Notes on the data: Chronic diseases and conditions
Estimated population with asthma, 2011–12 (PHA, LGA & PHN) and 2014–15 (Quintiles & Remoteness)
Note for Population Health Area (PHA), Local Government Area (LGA) and Primary Health Network (PHN): The indicators of chronic diseases and conditions have not been updated to reflect information in the 2014–15 National Health Survey (NHS). The modelling of these estimates was held over until small area Pharmaceutical Benefits Scheme (PBS) and Medicare Benefits Schedule (MBS) data were available, as these data were considered to be highly relevant for use as small area predictors in the production of the estimates. For example, for the indicators of diabetes type 2 and for mental health conditions, data as to the number of prescriptions filled under the PBS add strength as predictors.
The ABS expect to provide PHIDU with these estimates in early 2019.
Policy context: Asthma is a disorder affecting the small airways of the lungs. People with asthma have sensitive airways that narrow in response to certain "triggers", leading to difficulty in breathing. The airway narrowing is caused by inflammation and swelling of the airway lining, the tightening of the airway muscles, and the production of excess mucus. This results in a reduced airflow in and out of the lungs. At present, the cause of asthma is not known and there is no cure. However, with appropriate management, most people with asthma can lead normal, active lives.
Notes: In the absence of data from administrative data sets, estimates are provided for certain chronic diseases and conditions from the 2011–12 Australian Health Survey and 2014-15 NHS, conducted by the Australian Bureau of Statistics (ABS).
Estimates for Quintiles and Remoteness Areas are direct estimates from the 2014-15 NHS, extracted using the ABS Survey TableBuilder.
Estimates at the PHA level 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.
These data refer to persons ever told by a doctor or nurse that they have asthma, and whose asthma is current or long term. Whether a person's asthma is current or not was determined by whether they had had any symptoms of asthma or taken treatment for asthma in the last 12 months. A long-term condition is defined as a condition that is current and has lasted, or is expected to last, for 6 months or more.
Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, Quintiles and Remoteness Areas
Numerator: Estimated number of people with asthma as a current, long-term condition
Denominator: 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 2011-12 Australian Health Survey, ABS (unpublished).
Quintiles & Remoteness: Compiled by PHIDU based on direct estimates from the 2014-15 National Health Survey, ABS Survey TableBuilder.