A 24-hour dietary recall tool called Intake24 was the main source of dietary data from the National Nutrition and Physical Activity Survey (NNPAS) 2023 and the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023. Intake24 is an open-source self-completed computerised dietary recall system based on multiple-pass 24-hour recall. Intake24 was developed and validated by the University of Newcastle in the UK (Bradley et al. 2016; Foster et al. 2019) and adapted for Australia by Monash University (McCaffrey et al. 2025). It has been adapted for this study by the ABS in collaboration with Food Standards Australia New Zealand (FSANZ) and Monash University. 

In these surveys, it was used by interviewers during face-to-face interviews and by respondents as an online tool. The 24-hour dietary recall tool guided respondents to accurately report everything they ate and drank on the day before the interview, covering the full 24-hour period from midnight to midnight. Using a multiple pass approach, the tool navigated respondents through a step-by-step review of their day, enhancing recall and enabling prompts for commonly forgotten foods and drinks (e.g. snacks and water).

Respondents first recorded what was consumed:

• the time they ate or drank
• the name of the meal (e.g. breakfast, lunch)
• what they consumed, typed into separate fields (called “search terms”).

This was done for each meal. To help, default meal names and times were provided.

Intake24 then showed a list of possible foods based on what the respondent typed. They chose the closest match or refined their search term. They could report sandwiches and salads using predefined components (e.g. bread, spread, fillings). If a food wasn’t listed, they could report it as missing. Respondents then estimated how much they consumed using images of food and standard measures. Further detail can be found in Portion selection methods.

Intake24 used follow up questions for foods often eaten together. For example, “Did you have any butter or margarine with your bread?”. Before finishing, it checked for missing items and asked if:

• any drinks were consumed with a meal (if none were reported)
• any snacks were consumed throughout the day
• there were any other food or drink that hadn’t yet been mentioned.

There are more than 3,500 food and beverage items used in the study, including:

• individual food ingredients (e.g. flours, oils, fruits and vegetables)
• mixed dishes (e.g. spaghetti Bolognese, ham and cheese sandwich).

The food and portion files include foods eaten traditionally by Aboriginal and Torres Strait Islander peoples (sometimes called “traditional foods” or “bush tucker”). The ABS consulted with Aboriginal and Torres Strait Islander peoples and nutrition experts to include traditional foods commonly consumed in Australia. Some examples of these foods include kangaroo, wild-caught pig, dugong, turtle, wallaby, quandong, bush tomato and yams.

To help respondents estimate how much food and drink they had, Intake24 uses four main methods. These methods link to a portion weight estimate in grams.

1. Standard portions and measures

These are everyday sizes or amounts, like:

• a medium chicken drumstick
• a thick slice of bread
• a small packet of chips/crisps
• cups of cooked rice
• teaspoons of coffee powder.

Respondents chose the measure type and quantity (e.g. 2 thick slices of bread). They could adjust using fractions or multiples. All standard measures have weight estimates provided by FSANZ, which can be found in the AUSNUT 2023 - Food measures file on the FSANZ website.

2. Guide Images

There are images in Intake24 showing different sizes of similar foods or beverages. For example:

• soft drink cans and bottles
• yoghurt tubs and packets
• meats (e.g. chicken schnitzel).

Respondents picked the image that matched what they had and then indicated how many. These images helped with reporting foods and drinks like chocolate, fruits, meats, bottled drinks and snacks. Portion weights are available in the AUSNUT 2023 - Food measures file on the FSANZ website.

3. As-served images

The Intake24 images presented 5 to 7 images of food on a plate or in a bowl, with increasing amounts. Respondents chose the image that looked closest to what they ate. If they had more or less than the images show, they could adjust using fractions or multiples.

Note: Individual portion sizes for as-served images are not included in the AUSNUT food measures file, only the densities to allow the conversion into gram amounts are included.

4. Drink-scale

After choosing the drink container (e.g. mug or takeaway cup), respondents used an on-screen slider to indicate how full it was. Default fill levels were used. Intake24 calculates the portion amount based on the fill level and cup size.

Note: Individual portion sizes are not included in the AUSNUT food measures file, only the densities to allow the conversion into gram amounts are included.

Each food item within Intake24 had a unique food ID that connected it to the AUSNUT 2023 food and dietary supplement classification system. This includes an 8-digit survey ID and groupings into broader 5-, 3- and 2- digit category classifications. In some instances, multiple foods in Intake24 align to a single AUSNUT food if a food item is known by several names, but the food composition is the same or similar. Fifty-two “not further defined” codes were included for use in recipe creation, or when insufficient detail was provided in the survey. In addition, foods have been identified as discretionary or non-discretionary according to the Australian Dietary Guidelines (ADG). See Discretionary Foods for more information.

AUSNUT 2023 provides detailed profiles for foods and ingredients with the amount of energy, nutrients, vitamins, minerals, and ADG food group serves they contain per 100 grams. To calculate what each person consumed some portion sizes from Intake24 were first adjusted using a conversion factor (also called a density factor). The nutrients and food group values were then multiplied by the amount eaten per food, and totals summed for each recall day.

Further information on portion conversion factors and ADG food groups is available in the AUSNUT 2023 files on the FSANZ website, and a full list of available data is in the NNPAS Data Item List and the NATSINPAS Data Item List.

To make sure the food data from the recall were accurate and complete, four types of checks were done:

1. Missing foods 

Sometimes, respondents couldn’t find the exact food they ate. In these cases, they described the food in detail (e.g. brand, ingredients, how it was prepared and amount consumed). ABS and FSANZ reviewed this information and either:

• matched to an existing AUSNUT food, or
• created a new food item and associated profile within AUSNUT. 

Fifty-five new food items were added to AUSNUT through this process. Portion weights were assigned based on the respondent’s information and input from FSANZ.

2. Orphan foods 

'Orphan foods' that are usually eaten with something else (e.g. instant coffee powder with water), or were only partially entered (e.g., someone searched for “chips and gravy” but only added “chips”). Recalls were reviewed for possible orphan foods.

If identified, one of two options were applied:

1. the missing food items were added (e.g. add gravy to the meal).
2. the food was recoded to a more complete option (e.g. instant coffee made with water). 

Portions were imputed for these foods using the median or mode amount reported for the food (with consideration of age group and sex), or a standard measure (available in the FSANZ food measures file). 

3. Search term mismatches

Sometimes the food selected didn’t match the search term. For example, respondents may have:

• searched for “potato bake” and selected “roast potato”
• searched for “curry puffs” and selected “beef curry powder”.

Recalls were reviewed for possible search term mismatches. If identified, they were corrected using:

• the original search term
• portion size method
• other foods in the meal
• subsequent recalls or recalls of other people in the house.

4. No food or drink reported

In a few rare instances, a single line was reported in Intake24 with a comment provided (e.g. “no food or drink”). It is expected that some people may not consume food and drink in a single day, for example, if they are unwell, preparing for surgery or fasting. These records were retained and there was no exclusion criteria based on number of foods and eating occasions reported. 

After all dietary data were collected, the data were reviewed to check for errors and improve accuracy.

Recalls were reviewed by checking against: 

• age, sex, estimated basal metabolic rate and body size
• how the respondents reported across their recall (and subsequent recalls)
• whether the food made up a large proportion of their total intake
• how others respondents reported the same or similar foods
• whether foods existed in the market with those weights
• past survey data.

Ready meal and takeaway food data were checked against FSANZ data and readily available information from outlets in Australia.

Some examples of issues found include unusually high or low portion sizes (e.g. 2 kg pineapple, 20 L of water) and extremely high nutrient amounts (e.g. high amounts of calcium due to incorrect reporting of “milk powder” rather than “milk made from powder”). 

Fixes to portion weights included:

• winsorising extreme values
• applying scaling factors
• recoding to a standard measure.

Bradley J, Simpson E, Poliakov I, Matthews JN, Olivier P, Adamson AJ, Foster E (2016) Comparison of INTAKE24 (an Online 24-h Dietary Recall Tool) with Interviewer-Led 24-h Recall in 11-24 Year-Old, Nutrients, 8(6):358, accessed 25/07/2025.

Foster E, Lee C, Imamura F, Hollidge SE, Westgate KL, Venables MC, Poliakov I, Rowland MK, Osadchiy T, Bradley JC, Simpson EL, Adamson AJ, Olivier P, Wareham N, Forouhi NG, Brage S (2019), Validity and reliability of an online self-report 24-h dietary recall method (Intake24): a doubly labelled water study and repeated-measures analysis, Journal of Nutritional Science, 30(8):e29, accessed 25/07/2025.

