Geospatial dietary indicators

A key strength of the scanner data used in the Apparent Consumption of Selected Foodstuffs (ACSF) is its extensive geographic coverage. In 2023–24, sales data were sourced from more than 4,700 supermarket outlets, with 99.9% of the Australian population living in a Statistical Area Level 3 (SA3) serviced by at least one supermarket. This coverage enables the production of regional estimates of apparent food consumption.

Regional consumption estimates are of particular interest to public health policymakers and researchers seeking to understand how local socioeconomic and geographic factors relate to dietary quality. The ACSF dataset provides a unique opportunity to examine these relationships at scale.

In 2022, the ABS entered a partnership with the Australian Research Data Commons (ARDC) under the Translational Research Data Challenges initiative, contributing to the Food Security Data Challenges project. A key aim of this project is to address gaps in the spatial dimension of food security research. The ABS contributes by enhancing the ACSF dataset and supporting improved data coverage, granularity and infrastructure to enable reporting on food and nutrient consumption across small geographic areas.

The data presented in this article support comparisons across broad geographic groupings, including Socio-Economic Indexes for Areas (SEIFA) and Remoteness Areas. These comparisons highlight how socioeconomic and geographic factors influence dietary quality, which is an important dimension of food security[1]. While ACSF data do not capture household level experiences of food insecurity, they complement findings from the 2023 National Nutrition and Physical Activity Survey (NNPAS). That survey found that 1.3 million households (13.2%) experienced reduced quality, variety or quantity of food – and in some cases skipped meals or went hungry – because they could not afford enough food[2].

All consumption data used in this analysis are presented on a relative consumption basis. Amounts (for example, grams, kilojoules and nutrients) are standardised per 10,000 kilojoules (kJ) of energy purchased.

Standardising to a common energy denominator reduces the influence of differences in the overall volume of supermarket purchases across regions. This reflects variation in the extent to which people source their total dietary intake from local supermarkets.

Consistent with the national ACSF methodology, aggregated geographic units (such as States and Territories, SEIFA quintiles and Remoteness Areas) undergo additional adjustments to account for differences in purchasing patterns across capital cities and the balance of each state or territory. Further detail on concepts and methods is available in the Methodology section.

Most categories of Non-alcoholic beverages displayed higher consumption in more disadvantaged areas. Compared to the least disadvantaged quintile, consumption of:

• Soft drinks was 54% higher in the most disadvantaged quintile (233 grams per 10,000 kJ compared to 151 grams)
• Bottled water was 50% higher in the most disadvantaged quintile (203 grams compared to 136 grams)
• Fruit and vegetable juices and drinks was 16% higher in the most disadvantaged quintile (61 grams compared to 53 grams)
• Cordials had the steepest relative gradient, with consumption 61% higher in the most disadvantaged quintile (10.0 grams compared to 6.2 grams).

The Sugar-sweetened beverages group is composed of the sugar-sweetened products from the Non-alcoholic beverages group (i.e. excluding water, zero sugar products and 100% juice products).

Consumption of Sugar-sweetened beverages followed a steeper SEIFA gradient than for any of the overall Non-alcoholic beverages categories. In 2023–24, consumption of Sugar-sweetened beverages was highest in the most disadvantaged quintile (205 grams per 10,000 kJ) – 77% higher than in the least disadvantaged quintile (115 grams).

In 2023–24, consumption of Cereals and cereal products (primarily comprising grain and cereal products such as bread, rice, flour, pasta and breakfast cereals) had a moderate inverse association with SEIFA. Consumption was lowest in the most disadvantaged quintile (145 grams per 10,000 kJ) and higher in each successive quintile, peaking at 153 grams per 10,000 kJ in the least disadvantaged quintile.

While consumption of most contributing categories within Cereals and cereal products followed a similar SEIFA pattern, bread was the exception.

• Bread consumption (Regular breads and bread rolls and Flat breads and savoury or sweet breads combined) was highest in the second and third quintiles at 79 grams per 10,000 kJ.
• The lowest bread consumption was seen in the fifth quintile (least disadvantaged) at 74 grams per 10,000 kJ.

Among the other categories of Cereals and cereal products, the least disadvantaged quintile had the highest consumption, with levels around 20% higher than in the most disadvantaged quintile. These included:

• Flour, rice and other grains – the least disadvantaged quintile had the highest consumption (42 grams per 10,000 kJ), 20% greater than consumption in the most disadvantaged quintile (35 grams)
• Pasta and noodles – consumption in the least disadvantaged quintile was 19% higher than the most disadvantaged quintile (21 grams compared to 18 grams)
• Breakfast cereals – consumption in the least disadvantaged quintile was 19% higher than the most disadvantaged quintile (15.1 grams compared to 12.7 grams).

