Latest release

Australian Health Survey: Usual Nutrient Intakes methodology

Reference period
2011-12 financial year
Released
6/03/2015
Next release Unknown
First release

Explanatory notes

Introduction

1 This publication is the second release of nutrition data from the 2011-12 National Nutrition and Physical Activity Survey (NNPAS). The first release was published in May 2014.

2 The 2011-12 NNPAS was conducted throughout Australia from May 2011 to June 2012. The NNPAS was collected as one of a suite of surveys conducted from 2011-2013, called the Australian Health Survey (AHS).

3 The Australian Health Survey: Usual Nutrient Intakes publication contains usual (long term) nutrient intake information modelled from two days of 24-hour dietary recall data. Usual intakes of nutrients are provided by age groups and sex at the national level, including comparison with nutrient requirements, where relevant.

4 The statistics presented in this publication are only a selection of the information collected in the NNPAS. Further publications from the Australian Health Survey are outlined in the Release Schedule, while the list of data items currently available from the survey are available in the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

Scope of the survey

5 The National Nutrition and Physical Activity Survey (NNPAS) contains a sample of approximately 9,500 private dwellings across Australia.

6 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, excepting the Northern Territory where the population living in Very Remote areas accounts for around 23% of persons.

7 Non-private dwellings such as hotels, motels, hospitals, nursing homes and short-stay caravan parks were excluded from the survey. This may affect estimates of the number of people with some chronic health conditions (for example, conditions which may require periods of hospitalisation).

8 Within each selected dwelling, one adult (aged 18 years and over) and, where possible, one child (aged 2 years and over) were randomly selected for inclusion in the survey. Sub-sampling within households enabled more information to be collected from each respondent than would have been possible had all usual residents of selected dwellings been included in the survey.

9 The following groups were excluded from the survey:

• 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
• visitors to private dwellings.

Data collection

10 Trained ABS interviewers conducted personal interviews with selected residents in sampled dwellings. One person aged 18 years and over in each dwelling was selected and interviewed about their own health characteristics including a 24-hour dietary recall and a physical activity module. An adult, nominated by the household, was interviewed about one child (aged two years and over) in the household. Selected children aged 15-17 years may have been personally interviewed with parental consent. An adult, nominated by the household, was also asked to provide information about the household, such as the combined income of other household members. Children aged 6-14 years were encouraged to be involved in the survey, particularly for the 24-hour dietary recall and physical activity module. For further information, see Data Collection in the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

11 All selected persons were required to have a follow-up phone interview at least eight days after the face to face interview to collect a further 24-hour dietary recall. For those who participated, pedometer data was reported during this telephone interview.

Survey design

12 Dwellings were selected at random using a multistage area sample of private dwellings for the NNPAS.

The initial sample selected for the survey consisted of approximately 14,400 dwellings. This was reduced to approximately 12,400 dwellings after sample loss (for example, households selected in the survey which had no residents in scope of the survey, vacant or derelict buildings, or buildings under construction). Of those remaining dwellings, 9,519 (or 77.0%) were fully or adequately responding, yielding a total sample for the survey of 12,153 persons (aged two years and over).

New South WalesVictoriaQueenslandSouth AustraliaWestern AustraliaTasmaniaNorthern TerritoryAustralian Capital TerritoryAustralia
Households approached (after sample loss)2 2271 9831 9881 5511 5451 1559111 00612 366
Households in sample1 6661 3711 5251 2111 3341 0035928179 519
Response rate (%)74.869.176.778.186.386.865.081.277.0
Persons in sample2 1391 7491 9641 5261 7061 2457631 06112 153

NNPAS, approached sample, final sample and response rates

13 Of the 12,153 people in the final sample, 98% provided the first (Day 1), with the missing 2% of Day 1 dietary recalls being imputed. The second 24-hour dietary recall (Day 2) had 7,735 participants (64% of the total). The Day 2 24-hour dietary recall participation was slightly higher among older respondents, and sex did not appear as a factor in participation.

14 More information on response rates and imputation is provided in the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

15 To take account of possible seasonal effects on health and nutrition characteristics, the NNPAS sample was spread randomly across a 12-month enumeration period. Between August and September 2011, survey enumeration was suspended due to field work associated with the 2011 Census of Population and Housing.

Weighting, benchmarking and estimation

16 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 unit; for example, a household or a person. The weight is a value which indicates how many population units are represented by the sample unit.

