National Health Survey: First Results methodology

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About this survey


The 2020-21 National Health Survey (NHS) was conducted from August 2020 to June 2021. Data was collected from approximately 11,000 households around Australia.

The survey focused on the health status of Australians and health-related aspects of their lifestyles. Information was collected about respondents' long-term health conditions and on lifestyle factors which may affect health, such as tobacco smoking, alcohol consumption, fruit and vegetable consumption, sugar sweetened and diet drink consumption, and physical activity. Self-reported health status, height, weight, body mass, and use of health services were also collected.

Several topics were included for the first time in 2020-21 including e-cigarettes/vaping, food security and stressors.  The topics of food security and stressors were introduced in response to the COVID-19 pandemic.

The survey also collected a standard set of information about respondents including age, sex, country of birth, main language, employment, education, and income.

Impact of COVID-19 on survey estimates

The 2020-21 NHS data should be considered a break in time series from previous NHS collections and used for point-in-time national analysis only. The survey was collected during the COVID-19 pandemic which significantly changed the data collection. To maintain the safety of survey respondents and ABS Interviewers, it was collected via an online, self-complete form. Non-response is usually reduced through Interviewer follow up of households who have not responded. As this was not possible, there were lower response rates than previous NHS cycles, which impacted sample representativeness for some sub-populations. Comparisons to previous health data over time are not possible.

In addition to the changes resulting from the pandemic and data collection via an online form, there were a number of other changes made to the 2020-21 NHS. This survey had a planned change to sample design and only nationally representative estimates are available – State and Territory estimates have not been produced. There have also been various changes to content, question modules, instrument design and output data items as detailed in Summary of content changes. This includes the exclusion of medications data being collected directly from respondents and a revision to the classification of long-term health conditions (refer to Health conditions for more details). Information on people’s medication usage is provided via Pharmaceutical Benefits Scheme (PBS) data linkage. 

How the data is collected


The scope of the survey is as follows:

  • Usual residents (URs) in Australia aged 0 years and over living in private dwellings
  • Both urban and remote areas in all states and territories, except for very remote parts of Australia and discrete Aboriginal and Torres Strait Islander communities
  • Members of the Australian permanent defence forces living in private dwellings and any overseas visitors who have been working or studying in Australia for the last 12 months or more, or intend to do so.

The following people were excluded:

  • visitors to private dwellings
  • overseas visitors who have not been working or studying in Australia for 12 months or more, or do not intend to do so
  • members of non-Australian defence forces stationed in Australia and their dependents
  • non-Australian diplomats, diplomatic staff and members of their households
  • people who usually live in non-private dwellings, such as hotels, motels, hostels, hospitals, nursing homes and short-stay caravan park (people in long-stay caravan parks, manufactured home estates and marinas are in scope)
  • people in very remote areas
  • discrete Aboriginal and Torres Strait Islander communities
  • households where all Usual Residents are less than 18 years of age.

Collection Method

Due to the COVID-19 pandemic, data was collected via a self-completed online form. There were no face-to-face interviews.

Sample design

Households were randomly selected to participate in the survey.

To complete the survey a member of the selected household was required to register and complete the household form. Then one adult aged 18 years and over and one child aged 0-17 years were randomly selected to complete individual questionnaires.

If the randomly selected person was aged 0-14 years a parent/guardian answered the questions on the child’s behalf.

If the randomly selected person was aged 15-17 years, parental/guardian consent was sought for the selected person to answer the questions. Where consent was not given a parent/guardian answered the questions on the selected person’s behalf. 

Proxy interviews were accepted for selected adults where the selected adult was present during the interview. This resulted in a large increase in proxy interviews for the 2020-21 NHS; approximately 20% of all adult interviews were completed by a proxy respondent. This could be attributed to the online form and greater ability for household members to complete it on behalf of the selected person.

All proxy interviews that were completed without the selected adult being present were removed. This was because it would be difficult for questions in the NHS to be answered by another person without the selected adult being a present and active participant in the survey.

