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Food composition databases for nutrition labelling: Experience from Australia
Journal of Food Composition and Analysis 24 (2011) 682–685
Contents lists available at ScienceDirect
Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Report
Food composition databases for nutrition labelling: Experience from Australia J. Cunningham *, R. Sobolewski Food Standards Australia New Zealand, PO Box 7186, Canberra BC, ACT 2610, Australia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 4 November 2009 Received in revised form 4 June 2010 Accepted 5 July 2010 Available online 13 November 2010
Food composition databases prepared for nutrition labelling have some important differences to other food composition databases. Nutrient values must be expressed in accordance with legal requirements for nutrition labelling in the country where it will be used. The database should include all the nutrients that must be declared in labels and contain data for ingredients (including additives) used in manufacturing. Data should be as current as possible and it may be necessary to update the databases before release. Information on typical measures, indicative weight changes during processing and retention factors (if including vitamins and minerals) will be required, as will explanatory material appropriate to the audience. Challenge areas for use of a labelling database include foods prepared by soaking or packing in salt or by deep frying, and estimation of vitamin levels. Limited Australian and New Zealand research suggests that label and analytical data for proximate nutrients, fatty acids and sodium agree in around 60% of cases or more; for added micronutrients, no more than 50% of values agree. However there is no research available to show whether labels prepared from a labelling database are more or less accurate than labels prepared using analysis. The Australian experience shows that it is possible to develop a labelling database suitable for many, but not all, foods and nutrients, but there is a lack of information to assess the quality of the data produced. Crown Copyright ß 2010 Published by Elsevier Inc. All rights reserved.
Keywords: Nutrition labelling Food composition databases Australia Vitamins Legal requirements Manufacturing
1. Introduction Food Standards Australia New Zealand (FSANZ) is a binational government agency that establishes standards for the composition and labelling of foods sold in Australia and New Zealand. Although there is a binational food standards system, the two countries have separate food composition tables. In New Zealand, the national food composition tables are prepared by Plant & Food Research New Zealand. FSANZ manages the Australian food composition tables and the two countries work closely on food composition activities. Australia’s national food composition tables are called NUTTAB (FSANZ, 2007) and are available on-line and free of charge. Nutrition information panels have been mandatory for almost all packaged foods in Australia and New Zealand since late 2002 after a two year phase-in period. Energy and six nutrients (protein, total fat, saturated fat, total carbohydrate, total sugars and sodium) must be included in panels. Nutrient values must be presented per 100 g of the food and per serving, using no more than three significant figures. Other nutrients must be included in panels if specific claims are made about them in relation to that food (FSANZ, 2009a). Tolerance limits are not established.
* Corresponding author. Tel.: +61 2 6271 2213; fax: +61 2 6271 2278. E-mail address: [email protected] (J. Cunningham).
At the time mandatory nutrition labelling was introduced, there was considerable concern about the high cost of direct analysis of foods (NFO Donovan Research, 2002). Therefore in 2001 FSANZ launched an on-line product called the Nutrition Panel Calculator (NPC) to help Australian companies, particularly small companies, prepare for the introduction of mandatory nutrition labelling. The NPC is the most visited part of the organisation’s website, with more than 110,000 visitors in July 2009 alone. The NPC has two main parts – software that helps users to calculate the nutrients in their product based on its formulation, and a nutrient database. Feedback from users has been very positive and it has been an important factor in the successful introduction of mandatory nutrition labelling. Initial experience with providing the NPC itself was reviewed in 2004 (Cunningham et al., 2004). The purpose of this paper is to review the Australian experience in developing a food composition database for nutrition labelling purposes and to identify areas where such a database presents particular challenges. 2. Purpose of nutrition labelling and the role of labelling databases The Codex Alimentarius Guideline on Nutrition Labelling (CAC/ GL 2-1985, Codex Alimentarius, 2007) identifies a number of aims for nutrition labelling of foods. Apart from providing consumers with information to facilitate the choice of healthy food, nutrition
0889-1575/$ – see front matter . Crown Copyright ß 2010 Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jfca.2010.07.002
J. Cunningham, R. Sobolewski / Journal of Food Composition and Analysis 24 (2011) 682–685