17 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.

18 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.

19 The NNPAS was 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. For the NNPAS, a seasonal adjustment was also incorporated into the person weights.

20 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 organised physical activities) are obtained by multiplying the characteristic of interest with the weight of the reporting person and aggregating.

Reliability of estimates

21 All sample surveys are subject to sampling and non-sampling error. Estimates derived from models, including the NCI method, are also subject to prediction error and simulation variance.

22 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 95% Margin of Error (MoE).

23 In this publication, RSEs are provided for all count estimates. 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.

24 MoEs are provided for all proportion estimates to assist users in assessing the reliability of these types of estimates. The estimate combined with the MoE defines a range which is expected to include the true population value with a 95% level of confidence. This is known as the 95% confidence interval. This range should be considered by users to inform decisions based on the estimate.

25 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, errors in reporting by respondents or in recording of answers by interviewers, and occasional errors in coding and processing data.

26 Prediction error and simulation variance are forms of error which may occur when using a model such as the NCI method. Care was taken to ensure the input 24-hour dietary recall data was suitable for use in the model. Every effort is made to ensure an appropriate model specification is used through external literature research and statistical testing. For more information see Data Quality in the Users' Guide.

27 Where comparisons with guideline values (nutrient reference values or NRVs) have been made, any error in these guideline values will affect the quality of the resulting estimates. The NRVs are a set of recommendations made by the Australian National Health and Medical Research Council and the New Zealand Ministry of Health for nutritional intake, based on currently available scientific knowledge. More information on the methods used to derive the NRVs for each nutrient is available on the Nutrient Reference Values for Australia and New Zealand website.

28 Of particular importance to nutrition surveys is a widely observed tendency for people to under-report their food intake. This can include:

• actual changes in foods eaten because people know they will be participating in the survey
• misrepresentation (deliberate, unconscious or accidental), e.g. to make their diets appear more ‘healthy’ or be quicker to report.

Analysis of the 2011-12 NNPAS suggests that, like other nutrition surveys, there has been some under-reporting of food intake by participants in this survey. Given the association of under-reporting with overweight/obesity and consciousness of socially acceptable/desirable dietary patterns, under-reporting is unlikely to affect all foods and nutrients equally. No respondents were excluded from the sample on the basis of low total reported energy intakes (low energy reporters were included in the input data set for usual nutrient intakes). For more information see Under-reporting in Nutrition Surveys in the AHS Users' Guide, 2011-13.

29 Another factor affecting the accuracy of the 24-hour dietary recall data is that most young children are unable to recall their intakes. Similarly, parents/carers of school-aged children may not be aware of a child’s total food intake, which can lead to systematic under-reporting. Young children were encouraged to assist in answering the dietary recall questions. See the Interviews section of Data Collection for more information on proxy use in the 24-hour dietary recall module.

30 Another non-sampling error specific to nutrition surveys is the accuracy of the nutrient and measures database containing thousands of foods used to derive the nutrient estimates. The databases used for the 2011-12 NNPAS were developed by Food Standards Australia New Zealand specifically for the survey. A complete nutrient profile of 44 nutrients was created based on FSANZ’s latest available data, however, not all data was based on directly analysed foods. Some data was borrowed from overseas food composition tables, food label information, imputed data from similar foods, or data calculated using a recipe approach. See AUSNUT 2011-13 for more information.

31 Non-response occurs when people cannot or will not cooperate, or cannot be contacted. Non-response can affect the reliability of results and can introduce 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.

32 The following methods were adopted to reduce the level and impact of non-response:

• face-to-face interviews with respondents
• the use of interviewers, where possible, who could speak languages other than English
• follow-up of respondents if there was initially no response
• weighting to population benchmarks to reduce non-response bias.

33 By careful design and testing of the questionnaire, training of interviewers, and extensive editing and quality control procedures at all stages of data collection and processing, other non-sampling error has been minimised. However, the information recorded in the survey is essentially 'as reported' by respondents, and hence may differ from information collected using different methodology.

Comparisons with 1995 NNS

34 Comparisons of this publication with 1995 NNS usual nutrient intakes are not recommended due to changes in usual intake adjustment methodology and different survey methodology. See the Comparisons with 1995 NNS chapter of the AHS: Users' guide 2011-13 (cat. no. 4363.0.55.001) for more details.

Confidentiality

35 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.