Response rates

There were 11,110 fully responding households in the survey, or approximately 35% of the sample approached. The following table summarises the response rates achieved for the sample approached across Australia. Without face-to-face follow up for non-responding households, the level of response is much lower than usual. It was also harder to accurately determine levels of sample loss (e.g. vacant dwellings).

Response rates, Australia
 Total households approachedTotal households respondedResponse rate(a)

(a) Rate of response is calculated out of total sample approached.


The survey collected the following content:

  • Demographics - Age, Sex, Country of Birth, Main language spoken, Marital status
  • Household details - Type, Size, Household composition, Tenure, SEIFA, Geography
  • Labour force status
  • Educational attainment
  • Personal and Household Income
  • Migrant and Visa status
  • Self-assessed health status
  • Self-reported height, weight and body mass
  • Long-term health conditions such as arthritis, asthma, cancer, diabetes, hypertension, kidney disease etc
  • Risk factors such as tobacco smoking, e-cigarettes/vaping, alcohol consumption, fruit and vegetable consumption, sugar sweetened and diet drink consumption, and physical activity
  • Health service use
  • Bodily pain
  • Psychological distress

There were no physical measurements collected in 2020-21 NHS, such as blood pressure, height, weight and waist. Refer to Summary of content changes for more details.

Information of the revised classification of long-term health conditions can be found in Health conditions.

See the Data Item List for full details of content collected in the 2020-21 NHS or the sample version of the questionnaire for how the data was asked of respondents.

How the data is processed

Estimation methods

As only a sample of people in Australia were surveyed, results needed to be converted into estimates for the whole population. This was done through a process called weighting:

  • Each person or household is given a number (known as a weight) to reflect how many people or households they represent in the whole population
  • A person or household’s initial weight is based on their probability of being selected in the sample. For example, if the probability of being selected in the survey was one in 45, then the person would have an initial weight of 45 (that is, they would represent 45 people).

The person and household level weights are then calibrated to align with independent estimates of the in-scope population, referred to as ‘benchmarks’. The benchmarks use additional information about the population to ensure that:

  • people or households in the sample represent people or households that are similar to them
  • the survey estimates reflect the distribution of the whole population, not the sample.

Benchmarks align to the estimated resident population (ERP) at December 2020 which was 9,782,954 households and 24,995,375 people (after exclusion of people living in non-private dwellings, very remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities).

Sample counts and weighted estimates are presented in the table below.

Sample counts and weighted estimates, Australia
Age group (years)'000'000'000
0 - 4402.0424.0826.0780.4735.61,516.0
5 - 9434.0396.0831.0818.2780.31,601.6
10 - 14443.0440.0888.0813.1768.31,592.0
15 - 19389.0342.0736.0826.5610.71,451.0
20 - 24169.0223.0394.0717.4854.41,579.0
25 - 29289.0329.0622.0816.1818.91,637.9
30 - 34378.0447.0825.01,014.01,047.12,061.1
35 - 39432.0534.0966.0816.5889.91,706.4
40 - 44439.0515.0958.0860.3843.21,708.7
45 - 49374.0486.0860.0719.7764.31,484.0
50 - 54386.0475.0863.0836.0860.91,703.9
55 - 59414.0506.0921.0719.3754.41,477.7
60 - 64417.0515.0932.0705.3762.91,468.2
65 - 69437.0521.0958.0585.7653.91,239.6
70 - 74414.0411.0826.0548.3555.01,104.0
75 - 79231.0241.0472.0421.5469.0890.5
80 - 84115.0145.0260.0207.3272.3479.6
85 years and over66.076.0143.0138.7155.3294.2
Total all ages6,2297,02613,28112,344.412,596.424,995.4

(a) Sample count after removing some adult interviews reporting via proxy.
(b) Total includes persons who provided a response other than male or female.

In 2020-21, data from five household surveys including the NHS was combined to produce the Household Surveys Pooled Dataset (HSPD) to enable more accurate smoker status estimates. Smoking estimates from the HSPD and NHS datasets were aligned through the weighting process, in that the NHS smoking data was benchmarked in such a way as to match the HSPD smoking estimates. However, with perturbation for confidentiality reasons, the smoking estimates produced from the separate datasets will not match exactly.


