Notes on the data: Health risk factors
Estimated male, female or total population, aged 18 years and over, consuming alcohol at levels considered to be a high risk to health over their lifetime, 2017-18
Policy context: Excessive alcohol consumption is a major risk factor for morbidity and mortality; and the harmful use of alcohol is the world’s third largest risk factor for disease burden . Harmful drinking is a major determinant of neuropsychiatric disorders, such as alcohol use disorders and epilepsy and other noncommunicable diseases such as cardiovascular diseases, cirrhosis of the liver and various cancers. The harmful use of alcohol is also associated with several infectious diseases as alcohol consumption weakens the immune system .
Excessive alcohol consumption also causes harm beyond the physical and psychological health of the drinker in that it can harm the wellbeing and health of people around the drinker. A significant proportion of the disease burden attributable to harmful drinking arises from unintentional and intentional injuries, including those due to road traffic accidents, violence, and suicides . As a result, alcohol is associated with many serious social and developmental issues, including many forms of violence, child neglect and abuse, and absenteeism in the workplace.
In 2017-18, 16.1% of people aged 18 years and over consumed more than two standard drinks per day on average, exceeding the lifetime risk guideline. down from 21.9% in 2004-05 .
- World Health Organization (WHO). Alcohol - Fact sheet. 2011 Feb. Available from: http://www.who.int/mediacentre/factsheets/fs349/en/; last accessed 18 October 2013.
- Australian Bureau of Statistics (ABS) National Health Survey: First Results, 2017-18 — Australia. Canberra: ABS; 2018. Available from: Australia https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4364.0.55.0012017-18?OpenDocument; last accessed 14 January 2020.
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.
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.
The National Health and Medical Research Council guidelines for lifetime risk state that, for healthy men and women, drinking no more than two standard drinks on any day reduces the lifetime risk of harm from alcohol-related disease or injury. The data are for people aged 18 years and over.
Note that this indicator was previously published for the 2014-15 NHS for people aged 15 years and over.
Geography: Data available by Population Health Area, Local Government Area, Primary Health Network, quintile of socioeconomic disadvantage of area and Remoteness Area
Numerator: Estimated population aged 18 years and over who consumed more than two standard alcoholic drinks per day on average, exceeding the lifetime risk 2009 National Health and Medical Research Council (NHMRC) guideline
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
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.