The total amount of ‘Grains and cereals’ as defined in the Australian Dietary Guidelines (which defines the five food groups excluding discretionary sources) shows a steeper SEIFA gradient than the major food group. Consumption of ‘Grains and cereals’ was 12% higher in the least disadvantaged quintile compared to the most disadvantaged (252 grams per 10,000 kJ compared with 225 grams).

In contrast to the Cereals and cereal products group, the Cereal-based products group represents a wide variety of savoury and sweet products that are characterised by a greater level of processing and the presence of other ingredients. Although contributing less weight to the diet than Cereals and cereal products, these products are more often discretionary foods, generally higher in added sugars, saturated fat and sodium.

Consumption of Cereal-based products was associated with greater disadvantage. In 2023–24:

• Pastries (pies and sausage rolls being the largest constituents) had the greatest consumption in the most disadvantaged quintile (17.8 grams per 10,000 kJ) – 18% higher than in the least disadvantaged quintile (15.1 grams)
• consumption of Cakes, muffins and scones was 20% higher in the most disadvantaged quintile than in the least disadvantaged quintile (10.1 grams compared to 8.4 grams)
• consumption of Cereal-based mixed dishes (mostly pasta dishes and pizza) was highest in the second most disadvantaged quintile at 15.2 grams per 10,000 kJ – 9% higher than in the least disadvantaged quintile (13.9 grams)
• Sweet biscuits had the highest consumption in the most disadvantaged quintile (16.9 grams) – 17% higher than the least disadvantaged quintile (14.5 grams).

In contrast to the pattern of all other constituents of the Cereal-based products group, Savoury biscuits consumption was associated with less disadvantage – the highest consumption was recorded in the least disadvantaged quintile (9.8 grams per 10,000 kJ), which was 13% more than in the most disadvantaged quintile (8.7 grams).

In 2023–24, Dairy milk (plain and flavoured dairy milk combined) made up over 70% of the weight of the Milk products consumed.

• Dairy milk consumption was 15% higher in the most disadvantaged quintile than in the least disadvantaged quintile (241 grams per 10,000 kJ compared to 210 grams).
• A greater proportion of Dairy milk consumed in the least disadvantaged quintile was classed as reduced fat or skim milk (32%) compared to the most disadvantaged quintile (22%).

Dairy milk substitutes (soy, oat and nut-based products) are classified separately in the AUSNUT classification. In the least disadvantaged quintile, consumption of these milk alternatives was 67% higher than in the most disadvantaged quintile (26 grams per 10,000 kJ compared to 16 grams).

Among the other Milk products, consumption of:

• Yoghurt was highest in the least disadvantaged quintile (34 grams per 10,000 kJ), which was 42% higher than in the most disadvantaged quintile (24 grams)
• Cheese was also highest in the least disadvantaged quintile (26 grams) – 16% higher than in the most disadvantaged quintile (23 grams)
• Frozen milk products (over 95% of which was ice cream) was relatively flat across SEIFA quintiles – the highest consumption was in the second-most disadvantaged quintile (20 grams per 10,000 kJ), just 5% higher than in the least and second-least disadvantaged quintiles (both 19 grams)
• Cream was also highest in the second-most disadvantaged quintile (8.9 grams) – 17% higher than in the least disadvantaged quintile (7.6 grams).

Summarising the non-discretionary amounts of ‘Milk, yoghurt, cheese and/or alternatives’ as defined in the Australian Dietary Guidelines, consumption of these products was 6% higher in the most disadvantaged quintile compared to the least disadvantaged (297 grams per 10,000 kJ compared with 281 grams).

With the exception of Potatoes, each of the other Vegetable products categories were consumed in greater amounts in each successive SEIFA quintile (decreasing disadvantage). In 2023–24, these included:

• Other fruiting vegetables – consumption in the least disadvantaged quintile was 53% higher (60 grams per 10,000 kJ) than the most disadvantaged quintile (39 grams)
• Tomato and tomato products – consumption was 41% higher in the least disadvantaged quintile than in the most disadvantaged quintile (33 grams compared to 23 grams)
• Carrot and similar root vegetables – consumption in the least disadvantaged quintile was 34% higher than the most disadvantaged quintile (30 grams compared to 23 grams)
• Cabbage, cauliflower and other brassica – consumption was 54% higher in the least disadvantaged quintile than in the most disadvantaged quintile (19 grams compared to 13 grams).