labelling should ensure that a food is not described in a manner that is false, misleading, deceptive or insignificant. This suggests that the data contained in a food composition labelling database must be of high quality and sufficiently comprehensive that any results derived from its use are representative and reliable. However at the same time, it is important to recognise the innate variability in nutrient levels in foods (Greenfield and Southgate, 2003) and the uncertainty that is associated with sampling and analysis of foods (EURACHEM/CITAC, 2007) such that a nutrition label, however it is derived, will never be a perfect representation of the nutrient levels actually present in a food when it is consumed. This is recognised in the Codex Guideline where it is recommended that values used in label declarations should be weighted average values derived from data which are representative of the product being labelled and that tolerance limits should be set taking into account processing variability, inherent lability and variability of nutrients, among other factors (Codex Alimentarius, 2007). A well designed food composition database for labelling purposes can have the following roles: 1. As an alternative to direct analysis, where this is permitted in legislation. Using a database rather than direct analysis will generally be cheaper as it avoids the need for sample collection and expensive analysis and it will be quicker as it can be done immediately rather than waiting for laboratories to do their work. It also helps where laboratory capacity is limited in a region. 2. To provide guidance on when nutrients will be present at insignificant levels. Even in situations where direct analysis is required for most nutrients, analysis may not be necessary for those nutrients likely to be present at insignificant levels. Reference to a database will allow companies to identify where this is likely to be the case and to focus their resources on analysis of remaining nutrients. 3. To provide guidance on when a formulation change will affect nutrient levels. Formulations of manufactured foods can change regularly. For example, new colours may be used, salt levels may be reduced or oil type changed. Some of these changes will have no significant effect on the food’s nutrient profile and a labelling database can provide information that helps companies to decide whether or not the change warrants further analyses. 4. To assist with assessment of analytical results. It can be helpful for companies to cross check analytical results they have received against data for the same or similar foods in food composition tables as one step in assessing their own analytical data. This can help companies to identify major errors in data they have received. 5. To assist with exports. Even if countries require direct analysis of foods for labelling purposes, manufacturers may also be exporting products to other countries, such as Australia, that do allow the use of nutrient databases for label preparation; in this case a labelling database can be used to prepare nutrient data for a country-specific product formulation. Australia’s NPC was only designed for use with foods sold in Australia and New Zealand but we have had requests for assistance from companies that export food from Australia and wish to meet nutrition labelling requirements in other countries. 3. Features of a labelling database The features of a food composition database are determined by the purpose of the database. The purpose of a food composition database for nutrition labelling is to help food manufacturers and not to provide information directly for consumers or health professionals. Therefore it needs to meet the needs of manufac-
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turers as much as possible and omit features that are not relevant to them. The database should only include those nutrients that are required to be declared in labels to avoid confusion. If companies require additional nutrient data they can be referred to national reference food composition tables. There should be no missing nutrient values; a value should be presented for every nutrient in every food included in the database. Nutrient values should be defined in accordance with legislation, and these definitions may not be the same as in national reference databases. For example, under the Codex Guidelines and under Australian and New Zealand nutrition labelling requirements, an energy factor of 17 kJ/g is assigned to sugars, whereas our national reference database (NUTTAB) uses a factor of 16 kJ/g (FSANZ, 2007, 2009a). If the database is to be used by companies for export purposes, the design needs to consider legal requirements in other countries. The database should include data on ingredients that are used in manufacturing (including food additives) in the country for which it is being prepared. Some of these ingredients will not be available for direct purchase by consumers and may not be included in national reference databases. Australian experience has shown that failure to include manufacturing ingredients presents difficulties for users as they need to obtain this information from other sources. Flours and oils are two ingredient categories where FSANZ has identified that additional data are required to cover the specialty products used in manufacturing. Flours and oils often make up a significant proportion of a food as sold so variation in their composition can be a major determinant of, for example, the level of dietary fibre or saturated fat in a food containing them. At present FSANZ is expanding the range of ingredients contained in the labelling database following numerous user requests for particular ingredients, such as pig blood. However it is not always easy to obtain nutrient data for specialty ingredients as ingredient suppliers may be reluctant to release information to anyone other than their own customers, or the information may not be presented in a form that assists companies. A survey of Australian food businesses in 2004 found that 6% of surveyed companies found it difficult to obtain ingredient information from suppliers (Roy Morgan