Apparent Consumption of Selected Foodstuffs, Australia methodology

Latest release
Reference period
2024-25 financial year
Release date and time
30/10/2026 11:30am AEDT

Data collection

Introduction

The Apparent Consumption of Selected Foodstuffs, Australia, 2024–25 is an experimental series intended to provide information on trends in the food consumption and nutritional composition of products available from the food retail sector, a major component of the overall food supply in Australia. The data is complementary to the more detailed information available from national nutrition surveys, but with the advantage of being an ongoing (annual) collection that can be produced in a relatively timely and cost-effective manner. It helps to address a critical data gap relating to food and nutrient consumption required to inform policy makers, regulators, health researchers and the food industry.

The 2024–25 release of the Apparent Consumption of Selected Foodstuffs (ACSF) publication is the sixth release of ACSF since collection was resumed from 2018-19.  The previous historic collection of ACSF ceased in 2000 (1998–99 reference year) due to the poor fitness for purpose of previous data sources used for estimating the availability of certain foodstuffs. A review at that time found the costs and complexity of addressing the data quality concerns to be beyond resources available. This release moves the food classification and nutrient data from AUSNUT 2011–13 to AUSNUT 2023. All years from 2018–19 have been recoded to AUSNUT 2023, so the series remains comparable over time, but estimates differ from those previously published. See 'Transition to AUSNUT 2023' below.

The current ACSF concept makes use of aggregate transactions from scanner data (SD) that were originally sourced to improve economic measures such as the Consumer Price Index (CPI). The development of the current ACSF collection was supported and funded by the Department of Health and Aged Care to help inform Australian food nutrition policy and research. The use of sales data to measure apparent consumption is a key difference from the previous ABS Apparent Consumption of Foodstuffs collection which was based on national production plus imports minus exports.

The apparent consumption of selected foodstuff (ACSF) estimates in this publication comprise two components:

  1. Directly calculated measures of food quantities available for consumption from aggregated sales data provided by the major retailers using SD, and
  2. Indirectly estimated measures of the food quantities available for consumption that are not captured by the major retailers in the SD, which are based on household expenditure data.

Data sources

Scanner data

The primary data source for this publication is aggregated scanner data (SD) provided to the ABS by the major supermarket chains based on barcode scanning at the point of sale. The aggregate information comprises the Stock Keeping Unit (SKU) of the sales item, a description of the item, the geographical region of sale and weekly aggregate amounts of the quantity and value of the sales. The major supermarkets that provide data to the ABS account for around 78% of the value of sales of the food retail sector (i.e. the total from supermarkets, grocers, convenience stores and specialty food retailers).

2015–16 Household Expenditure Survey

The Household Expenditure Survey (HES) was undertaken every six years until 2015-16 (the most recent HES). ACSF uses the expenditure patterns in the 2015–16 HES to estimate the ratio of expenditure in stores not represented by SD to expenditure from the supermarkets in scope of SD (for a given product category in a given geographical area). Although no comprehensive adjustment (by product type and geographic area) is made to the 2015–16 HES data to align it to the ACSF reference periods, the weighting for each reference period is calibrated for changes in the proportion of total food retail turnover that is accounted for by SD. The adjustments are based on monthly estimates of retail turnover by industry sub-group from Retail Trade. Further information on the use of the HES for adjustment is provided in the 'Estimation' section below. 

Scope

The scope for this collection is all food and non-alcoholic beverages purchased for consumption in Australia from the food retail sector. This includes all food and non-alcoholic products assigned to the food and non-alcoholic beverage expenditure classes (ECs) used to compile the CPI with the exception of Restaurant meals and Take-away and fast foods. For the complete list of ECs, see the Annual weight update of the CPI and Living Cost Indexes, Appendix 1.

The 2015–16 HES collected expenditure from households representing about 97% of people in Australia. In expenditure terms, the 2015–16 HES estimated an average weekly expenditure of $237 per household on Food and non-alcoholic beverages. Of this, 34% ($80) was estimated to be on Meals out and fast foods, leaving 66% ($157 in 2015–16) of total food expenditure as in scope in the ACSF.