The Potatoes category showed a different pattern. Total Potatoes consumption was 14% higher in the two most disadvantaged quintiles (both 49 grams per 10,000 kJ) than in the least disadvantaged quintile (43 grams). However, this difference was driven largely by discretionary products such as chips, wedges and hash browns. Consumption of potato products was 34% higher in the most disadvantaged quintile than in the least disadvantaged, whereas consumption of regular potatoes was only 6% higher.

Based on the food groups defined in the Australian Dietary Guidelines (which excludes discretionary food), ‘Vegetables and legumes/beans’ consumption was 31% higher in the least disadvantaged quintile compared to the most disadvantaged (227 grams per 10,000 kJ compared with 174 grams).

Consumption of most Fruit products categories was greatest in the least disadvantaged quintile and smallest in the most disadvantaged quintile. In 2023–24, these included:

• Tropical and subtropical fruit (over 80% of which was bananas) – consumption in the least disadvantaged quintile was 36% higher than the most disadvantaged quintile (54 grams per 10,000 kJ compared to 40 grams)
• Apples and pears – consumption was 42% higher in the least disadvantaged quintile than in the most disadvantaged quintile (32 grams compared to 22 grams)
• Citrus fruit – consumption in the least disadvantaged quintile was 49% higher than the most disadvantaged quintile (26 grams compared to 17 grams)
• Berry fruit – consumption was 79% higher in the least disadvantaged quintile than in the most disadvantaged quintile (24 grams compared to 14 grams).

Based on the food groups defined in the Australian Dietary Guidelines (counting fruit from all non-discretionary sources), ‘Fruit’ consumption was 33% higher in the least disadvantaged quintile compared to the most disadvantaged (239 grams per 10,000 kJ compared with 180 grams).

Overall, Meat and poultry products consumption was less strongly associated with SEIFA quintile than many other food groups, but among the contributing sub-major food groups there were some notable patterns. In particular, Poultry was the only category for which consumption increased with lower disadvantage.

In 2023–24:

• consumption of Poultry was 8% higher in the least disadvantaged quintile than in the most disadvantaged quintile (58 grams per 10,000 kJ compared to 54 grams)
• in contrast, consumption of Poultry-based mixed dishes (such as chicken nuggets, schnitzel, and Kiev) was 31% higher in the most disadvantaged quintile than in the least disadvantaged quintile (16 grams compared to 12 grams).

Among other Meat products in 2023–24 were:

• Beef, lamb and pork – this was the second most consumed category (after Poultry) and the consumption level by quintile was relatively flat, ranging from 50 grams per 10,000 kJ in the first quintile (most disadvantaged) to 53 grams per 10,000 kJ in in the second, fourth and fifth quintiles
• Processed meat – consumption was 36% higher in the most disadvantaged quintile than in the least disadvantaged quintile (22 grams per 10,000 kJ compared to 16 grams)
• Sausages, frankfurts and saveloys – consumption in the most disadvantaged quintile was 40% higher than in least disadvantaged quintile (14 grams compared to 10 grams).

Summarising the non-discretionary amounts of ‘Meats, poultry, fish, eggs, tofu, nuts and seeds and legumes/beans’ as defined in the Australian Dietary Guidelines shows a clearer SEIFA gradient. Consumption of ‘Meats, poultry, fish, eggs, tofu, nuts and seeds and legumes/beans’ was 16% higher in the least disadvantaged quintile compared to the most disadvantaged (166 grams per 10,000 kJ compared with 143 grams).

Consumption of Fish and seafood products was mostly associated with increasing SEIFA quintile. In 2023–24:

• Fin fish (excluding canned fish) consumption was 85% higher in the least disadvantaged quintile compared to in the most disadvantaged quintile (7.4 grams per 10,000 kJ compared to 4.0 grams)
• Packed (commercially sterile) fish consumption was 17% higher in the least disadvantaged quintile compared to in the most disadvantaged quintile (6.2 grams compared to 5.3 grams)
• Seafood products (such as battered fish and fish fingers) had 17% higher consumption in the most disadvantaged quintile than the least disadvantaged quintile (3.5 grams compared to 3.0 grams).

Potato snacks and Corn snacks comprised the majority of Snack foods, and consumption of these products in 2023–24 diverged in their SEIFA association.

• Potato snacks consumption was 14% higher in the most disadvantaged quintile than in the least disadvantaged quintile (11.4 grams per 10,000 kJ compared to 10.0 grams).
• Corn snacks consumption was 13% higher level in the least disadvantaged quintile than in the most disadvantaged quintile (5.1 grams compared to 4.5 grams).