36 In this publication, confidentiality is protected due to modelling of age and sex groups only. No data is presented for small groups or individual respondents.

Rounding

37 Estimates presented in this publication have been rounded. As a result, sums of components may not add exactly to totals. Estimates of zero or rounded to zero and their corresponding measures of error have been represented by a dash.

38 All statistics relating to proportion of persons are rounded to one decimal place and all statistics relating to number of persons are rounded to whole numbers (‘000). Percentiles of usual nutrient intakes and mean usual nutrient intakes are rounded to one decimal place or whole numbers, depending on the corresponding Nutrient Reference Value or the scale of the data.

Acknowledgements

39 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.

40 The ABS gratefully acknowledges and thanks the Agricultural Research Service of the USDA for giving permission to adapt and use their Dietary Intake Data System including the AMPM for collecting dietary intake information as well as other processing systems and associated materials.

41 This publication is a joint release by the ABS and Food Standards Australia New Zealand (FSANZ). FSANZ and the ABS jointly investigated and validated the use of the NCI method with the 2011-12 NNPAS. FSANZ was contracted to provide advice throughout the survey development, processing, and collection phases of the 2011-12 NNPAS, and to provide a nutrient database for the coding of foods and dietary supplements consumed. The ABS would like to acknowledge and thank FSANZ for providing their support, advice and expertise to the 2011-12 NNPAS.

42 The ABS gratefully acknowledges and thanks researchers at the National Cancer Institute (NCI) in the USA and elsewhere for developing and making available the NCI method and corresponding SAS macros, and providing expert advice on the use of the method.

Products and services

43 Summary results from this survey are available in spreadsheet form from the Data downloads section in this release.

44 Because the NCI method produces estimates of usual nutrient intakes for groups and not individuals, usual nutrient intake data is not available at the unit record level.

45 Summary tables containing aggregated estimates of the prevalence of inadequate intakes, intakes above the upper level and intakes outside of acceptable macronutrient distribution ranges are available in the Data downloads section in this release. Information on how to aggregate estimates for different age and sex groups is in Summary Tables in the Users' Guide.

Related publications

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

Technical note

Reliability of the estimates

1 Two types of error are possible in an estimate based on a sample survey: sampling error and non-sampling error. Estimates derived from models, including the NCI method, are also subject to prediction error and simulation variance. 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 occupants of a sample of dwellings they are subject to sampling variability; that is they may differ from the figures that would have been produced if all dwellings 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 dwellings 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.

$$\large{{R S E \%=\left(\frac{S E}{estimate}\right) \times 100}}$$

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

4 The smaller the estimate the higher is 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.

6 Prediction error is the variability attributed to the statistical accuracy of the model used in this publication, including bias due to specification of the model. Simulation error is the variability due to simulating different random effects in order to generate usual distribution intakes. Although every effort is made to ensure an appropriate model specification is used, through external literature research and statistical testing, these errors are not quantified and also add to the uncertainty of the estimates.

Standard errors of proportions and percentages

7 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.

$$\large{R S E\left(\frac{X}{Y}\right)=\sqrt{R S E(X)^{2}-R S E(Y)^{2}}}$$

Comparison of estimates

8 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:

$$\large{SE \left(x-y \right)=\sqrt{[{SE}({x})]^{2}+\left[{SE}\left.({y})\right]{^2}\right.}}$$

9 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.

10 Another measure is the Margin of Error (MoE), which describes the distance from the precision 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.

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

$$\large{M O E(y) \approx \frac{R S E(y) * y}{100} * 1.96}$$

12 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

$$\Large{\frac{2.576}{1.96}}$$

13 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

14 Standard errors can be calculated using the estimates and the corresponding RSEs. For example, for females aged 19-30 years, the mean usual intake of protein was 77 grams. The RSE for this estimate is 2%, and the SE is calculated by:

\large{\begin{aligned} SE\ of \ estimate &=\left(\frac{R S E}{100}\right) \times estimate \\ \\ &=0.02 \times 77 \\ \\ &=1.54 \end{aligned}}

15 Standard errors can also be calculated using the MoE. For example the MoE for the estimate of the proportion of females aged 71 years and over whose usual daily protein intake was below 46 grams is +/- 2.5 percentage points. The SE is calculated by:

\large{\begin{aligned} SE \ of \ estimate &=\left(\frac{M O E}{1.96}\right) \\ \\&=\left(\frac{2.5}{1.96}\right) \\ \\ &=1.3 \end{aligned}}

16 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.

