Latest release

# National Aboriginal and Torres Strait Islander Health Survey methodology

Reference period
2018-19 financial year
Released
11/12/2019
Next release Unknown
First release

## Explanatory notes

### Introduction

The 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) was conducted between July 2018 and April 2019.

• It collected information from Aboriginal and Torres Strait Islander people of all ages in non-remote and remote areas of Australia, including discrete Indigenous communities.
• Funding for the survey was provided by the Australian Government Departments of Health and Prime Minister and Cabinet.
• Previous surveys have been conducted in 2012–13 and 2004–05. Some health data was also collected in the 2014–15, 2008 and 2002 National Aboriginal and Torres Strait Islander Social Surveys (NATSISS).
• It collected information on a number of topics for the first time, including mental health conditions, medications, consumption of sugar sweetened and diet drinks, experiences of harm and a hearing test. For further information see Appendix - survey topics.

The survey was dependent on the high level of cooperation received from Aboriginal and Torres Strait Islander people and their communities. Without their continued cooperation, the wide range of Aboriginal and Torres Strait Islander statistics published by the Australian Bureau of Statistics (ABS) would not be available.

The ABS is committed to using data to focus on the stories of Aboriginal and Torres Strait Islander people. For this reason, the ABS has not included comparisons with the non-Indigenous population in the narrated summaries and data highlights.

Users who require non-Indigenous comparisons can access information in some data cubes that have been published with age standardised proportions for both the non-Indigenous and Aboriginal and Torres Strait Islander populations. These are available on the Data downloads section. For further information, see Appendix - non-Indigenous comparisons.

### Consultation

The survey was developed in conjunction with numerous stakeholders, including representatives from Australian Government agencies, state/territory government agencies, non-government organisations, and academic and research institutions.

• An advisory group was established to assist the ABS in determining the content of the survey and to advise on data output requirements.
• Expert advisory panels provided advice to the ABS on two new topics – mental health and physical harm. These panels comprised members from both government and non-government agencies.
• New questions proposed for inclusion underwent cognitive testing to ensure concepts would be understood by respondents, and to enable the questions and associated procedures to be refined.

A dress rehearsal was conducted in non-remote and remote areas of Western Australia and the Northern Territory in October 2017 to test survey content and procedures.

The range of topics identified for possible inclusion exceeded the capacity of the survey. With the assistance of the advisory groups, these were assessed and priorities were established. Topics ultimately selected for inclusion were those identified as highest priority and which could be appropriately addressed in a survey of this type.

### Scope and coverage

The scope of the survey was all Aboriginal and Torres Strait Islander people living in private dwellings.

The following people were not included in the survey:

• non-Indigenous persons
• visitors to private dwellings staying for less than six months
• people in households where all residents are less than 18 years of age
• people who usually live in non-private dwellings, such as hotels, motels, hostels, hospitals, nursing homes and short-stay caravan park
• students at boarding school
• non-Australian diplomats, diplomatic staff and members of their household
• members of non-Australian defence forces stationed in Australia and their dependents
• overseas visitors.

Coverage exclusions apply to those people who were in scope for the survey, but who were not included in the sampling frame. The following coverage exclusions were applied:

• mesh blocks with no or very few Aboriginal and Torres Strait Islander households
• some discrete Indigenous communities and outstations with a small number of Aboriginal and Torres Strait Islander households, and
• Aboriginal and Torres Strait Islander people living in outstations which are not linked to a main community.

The overall coverage of the 2018–19 NATSIHS was approximately 33% of Aboriginal and Torres Strait Islander persons in Australia. The final sample has been weighted to population benchmarks which align with the scope of the survey to account for undercoverage. Refer to the Non-sampling error and undercoverage section below for more information.

The benchmarks are based on the most recently released Aboriginal and Torres Strait Islander estimated resident population (ERP), with an adjustment to account for the time period of the survey. For more information on ERP, see Estimates of Aboriginal and Torres Strait Islander Australians (cat. no. 3238.0.55.001).

As at 30 June 2016, the estimated resident Aboriginal and Torres Strait Islander population living in private and non-private dwellings was 798,365. Excluding persons in non-private dwellings, the projected Aboriginal and Torres Strait Islander population at 31 December 2018 was 814,013 and this is the population benchmark that the survey results were weighted to meet.

### Sample design

The survey was designed to produce reliable estimates for the whole of Australia, for each state and territory and for remoteness areas. The sample was designed to achieve a Relative Standard Error of less than 25% for key variables.

The survey sample had two parts:

• a community sample, made up of discrete Indigenous communities, including any outstations associated with them, and
• a non-community sample, made up of persons in private dwellings within areas outside of Indigenous communities.

Each part used a multi-stage sampling process to ensure the representativeness of the final sample.

As with previous ABS Aboriginal and Torres Strait Islander surveys, additional sample was collected in the Torres Strait Area, to ensure data of sufficient quality would be available for the Torres Strait Area and the remainder of Queensland.

The community sample was a random selection of discrete Indigenous communities and outstations in non-remote and remote areas.

• Selections were made using the Dwelling Register for Aboriginal and Torres Strait Islander Communities (DRATSIC). The DRATSIC was constructed from counts from the 2016 Census of Population and Housing.
• Communities in Tasmania were excluded from coverage entirely, consistent with the 2012–13 NATSIHS and the 2014–15 NATSISS.
• Non-remote communities in Western Australia and the Northern Territory were also excluded from coverage as only a small number of fully responding households were required in the sample design. As a result, these communities were removed from the sample, which was similar to the 2014–15 NATSISS.

Dwellings in the non-community sample were selected using a multi-stage area sample.

• Mesh blocks with no Aboriginal and Torres Strait Islander households, as identified in the 2016 Census, were excluded from coverage.
• Areas in remote Victoria and very remote Tasmania were excluded, consistent with the 2012–13 NATSIHS and the 2014–15 NATSISS.
• For each randomly selected dwelling within the selected mesh block, one usual resident aged 18 years or over was asked whether anyone in the household was of Aboriginal and/or Torres Strait Islander origin. This screening question was used to identify Aboriginal and Torres Strait Islander households, from which the sampling process was undertaken for participants in the survey.

### Number of people selected per household

Within each identified Aboriginal and Torres Strait Islander household in both the community and non-community sample:

• up to two adults (aged 18 years and over) and two children (aged 0–17 years) were randomly selected in non-remote areas, and
• up to one adult (aged 18 years and over) and one child (aged 0–17 years) were randomly selected in remote areas.

### Fully or adequately responding households

A fully responding household is one in which all parts of the interview were completed for all persons in scope.

An adequately responding household is the same as a fully responding household, but with legitimate ‘don't know’ answers or refusals where permitted in the survey. For example, adequately responding households include people who declined to answer the substance use questions or have their height, weight, waist circumference or blood pressure measured by an interviewer.

For information on sample counts and response rates, see Appendix- response rates, sample counts and estimates.

### Interviewer training

Information was collected by trained ABS interviewers using a computer based questionnaire. Prior to enumeration, interviewers:

• participated in cultural awareness training which outlined how to conduct surveys in Indigenous community areas and described cultural considerations
• completed classroom training and exercises to gain an understanding of the survey content and procedures.

### Face-to-face interviews

Interviewers conducted face-to-face interviews in all selected households.

A person aged 18 years or over was asked to provide basic information for all usual residents of the household, including Indigenous status, age, sex and relationships. This person, known as the household spokesperson, answered financial and housing questions, such as income, tenure arrangements and household facilities.

Personal interviews were then conducted with selected Aboriginal and Torres Strait Islander persons aged 15 years and over. Some people were unable to be interviewed because of:

• injury or illness (a proxy interview may have been arranged)
• cultural considerations, such as mourning the death of a family member (sorry business) or
• insufficient English skills and an interpreter was unable to be arranged.

For selected persons aged 15–17 years:

• a personal interview was conducted if a parent or guardian provided consent, or
• their interview was completed by a proxy (that is, by a parent or guardian). Around two-thirds (66%) of interviews were conducted by proxy for this age group.

An adult was asked to respond on behalf of children aged less than 15 years.

### Use of local Aboriginal and Torres Strait Islander advisors

In communities, interviewers were accompanied, where possible, by local Aboriginal and Torres Strait Islander advisors who assisted in conducting interviews. The advisors:

• explained the purpose of the survey
• introduced the interviewers, and
• assisted in identifying usual residents of a household and in locating residents who were not at home.

### Variations in data collection and survey questions

To take account of language and cultural differences, the collection method and survey questions sometimes varied in remote areas.

• Some questions were reworded to enhance a person’s ability to understand concepts.
• Some topics were excluded if it was considered problematic to collect or not applicable.

This means some data items are not available for the total Aboriginal and Torres Strait Islander population. Further information on the availability of data items can be found in the Data Item List, available in the Data downloads section.

In non-community areas, where a person selected in the survey initially refused to participate, a follow up letter was sent and a second visit was made (where possible) to encourage participation. There was no follow up of refusals in communities.

### Estimation methods

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

• Each person or household was given a number (known as a weight) to reflect how many people or households they represented in the whole population.
• A person or household’s initial weight was 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).

For the person level weights, 250 replicate weights were produced to ensure accurate estimates of the standard errors.

After calculating the initial person weights, an adjustment was incorporated into the weighting for persons and households to account for Aboriginal and Torres Strait Islander persons not covered by the sample.

The person and household level weights were separately calibrated to independent estimates of the in scope population, referred to as ‘benchmarks’. The benchmarks used additional information about the population to ensure that:

• people or households in the sample represented people or households that were similar to them
• the survey estimates reflected the distribution of the whole population, not the sample.

For this survey, person weights were simultaneously calibrated to the following population benchmarks:

• state/territory by remoteness area
• state/territory by age by sex
• Torres Strait Islander status by Torres Strait Islander region by adult/child status
• remoteness area by age by sex
• state/territory by discrete Indigenous community.

The survey was benchmarked to the estimated Aboriginal and Torres Strait Islander resident population living in private dwellings at 31 December 2018. As people in non-private dwellings (e.g. hotels) are excluded from the scope of the survey, they have also been excluded from the survey benchmarks. Therefore, the 2018–19 estimates do not, and are not intended to, match estimates for the total resident Aboriginal and Torres Strait Islander population obtained from other sources. This approach is consistent with the 2012–13 NATSIHS and 2014–15 NATSISS.

For household weights, the ABS does not produce counts of Aboriginal and Torres Strait Islander dwellings and, as a result, household level benchmarks are not available. Instead, household level weights for this survey were derived from person level benchmarks, consistent with the approach for the 2012–13 NATSIHS and 2014–15 NATSISS. This was done by:

• assigning the initial household weight (after the adjustment) to all Aboriginal and Torres Strait Islander persons in the household
• adjusting the weights to the person level benchmarks with the restriction that each person in the household must have the same final weight.

The resulting weight was the final household weight.

The sum of the household weights will only provide an estimate of the number of Aboriginal and Torres Strait Islander households. This method was analysed to ensure that person and household level estimates were as consistent as possible.

### Age standardisation

Age standardisation is a technique used to enhance the comparability of rates between populations with different age structures. This technique is often used to make comparisons between the non-Indigenous and Aboriginal and Torres Strait Islander populations. For further information, see Appendix - non-Indigenous comparisons.

### Accuracy

Two types of error affect the accuracy of sample surveys: sampling and non-sampling error.

### Sampling error

Sampling error is the difference between:

• estimates for a population made by surveying only a sample of people, and
• results from surveying everyone in the population.

The size of the sampling error can be measured. It is reported as the Relative Standard Error (RSE) and 95% Margin of Error (MOE). For more information see the Technical note.

In this publication, estimates with a RSE of 25% to 50% were flagged to indicate that the estimate has a high level of sampling error, and should be used with caution. Estimates with a RSE over 50% were also flagged and are generally considered too unreliable for most purposes.

Margins of Error are provided for proportions to help people using the data to assess how reliable it is. The proportion combined with the MOE shows the range likely to include the true population value with a given level of confidence. This is known as the confidence interval. People using the data need to consider this range if they are making decisions based on the proportion.

Analysis was done to compare the characteristics of respondents to the 2018–19 NATSIHS with a number of data sources to determine data consistency. Some sources for comparison included the:

• 2016 Census of Population and Housing
• 2012–13 NATSIHS
• 2014–15 NATSISS.

Estimates presented in this publication have been rounded. As a result, sums of components may not add exactly to totals.

### Non-sampling error and undercoverage

Undercoverage is one potential source of non-sampling error. It is the shortfall between the population represented by the achieved sample and the in-scope population. It can introduce bias into the survey estimates; however, the extent of any bias depends on the size of the undercoverage as well as the difference in the characteristics of those people in the coverage population and those of the in-scope population.

Undercoverage rates can be estimated by calculating the difference between the sum of the initial weights of the sample and the population count. If a survey has no undercoverage, then the sum of the initial weights of the sample would equal the population count (ignoring small variations due to sampling error).

In the 2018–19 NATSIHS, there was an increase in the undercoverage rate compared with previous ABS Aboriginal and Torres Strait Islander surveys. The overall 2018–19 NATSIHS undercoverage rate was approximately 67% of the in-scope population at the national level. The estimated undercoverage in both the 2012–13 NATSIHS and the 2014–15 NATSISS was 62%.

The overall undercoverage rate for non-community areas was 68% and for community areas was 57%. The undercoverage rate varied across the states and territories.

### Undercoverage rate in National Aboriginal and Torres Strait Islander Health Surveys, by state/territory

NSWVic.QldSAWATas.NTACTAust.
%
2018–1972.063.464.963.060.556.068.168.066.5
2012–1364.771.859.265.764.041.059.665.462.2

Given the high undercoverage rate in the 2018–19 NATSIHS, there was extensive analysis undertaken to ensure the results were consistent with other data sources. Potential bias due to undercoverage was addressed by the application of adjustments to the initial weights and through the use of population benchmarks.

Undercoverage may occur due to a number of factors, including:

• frame exclusions (areas being removed from the sampling frame)
• non-response
• people not identifying as being of Aboriginal and/or Torres Strait Islander origin
• issues arising in the field.

Each of the factors is explained in more detail below.

### Frame exclusions

Similar to the 2012–13 NATSIHS and 2014–15 NATSISS, frame exclusions were incorporated to make the sample design more efficient. Part of the frame exclusion that could be contributing to undercoverage are people who may have moved since the 2016 Census of Population and Housing.

### Non-response

Non-response may occur when people cannot or will not cooperate, or they cannot be contacted. The loss of information on persons and households reduces the sample and increases both sampling error and the likelihood of incurring response bias.

Non-response in this survey includes non-response to:

• the screening question
• the survey after identification of an Aboriginal and Torres Strait Islander household.

To reduce non-response, the following methods were used:

• face-to-face interviews with respondents
• employment of local Aboriginal and Torres Strait Islander advisors to assist with interviewing in communities
• follow up of respondents if there was initially no response
• aligning the estimates with population benchmarks to ensure the weighted file was representative of the population.

Of the households screened in non-community areas, 77% of households responded. Of those households who responded to the screening question, 3.9% were identified as having an Aboriginal or Torres Strait Islander usual resident. Of these identified households, 73% then responded to the survey.

In discrete Indigenous communities 74.6% of selected in-scope households responded to the survey.

### People not identifying as being of Aboriginal and/or Torres Strait Islander origin

Some Aboriginal and Torres Strait Islander households may not have been identified during the screening process due to:

• Aboriginal and Torres Strait Islander people not identifying themselves as being of Aboriginal and/or Torres Strait Islander origin
• the household spokesperson being unable to correctly provide the Indigenous status of other residents.