All in-scope foods are coded to the food classification system in AUSNUT 2023. Food Standards Australia New Zealand (FSANZ) developed it for the 2023 National Nutrition and Physical Activity Survey (NNPAS) and the 2023 National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (NATSINPAS). AUSNUT coding gives the ACSF an established food classification. It also lets SD and HES data be assigned to major food groups and subgroups for analysis. AUSNUT 2023 holds nutrient profiles for each food and non-alcoholic beverage. It links to Australian Dietary Guidelines (ADG) food group profiles (grams and serves of each ADG food group per 100 g) and to a discretionary food flag. Because ACSF and the 2023 NNPAS share one classification, similar high-level analyses (population averages) are possible from both. Important differences remain between foods as purchased (scanner data) and foods as eaten (nutrition surveys).

It should be noted that estimates of 'apparent consumption' of food and non-alcoholic beverage products are derived using information related to sales (that is, food available for consumption from purchases made from the food retail sector). Therefore, they are at best a partial representation of the apparent consumption due to scope limitations (see ‘Out of scope’ below). Furthermore, ‘apparent consumption’ methodologies typically don’t adjust for waste (see below) or changes in household inventories i.e. all food and non-alcoholic beverages available for apparent consumption (purchased) in a particular year are assumed to have been consumed in that year.

Out of scope

While SD (when used with the HES) can represent the majority of the food available for consumption in Australia, there are clear gaps where either SD sales or 2015–16 HES do not adequately capture representative food and non-alcoholic beverage amounts. These are:

  • Fast foods, cafe and restaurant meals
  • Meals provided by institutions that source food from the non-retail sector
  • Home grown or produced food
  • Wild foods obtained by gathering/foraging, hunting or fishing.

The exclusions in the HES sample comprise of:

  • Very Remote areas
  • Residents of non-private dwellings (e.g. hotels, boarding schools, nursing homes and prisons)
  • Households containing members of non-Australian defence forces or diplomatic personnel of overseas governments stationed in Australia.

The exclusions associated with the HES survey should have minimal impact on the indirect estimated measures compiled to represent the food quantities available for consumption from the non-major supermarkets not captured in the SD provided to the ABS.

Alcohol

Comprehensive liquor retail sales are not currently available from the source data. Alcoholic beverages are therefore excluded from the alcoholic beverages food group from AUSNUT (code 29). One exception to this classification exclusion is the subset of de-alcoholised beverages (AUSNUT code 296) made up of zero-alcohol beer and wine products. These de-alcoholised beverages are also presented alongside other selected non-alcoholic beverages within the selected beverages presented in Tables 1 and 5 to 14. 

Despite the exclusion of alcoholic beverages, Table 2 (nutrients available) and Table 3 (energy from macronutrients) indicate small amounts of alcohol consumption. This results from the alcohol occuring in products such as certain confectionery and desserts. 

Waste

The estimates presented in this publication are not adjusted for possible product wastage. The most recent estimate of total organic food wastage in Australia was around 3.1 million tonnes for 2018–19. This is the equivalent of around 340 grams per person per day (or 2.4 kg per week). While it may be expected that all perishable goods will be susceptible to a degree of waste, the waste estimates cannot provide further breakdowns, for instance how much is vegetables and fruits, and how much is baked goods, dairy produce, various meat products etc. Given most discretionary foods are packaged (and have a longer shelf life) they may be less likely to be disposed of than fresh produce. Such an imbalance in waste suggests greater care should be taken in interpreting the apparent consumption of non-discretionary foods and therefore the relative balance between discretionary and non-discretionary foods. In addition, different fresh foods may have different edible proportions (e.g. grapes have a higher edible proportion than pineapple) and no adjustment has been made to subtract the inedible proportion which may lead to further over-estimation of the amount of certain fresh products and nutrients available for consumption.

Geographical coverage

The SD provides aggregate data representing all regions of Australia serviced by major supermarket chains. Estimates in this publication are presented at the national level. While state and sub-state estimates are feasible, they are not included in this release.15 The SD provides aggregate data representing all regions of Australia serviced by major supermarket chains. Estimates in this publication are presented at the national level. While state and sub-state estimates are feasible, they are not included in this release.

