Data sources
This page outlines the data sources used for this report.
This report uses data from the Australian Bureau of Statistics’ (ABS) latest National Health Measure Survey (NHMS) 2022–24 to estimate the prevalence of overweight and obesity, and abdominal overweight and obesity. This data source was chosen because it provides nationally representative measured height, weight and waist circumference data, which were used to derive BMI categories and waist circumference risk.
The latest 2022–24 NHMS pools together measured data from the 2022 NHS and the 2023 National Nutrition and Physical Activity Survey (NNPAS) to create a larger sample for analysis.
When interpreting data from the NHMS 2022–24, some limitations need to be considered:
- The scope of the surveys was restricted to residents of private dwellings, and excluded residents of non-private dwellings such as hospitals, nursing homes, hotels, motels and boarding schools.
- Residents of Very remote areas and discrete Aboriginal and Torres Strait Islander communities were excluded from the survey. This is unlikely to affect national estimates but will impact prevalence estimates by remoteness.
- Physical measurements such as measured height, weight and waist circumference have relatively high rates of non-response due to their voluntary and sensitive nature.
- The non-response rate:
- for measured height and weight in adults was 48% in the 2022 NHS and 36% in the 2023 NNPAS.
- for measured height and weight in children was 57% in the 2022 NHS and 45% in the 2023 NNPAS.
- for measured waist circumference in adults was 39% in the 2022 NHS and 34% in the 2023 NNPAS.
- The process of imputation (done separately on the 2022 NHS and the 2023 NNPAS) was used to estimate missing data for measured height, weight and waist circumference. In this method, participants with a missing response were given the response of similar participants.
For more information, see Intergenerational Health and Mental Health Study methodology.
To report on trends in overweight and obesity, this report used the following ABS data sources:
- 2017–18 NHS
- 2014–15 NHS
- 2011–12 Australian Health Survey (AHS)
- 2007–08 NHS
- 1995 National Nutrition Survey (NNS).
These data sources were chosen because they provide nationally representative measured height, weight and waist circumference data, which were used to derive BMI categories and waist circumference risk.
When interpreting data from these surveys, some limitations need to be considered:
- The scope of the surveys was restricted to residents of private dwellings, and excluded residents of non-private dwellings such as hospitals, nursing homes, hotels, motels and boarding schools.
- Residents of Very remote areas and discrete Aboriginal and Torres Strait Islander communities were excluded from the surveys. This is unlikely to affect national estimates but will impact prevalence estimates by remoteness.
- The response rates for physical measures varied between surveys with decreasing response rates over time. The ABS imputed BMI for those people for whom BMI was not measured in the 2014–15 NHS and 2017–18 NHS. The imputation method for the 2014–15 NHS was similar to the 2017–18 NHS except it did not use self-reported BMI (ABS 2015).
- There was no imputation of BMI in the 1995 NNS, 2007–08 NHS and 2011–12 AHS and participants without a measured BMI were excluded from analysis.
Information about the surveys, including methodology and data quality statements, is available on the ABS website.
To report on the prevalence of overweight and obesity for Aboriginal and Torres Strait Islander (First Nations) people, the following ABS data sources were used:
- 2022–23 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS)
- 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS)
- 2012–13 Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS).
These surveys collected information on long-term health conditions and risk factors which may affect health, such as fruit and vegetable consumption and physical activity. Measured height, weight and waist circumference were also collected.
When interpreting data from the 2022–23 NATSIHS, some limitations need to be considered:
- The scope of the scope of the surveys was restricted to First Nations people living in private dwellings, and excluded residents of non-private dwellings such as hospitals, nursing homes, hotels, motels and boarding schools. The overall coverage of the 2022–23 NATSIHS was approximately 25% of Aboriginal and Torres Strait Islander persons in Australia. The final sample was weight to population benchmarks which align with the scope of the survey to account for under coverage.