There was a large increase in the number of people identifying as being of Aboriginal and/or Torres Strait Islander origin between the 2011 and 2016 Censuses of Population and Housing, and these people may not have chosen to identify in the same way for the 2018–19 NATSIHS for various reasons. Data from the 2016 Census is part of the population benchmarks used in this survey. For more information about the change across the Censuses, please refer to Census of Population and Housing: Understanding the Increase in Aboriginal and Torres Strait Islander Counts, 2016 (cat. no. 2077.0).

### Issues arising in the field

Known undercoverage due to other issues arising in the field included sample being excluded due to:

• overlap with the Monthly Population Survey and other special social surveys
• occupational, health and safety issues
• time constraints, particularly in Aboriginal and Torres Strait Islander communities and their associated outstations.

### Seasonal effects

The data was collected from July 2018 to April 2019 which may not be fully representative of other time periods in the year. For example, people were asked about the number of times they had consulted with a health professional in the two weeks prior to interview. Travel to access health care facilities, particularly in remote areas, may be subject to seasonal variation throughout the year. Results could have differed if the survey had been conducted over the whole year or in a different part of the year.

### How the data is released

The published results of the 2018–19 NATSIHS include a summary of findings and data cubes presented in spreadsheet format.

A copy of the survey questionnaire, prompt cards and the physical measurements card provided to respondents are available in the Data downloads section.

Additional data from the survey will be available via a range of other products and services:

• detailed microdata to be released in the DataLab at the same time as this publication
• a TableBuilder product (subject to the approval of the Australian Statistician) to be accessible via the ABS website using a secure log-on portal in early 2020
• a number of supplementary themed publications, released progressively after the main publication
• tables produced on request to meet specific information requirements from the survey (subject to confidentiality and sampling variability constraints).

To support the return of results to Aboriginal and Torres Strait Islander peoples, a series of thematic releases are planned for distribution to Aboriginal and Torres Strait Islander communities.

For further information on the comparability of data items see the Data downloads section.

### Confidentiality

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.

The ABS takes care in the specification of tables to reduce the risk of identifying individuals. Random adjustment of the data is considered the best way to do this. A technique called perturbation randomly adjusts all cell values to prevent identifiable data being exposed. These adjustments result in small introduced random errors, which often result in tables not being 'internally consistent' (that is, interior cells not adding up to the totals). However, the information value of the table as a whole is not impacted. This technique allows the production of very large/detailed tables valued by clients even when they contain cells of very small numbers.

In this publication, perturbation was applied to published data from 2018–19 onwards. Data from surveys before 2018–19 have not been perturbed, but have been confidentialised by suppressing cells if required.

### Interpretation of results

Care has been taken to ensure that the results of this survey are as accurate as possible. The following factors should be considered when interpreting these estimates.

• Information recorded in the survey is ‘as reported’ by respondents and may differ from information available from other sources or collected using different methodologies.
• Results of previous surveys have shown a tendency for people to under-report when asked about certain topics, such as alcohol consumption, smoking and substance use.
• Different data items were collected for different time periods. The reliability and accuracy of data are therefore dependent on the respondent's recall.
• Some people may have provided responses they felt were expected, rather than those that accurately reflect their own situation.

For a number of survey data items, some people were unwilling or unable to provide the required information.

• Where responses for a particular data item were missing for a person or household they were recorded in a ‘not known’, ‘not stated’ or ‘refusal’ category.
• 'Not stated’ categories have either been included in the data cubes as part of the total, or they appear as a separate category. This allows users to determine the suitability of the data for their purposes.

### Breastfeeding

Information was collected for children aged 0–3 years (that is, children up to 3 years and 11 months of age, also referred to as 0–47 months).

• The accuracy of the data may be affected in cases where an adult other than the child’s parent responded about the child.
• An age group of 0–5 months is used to describe children aged up to 5 months and 30 days.

### Chronic conditions

A chronic condition is a long-term health condition selected for reporting in this survey because it is common, poses significant health problems, has been the focus of population health surveillance efforts, and action can be taken to prevent its occurrence.

• People reporting diabetes mellitus and/or particular types of heart, stroke and vascular disease (angina, a heart attack, other ischaemic heart diseases, stroke or other cerebrovascular diseases) were included regardless of whether the condition was current and/or long-term.
• When counting the number of chronic conditions a person has, multiple conditions belonging to the same condition type are treated as the one condition. For example, a person reporting anxiety and depression is counted as having one chronic condition as they are both of the same condition type (mental and behavioural conditions).

### Disability

A person has a disability if they have an impairment which restricts their everyday activities and has lasted, or is expected to last, for at least six months. A person with a disability is classified by whether they have:

• a specific limitation with any core activities (mobility, communication and self-care)
• a specific restriction when participating in schooling or employment activities, or
• no specific limitation with core activities or restriction with schooling or employment activities.

A person has a specific limitation with a core activity if they need help from another person, have difficulty or use an aid or other equipment to perform at least one selected task. The level of limitation for each core activity is based on the amount of help a person needs with a selected task:

• profound — unable to do or always needs help with a core activity task
• severe — sometimes needs help or has difficulty with a core activity task
• moderate — does not need help but has difficulty with a core activity task
• mild — does not need help and has no difficulty, but uses aids or equipment or has other limitations with a core activity task

A person's overall level of core activity limitation is determined by their highest level of limitation in any of these activities. For example, if a person has a profound limitation with a communication task and a moderate limitation with a self-care task, they person is categorised as having a profound disability.

A person has a schooling restriction if, because of their disability, they:

• are not attending school/undertaking further study
• need time off school or study
• attend special classes or a special school
• have other related difficulties.

A person has an employment restriction if, because of their disability, they:

• are restricted in the type of job they could do
• are restricted in the number of hours they can work
• have difficulty finding suitable work
• need time off work
• are permanently unable to work.

A person with a ‘schooling/employment restriction only' is someone who reported no limitations with any of the core activities but reported having difficulty with schooling and/or employment activities.

### Employment

Information was collected using the short-form version of the questions used in the ABS’ monthly Labour Force Survey.

Two changes were made to the employment questions for the 2018–19 NATSIHS.

The first change was that all references to the Community Development Employment Projects (CDEP) were replaced with the Community Development Program (CDP). The labour force status of a person on the CDP depends on whether they had another job and other factors.

• If they had another job, they were considered to be employed.
• If they did not have another job and they reported they were paid by an employer or another source, they were considered to be employed.
• If they did not have another job and they reported they were paid by Centrelink or were unpaid, they were considered to be either unemployed or not in the labour force. They were asked further questions to determine their final labour force status.

The other change was that ‘unpaid trainee work’ was added to the list of categories for payment arrangements to align with changes made to the ABS’ standard employment module. Unpaid trainees were previously categorised as ‘Other’. It is expected that the population in this category is small.

The populations affected by these two changes are likely to be insignificant so there is no break in time series for the 2018–19 NATSIHS.

### Equivalised income

Differences in household types and compositions, and their requirements relative to income, can be taken into account by the application of equivalence scales. These scales are a set of ratios which, when applied to the income of different household or income unit types, produce standardised estimates of income which reflect the households' relative well-being. The modified Organisation for Economic Co-operation and Development (OECD) equivalence scale (1994) was used.

Equivalised income is derived by calculating an equivalence factor and then dividing income by that factor. The equivalence factor is built up by allocating points to each person in the household unit and summing those points. One point is allocated to the first adult in the unit, 0.5 points for each other person aged 15 years and over, and 0.3 points for each person aged less than 15 years. For example:

• a single person household has a factor of one, so equivalised income is therefore the same as reported income
• a household comprising two adults and a child aged less than 15 years would have a factor of 1.8, so equivalised income for this household is therefore the household income divided by 1.8.

Equivalised income is available in dollar amounts and deciles.

### Family composition

‘Family composition’ is created through the relationships that exist between a single ‘responsible adult’ and each other member of that family living in the household. Family composition is then allocated on the basis of whether the types of relationships given below are present or not in the family in the following order of precedence.

• A couple relationship is defined as a registered or defacto marriage, including same-sex relationships.
• A parent-child relationship is defined as a relationship between two persons usually resident in the same household. The child is attached to the parent via a natural, adoptive, step, foster or child dependency relationship.
• A child dependency relationship is defined as including all children under the age of 15 years (whether related or unrelated to the family reference person) and those natural, step, adopted or foster children who are full-time students aged 15–24 years.
• Other relationship is defined as including all those persons related by blood or by marriage who are not covered by the above relationships.

The definition of family used for the 2018–19 NATSIHS is a more restrictive definition than the ordinary notion of the term ‘family’ which generally includes relatives whether they live together or not. This is a reflection of the fact that, for survey-based research, it is necessary to place some physical bound on the extent of family for the purposes of being able to collect family data.

### Health actions

A health action is an action taken by a person in the two weeks prior to interview or, for admission to hospital, in the 12 months prior to interview, related to their health. When interpreting health action data, the following points should be noted.

• People were asked if there was a place they usually go when they are sick or need advice about their own health. In 2018–19, a change was made to combine ‘Aboriginal Medical Service’ and ‘Community Clinic’ into a single category. This was done to alleviate the problem for those who were unsure whether they attended an Aboriginal Medical Service or a Community Clinic.
• In 2018–19, the term ‘doctor’ was changed to ‘GP/General Practitioner’ or ‘specialist’ to remove ambiguity in some of the questions.
• People who reported a health condition in the other long-term conditions module, rather than in the specific condition module, may not have been asked particular questions about that condition. As a result, there may be under-reporting of some condition-specific health actions.

### Health conditions

Information was collected on broad range of health conditions, with the primary focus being on those that were current and long-term. A current long-term health condition is an illness, injury or disability which was current at the time of the interview and which had lasted at least six months, or which the person expected to last for six months or more.

Information on specific health conditions was collected in individual modules, as well as a general long-term health conditions module. Questions varied to take into account differences between non-remote and remote populations and demographic characteristics. For example, males and females were asked about different types of cancer testing.

Interviewers coded reported conditions using an extensive pick list of conditions built into the computer based questionnaire. For output purposes, conditions are grouped together based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10).

The following should be taken into consideration when using health conditions data.

• Some questions are subjective and responses may be influenced by factors unrelated to health.
• The potentially sensitive and personal nature of some questions may have impacted on people’s willingness to respond.
• Conditions which are reported in the long-term health conditions module, rather than the specific condition module, have not necessarily been diagnosed by a doctor or nurse.
• People who are usual residents of hospitals or nursing homes are outside the scope of the survey. As a result, the estimates in this survey may under-estimate the prevalence of certain conditions, especially those associated with age.
• As conditions are self-reported, people may report symptoms of an underlying condition, rather than the condition itself. For example, they may report having oedema which may be a symptom of a heart valve disorder.
• It is expected that conditions that were specifically mentioned in questions or shown on prompt cards would have been better reported than conditions for which responses relied entirely on a respondent’s judgement and willingness to report them.

### Income

The 2018–19 NATSIHS uses the short personal income module instead of the basic module used in the 2012–13 NATSIHS.

• In the basic module, people were prompted to think of all of their sources of income, and were then asked to provide a separate amount for each of their source(s).
• In the short module, people were asked to list all of their sources of income, but they were only required to provide one total amount for all of their income.
• One benefit in using the short income module is a lower proportion of refusals when people were asked for their total income. In the basic module, if a person refuses to state how much they earn from one source, their total income is classified as a refusal. In the short module, a person is only asked to provide one estimate which is of their total income.

In 2012–13, the Community Development Employment Projects (CDEP) was included as a category when asking about sources of personal income. As CDEP was discontinued in 2013, these questions were not included in the 2018–19 NATSIHS. Instead, questions were asked about the Community Development Program (CDP).

In the 2018–19 NATSIHS, the deciles for both household and personal income are not taken from the deciles within the survey. Instead, a national figure is used (which includes both non-Indigenous and Aboriginal and Torres Strait Islander households), meaning there will not necessarily be 10% of the in scope population within each decile. The decile boundaries from the 2017–18 NHS have been used, and adjusted for inflation using the Consumer Price Index to account for enumeration period differences between the 2017–18 NHS and the 2018–19 NATSIHS. This is a similar approach to that used in the 2012–13 NATSIHS and 2014–15 NATSISS.

The dollar amount cut-offs for equivalised household income deciles, gross weekly income of household deciles and gross weekly personal income deciles are available in the data item list via the Data downloads section.

### Medications

Information about medication use was only collected in non-remote areas. Interviewers recorded the Australian Register of Therapeutic Goods Administration (TGA) identification number of each medication taken by the respondent. These were either:

• AUST R medicines – all prescription medications and many over-the-counter products such as those used for pain relief, coughs and colds and antiseptic creams, or
• AUST L medicines – generally lower risk self-medication products, which include vitamins, minerals, and herbal and homoeopathic products.

For medications without an AUST R or AUST L code (for example, medications obtained overseas), interviewers were able to record details of the medication which were later coded by office staff. Up to 50 different medications were able to be recorded.

Therapeutic substances reported were coded as either medications or dietary supplements.

• Medications were coded to the World Health Organisation’s Anatomical Therapeutic Chemical (ATC) classification system based on their active ingredient(s) and their therapeutic application.
• Dietary supplements were coded to a classification adapted from the Australian Food, Supplement and Nutrient Database (AUSNUT) food classification by Food Standards Australian New Zealand (FSANZ).

The categorisation of substances as either medications or dietary supplements has been adopted for the purposes of describing data collected in the survey and should not be assumed to be an exact description of the contents of either category. For example, while the ATC includes codes for vitamins and minerals and other dietary supplements, such supplements were coded to the FSANZ supplements classification.

For the purpose of this survey, dietary supplements included:

• vitamins
• minerals
• herbal extracts (including Chinese herbs)
• amino acids
• mega 3 fatty acids
• other fatty acids
• glucosamine/chondroitin formulations.

### Substance use

The collection method for this topic varied between non-remote and remote areas.

• In non-remote areas, people had the option to answer questions using a self-completed computer based questionnaire.
• In remote areas, people were asked questions by an interviewer.

Substance use is likely to be under-reported.

• Responses to these questions were voluntary, with respondents able to not answer some or all of the questions.
• The potentially sensitive and personal nature of the questions may have impacted on people’s willingness to respond and what responses they provided.
• Under-reporting of substance use may be more common in remote areas as people provided their responses directly to the interviewer and may have had other household members present at the interview.
• The extent to which under-reporting has occurred is not able to be quantified.

### Comparability with previous surveys

The ABS previously conducted the NATSIHS in 2012–13 and 2004–05. In addition, the National Health Survey (NHS) conducted in 2001 included an Aboriginal and Torres Strait Islander sample known as the NHS (I).

The 2018–19 and 2012–13 surveys largely employed the same methodology and survey content to allow for comparability over time. Information about differences between the various iterations of the survey can be found below.

• The data item list for the 2018–19 NATSIHS contains information about items that can be compared between 2018–19 and 2012–13. It also includes information about whether the item is comparable to the 2017–18 NHS.

Between 2011 and 2016, the Aboriginal and Torres Strait Islander population increased by 18.4% or 100,800 people. When comparing estimates from the 2018–19 NATSIHS with previous surveys of the Aboriginal and Torres Strait Islander population, users should be aware of the large increase in the Aboriginal and Torres Strait Islander population and consider the impact this may have when interpreting change over time.

## Appendix - response rates, sample counts and estimates

### Show all

The 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) sample was designed to provide reliable estimates for the Aboriginal and Torres Strait Islander population for the whole of Australia, at state/territory level and for non-remote and remote areas.

#### Sample design

The sample design had an expected number of 11,700 fully responding persons. The final processing file compromised 10,579 fully responding persons, the calculation of which is explained below.