Reference period

The current release is the sixth edition in the series and covers the seven years from July 2018 to June 2025. Estimates for periods before July 2024 have been revised to maintain consistent time-series. 

Processing the data

Changes in this edition

Key methodological and output changes in the 2024-25 edition include:

  • Implementation of AUSNUT 2023, including updated food classifications, nutrient profiles, Australian Dietary Guidelines food group profiles and discretionary food classifications.
  • Improvements to the AUSNUT coding database, including additional product coding and refinement of existing product classifications.
  • Enhanced treatment of incomplete AUSNUT coding through revised weighting benchmarks based on products' assigned AUSNUT expenditure classes.
  • Introduction of new non-alcoholic beverage groupings, including sugar-sweetened and intense-sweetened beverage categories.

AUSNUT coding

Each supermarket product (SKU) was assigned an AUSNUT 2023 food code and a size (weight or volume) based on the product description. Coding was completed for around 95% of the total value of supermarket scanner data foods in each year, representing more than 120,000 unique SKUs.

AUSNUT is primarily designed to classify foods as consumed, while many supermarket products are sold in an unprepared form. AUSNUT 2023 includes additional codes for some unprepared foods (for example, uncooked pasta, flour and uncooked cuts of meat), which were applied where appropriate.

Because AUSNUT 2023 reflects the Australian food supply around 2023, it better captures product reformulation, including reduced-sugar and intense-sweetened products, than AUSNUT 2011-13. However, products reformulated after 2023, or products without a close AUSNUT match, may still be assigned nutrient profiles that differ from the product as sold.

Implementation of AUSNUT 2023

AUSNUT 2023 differs from AUSNUT 2011-13 in its food classification, nutrient profiles, Australian Dietary Guidelines (ADG) food group profiles and discretionary food flag.

  • Food classification: AUSNUT 2023 retains the hierarchical structure of major, sub-major and minor food groups, but some groups were added, split or renamed. Food group names and codes in this release therefore differ from earlier releases.
  • Nutrient profiles: Nutrient values were updated using newer analytical data from FSANZ food composition programs. Differences between AUSNUT versions may therefore reflect improved nutrient measurement rather than changes in foods themselves.
  • ADG food group profiles: ADG classifications were rebuilt for AUSNUT 2023 using an updated version of the 2011-13 methodology.

Discretionary food flag: For AUSNUT 2023, the flag was set at the 8-digit food level compared to 2011-13 where the flag was generally applied at the 5-digit (minor) food group. In addition, the 2023 discretionary flag extends the saturated fat criterion to more mixed foods and now includes trans fat. Sugar criteria were also aligned with the Healthy Food Partnership Reformulation Program targets, and a calcium criterion was added for dairy alternatives. See Discretionary foods.

Products in the ACSF coding database were transitioned to AUSNUT 2023 using a concordance developed from all 5,754 foods in AUSNUT 2011-13. Because AUSNUT 2023 consolidated many similar foods, particularly foods differing only by preparation method, the 2011-13 foods map to 3,741 AUSNUT 2023 foods and does not always have a one-to-one correspondence.

The concordance was developed in three stages:

  1. Direct matching using the FSANZ AUSNUT 2023 to AUSNUT 2011-13 mapping file.
  2. Description-based matching within similar food groups where no direct match existed.
  3. Refinement using similarity in nutrient and ADG food group profiles.

Over 90% of food consumption was matched with high confidence. Remaining foods were reviewed individually and assigned to the most suitable AUSNUT 2023 food based on classification and nutrient similarity.

The concordance was used as an initial transition mechanism and was followed by targeted review of high-value and high-volume supermarket products to improve coding quality within major food categories.

In cases where AUSNUT 2023 did not have a suitable match for the unprepared food, new food codes and descriptions were created with nutrient profiles being either borrowed from AUSNUT 2011-13 or derived from comparable AUSNUT 2023 foods using recipe assumptions.

