2033.0.55.001 - Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016 
Quality Declaration
Quality Declaration ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 27/03/2018
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GLOSSARY
DECILE Deciles divide a distribution into ten equal groups. In the case of SEIFA, the distribution of scores is divided into ten equal sized groups. The lowest scoring 10% of areas are given a decile number of 1, the second-lowest 10% of areas are given a decile number of 2 and so on, up to the highest 10% of areas which are given a decile number of 10. DISADVANTAGE The ABS defines relative socio-economic advantage and disadvantage in terms of people's access to material and social resources, and their ability to participate in society. The terms "disadvantage" and "socio-economic disadvantage" are used interchangeably in this publication. EQUIVALISED HOUSEHOLD INCOME Equivalised household income is total household income adjusted by the application of an equivalence scale to facilitate comparisons of income levels between households of differing size and composition. Equivalised total household income can be viewed as an indicator of the economic resources available to a standardised household. For a lone person household it is equal to household income. For a household comprising more than one person, it is an indicator of the household income that would be needed by a lone person household to enjoy the same level of economic well-being. For more information, refer to the 2016 Census Dictionary. LOADINGS Each variable in the analysis is correlated with each component of the Principal Component Analysis (PCA). This correlation is called the loading. Loadings help to interpret what aspects of advantage and disadvantage a component may represent. The loadings are also useful in analysing the results from using different sets of original variables (such as for the four indexes in SEIFA). For more information on PCA and loadings, refer to the 2016 SEIFA Technical Paper (available from the Downloads tab). LOCAL GOVERNMENT AREA (LGA) Local Government Areas (LGAs) are an ABS approximation of officially gazetted Local Government Areas as defined by each State and Territory Local Government Department. Local Government Areas cover incorporated areas of Australia. Incorporated areas are legally designated parts of a State or Territory over which incorporated local governing bodies have responsibility. The major areas of Australia not administered by incorporated bodies are the northern parts of South Australia and all of the Australian Capital Territory and the Other Territories. These regions are identified as "Unincorporated" in the ABS Local Government Area structure. LGAs are constructed from whole Mesh Blocks. MEAN A mean is an average; a measure of central tendency of a distribution. A mean SEIFA score can be calculated by adding the value of all scores and dividing this by the number of scores being added. MESH BLOCKS (MBs) Mesh Blocks are the smallest area geographical region in the ASGS. There are approximately 358,000 covering the whole of Australia. They are assigned to different categories based on the broad type of land use such as: residential, commercial, agricultural and parkland. Where possible, Mesh Blocks contain between 30 and 60 dwellings or no dwellings at all. Mesh Blocks are the building block for all the larger regions of the ASGS. NEED FOR ASSISTANCE The disability variable provides an indication of the physical or health aspects of relative socio-economic disadvantage. It is based on the need for assistance Census questions, which were developed to provide an indication of whether people have a profound or severe disability. People with a profound or severe disability are defined as those people needing help or assistance in one or more of the three core activity areas of self-care, mobility and communication, because of a disability, a long term health condition (lasting six months or more) or advanced age. For brevity, 'need for assistance' is referred to using the term 'disability'. Note that the Census measure was designed to indicate the disability status of people in Australia according to geographic areas, and for small groups within the broader population, and is not a comprehensive measure of disability. Disability can limit employment opportunities, and consequently access to financial resources. For the purpose of indicating relative socio-economic disadvantage, we have limited the scope of the SEIFA disability variable to people aged under 70. PERCENTILE Percentiles divide a distribution into 100 equal groups. In the case of SEIFA, the distribution of scores is divided into 100 equal groups. The lowest scoring 1% of areas are given a percentile number of 1, the second-lowest 1% of areas are given a percentile number of 2 and so on, up to the highest 1% of areas which are given a percentile number of 100. SEIFA percentiles are provided to allow users to create their own groupings, such as quartiles (which contain 25% of SA1s). POPULATION WEIGHTING SEIFA 2016 consists of indexes for five different types of area: Statistical Area Level 1 (SA1s), Statistical Area Level 2 (SA2s), Local Government Areas (LGAs), Postal Areas (POAs) and State Suburbs (SSCs). However, the SEIFA indexes can be used to create scores for other types of areas. Because SA1s form the basis of all of the standard geography boundaries, SA1 scores can be used to represent larger standard areas. To create the scores for larger geographies, the SA1 scores are aggregated using a population-based weighting. To do this, first multiply the score of each SA1 within the larger geography by its usual resident population, and then divide the sum of these population-weighted SA1s by the total number of people within the larger area. Population counts for SA1s (the number of usual residents in the SA1s) have been provided with the index scores. From these scores, ranks, deciles and percentiles are calculated in the same manner as with SA1s. It is important to note that, because of this method of construction, the distribution of scores for these larger geographic areas will not be a standard distribution. For example, the mean of the LGA scores will not be 