A total of 9,284 private dwellings were selected in the sample. These were identified by screening households in non-community areas or through selections of discrete Indigenous communities. The sample was then reduced to 8,707 households after excluding those unable to be contacted after screening

#### Response rates of initial selected sample

Households
no.%
Selected private dwellings9 284100.0
Sample loss
Vacant dwelling1892.0
All persons out of scope/coverage290.3
Other sample loss(a)3593.9
Total sample loss5776.2
Selected households after sample loss8 70793.8
a. Includes situations such as selected persons away for enumeration period, no adult in household, no longer any person identifying as being of Aboriginal and/or Torres Strait Islander origin, derelict dwelling, dwelling converted to non–dwelling or holiday home.

Of the 8,707 households in the final sample, 6,388 (73.4%) were fully or adequately responding households. These are households where at least one person selected to complete the survey had either completed it fully or to a point where their data could still be used.

#### Response rates of households after sample loss

Households
no.%
Selected households after sample loss8 707100.0
Full/part refusal91610.5
Full/part non–contact1 13613.0
Language problems90.1
Other2583.0

From the 6,388 fully or adequately responding households, there were 10,579 people included in the sample.

#### Persons in sample and response rates, by state/territory

UnitNSWVic.QldSAWATas.NTACTAust.
Households approached(a)no.1 1401 0821 5378381 3286171 8143518 707
Households in sampleno.8548081 1666039595201 2602186 388
Response rate%74.974.775.972.072.284.369.562.173.4
Total persons in sampleno.1 5401 3681 9099691 5649081 95037110 579
a. Excluding those unable to be contacted after screening

#### Fully responding persons in sample, by state/territory and remoteness

NSWVic.QldSAWATas.NTACTAust.
no.
Non-remote1 36713688776407048764003716 603
Remote173. .1 032329860321 550. .3 976
Total1 5401 3681 9099691 5649081 95037110 579
. . not applicable

Persons in the sample were then weighted to population benchmarks to reflect the size, age structure and geographical distribution of the total population. For more information about the population benchmarks, see Explanatory notes section.

#### Persons in sample and weighted estimates, by sex and age

PERSONS IN SAMPLE WEIGHTED ESTIMATE
MalesFemalesPersonsMalesFemalesPersons
Age group (years)no.no.no.'000'000'000
0–46596061 26549.246.695.4
5–96646021 26647.545.492.9
10–145865101 09645.543.989.6
15–1939339879141.840.081.7
20–2427539466937.136.473.9
25–2928944072932.833.065.7
30–3430546076525.327.552.3
35–3922438160520.722.943.5
40–4422633656218.821.340.3
45–4928233361520.223.443.6
50–5423430253617.820.438.1
55 and over7119691 68044.952.497.6
Total4 8485 73110 579401.5413.1814.0

#### Persons in sample and weighted estimates, by state/territory and age

UnitNSWVic.QldSAWATas.NTACTAust.
Persons in sample
0–17 yearsno.6285417273706173477801464 156
18–54 yearsno.6516138524447233869041704 743
55 years and overno.2612143301552241752665551 680
Total persons in sampleno.1 5401 3681 9099691 5649081 95037110 579
Weighted estimate
0–17 years'000109.624.695.917.440.311.625.53.0328.0
18–54 years'000127.828.4107.320.948.213.938.94.0388.8
55 and over'00035.87.225.54.911.14.38.00.897.6
Total weighted estimate'000271.960.2228.943.099.829.872.77.7814.0

#### Persons in sample and weighted estimates by age, sex and remoteness area

PERSONS IN SAMPLE WEIGHTED ESTIMATE
MalesFemalesPersonsMalesFemalesPersons
no.no.no.'000'000'000
MAJOR CITIES
0–17 years6205461 16662.959.3122.4
18–54 years5057331 23873.477.7150.5
55 years and over19423643015.718.834.4
Total major cities1 3191 5152 834151.9155.8307.7
INNER REGIONAL
0–17 years43739983642.240.883.2
18–54 years35349584842.845.087.8
55 years and over13816830611.412.223.8
Total inner regional9281 0621 99096.398.0194.4
OUTER REGIONAL
0–17 years36529465934.533.067.9
18–54 years29546375835.239.174.7
55 years and over1512113629.911.321.8
Total outer regional8119681 77980.583.4163.9
REMOTE
0–17 years25123448510.29.820.1
18–54 years28439868212.513.325.8
55 years and over881442323.34.07.3
Total remote6237761 39926.127.153.2
VERY REMOTE
0–17 years5134971 01017.716.934.5
18–54 years5147031 21724.526.150.5
55 years and over1402103504.85.810.6
Total very remote1 1671 4102 57747.048.595.7
AUSTRALIA
0–17 years2 1861 9704 156168.0159.9328.0
18–54 years1 9512 7924 743188.2200.4388.8
55 years and over7119691 68044.952.497.6
Total Australia4 8485 73110 579401.5413.1814.0

## Appendix - physical measurements

### Show all

In the 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), physical measurements of height, weight and waist circumference were collected from respondents aged two years and over, and was a voluntary component of the survey. Women who advised that they were pregnant were not measured. Voluntary blood pressure measurements were also collected from respondents aged 18 years and over. Persons with a high Body Mass Index (BMI) or blood pressure are at risk of developing chronic disease. BMI is a simple index of weight-for-height, which defines whether a person is underweight, normal weight, overweight or obese – see Appendix - Assessing health risk factors.

#### Non-response rates

Physical measurements had a relatively high rate of non-response due to their voluntary and sensitive nature. To correct for the high rate of non-response, imputation of values for those that did not have measurements collected was used to achieve estimates of physical measurements for the whole population.

#### Non-response rates for physical measurements, by age

Total persons in sampleBody Mass Index(a)Waist circumferenceBlood pressure
no.%%%
Children (2–17 years)
2–479852.355.3. .
5–778954.856.4. .
8–1194547.849.3. .
12–1462856.758.3. .
15–1752960.962.6. .
Total 2–14 years3 16052.454.4. .
Total 2–17 years3 68953.655.5. .
18–2493134.036.234.3
25–341 49438.339.937.4
35–441 16740.042.241.4
45–541 15142.744.441.6
55 years and over1 68042.745.343.0
Total 18 years and over6 42339.942.039.9
. . not applicable
a. Respondent's height and/or weight measurement not taken.

#### Self-reported height and weight

In addition to the voluntary measured items, respondents in the 2018–19 NATSIHS were also asked to self-report their height and weight measurements. Of those whose BMI was not measured, 55.8% of adults and 34.3% of children provided both self-reported height and weight measurements. This provided valuable information about the height and weight that was used in the imputation for people with missing values.

#### How imputation works

In the 2018–19 NATSIHS and both the 2014–15 National Aboriginal and Torres Strait Islander Social Survey (NATSISS) and 2017–18 National Health Surveys (NHS), missing values were imputed using the 'hot decking' imputation method. In this method, a record with a missing response (the 'recipient') receives the response of another similar record (the 'donor').

A number of characteristics (imputation variables) were used to match recipients to donors.

• age group
• sex
• part of state (capital city and balance of state)
• self-perceived body mass (underweight, acceptable, or overweight)
• level of exercise (sedentary, low, moderate or high)
• whether or not has high cholesterol (as a long-term health condition)
• self-reported BMI category (calculated from self-reported height and weight).

For example, a female recipient aged 35–39 years who lives in a capital city, has a self-reported BMI category of overweight (calculated using self-reported height and weight), has a self-perceived body mass of healthy, has high cholesterol and lives a sedentary lifestyle will match to a donor record who has the same profile (female, 35–39 years, self-reports as overweight, etc).

For BMI, 80.4% of imputed records used all seven imputation variables to match to a donor record. The remaining 19.6% could not be matched using all seven variables and were therefore matched using fewer variables. For example, 7.4% of imputed records were matched to donors using all imputation variables except part of state.

For children aged 2–14 years, the following variables were used:

• single year of age
• sex
• self-reported BMI
• part of state.

For those aged 15–17 years, the same imputation variables were used as for those aged 2–14 years, in addition to level of exercise and self-perceived body mass (only if a person answered for themselves). Cholesterol data was not collected for persons under 18 years of age and so could not be used as an imputation variable.

Single year of age was used in the imputation method for the 2018–19 NATSIHS, which differs from the 2017–18 NHS. The change was made for the 2018–19 NATSIHS as children's height and weight can change rapidly within a short period of time and, to avoid over or under estimating BMI, donors that were of the same age as the recipient were used. A similar change to the imputation method will be investigated for the next iteration of the NHS.

#### Impact of imputation

Physical measurement data (BMI, waist circumference and blood pressure) that includes imputed values are of suitable quality for comparisons with previous surveys; however, the Australian Bureau of Statistics (ABS) recommends using proportion comparisons only as imputation was not used on the physical measurement data in previous years.

The table below shows the impact of imputation on BMI estimates.

#### Measured and imputed Body Mass Index (BMI) results, by age(a)

Measured onlyMeasured and imputed
Body Mass Index categoryno.%no.%
2–17 years
Underweight1699.93579.7
Normal94255.12 02654.9
Overweight37421.982322.3
Obese22513.248313.1
Total overweight/obese59935.01 30635.4
Total 2–17 years1 710100.03 689100.0
18 years and over
Underweight1303.42213.4
Normal87222.61 41422.0
Overweight1 06227.51 79127.9
Obese1 79446.52 99746.7
Total overweight/obese2 85674.04 78874.5
Total 18 years and over3 858100.06 423100.0
a. Using National Aboriginal and Torres Strait Islander Health Survey 2018–19 unweighted sample counts.

#### Whether Body Mass Index (BMI) measured or imputed(a)

2–17 years18 years and over
Body Mass Indexno.%no.%
Measured1 71046.43 85860.1
Imputed1 97953.62 56539.9
Total3 689100.06 423100.0
a. Using National Aboriginal and Torres Strait Islander Health Survey 2018–19 unweighted sample counts.

## Appendix - mental health and wellbeing data

### Show all

This appendix provides information about the questions used to measure mental health conditions, and the questions to measure social and emotional wellbeing.

#### New set of questions

A new set of questions on mental and behavioural conditions was introduced in 2018–19, which asked respondents aged two years and over whether they had any of the following:

• depression
• anxiety
• harmful use or dependence on alcohol or drugs
• behavioural or emotional problems, and/or
• other mental health conditions.

Development and testing of the questions was informed through advice from an expert advisory panel, comprising members from government and non-government agencies. The questions were tested in non-remote and remote areas of Australia.

#### Comparability with other data sources

The change to the collection of this data means the 2018–19 results are not comparable with the 2012–13 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), the 2014–15 National Aboriginal and Torres Strait Islander Social Survey (NATSISS), or the 2017–18 National Health Survey (NHS).

• In the 2012–13 NATSIHS and the 2014–15 NATSISS, information about mental or behavioural conditions was collected as part of a set of questions covering a wide range of long-term health conditions. Results for 2018–19 show a higher proportion of people reported having a mental or behavioural condition than in 2012–13 and 2014–15. This may be due to the greater prominence of mental health questions in 2018–19.
• The ordering and wording of the questions in 2018–19 differs from the 2017–18 NHS. In 2018–19 respondents were asked whether they had been diagnosed with any of the listed conditions by a health professional, followed by questions on whether those conditions were still current and whether they had lasted, or were expected to last, six months or more. In the NHS, respondents were asked about any mental health conditions they had, regardless of whether those conditions were diagnosed by a health professional, followed by questions on the duration of those conditions and whether they had been diagnosed by a health professional.
• A list of mental and behavioural conditions was presented to people on a prompt card and the 2018–19 list was shorter than the 2017–18 NHS list. This was done to ensure the conditions on the prompt card could be easily identified by people in both non-remote and remote areas.

#### Social and emotional wellbeing

Social and emotional wellbeing was measured using several short series of questions taken from existing health and wellbeing surveys. Respondents aged 18 years and over and present at the interview were asked these questions. These questions could not be answered by someone else on the respondent’s behalf.

• Two sets of questions asked about the frequency of specific feelings in the four weeks prior to interview to measure psychological distress and positive emotional states.
• People in non-remote areas were asked two additional sets of questions about levels of mastery (the sense of control over one’s life) and perceptions of social support.

#### Kessler 5 (K5) score

The Kessler 5 (K5) score is a measure of non-specific psychological distress, derived from a modified version of the Kessler Psychological Distress Scale (K10). It uses five questions (instead of 10), and is designed for use in surveys of Aboriginal and Torres Strait Islander peoples. For more information see Information Paper: Use of the Kessler Psychological Distress Scale in ABS Health Surveys, Australia (cat. no. 4817.0.55.001).

The K5 (and K10) is not a diagnostic tool, but is used as an indicator of levels of psychological distress experienced recently.

• Respondents were asked questions about how often they had experienced negative emotional states in the previous four weeks by selecting one of five responses presented on a prompt card, ranging from ‘all of the time’ to ‘none of the time’.
• ‘Don’t know’ and refusal options were available and, if selected, an overall score was unable to be determined.
• Responses to the questions were combined to produce an overall score between five and 25.
• The scores were then grouped to describe the level of psychological distress as low/moderate (5–11) or high/very high (12–25).

The psychological distress results are comparable with the 2012–13 NATSIHS and the 2014–15 NATSISS. They are also comparable with the 2017–18 NHS, but there are some differences:

• the NHS uses the K10 instead of the K5
• two of the questions in the K10 are asked slightly differently in the K5 to ensure the questions are culturally relevant for Aboriginal and Torres Strait Islander people
• respondents were unable to select a response of ‘Don’t know’ in the NHS.

#### Positive wellbeing

There were four positive wellbeing questions, taken from the mental health and vitality scales of the Short Form 36 Health Survey (SF–36).

• Respondents were asked questions about how often they had experienced positive emotional states in the previous four weeks by selecting one of five responses presented on a prompt card, ranging from ‘all of the time’ to ‘none of the time’.
• ‘Don’t know’ and refusal options were available.

The results from each of the four questions are comparable with the 2012–13 NATSIHS and the 2014–15 NATSISS.

#### Pearlin Mastery Scale (non-remote only)

The Pearlin Mastery Scale is a set of seven statements used to measure how much a person feels in control over life events and outcomes. Higher levels of mastery can lessen the impact of stress on a person’s physical and mental wellbeing.

• Respondents were asked to respond to each statement by selecting one of four responses presented on a prompt card, ranging from ‘strongly agree’ to ‘strongly disagree’.
• ‘Don’t know’ and refusal options were available and, if selected, an overall score was unable to be determined.
• Responses to the statements were combined to produce an overall score between seven and 28.
• The scores were then grouped to describe the level of mastery as low (7–19) or high (20–28).

The Pearlin Mastery overall score and results from the individual statements are not comparable with the 2012–13 NATSIHS due to response category changes.

#### Multidimensional Scale of Perceived Social Support (MSPSS) (non-remote only)

A set of six statements from the Multidimensional Scale of Perceived Social Support (MSPSS) was used to measure a person’s perception of the social support they receive from family and friends.

• Respondents were asked to respond to each statement by selecting one of seven responses presented on a prompt card, ranging from ‘very strongly disagree’ to ‘very strongly agree’.
• ‘Don’t know’ and refusal options were available and, if selected, a score was unable to be determined.
• Responses to the statements were combined to produce a family score, a friends score and an overall score.
• The family, friends and overall scores were grouped to describe the level of perceived social support from each dimension as low (1–2.9), moderate (3–5) or high (5.1–7).

The MSPSS family, friends and overall scores and results from the individual statements are not comparable with the 2012–13 NATSIHS due to response category changes.

#### Other questions

Several other questions were asked to determine:

• the impact of psychological distress on employment and other regular activities
• how often physical health problems had been the cause of psychological distress
• use of health and community services, such as doctors and counsellors, for mental health
• barriers to using health services for mental health.

## Appendix - assessing health risk factors

### Show all

This appendix provides information about the guidelines and measures used to assess some specific lifestyle and related factors that impact on health.