McCaffrey T, Foster E, Ng, H, Ivaturi A, Abdulgalimov D, Poliakov I, Rowland M, Barklamb A, Legrand S, Prawira C, Olivier P (2025), Intake24-AUS Food List, Monash University, accessed 25/07/2025.

Dietary supplements were collected as part of the short questionnaire after the Intake24 dietary recall was completed. Respondents were asked to include all supplements consumed in the 24 hours prior to interview and prompted to select up to 15 supplements from a coder list. The list was extracted from the Australian Register of Therapeutic Goods (ARTG) and included around 18,000 listed medications. 

In this survey, dietary supplements included:

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

If respondents were unable to find their specific supplements from the provided list (for example, the supplement was new to the market), they could provide a text response. Respondents were encouraged to provide as much details as possible on the supplement, including the registration (AUST-L) number, name, brand and strength. 

Once they had reported the type of supplement, respondents were prompted for more information, including:

• dosage type (e.g. tablet, powder)
• how it was consumed (e.g. tablespoons, tablets)
• the number or amount consumed
• whether the spoon was heaped or level.

The AUSNUT supplement file contains 1,350 supplements listed by registration number and dosage type. Survey data were linked using registration number and dosage type. The registration number replaces the 8-digit code in the AUSNUT files that are provided for food and beverages. Dietary supplements were classified into sub-groups within AUSNUT 2023. Further information can be found in the AUSNUT files available on the FSANZ website.

Where a registration number was not available (for example, the response was “Vitamin D tablet” and brand/further information was not provided), the data were linked to a ‘not further defined’ category. These were used to capture similar supplements that were unable to be coded to a specific supplement. For example, ‘Dietary supplement, Vitamin D supplements, not further defined’ captures Vitamin D supplements with different strengths and brands. “Not further defined” codes were included for use in recipe creation, or when insufficient detail was provided in the survey. Forty-two individual “not further defined” codes were included for supplements (specific to dosage type).

Each supplement has a corresponding nutrient profile, calculated per dosage unit (e.g. nutrients per tablet). Some dosage units (e.g. drops, sips, tablespoons, teaspoons) were converted to a standard measure (e.g. grams, millilitres). For heaped teaspoons and tablespoons, an additional factor of 1.5 was applied to the standard measure. The nutrients per dosage unit were then multiplied by the number of doses consumed, and total nutrient intakes from dietary supplements summed for each recall day. 

Further information including details of Foods and Supplements consumed are available in the NNPAS Data Item List and the NATSINPAS Data Item List.

Data on dietary supplements collected in the National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) 2022–23 was mapped to the AUSNUT 2011–13 food and dietary supplement classification, as AUSNUT 2023 was not available at the time of publication.

Data were checked for consistency and completeness. Specific amendments included: 

• coding free text entries to a registration number (based on description)
• checking and recoding mismatches between reported and registered AUST-L administration route
• removal of registered medications and foods
• checking for improbable or impossible supplement amounts. 

Supplements were recoded if the reported consumption route (i.e., how they took the supplement) did not align with the registered ARTG consumption route. For example, if the respondent reported consuming the supplement as a powder, but the selected product was a tablet, the supplement was recoded to the registration number for the powder version of the product. 

Some respondents reported supplements as part of the dietary recall in Intake24 (usually reported as a missing food). These supplements were removed as foods and added to the dietary supplement dataset during processing.

AUSNUT 2023 was developed by Food Standards Australia New Zealand (FSANZ) to help turn information about foods and dietary supplements reported as consumed in the National Nutrition and Physical Activity Survey (NNPAS) 2023 and the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023 into estimates of food and dietary supplement consumption amounts and nutrient intakes. It also contains information to help users interpret the data and compare data with previous surveys. 

More information about AUSNUT 2023 is available on the FSANZ website. Each AUSNUT publication is specific to the survey and reflects the products available and consumed at the time. See Comparing food and nutrient collections over time for more information.

Food and dietary supplement consumption patterns can be described using several approaches. Data in AUSNUT 2023 was classified by the:

• food and dietary supplement classification
• Australian Dietary Guidelines (ADG) food group classification
• discretionary food flag.

These classification systems were adapted from those used in the Australian Health Survey (AHS) 2011–13 and the National Nutrition Survey 1995. The main aims of the AUSNUT 2023 were to:

• enable reporting of trends in food and supplement consumption and nutrient intake
• reflect the current food supply but allow room for changes in the food supply
• enable food, discretionary status and nutrient intake data to be reported by food group
• provide flexibility and access to detail for users with different research or reporting objectives.

There are many ways that foods and dietary supplements can be classified, and no single classification system will meet the needs of all users. The AUSNUT 2023 system was designed to meet the requirements of the 2023 study. Users who wish to reclassify the foods and supplements by different parameters will be able to access unit record file data in the DataLab later in 2025.

The AUSNUT food and dietary supplement classification system is tiered, with a unique code assigned to each individual food and dietary supplement. For foods, the first 2 digits denote a major food group, the first 3 digits a sub-major group, and the first 5 digits a minor group. There are 24 major groups used in the Intergenerational Health and Mental Health Study (IHMHS) comprising:

• 23 food groups: 128 sub-major groups, 477 minor groups and 3,741 individual food codes
• 1 dietary supplement group: 6 sub-major groups, 56 minor groups, and 1,350 individual supplement codes.

Note: The number of sub-major and minor groups may differ from the full AUSNUT 2023 classification. Some AUSNUT groups were suppressed in the ABS publications due to no responses being reported in either the NNPAS 2023 or the NATSINPAS 2023. 

Examples of food groups are shown in the table below. See Food consumption by AUSNUT food groups for information about interpreting these categories within ABS data. The full classification is available in the NNPAS Data Item List, the NATSINPAS Data Item List, and on the FSANZ website.

The Australian Dietary Guideline (ADG) classification system used in the NNPAS 2023 and NATSINPAS 2023 was adapted from the 2011–13 classification used in the AHS 2011–13. 

The ADG food groups are classified at 3 levels which include Major Food Groups (2-digit), Sub-groups (3-digit) and the Servings Sub-groups (4-digit), with the serving size used for each (e.g. 1 serve of vegetables is 75 g). The major food group categories are: 

• Grain (cereal) foods
• Vegetables and legumes/beans
• Fruit
• Milk, yoghurt, cheese and/or alternatives
• Meat, poultry, fish, eggs, tofu, nuts and seeds, and legumes, beans, and tofu
• Water
• Unsaturated spreads and oils
• Recipe
• Unclassified.

Examples of these food groups are shown in the table below. See Australian Dietary Guideline (ADG) food groups for information about interpreting these categories within ABS data. The full classification is available in the NNPAS Data Item List and the NATSINPAS Data Item List.

Food nutrient profiles

The food nutrient profiles contain information on the nutrient content of each 8-digit food and beverage. The file contains 58 nutrient items for each food including energy with and without dietary fibre, macronutrients, vitamins, minerals and other food components. Each nutrient value is presented on a per 100 g edible portion basis and merged to the NNPAS or NATSINPAS survey files to derive nutrient intake estimates per portion size and per day.

Food details

The food details file includes non-nutrient information about each 8-digit food, including IDs, a description, classifications, details about how the nutrient profile was created by FSANZ (e.g. from a recipe, analysed, borrowed), and other factors that fed into creating the nutrient profile and ADG recipe data where relevant.

Food measures

The food measures file lists standard portions and measures used in the 2023 study. This includes gram amounts, volumes, and densities. This file was used within the Intake24 tool, as well as to support data processing work. Some measures in the study, for example food served on a plate, were directly assigned a gram weight in Intake24, and are not included in this file. See the FSANZ website for more details regarding food densities.

Food nutrient recipes

The food nutrient recipes contain ingredients used to create mixed dish recipes in Intake24, and the weights assigned to ingredients used within the recipe. The foods collected in the study are often presented to respondents in Intake24 as made-up or “mixed dishes” with individual components considered. The file outlines the assumptions made in creating a nutrient profile for these mixed dishes.

Recipes may use “not further defined” foods - these nutrient profiles were created by FSANZ based on a weighted average of multiple products within the food type (usually defined by proportion of retail sales, or in the case of oils and fats in cooking, based on short answer survey responses, see Oils and fats).

For example, a “Sandwich or roll, ham & cheese” dish contains:

• Bread, commercial, not further defined
• Fat, butter, dairy blend, or margarine spread, not further defined
• Ham, leg, lean
• Cheese, for use on sandwiches, not further defined.

Data is published by the ABS in its reported state. Researchers will be able to link ingredient information to survey data in Datalab later in 2025.

Australian Dietary Guideline profiles and recipes

The ADG profiles contain information on the ADG food group content of each 8-digit food and beverage. The file contains the amount in grams and serves for 79 food subgroups. Each food group value is presented as a gram amount and serve amount on a per 100 g edible portion basis.