Confectionery products (particularly chocolate and muesli/snack bars) were consumed in greater quantities by the least disadvantaged quintiles. In 2023–24:

• Chocolate consumption was 12% higher in the least disadvantaged quintile than in the most disadvantaged quintile (21 grams per 10,000 kJ compared to 18 grams)
• Muesli/cereal bars consumption was 23% higher in the least disadvantaged quintile than in the most disadvantaged quintile (5.3 grams compared to 4.3 grams)
• Other confectionery products (mainly lollies) were consumed in relatively similar amounts across SEIFA quintiles, between 9.1 grams per 10,000 kJ in the first quintile (most disadvantaged) and 9.4 grams per 10,000 kJ in in the second quintile.

Among butter and margarine products in 2023–24:

• Margarine and Dairy blends consumption combined was 57% higher in the most disadvantaged quintile compared to the least disadvantaged (9.4 grams per 10,000 kJ compared to 6.0 grams)
• Butters consumption was 22% higher in the least disadvantaged quintile than in the most disadvantaged quintile (5.0 grams compared to 4.1 grams).

Total Plant oils consumption was 8% higher in the most disadvantaged quintile than for Australia overall (12.1 grams per 10,000 kJ compared to 11.2 grams). However, the SEIFA pattern at this broad level was obscured by contrasting consumption gradients for the different categories of Plant oils.

When grouped into three broad categories and an ‘other plant oils’ group, there are contrasting gradients between olive oil and other oils. In 2023–24:

• Olive oil consumption was 54% higher in the least disadvantaged quintile than in the most disadvantaged quintile (5.5 grams per 10,000 kJ compared to 3.6 grams)
• Canola oil consumption was 78% higher in the most disadvantaged quintile than in the least disadvantaged quintile (3.6 grams compared to 2.0 grams)
• Sunflower and vegetable oil were 49% higher in the most disadvantaged quintile than in the least disadvantaged quintile (4.1 grams compared to 2.8 grams).

Among other major food groups, there were several products for which the consumption weight differed markedly by SEIFA quintile.

• Eggs had a 27% greater consumption weight in the least disadvantaged quintile compared to the most disadvantaged quintile (26 grams and 20 grams per 10,000 kJ, respectively).
• Nuts were consumed 50% more in the least disadvantaged quintile than in the most disadvantaged quintile (23 grams and 15 grams per 10,000 kJ, respectively).
• Sugar, honey and syrups were consumed at a 47% higher level in the most disadvantaged quintile than in the least disadvantaged quintile (18 grams per 10,000 kJ compared to 12 grams).

Energy from carbohydrate was highest in the most disadvantaged quintile (44.3%) and lowest in the least disadvantaged quintile (43.2%). A breakdown of carbohydrate into starches and sugars shows a diverging pattern across quintiles.

• Starch contributed a slightly higher proportion of dietary energy in the least disadvantaged quintile (22.9%) compared with the most disadvantaged quintile (22.2%).
• Total sugars contributed a greater share of energy intake in the most disadvantaged quintile (21.0%) than in the least disadvantaged quintile (19.0%).

Free sugars is a category of sugar that includes the added sugars added to foods during processing plus the sugar that is naturally present in fruit juice and honey[4]. In 2023–24, free sugars contributed almost 1.3 times as much to dietary energy in the most disadvantaged quintile relative to the least disadvantaged quintile (13.6% compared to 10.7%).

For total fat, the relative contribution to energy by SEIFA quintiles was mostly similar, ranging from 39.1% in the fourth and fifth (least disadvantaged) quintiles, to 39.3% in the third quintile.

The proportion of dietary energy coming from saturated fat was lowest in the least disadvantaged quintile (15.1%) and highest in the second quintile (15.5%).

The proportion of dietary energy from protein was highest in the least disadvantaged quintile (15.7%) and lowest in the most disadvantaged quintile (14.7%).

The contribution of dietary fibre to energy was highest in the least disadvantaged quintile (2.1%) and lowest in the most and second-most disadvantaged quintiles (both 1.8%).

Natural folate (found in vegetable, legumes, cereals and fruit) intakes per 10,000 kJ were 17% higher in the least disadvantaged quintile (342 micrograms) than in the most disadvantaged (293 micrograms).

In contrast, folic acid (the form used in the fortification of bread and flour[5]) had slightly higher consumption in the middle and lower quintiles (between 189 and 191 micrograms).

Folate equivalents (which accounts for the physiologically active amount of folate from all dietary sources) was 5.3% higher in the least disadvantaged quintile than the most disadvantaged quintile (641 micrograms per 10,000 kJ compared to 608 micrograms).