17 There are about 19 chances in 20 that the estimate of the proportion of females aged 71 years and over whose usual daily protein intake was below 46 grams is +/- 2.5 percentage points from the population value.

18 Similarly, there are about 19 chances in 20 that the proportions of females aged 71 years and over whose usual daily protein intake was below 46 grams is within the confidence interval of 1.3% to 6.3%.

Significance testing

19 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:

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

20 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

The definitions used in this survey are not necessarily identical to those used for similar items in other collections. Additional information is contained in the Australian Health Survey: Users' Guide (cat. no. 4363.0.55.001).

Show all

24-hour dietary recall

This was the methodology used to collect detailed information on food and nutrient intake in the National Nutrition and Physical Activity Survey (NNPAS). The 24-hour dietary recall collected a list of all foods, beverages and dietary supplements consumed the previous day from midnight to midnight, and the amount consumed. For more information, see the 24-hour Dietary Recall chapter of the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

Acceptable Macronutrient Distribution Range (AMDR)

The Acceptable Macronutrient Distribution Range (AMDR) is an estimate of the range of intake for each macronutrient for individuals (expressed as percent contribution to energy), which would allow for an adequate intake of all the other nutrients whilst maximising general health outcomes. AMDRs are available for energy from the following nutrients: carbohydrate, fat and protein. See Nutrient Reference Values for Australia and New Zealand.

Alcohol

The term 'alcohol' is commonly used to refer to alcoholic beverages. However, in the 2011-12 NNPAS alcohol refers to pure alcohol (or ethanol), which, as a macronutrient, contributes 29 kJ per gram.

Alpha-linolenic acid

Alpha-linolenic acid is a plant-based omega-3 polyunsaturated fatty acid which is considered a small but important component of dietary intake in relation to helping reduce coronary heart disease risk.

Australian Health Survey (AHS)

The Australian Health Survey 2011-13 is composed of three separate surveys:

• National Health Survey (NHS) 2011-12
• National Nutrition and Physical Activity Survey (NNPAS) 2011-12
• National Health Measures Survey (NHMS) 2011-12.

In addition to this, the AHS Survey contains a Core dataset, which is produced from questions that are common to both the NHS and NNPAS. See The Structure of the Australian Health Survey for details.

Caffeine

Caffeine is a natural stimulant.

Calcium

Calcium is a mineral required for the growth and maintenance of the bones and teeth, as well as the proper functioning of the muscular and cardiovascular systems.

Carbohydrate

Carbohydrates usually provide the major part of energy in human diets. Carbohydrates are comprised of the elements of carbon, hydrogen and oxygen. Data for total carbohydrates include starch, sugars and related substances (sugar alcohols and oligosaccharides). Sugar alcohols and oligosaccharides are included in 'Total carbohydrates' but not in starch and sugar sub-totals. Therefore, total carbohydrate does not always equal the sum of sugars and starch.

Cereal based products and dishes

The 'Cereal based products and dishes' food group contains biscuits, cakes, pastries, pies, dumplings, pizza, hamburgers, hot dogs, and pasta and rice mixed dishes.

Cereals and cereal products

The 'Cereals and Cereal Products' food group includes grains, flours, bread and bread rolls, plain pasta, noodles and rice, and breakfast cereals.

Cholesterol

Cholesterol is a type of fat and a component of cell membrane.

Day 1 / Day 2 intake

Day 1 intake refers to information collected from the first 24-hour dietary recall, while Day 2 refers to information from the second 24-hour recall. In the 2011-12 NNPAS, Day 1 intake information was collected from all respondents, with a second 24-hour recall (Day 2) collected from around 64% of respondents. Nutrient intakes derived from 24-hour recall data do not represent the usual intake of a person because there is variation in day-to-day intakes. The second 24-hour recall is used to estimate and remove within-person variation in order to derive a usual nutrient intake distribution for the population. Usual nutrient intakes represent intakes over a long period of time.

Dietary energy

Dietary energy consists of energy provided by protein, fat, carbohydrate and alcohol. Small amounts of additional energy are from dietary fibre and organic acids.