The Australian Dietary Guideline recipes file lists any weight change factors applied to ingredients when calculating the ADG profiles for mixed dish recipes. These consider things like cooking and other preparation methods. For example, a weight change factor is applied to a “Sandwich or roll, ham & cheese, toasted” when creating the ADG profile, but this factor is not applied to the untoasted version.  

For further information about the ADGs, see Australian Dietary Guidelines (ADG) food groups.

Dietary supplement nutrient profiles

The dietary supplement nutrient profiles contain information on the nutrient content of each dietary supplement. The file contains 39 nutrient items for each supplement including macronutrients, vitamins, minerals and other components. Each nutrient value is presented on a per dose unit basis and merged to the NNPAS 2023 and NATSINPAS 2023 files to derive estimates per dosage and per day.

Dietary supplement details

The dietary supplement details file lists all supplements with a nutrient profile created by FSANZ, its ID, name, dose unit (e.g. tablet, film coated), and classification code. The file was used to classify supplements from their registration number to the food and dietary supplement classification. 

Dietary supplement recipes and ingredient profiles

The dietary supplement recipes detail ingredients used to create supplement nutrient profiles for the study, and the ingredient amounts. For example, one type of magnesium supplement contains:

• Magnesium amino acid chelates
• Magnesium oxide – heavy
• Manganese amino acid chelates
• Pyridoxine hydrochloride.

This file also includes an estimated formulation when items were unable to be coded to a specific registration code and were assigned a “not further defined” profile (e.g. Dietary supplement, multivitamin and/or multimineral, not further defined). The dietary supplement ingredient profiles contain information on the nutrient content of each ingredient used in the dietary supplement recipes. Data is published by the ABS in its reported state. Researchers will be able to link ingredient information to survey data in the Datalab later in 2025.

Food consumption patterns can be described using several approaches to data analysis that provide different types of information, the use of which will depend on the purpose of the dietary assessment. In the food and nutrients publication, food consumption patterns are presented by the AUSNUT food and supplement classification at the major and sub-major food group level (details of consumption at more detailed levels are available upon request and will be available in the DataLab later in 2025).

The major, sub-major, and minor food groups included in the food and dietary supplement classification are used to organise food consumption data in dietary surveys (see AUSNUT 2023 classification files). These classifications help identify where nutrients, discretionary foods and Australian Dietary Guideline (ADG) food groups are primarily consumed. 

For example, cross classifying nutrient intakes with AUSNUT food groups allows researchers to determine which of these food groups contribute most to specific nutrient intake estimates. Similarly, mapping of the AUSNUT food groups– such as ‘402 Medium fat (MF) dairy foods (4-10%) fat’ – to the ADG milk, yoghurt, cheese and/or alternatives group helps clarify which foods and AUSNUT food groups contribute to milk consumption patterns within an ADG food groups analysis.

When interpreting food, beverage and supplement consumption by AUSNUT food group, it is important to consider that the same ingredients can be found in different foods across various groups. So, the reported intake by major or sub-major food group might not show the total amount of each ingredient (e.g. milk) from all sources.

The methods used in the 2023 study are similar to those used in the National Nutrition Survey 1995 and the Australian Health Survey 2011-13. Food supply and consumption patterns change over time, and the food classification system is updated with each survey to include new foods or beverages. Each AUSNUT publication by FSANZ is specific to the corresponding survey and reflects the products available and consumed at the time. See Comparing food and nutrient collections over time for more information. A concordance of AUSNUT 2011–13 to 2023 is available on the FSANZ website.

Most people eat a moderate amount of a food, but a few eat a lot, resulting in skewed data. Most food consumption data are right hand skewed (positively skewed). The distribution of food consumption for the population (including consumers and non-consumers) will be different from the one for the people who eat the food (consumers), unless everyone consumes that food. To compare how much food Australians eat, it is measured in two ways using both the mean and median.

Mean (average) food intake (both consumers and non-consumers)

• This is the average amount of food eaten by everyone in a group, including the people who didn’t eat any
• It’s useful when comparing how much food different population groups eat each day
• It’s more affected by people who eat large amounts of food than the median for that population
• Values for mean consumption can be aggregated to see totals for larger food groups (e.g. all non-alcoholic beverages).

Median food intake (consumers only)

• This is the middle value or amount eaten by only the people who reported consuming the food or from a food group
• It shows what a “typical” eater of that food or food group consumed
• It’s best used when looking at specific food groups (like a certain type of fruit)
• It’s less affected by people who eat large amounts of food than the mean for that population
• It may be influenced by portion selection methods
• Median values cannot be added up across different foods or food groups, because the number of consumers of each one may be different, so they refer to different populations.

In the National Nutrition and Physical Activity Survey (NNPAS) 2023 and the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023, all recorded food and beverage amounts were converted to grams to enable nutrient value calculations. To support this, FSANZ developed a Food Measures file, which standardises the conversion of various portion types into gram weights. For beverages, volumes were converted to grams by multiplying by their density (g/ml). Both gram weight and volume are available on the survey files. See Food and beverage recall for more information about food measure and coding.

To estimate the consumption of sweetened beverages by volume, gram weights for drinks reported in powdered form or as undiluted cordial were converted to volumes using a hydration factor, representing the proportion of water typically added during preparation. Detailed guidance on replicating this process can be obtained from the ABS on request (health@abs.gov.au).

Alcoholic beverages were collected as part of the dietary recall and covered beer, wine, spirits, ciders & perry, and other alcoholic beverages like pre-mixed drinks and liqueurs. In 2023, a new category was added for dealcoholized beverages. Although these drinks contain little or no alcohol, they are still classified within the alcoholic beverage group due to similar consumption patterns and product characteristics.

Alcohol consumption tends to vary by day of the week with higher intake typically occurring on weekends. As the 24-hour recall captures only a single day, this can introduce bias in estimating alcohol intake. To account for this, the survey methodology includes data on the proportion of interviews conducted on each day of week. This should be considered when analysing alcohol consumption estimates. 

More comprehensive data on usual alcohol intake is available through the National Health Survey (NHS) 2022 and National Aboriginal and Torres Strait Islander Health Survey (NATSIHS) 2022–23.

Alcoholic beverages are the main source of estimated pure alcohol intake. See Food and nutrients in NNPAS 2023 and Energy and macronutrient intake in NATSINPAS 2023 for more information.

There are two main types of fruit and vegetable drinks: 

• 100% Fruit and vegetable juices – these only contain juice, typically with no added sugar or preservatives
• Fruit and vegetable drinks – these have less actual juice, and often include added ingredients like water, flavours and sweeteners.

According to the 2013 ADG, 100% juice can occasionally count as one serve of fruit (½ cup or 125 mL); however, fruit juice drinks with added sugar should be limited. Because of the difference, the AUSNUT 2023 classification now separates fruit and vegetable drinks to their own sub-major category instead of grouping them with 100% juice. 

People may confuse the two types of drink when reporting, which can affect data accuracy. While estimates from 24-hour-recall records may not give the best picture of consumption, the Apparent Consumption of Selected Food Stuffs, based on the AUSNUT 2011–13 classification, can provide reliable sales estimates. 

Nutrient intakes are derived from amounts of food, beverage and/or supplement reported as consumed in the study using the AUSNUT 2023 files. Nutrient intakes are reported to enable:

• comparison against Nutrient Reference Values (NRVs), the 2013 Australian Dietary Guidelines (ADG), national alcohol drinking guidelines
• monitoring of the mandatory addition of nutrients to food in Australia under the Australia New Zealand Food Standards Code
• comparison to previous national nutrition surveys (where feasible).

To promote meaningful comparisons with NRVs and the ADG, dietary intakes of nutrients are only reported where the food or supplement is the major source and available information is of sufficient quality on amounts of the nutrient in foods. 

Information on nutrient intakes from food and dietary supplements is available for the nutrients listed in the Nutrients table on the Downloads page.

One aspect of nutrient intake is that of a person's macronutrient intake compared to their total daily energy intake referred to as “Macronutrient balance” (NHMRC 2006). Unlike the micronutrients, macronutrients (proteins, fats and carbohydrates) all contribute to dietary energy intake. Alcohol can also contribute to dietary energy. The acceptable macronutrient distribution range (AMDR) represents the range of intake for each macronutrient, expressed as a percentage of total energy, that is associated with reduced risk of chronic disease and adequate intake of other essential nutrients.

The proportion of total energy contributed by macronutrients can be compared to the AMDRs. To compare survey results to established AMDRs, the percentage contribution to total energy from each macronutrient was calculated using standard energy conversion factors, see table below. Dietary supplements were assumed to contain zero energy and were excluded from the calculations.