#### Alcohol consumption

Alcohol consumption risk levels were assessed using the single occasion and lifetime risk guidelines from the National Health and Medical Research Council (NHMRC) 2009 Australian Guidelines to Reduce Health Risks from Drinking Alcohol.

• These two guidelines are for people aged 18 years and over and recommend a maximum number of standard drinks per day. A standard drink contains 12.5 millilitres (mLs) of alcohol.
• A separate guideline advises that, for people aged 15–17 years, the safest option is to delay the initiation of drinking alcohol for as long as possible. In this survey, people aged 15–17 years are assessed against the single occasion and lifetime risk guidelines to provide an estimate of the level of risk for this age group.

Alcohol consumption is likely to be under-reported. Some people who drank alcohol may not have reported it, and some may have reported it but understated the quantity consumed. The extent to which under-reporting has occurred is not able to be quantified.

#### Single occasion risk guideline

The single occasion risk guideline advises healthy males and females to drink no more than four standard drinks on a single occasion to reduce the risk of alcohol-related injury arising from that occasion.

In this survey, a person was considered to have exceeded the single occasion risk guideline if they had consumed more than four standard drinks on at least one day in the last 12 months.

• This was assessed using a person’s response to questions about the number of times in the last 12 months they had consumed five or more standard drinks in one day.
• The number of standard drinks was as reported by the person. This is different to the lifetime risk guideline, where the number of standard drinks was derived from information about the number, type, brand, and serving size of drinks consumed.

The lifetime risk guideline advises healthy males and females to drink no more than two standard drinks per day to reduce the risk of harm from alcohol-related disease or injury over their lifetime.

In this survey, a person was considered to have exceeded the lifetime risk guideline if they had consumed more than two standard drinks per day on average in the last week. It was assumed the level of alcohol consumption in the last week was typical.

The average number of standard drinks per day was derived from information provided by the person about:

• the number, type, brand, and serving sizes of alcoholic drinks consumed on (up to a maximum of) the three most recent days alcohol was consumed in the week prior to interview, and
• the total number of days alcohol was consumed that week.

It was derived by:

• calculating the total amount of alcohol consumed (in mLs) for each drink type by multiplying the alcohol content (%) by the volume (mL), based on the type (e.g. light beer, red wine), brand and number of drinks reported on the maximum of three most recent days alcohol was consumed in the previous week
• summing the drink type results to derive the total alcohol consumption for the maximum of three most recent days alcohol was consumed
• dividing that result by the number of days on which alcohol consumption was reported (that is, by one, two or three) to derive average daily alcohol consumption for those days
• multiplying that daily average by the total number of days alcohol was consumed that week, and
• dividing the result by seven to arrive at the average number of standard drinks consumed per day.

Where the precise type and/or brand of the drink was not known, the following default alcohol content values were used:

• light beer — 2.7%
• mid-strength beer — 3.5%
• full-strength beer — 4.9%
• wine coolers — 3.5%
• low alcohol wines — 0.9%
• fortified wines — 17.8%
• white wine — 12.4%
• red wine — 13.3%
• sparkling wine/champagne — 13.3%
• spirits — 40.0%
• liqueurs — 20.0%
• pre-mixed spirits (e.g. UDL) — 5.0%
• alcoholic cider — 4.7%
• cocktails — 31.5%
• other alcoholic drinks — 27.4%.

Particular types or brands may contain more or less alcohol than this. However, the default values were considered sufficiently representative for the purposes of assessing lifetime risk and single occasion risk.

#### People who did not consume any alcohol

People who did not consume any alcohol in the week prior to interview were categorised as:

• last consumed more than one week to less than 12 months ago
• last consumed 12 months or more ago, or
• never consumed.

#### Further information about measuring alcohol consumption

For a detailed explanation of the method used to measure alcohol consumption in ABS health surveys, see Alcohol Consumption in Australia: A Snapshot (cat. no. 4832.0.55.001).

#### Blood pressure (measured)

People aged 18 years and over were asked to provide a blood pressure reading, voluntarily taken by the interviewer at the time of interview. Readings were categorised as:

• normal — less than 120/80 mmHg (millimetres of mercury)
• normal-high — from 120/80 to less than 140/90
• high — from 140/90 to less than 160/100
• very high — from 160/100 to less than 180/110
• severe — from 180/110.

People were placed in the highest of the categories that either the systolic or diastolic reading fell into.

A reading of 140/90 mmHg or higher does not necessarily indicate a person has hypertension. In this survey, hypertension is defined as a condition that has lasted, or which the respondent expects to last, for six months or more.

The reading also does not take into account whether a person might have had a high blood pressure reading if they were not managing it through the use of medication.

#### Body Mass Index (BMI)

Body Mass Index (BMI) is a simple index of weight-for-height, commonly used for defining whether a person is underweight, normal weight, overweight or obese.

A BMI score is calculated using the formula weight (in kilograms) divided by the square of height (in metres). For example, a person who weighs 70 kilograms and whose height is 1.75 metres will have a BMI of 22.9 (70/(1.75m2) = 70/3.06 = 22.9).

There were two measures of BMI in this survey:

• self-reported (for people aged two years and over) — based on a person reporting their height and weight
• measured (for people aged two years and over) — based on a measure of the person’s height and weight, voluntarily taken by the interviewer at the time of interview.

Interviewers used digital scales to measure weight (maximum 200 kilograms) and a stadiometer to measure height (maximum 210 centimetres). Women who advised they were pregnant were not measured. For more information see Appendix - physical measurements.

#### BMI classification for persons aged 18 years and over

People aged 18 years and over were classified as underweight, normal weight, overweight or obese based on their BMI score as recommended by the World Health Organization’s BMI Classification:

• underweight Class 3 — 15.99 or less
• underweight Class 2 — 16.00–16.99
• underweight Class 1 — 17.00–18.49
• normal range — 18.50–24.99
• overweight — 25.00–29.99
• obese Class 1 — 30.00–34.99
• obese Class 2 — 35.00–39.99
• obese Class 3 — 40.00 or more.

#### BMI classification for children aged 2–17 years

BMI categories for children aged 2–17 years were:

• underweight — Class 3, Class 2, and Class 1
• normal range
• overweight
• obese Class 1.

The BMI scores for each category take into account the age and sex of the child. For a detailed list of the cut-offs see Appendix 4 in the National Health Survey: Users’ Guide, 2017–18 (cat. no. 4363.0).

#### Breastfeeding

Breastfeeding of children aged three years and under was assessed using the National Health and Medical Research Council's 2012 Infant Feeding Guidelines. The guidelines recommend infants:

• be exclusively breastfed to around six months of age (the six month guideline)
• continue to be breastfed with appropriate complementary foods until at least 12 months of age (the 12 month guideline).

The six month guideline was considered to have been met if a child had been exclusively breastfed for at least six months. Children under the age of six months were excluded.

The 12 month guideline was considered to have been met if a child was exclusively breastfed for at least six months and then continued to be breastfed to 12 months of age. Children under the age of 12 months were excluded.

If unable to determine whether a child was exclusively breastfed for six months, or exclusively breastfed for six months then continued to be breastfed to 12 months of age, they were classified as not known.

For further information about collection methods and data quality see Explanatory notes section.

#### Fruit and vegetable consumption

Fruit and vegetable consumption was assessed using the National Health and Medical Research Council (NHMRC) 2013 Australian Dietary Guidelines.

• The guidelines recommend a minimum number of serves of fruit and vegetables each day, depending on a person's age and sex.
• Several age recommendations include half servings. In this survey, only whole serves were collected, so half serves in the guidelines were rounded up to the nearest whole serve for the purpose of assessing whether a person met the relevant guideline.

#### Usual daily intake of fruit

Both males and females were considered to have met the guideline for fruit consumption if they usually consumed at least the following number of serves per day:

• one serve for those aged 2–3 years
• two serves for those aged four years and over.

One serve is approximately 150 grams of fresh fruit or 30 grams of dried fruit.

#### Usual daily intake of vegetables

Children were considered to have met the guideline for vegetable consumption if they consumed at least the following number of serves per day:

• three serves for those aged 2–3 years
• five serves for those aged 4–8 years
• five serves for those aged 9–11 years
• six serves for boys aged 12–17 years
• five serves for girls aged 12–17 years.

People aged 18 years and over were considered to have met the guideline if they usually consumed at least the following number of serves per day:

• six serves for males aged 18–70 years
• five serves for males aged 71 years and over
• five serves for females aged 18 years and over.

One serve is approximately half a cup of cooked vegetables or one cup of salad vegetables — equivalent to approximately 75 grams.

#### Physical activity (non-remote)

Physical activity undertaken by people living in non-remote areas was assessed based on an interpretation of Department of Health guidelines.

• For the 2014 guidelines, the Australia’s Physical Activity and Sedentary Behaviour Guidelines were used, which differ by age group. In this survey, the workplace activity component of the guidelines was excluded.
• For the pre-2014 guidelines, the National Physical Activity Guidelines for Australian Adults were used for all people aged 18 years and over.

To meet either set of guidelines, people needed to do varying combinations of some or all of the following physical activities:

• walking for transport
• walking for fitness, recreation or sport
• moderate intensity exercise
• vigorous intensity exercise
• strength or toning activities.

#### 2014 guidelines for people aged 15–17 years

In this survey, people aged 15–17 years were considered to have met the guidelines if, in the last week, they did:

• one or more of the following for at least 60 minutes every day: ­walking for transport, walking for fitness, recreation or sport, moderate intensity exercise, or vigorous intensity exercise, and
• some vigorous intensity exercise, and
• strength or toning activities on at least three days.

#### 2014 guidelines for people aged 18–64 years

In this survey, people aged 18–64 years were considered to have met the guidelines if, in the last week, they:

• did one or more of the following at least five days: walking for transport, walking for fitness, recreation or sport, moderate intensity exercise, or vigorous intensity exercise, and
• accumulated at least 150 minutes of any combination of the above (vigorous intensity exercise time is multiplied by two), and
• did strength or toning activities on at least two days.

#### 2014 guidelines for people aged 65 years and over

In this survey, people aged 65 years and over were considered to have met the guidelines if, in the last week, they did:

• one or more of the following every day: walking for transport, walking for fitness, recreation or sport, moderate intensity exercise, or vigorous intensity exercise, and
• any combination of the above for at least 30 minutes on five or more days.

#### Pre-2014 guidelines for people aged 18 years and over

There were two guidelines for people aged 18 years and over. In this survey, people were considered to have met:

• the first guideline if, in the last week, they had accumulated 150 minutes of physical activity from any combination of the following: walking for transport, walking for fitness, recreation or sport, moderate intensity exercise, or vigorous intensity exercise
• the second guideline if, in the last week, they met the first guideline and undertook any of those activities on at least five occasions.

For more information about the pre-2014 guidelines, see Australian Aboriginal and Torres Strait Islander Health Survey: Users’ Guide, 2012–13 (cat. no. 4727.0.55.002).

#### Smoking

People aged 15 years and over were asked about the extent to which they were regularly smoking tobacco products and using e-cigarettes/vaping at the time of interview.

Tobacco products include:

• manufactured (packet) cigarettes
• roll-your-own cigarettes
• pipes, cigars or other tobacco products.

Tobacco products exclude:

• chewing tobacco
• smoking of non-tobacco products (such as marijuana).

A person’s smoker status for tobacco products was categorised as:

• current daily smoker — a person who reported they regularly smoked one or more cigarettes, pipes, cigars or other tobacco products per day
• current smoker less than daily — a person who reported they smoked cigarettes, pipes, cigars or other tobacco products less frequently than daily
• ex-smoker — a person who reported they did not currently smoke but had previously either regularly smoked daily, smoked at least 100 cigarettes in their lifetime, or smoked pipes, cigars or other tobacco products at least 20 times in their lifetime
• never smoked — a person who reported they had never regularly smoked daily, smoked less than 100 cigarettes in their lifetime, and smoked pipes, cigars or other tobacco products less than 20 times in their lifetime.

An e-cigarette user/vape smoker was a person who uses or has ever used an electronic cigarette, a battery operated device that resembles tobacco cigarettes, pipes or cigars to inhale nicotine and/or other chemicals in a vapour form rather than smoke.

• For e-cigarettes/vapes containing nicotine, people were asked if they had used them in the previous 12 months and, if so, how often.
• For e-cigarettes/vapes excluding nicotine, people were asked whether they had ever used them and, if currently using them, how often.

Smoking is likely to be under-reported. Some current smokers may not have identified as such due to social pressures, especially where other household members were present at the interview. The extent to which under-reporting has occurred is not able to be quantified.

#### Waist circumference

Waist circumference is a measurement, in centimetres (cm), of a person’s waist. Measurements were voluntarily taken:

• by the interviewer at the time of interview using a tape measure (maximum 200 cm)
• from people aged two years and over, excluding women who had volunteered that they were pregnant.

The waist circumferences of people aged 18 years and over were classified by sex as recommended by the World Health Organization’s 2008 Waist Circumference and Waist-Hip Ratio: Report of a WHO Consultation as:

• not at risk — less than 94 cm for males, or less than 80 cm for females
• increased risk — 94 cm to less than 102 cm for males, or 80 cm to less than 88 cm for females
• substantially increased risk — 102 cm or more for males, or 88 cm or more for females.

## Appendix - physical and threatened physical harm data

### Show all

#### Collection of the data

People were asked to provide information on their experiences of physical and threatened physical harm in the previous 12 months.

Physical harm refers to any incident where a person was physically hurt or harmed by someone on purpose, including physical fights. Other forms of abuse (e.g. sexual, emotional, psychological) are not included.

Threatened physical harm refers to threats of physical harm that occurred either face-to-face or non-face-to-face (e.g. via instant message/social networking sites, text message, phone, email or writing).

• Due to the sensitive nature of the questions, responses were not compulsory, and a person may have chosen not to answer some or any of the questions.
• The same question wording was used in both non-remote and remote areas.
• This is the first time questions on physical and threatened physical harm have been included in the National Aboriginal and Torres Strait Islander Health Survey.
• The development and testing of the questions was overseen by an expert advisory panel, comprising members from government and non-government agencies.
• The question wording used in 2018–19 was drawn from a variety of ABS surveys and was thoroughly tested in non-remote and remote areas of Australia, including in discrete Indigenous communities.

#### Relationship to offender

People who had experienced physical harm or face-to-face threatened physical harm in the last 12 months were asked to identify:

• the offender(s) of the most recent incident
• the offender(s) related to all incidents within the last 12 months.

People may have experienced physical harm or face-to-face threatened physical harm by more than one offender in the previous 12 months. An offender may have been an Aboriginal or Torres Strait Islander person or a non-Indigenous person.

#### Identifying experiences of family and domestic violence

A person is considered to have experienced family and domestic violence within the context of the survey if they identified an intimate partner or family member as an offender.

An intimate partner is a:

• current partner (husband/wife/defacto)
• previous partner (husband/wife/defacto)
• boyfriend/girlfriend/ex-boyfriend/ex-girlfriend, or
• date.

A family member is a:

• parent
• child
• sibling, or
• other family member.

#### Data limitations

Experiences of harm are likely to be under-reported. While the relationship to offender data items can provide an indication of the number of people that have experienced physical harm or face-to-face threatened physical harm, the data does not provide a complete picture of physical harm, or the prevalence of family and domestic violence.

• Interviews are conducted face-to-face with a trained interviewer, but there is no requirement for a private interview setting. People may be less likely to disclose any experiences of physical harm or threatened physical harm by an intimate partner or family member if the offender is present in the home at the time of the interview.
• Some people who have experienced physical harm or threatened physical harm may not have wished to disclose this to the interviewer for other reasons.

