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Body Mass Index (BMI) is a simple index of weight-for-height that is commonly used to classify underweight, healthy weight, overweight and obesity.
BMI for adults aged 18 years and over are grouped as follows:
Underweight: BMI less than 18.5
Healthy weight: BMI 18.5 - 24.99
Overweight: BMI 25.00 - 29.99
Obese class 1: BMI 30.00 - 34.99
Obese class 2: BMI 35.00 - 39.99
Obese class 3: BMI 40 or more
Source: https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4363.0Glossary12017-18?OpenDocument.
1.7% of respondents to the 2021 ACT General Health Survey aged 18 years and over were classified as being underweight, 36.1% were a healthy weight, 35.5% were overweight, 15.6% were obese class I and 11.1% were obese class II and III. In 2021, males (40.5%) were significantly more likely to be classified as overweight than females (30.6%). There was no significant difference between males and females in the other BMI categories in 2021.
BMI is based on self-reported height and weight. To calculate BMI, weight in kilograms was divided by the square of height in metres.
For the purpose of reporting the ACT General Health Survey data on HealthStats, if the 95% confidence intervals of the estimates do not overlap, they are considered to be significantly different.
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.
Data for BMI are not collected every third year (i.e. 2019 and 2022).
Persons includes respondents who identified as male, female, other and those who refused to answer and may not always add to the sum of male and female.
The following estimates have a relative standard error of 25% to 50% and should be used with caution:
- 2011/12: underweight males, females, respondents aged 18 to 24 years, 45 to 64 years and 65 years and over
- 2013/14: underweight males, females, respondents aged 45 to 64 years and 65 years and over and overweight and obese class I respondents aged 18 to 24 years
- 2015/16: underweight females, respondents aged 45 to 64 years and 65 years and over and obese class II and III respondents aged 25 to 44 years
- 2018: underweight persons and females and overweight respondents aged 18 to 24 years
- 2020: underweight persons, overweight respondents aged 18 to 24 years, obese class I respondents aged 65 years and over and obese class II and III respondents aged 65 years and over
- 2021: underweight persons and females and overweight respondents aged 18 to 24 years.
The following estimates have not been published due to small numbers or a relative standard error greater than 50%:
-2011/12: underweight respondents aged 25 to 44 years obese class I and obese class II and III respondents aged 18 to 24 years
- 2013/14: underweight respondents aged 18 to 24 years and 25 to 44 years, obese class II and III respondents aged 18 to 24 years
- 2015/16: underweight males and respondents aged 18 to 24 years and obese class I and obese class II and III respondents aged 18 to 24 years
- 2018: underweight males, respondents aged 18 to 24 years, 25 to 44 years, 45 to 64 years and 65 years and over and obese class I and obese class II and III respondents aged 18 to 24 years
- 2020: underweight males and females, respondents aged 18 to 24 years, 25 to 44 years, 45 to 64 years and 65 years and over and obese class I and obese class II and III respondents aged 18 to 24 years
- 2021: underweight males, respondents aged 18 to 24 years, 25 to 44 years, 45 to 64 years and 65 years and over and obese class I and obese class II and III respondents aged 18 to 24 years.
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.