Pro-vitamin A is the collection of carotenoids (plant pigments) commonly found in vegetables, fruits and oils which are precursors to the active form of vitamin A[6]. In 2023–24, pro-vitamin A intake was 30% higher in the least disadvantaged quintile than the most disadvantaged quintile (3,040 micrograms per 10,000 kJ compared to 2,345 micrograms).

The vitamin A (retinol) equivalent was more balanced across quintiles – 13% higher in the least disadvantaged quintile than in the least disadvantaged quintile – due to the inefficient conversion of pro-vitamin A to retinol and the intake of preformed vitamin A (found in animal products) being slightly higher in the most disadvantaged quintile.

Vitamin C intake was 27% higher in the least disadvantaged quintile than in the most disadvantaged quintile (119 milligrams per 10,000 kJ compared to 94 milligrams). The major sources of vitamin C were:

• Fruit and vegetable juices and drinks (19.2% of vitamin C intake)
• Other fruiting vegetables (11.5%)
• Cabbage, cauliflower and other brassica (10.7%)
• Citrus fruit (10.5%).

Long chain omega-3 fatty acids were 33% higher in the least disadvantaged quintile than the most disadvantaged quintile (267 milligrams per 10,000 kJ compared to 200 milligrams).

Greater consumption of Non-alcoholic beverages with increasing remoteness was seen across most categories in 2023–24, with the greatest relative differences in the consumption of:

• Bottled water – 91% higher in Remote areas than Major Cities (313 grams per 10,000 kJ compared to 164 grams)
• Soft drinks – 54% higher in Very Remote areas than Major Cities (284 grams compared to 185 grams)
• Cordials – 138% higher in Very Remote areas than Major Cities (17.4 grams compared to 7.3 grams)
• Electrolyte and energy drinks – 44% higher in Very Remote areas than Major Cities (41 grams compared to 29 grams).

Compared with the Major Cities which consumed an average of 152 grams of Sugar-sweetened beverages per 10,000 kJ, 2023–24 consumption of Sugar-sweetened beverages was:

• 91% higher in Very Remote areas (290 grams per 10,000 kJ)
• 66% higher in Remote areas (252 grams)
• 38% higher in Outer Regional areas (209 grams)
• 19% higher in Inner Regional areas (180 grams).

The greater relative difference between Very Remote areas and Major Cities for consumption of Sugar-sweetened beverages compared to overall Non-alcoholic beverages (91% higher compared to 55% higher) also means that Sugar-sweetened beverages contributed a greater proportion of the overall Non-alcoholic beverages in Very Remote areas (41%) than Major Cities (33%).

While overall Fruit products consumption in 2023–24 was highest in Major Cities (166 grams per 10,000 kJ) and lowest in Outer Regional areas (135 grams), the patterns by Remoteness Areas varied widely by the Fruit products categories. Consumption of:

• Citrus fruit was highest in Very Remote Australia (26 grams per 10,000 kJ) – 55% more than in Outer Regional Australia (lowest with 17 grams), and 19% higher than in Major Cities (22 grams)
• Tropical and subtropical fruit (over 80% of which was bananas) was 27% higher in Major Cities than Remote Australia (48 grams per 10,000 kJ compared to 38 grams)
• Other fruit (mainly melons and grapes) was also highest in Major Cities (34 grams) – 19% higher than in Inner Regional Australia (29 grams)
• Apples and pears was highest in Major Cities (27 grams) – 22% more than the lowest consumption in Remote Australia (23 grams)
• Berry fruit had the largest differences across Remoteness Areas, with consumption in Major Cities being more than twice (or 105% higher) than in Very Remote areas (19 grams per 10,000 kJ compared with 9 grams).

In 2023–24, Dairy milk consumption (plain and flavoured dairy milk combined) was 12% higher in the Inner and Outer Regional areas (both 238 grams per 10,000 kJ) than Very Remote areas (212 grams).

Among other Milk products, the steepest gradient was seen for Yoghurt, with consumption in Major Cities 51% higher than in Very Remote areas (30 grams per 10,000 kJ compared to 20 grams).

Bread consumption (Regular breads and bread rolls and Flat breads and savoury or sweet breads combined) peaked in Outer Regional areas at 81 grams per 10,000 kJ – 7% higher than in Major Cities (76 grams per 10,000 kJ).

Among other Cereals and cereal products, consumption of:

• Rice was 87% higher in Major Cities than Inner Regional areas (25 grams per 10,000 kJ compared to 13 grams)
• Flour was more than twice as high (or 129% higher) in Very Remote areas than Outer Regional areas (23.4 grams per 10,000 kJ compared to 10.2 grams)
• Pasta and noodles was 79% higher in Major Cities than Very Remote areas (15.9 grams compared to 8.9 grams)
• Instant noodles was almost twice as high (or 95% higher) in Very Remote areas as Inner Regional areas (7.9 grams compared to 4.1 grams).