Some respondents may not have consumed any foods or beverages during the recall period, or that the foods and beverages they did consume were calculated to contain zero kilojoules of energy. Respondents with an energy intake of zero kilojoules on day the prior to interview (Day 1) were retained in totals for macronutrient contributions. For these respondents, macronutrient contributions were set to 0.

Basal metabolic rates (BMR) are the amount of energy needed for a minimal set of functions necessary for life over a defined period. They are sufficient only for the functioning of the vital organs such as the heart, lungs, nervous system, kidneys, liver, intestine, sex organs, muscles, and skin. 

A BMR was calculated for each respondent and expressed as kilojoules (kJ) per 24 hours using age, sex, weight (kg) and height (cm). There was no adjustment for activity levels or health status. Where measured weight or height was not available from a respondent, this was estimated using imputation in both surveys. This is a change to the study since 2011–13 and should be considered when interpreting BMR results over time. Further information about the imputation process is available under Physical Measures in each survey’s methodology.

The ratio of energy intake to basal metabolic rate (EI:BMR ratio) is used for determining low energy reporting in people aged 10 years or over. For more information on the use of this ratio see Under-reporting of energy intakes, the NNPAS 2023 methodology and the NATSINPAS 2023 methodology.

The formulae used to estimate BMR for different population groups are given below (Mifflin-St Jeor 1990). This is a change to the study since 2011–13, which used the Schofield equation method (Schofield 1985), and excluded measured height (cm). This change should be considered when interpreting BMR results over time. A comparison of mean BMR using each method is shown below by age, sex and body mass index.

This is a common issue in dietary recall studies and can include actual changes in foods eaten because people know they will be participating in the survey, or misrepresentation (deliberate, unconscious or accidental), e.g. to make their diets appear healthier or be quicker to report. 

It is important to distinguish between respondent error and genuine behavioural influences. Real-world factors that may affect energy intake include:

• household food insecurity, which can limit access to food and certain food types.
• individual dieting behaviours, such as fasting or dieting.
• seasonal and daily variation in eating habits.
• changes in food composition over time, such as increased consumption of sugar- and fat-reduced products.

A common method for identifying under-reporting of energy intakes is to compare each person's reported energy intake (EI) with their estimated basal metabolic rate (BMR). The ratio of energy to basal metabolic rate (EI:BMR) provides an indication of whether the reported intake is sufficient to live a normal lifestyle (i.e. not bed-bound). There was no adjustment for activity levels or health status.  

The Goldberg cut-off method (Goldberg et al. 1991) is widely used to classify individuals as either:

• Low Energy Reporters (LER) – those with an EI:BMR ratio less than 0.9, meaning their reported intake is less than 90% of their estimated daily resting energy requirements.
• Adequate Energy Reporters (AER) – those with an EI:BMR ratio of 0.9 or higher.

An EI:BMR of less than 0.9 may indicate under-reporting due to social desirability bias, but it can also reflect situational factors such as intentional dieting, fasting, and natural day-to-day variation in food consumption. Estimates of low-energy reporters by selected characteristics are provided in the Under-reporting section of each survey’s methodology.

Energy and some nutrients may be derived from several nutrient components. Within tables, both totals (or equivalents) and nutrient components are presented; however, not all components may be reported.  Totals may not be summed from their components if not all components are reported separately, or the data is averaged. For example, in Table 1 ‘Daily Energy and nutrients from food and beverages, by age and sex’, energy from macronutrients components will not sum to total energy, and the components of fat, polyunsaturated fat, carbohydrate and total sugars do not sum to their respective total. This is due to:

• Total energy: This will be greater than the sum of the macronutrient components (protein, fat, carbohydrate, dietary fibre and alcohol) because total energy accounts for the small amount of energy from organic acids that are not considered carbohydrates.
• Total fat: This includes other forms of fat such as non-fatty acid components of triglycerides, phospholipids, sterols and waxes.
• Total carbohydrate: This includes sugar alcohols, organic acids and other available carbohydrates in addition to sugars and starch.
• Polyunsaturated fat: This includes polyunsaturated fatty acids not included in the values for linoleic acid, alpha- linolenic acid, and total long chain omega 3 fatty acids.

Absolute (total) micronutrient intakes are mainly influenced by the amount of food and drink consumed, and hence energy intake. It is also useful to consider energy-adjusted micronutrient intakes, which are expressed as a nutrient amount per 1,000 kJ of energy. This helps control for factors like age, sex, bodyweight and physical activity that influence energy requirements, and focuses instead on dietary composition.

Some respondents may not have consumed any food or beverages during the recall period, or that the foods and beverages they did consume were calculated to contain zero kilojoules of energy. Respondents with an energy intake of zero kilojoules on day the prior to interview (Day 1) were retained in totals for energy-adjusted intakes. For these respondents, energy-adjusted intakes for all micronutrients were set to 0.

For more information about how each of the nutrients available in AUSNUT nutrient profiles for foods and dietary supplements are derived (and their respective components), visit the FSANZ website.

Assessment of dietary nutrient intakes derived from food recall data are limited by measurement error, and these should be considered. These include:

• Recall bias: Respondents may forget or misreport what they ate, leading to under- or over- estimation.
• Standard measures: Portion weights assigned based on standard food sizes (e.g. medium apple) are calculated based on food analysis and may not reflect the actual size of the foods consumed by the respondents.
• Nutrient profiles: Nutrient profiles are based on food analysis of sampled products, or derivation from the nutrient content of ingredients, and may not reflect the food composition of the foods consumed by the respondents.

During development of the dietary recall, and AUSNUT food measures list, quality assurance was undertaken to ensure gram weights were realistic and reflect the current food supply. Further research has been published on the Intake24 dietary recall tool and the error associated with estimating portion weights compared to other dietary recall tools (Whitton et al. 2024) and assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water (Foster et al. 2016). Information about how standard measures and nutrient profiles were developed is available on the FSANZ website.

Iodine and sodium intakes

Iodine and sodium intakes may be impacted by the methods used to collect data on added salt in the study. See Discretionary salt for more information.

Fat intakes

Fat intakes may be impacted by the methods used to derive the fat nutrient profiles for home prepared meals. See Oils and fats for more information.

Pure alcohol

Alcohol reported as a nutrient refers to pure alcohol or ethanol. Estimates of alcohol intake are calculated for alcoholic beverages and foods that contain small amounts due to ingredients. Examples include:

• beer, wine, cider
• cakes
• dressings and condiments (e.g. soy sauce)
• stir-fries
• liqueur filled chocolate.

The primary contributor to pure alcohol estimates comes from alcoholic beverages. See Alcoholic beverages for information about collection of alcoholic beverages consumption.

National Health and Medical Research Council (NHMRC) (2006), Nutrient Reference Values: Macronutrient balance, Eat for Health website, accessed 25/07/2025.

Foster E, Lee C, Imamura F, Hollidge SE, Westgate KL, Venables MC, Poliakov I, Rowland MK, Osadchiy T, Bradley JC, Simpson EL, Adamson AJ, Olivier P, Wareham N, Forouhi NG, Brage S (2019), Validity and reliability of an online self-report 24-h dietary recall method (Intake24): a doubly labelled water study and repeated-measures analysis, Journal of Nutritional Science, 30(8):e29, accessed 25/07/2025.

Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, WA, & Prentice, AM (1991), Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording, European Journal of Clinical Nutrition, 45(12):569-581, accessed 25/07/2025.

Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO (1990), A new predictive equation for resting energy expenditure in healthy individuals, The American Journal of Clinical Nutrition, 51(2):241-247, accessed 25/07/2025.

Schofield WN (1985), Predicting basal metabolic rate, new standards and review of previous work, Human Nutrition: Clinical Nutrition, 39(1):5-41, accessed 25/07/2025.

Whitton C, Collins CE, Mullan BA, Rollo ME, Dhaliwal SS, Norman R, Boushey CL, Delp EJ, Zhu F, McCaffrey TA, Kirkpatrick SI, Pollard CM, Healy JD, Hassan A, Garg S, Atyeo P, Mukhtar SA, Kerr DA (2024), Accuracy of energy and nutrient intake estimation versus observed intake using 4 technology-assisted dietary assessment methods: a randomized crossover feeding study, The American Journal of Clinical Nutrition, 120(1):196-210, accessed 25/07/2025.

The 2013 Australian Dietary Guidelines (ADG) and the Australian Guide to Heathy Eating offer comprehensive advice on the types and amounts of food needed for optimal health and wellbeing (Eat for Health 2013: NHMRC 2013a).  One of the key recommendations, Guideline 3, advises Australians to ‘Limit intake of foods containing saturated fats, added salt, added sugars and alcohol.’ Foods that fall under this category are referred to as discretionary foods.

