A crude rate is defined as the number of events over a specified period (for example, a year) divided by the total population at risk of the event.
Unless otherwise stated, crude rates are used throughout the publication.
Age-standardised rates enable comparisons to be made between populations that have different age structures, and over time as the age structure of the population of interest may change. Direct standardisation was used in this release, in which the age-specific rates (e.g. for 5 and 10 year age groups) are multiplied by a standard population. This effectively removes the influence of the age structure on the summary rate. Where age-standardised rates have been used, this is stated throughout the release.
All age-standardised rates in this release have used the June 2001 Australian total estimated resident population as the standard population.
Margin of Error
The observed value of a rate may vary due to chance even where there is no variation in the underlying value of the rate. Therefore, where measures based on survey data include a comparison between time periods, geographical locations, socioeconomic groups, country of birth or disability status, the margin of error (MoE) at the 95% confidence level has been calculated for proportion estimates. The margin of error is the largest possible difference (due to sampling error) that could exist between the estimate and what would have been produced had all persons been included in the survey.
Confidence intervals—constructed by taking the estimate plus or minus the MoE— are used to provide an approximate indication of the true differences between rates. If the confidence intervals do not overlap, the difference can be said to be statistically significant. Where alternative statistical tests were used to provide information about statistical significance, these are stated separately. The visualisation tool tip for each estimate includes the MoE at the 95% confidence level and/or a note where differences are found to be statistically significant.
However, statistically significant differences are not necessarily the same as differences considered to be of practical importance. It is possible for small differences that have practical importance to be found to be not statistically significant as they are below the threshold the significance test can reliably detect.
Percentages in the release are generally rounded to whole numbers except for those less than 10% which are rounded to 1 decimal place.
Numbers between 1,000 and 100,000 are rounded to the nearest hundred. Numbers over 100,000 are rounded to the nearest 1,000.
As a result of rounding, entries in columns and rows of tables as well as figures may not add to the totals shown. Unless otherwise stated, derived values are calculated using unrounded numbers.
Presentation of data
Some data are not published (n.p.) due to reliability and/or confidentiality reasons.
Survey data, obtained from a sample of the population, is subject to sampling error. Where estimates are subject to a level of sampling error too high for general use, they are not included in visualisations, but are included in data tables, with caveats.
Number estimates subject to a high level of sampling error—Relative Standard Error (RSE) between 25% and 50%— are annotated with an * in visualisations and data tables and should be used with caution.
Some data are not available for publication (n.a.). This can be due to several reasons, for example, the data are not collected and/or available, and/or denominator data is not available to calculate a rate.
The ABS estimated resident population (ERP) data were used to calculate most of the rates presented in this release for administrative data collections. Exceptions are where the denominator was available from within the data source.
Rates were calculated using the ERP of the reference year as at 30 June for calendar year data (1 January to 30 December) and 31 December for financial year data (1 July to 30 June). The denominator for rates by socioeconomic disadvantage and remoteness area were calculated by applying an ABS concordance between statistical areas (SA2) and socioeconomic disadvantage and between statistical areas and remoteness area, to the relevant ERP by SA2 counts.
Socioeconomic and remoteness area data
Data by socioeconomic area uses the Socio-Economic Indexes for Areas (SEIFA) the Index of Relative Socio-economic Disadvantage (IRSD). The IRSD is a general socio-economic index that summarises a range of information about the economic and social conditions of people and households within an area, including their access to material and social resources, and their ability to participate in society. A low score indicates relatively greater disadvantage in general. Data on socioeconomic area are presented by quintiles, with the 1st quintile representing the most disadvantaged group.
Data by remoteness are aligned to the 2016 Australian Statistical Geography Standard (ASGS) Remoteness Area Structure, and based on the person’s usual residence. The 2016 ASGS Remoteness Structure categorises geographic areas in Australia into 5 classes of remoteness areas based on their relative access to services using the Accessibility/Remoteness Index of Australia which is derived by measuring the road distance of a location from the nearest urban centre. The 5 classes are: Major cities, Inner regional, Outer regional, Remote, and Very remote.
Sex, gender, variations of sex characteristics and sexual orientation
In 2021, the ABS released the Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables, 2020. This standard was designed to support consistent collection of each of these four core variables, consequently allowing for more comprehensive and representative reporting in the future. However, data sources currently used for national reporting on family, domestic and sexual violence in this report do not collect data on sexual orientation or variations of sex characteristics. For this reason, only sex and gender are discussed here.
The mechanisms for collecting data on sex and/or gender vary across the data collections used in this report. When presenting statistics, the AIHW has used the terms most appropriate for the data source. In most cases, ‘male’ and ‘female’ are used, however it is not always known whether the data refer to sex characteristics (at birth or other point in time) or to gender. It should also be noted that some participants may not use and/or identify with these terms. Specific information about how sex and/or gender is collected in each data source, is included in Data Sources, where available. At times, the terms ‘men’ and ‘women’, and ‘boys’ and ‘girls’ are also used in high-level text to improve readability. Again, it should be noted that some participants may not use and/or identify with these terms.
The term ‘persons’ is used throughout to refer to all/total people.