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Reliability of estimates

Two types of error are possible in estimates based on a sample survey: 

  • non-sampling error    
  • sampling error.

Non-sampling error

Non-sampling error is caused by factors other than those related to sample selection.  It is any factor that results in the data values not accurately reflecting the true value of the population.

It can occur at any stage throughout the survey process. Examples include:

  • selected people that do not respond (e.g. refusals, non-contact)
  • questions being misunderstood 
  • responses being incorrectly recorded 
  • errors in coding or processing the survey data.

Sampling error

Sampling error is the expected difference that can occur between the published estimates and the value that would have been produced if the whole population had been surveyed. Sampling error is the result of random variation and can be estimated using measures of variance in the data.

Standard error

One measure of sampling error is the standard error (SE). There are about two chances in three that an estimate will differ by less than one SE from the figure that would have been obtained if the whole population had been included. There are about 19 chances in 20 that an estimate will differ by less than two SEs.

Relative standard error

The relative standard error (RSE) is a useful measure of sampling error. It is the SE expressed as a percentage of the estimate:

\(RSE\% = \left( {\frac{{SE}}{{estimate}}} \right) \times 100\)

Only estimates with RSEs less than 25% are considered reliable for most purposes. Estimates with larger RSEs, between 25% and less than 50%, have been included in the publication, but are flagged to indicate they are subject to high SEs. These should be used with caution. Estimates with RSEs of 50% or more have also been flagged and are considered unreliable for most purposes. RSEs for these estimates are not published.

Margin of error for proportions

Another measure of sampling error is the Margin of Error (MOE). This describes the distance from the population value that the sample estimate is likely to be within and is particularly useful to understand the accuracy of proportion estimates. It is specified at a given level of confidence. Confidence levels typically used are 90%, 95% and 99%.

For example, at the 95% confidence level, the MOE indicates that there are about 19 chances in 20 that the estimate will differ by less than the specified MOE from the population value (the figure obtained if the whole population had been enumerated). The 95% MOE is calculated as 1.96 multiplied by the SE:

\({\mathop{\rm MOE}\nolimits} = SE \times 1.96\)

The RSE can also be used to directly calculate a 95% MOE by:

\({\mathop{\rm MOE}\nolimits} (y) \approx \frac{{RSE(y) \times y}}{{100}} \times 1.96\)

The MOEs in this publication are calculated at the 95% confidence level. This can easily be converted to a 90% confidence level by multiplying the MOE by:


or to a 99% confidence level by multiplying the MOE by:


Depending on how the estimate is to be used, an MOE of greater than 10% may be considered too large to inform decisions. For example, a proportion of 15% with an MOE of plus or minus 11% would mean the estimate could be anything from 4% to 26%. It is important to consider this range when using the estimates to make assertions about the population.

Confidence intervals

A confidence interval expresses the sampling error as a range in which the population value is expected to lie at a given level of confidence. A confidence interval is calculated by taking the estimate plus or minus the MOE of that estimate. In other terms, the 95% confidence interval is the estimate +/- MOE. 

Calculating measures of error

Proportions or percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. A formula to approximate the RSE of a proportion is given below. This formula is only valid when the numerator (x) is a subset of the denominator (y):

\({\mathop{\rm RSE}\nolimits} \left( {\frac{x}{y}} \right) \approx \sqrt {{{[RSE(x)]}^2} - {{[RSE(y)]}^2}} \)

When calculating measures of error, it may be useful to convert RSE or MOE to SE. This allows the use of standard formulas involving the SE. The SE can be obtained from RSE or MOE using the following formulas:

\(SE = \frac{{RSE\% \times estimate}}{{100}}\)

\(SE = \frac{{MOE}}{{1.96}}\)

Comparison of estimates

The difference between two survey estimates (counts or percentages) can also be calculated from published estimates. Such an estimate is also subject to sampling error. The sampling error of the difference between two estimates depends on their SEs and the relationship (correlation) between them. An approximate SE of the difference between two estimates (x - y) may be calculated by the following formula:

\(SE(x - y) \approx \sqrt {{{[SE(x)]}^2} + {{[SE(y)]}^2}} \)

While this formula will only be exact for differences between unrelated characteristics or sub-populations, it provides a reasonable approximation for the differences likely to be of interest in this publication. 