Dietary fibre

Dietary fibre is generally found in edible plants or their extracts but can also come from synthetic analogues. It refers to the fractions of the plant or analogue that are resistant to digestion and absorption, which usually undergo fermentation in the large intestine. Dietary fibre plays a beneficial role in laxation, blood cholesterol levels, and blood glucose modulation. It comes in the form of polysaccharides, oligosaccharides and lignins.

Dietary guidelines

The National Health and Medical Research Council 2013 Australian Dietary Guidelines use the best available scientific evidence to provide information on the types and amounts of foods, food groups and dietary patterns that aim to:

• promote health and wellbeing
• reduce the risk of diet-related conditions
• reduce the risk of chronic disease.

The Guidelines are for use by health professionals, policy makers, educators, food manufacturers, food retailers and researchers.

The content of the Australian Dietary Guidelines applies to all healthy Australians, as well as those with common diet-related risk factors such as being overweight. They do not apply to people who need special dietary advice for a medical condition, or to the frail elderly.

Dietary supplement

For the purpose of the AHS, dietary supplements refer to products defined as Complementary Medicines under the Therapeutic Goods Regulations 1990 and that are not intended for inhalation or use on the skin. They include products containing ingredients that are nutrients, such as multivitamin or fish oil products.

Estimated Average Requirement (EAR)

The Estimated Average Requirement (EAR) is the daily nutrient level estimated to meet the requirements of half the healthy individuals in a particular life stage and gender group. EARs are available for the following nutrients: protein, vitamin A (as retinol equivalents), thiamin (B1), riboflavin (B2), niacin equivalents, vitamin B6, vitamin B12, folate equivalents, vitamin C, calcium, iodine, iron, magnesium, phosphorous, selenium and zinc. See Nutrient Reference Values for Australia and New Zealand.

Fat

Fat provides a significant amount of dietary energy and is also a carrier for fat-soluble vitamins and the source of essential fatty acids. It is the most energy dense of the macronutrients. The three fatty acid subtotals do not add up to total fat because total fat includes a contribution from the non-fatty acid components.o

Fatty acids

Fatty acids are units of carbon, hydrogen and oxygen which combine with glycerine to form fat. Most foods contain a mixture of monounsaturated, polyunsaturated and saturated fatty acids.

Fish and seafood products and dishes

The 'Fish and seafood products and dishes' food group includes fresh and tinned seafood, shellfish and mixed dishes with fish or seafood as the main component e.g. salmon mornay, fish curry and prawn cocktail.

Folate

In this publication, folate refers specifically to the naturally-occurring form of folate (tetrahydrofolate or THF).

Folate equivalents

Folate is a B group vitamin that is essential for healthy growth and development, which is important during pregnancy to help prevent the incidence of neural tube defects (such as spina bifida) in babies. Folate intake is measured in folate equivalents to take into account the higher bioavailability of folic acid (pteroyl glutamic acid, or PGA, the form used in food fortification and dietary supplements) than natural folate (tetrahydrofolate, or THF, the form found in foods and in the body). Folate equivalents = 1.67*folic acid + natural folate.

See folate.

Folic acid

Folic acid (pteroyl glutamic acid, or PGA) is the form of folate used in dietary supplements and for food fortification as it is more stable and bioavailable than the naturally-occurring forms in foods. As of September 2009, in Australia wheat flour for making bread is required to be fortified with folic acid, with the exception of wheat flour for making bread which is represented as organic. See Standard 2.2.1 of the FSANZ Food Standards Code.

Fortification

Fortification refers to adding vitamins and minerals to food. When there is determined to be a significant public health need, food manufacturers may be required to add certain vitamins or minerals to specified foods (mandatory fortification). In Australia, mandatory fortification of foods includes requirements for salt used in bread to be iodised, thiamin and folic acid to be added to wheat flour for making bread, and vitamin D added to edible oil spreads such as margarine. See Food Standards Australia New Zealand: Vitamins and minerals added to food.

Full probability method

The full probability method is a statistical method for finding the proportion of people within a group with inadequate intakes of a nutrient. It involves determining the probability that each observed usual intake of a nutrient will be below requirements for that nutrient. For a population group, the overall proportion of people within the group likely to be consuming inadequate intakes is calculated as the average probability of inadequacy. For more information, see the Beaton's full probability of method for iron chapter of the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

Iodine

Iodine is a mineral essential for the production of thyroid hormones, which are essential for normal growth and development, particularly of the brain. Since October 2009, regulations in Australia and New Zealand require that iodine is added to salt used for making bread (except organic bread and bread mixes for making bread at home). See Standard 2.2.1 of the FSANZ Food Standards Code.

