Notes on the data: COMPOSITE INDICATORS
Estimated population, aged 18 years and over, who were obese or overweight and had type 2 diabetes mellitus, 2014–15
Policy context: Each increment in a person's body weight above their optimal level is associated with an increase in the risk of ill health. Overweight arises through an energy imbalance over a sustained period of time. While many factors may influence a person's weight, weight gain is essentially due to the energy intake from the diet being greater than the energy expended through physical activity. The energy imbalance need only be minor for weight gain to occur, and some people, due to genetic and biological factors, may be more likely to gain weight than others. Overweight is associated with higher mortality and morbidity, and those who are already overweight have a higher risk of becoming obese.
Being obese has significant health, social and economic impacts, and is closely related to lack of exercise and to diet . Obesity increases the risk of suffering from a range of health conditions, including coronary heart disease, type 2 diabetes, some cancers, knee and hip problems, and sleep apnoea .
In 2014-15, 311,000 (or 1.8%) people aged 18 years and over had type 2 diabetes and were overweight and 575,000 (or 3.3%) people aged 18 years and over had type 2 diabetes and were obese.
- Australian Bureau of Statistics (ABS). Measures of Australia’s progress, 2010. (ABS Cat. no. 1370.0). Canberra: ABS; 2010
Notes: In the absence of data from administrative data sets, estimates are provided for certain chronic diseases and conditions from the 2014–15 National Health Survey (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.
The Body Mass Index (BMI) (or Quetelet's index) is a measure of relative weight based on an individual's mass and height. The height (cm) and weight (kg) of respondents, as measured during the AHS interview, were used to calculate the BMI, and overweight (but not obesity) was determined where a person’s BMI was between 25 and less than 30. Adults with a BMI equaling 30 or over where classified as obese. The BMI is a useful tool at a population level for measuring trends in body weight, and helping to define population groups who are at higher risk of becoming obese, and therefore developing long-term medical conditions associated with a high BMI, such as type 2 diabetes and cardiovascular disease. Note that the modelled estimates are based on the 84.3% of persons 18 years and over in the sample who had their height and weight measured.
Persons with type 2 diabetes refers to respondents who self-reported having been told by a doctor or nurse that they had type 2 diabetes mellitus, irrespective of whether the person considered their diabetes to be current or long-term.
Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, Quintiles and Remoteness Areas
Numerator: Estimated number of people aged 18 years and over with type 2 diabetes and were assessed as being obese or overweight (not obese) based on their measured height and weight
Denominator: 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.