Australian Health Survey: Biomedical Results for Nutrients methodology

1 This publication is the second release of information from the 2011–12 National Health Measures Survey (NHMS), which forms part of the 2011–13 Australian Health Survey (AHS). The first release, which focussed on chronic disease biomarkers, was published in August 2013. See Australian Health Survey: Biomedical Results for Chronic Diseases for more information.

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
• nutrient biomarkers, including tests for iron, folate, iodine, Vitamin B12 and Vitamin D.
   

See Appendix A for the list of tests conducted in the NHMS.

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 nutrient biomarkers, including iron, folate, iodine, Vitamin B12 and Vitamin D.The list of data items from the survey, as well as detailed information on the different tests used in the NHMS, is available in the Australian Health Survey: Users' Guide, 2011–13 (cat. no. 4363.0.55.001).

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 12,300 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. The first results from the National Aboriginal and Torres Strait Islander Health Survey were released on the 27th November 2013. See Australian Aboriginal and Torres Strait Islander Health Survey: First Results, Australia (cat. no. 4727.0.55.001) for more information. The remainder of the results will be released progressively into 2014.

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 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.

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 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, 2011–13 (cat. no. 4363.0.55.001).

19 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.

20 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).

21 The following table presents response rates for the NHMS.

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

23 More information on response rates is available in the Australian Health Survey: Users' Guide, 2011–13 (cat. no. 4363.0.55.001).

24 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.

25 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.

26 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.

27 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.

28 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.

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

30 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).

31 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.

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

33 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).

34 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.

35 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.

36 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.

37 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.

38 Results for nutrient biomarkers may vary depending on the type of test and assay used, as well as the type of machine employed to spin the samples. Details around the procedures followed for each of the nutrient biomarkers in the NHMS are outlined in Australian Health Survey: Users' Guide, 2011–13 (cat. no. 4363.0.55.001).

39 In the NHMS, urinary iodine levels were measured using the inductively coupled plasma mass spectrometry (ICP-MS) method. Many other studies including the 2003–04 Australian National Iodine Nutrition Study and the 2009–10 Victorian Health Monitor used the Sandell-Koltoff spectrophotometric (S-K) method to measure iodine levels. The World Health Organization and the International Council for Control of Iodine Deficiency Disorders (ICCIDD) determined a set of cut-offs using the S-K method to define if a population is iodine deficient. However, no agreed cut-offs have been developed yet for the new ICP-MS method. Therefore, the cut-offs for the S-K method were applied to the ICP-MS results in the NHMS to determine iodine deficiency. Research has shown there to be good agreement between the two methods overall, but the ICP-MS method may be more sensitive in detecting iodine deficiency than the S-K method. Therefore any comparison of iodine deficiency between the NHMS and studies that used the S-K method method should be applied with caution.

40 In the NHMS, month of collection was used to analyse the seasonal effects of Vitamin D deficiency. Although there were proportionally more people who had their blood samples taken in Autumn than in Spring, this only had a very small impact on the overall rate of Vitamin D deficiency at the population level.

41 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.

42 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.

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

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

45 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.

46 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.

47 Summary results from the NHMS are available in spreadsheet form from the Data downloads section in this release.

48 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, 2011–13 (cat. no. 4363.0.55.001).

49 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.

The following symbols and abbreviations are used in this publication: