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Journal Article

Citation

Falster MO, Randall DA, Lujic S, Ivers RQ, Leyland AH, Jorm LR. Accid. Anal. Prev. 2013; 54: 32-38.

Affiliation

University of Western Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia; Centre for Epidemiology & Research, NSW Ministry of Health, 73 Miller Street, North Sydney, NSW 2060, Australia. Electronic address: michael.falster@uws.edu.au.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.aap.2013.01.015

PMID

23474235

Abstract

Aboriginal people in Australia have higher rates of transport injury than non-Aboriginal people, but a greater proportion of Aboriginal people live in rural or remote areas where risk of these injuries is higher. This paper investigated the contributing effect of geography on the relationship between Aboriginality and road transport injury rates in the state of New South Wales. Linked hospital admission and mortality records for individuals for the years 2001-2007 were grouped into distinct injury events. Multilevel Poisson regression was used to examine disparities in injury rates between Aboriginal and non-Aboriginal people clustered within geographic areas of residence. Overall, Aboriginal people had higher rates of road transport injuries (IRR: 1.18, 95% CIs: 1.09-1.28). However, there was no significant difference when geographic clustering was taken into account (IRR: 1.00, 95% CIs: 0.96-1.04). This effect was further influenced by mode of transport for the injury, with Aboriginal people having higher rates of pedestrian (IRR: 1.96, 95% CIs: 1.75-2.19) and lower rates of motorcycle (IRR: 0.64, 95% CIs: 0.59-0.70) injuries in all almost all local areas, while there was no systematic pattern across geographic areas for small vehicle injuries (IRR: 1.01, 95% CIs: 0.94-1.08). Geography plays an important role in the population disparity of road transport injuries between Aboriginal and non-Aboriginal people, and has a differential impact for different types of road transport injury. Exploring how individual and geographic factors influence patterns of disparity allows for clearer targeting of future intervention strategies.


Language: en

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