Australian Institute of Health and Welfare (2022) Diabetes: Australian facts, AIHW, Australian Government, accessed 28 November 2022.
Australian Institute of Health and Welfare. (2022). Diabetes: Australian facts. Retrieved from https://pp.aihw.gov.au/reports/diabetes/diabetes
Diabetes: Australian facts. Australian Institute of Health and Welfare, 13 July 2022, https://pp.aihw.gov.au/reports/diabetes/diabetes
Australian Institute of Health and Welfare. Diabetes: Australian facts [Internet]. Canberra: Australian Institute of Health and Welfare, 2022 [cited 2022 Nov. 28]. Available from: https://pp.aihw.gov.au/reports/diabetes/diabetes
Australian Institute of Health and Welfare (AIHW) 2022, Diabetes: Australian facts, viewed 28 November 2022, https://pp.aihw.gov.au/reports/diabetes/diabetes
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Age-standardisation is a method of removing the influence of age when comparing populations with different age structures – either different populations at one time or the same population at different times.
Direct age-standardisation was used in this report. The Australian estimated resident population as at 30 June 2001 has been used as the standard population.
The observed value of a rate may vary because of the influence of chance and natural variation. To provide an indication of whether 2 rates are statistically different, 95% confidence intervals can be calculated and statistically significant differences highlighted.
A 95% confidence interval describes a span of numbers around the estimate which has a 95% chance of including the true value. When comparing 2 groups, if the 2 confidence intervals do not overlap, the reader can be confident that the difference between the groups is real, and not due to chance.
Confidence intervals were calculated for survey data in this report.
Comparisons of regions in this report use the ABS Australian Statistical Geography Standard (ASGS) 2016 Remoteness Structure, which groups Australian regions into 6 remoteness areas.
The 6 remoteness areas are Major cities, Inner regional, Outer regional, Remote, Very remote and Migratory. These areas are defined using the Accessibility/Remoteness Index for Australia (ARIA), which is a measure of the remoteness of a location from the services that large towns or cities provide.
In some instances, data for remoteness areas have been combined because of small sample sizes.
Further information on the ASGS is available on the ABS website.
Socioeconomic classifications in this report are based on the ABS Index of Relative Socio-economic Disadvantage (IRSD). Geographic areas are assigned a score based on social and economic characteristics of that area, such as income, educational attainment, public sector housing, unemployment and jobs in low-skill occupations. The IRSD relates to the average disadvantage of all people living in a geographical area. It cannot be presumed to apply to all individuals living in the area.
For the analyses in this report, the population is divided into 5 socioeconomic areas, with roughly equal populations (each around 20% of the total), based on the level of disadvantage of the statistical local area of their usual residence. The first group includes the 20% of areas with the highest levels of relative disadvantage (referred to as Group 1, most disadvantaged), while the last group includes the 20% of areas with the lowest levels of relative disadvantage (referred to as Group 5, least disadvantaged).
The IRSD values used in this report are based on the 2016 Census. Further information is available on the ABS website.
Country of birth is reported based on the Standard Australian Classification of Countries (SACC) which provides guidelines for consistent collection, aggregation and dissemination of statistics by country. The country names within the SACC reflect country titles recognised by the Australian Government.
People born in Australia are identified using country level classification (1100–1199), with the remainder of the classifications coming from major groups (1–9).
The country of birth values used in this report are based on the 2016 Census. Further information is available on the ABS website.
In this report, comparisons are made between Aboriginal and Torres Strait Islander persons and people who do not identify as Indigenous.
People with ‘not-stated’ Indigenous status are excluded from any analysis by Indigenous status.
Population data are used in this report to calculate the majority of rates. The population data used are estimated resident populations (ERPs) derived from the ABS Census of Population and Housing.
Throughout this report, rates are age-standardised to enhance comparison across groups where the age structure of the population may influence or confound interpretation. In these cases, the standard population used to calculate the age-standardised rate is the Australian ERP as at 30 June 2001.
The ABS 2016 Census base series B Indigenous population projections were used to derive rates (ABS 2019). To calculate non-Indigenous estimates, the Indigenous projections was subtracted from the total Australian ERP data.
The population of live births was based on the number of hospitalisations (pregnancies) with a birth event code (ICD-10-AM code Z37) in the year of interest. All pregnancies, regardless of outcome (that is, stillbirth or live birth) are counted by this method.
The number of new cases of gestational diabetes was calculated based on the number of hospitalisations of females with a birth event code (ICD-10-AM code Z37) and coexisting diagnosis of gestational diabetes (ICD-10-AM code O24.4) in the year of interest. A single birth event code is entered for each woman, regardless of the number of times she is hospitalised during the same pregnancy or the number of babies born.
Pre-existing diabetes in pregnancy was calculated using two sets of diabetes codes in ICD-10-AM: diabetes ‘E-codes’ and diabetes in pregnancy ‘O24-codes’ (see Classifications section)
The linked NDSS and APEG data were used to identify the prevalent population with living with type 2 diabetes to calculate incidence rates for the initiation of insulin treatment. The denominator population included all registrants with type 2 diabetes with no record of insulin use in the year of analysis. The population included all people with type 2 diabetes who were diagnosed between 2000 and 2020 and were still alive on 31 December of each year of analysis.
ABS (Australian Bureau of Statistics) (2019) Estimates and Projections, Aboriginal and Torres Strait Islander Australians, ABS, accessed 1 December 2021.
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