In 2019, FSANZ undertook an analytical program commissioned by the Australian Bureau of Statistics to improve and expand the nutrient dataset to support the upcoming 2023 National Nutrition and Physical Activity Survey (NNPAS). Twenty-nine foods were selected for nutrient analysis based on whether:
- they were new to the market and no nutrient composition data was available
- they were commonly consumed in the previous national nutrition survey
- they were likely to contribute significantly to population nutrient intakes
- the data held by FSANZ were out-dated or limited and unlikely to reflect the products currently available for consumption.
The nutrients selected to be analysed differed for each food depending on what data was available, the quality of the data, and whether the nutrient was likely to be present in the food.
Sampling
Eight samples were purchased for each food, with the exception of protein powder of which four samples were purchased. The foods were sampled across five states and territories (Australian Capital Territory, Queensland, Victoria, South Australia and Western Australia) to provide a range of production locations. For some samples, multiple items were required to ensure an appropriate sample weight was obtained (i.e. one sample of snack bars may have included 2- 8 items).
Sampling was carried out by FSANZ and the National Measurement Institute (NMI). All food purchases were made within capital city and metropolitan areas to represent the buying habits of the majority of the community. Food purchases were made at a range of retail outlets including supermarkets, butchers and health food stores. If more than one sample of the same brand was purchased, different batch codes or use by dates were selected where possible.
The complete list of foods selected for analysis is available in Table 1.
Table 1: Foods analysed in the NNPAS analytical program
Foods | No. of samples purchased (no. of items purchased*) | No. of brands/varieties |
---|---|---|
Beverages | ||
Flat white/latte/cappuccino, regular fat cow's milk | 8 (8) | 8 |
Kombucha | 8 (11) | 7 |
Tea, black | 8 (8) | 5 |
Water, coconut | 8 (12) | 5 |
Cereal products | ||
Breakfast cereal, All bran | 8 (8) | 1 |
Muesli, granola | 8 (8) | 6 |
Muesli, non-oat based | 8 (8) | 8 |
Porridge, cooked with water | 8 (8) | 5 |
Yoghurts | ||
Yoghurt, dairy, added cream, approx 6% fat, flavoured | 8 (13) | 2 |
Yoghurt, dairy, approx 2% fat, flavoured | 8 (18) | 2 |
Yoghurt, dairy, flavoured, 0.2% fat, 10% protein, intense sweetened | 8 (17) | 5 |
Yoghurt, almond, flavoured, sweetened | 8 (13) | 8 |
Yoghurt, coconut, flavoured, sweetened | 8 (13) | 8 |
Snack bars | ||
Snack ball, date/fruit base | 8 (17) | 8 |
Snack bar, nut-based | 8 (30) | 4 |
Snack bar, protein-based | 8 (13) | 7 |
Snack bar, oat based, baked | 8 (11) | 4 |
Poultry and pork | ||
Chicken, breast, raw | 8 (8) | 8 |
Chicken, breast, dry fried | n/a | n/a |
Chicken, mince, raw | 8 (8) | 8 |
Pork, belly, raw | 8 (8) | 8 |
Meat alternatives | ||
Meat alternative, legume and/or vegetable base | 8 (8) | 7 |
Meat alternative, Mycoprotein/fungus base | 8 (8) | 4 |
Meat alternative, protein (soy/wheat/pea) base | 8 (10) | 7 |
Tofu, firm | 8 (10) | 5 |
Other | ||
Pasta sauce, tomato based, commercial | 8 (10) | 6 |
Pasta sauce, cheese/cream based, commercial | 8 (10) | 7 |
Dip, hummus | 8 (11) | 6 |
Protein powder, unfortified | 4 (4) | 4 |
*In some instances, multiple items must be purchased to reach the required weight of 500 g per sample.
Preparation and analysis
The samples were delivered by hand or sent by courier to NMI. Once received, the samples were photographed and copies were provided to FSANZ for approval prior to analysis.
NMI prepared samples according to the sample preparation procedures provided by FSANZ. Each sample was weighed (before and after preparation where appropriate), homogenised and combined to form one composite sample. Nutrients analysed in this program are listed in Table 2.
NMI conducted the analyses at their Melbourne laboratories. Methods of analysis used have been accredited by the National Association of Testing Authorities.
Table 2: Nutrients analysed in the NNPAS analytical program
Proximates | Vitamins | Minerals | Other |
---|---|---|---|
Moisture | Carotenes (α and β) | Aluminum | Fatty acid profile |
Protein | Cryptoxanthin | Arsenic | Cholesterol |
Fat | Retinol | Calcium | Tryptophan |
Starch | Thiamin (Vitamin B1) | Copper | Caffeine |
Sugar profile | Riboflavin (Vitamin B2) | Iodine | Ethanol |
Total dietary fibre | Niacin (Vitamin B3) | Iron | |
Ash | Pyridoxine (Vitamin B6) | Lead | |
Organic acids | Cobalamin (Vitamin B12) | Magnesium | |
Pantothenic acid (Vitamin B5) | Manganese | ||
Total folates | Molybdenum | ||
Free folates | Phosphorus | ||
Ascorbic acid (Vitamin C) | Potassium | ||
Tocopherols (α, β, γ and δ) | Selenium | ||
Sodium | |||
Zinc |
Results
FSANZ validated the results using our existing analytical data, food labels (ingredient lists and nutrition information panels) where available, and data from international food composition databases for similar foods.
The majority of results were consistent with previous findings. A small number of analytes in some foods showed levels outside the expected range. These food samples were reanalysed by the laboratory, and all results were verified and accepted. A key finding from this program was the calcium value for tofu which was lower than previously analysed data, reflecting a change in firming agents used in the products from calcium chloride to magnesium chloride.
For the complete set of results generated from this program refer to:
Conclusion
The results of this analytical program have filled some important data gaps and given us an improved level of confidence about the composition of these foods which contribute to population nutrient intakes. The results will feed into the nutrient survey database which will support the National Nutrition and Physical Activity Survey. In addition, the results will feed into all other future releases of FSANZ published databases, including the Australian Food Composition Database.