Research, 2006). Because the labelling database is to assist manufacturers prepare nutrient data for their specific product formulation, the database does not need to include many of the mixed foods that are typical of home produced foods. It may also be important to update the names of the foods so that they incorporate names and terms familiar to manufacturers. If the database is derived from national food composition tables, as is the case with the Australian labelling database, it is important to consider the need to update values, particularly where it is anticipated that levels of some nutrients may have changed or methods of analysis improved. This is important not only at the time the database is first developed, but also throughout its life. In addition we have identified that sodium levels have decreased in some food groups since the labelling database was first prepared and therefore some sodium values are being updated. Fatty acid data are also being updated in cases where manufacturers have moved to reduce saturated and trans-unsaturated fatty acid levels in recent years (FSANZ, 2009b) and where improved analytical techniques have resulted in more robust estimates of saturated fat levels. It is also important to review the quality of the data in a labelling database, just as it is for a national reference database. Formal data quality guidelines have not been developed for the Australian labelling database to date. The majority of the data are derived from our published national reference database, where data are assessed for factors such as whether a representative sample was collected, appropriate methods of analysis were used,
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and adequate description of the sample including the origin of the data was provided. Where data are provided by industry or are derived from the literature, such information may not be available. The absence of formal data quality guidelines for the Australian tables has been identified as a weakness in a recent review (Castanheira, 2010) and is an issue that will be addressed in future food composition data releases. As with a reference food composition database, a labelling database needs to include more than simply nutrient values. Many manufacturers will need information on typical weight change factors, to account for loss or gain of moisture on cooking and to assist them to calculate a nutrient profile for their food; the Australian experience has shown that some manufacturers, particularly small ones, do not hold this information about their products. Data on the mass or volume of common measures can be very helpful, as can data on density if legal requirements state that liquid products must be labelled on a volume basis. No matter what the content of the labelling database is, it needs to be accompanied by simple and clear guidance for users. Those who use a database for labelling purposes may not be scientists and therefore guidance needs to be written for a non-technical audience. Guidance material should be updated when data are updated. 4. Challenges in use of labelling databases There are some instances where a labelling database cannot be used successfully for nutrition labelling purposes, unless the user has a high degree of skill and knowledge in this area. For example the nutrient profile of deep fried foods can be difficult to predict because of varying uptake of frying fats (Mellema, 2003). Processing steps such as packing in salt or soaking in brine can result in quite different sodium contents of apparently similar products depending on the exact processing conditions. This can make it difficult to estimate sodium levels from a labelling database. Fermentation may lead to some changes in nutrient content although in practice, this may not be significant for those nutrients that must be declared in labels. Use of a labelling database will not be appropriate if the database does not contain data for an ingredient that is likely to make a significant contribution to the food’s nutrient profile. Where such data are not available, direct analysis is likely to be necessary. One of the biggest challenges for a labelling database will be in dealing with vitamins, because of their labile nature. If vitamins are included in a labelling database, it will be necessary to include data for multiple versions of the same food differing in key production parameters that affect vitamin content. For example it may be necessary to include data on foods packed or processed using novel processing technologies, on different varieties of fruits or vegetables where this affects vitamin levels (e.g. orange sweet potato and white sweet potato, dark green leafy vegetables compared to pale green leafy vegetables) and on ingredients that may be fortified or unfortified with a particular nutrient (e.g. wheat flour with and without added folic acid). Vitamin retention factors can be provided with the nutrient data although there may not be factors available to cover all included vitamins for all industrial processing conditions (e.g. modified atmosphere storage or high pressure processing). Some vitamins are added to foods in nutritionally significant amounts for non-nutrient purposes, such as vitamins C and E used as antioxidants and carotenes and riboflavin as colours. A labelling database that is intended for use in estimating vitamin levels should include these additives among its ingredients. Labelling with vitamin content is not mandatory in Australia or under Codex requirements, unless a specific claim is made about