- Physical measurements such as measured height, weight and waist circumference have relatively high rates of non-response due to their voluntary and sensitive nature. The non-response rates have also increased over time. In 2022–23, the non-response rates:
- for measured height and weight in adults was 48%
- for measured height and weight in children was 62%
- for measured waist circumference in adults was 47%.
- The process of imputation was used to estimate missing data for measured height, weight and waist circumference. In this method, participants with a missing response were given the response of similar participants.
For more information, see the National Aboriginal and Torres Strait Islander Health Survey methodology.
The National Hospital Morbidity Database (NHMD) is a compilation of episode-level records from admitted patient morbidity data collection systems in Australian hospitals.
Reporting to the NHMD occurs at the end of a person’s admitted episode of care (separation or hospitalisation) and is based on the clinical documentation for that hospitalisation.
The NHMD is based on the Admitted Patient Care National Minimum Data Set (APC NMDS). It records information on admitted patient care (hospitalisations) in essentially all hospitals in Australia, and includes demographic, administrative and length-of-stay data, as well as data on the diagnoses of the patients, the procedures they underwent in hospital and external causes of injury and poisoning.
The hospital separations data do not include episodes of non-admitted patient care given in outpatient clinics or emergency departments. Patients in these settings may be admitted subsequently, with the care provided to them as admitted patients being included in the NHMD.
The following care types were excluded when undertaking the analysis: 7.3 (newborn – unqualified days only), 9 (organ procurement – posthumous) and 10 (hospital boarder).
Further information about the NHMD can be found in Admitted patient care NMDS 2023–24- external site opens in new window.
The National Mortality Database (NMD) comprises information about causes of death and other characteristics of the person, such as sex, age at death, area of usual residence and Indigenous status. The cause of death data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the ABS. The data are maintained by the AIHW in the NMD.
The data quality statements underpinning the AIHW NMD can be found in the following ABS publications:
- ABS quality declaration summary for Deaths, Australia- external site opens in new window.
- ABS quality declaration summary for Causes of death, Australia- external site opens in new window.
For more information see National Mortality Database (NMD).
The Australian Burden of Disease Study undertaken by the AIHW provides information on the burden of disease for the Australian population. Burden of disease analysis measures the impact of fatal (years of life lost, YLL) and non-fatal burden (years lived with disability, YLD), with the sum of non-fatal and fatal burden equating to the total burden (disability-adjusted life year, DALY).
The Australian Burden of Disease Study 2024 includes national estimates for 220 diseases and injuries in 2024 based on projections using historical trends in data. Projected estimates were done for the first time in ABDS 2022 and have been updated annually since. Burden estimates may be revised in the future as more data become available
ABDS 2024 also includes updated estimates of attributable burden due to selected modifiable risk factors, which were last updated as part of ABDS 2018.
The 2018 study also includes a component on risk factor burden and the impact and causes of illness and death in First Nations people. The 2022 First Nations Burden of Disease Study provides latest estimates of the burden of disease for First Nations people.
General methods for estimation of burden of disease can be found in Australian Burden of Disease Study: methods and supplementary material 2018. This includes descriptions for years of life lost (YLL), years lived with disability (YLD), disability-adjusted life years (DALY) and health-adjusted life expectancy (HALE).
For further information see Burden of disease
The AIHW Disease Expenditure Database provides a broad picture of the use of health system resources classified by disease groups and conditions.
It contains estimates of expenditure by Australian Burden of Disease Study conditions, age group, and sex for public and private hospital admitted patients, public hospital emergency department, public hospital outpatient services, primary health care (general practitioner services, dental expenditure, allied health and other services, pharmaceutical benefits scheme) and referred medical services (medical imaging, pathology and specialist services).
It does not allocate all expenditure on health goods and services by disease – for example, neither administration expenditure nor capital expenditure can be meaningfully attributed to any particular condition due to their nature.
For more information and details on the methods used, see: