Notes on the data: Chronic diseases and conditions
Estimated male, female or persons with mental and behavioural problems, 2017–18
Policy context: In 2017-18, an estimated 4.8 million Australians (20.1%) reported having a mental and behavioural condition; an increase from 17.5% in 2014-15 . The most common mental illnesses are anxiety related (13.1%) and mood affective disorders (10.8%) . The Productivity Commission reported in 2019 that the treatment of mental illness has been tacked on to a health system that has been largely designed around the characteristics of physical illness. They commented on a number of issues of concern arising from this approach, one of which was that, in contrast to many physical health conditions, mental illness tends to first emerge in younger people (75% of those who develop mental illness, first experience mental ill-health before the age of 25 years) raising the importance of identifying risk factors and treating illness early where possible . They estimated that the cost to the Australian economy of mental ill-health and suicide is, conservatively, in the order of $43 to $51 billion per year. Additional to this is an approximately $130 billion cost associated with diminished health and reduced life expectancy for those living with mental ill-health .
Women (22.3%) are more likely than men (17.8%) to have mental and behavioural conditions . The highest (self-reported) prevalence was recorded for those aged 15 to 24 years, at 30.0% for females and 21.3% for males .
- Australian Bureau of Statistics (ABS). Mental and behavioural conditions National Health Survey: First Results, 2017-18 - Australia. Canberra: ABS; 2018. Available from: https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4364.0.55.0012017-18?OpenDocument; last accessed 15 October 2019
- Productivity Commission, Mental Health, Draft Report. Available from: https://www.pc.gov.au/inquiries/current/mental-health/draft; last accessed 1 November 2019.
- Australian Bureau of Statistics (ABS). National Health Survey: First Results, 2017–18 — Australia. Canberra: ABS; 2018. Available from: https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4364.0.55.0012017-18?OpenDocument; last accessed 14 October 2019
Differences from data published by the Australian Bureau of Statistics (ABS):
Data by quintile of socioeconomic disadvantage and Remoteness will differ to the extent that data extracted from Survey TableBuilder have been randomised, whereas those published by the ABS are not. In addition, rates published by the ABS for modelled estimates are generally crude rates; rates published by PHIDU are age-standardised.
In the absence of data from administrative data sets, estimates are provided for selected health risk factors from the 2017–18 National Health Survey (NHS), conducted by the Australian Bureau of Statistics (ABS). Details of the method used and accuracy of results are available from the ABS paper Explanatory Notes: Modelled estimates for small areas based on the 2017-18 National Health Survey, available here.
Estimates at the Population Health Area (PHA) level are modelled estimates produced by the ABS, as described below (estimates at the Local Government Area (LGA) and Primary Health Network (PHN) level were derived from the PHA estimates).
For the Primary Health Network (PHN) data, differences between the PHN totals and the sum of LGAs within PHNs result from the use of different geographic correspondence files.
Estimates for quintile of socioeconomic disadvantage of area and Remoteness Area are direct estimates, extracted using the ABS Survey TableBuilder.
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 (xlsx) and viewable in the column 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 relatively high survey response rate in the NHS 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 very remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities; whereas these areas comprise less than 3% of the total population, Aboriginal people comprise up to one third of the population. The survey does not include persons usually resident in non-private dwellings (hospitals, gaols, nursing homes - and also excludes members of the armed forces).
This and other limitations of the method mean that estimates have not been published for PHAs with populations under 1,000.
The ABS used a number of methods to measure the quality of the estimates, one of which is the relative root mean squared error (RRMSE) of the modelled estimates. The RRMSEs are included with the data. Users are advised that:
- estimates with RRMSEs less than 25% are considered reliable for most purposes;
- 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.
Mental and behavioural problems data refer to persons who self-reported ever being told by a doctor or nurse that they had one or more of the following mental and behavioural problems, that were considered current and long:
- anxiety-related conditions (such as anxiety disorders/ feeling anxious, nervous or tense);
- mood (affective) disorders (such as depression/ feeling depressed);
- alcohol and drug problems;
- problems of psychological development;
- behavioural, cognitive and emotional problems with usual onset in childhood/adolescence;
- other mental and behavioural problems.
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.
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 from 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, quintile of socioeconomic disadvantage of area and Remoteness Area
Numerator: Estimated number of male, female or persons with current, long-term mental and behavioural problems
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: Age-standardised rates are based on Australian Bureau of Statistics data, produced as a consultancy for PHIDU, from the 2017—18 National Health Survey
Quintiles & Remoteness: Compiled by PHIDU based on direct estimates from the 2017–18 National Health Survey, ABS Survey TableBuilder.