Evidence map›Paper›PMID 21685144›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2012

A regionalised strategy for improving motor vehicle-related highway driver deaths using a weighted averages method.

Tad Kim, Frederick P Rivara, David W Mozingo, Lawrence Lottenberg, Zachary B Harris, George Casella, Huazhi Liu, Lyle L Moldawer, Philip A Efron, Darwin N Ang

Abstract read
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Tad KimDepartment of Surgery, University of Florida, Gainesville, Florida 32610-0108, USA.
Frederick P Rivara
David W Mozingo
Lawrence Lottenberg
Zachary B Harris
George Casella
Huazhi Liu
Lyle L Moldawer
Philip A Efron
Darwin N Ang

Funding

Novel Mechanisms and Approaches to Treat Neonatal SepsisR01GM097531 · NIGMS · UNIVERSITY OF FLORIDA · PI LARSON, SHAWN DAVID, MOLDAWER, LYLE L · 2011 to 2018
$2.3M
NIGMS NIH HHS R01 GM097531
6 · The paper itself

Abstract

objectiveThe state of Florida has some of the most dangerous highways in the USA. In 2006, Florida averaged 1.65 fatalities per 100 million vehicle miles travelled (VMT) compared with the national average of 1.42. A study was undertaken to find a method of identifying counties that contributed to the most driver fatalities after a motor vehicle collision (MVC). By regionalising interventions unique to this subset of counties, the use of resources would have the greatest potential of improving statewide driver death.

methodsThe Florida Highway Safety Motor Vehicle database 2000-2006 was used to calculate driver VMT-weighted deaths by county. A total of 3,468,326 motor vehicle crashes were evaluated. Counties that had driver death rates higher than the state average were sorted by a weighted averages method. Multivariate regression was used to calculate the likelihood of death for various risk factors.

resultsVMT-weighted death rates identified 12 out of 67 counties that contributed up to 50% of overall driver fatalities. These counties were primarily clustered in central and south Florida. The strongest independent risk factors for driver death attributable to MVC in these high-risk counties were alcohol/drug use, rural roads, speed limit ≥45 mph, adverse weather conditions, divided highways, vehicle type, vehicle defects and roadway location.

conclusionsUsing the weighted averages method, a small subset of counties contributing to the majority of statewide driver fatalities was identified. Regionalised interventions on specific risk factors in these counties may have the greatest impact on reducing driver-related MVC fatalities.

Indexed as

Accidents, TrafficAdolescentAdultCohort StudiesFemaleFloridaHumansMaleMiddle AgedMultivariate AnalysisRetrospective StudiesRisk FactorsYoung Adult

Identifiers

PMID21685144
PMCPMC4304665

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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.