#### Comparability to other data sources

The physical and threatened physical harm data collected in 2018–19 is not comparable to other ABS data sources collecting similar data, including:

## Appendix - survey topics

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Below is a list of topics included in the 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) as well as the degree of change to the questions from the last iteration of the survey in 2012–13. For more detail, see the Data Item List in the Data downloads section. The Data Item List also contains information about whether the item is comparable to the 2012–13 NATSIHS or the 2017–18 National Health Survey.

TopicDegree of change since 2012-13
SpokespersonMajor
Proxy checkNone
LanguageMinor
Educational attainmentMinor
Current studyMinor
EmploymentMinor
Self-assessed healthMinor
Body massMinor
Physical activityMinor
Smoker statusMinor
Tobacco consumptionMinor
ImmunisationNone
Social and emotional wellbeingMinor
DietMajor
BreastfeedingMajor
AlcoholMinor
Substance useMajor
DisabilityMajor
AsthmaMinor
CancerMinor
CardiovascularMinor
ArthritisNone
OsteoporosisNone
DiabetesMinor
Kidney diseaseNone
Sight and hearingMajor
Mental health conditionsNew
Other long-term conditionsMinor
MedicationsNew
Usual and preferred service providersMajor
Hospital visitsMinor
Doctors consultationsMajor
Oral healthMinor
Other health professionalsMinor
DiscriminationMajor
Private health insuranceMajor
Cultural identificationNone
Experiences of harmNew
IncomeMajor
Personal pensions and allowancesMajor
Blood pressureMinor
Physical measuresMinor
Hearing testNew

## Appendix - non-Indigenous comparisons

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When making comparisons between populations, it is important to consider whether these groups have different age structures. The Aboriginal and Torres Strait Islander population has a younger population than the non-Indigenous population. To account for the difference in age, the ABS uses a technique called age standardisation to produce proportions that people can use for comparison purposes. It is not recommended to compare results from the NATSIHS to other sources, such as the National Health Survey, if the data has not been age standardised.

#### Accessing non-Indigenous comparisons to 2018-19 data

In order to allow comparisons, the published results of the 2018–19 NATSIHS include selected data cubes with age standardised proportions presented for both the non-Indigenous and the Aboriginal and Torres Strait Islander populations. Data cubes can be accessed via the Data downloads section.

#### Age standardisation

Age standardisation is a technique used to enhance the comparability of rates between populations with different age structures. As many population characteristics are age-related, (for example, long-term health conditions and employment patterns), adjustments are made to account for the effects of the different age structures on the prevalence of these characteristics.

As age is strongly related to many health measures, estimates of prevalence which do not take account of age may be misleading. The age standardised estimates of prevalence are those rates that ‘would have occurred’ should both the Aboriginal and Torres Strait Islander and non-Indigenous populations have the same age composition. For this reason, where appropriate, estimates for Aboriginal and Torres Strait Islander people and non-Indigenous people have both been age standardised to reflect the age structure of the same population.

#### Rate ratios

The difference between age standardised rates can be expressed through rate ratios. A rate ratio is a ratio calculated by dividing the age standardised proportion of Aboriginal and Torres Strait Islander people with a particular characteristic by the age standardised proportion of non-Indigenous people with the same characteristic.

• A rate ratio of 1.0 indicates the age standardised prevalence of the characteristic is the same in the Aboriginal and Torres Strait Islander and non-Indigenous populations.
• A rate ratio greater than 1.0 indicates the age standardised prevalence of the characteristic is higher in the Aboriginal and Torres Strait Islander population.
• A rate ratio less than 1.0 indicates the age standardised prevalence of the characteristic is lower in the Aboriginal and Torres Strait Islander population.

## Appendix - hearing data

### Show all

In the 2018-19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), information about hearing was collected in two ways:

• reported by the respondent
• measured using a voluntary hearing test.

#### Reported hearing impairment

Respondents were presented with a prompt card and asked whether they had any hearing problems that had lasted, or were expected to last, for at least six months.

Respondents who indicated that they had one or more of the following were considered to have long-term hearing impairment in one or both ears:

• total deafness
• deaf in one ear
• hearing loss or partially deaf.

#### Measured levels of hearing

Measurements of hearing were collected from respondents aged seven years and over who did not have a cochlear implant using a voluntary, self-administered test. This was the first time this data has been collected by the ABS.

#### Methodology

The ABS worked with the National Acoustics Laboratories, the research division of Hearing Australia, to create a test that respondents could use on the interviewers' laptops out in the field to:

• detect whether a respondent had a hearing impairment in one or both ears
• assess a respondent’s level of hearing impairment where there was a hearing impairment.

The hearing test required respondents to listen through headphones to a series of beeps over two audio frequencies (one kilohertz and four kilohertz) and respond to hearing a beep by pressing a key on the laptop. Respondents were given a chance to practice prior to the test being administered.

Respondents who completed the test were given their results on a Measurements Card (available on the Downloads tab). The result for each ear was reported on the card as:

• pass, or
• see your GP or health service.

There is variability in the descriptors and ranges used to describe level of hearing impairment both within Australia and internationally. The test categorised the results into the following levels of hearing impairment for each ear, which were based on advice from the National Acoustics Laboratories:

• no measured hearing impairment – quietest sound that can be heard is 20 decibels or lower
• mild hearing impairment – quietest sound that can be heard is between more than 20 decibels and 40 decibels
• moderate hearing impairment – quietest sound that can be heard is between more than 40 decibels and 60 decibels
• severe or profound hearing impairment – quietest sound that can be heard is more than 60 decibels.

Respondents with a hearing impairment in both ears were classified by level of hearing impairment based on the ear with the better hearing. For example, respondents with a mild hearing impairment in one ear and a moderate hearing impairment in the other ear were classified as having a mild hearing impairment.

There are limitations with the hearing test – for example, the test is undertaken in the field with background noises, rather than in a soundproof room. However, a comparison of hearing test results with reported hearing impairment can indicate a respondent may have an unreported hearing impairment.

#### Response rates

The hearing test had a relatively high rate of non-response due to its voluntary and potentially sensitive nature.

#### Response rates for hearing test(a), by age and remoteness

NON-REMOTEREMOTETOTAL
Persons in sampleHearing test completedPersons in sampleHearing test completedPersons in sampleHearing test completed
no.%no.%no.%
Age group (years)
7–945935.528437.074336.1
10–1471638.037840.21 09438.8
15–1950543.828537.579041.5
20–2444955.021852.866754.3
25–2943354.029647.372951.3
30–3444152.632449.476551.2
35–3934048.826449.260449.0
40–4432251.624038.356245.9
45–4935645.825950.261547.6
50–5432447.521146.453547.1
55 years and over1 09245.858142.51 67344.7
Total persons aged 7 years and over5 43746.33 34044.28 77745.5
a. Respondents without a cochlear implant.

The data from those who undertook the hearing test was then used to impute the data for those who had not taken part in the test. Imputation gives a more complete and useful dataset. The following information was produced from the hearing test:

• summary result code for left ear (normal, mild, moderate, severe or worse) [1]
• summary result code for right ear (normal, mild, moderate, severe or worse) [1]
• whether hearing issue in one or both ears.

#### How imputation works

Missing values were imputed using two steps.

Firstly, all persons aged seven years and over were imputed as having a severe or profound hearing impairment in both ears if they reported they:

• had a hearing aid in both ears.

Then a 'hot decking' imputation method was used. In this method, a record with a missing response (the 'recipient') receives the response of another similar record (the 'donor'). Due to the low response rates, a donor could be used up to five times to populate recipient records. Persons with imputed values from the first step were excluded from this second step of the imputation process.

After some correlation analysis, a number of characteristics (imputation variables) were used to match recipients to donors:

• sex
• whether uses a hearing aid
• disability status
• highest year of school completed
• proficiency in English
• labour force status
• state/territory of residence
• type of health services available in local area.

For example, a female recipient who has a hearing aid in one ear, has a profound disability, has completed Year 10 or higher, speaks English well or very well, is not in the labour force, lives in Tasmania, and has no doctor/GP in the local area will match to a donor record who has the same profile (female, has a hearing aid in one ear, has a profound disability, etc).

Using these variables, all of the eligible recipient records were able to be imputed successfully.

#### Impact of imputation

The table below shows the impact of imputation on summary results for left and right ears.

#### Measured and imputed hearing test results(a), by remoteness

MEASURED ONLY(b) MEASURED AND IMPUTED(c)
Left ear Right ear Left ear Right ear
Level of hearing impairmentno.% no.% no.% no.%
Non-remote
No measured hearing impairment1 68368.2 1 72469.9 3 56965.5 3 69767.8
Mild hearing impairment52221.2 46518.8 1 14020.9 99318.2
Moderate hearing impairment1546.2 1646.6 3346.1 3536.5
Severe or profound hearing impairment1084.4 1144.6 4077.5 4077.5
Total non-remote2 467100.0 2 467100.0 5 450100.0 5 450100.0
Remote
No measured hearing impairment77252.7 77252.7 1 73551.9 1 73852.0
Mild hearing impairment45631.1 47732.6 1 05131.4 1 06731.9
Moderate hearing impairment1258.5 1349.2 2708.1 3049.1
Severe or profound hearing impairment1117.6 815.5 2868.6 2337.0
Total remote1 464100.0 1 464100.0 3 342100.0 3 342100.0
Total
No measured hearing impairment2 45562.5 2 49663.5 5 30460.3 5 43561.8
Mild hearing impairment97824.9 94224.0 2 19124.9 2 06023.4
Moderate hearing impairment2797.1 2987.6 6046.9 6577.5
Severe or profound hearing impairment2195.6 1955.0 6937.9 6407.3
Total3 931100.0 3 931100.0 8 792100.0 8 792100.0
a. Using 2018–19 National Aboriginal and Torres Strait Islander Health Survey unweighted sample counts.
b. Respondents aged seven years and over without a cochlear implant.
c. Respondents aged seven years and over.

#### Weighting imputed data

The imputation process meant that a new set of replicate weights had to be created for the imputed hearing test data. This is because the imputation process used donor records (and could use them up to five times), which can artificially lower the Relative Standard Errors. The new set of replicate weights adjusted for this and for the additional uncertainty in the estimates due to the use of imputed values rather than reported values.

Jackknife variance estimation for hot deck imputation was used to create the new replicate weights. This resulted in an increased variance when compared to the un-imputed data, which is to be expected.

Each record also retained the original main weight calculated as part of the normal weighting process – see Response rates, sample counts and estimates (appendix).

#### Footnote

1. Two of the labels used for the summary result code, which also appear in the data item list, are referred to by different labels throughout the rest of this appendix and in all hearing test-related commentary. 'Normal' is referred to as 'no measured hearing impairment' and 'severe or worse' is referred to as 'severe or profound'.

## Appendix - modelled estimates for small areas

### Show all

#### 1 Introduction

This publication contains modelled estimates of health conditions and risk factors for small areas based on data from the 2018-19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS), 2016 Estimated Resident Population (ERP), the 2016 ABS Census of Population and Housing, and aggregate administrative data sources. The term “small area” generally refers to a geographical area that is smaller than a state or territory, such as Indigenous Regions and Primary Health Networks.

#### 2 Methodology used

A modelled estimate can be interpreted as the expected number or proportion of people with a health condition or characteristic for an area of Australia based on the demographic information available for that area. The process of producing modelled small area estimates for health conditions measured in the NATSIHS consisted of the following components, described in detail in sections 2.1 to 2.9:

1. Identification of the outcome variables
2. Identification of the geographical areas
3. Selection of the predictor variables
4. Scoping the data
5. Creation of binary and proportion variables
6. Aggregating observations and merging datasets
7. Model selection
9. Assessment of the modelled estimates

#### 2.1 Identification of the outcome variables

From the NATSIHS, modelled small area estimates (counts, proportions, measure of error) have been produced for persons with the following health conditions and risk factors:

• Self-assessed health status, by sex
• Smoking status, by sex
• Body Mass Index, by sex
• Number of long term health conditions, by sex
• Disability status, by sex
• Psychological distress, by sex
• Alcohol long term risk
• Alcohol short term risk
• Substance use
• Number of chronic conditions, by sex
• Specific long term health conditions, by age group

For age groups:

• All ages
• 0 to 39 years
• 40 to 54 years
• 55 years and over

For more information about the outcome variables, including definitions, see the footnotes in each Data cube, the Glossary, or Explanatory Notes on the ABS Website.

#### 2.2 Identification of the geographical areas

The modelled estimates for small areas have been produced at the Indigenous Region (IREG) and Primary Health Network (PHN) geographies.

#### 2.3 Selection of the predictor variables

In order to predict outcome variables, predictor variables are required on both the NATSIHS dataset and a small area dataset containing population, Census, and administrative data. Predictor variables were created if data were available for small areas for all of urban, rural, remote and very remote Australia and if there was an expectation that they might be good predictors of the outcome variables.

For age and sex predictor variables, data at the small area level were obtained from ABS ERP data from Estimates of Aboriginal and Torres Strait Islander Australians, June 2016 (Cat. No. 3238.0.55.001). This is described below in section 2.4.

For other demographic variables collected in the NATSIHS, data at the small area level were obtained from the 2016 Census of Population and Housing, as this was the most up-to-date comprehensive source of demographic data due to the depth of information at small geographical levels.

Additional variables that were available at the small area level but not collected in the NATSIHS were also included in the model. These variables included other demographic variables on the Census, geographic variables, and variables from administrative sources.

Predictor variables that relate to the geographical areas where people reside included:

• remoteness area
• socio-economic indexes for areas (SEIFAs) – population-weighted deciles at the Statistical Areas Level 1 (SA1) level
• state and territory
• section of state (major urban/other urban/bounded locality/rural balance)
• Greater Capital City Statistical Area (GCCSA)/balance of state
• design area type (categorises inner city, large and small urban towns, rural towns and remote areas within states and territories for designing the sample of the NATSIHS)

Sources of geographical area data included:

Predictor variables obtained from administrative data sources are described in the following table:

Predictor variableData source
Indigenous Relative Socioeconomic Outcomes index (IRSEO) (2016)Public Health Information Development Unit (PHIDU) November 2019 release
http://phidu.torrens.edu.au/social-health-atlases/data#aboriginal-torres-strait-islander-social-health-atlas-of-australia
Participation in vocational education and training (2017)
Home and Community Care Program (HACC) clients (2014-15)
Proportion of Indigenous persons (2016)

Within most types of predictor variables (as discussed above), several separate categories of data items were included. The variables considered for inclusion in the model are listed in the Predictor variables tab of the Datacube.

#### 2.4 Scoping the data

The modelled estimates for small areas are applicable to persons who were usual residents of private dwellings to match the scope of the NATSIHS. They exclude:

• non-private dwellings, for example hospitals and aged care facilities

The base data source used to compile the modelled small area estimates was the ABS Estimated Resident Population (ERP) data from Estimates of Aboriginal and Torres Strait Islander Australians, June 2016 (Cat. No. 3238.0.55.001). Adjustments were made to the ERP data, by using ratios of private to non-private dwellings, calculated from the 2016 Census to match the scope of the NATSIHS, and then summed to the NATSIHS population state by age by sex estimates. These are the ‘population denominator’ estimates included in the Data cube. It is important to note that these population estimates are not official estimates and were created solely for analysis of the NATSIHS modelled small area estimates and will not match other population data at the IREG or PHN geography level.

Adjustments were also made to the Census data, specifically the predictor variables obtained from the Census (described above in section 2.3) to match the scope of the NATSIHS. Persons residing in non-private dwellings were removed from the small area dataset using persons’ dwelling type available on the Census datasets for respondents at home on Census night. However, for persons who were not at home on Census night, information is not collected to determine if the dwelling they usually reside in is a private or non-private dwelling; therefore, their records were deleted from the small area dataset. This data adjustment assumes that the people who were away from home on Census night and live in private dwellings have the same health characteristics as the people who were at home in a private dwelling.