Consumption of Cereal-based products contrasted by broad product groupings. In 2023–24, consumption of:

• Biscuits, cakes and pastry products (combined) was 23% higher in the Inner Regional areas than Very Remote areas (55 grams per 10,000 kJ compared to 45 grams)
• Cereal-based mixed dishes was 41% higher in Very Remote areas than Major Cities (20 grams compared to 14.2 grams), with much of this difference resulting from greater consumption of pizza and canned spaghetti in Very Remote areas.

Among Meat and poultry products in 2023–24, the greatest relative differences in consumption were seen in:

• Processed meat – consumption was 75% higher in Very Remote areas than Major Cities (31 grams per 10,000 kJ compared to 18 grams)
• Sausages, frankfurts and saveloys – consumption was 50% higher in Very Remote areas than Major Cities (18 grams compared to 12 grams).

In 2023–24, overall Fish and seafood products consumption decreased with increasing remoteness – from 18.7 grams per 10,000 kJ in Major Cities to 11.8 grams in Very Remote areas.

Among Fish and seafood products categories, the largest relative differences in consumption were for:

• Fin fish (excluding canned) – consumption in Major Cities was over three times greater than in Very Remote areas (6.0 grams per 10,000 kJ compared to 1.8 grams)
• Crustacea – Major Cities had 2.2 times the level of consumption in Very Remote areas (2.9 grams compared to 1.3 grams).

In 2023–24, the consumption patterns of Snack foods and Confectionery products across Remoteness Areas varied by product type, but the greatest relative differences were seen in consumption of:

• Muesli/cereal bars – consumption was 61% higher in Major Cities than Very Remote areas (5.0 grams per 10,000 kJ compared to 3.1 grams)
• Corn snacks – consumption was 22% higher in Major Cities than Remote areas (4.9 grams compared to 4.0 grams)
• Chocolate – consumption was 14% higher in Inner Regional areas than in Very Remote areas (20.1 grams compared to 17.6 grams).

In 2023–24, free sugars contributed an increasing share of dietary energy with increasing remoteness – increasing from 11.8% in Major Cities to 14.5% in Very Remote areas. This is consistent with the trend for Sugar-sweetened beverages consumption.

In 2023–24, calcium intakes peaked in Inner Regional areas (891 milligrams per 10,000 kJ) but generally decreased with remoteness with Very Remote areas being lowest at 814 milligrams per 10,000 kJ.

In 2023–24, sodium intakes were high throughout all Remoteness Areas but peaked in Very Remote areas at 3,612 milligrams per 10,000 kJ. This was between 4-6% higher than other regions.

In 2023–24, iodine intakes were highest in Major Cities (184 micrograms per 10,000 kJ) and lowest in the Remote and Very Remote areas (both 170 micrograms). The food sources contributing most to iodine intakes were dairy milk and iodised table salt.

In 2023, long chain omega-3 fatty acid intakes were considerably higher in Major Cities at 237 milligrams per 10,000 kJ. This was 15% higher than Inner Regional areas (206 milligrams) and 35% higher than Very Remote areas (175 milligrams). This is consistent with consumption of Fish and seafood products (which were a leading source of omega-3) decreasing with increasing remoteness.

For the majority of the supermarket chains, the weekly sales data supplied to ABS were provided at the individual store level, but in all cases, sales data were accompanied by relational datasets that include the name and location of the individual contributing stores. This information was used to geocode each participating supermarket to a Statistical Area Level 2 (SA2). SA2s are the third level in the main structure of the Australian Statistical Geographic Standard (ASGS) with each level being the aggregate of the units below. For example, the SA2s are aggregates of SA1s, which in turn are comprised of mesh blocks (the base level). 

For the purpose of this project, SA2 was considered the most pragmatic geographic unit to use because while fairly small (they often equate to a suburb in urban areas) they can be directly aggregated into other areas such as Socio-Economic Indexes for Areas (SEIFA), Remoteness Areas, as well as higher level geographies (SA3, SA4 and State/Territory).

For the minority of weekly sales that were not supplied at store level, ABS obtained a customised data extract of store level sales for the 2020–21 period to construct a pro-rata distribution model of SA2 sales from SA4 sales. The model derived a weight fraction (proportion of total tonnes) of each AUSNUT-coded food product for each constituent SA2 from the parent SA4. In cases where new stores were operating in 2023–24 that were not present in 2020–21, the 2020–21 SA4 to SA2 relationship was assumed to have been maintained. An exception to this assumption was when the SA2 had a store operating in 2023–24 that did not have a store in 2020–21. In these cases, the new SA2 was assigned the product distribution pattern equivalent to the SA4 to which it belongs, with the weight of the distribution based on the numerical representation of that SA2 among the total number of SA2s from the SA4.

