Socio-Economic Indexes for Areas (SEIFA) cluster
Collection and usage attributes
|Guide for use:||SEIFA is a suite of four summary measures that have been created from 2006 Census information. The indexes can be used to explore different aspects of socio-economic conditions by geographic areas. For each index, every geographic area in Australia is given a SEIFA number which shows how disadvantaged that area is compared with other areas in Australia.
Each index summarises a different aspect of the socio-economic conditions of people living in an area. They each summarise a different set of social and economic information. The indexes provide more general measures of socio-economic status than is given by measuring income or unemployment alone, for example.
The four indexes in SEIFA 2006 are:
The concept of relative socio-economic disadvantage is neither simple, nor well defined. SEIFA uses a broad definition of relative socio-economic disadvantage in terms of people's access to material and social resources, and their ability to participate in society. While SEIFA represents an average of all people living in an area, SEIFA does not represent the individual situation of each person. Larger areas are more likely to have greater diversity of people and households.
SEIFA 2006 is released for the following geographic levels:
The basic geographic level used to create SEIFA is the CD. The CD is the smallest spatial unit in the Australian Standard Geographic Classification (ASGC) (ABS cat no 1216.0). SLAs and LGAs are larger units in the ASGC. POAs are a CD-based approximation of Australia Post postcodes, and are part of the Census Geographic Areas classification (ABS cat no 2905.0).
The data elements listed below do not lead directly to the four SEIFA measures. Rather, they are used to determine the geographic location which can be examined on the SEIFA indexes. As SEIFA is collected at the Collection District level, the collection of information about a person's or service provider organisation's locality and postcode enables the user to ascertain the Collection District or larger geographical entity which can then be found in the relevant SEIFA index.
A number of tools have been designed to assist users to assign geographic area codes on the basis of localities and postcodes. Chief amongst these has been the National Localities Index (NLI).The NLI consists of two parts - a Localities Index and a Streets Sub-Index. The Localities Index contains a list of all Localities in Australia. In broad terms, a Locality is a place where people live or work - or say they live or work. Localities are assigned their full ASGC Main Structure code (i.e. S/T, SD, SSD and SLA codes). The majority of Localities lie wholly within one SLA but where they are split between two or more SLAs, street information is recorded in the Streets Sub-Index.
The NLI is not available beyond the Australian Standard Geographical Classification (ASGC) 2007. The final edition of the NLI was released in July 2007; it was current up until 30 June 2008. The NLI has been replaced by the 'Locality to SLA Concordance' which is a list of State, Locality and Postcode combinations that can be used to determine an ASGC Statistical Local Area ( SLA) code. This list has been derived from various geographic information sources. Currently the 'Locality to SLA Concordance' is revised and released each year.
Similar concordances may be made available for the forthcoming Australian Statistical Geography Standard (ASGS).
SEIFA indexes are assigned to areas, not to individuals. They indicate the collective socio-economic status of the people living in an area. A relatively disadvantaged area is likely to have a high proportion of relatively disadvantaged people. However, such an area is also likely to contain people who are not disadvantaged, as well as people who are relatively advantaged.
Source and reference attributes
|Submitting organisation:||Australian Institute of Health and Welfare.|
|Related metadata references:|
Has been superseded by Socio-Economic Indexes for Areas (SEIFA) cluster 2010
|Implementation in Data Set Specifications:|
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