Notes on the data: Chronic diseases and conditions

Estimated population with arthritis, 2017–18

 

Policy context:  Arthritis is a collective term for a range of inflammatory conditions that affect joints, muscles and bones within the body, they include osteoarthritis, rheumatoid arthritis, juvenile arthritis and gout. These conditions can cause symptoms include pain, stiffness, swelling and redness in affected joints contributing to pain, illness and disability, impacting on one’s quality of life and wellbeing [1].

According to self-reported data from the National Health Survey 2017-18, arthritis affects around 3.6 million Australians or 15% of the total population. Arthritis is more prevalent in females (17.9%) than males (12.1%), a pattern which has been steady since 2004-05. Arthritis is common particularly among older Australians as prevalence of arthritis also increases with age [2].

References

  1. Australian Institute of Health and Welfare (AIHW). Athritis. Cat. no. PHE 234. 2019. Canberra: AIHW. Available from:https://www.aihw.gov.au/reports/chronic-musculoskeletal-conditions/arthritis; last accessed 10 December 2019.
  2. Australian Bureau of Statistics (ABS). Arthritis and Osteoporosis. National Health Survey: First Results, 2017–18 — Australia. Canberra: ABS; 2018. Available from: https://www.abs.gov.au/ausstats/abs@.nsf/Lookup/by%20Subject/4364.0.55.001~2017-18~Main%20Features~Arthritis%20and%20osteoporosis~30; last accessed 10 December 2019
 

Notes:

Differences from data published by the Australian Bureau of Statistics (ABS):

Data by quintile of socioeconomic disadvantage and Remoteness will differ to the extent that data extracted from Survey TableBuilder have been randomised, whereas those published by the ABS are not. In addition, rates published by the ABS for modelled estimates are generally crude rates; rates published by PHIDU are age-standardised.

Modelled Estimates:

In the absence of data from administrative data sets, estimates are provided for selected health risk factors from the 2017–18 National Health Survey (NHS), conducted by the Australian Bureau of Statistics (ABS). Details of the method used and accuracy of results are available from the ABS paper Explanatory Notes: Modelled estimates for small areas based on the 2017-18 National Health Survey, available here.

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 the PHA estimates).

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 geographic correspondence files.

Estimates for quintile of socioeconomic disadvantage of area and Remoteness Area 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 (xlsx) and viewable in the column 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 relatively high survey response rate in the NHS 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 very remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities; whereas these areas comprise less than 3% of the total population, Aboriginal people comprise up to one third of the population. The survey does not include persons usually resident in non-private dwellings (hospitals, gaols, nursing homes - and also excludes members of the armed forces).

This and other limitations of the method mean that estimates have not been published for PHAs with populations under 1,000.

The ABS used a number of methods to measure the quality of the estimates, one of which is the relative root mean squared error (RRMSE) of the modelled estimates. The RRMSEs are included with the data. Users are advised that:

  • estimates with RRMSEs less than 25% are considered reliable for most purposes;
  • 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.

Indicator detail

These data refer to respondents who were asked whether they have, or had ever had:

  • gout;
  • rheumatism;
  • arthritis;
  • osteoarthritis;
  • rheumatoid arthritis;
  • other types of arthritis.

If they reported either gout or rheumatism, they were then asked whether their condition was expected to last for six months or more. If they identified an arthritis condition, other than gout or rheumatism, they were asked whether they had ever been told by a doctor or nurse that they have the condition. Only persons whose arthritis was current and long-term were recorded as having arthritis. Persons who reported having arthritis, which was not current and long-term, were recorded as not having arthritis. 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.

Arthritis is defined as osteoarthritis, rheumatoid arthritis and other arthritis or type unknown, that is current and long-term.

 

Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, quintile of socioeconomic disadvantage of area and Remoteness Area

 

Numerator:  Estimated number of people with arthritis 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

 

Source:  

PHA, LGA & PHN: Age-standardised rates are based on Australian Bureau of Statistics data, produced as a consultancy for PHIDU, from the 2017—18 National Health Survey.

Quintiles & Remoteness: Compiled by PHIDU based on direct estimates from the 2017–18 National Health Survey, ABS Survey TableBuilder.

 

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