets and neighbourhoods of the city that should lead to decreasing numbers of PPRTIs.

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          Most cited references31

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          Socioeconomic status and injury mortality: individual and neighbourhood determinants.

          This study examined both individual and neighbourhood correlates of injury mortality to better understand the contribution of socioeconomic status to cause specific injury mortality. Of particular interest was whether neighbourhood effects remained after adjusting for individual demographic characteristics and socioeconomic status. Census tract data (measuring small area socioeconomic status, racial concentration, residential stability, urbanisation, and family structure) was merged with the National Health Interview Survey (NHIS) and a file that links the respondents to subsequent follow up of vital status and cause of death data. Cox proportional hazards models were specified to determine individual and neighbourhood effects on homicide, suicide, motor vehicle deaths, and other external causes. Variances are adjusted for the clustered sample design of the NHIS. United States, 1987-1994, with follow up to the end of 1995. From a sample of 472 364 persons ages 18-64, there were 1195 injury related deaths over the follow up period. Individual level effects were generally robust to the inclusion of neighbourhood level variables in the models. Neighbourhood characteristics had independent effects on the outcome even after adjustment for individual variability. For example, there was approximately a twofold increased risk of homicide associated with living in a neighborhood characterised by low socioeconomic status, after adjusting for individual demographic and socioeconomic characteristics. Social inequalities in injury mortality exist for both persons and places. Policies or interventions aimed at preventing or controlling injuries should take into account not only the socioeconomic characteristics of people but also of the places in which they live.
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            • Record: found
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            Exploring spatial autocorrelation of traffic crashes based on severity

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              • Article: not found

              The role of built environment on pedestrian crash frequency

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                Author and article information

                Contributors
                KianiB@mums.ac.ir
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                19 May 2020
                19 May 2020
                2020
                : 20
                : 722
                Affiliations
                [1 ]GRID grid.411583.a, ISNI 0000 0001 2198 6209, Social Determinants of Health Research Centre, , Mashhad University of Medical Sciences, ; Mashhad, Iran
                [2 ]GRID grid.411583.a, ISNI 0000 0001 2198 6209, Department of Medical Informatics, Faculty of Medicine, , Mashhad University of Medical Sciences, ; Mashhad, Iran
                [3 ]GRID grid.3575.4, ISNI 0000000121633745, 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
                [4 ]GRID grid.1001.0, ISNI 0000 0001 2180 7477, 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
                [5 ]GRID grid.411583.a, ISNI 0000 0001 2198 6209, Center for Accident and Emergency Medicine Management, , Mashhad University of Medical Sciences, ; Mashhad, Iran
                [6 ]GRID grid.411583.a, ISNI 0000 0001 2198 6209, Student Research Committee, School of Health, , Mashhad University of Medical Sciences, ; Mashhad, Iran
                Author information
                http://orcid.org/0000-0002-8816-328X
                Article
                8911
                10.1186/s12889-020-08911-2
                7236119
                32430028
                7d76706b-06bd-4458-8dc3-050b2a0959a1
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 18 December 2019
                : 13 May 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004748, Mashhad University of Medical Sciences;
                Award ID: 970733
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Public health
                spatial analysis,geographical information system,paediatric,pedestrian accident,road traffic injuries,iran,cluster analysis

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