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Australian Health Survey: Biomedical Results for Chronic Diseases methodology

Reference period
2011 - 2012
Released
5/08/2013
Next release Unknown
First release

Explanatory notes

Introduction

1 This publication is the first release of information from the 2011–12 National Health Measures Survey (NHMS), which forms part of the 2011–13 Australian Health Survey (AHS).

2 For more information on the structure of the AHS, see Structure of the Australian Health Survey. The following information focusses on the NHMS component of the survey only.

3 All people aged 5 years and over who participated in either the National Health Survey (NHS) or the National Nutrition and Physical Activity Survey (NNPAS) were invited to participate in the voluntary NHMS. The NHMS took place throughout Australia from March 2011 to September 2012. Participants voluntarily provided blood and urine samples, which were then analysed for specific biomarkers.

4 The 2011–12 NHMS collected information about:

  • chronic disease biomarkers, including tests for diabetes, cholesterol, triglycerides, kidney disease and liver function; and
  • nutrition biomarkers, including tests for iron, folate, iodine and vitamin D levels.
     

See Appendix A for the full list of tests conducted.

5 In addition, the broader survey collected a wide range of information about health conditions, risk factors (for example, obesity), health service usage, medications and demographic and socioeconomic factors, which can be analysed in relation to the NHMS results.

6 The statistics presented in this publication focus on biomarkers of chronic disease, including cardiovascular disease, diabetes and kidney disease. Information on nutrition biomarkers will be released in late 2013. Further publications from the Australian Health Survey are outlined in the Release Schedule, while the list of data items available from the survey will be available in the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

Scope of the survey

7 The NHS and NNPAS included a combined sample of approximately 25,000 private dwellings across Australia. Urban and rural areas in all states and territories were included, while Very Remote areas of Australia and discrete Aboriginal and Torres Strait Islander communities (and the remainder of the Collection Districts in which these communities were located) were excluded. These exclusions are unlikely to affect national estimates, and will only have a minor effect on aggregate estimates produced for individual states and territories, except the Northern Territory where the population living in Very Remote areas accounts for around 23% of persons.

8 The 2011–13 AHS also included an additional representative sample of around 13,000 Aboriginal and Torres Strait Islander people, which was collected between April 2012 and July 2013. This is a separate collection of Aboriginal and Torres Strait Islander people living in remote and non-remote areas, including discrete Aboriginal and Torres Strait Islander communities. This survey also included a biomedical component. Results from this separate survey will be released progressively from November 2013.

9 Non-private dwellings such as hotels, motels, hospitals, nursing homes and short-stay caravan parks were excluded from the NHS and NNPAS. This may affect estimates of the number of people with some chronic conditions; for example, conditions which may require periods of hospitalisation, such as kidney disease.

10 Within selected dwellings of the NHS and NNPAS, a random sub-sample of residents was selected as follows:

  • one adult (aged 18 years and over); and where applicable
  • one child aged 0–17 years (NHS) or
  • one child aged 2–17 years (NNPAS).
     

11 The following groups were also excluded from the NHS and NNPAS:

  • certain diplomatic personnel of overseas governments, customarily excluded from the Census and estimated resident population;
  • persons whose usual place of residence was outside Australia;
  • members of non-Australian Defence forces (and their dependents) stationed in Australia; and
  • visitors to private dwellings.
     

12 All selected persons aged 5 years and over were then invited to participate in the voluntary NHMS. Children aged 5–11 years were asked to provide a urine sample only, whereas people aged 12 years and over were asked to provide both a blood and urine sample.

Data collection

13 The interview components of the NHS and NNPAS were conducted under the Census and Statistics Act (CSA) 1905. Ethics approval for the NHMS component was sought and gained from the Australian Government Department of Health and Ageing’s Departmental Ethics Committee.

14 At the completion of NHS or NNPAS questions, interviewers explained the voluntary NHMS component and provided a written information sheet.

15 Informed consent was sought from adults and from parents/legal guardians of children through completion of a consent form. A copy of the consent form was left with the respondent. Those that agreed to take part were provided a referral form to complete (including whether specific medications or supplements were regularly taken) to provide to the collection clinic.

16 A follow-up reminder process was used for respondents who consented to the NHMS but had not yet attended a collection clinic. This process took the form of phone calls or letters arranged ten days apart from the interview date. Also, home visits and temporary clinics were offered to participants in certain circumstances to maximise participation rates, particularly in remote areas and for those who were incapacitated. To reduce expenses for travel, child-care or time off work, participants were able to claim a reimbursement of $50 paid into an Australian bank account.

17 Most blood and urine samples were collected at Sonic Healthcare collection clinics or via a home visit using standard operating procedures for phlebotomy collection.

18 In order to get an accurate reading for the fasting plasma glucose, LDL cholesterol and triglyceride tests, participants providing blood samples were asked to fast for 8 hours before their test. The results presented in this publication for these tests refer only to those people who did fast (approximately 79% of adults who participated in the NHMS).

