Attitudes and perceptions towards drugs by region

This interactive figure illustrates a selection of attitudes and perceptions towards alcohol, tobacco, cannabis, and other illicit drugs by region, as measured among people aged 14 and over in 2022–2023.

There are two steps for people to interact with the figure. The first step allows people to enter a postcode, which will result in the figure displaying the region that the postcode is located within. The second step allows people to explore the findings in the displayed region for one of four drug types: alcohol, tobacco, cannabis, or other illicit drugs.

If the drug type of alcohol is selected, the figure will display the measure people most supported to reduce the problems associated with excessive alcohol use, and the measure people most opposed. It will also display the measure in the selected region that had the largest difference to the national average.

If the drug type of tobacco is selected, the figure will display the measure people most supported to reduce tobacco use and the measure people most opposed. The figure will also display the measure in the selected region that had the largest difference to the national average.

If the drug type of cannabis is selected, the figure will display results within the selected region regarding the legality of cannabis and cannabis possession, and the proportion of people who believe they would try cannabis if it were legal.

If the drug type of other illicit is selected, the figure will display the proportions of people in the selected region that supported drug checking services, legalisation of ecstasy, and support for measures relating to harm reduction and law enforcement.

Definitions

Measures of support and approval

• People were asked to indicate how strongly they would support or oppose specific policies, or whether they personally approve or disapprove, using a 5-point scale. Unless otherwise stated, proportions for ‘support’ include people who selected “Support” and “Strongly support” in the survey. Similarly, proportions for ‘oppose’ include responses of “Oppose” and “Strongly oppose”, and proportions for ‘approve’ include responses of “Approve” and “Strongly approve”.
• Respondents who selected “Don’t know enough to say” have been removed from the denominator for all proportions. As such, proportions of support or opposition are expressed as proportions of those who believed they knew enough about the statement to express their level of support.

Measures with the largest difference or change

• The measures with the largest difference to the National proportion were chosen by examining the difference between the result for that region and the National result, relative to the National proportion.
• Similarly, the measures with the largest change since 2010 were chosen by examining the difference between the 2022–2023 proportion and the 2010 proportion, relative to the 2010 proportion.

Geographic data

Household selection process

• The survey sample was selected using stratified, multistage random sampling. There were 15 strata in total, including the capital city and ‘rest of state’ for each state and territory, except for the Australian Capital Territory which operated as one stratum.
• Statistical Areas are a geographic classification defined by the Australian Bureau of Statistics Australian Statistical Geography Standard (ASGS). They encompass 4 levels, with increasing size and population: Statistical Areas Level 1 (SA1); Statistical Areas Level 2 (SA2); Statistical Areas Level 3 (SA3); and Statistical Areas Level 4 (SA4). For population sizes of Statistical areas see Australian Statistical Geography Standard (ASGS): Main Structure and Greater Capital City Statistical Areas.
• For capital city strata, SA1s were selected with probability proportional to the number of private households in the area. The major regional centres of Illawarra, Newcastle and Lake Macquarie, Geelong, Cairns, Gold Coast, and Sunshine Coast also used this SA1 selection process, to reduce geographical clustering.
• In all other areas in the ’rest of state’ strata, SA2s were selected for the first stage, with probability proportional to the number of households within the area. From within each selected SA2, SA1s were selected with probability proportional to the number of private households calculated in the same way.

Differences in 2010 survey

• While the same 15 strata were used in selecting the sample for the 2010 National Drug Strategy Household Survey, geographic areas were instead defined according to the 2006 Australian Standard Geographical Classification (ASGC):
• For capital city strata, Census Collection Districts (CCDs) were selected with the probability proportional to the number of private households in the district.
• In all other areas, Statistical Local Areas (SLAs) were chosen as the first stage instead, with CCDs selected within each SLA proportional to the number of private households at the 2006 Census.