AUSNUT 2023 codes were applied consistently to products across all reference periods. Consequently, differences from previously published estimates primarily reflect changes in classification, nutrient composition and food group definitions rather than a revision of the underlying sales. This was supported by testing which indicated differences in nutrient estimates (comparing AUSNUT 2023 with 2011-13) were driven principally by revisions to nutrient profiles within matched foods rather than the concordance limitations.

Coding weighting adjustment

Although AUSNUT coding is primarily automated using machine learning, products with match confidence below a specified threshold require manual review. Because this manual process is a constraint to scaling auto-coding, products are prioritised for coding according to their sales value to maximise coverage of total sales.

Products that remain uncoded (representing less than 5% of sales value within each EC) are accounted for through weighting adjustments. Weights are calculated as the inverse of the coding proportion and are calibrated by EC, sales month and supermarket chain. This effectively prorates the uncoded sales across the distribution of observed AUSNUT codes within the corresponding calibration group.

In previous releases, weighting was benchmarked using the expenditure class originally assigned to each product. In this release, benchmarking uses the expenditure class corresponding to the product's assigned AUSNUT 2023 code. Where the original and AUSNUT-derived expenditure classes differ, the AUSNUT-derived class is used because it more accurately reflects the product's food type.

This approach improves consistency between coding and weighting. However, because expenditure class corrections can only be applied to coded products, a small proportion of uncoded products may remain assigned to an expenditure class that would differ if coding had been completed.

The weighting approach assumes that:

  1. Adjustment is required because coding rates vary over time, between expenditure classes and between retailers.
  2. Potential bias introduced by weighting is limited because coding coverage is high within expenditure classes (exceeding 95% of value).
  3. Coded products are representative of all products within each expenditure class.
  4. Products selected for coding are systematically prioritised from highest to lowest value within expenditure classes.

Estimation

As mentioned above, there are two components to the estimates of apparent consumption of foodstuffs presented in this publication. The components are:

  1. Directly estimated component. This is simply the quantity of each item multiplied by the size (grams or mL) of the item in the SD.
  2. Indirectly estimated component. This uses 2015–16 HES data to derive an expenditure ratio of food items from the non-major supermarkets and other food retail outlets to the major supermarkets to estimate the food quantities available for consumption that are not captured in the SD. The expenditure ratios are then applied to a grams per dollar value to derive the estimated quantity (weight or volume) of that food or non-alcoholic beverage available for consumption from the non-major supermarkets and other food retail outlets. 

The adjustment for the indirectly estimated component may be summarised as a five-step process: 

  1. Map 2015–16 HES food and non-alcoholic beverage expenditure codes to AUSNUT 2023 codes.
  2. Estimate the Food retail sector expenditure ratio from non-major supermarkets and other food retail outlets to the major supermarkets by each food group by region from the data reported in the 2015–16 HES. This step provides the expenditure ratio for a defined food group for each Greater Capital City Statistical Area (GCCSA). This is expressed below where i = a given food group in a given GCCSA geographical area, MS represents major supermarkets, NMS represents the food retailers from non-major supermarkets and other food retail outlets and Exp() represents the respective expenditure amounts.

    \(\large{Coverage \ weight _{i}=\frac{\sum w_{i} \times E x p_{i}(N M S)}{\sum w_{i} \times E x p_{i}(M S)}}\)

  3. The coverage weights are then calibrated to account for fluctuations in the contribution of supermarkets sales to total food retail turnover (from Retail Sales) by applying a benchmark ratio. This benchmark ratio is defined as the average ratio of SD to total food retail (RT) for the 2015-16 period (i.e. HES reference period). The monthly adjustment is then calculated by applying this benchmark ratio to each month’s ratio of SD to RT. 
  4. Derive amounts (grams or mL) per dollar for each product based on the known prices per product size in the SD.
  5. Apply the amounts per dollar (from step 4) to the calibrated to expenditure ratios (from step 3) and multiply by the observed sales values in the SD to derive the imputed amounts in grams or mL of foods and non-alcoholic beverages available for consumption from non-major supermarkets and other food retail outlets.