Modelled estimates were not produced for IREGs or PHNs that are entire states. This includes the Tasmania and ACT IREGs; and the Tasmania, NT and ACT PHNs. State-level data should be obtained from the NATSIHS published data or the TableBuilder product, as the NATSIHS sample size is designed to be sufficient at State and Territory level to directly estimate these health statistics. Modelled small area estimates are not designed for use at large geographies such as states.

Additional exclusions that were applied to the data included:

• residents of Other Territories

#### 2.5 Creation of binary and proportion variables

On the NATSIHS dataset outcome variables were created as binary variables to make them suitable for the type of modelling undertaken (logistic regression). For the outcome variables described in section 2.1 binary variables are created for each category of the outcome variable. For example, in the case of Body Mass Index, binary variables are created separately for underweight/normal weight, overweight, and obese. On both the NATSIHS and the small area datasets, predictor variables that were categorical were also created as binary variables. An observation took the value of 1 if an individual had a characteristic of interest and 0 otherwise. For example:

1. in the case of overweight, the outcome variable for overweight took the value of 1 if an individual was overweight and 0 if the individual was not overweight
2. in the case of labour force status, the predictor variable for employed took the value of 1 if an individual was employed and 0 if the individual was unemployed, not in the labour force or aged 0-14 years

Binary variables were also created on the small area dataset denoting quintiles of the characteristic of interest. For example:

• for hospital admissions, a binary variable was created to denote whether the person lived in an area in the bottom quintile of admission rates

In addition, proportions of an area’s population with the characteristic of interest is also calculated as a predictor variable. For example:

• the proportion of an area’s population having had a hospital admission is recorded as a predictor variable for each small area

#### 2.6 Aggregating observations and merging datasets

All data sources were aggregated to a fixed structure (cross classification cell groups) including several levels of geography, five year age group and sex. This decreases the size of the datasets (especially the Census dataset) to increase the efficiency of the modelling process.

The Census, adjusted ERP and administrative datasets were then merged into one small area dataset.

#### 2.7 Model selection

Models were created for each outcome variable, and each category of the outcome variables described in section 2.1 independently. For example, a different model is created and selected for overweight than for obese. However within each outcome variable the same model is used for each output classification, for example geography, age group, and sex.

The model selection method uses the small area dataset to measure the relationship between the outcome variable and possible predictor variables to determine one set of significant predictor variables. This method assumes that the relationships observed in the survey data at State and National levels also hold at the small area level. The significant predictor variables for each model are listed in the Predictor variables tab of the Data cube.

Random effects logistic regression models are used for each outcome variable. As part of any model selection process an appropriate significance level must be chosen for determining which predictor variables to include in the models. The 0.05 (95%) level is most commonly used; however, due to NATSIHS’ relatively large sample sizes, the Bayesian Information Criterion (BIC) was used to reduce the risk of over-fitting.

To verify that the model adequately predicted the outcome variable, the models were applied to small area data, summed to create Australia level modelled estimates and compared with reliable direct survey weighted estimates. This property is known as model additivity. Where model additivity was not similar, additional predictor variables were included in the model until suitable model additivity was achieved.

Using the selected model for each outcome variable, a mixed estimate comprised of modelled and survey data is then produced for each small area output classification (IREG or PHN by sex or age group). A mixed/composite estimate reflects the best trade-off between the accuracy of the direct survey weighted estimate and the error associated with the modelled estimate. For a small area that happens to have a low sampling error (because of a large sample size within that small area, for example), more weight will be given to the direct estimate when calculating a modelled estimate for that small area. On the other hand, for a small area with high sampling error, more weight will be given to the model based prediction as this will be more reliable in calculating the modelled estimate for that small area. This takes advantage of what is known about the small area location from the survey to improve the modelled estimates.

#### 2.8 Final adjustments and outputs

The modelled estimates are then adjusted so that they sum to national direct survey estimates. The adjustment also ensures that estimates for outcome variable categories within a broader outcome category, for example Body Mass Index categories sum to the population within each small area. The associated errors resulting from the modelling process (described in Section 3), which improve on direct survey estimates’ errors, were not adjusted.

The modelled estimates in the Datacube as:

• counts with selected characteristic (number of persons)
• relative error
• proportion
• 95% margin of error of proportion (95% MoE)
• total population (expected number of people in each small area).

The denominators (total population) used to calculate the proportions are the unofficial population estimates for each IREG or PHN (based on adjusted ERP) described above in section 2.4.

To mitigate against the identification of survey respondents, modelled estimates have been confidentialised to ensure they meet ABS requirements for confidentiality. Small area locations (IREGs or PHNs) with populations or modelled counts that didn’t meet the confidentiality rules have modelled estimates comprised solely of the modelled component, rather than the mixed/composite estimator described above. This means that no sampled contribution is included in such modelled estimates, regardless of whether sample exists in these small areas.

One facet of the adjustment process is that the ‘population denominator’ estimates for each small area will not exactly match between outcome variables. The differences are insignificant and are solely due to the adjustment process.

#### 2.9 Assessment of the modelled estimates

Various measures were taken to examine the modelled estimates. Modelled estimates were compared with direct survey estimates from the NATSIHS for areas that were sampled. For the survey estimates, 95% Confidence Intervals (CIs) were calculated. These were plotted against the modelled estimates to see if the majority of modelled rates fell within the CIs of the NATSIHS estimates.

Relative root mean squared errors (RRMSEs) (described in section 3.4) of the modelled estimates were examined to ensure that the majority were of suitable quality.

The number, range, and applicability of predictor variables included in the models used to create the small area estimates were considered.

Comparisons among the small area estimates and choropleth maps were produced to assess whether the modelled estimates aligned with expectations. Data were confronted with available ABS National level data to assess whether the modelled estimates aligned with expectations.

Please see section 5 for a quality summary for the modelled small area estimates.

#### 3 Accuracy of results

The process undertaken in producing modelled estimates overcomes much of the volatility at the IREG or PHN levels caused by sampling error. However, it should be remembered that the modelled estimates produced are still subject to errors.

The errors associated with the modelled small area estimates fall into three categories, as follows:

• 1. sampling error
2. non-sampling error
3. modelling error

These errors are combined into an overall measure of accuracy, the relative root mean squared error (RRMSE), described in section 3.4.

#### 3.1 Sampling error

Sampling error is introduced into estimates because the NATSIHS data were collected from only a sample of dwellings. Therefore, they are subject to sampling variability; that is, modelled estimates may differ from those that would have been produced if all dwellings had been included in NATSIHS. The smaller the sample obtained within a small area, the greater the sampling error associated with that small area's modelled estimates will be.

#### 3.2 Non-sampling error

The imprecision due to sampling error should not be confused with inaccuracies due to imperfections occurring in the survey process. Such imperfections include mistakes made in reporting by respondents and recording by interviewers, and errors made in coding and processing data. Inaccuracies of this kind are referred to as non-sampling error, and they occur in any enumeration, whether it be a full count (Census) or a sample. Unlike the other sources of error, non-sampling error is not measurable and therefore isn’t accounted for in the measured error (direct or modelled) that accompanies these estimates. Every effort is made to reduce non-sampling error to a minimum through careful design of questionnaires, intensive training and supervision of interviewers, and rigorous procedures; as detailed in the Explanatory Notes.

#### 3.3 Modelling error

Modelling error is introduced by model misspecification. This can occur when the choice of model is incorrect, a key predictor variable is left out or an inappropriate predictor variable is included. Therefore, the selected predictor variables chosen in the models may result in inaccurate modelled estimates for certain small areas, particularly those small areas where there isn’t a strong correlation between the available predictor variables and the health conditions. The models that have been chosen have been tested against a range of possible alternative models; however, they are only the most preferred models subject to available data at the time.

#### 3.4 Relative Root Mean Squared Error (RRMSE) and Margin of Error (MoE)

A measure of the quality of the modelled estimates is the RRMSE. The RRMSE is used as a measure of prediction error informing how well the models predict the outcome variables. In its calculation it also inherits some aspects of modelling and sampling error. The RRMSE generally decreases as the population size increases, and is used to assess the reliability of modelled estimates.

As a general rule of thumb, estimates with RRMSEs less than 25% are considered reliable for most purposes, estimates with RRMSEs between 25% and 50% should be used with caution and estimates with RRMSEs greater than 50% are considered too unreliable for general use.

In the case of estimates of proportions, estimates with 95% MoEs greater than 10 percentage points are considered too unreliable for general use.

Estimates that were altered by more than 10% due to the adjustment process described in section 2.8 should be used with caution, as the RRMSE and 95% MoE are likely to be smaller than the true error for these estimates.

#### 4 Using modelled estimates

The small area modelled estimates can be interpreted as the expected number or proportion of people with a health condition or characteristic for a typical area in Australia with the same characteristics. For some small area locations (IREGs or PHNs), there will be differences between the modelled estimates and the actual number of people with the characteristic of interest. One explanation for this is that significant local information about particular small areas exists but has not been collected for all areas and cannot be incorporated into the models. This sort of information is usually not measurable, and relies on local or expert knowledge.

Small area modelled estimates should be viewed as a tool that when used in conjunction with local area knowledge as well as the consideration of the modelled estimates reliability, can provide useful information that can assist in making decisions for small geographic areas. Care needs to be taken to ensure decisions are not based on inaccurate estimates. The provided modelled small area estimates can be aggregated to larger regions (such as regional planning regions) to help improve decision making. Small area estimates can be aggregated together using an approximation formula outlined in section 6. Aggregation of small areas should be done taking into account local knowledge about these areas.

#### 5 Quality summary for modelled estimates

The quality of the modelled estimates were assessed according to the following criteria:

1. the number, range, and applicability of predictor variables included in the models
2. consistency with national direct survey estimates. For example, whether modelled estimates for circulatory system diseases increased proportionally with age
3. median RRMSE, as a measure of prediction accuracy

These culminated in an overall reliability assessment, which has three categories:

• reliable, meaning the modelled estimates are suitable for general use
• less reliable, meaning the modelled estimates should be used with caution
• unreliable, meaning the modelled estimates are unsuitable for general use. Modelled estimates assessed as unreliable are not published.

#### Reliability assessment table: IREG and PHN estimates

Outcome variableNumber and range of predictor variablesConsistency with National dataMedian RRMSE (all persons estimates - IREG)Median RRMSE (all persons estimates - PHN)Overall Reliability Assessment
Self-assessed health status - Excellent/ Very goodReliableReliable5.5% Reliable5.2% ReliableReliable
Self-assessed health status – GoodLess reliableReliable4.2% Reliable3.8% ReliableLess Reliable
Self-assessed health status - Fair/ PoorReliableReliable9.0% Reliable7.2% ReliableReliable
Smoking status - Current daily smokerReliableReliable6.0% Reliable6.9% ReliableReliable
Smoking status - OtherReliableReliable4.3% Reliable3.4% ReliableReliable
BMI - Underweight/ NormalReliableReliable5.0% Reliable4.9% ReliableReliable
BMI - OverweightReliableReliable3.2% Reliable3.0% ReliableReliable
BMI - ObeseReliableReliable4.4% Reliable3.8% ReliableReliable
BMI - Overweight/ ObeseReliableReliable2.3% Reliable1.9% ReliableReliable
Number of long term conditions - One or twoReliableReliable3.9% Reliable3.6% ReliableReliable
Number of long term conditions - Three or moreReliableReliable6.0% Reliable4.4% ReliableReliable
Number of long term conditions - One or moreReliableReliable3.2% Reliable2.4% ReliableReliable
Number of long term conditions - NoneReliableReliable5.3% Reliable6.4% ReliableReliable
Disability - Has disabilityReliableReliable6.0% Reliable5.1% ReliableReliable
Disability - No disabilityReliableReliable3.4% Reliable3.3% ReliableReliable
Psychological distress - Low/ ModerateReliableReliable3.8% Reliable4.0% ReliableReliable
Psychological distress - High/ Very highReliableReliable8.5% Reliable7.5% ReliableReliable
Alcohol long term risk - ExceededReliableReliable10.9% Reliable9.4% ReliableReliable
Alcohol long term risk - Did not exceedReliableReliable10.3% Reliable8.1% ReliableReliable
Alcohol long term risk - OtherReliableReliable4.1% Reliable4.4% ReliableReliable
Alcohol short term risk - ExceededReliableReliable5.4% Reliable5.1% ReliableReliable
Alcohol short term risk - Did not exceedReliableReliable12.3% Reliable10.0% ReliableReliable
Alcohol short term risk - OtherReliableReliable6.4% Reliable6.8% ReliableReliable
Substances use - Has used substancesReliableReliable7.4% Reliable6.5% ReliableReliable
Substances use - Has not used substancesReliableReliable5.1% Reliable5.0% ReliableReliable
Number of chronic conditions - One or twoReliableReliable4.4% Reliable3.4% ReliableReliable
Number of chronic conditions - Three or moreReliableReliable11.1% Reliable8.0% ReliableReliable
Number of chronic conditions - One or moreReliableReliable4.2% Reliable3.3% ReliableReliable
Number of chronic conditions - NoneReliableReliable2.7% Reliable3.2% ReliableReliable
Endocrine, nutritional and metabolic diseasesReliableReliable6.8% Reliable6.4% ReliableReliable
Circulatory system diseasesReliableReliable6.2% Reliable5.5% ReliableReliable
Respiratory system diseasesReliableReliable7.3% Reliable5.3% ReliableReliable
NeoplasmsUnreliableNot assessedNot assessedNot assessedUnreliable

#### 6 Estimating aggregated areas

The following formulas describe the estimation of aggregated areas. This may be done for one of two reasons:

1. Estimates are required for a bespoke small area of interest
2. Where the error (RRMSE) for an area is unacceptably high, aggregating areas can decrease the error

Note that the error formula is an approximation only, and that these should only be used where alternative modelled estimates are not available. Aggregation of the modelled small area estimates to large geographies such as capital city or state/territory level is not recommended. If you require capital city or state/territory level data for the characteristics of health conditions provided here at small area level, then use of NATSIHS published data (or use of the TableBuilder product) is recommended.

The following formulae are used to estimate the count for an aggregated area.

$$\large{Count_{aggregated \ area} = \sum \limits_{small \ area} \ Count_{small \ area}}$$

$$\large{Proportion_{aggregated \ area} = \frac{Count_{aggregated \ area}}{Population_{aggregated \ area}}}$$

The following formula may be used to approximate the RRMSE for an aggregated area.

$$\large{RRMSE_{aggregated \ area} = \frac {\sqrt{{ \sum_{small \ area}} \left(Count_{small \ area^2}\times RRMSE_{small \ area^2}\right)}}{Count_{aggregated \ area}}}$$

The following formula may then be used to derive an approximate 95% MoE for an aggregated area.

$$\large{\text{95% } MoE_{aggregated \ area} = RRMSE_{aggregated \ area} \times Proportion_{aggregated \ area} \times 1.96}$$

## Technical note - 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 persons 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.

### 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:

$$\large R S E \%=\left(\frac{S E}{e s t i m a t e}\right) \times 100$$

RSEs for published estimates are supplied in Excel data tables, available via the Data downloads section.

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.

### Standard errors of proportions and percentages

A measure of sampling error can be calculated for proportions formed from the ratio of two estimates.

For proportions where the denominator (y) is an estimate of the number of persons in a group and the numerator (x) is the number of persons in a sub-group of the denominator, the formula to approximate the RSE is given below. The formula is only valid when x is a subset of y:

$$\large\operatorname{RSE}\left(\frac{x}{y}\right) \approx \sqrt{[R S E(x)]^{2}-[R S E(y)]^{2}}$$

### Comparison of estimates

Published estimates can be used to calculate the difference between two survey estimates. 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 and y) may be calculated by the following formula:

$$\large S E(x-y) \approx \sqrt{[S E(x)]^{2}+[S E(y)]^{2}}$$

While the above formula will only be exact for differences between unrelated characteristics of sub-populations, it is expected that it will provide a reasonable approximation for other data comparisons.