Geographic presentation in this release

• This data visualisation presents data at the smallest geographic area possible. For all jurisdictions except the Australian Capital Territory, this has resulted in data being presented at the SA4 level. Due to the oversampling in the Australian Capital Territory, and the relatively low number of SA3s in the area, data were robust enough to be presented at the SA3 level.
• Survey data were assigned to SA4/SA3 in the 2021 ASGS based on where the household was located:
  • 2022–2023: As SA1s are entirely located within SA3s and SA4s, survey responses were simply assigned to the relevant geographic area in 2022–2023.
  • 2010: As many CCDs cross SA3 and SA4 boundaries, survey responses were assigned to 2011 ASGS SA2s proportionally, based on how much of the CCD was in each SA2. Then 2011 SA2s were assigned proportionally to 2021 SA2s, which were then grouped to the SA3/SA4 level.
• All correspondences between SAs (both 2011 and 2021) were sourced from the Australian Bureau of Statistics release Australian Statistical Geography Standard (ASGS): Main Structure and Greater Capital City Statistical Areas. Correspondences between CCDs and 2011 SA2s were sourced from Australian Statistical Geography Standard (ASGS): Correspondences, July 2011.

Geographic areas with missing or unreliable data

• Due to the stratified random sampling approach, no data were collected in some statistical areas. This includes all statistical areas in Other Territories, those used for No Usual Address and those used for Migratory – Offshore – Shipping purposes. Additionally, the following areas had no data collected in 2022–2023:
  • Riverina (113)
  • North West (215)
  • Uriarra – Namadgi (80111)
• Where data are not available for an area, postcodes have been removed from the data visualisation so that they cannot be selected.
• Some statistical areas did appear in the survey collection, but the data were considered too unreliable to be reported on their own. This can occur when the sample size is too small, or when very few SA2s were sampled within an SA4 (meaning that results cannot be generalised to the broader SA4).
• In these cases, SA4s were grouped together, to ensure that all data were reported where possible. SA4s were grouped together if there was a data quality issue (e.g. small sample size or large sampling error), provided they were adjacent, the sampled SA2s were located close to the neighbouring SA4, and groupings did not cross State and Territory boundaries. The approach was applied for grouping SA3s in the ACT.
• Data for the following statistical areas were combined to ensure all data could be presented reliably:
  • Coffs Harbour – Grafton (104) and New England and North West (110)
  • Far West and Orana (105) and Murray (109)
  • Illawarra (107) and Southern Highlands and Shoalhaven (114)
  • Ballarat (201) and Warrnambool and South West (217)
  • Brisbane – West (304) and Moreton Bay – South (314)
  • Darling Downs – Maranoa (307) and Queensland – Outback (315)
  • Ipswich (310) and Toowoomba (317)
  • Barossa – Yorke – Mid North (405) and South Australia – South East (407)
  • Bunbury (501) and Mandurah (502)
  • Western Australia – Outback (North) (510) and Western Australia – Outback (South) (511)
  • Launceston and North East (602) and South East (603)
  • Belconnen (80101) and Molonglo (80110)
  • Weston Creek (80108) and Woden Valley (80109)
  • Canberra East (80103) and South Canberra (80106)

Postcode selection

• The data visualisation tool presents data at the SA4 or SA3 level, depending on where the selected postcode is found. Postcodes were assigned to the geographic region that they had the highest proportion of area in.
• In 2022–2023, due to data availability, Postal Areas are applied in mapping. Postal Areas are an ABS Mesh Block approximation of a general definition of postcodes. They enable comparison of ABS data with other data collected using postcodes as the geographic reference. ABS approximations of administrative boundaries do not match official legal boundaries and should only be used for statistical purposes. Postal Areas were mapped to SA3s using Australian Statistical Geography Standard (ASGS): Edition 3 - Postal Areas.
• Postcodes (Postal Areas) that map to regions where data is not available (e.g., Riverina) and those that do not map to any reported SA4 or SA3 cannot be selected in the data visualisation.