that vitamin. Therefore the FSANZ labelling database does not include any vitamin data and users are advised to consider direct analysis if vitamin values are to be declared. However direct analysis of vitamins presents many challenges and requires laboratories to have skills and experience in this work (Ball, 2006). The Australian experience has shown that many users of a labelling database do not have strong skills in nutrition or food science. Therefore the integration of the labelling database with a calculation tool, such as our Nutrition Panel Calculator, has been particularly useful for them. 5. Accuracy of the values prepared from a labelling database There has not been any research published to date to determine how well values generated from FSANZ’s labelling database agree with results generated through direct analysis. However some government agencies in Australia and New Zealand have done small studies on the accuracy of nutrition labelling in general, comparing analysed nutrient values to values stated on the label for the same food. All of these studies examined only a small number of replicates of each brand and none assessed the source of the label data (Fabiansson, 2006; Thomson, 2006, 2007; Thomson and Jones, 2009; FSANZ, 2009c). Table 1 summarises the findings of these studies. Fabiansson (2006) analysed five replicate samples of each of 70 foods collected in Australia using established (AOAC) analytical techniques for four of these nutrients (protein, total fat, total sugars, and saturated fat) and a modified AOAC method for sodium. For five of the nutrients that must be included on labels, label vs analysed values for protein were more commonly in agreement (defined as being within 20% of the label value) than for the remaining nutrients (80% vs 59–73% agreement); energy and total carbohydrate values were not analysed. However when minor variations were excluded (less than 1 g/100 g for protein, total fat, total sugars and saturated fat, and less than 10 mg/100 g for sodium), between 80 and 95% of declared values were accurate. The paper did not report the measurement uncertainty associated with the analyses undertaken. A small study undertaken by Food Standards Australia New Zealand (2009c) found that of 165 individual food samples collected from Australian retail outlets, 85% contained a sodium content that was within 20% of, or less than, the label claim. Sodium content was measured in an accredited laboratory using inductively coupled plasma atomic emission spectroscopy with a limit of detection of 1 mg/kg. In most cases replicate purchases were not made so it is not possible to assess within-brand variation or to determine reasonable average values for a specific product. The selected samples did not cover all categories of processed foods available in Australia and therefore can only be considered to be indicative. These small studies suggests that educating consumers to check label values for protein, sugars, fat, saturated fat and sodium should assist them to make appropriate food choices. A recent Australian study of education measures to reduce salt intake supports this. Ireland et al. (2010) found that advising adult participants to select processed foods where the label declaration of sodium was less than 120 mg/100 g (qualifying the food to be labelled as low in sodium) led to significant reductions in urinary sodium excretion. For added vitamins and minerals, for which inclusion in nutrition information panels is voluntary, label and analysed values are less likely to be in agreement than for the nutrients that must be included in labels. Three small scale New Zealand studies of levels of retinol, vitamin D, vitamin C, folate, calcium and zinc in foods to which these nutrients were added found that between 27% (retinol) and 50% (calcium) of label values agreed with analysed
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Table 1 Agreement between analysed and label values for 11 nutrients in foods analysed in Australia and New Zealand. Nutrient (method of analysis cited by authors)
Mandatory nutrients (Australian samples) (Fabiansson, 2006) Protein (AOAC 935.36 and 923.03) Sodium (‘modified’ AOAC 984.27) Saturated fat (AOAC 969.33) Sugars, total (HPLC, further detail not provided) Total fat (AOAC 954.02, 922.06, 960.39 and AS 2300.1.3) Sodium (Australian samples) (FSANZ, 2009a,b,c) Sodium (ICPAES, further detail not provided) Added micronutrients, voluntary declaration (New Zealand samples) Retinol (modifications of published HPLC method with fluorescence detection) Vitamin D (HPLC, published method) Vitamin C (HPLC with fluorescence detection, published method) Folate, total (Tri-enzyme, microbiological, published method) Calcium (atomic absorption spectroscopy, further details not provided) Zinc (ICP-MS, further detail not provided)
Sample source
70 70 70 70 70
samples, samples, samples, samples, samples,
5 5 5 5 5
replicate replicate replicate replicate replicate
% of labels in agreement with analysed valuea samples samples samples samples samples
of of of of of
each each each each each
80 73 65 61 59
165 samples, primarily single samples only
60
22 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 18 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 25 samples of fortified foods, 5 replicate samples of each (Thomson, 2007) 29 samples of fortified foods, up to 5 replicate samples of each (Thomson and Jones, 2009) 18 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 20 samples of fortified foods, 5 replicate samples of each (Thomson, 2007)
27 33 28 45 51 50
a Agreement assessed as label values falling within 20% of the analysed value for Fabiansson (2006) and FSANZ (2009a,b,c), within 1.2 standard deviations of the analysed value for Thomson (2006) and Thomson (2007), or within the 95% confidence interval for the analysed product for Thomson and Jones (2009).