19 All blood and urine samples were then analysed at a central laboratory at Douglass Hanly Moir (DHM) Pathology in Sydney, Australia on machines accredited by the National Association of Testing Authorities (NATA). DHM conducted Internal Quality Control (QC) analysis for all instruments used to conduct analysis on the samples. More information on NHMS quality assurance methods and procedures will be available in the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

20 All participants were provided with a pathology report of their results via post. Participants could also nominate for their results to be sent to their regular doctor. In cases where the results were outside the normal range, participants were contacted by a qualified health professional and encouraged to discuss their results with their doctor. If the test results showed a significantly high or low result which was dangerous to the person's health, they were contacted immediately and advised on the best course of action.

Response rates

21 In the NHS and NNPAS combined, there were a total of 25,080 households fully responding, giving a response rate of 81.6%. With the selection of one adult and one child aged 2–17 years where applicable, this resulted in a total of 31,837 persons in sample (or 30,329 aged 5 years and over and 27,636 aged 12 years and over).

NHS/NNPAS response rates, 2011-12

Households approached (after sample loss)no.
30 721
Households in sampleno.
25 080
 Household response rate%
81.6
Persons in sample  
 2 years and overno.
31 837
 5 years and overno.
30 329
 12 years and overno.
27 636
 

22 The following table presents response rates for the NHMS.

NHMS response rates, 2011-12

    Number of persons no.Proportion of persons %
5 YEARS AND OVER
Persons in sample (NHS/NNPAS)
30 329
100.0
 Participated in NHMS
11 248
37.1
  Urine sample provided
10 536
34.7
 Did not participate in NHMS
19 081
62.9
12 YEARS AND OVER
Persons in sample (NHS/NNPAS)
27 636
100.0
 Participated in NHMS
10 403
37.6
  Blood sample provided  
   Fasting sample
8 168
29.6
   Non-fasting sample
2 024
7.3
 Did not participate in NHMS
17 233
65.3
 

23 In 2011–12, 79% of persons aged 18 years and over who participated in the NHMS fasted. Data relating to fasting tests (for example, the fasting plasma glucose test) relate to the fasting population only. Analysis of the characteristics of people who fasted compared with those who did not fast showed no difference between fasters and non-fasters.

24 The following table compares characteristics of persons who participated in the NHMS with those who participated in the NHS and NNPAS.

Comparisons between NHMS and NHS/NNPAS samples, persons aged 18 years and over, 2011-12

 NHMS (unweighted) %NHS/NNPAS (unweighted) %
Married(a)
58.5
52.8
Born in Australia
70.9
71.4
Has a non-school qualification
62.5
59.1
In the Labour Force
63.6
66.5
Self-reported diabetes(b)
7.0
6.5
Self-reported high cholesterol
12.0
9.6
Excellent or Very Good self-assessed health
53.4
52.9
Current daily smoker
12.0
17.6
Overweight/obese(d)
66.4
64.9
a. Includes de facto couples.
b. Includes persons who self-reported they had diabetes, regardless if it was current or long-term (excludes gestational diabetes).
c. Includes persons who self-reported they had high cholesterol and it was current and long-term.
d. Includes only persons for whom height and weight were measured.
 

25 More information on response rates is available in the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

Weighting, benchmarking and estimation

26 Weighting is a process of adjusting results from a sample survey to infer results for the in-scope total population. To do this, a weight is allocated to each sample person. The weight is a value which indicates how many population units are represented by the sample unit.

27 The first step in calculating weights for each person was to assign an initial weight, which was equal to the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 others). An adjustment was then made to these initial weights to account for the time period in which a person was assigned to be enumerated.

28 The weights are calibrated to align with independent estimates of the population of interest, referred to as 'benchmarks', in designated categories of sex by age by area of usual residence. Weights calibrated against population benchmarks compensate for over or under-enumeration of particular categories of persons and ensure that the survey estimates conform to the independently estimated distribution of the population by age, sex and area of usual residence, rather than to the distribution within the sample itself. The selection of benchmarks was chosen to maximise the accuracy of the estimates of biomedical characteristics, by reducing both random and systematic errors as much as possible.

29 The NHMS results were benchmarked to the estimated resident population living in private dwellings in non-Very Remote areas of Australia at 31 October 2011. Excluded from these benchmarks were persons living in discrete Aboriginal and Torres Strait Islander communities, as well as a small number of persons living within Collection Districts that include discrete Aboriginal and Torres Strait Islander communities. The benchmarks, and hence the estimates from the survey, do not (and are not intended to) match estimates of the total Australian resident population (which include persons living in Very Remote areas or in non-private dwellings, such as hotels) obtained from other sources.

30 Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristic of interest. Estimates of non-person counts (for example, number of conditions) are obtained by multiplying the characteristic of interest with the weight of the reporting person and aggregating.

31 The weights for the NHMS are different to the weights for the combined NHS/NNPAS due to the differing response patterns between the surveys.

32 An investigation was undertaken to determine whether the accuracy of NHMS estimates could be improved by weighting with any other variables collected in the NHS and NNPAS, including smoking status, Body Mass Index, self-assessed health, physical activity, employment status, marital status, country of birth and blood pressure. While the use of some of these variables would have improved the accuracy of some NHMS estimates (e.g. the use of smoker status in the weighting process would have ensured that totals relating to current daily smokers were identical in the NHMS to those in the combined NHS and NNPAS), they made no difference to the main variables of interest in the NHMS (i.e. estimates of diabetes, cholesterol) and even in some cases increased the measure of sampling error or Relative Standard Error (RSE).

33 The decision to maximise the accuracy of these main variables of interest in the NHMS by not including those other variables in the calculation of weights for the NHMS means that, while variables collected in the NHMS can be analysed with variables collected in either the NHS or NNPAS, the NHS and NNPAS should be used when reporting on the prevalence of these variables. For example, for self-reported medical conditions and risk factors such as smoking, the most accurate prevalences should be calculated using the combined NHS and NNPAS sample.

Reliability of estimates

34 All sample surveys are subject to sampling and non-sampling error.

35 Sampling error is the difference between estimates, derived from a sample of persons, and the value that would have been produced if all persons in scope of the survey had been included. For more information refer to the Technical Note. Indications of the level of sampling error are given by the Relative Standard Error (RSE) and Margin of Error (MoE).

36 In this publication, estimates with an RSE of 25% to 50% are preceded by an asterisk (e.g. *3.4) to indicate that the estimate has a high level of sampling error relative to the size of the estimate, and should be used with caution. Estimates with an RSE over 50% are indicated by a double asterisk (e.g. **0.6) and are generally considered too unreliable for most purposes. These estimates can be used to aggregate with other estimates to reduce the overall sampling error.

37 The MoEs are provided for all proportions to assist users in assessing their reliability. Users may find this measure is more convenient to use, rather than the RSE, in particular for small and large proportions. The proportion combined with the MoE defines a range which is expected to include the true population value with a given level of confidence. This is known as the confidence interval. This range should be considered by users to inform decisions based on the proportion.

38 Non-sampling error may occur in any data collection, whether it is based on a sample or a full count such as a census. Non-sampling errors occur when survey processes work less effectively than intended. Sources of non-sampling error include non-response or missing test results, errors in reporting by respondents or in recording of answers by interviewers, and occasional errors in coding and processing data.

39 Non-response can affect the reliability of results and can introduce a bias. The magnitude of any bias depends on the rate of non-response and the extent of the difference between the characteristics of those people who responded to the survey and those who did not.

Classifications

40 Country of birth was classified to the Standard Australian Classification of Countries (cat. no. 1269.0).

41 Main language spoken at home was classified according to the Australian Standard Classification of Languages (cat. no. 1267.0).

42 Descriptions for data items such as diabetes, Body Mass Index and blood pressure are included in the Glossary to this publication.

Confidentiality

43 The Census and Statistics Act, 1905 provides the authority for the ABS to collect statistical information, and requires that statistical output shall not be published or disseminated in a manner that is likely to enable the identification of a particular person or organisation. This requirement means that the ABS must take care and make assurances that any statistical information about individual respondents cannot be derived from published data.

44 Some techniques used to guard against identification or disclosure of confidential information in statistical tables are suppression of sensitive cells, random adjustments to cells with very small values, and aggregation of data. To protect confidentiality within this publication, some cell values may have been suppressed and are not available for publication but included in totals where applicable. As a result, sums of components may not add exactly to totals due to the confidentialisation of individual cells.

Rounding

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

46 Proportions presented in this publication are based on unrounded figures. Calculations using rounded figures may differ from those published.

Acknowledgements

47 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act, 1905.

48 The 2011–13 AHS, and particularly the NHMS component, was developed with the assistance of several advisory groups and expert panels. Members of these groups were drawn from Commonwealth and state/territory government agencies, non-government organisations, relevant academic institutions and clinicians. The valuable contributions made by members these groups are greatly appreciated.

Products and services

49 Summary results from the NHMS are available in spreadsheet form from the data downloads section in this release.

50 Special tabulations are available on request. Subject to confidentiality and sampling variability constraints, tabulations can be produced from the survey incorporating data items, populations and geographic areas selected to meet individual requirements. A list of data items is available from the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

52 Current publications and other products released by the ABS are listed on the ABS website www.abs.gov.au. The ABS also issues a daily Release Advice on the website which details products to be released in the week ahead.