Discretionary foods are described as “foods and drinks not necessary to provide the nutrients the body needs, but that may add variety. However, many of these are high in saturated fats, sugars, salt and/or alcohol, and are therefore described as energy dense. They can be included sometimes in small amounts by those who are physically active, but are not a necessary part of the diet” (NHMRC 2013a).

The Educators Guide to Eat for Health further explains that discretionary foods can enhance the enjoyment of eating, especially during social, family or cultural events. However, it emphasises the importance of portion control and treating these foods as occasional extras, particularly in the context of energy requirements and healthy eating patterns (NHMRC 2013b).

The ADG recommend replacing discretionary foods with healthier alternatives from the same food group, those with lower saturated fats, sugar and salt content, and to limit alcohol intake (NHMRC 2013a). 

To monitor consumption patterns, a discretionary food flag was applied to foods reported as consumed in the study. This flag identifies foods that match the discretionary food definitions for different food types outlined in the 2013 ADG (Eat for Health 2013; NHMRC 2013a, 2013b).

The discretionary food flag was assigned at the 8-digit AUSNUT 2023 code level based on the following principles.

Non-discretionary foods

• Food groups clearly classified within the ADG food groups (e.g. fruit, vegetables), were flagged as non-discretionary.

Discretionary foods

• Entire AUSNUT food groups (major, sub-major or minor) identified as discretionary in the 2013 ADG (e.g. alcoholic drinks, confectionery) were flagged as discretionary.

Mixed foods

• For foods with mixed ingredients (e.g. burgers, soups, dips, pizzas, dairy desserts, dairy alternatives and products), nutrient profile criteria for fat, total sugars, sodium and/or calcium content were applied at the 8-digit AUSNUT level to determine discretionary status.
• Nutrient criteria application: All relevant foods were assessed using updated AUSNUT 2023 nutrient profiles, including both homemade and commercial versions, unless otherwise specified.
• Expanded saturated fat criterion: Previously limited to certain foods in the Cereal-based foods and products category in AUSNUT 2011–13, this criterion was extended to similar mixed foods at the 8-digit level for consistency in AUSNUT 2023. Trans fat was also added to the criterion, as noted below.

Oil content consideration

• Mixed foods composed solely of the five foods group ingredients and small amounts of unsaturated or monounsaturated oils were considered non-discretionary.

Discretionary status was determined using the following nutrient content criteria. Foods meeting these criteria were flagged as discretionary:

• Fat: > 5 g saturated fatty acids + trans fatty acids per 100 g for cereal-based foods and similar mixed foods (e.g. pizza, crumbed meats, battered or crumbed fish and seafood, fried vegetables).
• Total sugars: > 20 g total sugars per 100 g for breakfast cereals without fruit, > 22.5 g total sugars per 100 g for breakfast cereals with added dried fruit.
• Sodium:  > 280 mg sodium per 100 g for soups, 270-720 mg per 100 g for savoury biscuits, depending on the type.
• Calcium: < 100 mg calcium per 100 g for mixed foods with dairy content or dairy alternatives. Additionally, dairy alternative beverages were flagged as discretionary if they contained < 100mg calcium and > 5 g sugar per 100 g.

Consideration was given to nutrient criteria used in the Department of Health, Disability and Ageing Food Reformulation Program, which is a joint government and food industry voluntary initiative that aims to improve the potential health benefits of food available in Australia by setting  targets for the desired nutrient content of selected food groups through reducing the fat, total sugars and/or sodium content to be in line with the 2013 ADG (DHAC 2022). 

The discretionary food flag list may not be suitable for all applications. Researchers who may wish to apply different classifications in their own research will be able to in the DataLab later in 2025.

For further information on changes made to the discretionary food flag since the AHS 2011–13, see Comparing food and nutrient collections over time.

Further details of the principles for assigning a discretionary food flag and rationale for the changes since the AHS 2011–13 can be obtained from the ABS on request (health@abs.gov.au).

The discretionary food criteria follow the intention of the 2013 Guidelines: to identify foods high in saturated fats, sugar, salt, alcohol and energy, and flag these as discretionary. 

Some discretionary foods are often consumed in large amounts and may result in a high intake of saturated fat, sugar, salt, alcohol and/or energy. The discretionary food flag does not consider portion size, or the total amount of each food consumed and is not intended for use in this way. Advice on the quantity of different types of food to consume per day is given in the 2013 ADG.

For some food types, nutrient criteria are used to determine discretionary food status. In most cases a single nutrient criterion is used to determine discretionary status.  The nutrient criterion is chosen based on which nutrient has the higher percentage contribution for that food group to overall nutrient intake, making it a higher priority due to expected health impact. As a result, some discretionary food flags within a given food group may seem inconsistent at first glance. 

Example of an apparent inconsistency: 

• savoury crackers may be high in both saturated fat and sodium (from added salt)
• only sodium content is used as the deciding factor for this food group
• a regular cracker with a low sodium content may be considered non-discretionary, even if it has a high saturated fat content
• meanwhile, a reduced-fat version may be flagged as discretionary if it has a higher sodium content that exceeds the relevant sodium criterion.

These decisions reflect how nutrient criteria have been applied to eligible individual 8-digit foods and may differ from general expectations of what is a “discretionary food”.

Department of Health (DoH) (2013), National Healthy Schools Canteen – Guidelines for healthy foods and drinks supplied in school canteens, DoH, accessed 25/07/2025.

Department of Health and Aged Care (DHAC) (2022), Partnership Reformulation Program – Summary of food categories and reformulation targets, DHAC, accessed 25/07/2025.

Eat for Health (2013), Eat for Health Dietary Guidelines Summary, National Health and Medical Research Council in conjunction with the Department of Health and Ageing, accessed 25/07/2025.

National Health and Medical Research Council (NHMRC) (2013a), Australian Dietary Guidelines, NHMRC, accessed 25/07/2025.

National Health and Medical Research Council (NHMRC) (2013b), Eat for Health – Educators guide, NHMRC in conjunction with the Department of Health and Ageing, accessed 25/07/2025.

Public Health England (PHE) (2016), The Eatwell Guide, National Health Service, accessed 25/07/2025.

World Health Organization (WHO) (2018), WHO plan to eliminate industrially-produced trans-fatty acids form the global food supply, WHO, accessed 25/07/2025.

World Health Organization (WHO) (2020), Healthy Diet: Fact Sheet, WHO, accessed 25/07/2025.

The 2013 Australian Dietary Guidelines (ADG) encourage Australians to eat a wide variety of nutritious foods from the Five Food Groups every day and drink plenty of water. The five food groups are:

• Vegetables and legumes and beans
• Fruit
• Milk, yoghurt, cheese and/or alternatives
• Lean meats and alternatives (e.g. poultry, fish, eggs, tofu, nuts and seeds, and legumes and beans)
• Grain (cereal) foods.

The ADG also recommend a small amount of unsaturated fats, oils and spreads can be eaten. To meet nutrient requirements and reduce the risk of chronic disease, the ADG provides minimum recommended serves for each food group based on age and life stage. 

The ADG food groups are classified at 3 levels which include Major Food Groups, Sub-groups and the Servings Sub-groups. The major food group categories include the above groups, as well as water, unsaturated spreads and oils, and unclassified. See AUSNUT 2023 classification files for more information.

To determine how much of each food group type a person consumed, the total amount of each food type from all sources is calculated in grams. This includes:

• single foods (e.g. apple, bread)
• ingredients in mixed dishes (e.g. apple in apple pie, bread in a sandwich).

Recipes were developed by FSANZ to estimate how much of each ADG food group is included in mixed foods. More information is available on the FSANZ website.

Once the total amount of each ADG food type consumed is calculated, it is converted into serves using standard serve sizes from the ADG to give the total number of serves from each of the ADG Food Groups for each person (e.g. the number of serves of milk consumed as part of the Milk, yoghurt and cheese group and/or alternatives group).

The associated serving size can be found in the AUSNUT 2023 – Australian Dietary Guidelines classification system on the FSANZ website.

The number of serves of the ADG Five Food Groups consumed by each respondent per day are available in the microdata files for National Nutrition and Physical Activity Survey (NNPAS) 2023 and the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023. A comparison of reported number of serves of the ADG food groups to recommendations in the 2013 ADG for a population group of interest may be used to help assess diet quality. This data is available on request, and will become available in the DataLab later in 2025.

Data items and related output categories for this topic are available from the NNPAS Data Item List and the NATSINPAS Data Item List.

Information is reported on dietary habits, reasons for choosing a diet or eating pattern, food avoidance and the reasons for avoiding certain foods (National Nutrition and Physical Activity Survey (NNPAS) only), and on the use of oils, fats and salt in preparing and cooking food for consumption. 