Significance testing

When comparing estimates between surveys or between populations within a survey, it is useful to determine whether apparent differences are 'real' differences or simply the product of differences between the survey samples. 

One way to examine this is to determine whether the difference between the estimates is statistically significant. This is done by calculating the standard error of the difference between two estimates (x and y) and using that to calculate the test statistic using the formula below:

\(\left( {\frac{{|x - y|}}{{SE(x - y)}}} \right)\)


\(SE(y) \approx \;\frac{{RSE(y) \times y}}{{100}}\)

If the value of the statistic is greater than 1.96, we can say there is good evidence of a statistically significant difference at 95% confidence levels between the two populations with respect to that characteristic. Otherwise, it cannot be stated with confidence that there is a real difference between the populations.

How the data is released

Release strategy

This release presents national health estimates for 2020-21. Commentary presents analysis by age groups, sex and selected population characteristics. The sample design of approximately 11,000 households is not sufficient to enable detailed analysis of state and territory estimates.

Data Cubes (spreadsheets) in this release present tables of estimates, proportions and their associated measures of error. A data item list is also available.

Detailed microdata is also available on DataLab for users who want to undertake interactive (real time) complex analysis of microdata in the secure ABS environment.


The Census and Statistics Act 1905 authorises the ABS to collect statistical information and requires that information is not published in a way that could identify a particular person or organisation. The ABS must make sure that information about individual respondents cannot be derived from published data.

To minimise the risk of identifying individuals in aggregate statistics, a technique called perturbation is used to randomly adjust cell values. Perturbation involves small random adjustment of the statistics which have a negligible impact on the underlying pattern. This is considered the most satisfactory technique for avoiding the release of identifiable data while maximising the range of information that can be released. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values in Data Cubes to derive a total may give a slightly different result to the published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.

Summary of content changes

The following table summarises content changes applied in the 2020-21 NHS. For full details of data items refer to the Data Item List.

2020-21 NHS Content Changes Summary
  • To improve and make the questionnaire more suitable for online reporting, information text boxes were added to questions, where applicable, to assist with respondents' understanding. In some topics, question skips were allowed to facilitate refusals, while in others, a specific Don't know check box was added.
  • Graphics were added to various modules to enhance user understanding and replace the need for prompt cards.  
  • New coder interface for country of birth, main language and conditions, using drop down lists, allowing for coder selection of free text to be entered.
  • Minor question and sequencing updates to improve comparability across other household surveys.
  • Minor question and sequencing updates to improve comparability across other household surveys.
  • New question design to improve comparability across household surveys and more accurate reporting.
Visa Status
  • New question module and associated outputs.
Health service use
  • Question module similar to the 2014-15 National Health Survey, but only 12 month time period captured.
  • Types of health professionals list updated.
Mental Health and Wellbeing
  • Soft refusals (question skips) allowed for K10 questions for online reporting.
Diet (includes fruit and vegetable consumption and sweetened and diet beverages consumption)
  • Changes to fruit and vegetable visual aids for serving sizes.
  • Question updates to fruit and vegetable number of serves to allow more accurate reporting and reporting against guidelines.
  • Sweetened and diet beverages question updates to reduce respondent burden.
  • Changes to sweetened and diet beverages visual aids.
  • Minor changes to question wording and improvements to question sequencing to improve data quality.
Physical Activity
  • Major updates to question module to improve respondent experience and allow for more accurate reporting.
  • Activity timing data captured for each individual day of the last week.
  • Outputs now include new physical activity day level, with daily timing data for each physical activity domain.
  • New questions and outputs on use of e-cigarettes and vaping.
Alcohol consumption
  • Alcohol consumption module updated to report consumption of common alcohol drink types instead of specific alcohol brands.
  • Redesigned daily consumption questions into matrix style to capture volume and number of drinks by alcohol type.
  • 12 month alcohol consumption questions re-ordered to reduce respondent burden.
  • Outputs updated to include new 2020 Alcohol Guidelines along side 2009 Alcohol Guidelines.
Health Conditions
  • Condition lists, similar to prompt cards, added to screen to assist with online only reporting.
  • Information boxes were added, where applicable, to assist with respondent understanding.
  • Minor changes to question wording and sequencing across all condition modules to improve online reporting and data quality.
  • Conditions coder updated and redesigned for use in online form as a drop down box.
  • User presented with suggested conditions which match search text.
  • Allows for free text or selected condition from coder. Some auto-coding of free text fields where common conditions reported.
Food security
  • New questions added in response to COVID-19.
  • New questions added in response to COVID-19.
Physical Measurements (height, weight, waist and blood pressure)
  • Not collected in 2020-21 National Health Survey.
  • Not collected in 2020-21 National Health Survey; data provided via linkage to PBS.