1000, just as the standard deviation will not be 100. Also, the LGA deciles do refer to 10% of LGAs, and have only an indirect relationship to the SA1 deciles. An individual LGA will contain multiple SA1s, with a range of SA1 scores, ranks and deciles that will be different to the LGA score, rank and decile. For more information refer to Chapter 4.3 of the Technical Paper. POSTAL AREA (POA) Postal Areas (POAs) are an ABS approximation of postcodes. A postcode is a four digit number used by Australia Post to assist with mail delivery. POAs are constructed from whole Mesh Blocks. Some Australia Post postcodes are not included in the Postal Area classification. This occurs when no Mesh Block can be allocated to a particular postcode. Postal Areas exclude Australia Post postcodes that are not street delivery areas. These include post office boxes, mail back competitions, large volume receivers and specialist delivery postcodes. There are instances where postcodes cross state or territory boundaries. The corresponding POAs also cross state or territory boundaries. The POA number is the same as the matched postcode. POAs do not have names. RANK To determine the SEIFA rank, all the areas are ordered from lowest score to highest score. The area with the lowest score is given a rank of 1, the area with the second-lowest score is given a rank of 2 and so on, up to the area with the highest score which is given the highest rank. While two areas may appear to have the same score due to rounding, every area has an individual score and an individual rank. However, caution should be used when distinguishing areas with similar scores and ranks. SCORE A SEIFA score is created using information about people and households in a particular area. An SA1 score is standardised against a mean of 1000 with a standard deviation of 100. This means that the average SEIFA SA1 score will be 1000 and the middle two-thirds of SEIFA scores will fall between 900 and 1100 (approximately). (Refer to Standardisation in this Glossary). A SEIFA score provides detailed information and is used for more sophisticated analysis. Ranks or deciles should be used for most analyses. STATISTICAL LOCAL AREA (SLA) Statistical Local Areas (SLAs) are an older geographic classification. They are not used in the ASGS, and so scores at the SLA level are not being provided in SEIFA 2016. STATISTICAL AREAS LEVEL 1 (SA1s) SA1s are the smallest region of the ASGS for which a wide range of Census data will be released. They have an average population of about 400 people. They are built from whole Mesh Blocks. STATISTICAL AREAS LEVEL 2 (SA2s) SA2s have an average population of about 10,000, and generally have a population between 3,000 and 25,000 people. They are built from whole SA1s. STATISTICAL AREAS LEVEL 3 (SA3s) SA3s generally have a population between 30,000 and 130,000 people. They are built from whole SA2s. In regional areas, SA3s represent the area serviced by regional cities that have a population over 20,000 people. In the major cities, SA3s represent the area serviced by a major transport and commercial hub. STATISTICAL AREAS LEVEL 4 (SA4s) The SA4 regions are the largest sub-State regions in the Main Structure of the Australian Statistical Geography Standard (ASGS). In regional areas, SA4s tend to have populations bewteen 100,000 and 300,000 people. In metropolitan areas, the SA4s tend to have populations between 300,000 and 500,000 people. STATE SUBURBS (SSC) State Suburbs (SSCs) are an ABS approximation of Gazetted Localities, created by allocating one or more Mesh Blocks. State Suburbs are created to enable the release of ABS data on areas that, as closely as possible, approximate Gazetted Localities. This methodology is different to the that used in 2011 where State Suburbs were defined using whole SA1s. This is a significant change and as a result Gazetted Localities represented in the State Suburb classification have a better overall level of accuracy. STATE ELECTORAL DIVISION (SED) State Electoral Divisions (SED) are an ABS approximation of State Electoral Districts. A state electoral district is an area legally prescribed for the purpose of returning one or more members to the State or Territory Lower Houses of Parliament, or the relevant equivalent. Boundaries are based upon the State Electoral Districts current on Census Night 9 August 2016. SEDs are constructed out of whole SA1s. STANDARD GEOGRAPHIC AREAS The Australian Statistical Geography Standard (ASGS) is the geographical standard currently used by the ABS for the collection and dissemination of statistics. It is a hierarchically structured classification with a number of spatial units to satisfy different statistical purposes. The ASGS areas used for SEIFA 2016 are:
The following are non-ABS structures. These structures are approximations of regions that the ABS does not define or maintain.
STANDARDISATION The standard distribution chosen for SEIFA has a mean of 1000 and a standard deviation of 100. First, all of the SA1s are ordered from the lowest to highest score. Second, all the scores are shifted so that the average area now has a new score of 1000. The areas are still in the same order, but they all have new scores spread around the average of 1000. The final stage changes how these scores are spread around the average. While they still remain in order, the scores are spread out (or condensed) so that two-thirds of the areas have 'standardised' scores somewhere between 900 and 1100; that is, approximately two-thirds of the scores lie within 100 either side of the average of 1000. This means that approximately 15% of SA1s have a score lower than 900 with the remaining 85% of SA1s having a score higher than 900. Approximately 85% of SA1s have a score lower than 1100 with the remaining 15% of SA1s have a score higher than 1100. It is important to note that the distributions of the SEIFA indexes are not exactly a normal distribution, even though they have been standardised. However, the above proportions are roughly the same. Standardisation is useful when interpreting the scores and where the scores are used for more technical analysis. Document Selection These documents will be presented in a new window.
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