Notes on the data: Chronic diseases and conditions
Estimated male, female or persons with mood (affective) disorders, 2014–15
Policy context: In 2014-15, there were an estimated 4.0 million Australians (17.5%) who reported having a mental and behavioural condition . The most common mental illnesses are anxiety related (11.2%) and mood affective disorders, which includes depression, (9.3%) . Women (19.2%) are more likely than men (15.8%) to have mental and behavioural conditions .
Data for 2014-15 are not comparable to earlier years due to a change in collection methodology. In 2014-15, information on mental health conditions was obtained through a new Mental, Behavioural and Cognitive Conditions module, while in previous years it was collected as part of the Long Term Conditions module.
- Australian Bureau of Statistics (ABS). National Health Survey: First Results, Australia, 2014-15. (ABS Cat. no. 4364.0.55.001). Canberra: ABS; 2015.
Notes: In the absence of data from administrative data sets, estimates are provided for certain chronic diseases and conditions from the 2014–15 NHS, conducted by the Australian Bureau of Statistics (ABS).
Estimates at the PHA level are modelled estimates produced by the ABS, as described below (estimates at the LGA and PHN level were derived from the PHA estimates).
Users of these modelled estimates should note that they do not represent data collected in administrative or other data sets. As such, they should be used with caution, and treated as indicative of the likely social dimensions present in an area with these demographic and socioeconomic characteristics.
The numbers are estimates for an area, not measured events as are, for example, death statistics. As such, they should be viewed as a tool that, when used in conjunction with local area knowledge and taking into consideration the prediction reliability, can provide useful information that can assist with decision making for small geographic regions. Of particular note is that the true value of the published estimates is also likely to vary within a range of values as shown by the upper and lower limits published in the data (xls) and viewable in the bar chart in the single map atlases.
What the modelled estimates do achieve, however, is to summarise the various demographic, socioeconomic and administrative information available for an area in a way that indicates the expected level of each health indicator for an area with those characteristics. In the absence of accurate, localised information about the health indicator, such predictions can usefully contribute to policy and program development, service planning and other decision-making processes that require an indication of the geographic distribution of the health indicator.
The survey response rate of around 85% provides a high level of coverage across the population; however, the response rate among some groups is lower than among other groups, e.g., those living in the most disadvantaged areas have a lower response rate than those living in less disadvantaged areas. Although the sample includes the majority of people living in households in private dwellings, it excludes those living in the most remote areas of Australia; whereas these areas comprise less than 3% of the total population, Aboriginal people comprise up to one third of the population in these areas. This and other limitations of the method mean that estimates have not been published for PHAs with populations under 1,000, or with a high proportion of their population in:
- non-private dwellings (hospitals, gaols, nursing homes - and also excludes members of the armed forces);
- in Very Remote areas;
- in discrete Aboriginal communities; and
- where the relative root mean square errors (RRMSEs) on the estimates was 1 or more (estimate replaced with ≠)
- Estimates with RRMSEs from 0.25 and to 0.50 have been marked (~) to indicate that they should be used with caution; and those greater than 0.50 but less than 1 are marked (~~) to indicate that the estimate is considered too unreliable for general use.
- For the PHN data, differences between the PHN totals and the sum of LGAs within PHNs result from the use of different concordances.
Mood (affective) disorders were identified through self-reported information that respondents reported ever being told by a doctor or nurse that they had one or more mood (affective) disorders such depression/ feeling depressed and that it was current and long-term at the time of the interview. A current and long-term condition is defined as a medical condition that has lasted or expected to last six months or more and was current at the time of the interview. Mood disorders include depression and other mood (affective) disorders.
Note for all mental and behavioural problems data: In the 2014-15 National Health Survey, a module specifically dedicated to mental and behavioural conditions was included to collect information on cognitive, organic and behavioural conditions. Previously mental and behavioural conditions were collected in a module that included a wide range of long-term health conditions. The number of persons who reported having a mental and behavioural condition in 2014–15 has increased since the 2011–12 NHS, potentially due to the greater prominence of mental and behavioural conditions in the new module. Data on mental and behavioural conditions for 2014–15 are therefore not comparable with data in previous National Health Surveys. For more information refer to the explanatory notes in the ABS National Health Survey: First Results, 2014-15 (cat. no. 4364.0.55.001).
Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, Quintiles and Remoteness Areas
Numerator: Estimated number of male, female or persons with current, long-term mood (affective) disorders
Denominator: Male, female or total population
Detail of analysis: Indirectly age-standardised rate per 100 population; and/or indirectly age-standardised ratio, based on the Australian standard
PHA, LGA & PHN: Compiled by PHIDU based on modelled estimates from the 2014–15 National Health Survey, ABS (unpublished).
Quintiles & Remoteness: Compiled by PHIDU based on direct estimates from the 2014–15 National Health Survey, ABS Survey TableBuilder.