Notes on the data: Chronic diseases and conditions

Estimated population, aged 18 years and over, with diabetes mellitus, 2011-12

 

Note: The indicators of chronic diseases and conditions have not been updated to reflect information in the 2014–15 National Health Survey. The modelling of these estimates has been held over until a final decision is made as to access by PHIDU to small area data considered to be highly relevant for use as small area predictors in the production of these estimates. For example, for the indicator of diabetes type 2, the MBS item for HbA1c and, for mental health conditions, anti-depressant medications from PBS both add strength to the available predictors. Work will proceed with the current predictors until these data is made available.

 

Policy context:  Diabetes mellitus is a chronic disease characterised by high blood glucose levels resulting from defective insulin production, insulin action or both [1]. There are a number of different forms of diabetes, which can cause a number of serious complications, especially cardiovascular, eye and renal diseases.

Aboriginal and Torres Strait Islander peoples and others who are socioeconomically disadvantaged are at higher risk of developing diabetes mellitus, and have much greater hospitalisation and death rates from diabetes than other Australians.

Reference

  1. World Health Organization (WHO). Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus. Geneva: Department of Noncommunicable Disease Surveillance, WHO; 1999.
 

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, conducted by the Australian Bureau of Statistics (ABS).

Estimates at the Population Health Area (PHA) 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 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:

  1. non-private dwellings (hospitals, gaols, nursing homes - and also excludes members of the armed forces);
  2. in Very Remote areas;
  3. in discrete Aboriginal communities; and
  4. where the relative root mean square errors (RRMSEs) on the estimates was 1 or more (estimate replaced with ≠)

Notes:

  1. 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.
  2. 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.

Indicator detail

The prevalence of diabetes mellitus was measured by a glycosylated haemoglobin test (commonly referred to as HbA1c), derived from tests on blood samples from volunteering participants selected as part of the AHS: people with an HbA1c level of greater than or equal to 6.5% were recorded as having diabetes mellitus (6.5% is the World Health Organization’s recommended diagnostic cut-off point for diabetes mellitus).

 

Numerator:  Estimated number of people aged 18 years and over with diabetes mellitus

 

Denominator:  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

 

Source:  

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 2011-12 Australian Health Survey, ABS Survey TableBuilder.

 

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