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Mortality in a cohort of remote-living Aboriginal Australians and associated factors.


ABSTRACT: We aimed to describe mortality in a cohort of remote-living Aboriginal Australians using electronic record linkage.Between 2004 and 2006, 363 Aboriginal people living in remote Western Australia (WA) completed a questionnaire assessing medical history and behavioural risk factors. We obtained mortality records for the cohort from the WA Data Linkage System and compared them to data for the general population. We used Cox proportional hazards regression to identify predictors of mortality over a 9-year follow-up period.The leading causes of mortality were diabetes, renal failure, and ischaemic heart disease. Diabetes and renal failure accounted for 28% of all deaths. This differed from both the Australian population as a whole, and the general Indigenous Australian population. The presence of chronic disease did not predict mortality, nor did behaviours such as smoking. Only age, male sex, poor mobility, and cognitive impairment were risk factors.To reduce premature mortality, public health practitioners should prioritise the prevention and treatment of diabetes and renal disease in Aboriginal people in remote WA. This will require a sustained and holistic approach.

SUBMITTER: Hyde Z 

PROVIDER: S-EPMC5886486 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Mortality in a cohort of remote-living Aboriginal Australians and associated factors.

Hyde Zoë Z   Smith Kate K   Flicker Leon L   Atkinson David D   Almeida Osvaldo P OP   Lautenschlager Nicola T NT   Dwyer Anna A   LoGiudice Dina D  

PloS one 20180405 4


<h4>Objectives</h4>We aimed to describe mortality in a cohort of remote-living Aboriginal Australians using electronic record linkage.<h4>Methods</h4>Between 2004 and 2006, 363 Aboriginal people living in remote Western Australia (WA) completed a questionnaire assessing medical history and behavioural risk factors. We obtained mortality records for the cohort from the WA Data Linkage System and compared them to data for the general population. We used Cox proportional hazards regression to ident  ...[more]

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