### Margins of error

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. 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:

$$\large\operatorname{MOE}(y) \approx \frac{R S E(y) \times y}{100} \times 1.96$$

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:

$$\large\frac{1.645}{1.96}$$

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

$$\large\frac{2.576}{1.96}$$

### 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. The confidence interval can easily be constructed from the MOE by taking the estimate plus or minus the MOE of the estimate.

### 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:

$$\Large\frac{|x-y|}{S E(x-y)}$$

where

$$\large S E(y) \approx \frac{R S E(y) \times y}{100}$$

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.

## Glossary

### See all

The definitions used in this survey may not be identical to those used for the same or similar items in other surveys. For more information about these differences, refer to the Explanatory notes section and appendices.

#### Aboriginal person

A person who identified themselves, or was identified by another household member, as being of Aboriginal origin, or both Aboriginal and Torres Strait Islander origin.

#### Aboriginal and Torres Strait Islander household

A household where at least one resident has been identified as being of Aboriginal and/or Torres Strait Islander origin.

#### Aboriginal and Torres Strait Islander people

People who identified themselves, or were identified by another household member, as being of Aboriginal origin, Torres Strait Islander origin, or both Aboriginal and Torres Strait Islander origin.

A person aged 18 years or over.

#### Age standardisation

A technique used to remove age as a factor when comparing characteristics that are age-related (for example, long-term health conditions) between two or more populations with different age structures. See Explanatory notes section.

#### Alcohol consumption risk level

A risk level assessed using the 2009 National Health and Medical Research Council (NHMRC) guidelines for the consumption of alcohol. See Appendix - assessing health risk factors.

#### Arthritis

A long-term health condition involving inflammation of the joints often resulting in pain, stiffness, disability and deformity.

#### Asthma

A long-term health condition marked by episodes of wheezing, chest tightness and shortness of breath associated with widespread narrowing of the airways within the lungs and obstruction of airflow.

#### Australian Standard Classification of Education (ASCED)

A classification, covering all sectors of the education system (schools, vocational education and training, and higher education), comprising two component classifications — Level of Education and Field of Education. See Australian Standard Classification of Education (ASCED), 2001 (cat. no. 1272.0).

#### Australian Statistical Geography Standard (ASGS)

A framework of statistical areas used by the Australian Bureau of Statistics and other organisations to enable the publication of statistics that are comparable and spatially integrated. See Australian Statistical Geography Standard (ASGS).

#### Back problems (dorsopathies)

A group of long-term health conditions of the back or spine including sciatica (nerve pain), disc disorders, back pain/problems not elsewhere classified, and curvature of the spine.

#### Blood pressure

A measurement of the pressure of the blood in the arteries, expressed in the form of, for example, 120/80 mmHg (millimetres of mercury). The higher number is the systolic blood pressure, which measures the pressure in the arteries as the heart pumps blood during each beat. The lower number is the diastolic blood pressure which measures the pressure in the arteries as the heart relaxes before the next beat. See also High blood pressure (measured), Hypertension (high blood pressure), Appendix - physical measurements and Appendix - assessing health risk factors.

#### Body Mass Index (BMI)

An index of weight-for-height, calculated using the formula weight (in kilograms) divided by the square of height (in metres), used to classify people as underweight, normal weight, overweight or obese. See Appendix - assessing health risk factors.

#### Breastfeeding

Refers to children aged 0–3 years (that is, children up to 3 years and 11 months of age) receiving breast milk (including expressed milk) from the mother, a wet nurse or a breast milk donor. Exclusive breastfeeding refers to children receiving only breastmilk and no other fluids, food or water, with the exception of vitamins, minerals and medicines where necessary. See Appendix - assessing health risk factors.

#### Canadian National Occupancy Standard for Housing Appropriateness

A widely used measure of housing utilisation that is sensitive to both household size and composition. See Canadian National Occupancy Standard for information about the criteria used to assess bedroom requirements and households requiring at least one additional bedroom.

#### Cancer (malignant neoplasms)

A long-term health condition in which the body’s cells grow and spread in an uncontrolled manner. A cancerous cell can arise from almost any cell so cancer can be found almost anywhere in the body.

#### CDP (Community Development Programme)

A Government initiative assisting job seekers in remote areas to gain the skills, training and capabilities needed to find sustainable employment and contribute to their communities through a range of flexible activities. CDP participants were classified as:

• employed if they also had a non-CDP job, or
• unemployed or not in the labour force, depending on their job search activities.

#### Cerebrovascular disease

A group of long-term health conditions in which the blood flow in the brain is temporarily or permanently affected by blood vessel narrowing or rupture, clot formation or blockage, including stroke.

#### Child

A person aged 0–17 years.

#### Chronic bronchitis

A long-term health condition characterised by inflammation of the lining of the airways (bronchial tubes) causing mucus production, coughing and difficulty breathing.

#### Chronic condition

A long-term health condition selected for reporting in this survey because it is common, poses significant health problems, has been the focus of population health surveillance efforts, and action can be taken to prevent its occurrence. Includes:

• arthritis
• asthma
• back problems (dorsopathies)
• cancer (malignant neoplasms)
• chronic obstructive pulmonary disease (COPD)
• diabetes (diabetes mellitus)
• heart, stroke and vascular disease (heart disease)
• kidney disease
• mental and behavioural conditions
• osteoporosis.

#### Chronic obstructive pulmonary disease (COPD)

A group of long-term health conditions which cause narrowing of the airways (bronchial tubes) in the lungs, making it difficult to breathe. Includes:

• emphysema
• chronic bronchitis
• severe asthma (where it is difficult to treat and manage the symptoms).

#### Comorbidity

A term used in this survey to describe the occurrence of two or more long-term health conditions.

#### Core activity limitation

A person has a core activity limitation if they need help, have difficulty, or use aids or equipment with mobility, self-care and/or communication. A core activity limitation is classified as profound, severe, moderate or mild based on their highest level of limitation in any of those activities. See also Disability status.

#### Current daily smoker

A person who reported at the time of interview that they regularly smoked one or more cigarettes, pipes, cigars or other tobacco products per day. See Appendix - assessing health risk factors.

#### Current smoker — less than daily

A person who reported at the time of interview that they smoked cigarettes, pipes, cigars or other tobacco products less frequently than daily. See Appendix - assessing health risk factors.

#### Deafness

Partial or total loss of hearing.

#### Dependent children

Children aged less than 15 years and full-time secondary or tertiary students aged 15–24 years for whom there is no identified partner or child of their own usually resident in the same household.

#### Diabetes (diabetes mellitus)

A long-term health condition in which blood glucose levels become too high due to the body producing little or no insulin, or not responding to insulin properly. Excludes gestational diabetes.

#### Diet drinks

Includes soft drinks (including those in ready to drink alcoholic beverages), cordials, sports drinks or energy drinks that have been sweetened with artificial sweeteners rather than sugar. Excludes hot tea/coffee sweetened with sugar replacements like ‘Equal’.

#### Diet

Refers to fruit and vegetable consumption and/or sugar sweetened and diet drink consumption.

#### Disability

A person has a disability if they have an impairment which restricts their everyday activities and has lasted, or is expected to last, for at least six months. A person with a disability is classified by whether they have:

• a specific limitation with any core activities (mobility, communication and self-care)
• a specific restriction when participating in schooling or employment activities, or
• no specific limitation with core activities or restriction with schooling or employment activities.

See Disability in Explanatory notes.

#### Discrete Indigenous community

A geographical location that:

• is bounded by physical or legal boundaries
• has 50 or more Aboriginal and Torres Strait Islander people usually resident
• is inhabited, or intended to be inhabited, predominantly by Aboriginal and Torres Strait Islander people (more than 50% of usual residents)
• has housing or infrastructure (power, water, sewerage) that is managed on a community basis
• usually has services such as schools, health clinics, shops and council depots.

#### Ear or hearing problems

A group of long-term health conditions affecting the ear or hearing which include:

• complete deafness, partial deafness and hearing loss not elsewhere classified (in one or both ears)
• diseases of the middle ear and mastoid processes
• diseases of the inner ear
• other diseases of the ear.

#### E-cigarette/vape smoker

Refers to a person who uses and/or has ever used an electronic cigarette, a battery operated device that resembles tobacco cigarettes, pipes or cigars to inhale nicotine and/or other chemicals in a vapour form rather than smoke. These devices are designed to simulate the act of smoking tobacco cigarettes but do not involve the burning of tobacco. A range of names are used to describe them, including e-cigs, electronic nicotine delivery systems (ENDS), e-shisha, e-cigars, e-pipes, e-hookas, hookah-pens, and vape-pipes. See Appendix - assessing health risk factors.

#### Emphysema

A long-term health condition marked by shortness of breath due to damaged air sacs in the lungs.

#### Employed

Persons aged 15 years and over who had a job or business, or who undertook work without pay in a family business for a minimum of one hour per week. Includes persons who were absent from a job or business.

#### Employed full-time

Employed persons who usually work 35 hours or more per week (in all jobs).

#### Employed part-time

Employed persons who usually worked less than 35 hours per week (in all jobs).

#### Exercise

See Physical activity.

#### Exercise for fitness, recreation or sport

Refers to walking for fitness, recreation or sport. See also Physical activity.

#### Ex-smoker

A person who reported at the time of interview that they did not currently smoke but had either:

• regularly smoked daily
• smoked at least 100 cigarettes in their lifetime, or
• smoked pipes, cigars or other tobacco products at least 20 times in their lifetime.

See Appendix - assessing health risk factors.

#### Eye or sight problems

A group of long-term health conditions affecting the eye or sight which include:

• cataract
• glaucoma
• disorders of the choroid (the vascular layer of the eye) and retina
• disorders of the ocular muscles, binocular movement, accommodation and refraction
• visual disturbances and blindness
• other diseases of the eye and adnexa (structures involved in protecting and/or supporting the function of the eye, such as the eye socket, eyelids and tear system).

#### Family

Refers to two or more persons, one of whom is at least 15 years of age, who are related by blood, marriage (registered or de facto), adoption, step or fostering, and who are usually resident in the same household. A family is identified by the presence of a couple relationship, lone parent-child relationship or other blood relationship, which means some households contain more than one family.

#### Family composition

Refers to type of family:

• couple family with no children
• couple family with children
• one parent family
• other family.

#### Family composition of household

A classification of households, based families within the household:

• one family households
• multiple family households
• non-family households (lone person and group households).

#### Fruit or vegetable consumption

Refers to a usual daily intake of fruit or vegetables. Adequate consumption of fruit or vegetables means the usual daily intake meets or exceeds the number of serves recommended for a person’s age and sex in the National Health and Medical Research Council (NHMRC) 2013 Australian Dietary Guidelines. See Appendix - assessing health risk factors.

#### Health action

An action taken by a person in the two weeks prior to interview or, for admission to hospital, in the 12 months prior to interview, related to their health, including:

• visit to outpatient clinic or casualty/emergency or day clinic
• consultation with general practitioner (GP) and/or specialist
• consultation with dental professional
• consultation with other health professionals (OHP) (see also Other health professional).

#### Health risk factors

Selected behaviours, events and circumstances that impact on health, comprising:

• alcohol consumption
• blood pressure (measured)
• body mass (e.g. overweight or obese)
• breastfeeding
• consumption of sugar sweetened and diet drinks
• fruit and vegetable intake
• immunisation
• physical activity
• physical harm or threatened physical harm
• removal from natural family
• smoking
• substance use
• unfair treatment
• waist circumference.

#### Hearing impairment (measured)

Partial or complete loss of hearing in one or both ears based on results of voluntary, self-administered hearing test undertaken by respondents without a cochlear implant at the time of interview. For people with a hearing impairment in both ears, the level of hearing impairment is classified as mild, moderate, or severe or profound based on the ear with the lowest level of impairment. See Hearing data (appendix).

#### Hearing impairment (reported)

A long-term health condition marked by partial or complete loss of hearing in one or both ears. See also Ear or hearing problems.

#### Heart, stroke and vascular disease (heart disease)

A group of long-term health conditions which includes:

• ischaemic heart disease (including heart attack and angina)
• cerebrovascular disease (including stroke)
• heart failure
• oedema (fluid retention)
• diseases of arteries, arterioles and capillaries.

#### High blood pressure (measured)

A measured blood pressure reading of 140/90 mmHg (millimetres of mercury) or higher, voluntarily taken at the time of interview and so does not necessarily indicate a long-term condition. In this survey, measured high blood pressure is distinguished from hypertension which is self-reported as a long-term health condition. See also Hypertension (high blood pressure), Appendix - physical measurements and Appendix - assessing health risk factors.

#### High sugar levels

High sugar levels in blood or urine. See also Diabetes (diabetes mellitus).

An area of land with which Aboriginal and Torres Strait Islander people have ancestral and/or cultural links.

#### Household

One or more persons, at least one of whom is aged 18 years or over, usually resident in the same private dwelling.

#### Household income

The sum of the personal cash incomes of all household members aged 15 years and over, presented in dollars and deciles and in reported and equivalised form. See Explanatory notes section.

#### Household spokesperson

A person aged 18 years or over who is nominated as the best person to provide information about the household as a whole, such as household income and tenure arrangements. The person does not need to be selected for the survey or be of Aboriginal and/or Torres Strait Islander origin to act as household spokesperson.

#### Hypertension (high blood pressure)

A long-term health condition in which the blood pressure in the arteries is elevated, requiring the heart to work harder than normal to circulate blood through the blood vessels. In this survey, hypertension is distinguished from high blood pressure (measured), which is a blood pressure reading taken at the time of interview and does not necessarily indicate a long-term health condition. See also Blood pressure.

#### ICD–10

Refers to a classification developed by the ABS for use in ABS health surveys based on the 10th revision of the International Classification of Diseases and Health Related Problems. See also Type of condition.

#### Immunisation

Refers to influenza and pneumococcus vaccinations only. According to the Australian Government Department of Health’s Australian Immunisation Handbook:

• annual influenza vaccination is recommended for all persons aged 15 years and over
• the number of recommended pneumococcal vaccines depends on age, Indigenous status and the presence of a condition(s) associated with an increased risk of invasive pneumococcal disease.

#### Impairment

A person has an impairment if they have a loss or abnormality in body structure or physiological function, including mental functions. Abnormality refers to a significant variation from established statistical norms. Examples of impairment are loss of sight, loss of a limb, disfigurement or deformity, impairment of mood or emotion, impairment of speech, hallucinations, loss of consciousness, and any other lack of function of body organs. See Disability in Explanatory notes.

#### Indigenous Regions (IREGs)

The highest level of the Indigenous Structure of the 2016 Australian Statistical Geography Standard (ASGS). See Australian Statistical Geography Standard (ASGS): Volume 2 - Indigenous Structure, July 2016 (cat. no. 1270.0.55.002).

#### Indigenous status

Refers to whether the person is of Aboriginal and/or Torres Strait Islander origin, as identified by the household spokesperson so not necessarily self-identified. Status is classified as:

• Aboriginal
• Torres Strait Islander
• both Aboriginal and Torres Strait Islander
• neither Aboriginal nor Torres Strait Islander.

#### Ischaemic heart disease

A long-term health condition, also called coronary artery disease, involving the build-up of plaque (fatty material) in the heart’s arteries, causing them to narrow, reducing blood flow and oxygen to the heart (ischaemia). It includes angina (chest pain and discomfort) and heart attack.

#### Kessler 5 (K5) score

See Psychological distress and Appendix - mental health and wellbeing.

#### Kidney disease

A long-term health condition, also called renal disease, in which a person’s kidney function is reduced or damaged, affecting its ability to filter blood.

