PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-2 (2)
 

Clipboard (0)
None

Select a Filter Below

Journals
Authors
more »
Year of Publication
Document Types
1.  Adjusting for under-identification of Aboriginal and/or Torres Strait Islander births in time series produced from birth records: Using record linkage of survey data and administrative data sources 
Background
Statistical time series derived from administrative data sets form key indicators in measuring progress in addressing disadvantage in Aboriginal and Torres Strait Islander populations in Australia. However, inconsistencies in the reporting of Indigenous status can cause difficulties in producing reliable indicators. External data sources, such as survey data, provide a means of assessing the consistency of administrative data and may be used to adjust statistics based on administrative data sources.
Methods
We used record linkage between a large-scale survey (the Western Australian Aboriginal Child Health Survey), and two administrative data sources (the Western Australia (WA) Register of Births and the WA Midwives’ Notification System) to compare the degree of consistency in determining Indigenous status of children between the two sources. We then used a logistic regression model predicting probability of consistency between the two sources to estimate the probability of each record on the two administrative data sources being identified as being of Aboriginal and/or Torres Strait Islander origin in a survey. By summing these probabilities we produced model-adjusted time series of neonatal outcomes for Aboriginal and/or Torres Strait Islander births.
Results
Compared to survey data, information based only on the two administrative data sources identified substantially fewer Aboriginal and/or Torres Strait Islander births. However, these births were not randomly distributed. Births of children identified as being of Aboriginal and/or Torres Strait Islander origin in the survey only were more likely to be living in urban areas, in less disadvantaged areas, and to have only one parent who identifies as being of Aboriginal and/or Torres Strait Islander origin, particularly the father. They were also more likely to have better health and wellbeing outcomes. Applying an adjustment model based on the linked survey data increased the estimated number of Aboriginal and/or Torres Strait Islander births in WA by around 25%, however this increase was accompanied by lower overall proportions of low birth weight and low gestational age babies.
Conclusions
Record linkage of survey data to administrative data sets is useful to validate the quality of recording of demographic information in administrative data sources, and such information can be used to adjust for differential identification in administrative data.
doi:10.1186/1471-2288-12-90
PMCID: PMC3493324  PMID: 22747850
2.  Do places affect the probability of death in Australia? A multilevel study of area‐level disadvantage, individual‐level socioeconomic position and all‐cause mortality, 1998–2000 
Background
In Australia, studies finding an association between area‐level socioeconomic disadvantage and mortality are often based on aggregate‐ecological designs which confound area‐level and individual‐level sources of socioeconomic variation. Area‐level socioeconomic differences in mortality therefore may be an artefact of varying population compositions and not the characteristics of areas as such.
Objective
To examine the associations between area‐level disadvantage and all‐cause mortality before and after adjustment for within‐area variation in individual‐level socioeconomic position (SEP) using unlinked census and mortality‐register data in a multilevel context.
Setting, participants and design
The study covers the total Australian continent for the period 1998–2000 and is based on decedents aged 25–64 years (n = 43 257). The socioeconomic characteristics of statistical local areas (SLA, n = 1317) were measured using an index of relative socioeconomic disadvantage, and individual‐level SEP was measured by occupation.
Results
Living in a disadvantaged SLA was associated with higher all‐cause mortality after adjustment for within‐SLA variation in occupation. Death rates were highest for blue‐collar workers and lowest among white‐collar employees. Cross‐level interactions showed no convincing evidence that SLA disadvantage modified the extent of inequality in mortality between the occupation groups.
Conclusions
Multilevel analysis can be used to examine area variation in mortality using unlinked census and mortality data, therefore making it less necessary to use aggregate‐ecological designs. In Australia, area‐level and individual‐level socioeconomic factors make an independent contribution to the probability of premature mortality. Policies and interventions to improve population health and reduce mortality inequalities should focus on places as well as people.
doi:10.1136/jech.2006.046094
PMCID: PMC2465593  PMID: 17183009

Results 1-2 (2)