Limitations of method

Three main limitations have been identified which will impact the validity of the expenditure ratios. These are:

  1. Loss of fine product detail in mapping of HES expenditure codes (HEC) to AUSNUT codes 
  2. Representivity of the stores identified in the subset of HES data that was used to estimate proportion of expenditure from the major and non-major supermarkets and other food retail outlets (and that it represents a period nine years prior to the current ACSF reference period) 
  3. Estimation of the amount (grams or mL) per dollar of food represented in the SD.

Mapping of HES expenditure codes to AUSNUT codes

The aim of this step is to define common groups of products that represent broad types of food and non-alcoholic beverages groups in terms of their propensity to be bought from the major supermarkets or other retail outlets.

Alignment of 2015–16 HES food expenditures with the SD was performed by creating a correspondence which maps foods and non-alcoholic beverages from both the HES (124 relevant codes) and AUSNUT (around 3,750 codes) to common food groups. After collapsing a number of HES codes which were not similarly split in AUSNUT, each classification was mapped to a common set of 63 defined food groups. 

Representation of identified stores in the subset of HES

The HES was used to provide estimates of the expenditure ratios (by food group and geography) of the in-scope supermarkets. However, the receipt information identifying the store at which food purchases were made in the 2015–16 HES was not an essential survey input data item, and was only captured incidentally (where the respondent retained the receipt to assist in recording expenditures). Although a receipt identifying the store was provided for almost three-quarters (74%) of relevant food and non-alcoholic beverages expenditure, this subset is likely to over represent the transactions where the respondent purchased multiple grocery items. This led to a moderate correlation between a food item having a receipt and that food being purchased at one of the major supermarkets in scope of the SD. With no further adjustment made, this association may indicate some bias favouring expenditures from the major supermarkets. Such a bias may tend to underestimate the expenditure ratios for foods coming from specialty shops (e.g. butchers, bakeries, fresh food markets or seafood shops). 

The calibration process for each year’s weight (described in step 3 above) also has limitations including:

  • The estimates of specialised food retail are not broken down for type of products. In other words, this adjustment cannot account for different rates of change by different food specialisations (e.g. butcher shops, delicatessens and fruit and vegetable stores are all assumed to increase/decrease at the overall rate)
  • Retail Trade estimates are based on sampled units which results in sampling error (i.e. the difference between results from the sample compared to if the entire population was surveyed). However, given the monthly food retailing estimates have relative standard errors of less than 2% and the ratios used for calibration are 12 month aggregations, the sampling error is expected to be a negligible component. 

Deriving a gram or mL amount of food or beverage per dollar

Translating the expenditure ratios to amounts (grams or mL) of food per dollar was performed by:

  1. Deriving a median amount (grams or mL) per dollar at the AUSNUT code level, based on all contributing SKUs to each AUSNUT code
  2. Applying that gram or mL per dollar amount to the expenditure ratio to estimate the imputed amount of each food. In practice, foods being imputed are aggregates of AUSNUT coded foods, so the imputation uses weighted aggregates of the applicable AUSNUT code medians.

The major limitation of this method is the assumption that amounts per dollar from major supermarkets represent the same amount for other retailers (e.g. convenience stores and specialty stores). It is more likely that for many products the amounts of food or non-alcoholic beverage available for consumption per dollar expended are higher at the major supermarkets on equivalent items.

By using the median, it assumes the midpoint value is representative of the aggregate amount (grams or mL) per dollar across all products in the defined food group. Analysis of the SD shows some amounts (grams or mL) per dollar distributions are bi-modal, with product items concentrated around small sized products (lower grams or mL per dollar) and bulk products (higher grams or mL per dollar). Therefore, if the expenditure in non-major supermarkets and other food retail outlets includes less of the bulk packages then the imputed amount of food or non-alcoholic beverage (grams or mL) per dollar may be an overestimate.

Per capita estimates

Daily per capita estimates are derived by dividing the annual total by the number of days in the reference year and dividing by the Estimated Resident Population (ERP). Data representing each financial year uses the ERP for December. For example, the 2023-24 estimates use ERP for December 2023. Monthly estimates use a monthly population estimate interpolated from the quarterly ERP. 