Health conditions

A long-term health condition was defined as a medical condition (illness, injury or disability) which was current at the time of interview and had lasted, or was expected to last, 6 months or more. 

Some reported conditions were assumed to be long-term, including asthma, arthritis, cancer, osteoporosis, diabetes, sight problems, rheumatic heart disease, heart attack, angina, heart failure and stroke. Diabetes, rheumatic heart disease, heart attack, angina, heart failure and stroke were also assumed to be current. Respondents could report multiple health conditions.

Any reported health conditions that did not meet this definition were excluded from estimates, e.g. a person may have been told that they had a health condition in the past but it is no longer current or expected to last 6 months or more.  Conditions that were not considered to be current and long term can be analysed using the data item Condition Status (CONDSTAT) on the survey microdata.

The classification hierarchy is based on the 10th revision of the International Classification of Diseases (ICD). The classification was updated for the 2020-21 NHS to improve use of the conditions data.

See the Data Item List for full details of the conditions classification used in the 2020-21 NHS.

A concordance for the current 2020-21 classification to the previous version used in the 2017-18 NHS is available on request.

Alcohol consumption

Alcohol consumption risk levels have been assessed using guidelines from the National Health and Medical Research Council (NHMRC) released from 2009 and updated in 2020. The updated guidelines were released after the 2020-21 NHS commenced collection.

Analysis in the commentary of the 2020-21 NHS has focussed on assessing alcohol consumption against the updated 2020 guideline. However, data has been provided in the Data Cubes to assess against the 2009 guidelines to provide a closure of this analysis. Analysis of the updated 2020 guidelines cannot be directly compared to the 2009 guidelines and therefore represents a break in time series.

Current 2020 guidelines

The most recent Australian Adult Alcohol Guideline, released by NHMRC in December 2020, is based on Guideline 1 of the Australian Guidelines to Reduce Health Risks From Drinking Alcohol. Guideline 1 recommends that ‘to reduce the risk of harm from alcohol-related disease or injury, healthy men and women should drink no more than 10 standard drinks a week and no more than 4 standard drinks on any one day. The less you drink, the lower your risk of harm from alcohol’. Persons aged 18 years and over who exceeded the Guideline have been interpreted as those who either consumed more than 10 standard drinks per week, or more than 4 standard drinks on a single day, or both components (i.e. groups A, B or C) (see the table below). The guidelines aim to reduce the risk of dying from alcohol-related disease and injury. Adults who drink within the Guideline recommendation have a less than 1 in 100 chance of dying from an alcohol-related condition (i.e. group D).

Additional advice was received that consuming more than 4 standard drinks on any day at least monthly in the last year was an appropriate measure in line with NHMRC recommendations. This means that those who consumed more than 4 standard drinks on any day at least monthly are considered to have exceeded the 1 in 100 chance of dying from an alcohol-related condition. This survey measures monthly consumption as consuming 5 or more drinks at least 12 or more times in the last 12 months. This measure is not directly comparable to single occasion risk interpreted from the NHMRC 2009 Guideline 2.

