Geographical structures

The geographical structures available for the latest Social Health Atlases of Australia and Aboriginal and Torres Strait Islander Social Health Atlas are detailed below. Data by Statistical Local Area, Medicare Local and Local Hospital Network, based on the Australian Standard Geographical Classification (ASGC), are no longer being updated. The final release data and maps based on these geographies, together with Census data by Statistical Area Level 2, are available from the Data archive section of the website.

Social Health Atlases of Australia (and Topic-Specific Atlases)

Population Health Areas

Population Health Areas (PHAs) are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

PHAs based on the 2011 Australian Statistical Geography Standard (ASGS) were first released in the December 2016 release. PHA boundaries have been updated to reflect the 2016 ASGS. Where PHA boundaries have changed between 2011 and 2016, the data for non-Census indicators have been created using an Australian Bureau of Statistics SA2 correspondence based on 2011 population distributions. For PHA areas such as Colac Region/ Otway (85.2%), Moyne - East/ Moyne - West (-30.3%), Bli Bli/ Diddilibah – Rosemount (125.3%) and Noosa Hinterland (-26.4%) where the population has changed substantially between 2011 and 2016, the data should be treated with caution.

Australian Statistical Geographical Standard (ASGS)

For further information, refer to the Population Health Areas: Overview.

To find the code and/or name of a PHA, refer to the full list of Population Health Areas (including Statistical Areas Level 2 (SA2)). In addition, to search for a suburb and determine which PHAs this suburb falls into and what percentage of the suburb's population is in a PHA, refer to the suburb to PHA correspondence for 2016 and 2011 (xls).

For shapefiles of PHAs, refer to the PHA shape files.

Local Government Areas

The Local Government Areas (LGAs) presented in the PHIDU Social Health Atlases are based on the Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2016.

LGAs are an Australian Bureau of Statistics (ABS) approximation of officially gazetted LGAs as defined by each State and Territory Local Government Department. LGAs cover incorporated areas of Australia. For further information regarding the LGA structure, refer to the ABS information at: Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, July 2016.

Caveat on LGA data quality

The data presented by Local Government Area (LGA) have been estimated from the postcode of the address, as the LGA of usual residence was not more accurately geocoded (e.g., from the street address). These estimates are of variable quality, as the allocation from a postcode to one or more LGAs was based on the proportion of the total population falling within LGAs covered by the postcode. The proportional allocations are as providedby the Australian Bureau of Statistics (ABS)

This method does not account for variations in the proportion of a postcode varying between different constituent LGAs or parts of LGAs according to different population characteristics such as age groups or Indigenous status, or the location of facilities which can alter the proportion (e.g., a nursing home in part of the postcode will not be recognised by this method).

Cherbourg (S) in Queensland provides an example of the poor quality of outcomes that can result from this process. Under the ABS allocation, Cherbourg (S) is allocated 26.2% of the population of postcode 4605. However, almost three quarters (72.4%) of the Aboriginal and Torres Strait Islander population of postcode 4605 is estimated to live in Cherbourg (S) and not in either of the other two LGAs allocated population from the postcode. As a result of this approach, the Australian Childhood Immunisation Register (ACIR) recorded 14 children at age 1 year in 2017, 12 of whom were immunised. Using data more accurately geocoded by ABS, there were 46 births in Cherbourg (S), indicating a substantial shortfall in the data in the ACIR.

The quality indicators of LGA estimates produced by the ABS include Good (348 LGAs), Acceptable (126 LGAs) or Poor (70 LGAs) as listed here. The definitions for these quality indicators are as follows:

  • Good - The ABS expects that the correspondence used has converted data to a high degree of accuracy and users, therefore the converted data will reflect the actual characteristics of the geographic areas involved.
  • Acceptable - The ABS expects that the correspondence used has converted data to a reasonable degree of accuracy, though caution needs to be applied as the quality of the converted data will vary and may differ in parts from the actual characteristics of the geographic areas involved.
  • Poor - The ABS expects that there is a high likelihood the correspondence used has not converted data accurately, therefore the converted data should be used with caution and may not reflect the actual characteristics of many of the geographic areas involved.
  • Not known - Not known.

PHIDU is in contact with data custodians to obtain better quality data for LGAs.

Primary Health Networks

Primary Health Networks (PHNs) comprise 31 primary health care organisations across Australia. For further information, including digital boundary and concordance files, refer to the Department of Health Primary Health Networks information.

Quintiles of Socio-economic Disadvantage of Area

The Quintiles of Socio-economic Disadvantage of Area data, presented as Inequality graphs, are based on the ABS Index of Relative Socio-economic Disadvantage.

To calculate rates by socio-economic status, Population Health Areas (PHAs1) were ranked based on the Index of Relative Socio-economic Disadvantage score from the 2016 Census. The listing was then divided into five groups with each group comprised of approximately 20% of the population in Australia. The data for each indicator in this atlas were then allocated (at the PHA level) to the appropriate group and the rate for that indicator calculated for each of the five groups; the groups are referred to as quintiles of socio-economic disadvantage, reflecting the index on which they are based. This exercise was repeated for PHAs in each State and Territory, each capital city and each Rest of State/Territory area.