Appendix A - NHMS biomarkers

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Summary of chronic disease biomarkers

 AgeTest typeFasting
Cardiovascular disease biomarkers   
Total cholesterol12+BloodNo
HDL cholesterol12+BloodNo
LDL cholesterol12+BloodYes
Triglycerides12+BloodYes
Apolipoprotein B12+BloodNo
Diabetes biomarkers
Fasting plasma glucose12+BloodYes
HbA1c12+BloodNo
Kidney disease biomarkers
ACR (Albumin creatinine ratio)5+UrineNo
eGFR (estimated glomerular filtration rate)18+BloodNo
Liver function biomarkers
ALT (alanine aminotransferase)12+BloodNo
GGT (gamma glutamyl transferase)12+BloodNo
Anaemia
Haemoglobin12+BloodNo
Tobacco use
Cotinine12+BloodNo
 

Summary of nutrient biomarkers

 AgeTest typeFasting
Folate
Serum folate12+BloodNo
Red cell folate (RCF)12+BloodNo
Vitamin B12
Serum B1212+BloodNo
Iron
Serum ferritin12+BloodNo
Soluble transferrin receptor (sTfR)12+BloodNo
Haemoglobin12+BloodNo
Inflammation marker (CRP)12+BloodNo
Vitamin D
Serum 25(OH)D12+BloodNo
Iodine
Iodine5+UrineNo
Sodium
Sodium concentration5+UrineNo
Potassium
Potassium concentration5+UrineNo

Technical note

Reliability of the estimates

1 Two types of errors are possible in an estimate based on a sample survey: sampling error and non-sampling error. The sampling error is a measure of the variability that occurs by chance because a sample, rather than the entire population, is surveyed. Since the estimates in this publication are based on information obtained from a sample of persons they are subject to sampling variability; that is, they may differ from the figures that would have been produced if all persons had been included in the survey. One measure of the likely difference is given by the standard error (SE). There are about two chances in three that a sample estimate will differ by less than one SE from the figure that would have been obtained if all persons had been included, and about 19 chances in 20 that the difference will be less than two SEs.

2 Another measure of the likely difference is the relative standard error (RSE), which is obtained by expressing the SE as a percentage of the estimate. The RSE is a useful measure in that it provides an immediate indication of the percentage errors likely to have occurred due to sampling, and thus avoids the need to refer also to the size of the estimate.

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

3 RSEs for the published estimates and proportions are supplied in the online version of this publication on the ABS website.

4 The smaller the estimate the higher the RSE. Very small estimates are subject to such high SEs (relative to the size of the estimate) as to detract seriously from their value for most reasonable uses. In the tables in this publication, only estimates with RSEs less than 25% are considered sufficiently reliable for most purposes. However, estimates with larger RSEs, between 25% and less than 50% have been included and are preceded by an asterisk (e.g. *3.4) to indicate they are subject to high SEs and should be used with caution. Estimates with RSEs of 50% or more are preceded with a double asterisk (e.g. **0.6). Such estimates are considered unreliable for most purposes.

5 The imprecision due to sampling variability, which is measured by the SE, should not be confused with inaccuracies that may occur because of imperfections in reporting by interviewers and respondents and errors made in coding and processing of data. Inaccuracies of this kind are referred to as the non-sampling error, and they may occur in any enumeration, whether it be in a full count or only a sample. In practice, the potential for non-sampling error adds to the uncertainty of the estimates caused by sampling variability. However, it is not possible to quantify the non-sampling error.

Standard errors of proportions and percentages

6 Proportions and percentages formed from the ratio of two estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. For proportions where the denominator is an estimate of the number of persons in a group and the numerator is the number of persons in a sub-group of the denominator group, the formula to approximate the RSE is given below. The formula is only valid when x is a subset of y.

\(\operatorname{RSE}\left(\frac{\mathrm{X}}{\mathrm{Y}}\right)=\sqrt{\mathrm{RSE}(\mathrm{X})^{2}-\mathrm{RSE}(\mathrm{Y})^{2}}\)

Comparison of estimates

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

\(\operatorname{SE}(\mathrm{x}-\mathrm{y})=\sqrt{[\mathrm{SE}(\mathrm{x})]^{2}+[\mathrm{SE}(\mathrm{y})]^{2}}\)

8 While the above formula will be exact only for differences between separate and uncorrelated (unrelated) characteristics of sub-populations, it is expected that it will provide a reasonable approximation for all differences likely to be of interest in this publication.

9 Another measure is the Margin of Error (MOE), which describes the distance from the population value of the estimate at a given confidence level, and 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 all dwellings had been enumerated). The 95% MOE is calculated as 1.96 multiplied by the SE.

10 The 95% MoE can also be calculated from the RSE by:

\(\operatorname{MoE}(\mathrm{y}) \approx \frac{\mathrm{RSE}(\mathrm{y}) \times \mathrm{y}}{100} \times 1.96\)

11 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 by a factor of

\(\Large \frac{2.576}{1.96}\)

12 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 of the same level of confidence by taking the estimate plus or minus the MoE of the estimate.