Iron

Iron is a mineral essential for the oxygen carrying ability of red blood cells.

Linoleic acid

Linoleic acid is a particular type of omega 6 polyunsaturated fatty acid associated with blood lipid profiles seen as having a lower risk of coronary heart disease.

Long-chain omega 3 fatty acids

Long-chain omega 3 fatty acids are a particular type of omega 3 fatty acid (eicosapentaenoic acid, docosapentanoic acid, and docosahaexanoic acid) with cardiovascular and anti-inflammatory benefits.

Macronutrient

Macronutrients are nutrients that provide energy and raw materials for body tissues and processes. They include protein, fats, carbohydrates and alcohol.

Magnesium

Magnesium is a mineral involved in a number of body processes, as a cofactor for more than 300 enzyme systems.

Margin of Error (MoE)

Margin of Error (MoE) describes the distance from the population value that the sample estimate is likely to be within, 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 the entire population had been enumerated). In this publication, MoE has been provided at the 95% confidence level for proportions of persons and usual daily proportions of energy from macronutrients. For more information see the Technical Note of this publication.

Median

The median is the middle value in a set of observations. In this release, median usual intakes for each age and sex group are shown as the 50th percentile of the range of observations simulated by the NCI method.

Mean

The mean is the sum of the value of each observation in a dataset divided by the number of observations. This is also known as the arithmetic average. In this release, mean usual intakes for each age by sex group are calculated from the distribution of usual nutrient intakes simulated by the NCI method.

Meat, poultry and game products and dishes

The 'Meat, poultry and game products and dishes' food group includes beef, sheep, pork, poultry, sausages, processed meat (e.g. salami) and mixed dishes where meat or poultry is the major component e.g. casseroles, curried sausages and chicken stir-fry.

Milk products and dishes

The 'Milk products and dishes' food group includes milk, yoghurt, cream, cheese, custards, ice cream, milk shakes, smoothies and dishes where milk is the major component e.g. cheesecake, rice pudding and creme brulee.

Minerals

Minerals are inorganic elements which are essential nutrients required in small amounts from the diet for normal growth and metabolic processes.

Moisture

Moisture, as measured in the NNPAS, is the water from all food and beverage sources.

Monounsaturated fat

Monounsaturated fat or monounsaturated fatty acids are a type of fat predominantly found in plant-based foods, although there are exceptions.

National Health Measures Survey

The National Health Measures Survey, which is sometimes referred to as the biomedical component of the AHS, focused on early lifestyle-related diseases through blood and urine testing. Information was collected on:

• cardiovascular disease
• apolipoprotein B (Apo B)
• high-density lipoprotein (HDL) cholesterol
• low-density lipoproteins (LDL) cholesterol
• total cholesterol
• triglycerides

• diabetes
• fasting plasma glucose
• glycated haemoglobin (HbA1c)

• chronic kidney disease
• estimated glomerular filtration rate (eGFR)
• urinary albumin creatinine ratio (ACR)

• liver function
• alanine aminotransferase (ALT)
• gamma-glytamyl transferase (GGT)

• risk factors
• serum cotinine

• nutrition status
• haemoglobin (Hb)
• serum ferritin
• soluble transferrin receptor (sTfR)
• serum folate
• red cell folate (RCF)
• serum vitamin B12
• serum 25-hydroxyvitamin D [25(OH)D]
• urinary sodium
• urinary potassium
• urinary iodine.

Participants were those people aged five years and over, who were selected for either NHS or NNPAS and agreed to also participate in the NHMS. Children aged 5 to 11 were only asked to provide urine samples. For more information about the tests, see Biomedical Measures.

National Nutrition and Physical Activity Survey (NNPAS)

The National Nutrition and Physical Activity Survey focused on collecting information on:

• dietary behaviour and food avoidance (including 24-hour dietary recall)
• selected medical conditions that had lasted, or were expected to last, for six months or more
• cardiovascular and circulatory conditions
• diabetes and high sugar levels
• kidney disease

• blood pressure
• female life stages
• physical activity and sedentary behaviour (including eight-day pedometer component)
• use of tobacco
• physical measurements (height, weight and waist circumference).