In addition to showing the variation between the quintiles for each indicator in a chart, a rate ratio is given to describe the magnitude of variation between the most disadvantaged and least disadvantaged quintile for each indicator. A rate ratio of 1 indicates that the rate in the least and most disadvantaged quintiles is the same. A rate ratio greater than 1 shows there is a higher rate in the most disadvantaged quintile, e.g., a rate ratio of 2 would indicate there is double the activity in the most disadvantaged compared to the least disadvantaged quintile. Rate ratios that are greater than or less than 1 is indicative that there may be some inequality in access to services across population groups, or in early death when looked at by level of disadvantage. However, it is also important, and informative, to note that variations occur across all the quintiles: in many cases there is a social gradient, a variation in the data that runs from top to bottom of the socio-economic spectrum.


1Prior to 2011, quintiles of socio-economic disadvantage of area were based on Statistical Local Areas.

Remoteness Areas

The Remoteness graphs and associated data are based on the ABS Remoteness Structure.

The Australian Bureau of Statistics' (ABS) Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure1 is a framework for statistical geography, which defines locations in terms of remoteness2. Geographic remoteness is essentially a measure of a physical location's level of access to goods and services3. Large population centres tend to have a greater range of goods and services available than small centres.

The measures of remoteness used by the ABS are based on population estimates obtained from the Census of Population and Housing, conducted every five years. Remoteness measures are calculated using Accessibility/Remoteness Index of Australia (ARIA+) scores, which are based on the distance of geographic locations from the nearest population centre in various size ranges. The lower the ARIA+ score for a location, the better its level of access to goods and services.3

Box 1: Classification of Remoteness Areas in Australia

The ABS Australian Statistical Geography Standard (ASGS) Remoteness Structure allocates areas to one of six Remoteness Areas depending on their distance from urban centres, where the population size of the urban centre is considered to govern the range and types of services available. Remoteness Areas used in PHIDU reports cover the following five categories: Major Cities of Australia, Inner Regional Australia, Outer Regional Australia, Remote Australia and Very Remote Australia. The sixth Remoteness Area covers populations in areas recorded as off-shore, migratory and shipping and is not of relevance to the data in these reports.

The category Major Cities includes Australia’s capital cities, with the exceptions of Hobart and Darwin, which are classified as Inner Regional and Outer Regional, respectively.

From April 2018 data are being coded to Remoteness Areas released by the ABS in March 2018 and are presented under the `latest’ period heading.

In the time series set, data coded to classifications for 2006 and earlier have been re-compiled to match the 2011 Remoteness Area, and later data have been re-coded to those 2011 areas.

Readers should note that the presentation of data by Remoteness Area is dependent on the recording of addresses in the various administrative data collections from which data in this report are drawn.


1Australian Bureau of Statistics (ABS). Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2011. (ABS Cat. no. 1270.055.005). Canberra: ABS; 2013

2Australian Population and Migration Research Centre (APMRC). ARIA (Accessibility/Remoteness Index of Australia), 2013. [cited 2016 April 1]. Available from: http://www.adelaide.edu.au/apmrc/research/projects/category/about_aria.html

3Australian Institute of Health and Welfare (AIHW). Remoteness classification (ASGS-RA) N – METeOR. [Internet; cited 2016 March 31]. Available from: http://meteor.aihw.gov.au/content/index.phtml/itemId/531713/meteorItemView/long

Regional Centres

Regional Centres are based on the following criteria set out in the Centre for Aboriginal Economic Policy Research's (CAEPR) 2011 Census Paper Series – Paper 12 Regional Centres:

  • They must be classified by the Australian Bureau of Statistics (ABS) as a Significant Urban Area (SUA ) which implies a population of 10,000 usual residents or more;
  • They cannot have a population of 250,000 usual residents or more, as that would put them in the ‘major city’ category in the ABS’s remoteness hierarchy; and
  • They must have an Indigenous population estimate of at least 1,000 usual residents

There are 46 Regional Centres across Australia (based on 2016 Census) data.

Aboriginal & Torres Strait Islander Social Health Atlas of Australia (and Topic-Specific Atlases)

Indigenous Areas

Indigenous Areas (IARE), based on the ABS 2016 ASGS Indigenous Structure, are medium sized geographical units designed to facilitate the release and analysis of more detailed statistics for Aboriginal and Torres Strait Islander Peoples. There are 430 IARE presented by the ABS 2016 ASGS Indigenous Areas (IARE).

Indigenous Regions

Indigenous Regions (IREG), based on the ABS 2016 ASGS Indigenous Structure, are large geographical units loosely based on the former Aboriginal and Torres Strait Islander Commission boundaries. They are created by combining together one or more Indigenous Areas. There are 58 IREG presented by the ABS 2016 ASGS Indigenous Regions (IREG).