In a life threatening emergency dial Triple Zero (000)
Call Mental Health Triage on
1800 629 354
(free call except from mobiles or public phones) or
For a poison emergency in Australia call
13 11 26
Drug and Alcohol Help Line
The Drug and Alcohol Help Line is available 24-hours, 7 days a week on
Health Protection Service
For after hours urgent public health matters including environmental health, radiation safety, food poisoning and communicable disease management phone:
02 5124 9700
24 hour health advice
1800 022 222
ACT State Emergency Service
during flood or storms
The majority of respondents to the 2021 ACT General Health Survey aged 18 years and over described their weight as healthy (52.3%). While males (55.7%) were slightly more likely to describe their weight as healthy than females (49.0%), this difference was not statistically significant.
Note: The indicator shows self-reported data collected through Computer Assisted Telephone Interviewing (CATI). Estimates were weighted to adjust for differences in the probability of selection among respondents and were benchmarked to the estimated residential population using the latest available Australian Bureau of Statistics population estimates.
Persons includes male, female, other and refused sex respondents and may not always add to the sum of male and female.
The following estimates have a relative standard error between 25% and 50% and should be used with caution:
- 2018: underweight males, underweight females, very overweight males
- 2019: underweight males, underweight females
- 2020: underweight persons, underweight males
- 2021: underweight males, very overweight males, underweight females.
The following estimates have not been published due to small numbers or a relative standard error greater than 50%:
- 2020: underweight and very overweight females.
Statistically significant differences are difficult to detect for smaller jurisdictions such as the Australian Capital Territory. Sometimes, even large apparent differences may not be statistically significant. This is particularly the case in breakdowns of small populations because the small sample size means that there is not enough power to identify even large differences as statistically significant.