No adjustments have been made to the ERP for foods and non-alcoholic beverages that are typically consumed by selected age groups only, such as baby food.

Measuring Australian Dietary Guidelines food groups

Many food products are mixtures of food groups. Total apparent consumption of each ADG food group is therefore measured with the AUSNUT 2023 ADG profiles, which give the grams and serves of each ADG food group per 100 g of each food. The ADG classification used for AUSNUT 2023 was adapted from the one developed by FSANZ for the 2011–13 Australian Health Survey. For more information, see Assessing the 2011–13 AHS against the Australian Dietary Guidelines - Classification System and Database Development Explanatory notes. 

Revisions

Estimates in this publication for years prior to 2024-25 have been revised from the previous releases. While the most significant change in this edition is incorporation of AUSNUT 2023 (discussed above), other revisions have also been applied. The changes may be categorised as:

  1. Revisions to AUSNUT coding 
  2. Cleaning of input sales data to remove or adjust outliers
  3. Updating the benchmarks used to weight incomplete AUSNUT coding 

The revisions to AUSNUT coding are enhancements to the database used to map food products to AUSNUT classification and include: 

  • changes to the weight/volume of products previously coded
  • changes to the specific AUSNUT code assigned to products previously coded (including scope decisions)
  • coding of additional food and beverage products that were not previously coded (but were sold previously)
  • imputation of nutrient lines for particular foods to improve nutrient accuracy.

Scanner data can occasionally contain anomalous sales records arising from reporting or processing issues. These anomalies may result in under- or over-stated sales values, including those caused by missing contributing units or duplicated transactions. The ABS applies statistical editing and imputation methods to identify and treat these records. Where appropriate, replacement values are derived from adjacent periods to produce estimates that are more representative of underlying sales patterns.

The 2024-25 ACSF has also created new groupings for categories of non-alcoholic beverages presented in Tables 1, 5-14. The custom groupings provide the consumption levels by type of beverage and by sugar-sweetened and intense-sweetened type. These are complemented by 100% fruit juice, bottled water and other selected beverages. Appendix A lists the codes in each beverage grouping used in Tables 1, 5–13 and 14. 

Glossary

AUSNUT context

Many of the definitions used in the Apparent Consumption of Selected Foodstuffs (ACSF) and referenced in this glossary are food groups from the food classification provided by AUSNUT 2023 with details from the Food details file available from FSANZ. Similarly, the nutrients and other food components used in the ACSF and defined in this glossary come from the AUSNUT 2023 food nutrient profiles and are described in the List of nutrients file. 

Acceptable macronutrient distribution ranges (AMDR)

Added sugars

Alcohol

Apparent consumption

Australian Dietary Guidelines (ADG)

Australian Dietary Guidelines profiles

Australian Dietary Guidelines food groups

Average recommended serves

Basic food groups

Carbohydrate

Cereal-based products

Cereals and cereal products

Commercially sterile

Confectionery

Dairy and meat substitutes

Dietary fibre

Discretionary foods

Egg products

Energy

Energy from macronutrients

Estimated resident population (ERP)

Fat

Fats and oils

Fish and seafood products

Five food groups

Food classification or food groups

Free sugars

Fruit products

Infant formulae and foods

Intense-sweetened

Intense-sweetened beverages

Intrinsic sugars

Legume and pulse products

Mean

Meat and poultry

Milk products

Miscellaneous

National Nutrition and Physical Activity Survey (NNPAS) 2023

Non-alcoholic beverages

Non-discretionary foods

Nutrient

Nutrient database

Nutrient Reference Value (NRV)

