3302.0.55.003 - Life Tables for Aboriginal and Torres Strait Islander Australians, 2015-2017  
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 29/11/2018   
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Chapter 2: Quality issues with Aboriginal and Torres Strait Islander Australians described the data required for producing Aboriginal and Torres Strait Islander life tables and life expectancy estimates, and quality issues associated with these data. This Chapter details the use of data linkage techniques to derive Aboriginal and Torres Strait Islander deaths identification rates. Specifically, it describes the Census Data Enhancement Indigenous Mortality Study, discusses the analyses undertaken and presents the results. To calculate estimates of life expectancy using direct methods, it is important to ensure that the classification of records as Aboriginal and Torres Strait Islander occurs in a consistent manner in both the numerator (deaths) and the denominator (population).


The Indigenous Mortality Study was first conducted as part of the ABS Census Data Enhancement (CDE) project for the 2006 Census. It has been repeated for subsequent Censuses. Most recently, the CDE project consists of a number of studies which have brought together data from the 2016 Census of Population and Housing and other specified datasets.

For more information on the 2016 CDE project, see the paper: 'Linking Death registrations to the 2016 Census' (cat. no. 3302.0.55.004) to be released in December 2018.

The aims of the CDE Indigenous Mortality Study were to:

  • assist in understanding the differences in recording of Indigenous status between death registrations and Census data; and
  • assess the under-identification of Aboriginal and Torres Strait Islander deaths in death registrations records.

The CDE Indigenous Mortality Study involved linking Census records with death registration records to examine differences in the reporting of Indigenous status across the two datasets. Specifically the study linked 2016 Census records with all registered deaths that occurred from 9 August 2016 to 28 September 2017, with a slightly longer range than 12 months to allow time for all relevant deaths to be registered and processed.

In the absence of any unique identifier in the Census and deaths datasets, linking was performed using probabilistic methods. Three groups of variables, name (first name and surname), personal characteristics (date of birth, age, sex, place of birth, year of arrival and marital status), and geographic information (street number, street name, suburb, mesh block and postcode) were used to link death records to Census records. Variables common to both datasets were standardised to ensure consistent coding and formatting. The two datasets were linked in a way that was independent of reported Indigenous status so that any future analysis would not be affected by bias introduced in the linking process. For this reason, Indigenous status was not used as a linking variable.

The 2016 Death registrations to Census linkage project builds on the success of other data integration programs, incorporating enhancements from these programs.

The main enhancements implemented for the 2016 project included:
  • use of non-sequential probabilistic linking of 2016 Census data to death records (as opposed to sequential probabilistic linking used in 2011),
  • use of alternative address information from Census and Death registrations to improve linkage of records between datasets,
  • improving name repair processes, where the rarity of a name was used in evaluating the quality of links established, and
  • an enhanced clerical review strategy resulting in higher quality links.

Internationally, similar record linkage studies have been conducted in New Zealand where the 1981, 1986, 1991, 1996 and 2001 Censuses were each anonymously and probabilistically linked to three years of subsequent deaths data, allowing a comparison of ethnicity recording (Ajwani et al., 2003; Blakely et al., 2002a; Blakely et al., 2002b). Large nationally representative studies based on linked Census and deaths data have also been conducted in the United Kingdom, France, Sweden and Netherlands. The results from these studies have been used in various ways including the provision of evidence for policy decisions and the setting of policy targets for special intervention programs.