Self-reported questions about the number of serves of fruit and vegetables, used in other health surveys, were included in the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023, but not in the NNPAS 2023. Information on the number of serves, estimated from dietary recall data, as described in the 2013 Australian Dietary Guidelines (ADG) are available in both surveys. See Australian Dietary Guidelines (ADG) food groups for more information.

Data items and related output categories for this topic are available in the NNPAS Data Item List and the NATSINPAS Data Item List.

Respondents may add salt as a food within their dietary recall, and this was retained during data processing. However, as salt is not specifically prompted in Intake24, estimates should be considered with caution. Respondents were asked general questions about salt use in food preparation, cooking and at the table, and whether the salt they use was iodised. Further information is provided on the short questions in the NNPAS 2023 methodology and the NATSINPAS 2023 methodology.

The AUSNUT files reflect salt consumption in food ‘as sold’ for fresh or processed foods and takeaway foods. AUSNUT recipes for home prepared foods do not assume any amounts of added salt (iodised or non-iodised). See the Food recipes file and Nutrient Profiles on the FSANZ website for more information. 

Salt is a source of sodium and if iodised salt is used, of iodine.  No adjustment was made during data processing based on survey responses to the short questions on salt use, so total dietary sodium and iodine intakes may be underestimated.

Respondents were asked about the main oil or fat used when cooking dishes containing vegetables, meat, chicken or seafood. Further information is provided in the NNPAS 2023 methodology and the NATSINPAS 2023 methodology.

Data were used to inform fat and oil content of the AUSNUT food recipes created by FSANZ for ‘not further defined foods’, see Food and beverage recall. The highest used oils and fats in the general population are outlined in the table below.

The ABS has conducted three major national nutrition surveys:

• National Nutrition Survey 1995
• Australian Health Survey (AHS) 2011–13
• Intergenerational Health and Mental Health Study (IHMHS) 2023.

In the 1995 collection, information was collected for the general population. However, in 2011–13 and 2023, surveys were run for the general population and for Aboriginal and Torres Strait Islander peoples. 

These surveys help track dietary information over time, and the ABS expects users will compare them to understand changes over time.

Each survey collected cross-sectional information for people aged 2 years and over, across all seasons of the year, to account for seasonal variation in the food supply and dietary patterns. Each survey used:

• 24-hour recall method to record food and supplement intake over 1 or 2 days
• short questions to collect additional dietary information.

When comparing results from different ABS collections, it’s important to consider the factors that may impact the comparability. Differences seen across time may reflect actual changes in dietary habits or the food supply, but they can also result from changes to data collection methods, coding systems, analysis techniques and food classification systems.

While all surveys used a similar approach – randomly selecting participants and using 24-hour multi-pass recall methods – data collection methods have evolved with technology:

National Nutrition Survey 1995

• Conducted face to face using paper forms and a food booklet
• 10% of respondents completed a Day 2 recall
• Foods were manually coded by ABS with input from Food Standards Australia New Zealand (FSANZ).

National Nutrition and Physical Activity Survey (NNPAS) 2011–12 and National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2012–13 (AHS 2011–13)

• Conducted face to face by ABS interviewers using the Automated multiple-pass method (AMPM) with a food booklet
• 64% of respondents completed a Day 2 recall via telephone interview
• About 70% of items were automatically coded, the remaining were coded by ABS with input from FSANZ.

NNPAS 2023 and NATSINPAS 2023 (IHMHS 2023)

• Conducted face to face by ABS interviewers using Intake24, with inbuilt food images or graphics
• 84% of respondents completed a Day 2 recall via web form or face-to-face
• Most foods were coded by respondents and interviewers during interviews; search-term matches were reviewed by ABS with FSANZ input.

Aboriginal and Torres Strait Islander peoples were not required to complete a Day 2 recall in the NATSINPAS 2023.

A summary of the main content changes applied in NNPAS 2023 compared with the NNPAS 2011–12 is given in the NNPAS 2023 methodology.

As different methods for estimating food and nutrition intakes were used in each of the surveys, data from these topics should be compared with caution across time. Similarly, use caution when comparing these surveys with other studies using a different method of data collection to capture dietary information.

Under-reporting of food, beverage and supplement intakes is considered by ABS prior to publishing results. The level of under-reporting and reason for it may change with each nutrition survey, so the food and nutrient intake data should be interpreted with care. For more information, see the NNPAS 2023 methodology and the NATSINPAS 2023 methodology.

The types of food and supplements consumed have changed over time. For each national survey, the AUSNUT food and dietary supplement database is updated to match the foods, beverages and dietary supplements respondents report. There are changes in the individual foods and dietary supplements and in their nutrient profiles for AUSNUT 2023 compared to previous versions (AUSNUT 1995 and AUSNUT 2011–13). These changes happened because:

• new food and dietary supplements became available
• nutrient data for some food and supplements were updated
• respondents reported their food differently
• foods and dietary supplements were grouped differently within the classification
• a new dietary recall tool and food list was used
• foods were coded differently to the classification. 

For the 2023 surveys, there were fewer foods listed, with less specificity for some food groups. Some food groups have expanded in the food supply resulting in new foods being added. Examples of changes include:

• less detail about cooking fats or how meat was trimmed
• fruit and vegetable drinks listed separately from juice at the sub-major level
• some types of iced versus uniced cakes were combined
• fewer options for pizza bases, sauces and oils
• some foods were removed or added in categories like fish, seafood, fruit and milk products
• a new sub-major category for de-alcoholised drinks (e.g. no alcohol wine)
• new foods with very low energy, reduced sugar and/or added protein. 

Care should be taken when comparing food consumption patterns and nutrient intakes over time. Concordance files for AUSNUT code changes for the 1995 to 2011–13 surveys, and for the 2011–13 to 2023 surveys are available on the FSANZ website. These should be used for comparative purposes.

Discretionary food flag in the AHS 2011–13

In the NNPAS 2011–12 and NATSINPAS 2012–13, all foods were assigned an 8-digit code from the AUSNUT 2011–13 food classification system. The discretionary food flag was assigned primarily at the 5-digit level (minor food group), with some exceptions at the 8-digit level, such as for breakfast cereals. 

Flagging decisions were made by the ABS, in consultation with the then Department of Health and nutrition experts, using the following sources:

• 2013 Australian Dietary Guidelines (ADG) (NHMRC 2013a, 2013b; Eat for Health 2013)
• AUSNUT 2011–13
• 2009 Modelling document used in developing the ADG, referencing the National Nutrition Survey 1995 and the AUSNUT 1995 database.

Discretionary food flag in the NNPAS 2023 and NATSINPAS 2023

In the 2023 surveys, all foods were again assigned an 8-digit code but this time the discretionary food flag was applied exclusively at the 8-digit level.

The ABS collaborated with the Department of Health, Disability and Ageing, the National Health and Medical Research Council and nutrition experts, to refresh the principles and criteria for flagging, using updated sources:

• 2013 ADG and supporting documents (NHMRC 2013a, 2013b; Eat for Health 2013)
• AUSNUT 2023
• National Healthy Schools Canteen Guidelines (DoH 2013)
• Department of Health, Disability and Aged Care Food Reformulation Program: Food categories and reformulation targets, (DHAC 2022)
• International dietary guidelines from Canada, England, New Zealand and the United States of America (PHE 2016; Health Canada 2018a, 2018b, 2018c; MoH NZ 2020; USDA & USDHHS 2020; WHO 2018, 2020).

Feedback from stakeholders on the 2011-13 discretionary food list was also considered. Notably, the term ‘discretionary foods’ is not commonly used in the overseas guidelines, although some, such as England’s 2016 EatWell Guide, do provide nutrient criteria for identifying foods higher in saturated fats, sugars and/or salt (sodium) (PHE 2016). 

Impact of changes in the criteria for discretionary foods

Most foods in AUSNUT 2023 kept the same discretionary status using the refreshed principles. Only 205 out of 3536 foods (6%) were updated using the refreshed criteria. 

Discretionary status may have changed since the previous survey due to changes in nutrient profiles over time, for example, due to use of mono-or polyunsaturated fats rather than saturated fats in a food’s preparation. 

Application of criteria at the 8-digit food level has led to changes for some foods as to whether they have been flagged as discretionary or not in AUSNUT 2023 compared to AUSNUT 2011-13, where the discretionary food flag was usually applied at the broader 5-digit level minor food subgroup level. For example, all dips were previously flagged as discretionary, but in 2023 some vegetable-based dips, like hummus, are now flagged as non-discretionary. Cream cheese or sour cream-based dips remain discretionary. Similarly, all hot potato chips were flagged at the 5-digit level as discretionary in AUSNUT 2011–13, but some products were considered non-discretionary when the saturated fat and trans-fat criterion was applied at the 8-digit level in 2023.  