Other selected beverages

Per capita estimates

Protein

Recommended usual intake of fruit

Recommended usual intake of vegetables

Saturated fat

Savoury sauces and condiments

Seed and nut products

Selected beverages

Serves

Snack foods

Sodium

Soup

Special dietary foods

Sugar products

Sugar-sweetened beverages

Total fat

Total sugars

Vegetable products

Appendix A

Customised classification of beverages, based on AUSNUT 2023 code groupings

Beverage groupingSub-groupAUSNUT 2023 code (a)Code levelAUSNUT 2023 descriptionDiscetionary status (b)
Soft drinksSugar-sweetened11601MinorSoft drinks, non-colaDiscretionary
Soft drinksSugar-sweetened11603MinorSoft drinks, colaDiscretionary
Soft drinksSugar-sweetened11605MinorFlavoured mineral watersDiscretionary
Soft drinksSugar-sweetened11103001FoodIce tea, commercialDiscretionary
Soft drinksIntense-sweetened (c)11602MinorSoft drinks, non-cola, reduced or no added sugarDiscretionary
Soft drinksIntense-sweetened (c)11604MinorSoft drinks, cola, reduced or no added sugarDiscretionary
Soft drinksIntense-sweetened (c)11606MinorFlavoured mineral waters, reduced or no added sugarDiscretionary
Soft drinksIntense-sweetened (c)11103002FoodIce tea, commercial, intense sweetened or dietDiscretionary
Soft drinksIntense-sweetened (c)11103004FoodKombuchaDiscretionary
Energy drinksSugar-sweetened11703MinorEnergy drinksDiscretionary
Energy drinksIntense-sweetened (c)11704MinorEnergy drinks, intense sweetenedDiscretionary
Sports drinksSugar-sweetened11701001FoodSports drink, ready to drink, all flavoursDiscretionary
Sports drinksSugar-sweetened11702001FoodSports drink, dry powder, all flavoursDiscretionary
Sports drinksSugar-sweetened11701003FoodSports drink, made from dry powder & water, all flavours, standard dilutionDiscretionary
Sports drinksIntense-sweetened (c)11701002FoodSports drink, ready to drink, all flavours, sugar freeDiscretionary
CordialsSugar-sweetened11501MinorCordials, made from concentrateDiscretionary
CordialsSugar-sweetened11503MinorCordial concentrateDiscretionary
CordialsIntense-sweetened (c)11502MinorCordials, made from concentrate, reduced or no added sugarDiscretionary
CordialsIntense-sweetened (c)11504MinorCordial concentrate, reduced or no added sugarDiscretionary
Fruit and vegetable drinksSugar-sweetened11401MinorFruit drinks (ready to drink or made from concentrate)Discretionary
Fruit and vegetable drinksSugar-sweetened11402MinorVegetable drinksDiscretionary
Fruit and vegetable drinksIntense-sweetened (c)11401007FoodFruit drink, blackcurrant, commercial, intense sweetenedDiscretionary
Fruit and vegetable drinksIntense-sweetened (c)11401009FoodFruit drink, cranberry, commercial, intense sweetenedDiscretionary
100% fruit and vegetable juicesFruit juice11301MinorFruit juicesNon-discretionary
100% fruit and vegetable juicesFruit juice11304001FoodJuice, fruit blend, commercial, added vitamins & mineralsNon-discretionary
100% fruit and vegetable juicesVegetable juice11302MinorVegetable juicesNon-discretionary
100% fruit and vegetable juicesVegetable juice11303MinorFruit and vegetable juice blendsNon-discretionary
100% fruit and vegetable juicesVegetable juice11304002FoodJuice, fruit & vegetable blend, commercial, added vitamins & mineralsNon-discretionary
Bottled waterWater, plain and carbonated11802003FoodWater, bottled, carbonated or soda waterNon-discretionary
Bottled waterWater, plain and carbonated11802001FoodMineral water, naturalNon-discretionary
Bottled waterWater, plain and carbonated11802002FoodWater, bottledNon-discretionary
Bottled waterFlavoured water – sugar-sweetened (d)11803001FoodWater, bottled, flavoured, added sugar, vitamins & mineralsDiscretionary
Bottled waterFlavoured water – intense-sweetened (d)11803002FoodWater, bottled, flavoured, no added sugar, added vitamins & mineralsNon-discretionary
Bottled waterFlavoured water – sugar-sweetened (d)11804001FoodWater, bottled, flavoured, added sugarDiscretionary
Bottled waterFlavoured water – intense-sweetened (d)11804002FoodWater, bottled, flavoured, no added sugarNon-discretionary
Other selected beveragesCoconut water22203010FoodCoconut, water or juiceNon-discretionary
Other selected beveragesFlavoured milks and milkshakes198Sub-majorFlavoured milks and milkshakesMixed (1 of 20)
Other selected beveragesDairy milk substitutes, flavoured202Sub-majorDairy milk substitutes, flavouredMixed (4 of 12)
Other selected beveragesBreakfast cereal beverages11905MinorBreakfast cereal beveragesNon-discretionary
Other selected beveragesDe-alcoholised beverages296Sub-majorDe-alcoholised beveragesDiscretionary

