Notes on the data: Composite indicators
Estimated male, female and total population, aged 18 years and over, who had at least one of four health risk factors, 2014-15
Policy context: Smoking, consuming alcohol at levels considered to be a high risk to health, obesity and undertaking no or little exercise are all important risk factors for developing chronic disease.
In 2014-15, over three quarters (77.6%) of the population were estimated to have at least one of these four risk factors; the proportion was higher for females (73.0%) than for males (81.4%). The proportions for the individual risk factors were 66.3% for people undertaking no or low exercise, 27.9% for people who are obese, 16.7% for people consuming alcohol at levels considered to be a high risk to health over their lifetime, and 16.1% for current smokers .
- Australian Bureau of Statistics (ABS) National Health Survey: First Results, 2014–15. Available from http://www.abs.gov.au/ausstats/abs@.nsf/mf/4364.0.55.001; last accessed 4/12/2016.
Notes: In the absence of data from administrative data sets, estimates are provided for selected health risk factors from the 2014–15 National Health Survey (NHS), conducted by the Australian Bureau of Statistics (ABS).
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 PHA estimates).
Estimates for Quintiles and Remoteness Areas 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 (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 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 Primary Health Network (PHN) data, differences between the PHN totals and the sum of LGAs within PHNs result from the use of different concordances.
The four risk factors are: current smokers; consuming alcohol at levels considered to be a high risk to health over their lifetime; obese from measured height and weight; and no or low exercise in the week prior to interview. See each indicator for definitions.
Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, Quintiles and Remoteness Areas
Numerator: Estimated number of males, females or persons aged 18 years and over who had one of four risk factors
Denominator: Male, female or total population aged 18 years and over
Detail of analysis: Indirectly age-standardised rate per 100 population (aged 15 years and over); 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.