Guideline 1 Summary of Exceeded Alcohol Consumption Groups
 More than 4 standard drinks on any one day at least 12 times (monthly) in the last year4 or less standard drinks on any one day
More than 10 standard drinks per weekAB
10 or less standard drinks per weekCD

Guideline 2 recommends that ‘to reduce the risk of injury and other harms to health, children and young people under 18 years of age should not drink alcohol’. That is, not consuming alcohol is the safest option. However, this population group has been assessed in the NHS against the Australian Adult Alcohol Guideline. This allows for assessment of the levels of risky drinking for this age group. Data presented for people aged 15-17 years in this release does not reflect guideline 2.

For more detailed information, see Australian guidelines to reduce health risks from drinking alcohol.

Previous 2009 Alcohol guidelines

The 2009 lifetime risk guideline (guideline 1) recommended no more than 2 standard drinks per day (equivalent of 14 standard drinks per week). This guideline was assessed using average daily consumption of alcohol for persons aged 15 years and over, derived from the type, number and serving sizes of beverages consumed on the three most recent days of the week prior to interview, in conjunction with the total number of days alcohol was consumed in the week prior to interview.

The 2009 single occasion risk guideline (guideline 2) recommended no more than 4 standard drinks on a single occasion. This guideline was assessed using questions on the number of times in the last 12 months a person's consumption exceeded specified levels.

Physical activity

Physical activity refers to a combination of exercise and workplace activity. Exercise includes walking for transport, walking for fitness, sport or recreation, moderate exercise and/or vigorous exercise undertaken in the last week. Workplace activity is physical activity undertaken in the workplace which includes moderate and/or vigorous activity undertaken on a typical workday.

Australia’s Physical Activity and Sedentary Behaviour Guidelines, released in 2014, are assessed against the respective age group for NHS data.

The 2014 Guidelines recommend that:

  • Children and young people (5-17 years) accumulate at least 60 minutes of moderate to vigorous physical activity every day, from a variety of activities including some vigorous, and do muscle strengthening activities on at least three days each week 
  • Adults (18-64 years) should be active most days of the week, accumulate 150 to 300 minutes moderate intensity physical activity or 75 to 150 minutes of vigorous intensity physical activity (or an equivalent combination each week), and do muscle strengthening activities on at least two days each week
  • Older Australians (65 years and over) should accumulate at least 30 minutes of moderate intensity physical activity on most, preferably all, days.

Minutes undertook physical activity is based on respondents meeting the recommended guideline of at least 150 minutes of physical activity a week. Minutes spent on vigorous activity is multiplied by a factor of two.

For more information, see Australia's Physical Activity and Sedentary Behaviour Guidelines.


A balanced diet, including sufficient fruit and vegetables, reduces a person's risk of developing conditions such as heart disease and diabetes. The National Health and Medical Research Council's (NHMRC) 2013 Australian Dietary Guidelines recommend a minimum number of serves of fruit and vegetables each day, depending on a person's age and sex, to ensure good nutrition and health. Adequacy of intake (consumption) is based on whether a respondent's reported usual daily intake in serves of fruit or vegetables meets or exceeds each recommendation.

Usual daily intake of fruit refers to the number of serves of fruit (excluding drinks and beverages) usually consumed each day, as reported by the respondent. A serve is approximately 150 grams of fresh fruit or 50 grams of dried fruit. Adequate daily fruit intake refers to whether the respondent met the minimum number of serves as recommended in the NHMRC 2013 Australian Dietary Guidelines. Juices were excluded.

Usual daily intake of vegetables refers to the number of serves of vegetables (excluding drinks and beverages) usually consumed each day, as reported by the respondent. A serve is approximately half a cup of cooked vegetables (including legumes) or one cup of salad vegetables - equivalent to approximately 75 grams. Adequate daily vegetable intake refers to whether the respondent met the minimum number of serves as recommended in the NHMRC 2013 Australian Dietary Guidelines. Tomatoes were included as vegetables while juices were excluded.

