Linked Life Data

18032087

Source:http://linkedlifedata.com/resource/pubmed/id/18032087

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2008-4-3
pubmed:abstractText
Data on road traffic fatalities, serious casualties and slight casualties in each local authority district England and Wales were obtained for 1995-2000. District-level data were assembled for a large number of potential explanatory variables relating to population numbers and characteristics, traffic exposure, road length, curvature and junction density, land use, elevation and hilliness, and climate. Multilevel negative binomial regression models were used to identify combinations of risk factors that predicted variations in mortality and morbidity. Statistically significant explanatory variables were the expected number of casualties derived from the size and age structure of the resident population, road length and traffic counts in the district, the percentage of roads classed as minor, average cars per capita, material deprivation, the percentage of roads through urban areas and the average curvature of roads. This study demonstrates that a geographical approach to road traffic crash analysis can identify contextual associations that conventional studies of individual road sections would miss.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
T
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1353-8292
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
519-35
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Geographical variations in mortality and morbidity from road traffic accidents in England and Wales.
pubmed:affiliation
School of Environmental Sciences, University of East Anglia, Norwich, Norfolk NR4 7TJ, UK. a.p.jones@uea.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't