NCI method

The NCI method is a mathematical statistical model developed by the National Cancer Institute of the USA. In this publication, the model has been used to estimate the distribution of long term or usual intakes for each age and sex group, using the two days of dietary intake data for all respondents in that age and sex group. For more information, see the Overview of the NCI Method chapter of the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

Niacin equivalents

Niacin intake requirements are expressed as niacin equivalents. 1 mg of niacin equivalents is equal to 1 mg of niacin or 60 mg of tryptophan. Niacin (vitamin B3) is a general term for nicotinic acid and nicotinamide. Tryptophan is an amino acid that is converted to nicotinamide. Niacin is involved in energy metabolism.

Nutrient

Nutrients are chemical substances provided by food that are used by the body to provide energy, structural materials, and biochemical cofactors to support the growth, maintenance, and repair of body tissues. Major sources of nutrients are available in AHS: Nutrition First Results - Foods and Nutrients (cat. no. 4364.0.55.007).

Nutrient Database

The Nutrient Database used to derive energy and nutrient estimates for the 24-hour dietary recall data was developed by Food Standards Australia New Zealand. See AUSNUT 2011-13.

Nutrient Reference Value (NRV)

The Nutrient Reference Values (NRVs) are a set of recommendations made by the National Health and Medical Research Council (NHMRC) and New Zealand Ministry of Health in 2006 for nutritional intake, based on currently available scientific knowledge. See Nutrient Reference Values for Australia and New Zealand.

Percentage contribution to energy intake

Percentage contribution to energy intake refers to the proportion of energy that a food or macronutrient contributes to each person's total energy intake. In the NNPAS, the energy from each macronutrient was estimated by multiplying each gram of a particular macronutrient by a conversion factor to determine the kilojoules of energy. For more information, see the Nutrient Intake chapter of the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001). For more information on the way in which percentage usual contribution to total energy intake has been calculated using the NCI method, see the Model implementation: data used and model specification chapter of the AHS: Users' Guide, 2011-13 (cat. no. 4363.0.55.001).

Phosphorus

Phosphorus is the second most abundant mineral in the body. It plays an important role in the formation of bones and teeth, protein production, and energy-producing activities in cells.

Polyunsaturated fat

Polyunsaturated fat or polyunsaturated fatty acids are a type of fat predominantly found in plant-based foods, although there are exceptions. Linoleic acid, alpha-linolenic acid, long-chain omega 3 fatty acids, and other polyunsaturated fatty acids are included in the polyunsaturated fatty acid total.

Potassium

Potassium is a mineral which is the major positive ion of fluid within cells and is found at close to constant levels in lean body tissues.

Preformed vitamin A

Preformed vitamin A, or retinol, is a form of vitamin A.

In this release, prevalence of inadequacy (from foods) for a particular nutrient is the estimate of persons who aren’t meeting their requirements for a nutrient. For all nutrients except iron, this is estimated in this publication as the proportion of persons with an intake below the EAR. For iron, this has been estimated using the full probability method. See Reporting Against Nutrient Reference Values in the User’s Guide for more details.

Pro vitamin A

Pro vitamin A is a form of vitamin A. Where information on levels of carotenes other than beta carotene in foods was available, this has been included in the pro vitamin A total as beta carotene equivalents, according to the equation pro vitamin A = beta carotene + 0.5*alpha carotene + 0.5*cryptoxanthin. This equation takes into account the differing biological activities of the different forms of pro vitamin A.

Protein

Protein supplies essential amino acids and is also a source of energy. Protein can be supplied from animal or vegetable matter, though individual vegetable proteins do not contain all the essential amino acids required by the body – they may be limited in one of these essential amino acids.

Relative Standard Error (RSE)

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

Riboflavin (vitamin B2)

Riboflavin is a B group vitamin important for converting other nutrients into bioactive forms.

Saturated fat

Saturated fat or saturated fatty acids are a type of fat predominantly found in animal-based foods, although there are exceptions. Saturated fat is the total of all saturated fatty acids, that is, all fatty acids without any double bonds.

Selenium

Selenium is a mineral that functions as an antioxidant and in thyroid metabolism.

Sodium

Sodium is a mineral which occurs in a number of different forms but is generally consumed as sodium chloride (commonly known as 'salt').

Starch

See carbohydrate.

Supplement

See dietary supplement.