Other changes may have occurred due to changes in nutrient criteria and the scope of foods to which they are applied.

Most changes to the flag occurred in:

• Cereal-based products and in some mixed dishes containing cereal ingredients (e.g. crumbed or battered meat, fish and vegetables) due to broader application of the saturated and trans-fat criterion.
• Milk and products and dairy alternatives categories where new calcium and sugar criteria were applied. 

In total, 31% of AUSNUT 8-digit foods were flagged as discretionary in AUSNUT 2023 compared with 31% of foods using the 2011–13 criteria. See the proportion of foods flagged as discretionary within each major food group using the old and refreshed criteria in the table below.

The age groups for reporting food and nutrient intakes from the NNPAS 2023 and NATSINPAS 2023 have changed, following a recent decision by the Department of Health, Disability and Ageing (DHDA) and the National Health and Medical Research Council (NHMRC) to better align with pre-school, primary school, high school years, and to define adults as 18 years and over. The following age groups are used in data downloads:

• 2–4 years
• 5–11 years
• 12–17 years
• 18–29 years
• 30–49 years
• 50–64 years
• 65–74 years
• 75 years and over.

Time series data published by the ABS will present food and nutrient results from previous nutrition surveys using the new age groups for comparative purposes, where appropriate.

Weighted NRVs for new age groups

For the purposes of reporting survey estimates, re-derived weighted Estimated Average Requirement (EAR) and/or Upper Level of Intake (UL) for nutrients are provided below for the new age groups. Weighted NRVs were derived for males and females separately where the original age groups were separated by sex. In most cases the weighted EAR and UL values for boys and girls aged 2-4 years and 5-11 years are the same. In this publication the weighted EALs and ULs for the new age groups are presented alongside Day 1 nutrient intakes where relevant to provide context for the results. In general, it is not appropriate to compare mean nutrient intakes to an Adequate Intake (AI) based on median intakes of healthy populations, AIs are not presented alongside nutrient intakes in this publication.  Single day nutrient intakes should not be used to assess population nutrient deficiency or excess, since NRVs are set for age groups that cover a longer period of several years or a life stage e.g. for a female who is pregnant and/or lactating.

Department of Health (DoH) (2013), National Healthy Schools Canteen – Guidelines for healthy foods and drinks supplied in school canteens, DoH, accessed 25/07/2025.

Department of Health and Aged Care (DHAC) (2022), Partnership Reformulation Program – Summary of food categories and reformulation targets, DHAC, accessed 25/07/2025.

Eat for Health (2013), Eat for Health Dietary Guidelines Summary, National Health and Medical Research Council in conjunction with the Department of Health and Ageing, accessed 25/07/2025.

Health New Zealand (2020), Eating and activity guidelines for adults, updated 2020, Health New Zealand, accessed 25/07/2025.

National Health and Medical Research Council (NHMRC) (2013a), Australian Dietary Guidelines, NHMRC, accessed 25/07/2025.

National Health and Medical Research Council (NHMRC) (2013b), Eat for Health – Educators guide, NHMRC in conjunction with the Department of Health and Ageing, accessed 25/07/2025.

Public Health England (PHE) (2016), The Eatwell Guide, National Health Service, accessed 25/07/2025.

United States Department of Agriculture (USDA) and United States Department of Health and Human Services (USDHHS) (2020), Dietary Guidelines for Americans, 2020-2025, USDHHS, accessed 25/07/2025.

World Health Organization (WHO) (2018), WHO plan to eliminate industrially-produced trans-fatty acids form the global food supply, WHO, accessed 25/07/2025.

World Health Organization (WHO) (2020), Healthy Diet: Fact Sheet, WHO, accessed 25/07/2025.

The Nutrient Reference Values for Australia (NRVs) are evidence‑based recommendations. They specify the amounts of essential nutrients needed to meet the requirements of healthy individuals and reduce the risk of adverse health outcomes. 

Total nutrient intakes for a population group may be compared to the relevant NRVs (NHMRC 2017). It is preferable to use usual nutrient intakes to assess the nutritional status of a population, where possible. See Single day, average, and usual intakes for more information.

NRVs are set by the National Health and Medical Research Council (NHMRC) for different age and sex groups or life stages. Following a decision by the Department of Health, Disability and Ageing (DHDA) and the NHMRC, the age groups for reporting food and nutrient intakes from the National Nutrition and Physical Activity Study 2023 were changed. See Changes in NHMRC reference age groups for more information. 

The ABS re-derived weighted NRVs for the new age groups to report survey estimates. For further information about how these NRVs were calculated, see Changes to Nutrient Reference Values (NRV). The NHMRC is undertaking a rolling review of NRVs, where the new age groups will be used in the future. Updates to the 2006 NRVs for fluoride and sodium were published in 2016 and 2017. 

NRVs such as estimated average requirements (EARs) and upper levels of intake (ULs) are intended to be used at a population level for assessment of the nutrition status of the population of interest (NHMRC 2017). The Suggested Dietary Targets (SDTs) for dietary fibre (38 g/day adult males, 28 g/day adult females) and the revised SDT for sodium (2000 mg/day, adults only) may be referred to in the commentary to put these nutrient intakes in context. Comparison of the NRV to an individual's single day intake does not confirm a specific diagnosis (e.g. a nutrient deficiency) without consultation with a health professional.

Comparison of nutrient intakes estimated from 24-hour recall records with NRVs are not necessarily the best measure of the proportion of the population with nutrient deficiency or excess for some nutrients, particularly for vitamin D, iodine and sodium. Biomedical measures were also taken in the National Health Measures Study (NHMS) 2022–24 to reliably collect information on key vitamins and minerals from a sample of respondents of the National Nutrition and Physical Activity Survey (NNPAS) and National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS). Data on iron, calcium, vitamin D, folate and vitamin B12 were collected for participating respondents aged 12 years and over, and on sodium, potassium and iodine for participating respondents aged 5 years and over. See Biomedical collections for more information.

National Health and Medical Research Council (NHMRC) (2017), Nutrient Reference Values for Australia and New Zealand Including Recommended Dietary Intakes, NHMRC website, accessed 02/03/2026.

Usual intakes are an estimate of what people 'usually' eat, not just what they eat in one day. These estimates can be done for both foods and nutrients. 

National nutrition surveys usually collect a couple of days of dietary recalls (rather than covering longer periods) because of time, cost, and to reduce burden on respondents. Because these recalls are short‑term, they are adjusted to estimate long‑term or “usual” intake.

For the National Nutrition and Physical Activity Survey (NNPAS) 2023, the ABS collected two 24-hour dietary recalls and then modelled the results to create longer-term intakes. 

For the NNPAS 2023, nutrient and food consumption for the first (Day 1) and second 24-hour recall (Day 2) can be used to estimate usual (habitual) intakes for selected population groups.

Food consumption derived from a single 24-hour recall may not represent the usual consumption patterns of a person because there is often variation in foods consumed on a day-to-day basis. The second 24-hour recall is used to estimate and reduce within-person variation and produce a usual distribution for the population; this can be either for food consumption amounts by AUSNUT food group or serves of Australian Dietary Guidelines (ADG) foods and/or nutrient intakes. It is preferable to use usual food intakes or usual serves to assess dietary patterns and usual nutrient intakes to assess the nutritional status of a population, where possible.

The usual intakes are not just an average of the two days of data for an individual. An average of the two days usually leads to biased estimates (Herrick et al. 2018) as it does not:

• account for days when a person eats none of the food, or highly skewed amounts
• separate within-person (day-to-day) variation from the variation between people
• allow for the correlation between how often a food is eaten and how much is eaten
• use extra information (covariates). 

Estimates of usual intakes require two 24-hour recalls. Estimates of usual intakes for the Aboriginal and Torres Strait Islander population are not available from the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS) 2023 as the NATSINPAS only collected a single day of recall. 

Data presented in the Foods and Nutrients release for the NNPAS and NATSINPAS are calculated based on the Day 1 recall, that is the 24 hours (from midnight to midnight) prior to interview.

Usual Nutrient Intakes for the NNPAS are calculated from Day 1 and Day 2 recall data. 

Usual intakes are important because food and nutrient guidelines, such as the Nutrient Reference Values (NRVs) or Australian Dietary Guidelines (ADGs), are based on usual intakes. Without adjusting, the results could over- or under- estimate how many people meet these guidelines.

