Evidence map›Paper›PMID 24498051›Full record

ArticlePloS one2014

Brazilian road traffic fatalities: a spatial and environmental analysis.

Luciano de Andrade, João Ricardo Nickenig Vissoci, Clarissa Garcia Rodrigues, Karen Finato, Elias Carvalho, Ricardo Pietrobon, Eniuce Menezes de Souza, Oscar Kenji Nihei, Catherine Lynch, Maria Dalva de Barros Carvalho

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

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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

10 authors.

Luciano de AndradeDepartment of Nursing, State University of the West of Parana, Foz do Iguaçu, Parana, Brazil ; Department of Surgery, Duke University Health System, Durham, North Carolina, United States of America ; Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America.
João Ricardo Nickenig VissociDuke Global Health Institute, Duke University, Durham, North Carolina, United States of America ; Department of Medicine, Faculdade Inga, Maringa, Brazil.
Clarissa Garcia RodriguesDuke Global Health Institute, Duke University, Durham, North Carolina, United States of America ; Instituto de Cardiologia do RS - Fundação Universitaria de Cardiologia, Porto Alegre, RS, Brazil.
Karen FinatoDepartment of Nursing, State University of the West of Parana, Foz do Iguaçu, Parana, Brazil.
Elias CarvalhoDuke Global Health Institute, Duke University, Durham, North Carolina, United States of America ; Graduate Program in Informatics (PPGIA), PUC-PR, Curitiba, Parana, Brazil ; Department of Health Sciences, State University of Maringa, Maringa, Parana, Brazil.
Ricardo PietrobonDepartment of Surgery, Duke University Health System, Durham, North Carolina, United States of America.
Eniuce Menezes de SouzaDepartment of Health Sciences, State University of Maringa, Maringa, Parana, Brazil.
Oscar Kenji NiheiDepartment of Nursing, State University of the West of Parana, Foz do Iguaçu, Parana, Brazil.
Catherine LynchDepartment of Surgery, Duke University Health System, Durham, North Carolina, United States of America ; Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America.
Maria Dalva de Barros CarvalhoDepartment of Health Sciences, State University of Maringa, Maringa, Parana, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRoad traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. METHODS AND

findingsFour techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes.

conclusionsBy combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies.

Indexed as

Accidents, TrafficEnvironmentSafetyBrazilHumansPublic HealthRisk FactorsRural Population

Identifiers

PMID24498051
PMCPMC3907522

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.