Example of interpretation of sampling error

13 Standard errors can be calculated using the estimates and the corresponding RSEs. For example, in the 2011-12 AHS: Biomedical results for chronic diseases, the estimated proportion of males aged 18 years and over who have abnormal levels of total cholesterol is 32.4%. The RSE for this estimate is 3.2%, and the SE is calculated by:

\(\begin{aligned} \mathrm{SE} \text { of estimate } &=\left(\frac{\mathrm{RSE}}{100}\right) \times \text { estimate } \\ &=0.032 \times 32.4 \\ &=1.0 \end{aligned}\)

14 Standard errors can also be calculated using the MoE. For example, the MoE for the estimate of the proportion of males aged 18 years and over who have abnormal levels of total cholesterol is +/- 2.0 percentage points. The SE is calculated by:

\(\begin{aligned} \mathrm{SE} \text { of estimate } &=\left(\frac{\mathrm{MoE}}{1.96}\right) \\ &=\left(\frac{2.0}{1.96}\right) \\ &=1.0 \end{aligned}\)

15 Note due to rounding the SE calculated from the RSE may be slightly different to the SE calculated from the MoE for the same estimate.

16 There are about 19 chances in 20 that the estimate of the proportion of males aged 18 years and over who have abnormal levels of total cholesterol is within +/- 2.0 percentage points from the population value.

17 Similarly, there are about 19 chances in 20 that the proportions of males aged 18 years and over who have abnormal levels of total cholesterol is within the confidence interval of 30.4% to 34.4%.

Significance testing

18 For comparing estimates between surveys or between populations within a survey it is useful to determine whether apparent differences are 'real' differences between the corresponding population characteristics 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:

\(\Large \frac{|\mathrm{x}-\mathrm{y}|}{\mathrm{SE}(\mathrm{x}-\mathrm{y})}\)

19 If the value of the statistic is greater than 1.96 then we may 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

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Age standardisation

Age standardisation is a way of allowing comparisons between two or more populations with different age structures, in order to remove age as a factor when examining relationships between variables. For example, the age structure of the population of Australia is changing over time. As the prevalence of a particular health condition (for example, arthritis) may be related to age, any increase in the proportion of people with that health condition over time may be due to real increases in prevalence or to changes in the age structure of the population over time or to both. Age standardising removes the effect of age in assessing change over time or between different populations. Age standardised proportions in this publication have been age-standardised to the 2001 standard population.

Albumin creatinine ratio (ACR)

The ratio of albumin (a protein) to creatinine (a waste product) in the urine can determine how well the kidneys are functioning. An elevated ACR result may indicate kidney disease or kidney damage. In this survey, abnormal ACR - also known as albuminuria - is defined as 2.5 mg/mmol or greater for males, and 3.5 mg/mmol or greater for females.

Albuminuria

Albuminuria is defined as the presence of albumin, a type of protein, in the urine. In this survey, the presence of albuminuria was defined as an ACR reading of greater than or equal to 2.5 mg/mmol for males and greater than or equal to 3.5 mg/mmol for females.

Also see Albumin creatinine ratio (ACR), Macroalbuminuria, Microalbuminuria and Normoalbuminuria.

Alanine aminotransferase (ALT)

ALT is an enzyme found mainly in the liver. When the liver is damaged or diseased, ALT leaks into the bloodstream. In this survey, abnormal ALT is defined as greater than 30 U/L for males aged 12–14 years, and greater than 40 U/L for males aged 15 and over. For females aged 12 years and over, abnormal ALT is defined as greater than 30 U/L.

Anaemia

Anaemia describes a decrease in either the number of red blood cells in the body or the quantity of haemoglobin within red blood cells.

Also see haemoglobin.

Apolipoprotein B (Apo B)

Apo B is a protein that helps form the structure of LDL and other "bad" cholesterol particles. Apo B is not found in HDL ('good') cholesterol particles. Therefore, measuring apolipoprotein B levels can indicate the concentration of 'bad' cholesterol in the blood. In this survey, abnormal Apo B is defined as greater than 1.2 g/L for males and greater than 1.3 g/L for females.

Atherosclerosis

Atherosclerosis is the build up of fatty deposits in the blood vessels. Arteries that have been narrowed by atherosclerosis can constrict the flow of blood through the body, increasing the risk of heart attack, stroke, and other conditions. Atherosclerosis is a common cause of heart disease.

At high risk of diabetes

In this survey, a person was considered to be at high risk of diabetes if they did not currently have diabetes, but had an impaired fasting plasma glucose result, that is, a fasting plasma glucose level ranging from 6.1 mmol/L to less than 7.0 mmol/L. The equivalent cut-off for the glycated haemoglobin (HbA1c) test was a value of 6.0% to less than 6.5%.

Also see Diabetes, Known diabetes and Newly diagnosed diabetes.

Blood pressure

See High blood pressure.

Body Mass Index (BMI)

Body Mass Index (BMI) is a simple index of weight-for-height that is commonly used to classify underweight, normal weight, overweight and obesity. It is calculated from height and weight information, using the formula weight (kg) divided by the square of height (m). To produce a measure of the prevalence of underweight, normal weight, overweight or obesity in adults, BMI values are grouped according to the table below which allows categories to be reported against both the World Health Organization (WHO) and National Health and Medical Research Council (NHMRC) guidelines.