For example, suppose we want to estimate the number of people who consume at least two serves of vegetables per day. As shown in Figure 1, a single‑day intake measure may indicate a larger proportion of people consuming fewer than two serves. This is simply because their intake happened to be lower on that particular day. However, this may not reflect their typical eating pattern. The opposite could also be true, a single-day intake of serves could be higher than usual.  A usual‑intakes model can account for occasional decreases or increases in consumption. In Figure 1, the estimated proportion of people who usually consume two serves of vegetables per day is higher than what the single‑day data alone would suggest.

There are multiple ways to model usual intakes. The ABS used the National Cancer Institute (NCI) method for this study and for the previous Australian Health Survey (AHS) in 2011–13. The method models dietary intake from 24-hour recalls to:

• estimate the usual intake for groups of people
• account for the effects of different characteristics, such as age or day of week
• account, partially, for bias resulting from measurement error (NCI 2024).

The output from the NCI method is a simulated distribution of usual intakes for groups. The method relies on pooled group data for its calculations. It does not produce usual intake estimates for individual respondents.

The NCI method works best when estimating frequently consumed foods and nutrients. It may be applied by users to the different classifications output in the ABS DataLab, for example AUSNUT 2023. Caution is advised when using the method with infrequently consumed foods and dietary supplements.

The ABS used version 2 of the NCI Method SAS macros, available at Usual Dietary Intakes: SAS Macros for the NCI Method. These are the same versions used in 2011–13.

The NCI method models usual nutrient intake or usual food consumption as:

                                probability of consumption x amount consumed

There are three available models based on this premise.  The ABS used two:

1. One-part model: This model assumes everyone consumes the nutrient or food every day, so the probability of consumption is 1. It is used for nutrients and foods that almost everyone eats daily. Only the amount consumed is modelled, and any zero intakes are replaced with half of the lowest non-zero value in the dataset.
2. Correlated two-part model: Some foods and nutrients are not consumed every day, and the chance of eating them is correlated to how much is eaten. For example, people who drink tea tend to consume more than one cup a day. This model accounts for this correlation.

For the Usual Nutrient Intakes 2023 publication, the two-part model was used when more than 5% of people had zero amounts of the nutrient. This applied to folic acid, caffeine, alcohol, and percentage of energy from alcohol. 

All other nutrients use the one-part model, because almost all people consume them daily.

The data was split into three groups:

• children aged 2 to 11 years
• males aged 12 years and older
• females aged 12 years and older.

The method was run separately for each group. Males and females aged 12 years and over were separated to allow for differences in consumption by sex. Children aged 2–11 years were modelled together because males and females in this age range usually have similar intakes. Combining this group also increases the sample size. 

Alcohol and percentage of energy from alcohol were treated differently. For these, the model was run for both males and females aged 18 years and over and younger age groups were not included as they had too few non-zero alcohol intakes.

Covariates in the NCI method are independent variables or characteristics that describe individuals in a group. They may influence what was consumed, for example, respondents may eat different foods on different days of the week or be less inclined to report as much detail in a subsequent recall (Serban et al. 2022). 

The ABS used four covariates known to affect food and nutrient intake:

• age and sex (combined)
• day of week
• sequence (order) of recall.

The specific categories used are listed in the table below.

Data for age groups not listed above (e.g. total 2–17 year olds) were input to the distribution model (distrib macro) after the covariates have been considered and simulation run (i.e. processed with the mixtran macro and Monte Carlo component of the distrib macro) (NCI 2024).

Ratios compare one variable by another and can be compared to one another using a proportion (for example, the percentage of energy that was discretionary compared to non-discretionary). 

There are four nutrient ratios published for the NNPAS 2023. These are percentages of total energy intake from carbohydrates, proteins, fats, and pure alcohol (ethanol). 

Two approaches can be used when modelling usual intake of a ratio. These either apply the ratio to:

1. each person’s data before the model is run (create a “usual intake of the ratio”)
2. the group usual intake data after the model is run (create a “ratio of usual intake”).

The first approach was used for this survey, and the estimate of the distribution of the 'usual ratio of intakes'. Results should be interpreted based on this approach (Freedman et al. 2010). 

Ratios were calculated on an individual basis, as a percentage of the person’s total daily energy. Energy conversion factors were applied to calculate each macronutrient's contribution. For more information on the calculation of these ratios, see Macronutrient contribution to energy intake.

The Nutrient Reference Values for Australia (NRVs) are evidence‑based recommendations. They specify the amounts of essential nutrients needed to meet the requirements of healthy individuals and reduce the risk of adverse health outcomes. These recommendations are based on long-term or usual nutrient intakes. 

At the time of the Usual Nutrient Intakes 2023 release, the NRVs available were current as of 2017 (NHMRC 2017). Following a decision by the Department of Health, Disability and Ageing (DHDA) and the National Health and Medical Research Council (NHMRC), the age groups for reporting food and nutrient intakes from the NNPAS 2023 were changed. The ABS re-derived weighted NRVs for the new age groups to report survey estimates. For further information about how these NRVs were calculated, see Changes to Nutrient reference Values (NRV).

For each nutrient with an NRV, two steps were followed to estimate the proportion of the population below or above the reference value:

• Step 1. Estimate the population group’s usual nutrient intake distribution. The NCI method was used to estimate these for this survey.
• Step 2.  Compare usual intakes with the NRV to determine the proportion of people whose intake falls above or below the requirement for their age and sex group.

Specific information for the NRVs reported in the Usual Nutrients Intakes 2023 publication can be found below.

To stay healthy, our bodies need certain amounts of vitamins, minerals and other nutrients. One way to check if people are getting enough is by using the Estimated Average Requirement (EAR). 

The EAR is the daily amount of a nutrient that is expected to meet the needs of half the healthy individuals in a particular age and sex group (NHMRC 2006). Usual intake below the EAR indicates the people who are at higher risk of health problems from not getting enough of that nutrient.

To understand how many people might not be meeting their nutrient needs, we compare usual intakes with the EAR. The Usual Nutrients Intakes 2023 publication uses two main methods:

1. EAR cut‑point method: this method is used for most nutrients. It works well when nutrient requirements are even across the population. It simply counts how many people in a group have usual intakes below the EAR.
2. Full probability method: this method is used for iron. Iron needs vary more between people, so a more detailed method is needed to estimate the risk of inadequate intake.

More detail about how these methods were applied is listed below.

The UL is the highest average daily amount of a nutrient intake that most people can consume without a high risk of adverse health effects. As intake increases above the UL, the potential risk increases (NHMRC 2006).

The proportion of people with usual intake above the UL indicates how many may be at risk of health problems from getting too much of that nutrient (NHMRC 2017). Not everyone who consumes above the UL will have harmful effects, but their risks are higher than for people who stay at or below the UL (Health Canada 2017).

Suggested Dietary Targets (SDTs) are a daily average intake from food and beverages for certain nutrients that that may help in prevention of chronic disease. SDTs have been set for some nutrients where there is evidence that a daily average intake below or above the SDT could have benefits in reducing chronic disease risk (NHMRC 2017). Any comparisons of reported usual nutrient intakes to SDTs should be made considering the basis for the SDT used, and any new evidence available since it was set.

The Acceptable Macronutrient Distribution Ranges (AMDRs) define the recommended proportions of energy that should come from each macronutrient. These ranges aim to support good health while still allowing enough of other nutrients (NHMRC 2017). If usual intakes fall outside of these ranges, it suggests an imbalance that may raise long‑term chronic disease risk (Health Canada 2017). 

The Usual Nutrient Intakes 2023 reports the proportion of people with usual intakes below, within or above each AMDR. Macronutrients included are carbohydrates, protein, and fat. For details on how these are calculated, see Modelling ratios of nutrients, above.

There are no NRVs set for caffeine. There are recommended maximum daily levels of caffeine available to compare against (FSANZ 2023). The recommended levels are based on how many milligrams of caffeine a person consumes per kilogram of their body weight. Going above these levels increases the risk of negative health effects (FSANZ 2023). Comparisons of reported usual caffeine intakes to the maximum levels should consider how the limits are set. This includes any new evidence available since they were set.

Some nutrients have different NRVs for people who are pregnant or breastfeeding. This is because their bodies need additional nutrients to support the growth of the baby and produce breast milk (NHMRC 2017). 

The NNPAS 2023 did not report usual intakes for this population because there were too few people in the sample. 

Where usual nutrient intakes are compared with the NRVs, any results that sit outside of the reference values need to be interpreted carefully. It is important to understand how the NRVs were established, because this affects what the results mean. 

At the time of release of Usual Nutrient Intakes 2023, the current NRVs were those published by the NHMRC in 2006 and 2017 (NHMRC 2017). 

More information about how the NRVs were developed for each nutrient is available on the NHMRC Nutrient Reference Values website.  

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National Cancer Institute (NCI) (2024), Usual Dietary Intakes: The NCI Method, NCI website, accessed 02/03/2026. 

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