Notes on the data: Health risk factors

Estimated male, female or total population, aged 18 years and over, who were obese or overweight, 2017-18

 

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 [1]. 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 [1].

Over more than two decades from 1995 to 2017-18, the proportion of the Australian population aged 18 years and over who were overweight or obese increased by 19.0%, from 56.3% to 67.0%: the increase was greater for females (27.0%) than for males (17.0%). Of major concern is that whereas the proportion who are overweight has decreased slightly for males (down by 7%) and increased only slightly for females (up by 3%), the proportion who are obese has gone up by 67%, from 18.7% to 31.3%. The increase in obesity for males was greater than for females, at 75.7% and 65.9%, respectively [2].

The increase, from 2014–15 to 2017–18, in the proportion of the Australian population aged 18 years and over who were overweight or obese was also driven by an increase in those categorised as obese [3].

In 2017-18, the proportion of adults aged 18 years and over who were overweight or obese in general increased with age. However, there was a large increase for those aged 18-24 years, with 38.9% overweight or obese in 2014-15 compared with 46.0% in 2017-18 [3].

A fact sheet on obesity and overweight rates can be accessed here.

References

  1. Australian Bureau of Statistics (ABS). Measures of Australia’s progress, 2010. (ABS Cat. no. 1370.0). Canberra: ABS; 2010.
  2. Australian Bureau of Statistics (ABS). Unpublished.
  3. Australian Bureau of Statistics (ABS). Overweight and obesity. 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~Overweight%20and%20obesity~90: last accessed 15 October 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 at the Population Health Area (PHA) level for selected health risk factors from the 2017–18 National Health Survey (NHS), conducted by the Australian Bureau of Statistics (ABS). The estimates at the Population Health Area (PHA) are modelled estimates produced by the ABS (estimates at the Local Government Area (LGA) and Primary Health Network (PHN) level were derived from the PHA estimates).

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.

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

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 NHS 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 66.2% of persons 18 years and over in the sample who had their height and weight measured. For respondents who did not have their height and weight measured, imputation was used to obtain height, weight and BMI scores. For more information refer to Appendix 2: Physical measurements in the ABS publication National Health Survey: First Results, 2017-18 (Cat. no. 4364.0.55.001).

 

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 males, females or persons aged 18 years and over who were assessed as being overweight (not obese) or obese, based on their measured height and weight

 

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

 

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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