Body Mass Index, adults

CategoryRange
UnderweightLess than 18.50
Normal range18.50 — 24.99
Overweight25.00 — 29.99
Obese30.00 or more
 

Separate BMI classifications were produced for children. BMI scores were created in the same manner described above but also took into account the age and sex of the child. There are different cutoffs for BMI categories (underweight/normal combined, overweight or obese) for male and female children. These categories differ to the categories used in the adult BMI classification and follow the scale provided in Cole TJ, Bellizzi MC, Flegal KM and Dietz WH, Establishing a standard definition for child overweight and obesity worldwide: international survey, BMJ 2000; 320. For a detailed list of the cutoffs used to calculate BMI for children see the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001)

Cholesterol

Cholesterol is a type of fat that circulates in the blood. It is essential for many metabolic processes, including the production of hormones and in building cells. There are two main types of cholesterol: high density lipoprotein (HDL) and low density lipoprotein (LDL).

Also see Total cholesterol, HDL cholesterol and LDL cholesterol.

Chronic kidney disease stages

Chronic kidney disease stages were derived using a combination of participants' estimated glomerular filtration rate (eGFR) results with their albumin creatinine ratio (ACR) results. The different stages were defined as follows:

  • No indicators of chronic kidney disease - eGFR greater than or equal to 60 mL/min/1.73 m² and no presence of albuminuria
  • Stage1 - eGFR greater than or equal to 90 mL/min/1.73 m² & albuminuria
  • Stage 2 - eGFR 60 to 89 mL/min/1.73 m² & albuminuria
  • Stage 3a - eGFR 45–59 mL/min/1.73 m²
  • Stage 3b - eGFR 30–44 mL/min/1.73 m²
  • Stage 4–5 - eGFR less than 30 mL/min/1.73 m²
     

Collection District (CD)

A CD is the second smallest geographic area defined in the Australian Standard Geographical Classification (ASGC), the smallest being the Mesh Block. The CD was designed for use in the Census of Population and Housing as the smallest unit for collection and processing.

Cotinine

Cotinine is produced in the process of breaking down, or metabolising, nicotine. Elevated levels of cotinine in the blood can be used to determine exposure to tobacco smoke. However, cotinine levels only remain elevated for around 20 hours after exposure to tobacco smoke, therefore it can only provide a measure of short-term exposure. In this survey, cotinine levels of 140 nmol/L or greater indicate exposure to tobacco smoke.

Current daily smoker

A current daily smoker is a respondent who reported at the time of interview that they regularly smoked one or more cigarettes, cigars or pipes per day. Also see Smoker status.

Diabetes

Diabetes is a chronic condition where insulin, a hormone that controls blood glucose levels, is no longer produced or is not produced in sufficient amounts by the body. In this survey, diabetes prevalence was derived using a combination of blood test results and self-reported information on diabetes diagnosis and medication use.

Also see Known diabetes, Newly diagnosed diabetes and At high risk of diabetes.

Dyslipidaemia

Refers to a number of different lipid disorders (that is, conditions where there are too many fats in the blood). In this survey, a person was considered to have dyslipidaemia if they had one or more of the following:

  • Taking cholesterol-lowering medication
  • Total cholesterol greater than or equal to 5.5 mmol/L
  • HDL cholesterol less than 1.0 mmol/L for men and less than 1.3 mmol/L for women
  • LDL cholesterol greater than or equal to 3.5 mmol/L
  • Triglycerides greater than or equal to 2.0 mmol/L
     

Estimated glomerular filtration rate (eGFR)

eGFR measures the rate at which the kidneys filter wastes from the blood. It is considered to be the best measure of kidney function. In this survey, abnormal kidney function using eGFR is defined as a reading of less than 60 mL/min/1.73m².

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. Also see Unemployed and Not in the labour force.

Fasting plasma glucose

A blood test that measures the amount of glucose (a sugar) in the blood. In this survey, fasting plasma glucose levels of 7.0 mmol/L or greater indicates diabetes. A fasting plasma glucose level from 6.1 mmol/L to less than 7.0 mmol/L is known as impaired fasting plasma glucose and indicates that a person is at high risk of diabetes.

Gamma glutamyl transferase (GGT)

GGT is an enzyme that is found in high concentrations in the liver, and in lesser concentrations in the kidneys, bile duct, pancreas, gallbladder, spleen, heart, and brain. When these tissues are damaged by disease or inflammation, GGT leaks from the tissue into the bloodstream. In this survey, abnormal GGT is defined as greater than 30 U/L for children aged 12–14 years. Abnormal GGT is defined as greater than 40 U/L for males aged 15–17 years, and as greater than 50 U/L for males aged 18 years and over. For females aged 15 years and over, abnormal GGT is defined as greater than 35 U/L.

Haemoglobin

Haemoglobin is an iron-containing protein and is found in the red blood cells and helps transport oxygen from the lungs to the rest of the body. Low haemoglobin levels in the blood may indicate anaemia. In this survey, the risk of anaemia is defined using haemoglobin levels. For children aged 12–14 years and for non-pregnant women aged 15 years or older, haemoglobin levels less than 120 g/L are defined as at risk of anaemia. For pregnant women, haemoglobin levels less than 110 g/L are defined as at risk of anaemia. For males aged 15 years or older, haemoglobin levels less than 130 g/L are defined as at risk of anaemia.

