Notes on the data: Health risk factors
Estimated male, female and total population, aged 18 years and over, with a waist circumference indicating an increased/substantially increased risk of developing chronic diseases, 2014-15
Policy context: Waist circumference is a commonly used measure of whether a person is of a healthy weight or not. In particular, it provides a good estimate of body fat, and can indicate a person's potential risk of developing chronic diseases such as heart disease and Type 2 diabetes.
In 2014-15, the average waist measurement for men aged 18 years and over was 97.5cm, while for women of the same age it was 87.5cm. Both averages are considerably above the measurements indicating increased risk (94cm and 80cm respectively), particularly for women .
More than half (58.8%) of all men aged 18 years and over had a waist circumference that put them at an increased risk of developing chronic diseases, while two in three (65.4%) women had an increased level of risk .
Between 2007-08 and 2011-12 the proportions of men and women at increased risk rose, from 55.4% to 59.6% respectively for men, and 63.8% to 66.3% respectively for women. However, between 2011-12 and 2014-15 the proportions have remained stable. This corresponds with the slowing in recent years of the trend in increases in the proportion of Australians who are overweight or obese based on Body Mass Index .
- Australian Bureau of Statistics (ABS) Waist circumference, 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.
A waist measurement of 94cm or more for men or 80cm or more for women indicates that a person is at increased risk of developing chronic disease .
- World Health Organisation, 2000, Obesity: preventing and managing the global epidemic. Report of a WHO Consultation, 2000. Available from: http://libdoc.who.int/trs/WHO_TRS_894.pdf.
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 a waist circumference increasing risk or substantially increasing risk of developing chronic disease
Denominator: Male, female or total population aged 18 years and over
Detail of analysis: Indirectly age-standardised rate per 100 population (aged 18 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.