2013 NHMRC Australian Dietary Guidelines
Recommended serves per day
  Age group (years)
  2-34-89-1112-1314-1819-5051-7070 years and over
Males 11.5222222
Females 11.5222222
Males 2.54.555.55.565.5(a)5
Females 2.54.5555555

a. Rounded up to 6 serves in published data.
Source: Australian Bureau of Statistics, National Health Survey: First Results methodology 2017-18 financial year

For more information, see the National Health and Medical Research Council (NHMRC) 2013 Australian Dietary Guidelines

Sweetened Beverages

Sugar sweetened drinks includes soft drinks, cordials, sports drinks, or caffeinated energy drinks. This may include soft drinks in ready to drink alcoholic beverages, and excludes fruit juice, flavoured milk, 'sugar free' drinks, or coffee / hot tea. This was reported on usual consumption per day/week.

Diet drinks have artificial sweeteners added to them rather than sugar and includes diet soft drink, cordials, sports drinks, or caffeinated energy drinks. This may include diet soft drinks in ready to drink alcoholic beverages, and excludes non-diet drinks, fruit juice, flavoured milk, water or flavoured water, or coffee/tea flavoured with sugar replacements like 'Equal'.

PBS Medications

For the 2020-21 NHS, medications data was sourced from the Pharmaceutical Benefits Scheme (PBS) instead of being collected directly from survey respondents. To enable this, the 2020-21 NHS sample was linked to the ABS’ Multi-Agency Data Integration Project (MADIP) asset to source the PBS administrative data including Repatriation PBS (RPBS) data, with appropriate permissions. The PBS and RPBS administrative data was then used to create new medications data items which are added to the 2020-21 NHS dataset for this release.  

For more information on the MADIP asset, refer to Multi-Agency Data Integration Project (MADIP)

Pharmaceutical Benefits Scheme (PBS)

The PBS is an Australian Government program that subsidises medications listed on the PBS Schedule for all Australian residents who hold a current Medicare card. In addition, some overseas visitors are eligible for some PBS medications through reciprocal health care agreements. The PBS subsidises medications for most medical conditions, and most PBS and RPBS subsidised prescriptions are dispensed by pharmacists and used by patients at home. Patients pay a “co-payment” towards the cost of PBS subsidised medications, and many PBS medicines cost significantly more that the co-payment amount.

There are programs operating under Section 100 of the National Health Act 1953 particularly in remote and very remote areas, such as the Aboriginal Medical Services, which receive access to free and subsidised medicines, at times on a bulk supply basis, that are not captured through the PBS data when distributed to patients. Noting that the NHS sample design excludes very remote areas.

PBS subsidised prescriptions do not include over-the-counter medications, private prescriptions, dietary supplements, or medications supplied to most public hospital in-patients. Non-prescription medications and products are generally available in pharmacies, supermarkets, health food stores and other retailers and are typically used for mild health problems. There are also prescription medicines that are not listed on the PBS, referred to as non-PBS prescriptions. These medications, products and non-PBS prescriptions are not represented in the NHS-PBS linked data.

The PBS Safety Net scheme is intended to protect patients from large out of pocket costs when they require a number of medicines within a calendar year. There are two Safety Net thresholds – one for concession card holders and one for all other patients. Individuals and families who spend an amount equal to their Safety Net threshold on co-payments in a calendar year receive further prescriptions for that year for free (if they are concession card holders) or for the concessional co-payment rate (if they are general patients) applicable to that year. 

For further information on the PBS, refer to Pharmaceutical Benefits Scheme (PBS).

NHS-PBS linked data

The NHS-PBS linked data has been used to create data items for use with the 2020-21 NHS dataset. These include:

  • number of medications supplied per NHS respondent
  • medication types as classified using the Anatomical Therapeutic Chemical (ATC) Classification
  • the method for dispensing PBS medication or ‘pharmacy type’
  • concessions or entitlements per prescription or ‘patient entitlement status’.

This last group includes different Safety Net categories eg. General Safety Net prescription, Concessional Safety Net prescription, or Repatriation (Department of Veterans' Affairs - DVA) Safety Net prescription.