See also Anaemia.

HbA1c test

Glycated haemoglobin, commonly known as HbA1c, is a blood test that measures what the person's average blood glucose level has been in the previous three months. Results from the HbA1c test can be expressed either as a percentage (%) or as a measurement in mmol/mol. In this survey, normal HbA1c is defined as less than 6.0%; at high risk of diabetes is defined as 6.0% to less than 6.5% and levels greater than or equal to 6.5% indicate diabetes.

HDL cholesterol

High density lipoprotein (HDL) cholesterol is the measure of "good" cholesterol. HDL picks up excess cholesterol in the blood and takes it to the liver where it is broken down. High levels of HDL cholesterol reduce the risk of heart disease, while low levels increase the risk. In this survey, abnormal HDL cholesterol is defined as less than 1.0 mmol/L for males, and as less than 1.3 mmol/L for females.

High blood pressure

A measured blood pressure reading of 140/90 mm Hg (millimetres of mercury) or higher. Data on high blood pressure in this publication refer to measured blood pressure only, and do not take into account whether people who might otherwise have high blood pressure are managing their condition through the use of blood pressure medications.

Impaired fasting plasma glucose

A fasting plasma glucose level ranging from 6.1 mmol/L to less than 7.0 mmol/L. Also see At high risk of diabetes.

Index of Relative Socio-Economic Disadvantage

This is one of four Socio-Economic Indexes for Areas (SEIFA) compiled by ABS following each Census of Population and Housing. The indexes are compiled from various characteristics of persons resident in particular areas: the Index of Relative Socio-Economic Disadvantage summarises attributes such as low income, low educational attainment, high unemployment and jobs in relatively unskilled occupations. A lower Index of Relative Socio-Economic Disadvantage quintile (e.g. the first quintile) indicates relatively greater disadvantage and a lack of advantage in general. A higher Index of Relative Socio-Economic Disadvantage (e.g. the fifth quintile) indicates a relative lack of disadvantage and greater advantage in general. For further information about SEIFA see the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

Kidney disease stages

See Chronic kidney disease stages

Known diabetes

In this survey, a person was considered to have known diabetes if:

  • they had ever been told by a doctor or nurse that they have diabetes and they were taking diabetes medication (either insulin or tablets); OR
  • they had ever been told by a doctor or nurse that they have diabetes and their blood test result for fasting plasma glucose was greater than or equal to the cut off point for diabetes (that is, greater than or equal to 7.0 mmol/L).
     

People who had been told by a doctor or nurse that they have diabetes, but who were not taking medication for diabetes and did not have a fasting plasma glucose level of 7.0 mmol/L or greater, were classified as not having diabetes.

People with known diabetes were further classified as having Type I, Type II or Type unknown, based on the type of diabetes that a doctor or nurse told them they had. Women with gestational diabetes were excluded.

The corresponding diabetes cut-off for HbA1c is a value of 6.5% or greater.

Labour force status

Refers to the employment situation of respondents at the time of the survey. Categories are:

  • employed
  • unemployed (aged 15 years and over, not employed and actively looked for work in the 4 weeks prior to the survey)
  • not in the labour force (all children less than 15 years, and persons 15 years and over who were neither employed or unemployed).
     

See also Employed, Unemployed, Not in the labour force.

LDL cholesterol

Low density lipoprotein (LDL) cholesterol is the measure of "bad" cholesterol in the blood. Over time, LDL cholesterol can build up in the blood vessels and arteries, blocking the passage of blood flow. In this survey, abnormal LDL cholesterol is defined as 3.5 mmol/L or greater.

Also see Total cholesterol and HDL cholesterol.

Macroalbuminuria

An increased amount of albumin, a protein, in the urine. Macroalbuminuria is defined as an albumin creatinine ratio (ACR) of more than 25 mg/mmol for males, or more than 35 mg/mmol for females. Also see Albumin creatinine ratio (ACR).

Margin of Error (MoE)

Describes the distance from the precision of the estimate at a given confidence level, and is specified at a given level of confidence (95% in this publication). In this publication, Margin of error has only been provided for proportions and averages tables. For more information see the Technical notes of this publication.

Microalbuminuria

A slightly increased amount of albumin, a protein, in the urine. Microalbuminuria is defined as an albumin creatinine ratio (ACR) of 2.5 to 25 mg/mmol for males, or 3.5 to 35 mg/mmol for females. Also see Albumin creatinine ratio (ACR).

Newly diagnosed diabetes

In this survey, a person was considered to have newly diagnosed diabetes if they reported no prior diagnosis of diabetes but had a fasting plasma glucose value of 7.0 mmol/L or greater. The equivalent cut-off for the HbA1c test is a value of 6.5% or greater.

Also see Known diabetes and At high risk of diabetes.