As noted in the Estimation section of the ACSF Methodology notes, the estimates of apparent consumption are adjusted to account for food products obtained from stores that are beyond the scope of the supermarket scanner data (e.g. grocers and convenience stores). This adjustment is based in part on the ratio of food product expenditure between the major supermarkets and all food retail by areas and is derived from the 2015–16 Household Expenditure Survey (HES), and is applied at the Greater Capital City Statistical Area (GCCSA) level.

Adjusting at the GCCSA level is a limitation of the 2015–16 HES sample design which was not intended to support reliable estimates at smaller geographic areas (SA2, SA3 or SA4). Consequently, the coverage adjustment in this project has only been applied to larger aggregates – specifically State and Territory, SEIFA quintiles, and Remoteness Areas – and not to SA3 or SA4.

Applying the coverage adjustment at higher levels of aggregation, but not to individual the SA3s and SA4s has two broad implications for comparability:

1. Estimates within and between SEIFA quintiles, Remoteness Areas, and States and Territories are expected to be more comparable and less biased than unadjusted scanner-based estimates, as the adjustment accounts for food purchases from non-supermarket retailers.
2. SA3 and SA4 estimates are based solely on sales from in-scope supermarkets. As a result, these estimates should be interpreted with caution, as consumption patterns may be biased in areas where non-supermarket food retail plays a relatively larger role.

While the application of the coverage adjustment helps to compensate for varying propensities to shop for certain food products at supermarkets, it remains a broad adjustment that cannot account for supermarket purchasing patterns in specific areas. In addition, the per capita overall amounts of foods (e.g. total dietary energy) obtained from supermarkets and other food retail will vary with other geographic and socioeconomic characteristics. For example, households in one particular region may purchase more or less of their overall dietary intakes from supermarkets than households from another region depending on factors such as life stage, income and the availability of dining options such fast food, restaurants and clubs.

One way of overcoming the differences in levels of consumption and thus allowing direct comparisons among areas is to standardise the consumption to a relative base. In this project, apparent consumption is presented in amounts (such as mg, g, mL, kilojoules) per 10,000 kJ. The selection of amount per 10,000 kJ was based on:

• dietary energy being a well understood physiological requirement (and may be viewed as an energy budget comprised of dietary choices)
• 10,000 kJ is a relatable base because the daily dietary energy consumed by the average adult was around 8,000 kJ according to the latest National Nutrition and Physical Activity Survey (although that is considered an under-estimate due to widespread under-reporting in food recall surveys).

Although the standardised results do not support comparisons of absolute consumption between areas, they provide a clear basis for comparing the composition of dietary intake. This enables the published data to be used to assess dietary quality by examining indicators such as the relative amounts of food groups or key nutrients.

The supermarkets included in the 2023–24 scanner dataset provide sales information across all regions of Australia. Approximately 85% of the June 2023 ERP live in an SA2 with at least one contributing supermarket, and over 99% of the population reside in an SA3 with at least one supermarket.

Despite this broad coverage, two general limitations are:

1. the extent to which people do supermarket shopping in a different area to where they live may impact the validity of the results (see the Measuring representativity section)
2. for some geographical areas, confidentiality obligations have necessitated data suppression for the affected areas (see the Confidentiality section).

A key assumption when using area-based sales data to represent the consumption of that area is that people tend to do their supermarket shopping in the same area where they live. However, directly measuring the relationship would require a dataset with both the place of residence of the consumer and the place the consumer made the expenditure. In the absence of such definitive data, representativity can be assessed indirectly by comparing how closely the spatial pattern of supermarket sales aligns with the spatial pattern of the population.

For this project, sales were aggregated from SA2s into higher geographies including SEIFA quintiles, Remoteness Areas and State and Territory level. For these sales aggregates to meaningfully represent the populations who live there, the distribution of sales across smaller areas (e.g. SA2s) should be reasonably consistent with the distribution of the population. Correlation coefficients between these distributions were used to assess this alignment.

At the SA2 level, the correlation between the distribution of population and supermarket expenditure within each SA3 was 0.70 nationally, indicating a moderately positive relationship. Given that 15% of the population live in SA2s without a contributing supermarket, this level of correlation suggests reasonable alignment. Correlations were lower in Tasmania (0.52), the Northern Territory (0.43), and the Australian Capital Territory (0.21), reflecting a greater imbalance between the SA2s where people live and where supermarkets sales occur.