Data items created from the NHS-PBS linked data can be analysed with demographics, long-term health conditions and health risk behaviours collected from NHS respondents. A full list of the PBS medications data items created for this NHS release can be found in the Data Item List.

The PBS data provides the date of prescription and the date of supply. The timeframe used for analysis of PBS-NHS data in this release is based on date of supply, and spans from 180 days (6 months) before the NHS interview up to 180 days (6 months) after the date of the NHS interview (ie. a total time period of 12 months). This timeframe was chosen to allow for wider analysis of medications use for NHS self-reported health data, however other timeframes have also been created for the NHS-PBS linked data.

MADIP linkage results have defined three (3) population groups for the NHS-PBS linked data. There are: NHS records that have been linked to MADIP and have PBS data; NHS records that have been linked to MADIP but do not have any PBS data (the ‘No PBS medications’ population); and NHS records that were unable to be linked to MADIP (unknown PBS data). This last group accounts for approximately 2.3% of all 2020-21 NHS respondents.

It should be noted that PBS data tells us when a subsidised medication is prescribed and dispensed, but not whether the patients actually consumed the medication. It is also possible to have multiple prescriptions per medication type, and multiple medication types per person.

Anatomical Therapeutic Chemical (ATC) Classification

PBS medication types are classified using the 2022 Anatomical Therapeutic Chemical (ATC) classification system which is maintained by the World Health Organisation (WHO) and widely used internationally.

Under the ATC, medications are classified into different groups based on the main active ingredient, the organ or system on which they act, and their therapeutic, pharmacological and chemical properties. Drugs are classified in a hierarchy with five different levels.

  • The ATC first or main level has fourteen main anatomical or pharmacological groups comprising: Alimentary tract and metabolism; Blood and blood forming organs; Cardiovascular system; Dermatologicals; Genito urinary system and sex hormones; Systemic hormonal preparations, excluding sex hormones and insulins; Anti-infectives for systemic use; Antineoplastic and immunomodulating agents; Musculo-skeletal system; Nervous system; Antiparasitic products, insecticides and repellents; Respiratory system; Sensory organs; and Various.
  • The ATC second level divides each main group into either Pharmacological or Therapeutic subgroups.
  • The ATC third and fourth levels are Chemical, Pharmacological or Therapeutic subgroups.
  • The ATC fifth level is the chemical substance.

Within this 2022 release, medications were classified down to the fourth ATC level ie. this is the lowest level of detail supported by the NHS-PBS data linkage. The count of medication types has been defined as the total count of unique ATC codes at the fourth ATC level.

The first or main ATC level has been used in the datacubes. The list below includes examples of common uses and treatments for the fourteen main anatomical or pharmacological groups:

     A. Alimentary tract and metabolism – reflux, ulcer, anti-nausea and diabetic medications

     B. Blood and blood forming organs – blood thinners, vitamin K, anti-anemic preparations (e.g. iron, B12, folic acid)

     C. Cardiovascular system – cholesterol-lowering, blood pressure and heart failure medication

     D. Dermatologicals – topical corticosteroids for skin conditions (e.g. dermatitis, eczema)

     G. Genito urinary system and sex hormones – contraceptives, menopausal and gynaecological medications

     H. Systemic hormonal preparations, excluding sex hormones and insulins – anti-inflammatory medications for autoimmune disorders (e.g. rheumatoid arthritis) and thyroid issues

     J. Antiinfectives for systemic use – bacterial antibiotics and antivirals

     L. Antineoplastic and immunomodulating agents – immunosuppressants and anti-cancer medications

     M. Musculo-skeletal system – non-steroid based anti-inflammatory medications

     N. Nervous system – pain relief and medications used for mental health

     P. Antiparasitic products, insecticides and repellents – medications used for infestations, parasitic worms and insect pests

     R. Respiratory system – asthma and Chronic Obstructive Pulmonary Disease (COPD) medications

     S. Sensory organs – anti-inflammatory and antibiotic medications used for the ear and eyes

     V. Various – nutrients, treatment for high potassium/phosphate and other therapeutic medications.

For further information on the ATC, refer to WHOCC - Structure and principles.

Data downloads

Data item list


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