#### Labour force participation rate

For any group, the labour force (employed persons plus unemployed persons) expressed as a percentage of the civilian population aged 15 years and over in the same group.

#### Labour force status

Identifies whether a person is employed, unemployed or not in the labour force.

Refers to the lifetime risk guideline from the National Health and Medical Research Council (NHMRC) guidelines 2009 Australian Guidelines to Reduce Health Risks from Drinking Alcohol. A person is considered to have exceeded the guideline if they consumed more than two standard drinks per day on average in the last week. See Appendix - assessing health risk factors.

#### Limitation

A person has a limitation if they have difficulty, need assistance from another person, or use an aid or equipment, to do a particular core activity (mobility, communication and self-care). The level of the limitation with core activities is classified as profound, severe, moderate or mild, based on the level of support required. See Disability in Explanatory notes.

#### Long sighted (hyperopia)

A condition of the eye where the light that comes into the eye does not directly focus on the retina but behind it, causing the image of a close object to be out of focus, but that of a distant object to be in focus.

#### Long-term health condition

An illness, injury or disability which has lasted at least six months, or which the person expects to last for six months or more.

• Asthma is classified as current if the person reported at the time of interview they were having symptoms or treatment. To be current, symptoms of asthma or treatment for asthma must have occurred in the last 12 months.
• Asthma, arthritis, cancer, osteoporosis, diabetes (excluding gestational diabetes), sight and hearing problems are assumed to be long-term.
• Heart attack, angina, heart failure and stroke are assumed to be both current and long-term.

#### Measured blood pressure

See High blood pressure (measured) and Appendix - Physical measurements.

#### Median

For any distribution, the median value is that which divides the relevant population into two equal parts, with half falling below and half exceeding that value. For example, the median height is the height at which half the population is taller and half is shorter.

#### Mental and behavioural conditions (mental health conditions)

A group of long-term health conditions that affect mood, thinking and behaviour which includes:

• organic mental problems
• alcohol and drug problems
• mood (affective) disorders such as depression
• anxiety-related problems, and
• other mental and behavioural problems.

#### Mesh block

The smallest geographical unit in the Australian Statistical Geography Standard (ASGS). Mesh Blocks form the basis for the larger regions of the ASGS such as Remoteness Areas.

#### Metric cup

A measure of volume, commonly associated with cooking and serving sizes, equal to 250 millilitres.

#### Moderate intensity exercise

Physical activity that causes a moderate increase in the person’s heart rate or breathing, such as gentle swimming, social dancing, and weight lifting. Excludes:

• walking for transport
• walking for fitness, recreation or sport
• household chores, gardening or yard work, and
• any activity done as part of person’s job.

See Appendix - assessing health risk factors.

#### Multidimensional Scale of Perceived Social Support (MSPSS) score

A measure of how a person perceives their level of social support from family and friends, derived from a modified version of the Multidimensional Scale of Perceived Social Support, which uses six questions instead of 12. The scale is used to derive a family score, a friends score and a total score which indicate whether a person perceives the level of social support from each as low, moderate or high. See Appendix - mental health and wellbeing.

#### Neoplasms

A new growth of abnormal tissue (a tumour) that is either benign (non-cancerous) or malignant (cancerous).

#### Never smoked

A person who at the time of interview reported they had:

• never regularly smoked daily,
• smoked less than 100 cigarettes in their lifetime, and
• smoked pipes, cigars or other tobacco products less than 20 times in their lifetime.

See Appendix - assessing health risk factors.

#### Non-remote areas

Refers to the Major Cities, Inner Regional and Outer Regional Remoteness Areas combined. This grouping is generally used for comparing non-remote areas with remote areas.

#### Non-school qualification

A qualification awarded for educational attainments other than those of pre-primary, primary or secondary education. Includes qualifications at the following levels:

• Master Degree
• Bachelor Degree
• Advanced Diploma and Diploma, and
• Certificates I, II, III and IV.

#### Not in the labour force

Persons who are not employed or unemployed as defined, including persons who:

• are retired
• no longer work
• do not intend to work in the future
• are permanently unable to work, or
• have never worked and never intend to work.

#### Nutrition

See Diet.

#### Osteoporosis

A long-term health condition which thins and weakens bone mineral density, generally caused by loss of calcium, and which leads to increased risk of fracture.

#### Other health professional

Health professionals other than dentist, general practitioner (GP) or specialist. Includes:

• Aboriginal health worker
• accredited counsellor
• acupuncturist
• alcohol and drug worker
• audiologist/audiometrist
• chiropodist/podiatrist
• chiropractor
• dietitian/nutritionist
• herbalist
• hypnotherapist
• naturopath
• nurse
• occupational therapist
• optician/optometrist
• osteopath
• physiotherapist/hydrotherapist
• psychologist
• social worker/welfare officer
• speech therapist/pathologist

#### Otitis media

A middle ear infection.

#### Pearlin Mastery Scale score

A score, derived from a set of seven questions, which measures the extent to which a person feels control over life outcomes. See Appendix - mental health and wellbeing.

#### Physical activity — non-remote areas

Refers to any or all of the following activities:

• walking for transport (walking that was continuous for at least 10 minutes for the purpose of getting to and from places)
• walking for fitness, recreation or sport (walking that was continuous for at least 10 minutes for fitness, recreation or sport)
• moderate intensity exercise
• vigorous intensity exercise
• strength or toning activities
• workplace activity (physical activity undertaken in the workplace on a typical day, categorised as mostly sitting, mostly standing, mostly walking, or mostly heavy labour or physically demanding work).

See Appendix - assessing health risk factors.

#### Physical activity — remote areas

Refers to any or all of the following activities:

• playing football/soccer
• playing softball/cricket
• swimming
• running
• hunting/gathering bush foods/fishing
• dancing (including ceremonial dancing)
• housework/gardening/heavy yardwork
• walking to places
• other.

#### Physical activity guidelines

Refers to the ABS’ interpretation of the physical activity (excluding workplace activity) component of the following Department of Health guidelines:

See Appendix - assessing health risk factors.

#### Physical harm

Refers to any incident where a person was physically hurt or harmed by someone on purpose, including physical fights. Other forms of abuse (e.g. sexual, emotional, psychological) are excluded. See Appendix - physical and threatened physical harm data.

#### Prevalence

Refers to the number of cases of a particular characteristic (e.g. a specific long-term condition such as cancer) that are present in a population at one point in time. It differs from incidence, which refers to the number of new cases of a particular characteristic that occur within a certain period (e.g. number of new cases of cancer in a calendar year).

#### Private dwelling

Refers to a house, flat, unit or any other structure used as a private place of residence at the time of survey.

#### Profound or severe disability

Refers to a person with a profound or severe limitation when performing selected tasks related to communication, mobility or self-care. See Disability status and Explanatory notes section.

#### Proxy

A person who answers the survey questions on behalf of the person selected for the interview when the person selected is:

• incapable of answering for themselves (e.g. due to illness/injury or cultural considerations)
• a child aged 14 years or under
• a child aged 15–17 years when parental consent is not given to interview them personally.

#### Psychological distress

A measure of non-specific psychological distress experienced recently, derived from a modified version of the Kessler Psychological Distress Scale (K10) called the Kessler 5 (K5). See Appendix - mental health and wellbeing.

#### Rate ratio

A ratio calculated by dividing the age standardised proportion of Aboriginal and Torres Strait Islander people with a particular characteristic by the age standardised proportion of non-Indigenous people with the same characteristic. See Explanatory notes section.

#### Remote areas

Refers to the Remote and Very Remote Remoteness Areas combined. This grouping is generally used for comparing non-remote areas with remote areas.

#### Removal from natural family

Refers to a person and/or any of their relatives who have ever been taken away from their natural family as a child by the government, or been taken away to a mission.

#### Remoteness areas

A measure of relative access to services which is used to divide Australia into five classes of remoteness:

• Major Cities
• Inner Regional
• Outer Regional
• Remote, and
• Very Remote.

See Australian Standard Geography Standard (ASGS): Volume 5 — Remoteness Structure, July 2016 (cat. no. 1270.0.55.005).

#### Restriction (schooling or employment)

A person has an education or employment restriction if they have difficulty participating, need assistance from another person or use an aid or equipment in schooling or employment. See Disability in Explanatory notes.

#### Selected chronic condition

See Chronic condition.

#### Self-assessed health status

A person's general assessment of their health as excellent, very good, good, fair or poor.

#### Short sighted (myopia)

A condition of the eye where the light that comes into the eye does not directly focus on the retina but in front of it, causing the image of a distant object to be out of focus, but that of a close object to be in focus.

#### Single occasion risk (alcohol consumption)

Refers to the single occasion risk guideline from the National Health and Medical Research Council (NHMRC) 2009 Australian Guidelines to Reduce Health Risks from Drinking Alcohol. A person is considered to have exceeded the guideline if they consumed more than four standard drinks on at least one day in the last 12 months. See Appendix - assessing health risk factors.

#### Smoker status

Refers to the extent to which a person was regularly smoking tobacco products at the time of interview. See Appendix - assessing health risk factors.

#### Socio-Economic Indexes for Areas (SEIFA)

Refers to four Indexes compiled by the ABS following the 2016 Census of Population and Housing, summarising different aspects of the socio-economic condition of areas. The Index of Relative Socio-economic Disadvantage is the one most frequently used in health analysis. See Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia (cat. no. 2033.0.55.001).

#### Standard drink

A drink of alcohol containing 12.5 millilitres (mLs) of alcohol.

#### Strength or toning activities

Activities designed to increase muscle strength or tone, such as lifting weights, resistance training, pull ups, push ups, or sit ups. See Appendix - assessing health risk factors.

#### Stroke

A long-term health condition that occurs when the blood supply to the brain is restricted by a blockage or bleeding, causing damage to the affected tissue which may cause paralysis, speech impairment, loss of memory and reasoning ability, coma or death.

#### Substance use

The use of substances for non-medical purposes by a person in the 12 months prior to interview including:

• pain killers or analgesics
• tranquillisers or sleeping pills
• amphetamines, ice or speed
• marijuana, hashish or cannabis resin
• heroin
• cocaine
• hallucinogens (LSD/synthetic/naturally occurring)
• ecstasy or other designer drugs
• petrol
• other inhalants
• kava
• other substances.

#### Sugar drinks/sugar sweetened drinks

Includes soft drinks (including those in ready to drink alcoholic beverages), cordials, sports drinks or energy drinks that have been sweetened with sugar. Excludes fruit juice, flavoured milk, ‘sugar free’ drinks, and hot tea/coffee. See also Diet drinks.

#### Threatened physical harm

Refers to threats of physical harm that occurred either face-to-face or non-face-to-face (e.g. via instant message/social networking sites, text message, phone, email, writing). See Appendix - physical and threatened physical harm data.

#### Torres Strait Islander person

A person who identified themselves, or was identified by another household member, as being of Torres Strait Islander origin, or both Torres Strait Islander and Aboriginal origin.

#### Type of condition

Refers to the type of long-term health condition, which uses a classification developed by the ABS for use in ABS health surveys based on the 10th revision of the International Classification of Diseases and Health Related Problems (ICD10).

#### Unemployed

Persons aged 15 years and over who were not employed and actively looking for work in the four weeks prior to the survey, and were available to start work in the week prior to the survey.

#### Unemployment rate

For any group, the number of unemployed people expressed as a percentage of the labour force in the same group.

#### Unfair treatment

Refers to when a person reported they had been treated unfairly because they are of Aboriginal or Torres Strait Islander origin.

#### Use of health services

See Health action.

#### Vigorous intensity exercise

Physical activity that causes a large increase in the person’s heart rate or breathing, such as jogging, cycling, aerobics, or competitive sport. Excludes:

• walking for transport
• walking for fitness, recreation or sport
• household chores, gardening or yard work, and
• any activity done as part of a person’s job.

See Appendix - assessing health risk factors.

#### Waist circumference

A measurement, in centimetres, of a person’s waist. It is based on the midway point between the bottom of a person’s ribs and the top of their hip bone, and used to classify people as at increased risk of developing chronic conditions or not at risk. See Appendix - assessing health risk factors.

## Quality declaration - summary

### Institutional environment

For information on the institutional environment of the Australian Bureau of Statistics (ABS), including the legislative obligations of the ABS, financing and governance arrangements, and mechanisms for scrutiny of ABS operations, please see ABS Institutional Environment.

### Relevance

Information from the 2018–19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) contributes to existing data on Aboriginal and Torres Strait Islander people and the formulation of government policies and legislation.

The 2018–19 NATSIHS collected information on a range of topics including:

• long term health conditions
• health actions and health service use
• nutrition
• physical activity
• physical measurements including a hearing test
• risk factors such as alcohol consumption, discrimination, smoking and substance use
• experiences of harm
• medications
• social and emotional wellbeing
• cultural identification
• language
• general demographic information
• personal and household characteristics
• education and employment
• income.

### Timeliness

The NATSIHS was conducted from 1 July 2018 to 13 April 2019.

A summary of findings, including a broad set of tables in spreadsheet format was available on the ABS website on 11 December 2019.

For individuals who wish to undertake more detailed analysis of the NATSIHS data, detailed microdata was released via the DataLab on 11 December 2019. A TableBuilder product will be released, subject to the approval of the Australian Statistician.

### Accuracy

The 2018–19 NATSIHS sample was designed to produce reliable estimates by remoteness areas, and at the national level and state/territory levels.

The sample for the non-community component was selected at random using a multi-stage area sample of addresses from the ABS's Address Register. The sample for the community component was selected from the ABS's Dwelling Register for Aboriginal and Torres Strait Islander Communities. After sample loss and non-response, the final sample achieved included approximately 6,400 private dwellings and 10,600 persons.

Estimates in this publication are subject to both sampling and non-sampling errors. Sampling error is the error associated with taking a sample of dwellings rather than going to all dwellings in Australia. In this publication the sampling error is measured by the relative standard error (RSE), which is the standard error expressed as a percentage of the estimate, and the margin of error (MoE), which describes the distance from the population value that the sample estimate is likely to be within for a given level of confidence. Non-sampling errors can occur in any data collection, whether based on a sample or a full count such as a census. Sources of non-sampling error include:

• non-response
• errors in reporting by respondents or recording answers by interviewers
• errors in coding or processing of data.

Every effort was made to reduce the non-sampling error by careful design and testing of questions, training interviewers, follow-up of respondents and extensive editing and quality control procedures at all stages of data processing.

Estimates, RSEs and MoEs in this publication have been assessed to ensure the confidentiality of individuals and dwellings contributing to the survey. Estimates in this publication have been randomly adjusted using the statistical process of perturbation to ensure confidentiality of respondents. In most cases, perturbation will have only a small impact on the estimate, while ensuring the information value of the published data as a whole is not impaired.

### Coherence

This is the fourth health survey of Aboriginal and Torres Strait Islander people conducted by the ABS. The previous surveys were conducted in 2012-13 (as part of the Australian Health Survey), 2004–05 and 2001.

Information about the comparability of each data item to the previous release in 2012–13, as well as to the 2017–18 National Health Survey, can be found in the Data Item List via the Data downloads section.

### Interpretability

This publication contains tables and a summary of findings to assist with the interpretation of the results of the survey. Detailed Methodology, a Technical Note on Reliability of Estimates and a Glossary are also included, providing information on the terminology, classifications and other technical aspects associated with these statistics.

### Accessibility

Estimates and associated RSEs and MoEs for proportions are available in Excel spreadsheets, which can be accessed from the Data downloads section.

Detailed microdata was released on the ABS website on 11 December 2019. It is expected that a TableBuilder will be produced from the NATSIHS, subject to the approval of the Australian Statistician. For further details, refer to the Microdata Entry Page on the ABS website.

Special tabulations of NATSIHS data are available on request for a fee. Tabulations can be produced from the survey subject to confidentiality and sampling variability constraints.