Non-HDL Cholesterol

Calculated by subtracting the level of HDL cholesterol from the level of total cholesterol. Non-HDL cholesterol levels are monitored as part of diabetes management as a tool to assess cardiovascular risk.

Normoalbuminuria

Normal levels of protein in the urine. Normoalbuminuria is defined as an albumin creatinine ratio (ACR) of less than 2.5 mg/mmol for males, or less than 3.5 mg/mmol for females. See also Albumin creatinine ratio (ACR).

Normal weight

See Body Mass Index (BMI)

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.
     

Obese

See Body Mass Index (BMI).

Overweight

See Body Mass Index (BMI).

Relative Standard Error (RSE)

The standard error expressed as a percentage of the estimate. For more information see the Technical notes in this publication.

Remoteness

The Remoteness Structure for the Australian Statistical Geography Standard (ASGS) 2011, has five categories based on an aggregation of geographical areas which share common characteristics of remoteness, determined in the context of Australia as a whole. These categories are:

  • Major cities of Australia
  • Inner regional Australia
  • Outer regional Australia
  • Remote Australia
  • Very remote Australia
     

The five categories are generally aggregated in some way for use in output.

The 2011 Remoteness Structure has been built using the same principles as the 2006 Remoteness Structure. The primary difference is that it was built from ASGS Statistical Area Level 1 (SA1) regions rather than from 2006 Census Collection Districts (CCD).

Smoker status

The extent to which a respondent was smoking at the time of interview, and refers to regular smoking of tobacco, including manufactured (packet) cigarettes, roll-your-own cigarettes, cigars and pipes, but excludes chewing tobacco and smoking of non-tobacco products. Categorised as:

  • Current daily smoker - a respondent who reported at the time of interview that they regularly smoked one or more cigarettes, cigars or pipes per day;
  • Current smoker - Other - a respondent who reported at the time of interview that they smoked cigarettes, cigars or pipes, less frequently than daily;
  • Ex-smoker - a respondent who reported that they did not currently smoke, but had regularly smoked daily, or had smoked at least 100 cigarettes, or smoked pipes, cigars, etc at least 20 times in their lifetime; and
  • Never smoked - a respondent who reported they had never regularly smoked daily, and had smoked less than 100 cigarettes in their lifetime and had smoked pipes, cigars, etc less than 20 times.
     

Total cholesterol

Total cholesterol is a measure of all the different types of fats in the blood. In this survey, abnormal total cholesterol is defined as 5.5 mmol/L or greater.

Also see Cholesterol, HDL cholesterol, and LDL cholesterol.

Triglycerides

Triglycerides are a fatty substance in the blood typically caused by a diet high in fat and kilojoules. Triglycerides can also become elevated as a result of having other conditions, such as diabetes and kidney disease. In this survey, abnormal triglycerides are defined as 2.0 mmol/L or greater.

Underweight

See Body Mass Index (BMI).

Unemployed

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

Waist circumference

Waist circumference is associated with an increased risk of metabolic complications associated with obesity. The World Health Organisation (WHO) and National Health and Medical Research Council (NHMRC) approved the following guidelines for Caucasian men and women:

Waist measurement guidelines, adults

 MenWomen
Not at riskWaist circumference less than 94 cmWaist circumference less than 80 cm
Increased riskWaist circumference more than or equal to 94 cmWaist circumference more than or equal to 80 cm
Greatly increased riskWaist circumference more than or equal to 102 cmWaist circumference more than or equal to 88 cm

Abbreviations

The following symbols and abbreviations are used in this publication:

Show all

. .not applicable
AATSIHSAustralian Aboriginal and Torres Strait Islander Health Survey
ACRAlbumin Creatinine ratio
ABSAustralian Bureau of Statistics
AHSAustralian Health Survey
ALTAlanine aminotransferase
ASGCAustralian Standard Geographical Classification
AusDiabAustralian Diabetes, Obesity and Lifestyle Study, 1999-2000
BMIBody Mass Index
CDcollection district
CKDChronic kidney disease
CKD-EPIChronic Kidney Disease Epidemiology Collaboration
cmcentimetre
CVDCardiovascular disease
DHMDouglass Hanly Moir
DoHACommonwealth Department of Health and Ageing
eGFRestimated glomerular filtration rate
FPGfasting plasma glucose
g/Lgrams per litre
GGTGamma glutamyl transferase
HbA1cGlycated haemoglobin test
HDLHigh-density lipoprotein
kgkilogram
LDLLow-density lipoprotein
mL/minmillilitres per minute
mm Hgmillimetre of mercury
mmol/Lmillimoles per litre
MoEMargin of Error
nanot available
necnot elsewhere classified
NHMSNational Health Measures Survey
NHSNational Health Survey
nmol/Lnanomoles per litre
NNPASNational Nutrition and Physical Activity Survey
OGTTOral Glucose Tolerance Test
RSErelative standard error
SEstandard error
SEIFASocio-Economic Indexes for Areas
VHMVictorian Health Monitor
WHOWorld Health Organization