Thiamin (vitamin B1)

Thiamin is a B group vitamin that helps the body convert food to energy for the brain, nervous system and muscles. In Australia, wheat flour for making bread is required to be fortified with thiamin. See Standard 2.2.1 of the FSANZ Food Standards Code.

Total fat

Total fat includes the fatty acids reported on in this release as well as some fats not separately reported on, such as non-fatty acid components of triglycerides, phospholipids, sterols and waxes.

Total sugars

Total sugars are the sum of fructose, glucose, sucrose, maltose, lactose and galactose. In the NNPAS, naturally occurring sugars cannot be differentiated from those that are added.

Trans fatty acids

Trans fatty acids are produced from hydrogenating unsaturated oils during food processing, and are naturally occurring in ruminant animal foods. The food composition data used for the 2011-13 AHS include both monounsaturated and polyunsaturated trans fats.

Under-reporting

Under-reporting refers to the tendency (bias) of respondents to underestimate their food intake in self-reported dietary surveys. It includes actual changes in foods eaten because people know they will be asked about them, and misrepresentation (deliberate, unconscious or accidental), for example to make their diets appear more ‘healthy’ or be quicker to report.

Upper Level of Intake (UL)

The Upper Level of Intake (UL) of a nutrient is the highest average daily intake level that is likely to pose no adverse health effects to almost all individuals in the general population. As intake increases above the UL, the potential risk of adverse effects increases. ULs are available for the following nutrients: calcium, iodine, iron, phosphorous, selenium, zinc, preformed vitamin A (retinol), folic acid, vitamin E, sodium, and long-chain omega 3 fatty acids. See Nutrient Reference Values for Australia and New Zealand.

Usual intakes

Usual intakes represent food and nutrient intake over a long period of time. For a single person, dietary intake varies day-to-day. A single 24-hour dietary recall does not represent the usual, or long term, intake of a person because of this variation. In the 2011-12 NNPAS, all respondents were asked for follow-up contact phone details in order to conduct a second 24-hour recall over the phone at least eight days later. A second 24-hour recall was collected from 64% of respondents. The second 24-hour recalls were used to estimate and remove within-person variation in order to derive a usual nutrient intake distribution for the population.

Vegetable products and dishes

The 'Vegetable products and dishes' food group includes vegetables and dishes where vegetables are the major component, for example salad or vegetable casserole.

Vitamins

Vitamins are organic compounds found naturally in food and are either fat or water soluble. They are required in small amounts. Vitamins enable the human body to function efficiently by regulating biochemical processes such as growth metabolism, cell reproduction, digestion, and oxidation of the blood.

Vitamin A retinol equivalents

Vitamin A is a fat soluble vitamin which helps maintain normal reproduction, vision, and immune function. Vitamin A intake is measured in retinol equivalents to reflect the contribution of pro vitamin A and preformed vitamin A, using the equation: vitamin A retinol equivalents = retinol + beta carotene/6 + alpha carotene/12 + cryptoxanthin/12. The equation takes into account the differing biological activities of the different forms of vitamin A.

Vitamin B6

Vitamin B6 is involved in the metabolism of amino acids, glycogen and sphingoid bases, where it functions as a coenzyme.

Vitamin B12

Vitamin B12, also known as cobalamin, has a key role in the normal functioning of the brain and nervous system, and the formation of blood.

Vitamin C

Vitamin C refers to compounds with antiscorbutic activity and antioxidant properties.

Vitamin E

Vitamin E refers to a group of compounds called tocopherols and tocotrienols. It prevents the oxidation of polyunsaturated fatty acids, acting as an antioxidant in the lipid phase of cell membranes.

Zinc

Zinc is a mineral required for the function of many enzymes and has a role in protein and DNA synthesis.

Abbreviations

Show all

The following symbols and abbreviations are used in this publication:

 ABS Australian Bureau of Statistics AHS Australian Health Survey AMDR Acceptable Macronutrient Distribution Range DNA deoxyribonucleic acid EAR Estimated Average Requirement FSANZ Food Standards Australia New Zealand mg milligram mg/kg bw/day milligram per kilogram of bodyweight per day g gram kJ kilojoule MoE Margin of Error NCI National Cancer Institute NHMRC National Health and Medical Research Council NHMS National Health Measures Survey NHS National Health Survey NNPAS National Nutrition and Physical Activity Survey NRV Nutrient Reference Value NTD neural tube defect RSE Relative Standard Error µg microgram UL Upper Level of Intake