(a) A three-digit or five-digit code includes every eight-digit food beneath it.
(b) All codes in the soft drinks, energy drinks, sports drinks, cordials and fruit and vegetable drinks groupings are discretionary. Juices, plain water, coconut water, breakfast cereal beverages and no-added-sugar flavoured waters are non-discretionary. Flavoured milks (1 of 20 foods) and flavoured dairy milk substitutes (4 of 12) are mixed.
(c) Includes foods described in AUSNUT 2023 as reduced or no added sugar, as well as those described as intense sweetened, diet or sugar free.
(d) Flavoured water is presented under Bottled water and is also included in Total selected sugar-sweetened beverages / Total selected intense-sweetened beverages.

Appendix B

Number of discretionary foods in selected AUSNUT sub-major food groups

Sub-major groupSub-major groupFoods in groupDiscretionary foodsProportion discretionary
CodeLabelCountCount%
111Tea18844
112Coffee and coffee substitutes501224
114Fruit and vegetable drinks1717100
115Cordials1717100
116Soft drinks2222100
117Electrolyte and energy drinks1313100
118Bottled water12217
119Other beverage flavourings and prepared beverages311961
123Flat breads and savoury or sweet breads561934
125Breakfast cereals, ready to eat871922
131Sweet biscuits5050100
132Savoury biscuits341338
133Cakes, muffins, scones938692
134Pastries876069
135Cereal-based mixed dishes2413012
136Batter-based products271348
141Butters66100
142Dairy blends55100
143Margarine and table spreads1616
145Other fats1212100
146Unspecified fats4250
155Fish and seafood products (homemade and takeaway)38924
156Fish and seafood-based mixed dishes3513
169Mixed dishes where fruit is the major component6233
172Dishes where egg is the major ingredient24313
181Beef, lamb and pork16611
183Poultry7934
185Sausages, frankfurts and saveloys151067
186Processed meat4646100
187Beef, lamb and pork-based mixed dishes1031111
188Sausage, bacon, ham-based mixed dishes5480
189Poultry-based mixed dishes60610
191Dairy milk3226
193Cream1616100
194Cheese56713
195Frozen milk products4444100
196Custards9222
197Other milk-based products191263
198Flavoured milks and milkshakes2015
202Dairy milk substitutes, flavoured12433
203Cheese substitute2150
204Dairy milk substitute, ice confection44100
205Dairy milk substitute, yoghurt10220
206Meat substitutes23417
212Dry soup mix33100
213Soup, prepared from dry soup mix3133
214Canned condensed soup (unprepared)33100
215Soup, commercially sterile or canned8675
216Soup, purchased ready to eat251872
221Seeds and seed products1417
222Nuts and nut products64914
231Gravies and savoury sauces575596
232Pickles, chutneys and relishes151493
233Salad dressings17847
234Stuffings11100
235Dips16744
241Potatoes, chips and other potato products53611
249Dishes where vegetable is the major component7668
252Mature legume and pulse products3213
261Potato snacks1212100
262Corn snacks121192
263Extruded or reformed snacks55100
264Other snacks1313100
271Sugar, honey and syrups3030100
272Jam and other sweet spreads1919100
273Sugar-based mixed dishes (excl. confectionery)2727100
281Chocolate5151100
282Fruit, nut and seed-based confectionery111091
283Fruit, nut and cereal bars and balls2727100
284Other confectionery3131100
301Formulated dietary foods1406949
311Yeast, and yeast vegetable or meat extracts10880
312Intense sweetening agents1313100
313Herbs, seasonings and stocks30723
315Chemical raising agents1517
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