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Predictors of injury mortality: findings from a large national cohort in Thailand

Yiengprugsawan, Vasoontara; Berecki-Gisolf, Janneke; Bain, Christopher; McClure, Roderick; Sleigh, Adrian; Seubsman, Sam-ang

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OBJECTIVE To present predictors of injury mortality by types of injury and by pre-existing attributes or other individual exposures identified at baseline. DESIGN 5-year prospective longitudinal study. SETTING Contemporary Thailand (2005-2010), a country undergoing epidemiological transition. PARTICIPANTS Data derived from a research cohort of 87 037 distance-learning students enrolled at Sukhothai Thammathirat Open University residing nationwide. MEASURES Cohort members completed a...[Show more]

dc.contributor.authorYiengprugsawan, Vasoontara
dc.contributor.authorBerecki-Gisolf, Janneke
dc.contributor.authorBain, Christopher
dc.contributor.authorMcClure, Roderick
dc.contributor.authorSleigh, Adrian
dc.contributor.authorSeubsman, Sam-ang
dc.date.accessioned2016-04-01T03:04:28Z
dc.date.available2016-04-01T03:04:28Z
dc.identifier.issn2044-6055
dc.identifier.urihttp://hdl.handle.net/1885/100936
dc.description.abstractOBJECTIVE To present predictors of injury mortality by types of injury and by pre-existing attributes or other individual exposures identified at baseline. DESIGN 5-year prospective longitudinal study. SETTING Contemporary Thailand (2005-2010), a country undergoing epidemiological transition. PARTICIPANTS Data derived from a research cohort of 87 037 distance-learning students enrolled at Sukhothai Thammathirat Open University residing nationwide. MEASURES Cohort members completed a comprehensive baseline mail-out questionnaire in 2005 reporting geodemographic, behavioural, health and injury data. These responses were matched with national death records using the Thai Citizen ID number. Age-sex adjusted multinomial logistic regression was used to calculate ORs linking exposure variables collected at baseline to injury deaths over the next 5 years. RESULTS Statistically significant predictors of injury mortality were being male (adjustedOR 3.87, 95% CI 2.39 to 6.26), residing in the southern areas (AOR 1.71, 95% CI 1.05 to 2.79), being a current smoker (1.56, 95% CI 1.03 to 2.37), history of drunk driving (AOR 1.49, 95% CI 1.01 to 2.20) and ever having been diagnosed for depression (AOR 1.91, 95% CI 1.00 to 3.69). Other covariates such as being young, having low social support and reporting road injury in the past year at baseline had moderately predictive AORs ranging from 1.4 to 1.6 but were not statistically significant. CONCLUSIONS We complemented national death registration with longitudinal data on individual, social and health attributes. This information is invaluable in yielding insight into certain risk traits such as being a young male, history of drunk driving and history of depression. Such information could be used to inform injury prevention policies and strategies.
dc.description.sponsorshipThis study was supported by the International Collaborative Research Grants Scheme with joint grants from the Wellcome Trust UK (GR071587MA) and the Australian National Health and Medical Research Council (268055), and as a global health grant from the NHMRC (585426).
dc.publisherBMJ Publishing Group
dc.rightsThis is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/3.0/
dc.sourceBMJ Open
dc.subjectpublic health
dc.titlePredictors of injury mortality: findings from a large national cohort in Thailand
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume4
dc.date.issued2014
local.identifier.absfor111799
local.identifier.ariespublicationU3488905xPUB2488
local.publisher.urlhttp://www.bmj.com/company/
local.type.statusPublished Version
local.contributor.affiliationYiengprugsawan, Vasoontara, College of Medicine, Biology and Environment, CMBE Research School of Population Health, Natl Centre for Epidemiology & Population Health, The Australian National University
local.contributor.affiliationBerecki-Gisolf, Janneke, Monash University, Australia
local.contributor.affiliationBain, Christopher, College of Medicine, Biology and Environment, CMBE Research School of Population Health, Natl Centre for Epidemiology & Population Health, The Australian National University
local.contributor.affiliationMcClure, Rod, Monash University, Australia
local.contributor.affiliationSeubsman, Sam-ang, College of Medicine, Biology and Environment, CMBE Research School of Population Health, Natl Centre for Epidemiology & Population Health, The Australian National University
local.contributor.affiliationSleigh, Adrian, College of Medicine, Biology and Environment, CMBE Research School of Population Health, Natl Centre for Epidemiology & Population Health, The Australian National University
dc.relationhttp://purl.org/au-research/grants/nhmrc/268055
local.identifier.essn2044-6055
local.bibliographicCitation.issue6
local.bibliographicCitation.startpagee004668
local.bibliographicCitation.lastpagee004668
local.identifier.doi10.1136/bmjopen-2013-004668
dc.date.updated2016-06-14T08:44:29Z
local.identifier.scopusID2-s2.0-84901949111
local.identifier.thomsonID000339717100023
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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