At the SA3 level, correlations within each SA4 were greater than 0.90 in every state and territory. This strong alignment is expected, as nearly all SA3s contain one or more supermarkets, reducing the impact of the uneven distribution of stores across SA2s.

Despite the general alignment between supermarket sales and population distribution at the SA3 level, some regions were still found to have data gaps. For some regions the data gap is a consequence of missing data, in others it may result from the major supermarkets not operating in certain areas.

One simple indicator of coverage is the number of supermarket stores (providing data) per 100,000 population. It is important to note that although this indicator is relevant to the representation in this project, it is not necessarily indicative of the true supermarket service level because of the difference between the number of stores operating in an area and the number for which sales data was supplied.

Compared to the national average of 17.7 supermarkets per 100,000 population, the 2023–24 coverage in Tasmania was just over half that level (9.1 stores per 100,000 population).

In addition to the data quality impact, the lower representation also necessitates further data suppression throughout Tasmania due to the concentration of sales from the remaining data providers (discussed further below). For this reason, the estimates from Tasmania at SA3, SA4 and State level were deemed unpublishable from both a confidentiality and data validity view. However, sales from Tasmania are still used to contribute to the SEIFA, Remoteness Areas and national level aggregates.

For the Northern Territory, the remote areas between Alice Springs and Darwin have very few major supermarket chains operating (although there are independently operated stores in those areas). As with Tasmania, where sales were not suitable for publishing at Statistical Area level, the sales were still used to contribute to higher geographical aggregates such as SEIFA, Remoteness Areas and the national level.

As the institution responsible for providing official statistics for Australia, the ABS operates within a legislative framework that seeks to maximise the dissemination of information while ensuring that information is not released in a way that is likely to enable individuals or organisations to be identified. In line with this legislative requirement, confidentiality is maintained through the suppression of cells which may pose a disclosure risk.

• At the SA3 level, the disclosure rule determined that 254 SA3s were publishable. This includes the secondary suppression required where there is the potential for differencing from the SA4 level total to the sum of the remaining SA3s. While this represented 77% of the 330 in-scope SA3s, accounting for distribution of the population, the published data represents 90% of the population.
• Among the 88 SA4s with supermarket sales, 81 (92%) were publishable.
• At the State and Territory level, data for Tasmania required suppression consistent with the SA3 and SA4 level disclosure across the state.

Socio Economic Indexes for Areas (SEIFA) and Remoteness Areas are both broad, aggregated geographic classifications, but they differ substantially in how they are constructed and what they represent.

SEIFA quintiles are designed to represent a roughly equal share of the population – about 20% in each quintile – based on the distribution of relative socioeconomic disadvantage. Because SEIFA quintiles are population balanced, comparisons across quintiles inherently reflect groups of similar population size, facilitating distributional analysis that is not distorted by large differences in population counts.

Remoteness Areas, by contrast, are designed to represent geographic access to services. Each area in Australia is grouped to one of five categories (from Major Cities to Very Remote) based on the detailed Accessibility and Remoteness Index of Australia Plus (ARIA+). As a result, the population distribution across these areas is highly skewed towards the urban areas. In 2023, around 90% of the resident population and 90% of the food sales from scanner data were from the Major Cities and Inner Regional areas. In contrast, the Remote and Very Remote areas represent less than 2% of the population.

Results for Very Remote Australia should be interpreted with particular caution. These areas account for less than one percent of the national population, and food purchasing patterns may differ substantially because small independent stores which play an important role in Very Remote communities are not included in the scanner data.

Across Remoteness Areas, the SEIFA profile of food sales becomes progressively skewed toward greater socioeconomic disadvantage. In Major Cities, the two most disadvantaged quintiles (the first and second quintiles) together account for 31% of food sales. In contrast, these quintiles represent 76% of sales in Remote areas and 61% in Very Remote areas.

This strong association between increasing Remoteness and higher levels of disadvantage indicates that analyses of food consumption by Remoteness Area are likely to be confounded by SEIFA, with disadvantage tending to increase as areas become more remote.

Independent of SEIFA, differing age structures of Remoteness Areas provides additional context for interpreting results. Inner Regional and Outer Regional areas have older populations with around 22% aged 65 years and over. By contrast, Remote and Very Remote areas skew younger, with higher proportions of children (19% and 21% under 15 years) and fewer older people (18% and 11% aged 65+). While the three largest regions (Major Cities, Inner Regional, Outer Regional) have similar shares of children (17–18%), compared to the Regional Areas, Major Cities have a smaller representation of people aged 65 years and over (16% compared to around 22%).