values; ‘agreement’ was defined as the label value being within 1.2 times the standard deviation for analysed values, or within the 95% confidence interval for analysed values in the case of folate. Analyses were conducted using published methods by accredited laboratories The lower agreement between analysed and label values for vitamins and minerals may reflect factors such as the practice of using ‘overages’ to ensure a product maintains, at a minimum, the amount claimed on the label for the duration of a product’s shelf life, loss of vitamins during storage, variation in the rate of addition of micronutrients, natural variation in intrinsic levels of the nutrient and greater measurement uncertainty for these nutrients. However between 59% (retinol) and 93% (folate) of products contained levels of added nutrients that were at or above the label claim, which suggests that the label information would assist consumers to correctly select foods that are sources of these nutrients in the majority of cases. 6. Conclusions Generating accurate nutrition labels is challenging, whether by direct analysis or from food composition databases. Food composition databases can provide an alternative to direct analysis that can be successfully used for many foods, provided the database is comprehensive, industry focussed and aligned with regulation. Regardless of the quality of the database, there will be some production methods and some nutrients that are unsuited to estimation from a database, and would be better suited to direct laboratory analysis. There is a need for additional research to assess how well labelling databases work compared to direct analysis, with the aim of providing guidance for improving labelling databases. References Ball, G.F.M., 2006. Vitamins in Foods: Analysis, Bioavailability, and Stability. CRC Press, Boca Raton. Castanheira, I. Auditing the Australian Food Composition Program, 2010 (unpublished). Codex Alimentarius, 2007. Guidelines on Nutrition Labelling. CAC/GL 2-1985. In: FAO, WHO, (Eds.), Food Labelling. 5th ed. FAO, Rome, pp. 25–31.
Cunningham, J., Trevisan, L., Milligan, G., 2004. Lessons learned from providing a free nutrition labelling tool for industry—the Australian experience. Journal of Food Composition & Analysis 17, 565–574. EURACHEM/CITAC, 2007. Measurement Uncertainty Arising from Sampling—A Guide to Methods and Approaches, 1st ed. EURACHEM Secretariat, BAM, Berlin. Fabiansson, S.U., 2006. Precision in nutritional information declarations on food labels in Australia. Asia Pacific Journal Clinical Nutrition 15 (4), 451–458. Food Standards Australia New Zealand (FSANZ), 2007. NUTTAB 06. Retrieved October 23, 2009 from http://www.foodstandards.gov.au/monitoringandsur veillance/nuttab2006/index.cfm. Food Standards Australia New Zealand (FSANZ), 2009a. Standard 1.2.8 Nutrition Information Requirements. Australia New Zealand Food Standards Code, Amendment 112. Retrieved October 23, 2009 from http://www.foodstandards. gov.au/thecode/foodstandardscode/standard128nutrition4235.cfm. Food Standards Australia New Zealand (FSANZ), 2009b. Intakes of trans fatty acids in New Zealand and Australia. Retrieved October 23, 2009 from http:// www.foodstandards.gov.au/_srcfiles/TFAs_intakes_2009.pdf. Food Standards Australia New Zealand (FSANZ), 2009c. Sodium levels in a range of packaged and takeaway foods. Retrieved 28 May, 2010 from http://www.food standards.gov.au/scienceandeducation/publications/sodiumlevelsinaran ge4648.cfm. Greenfield, H., Southgate, D.A.T., 2003. Food Composition Data—Production, Management and Use, 2nd ed. Food and Agricultural Organization, Rome. Ireland, D.-M., Clifton, P.M., Keogh, J.B., 2010. Achieving the salt intake target of 6 g/ day in the current food supply in free-living adults using two dietary education strategies. Journal of the American Dietetic Association 10, 763–767. Mellema, M., 2003. Mechanism and reduction of fat uptake in deep-fat fried foods. Trends in Food Science & Technology 14, 364–373. NFO Donovan Research, 2002. Food labelling issues—stakeholder qualitative research. Report to ANZFA. Downloaded on October 23, 2009 from http:// www.foodstandards.gov.au/_srcfiles/Stakeholder_REsearch_Food_labels_April02.pdf. Roy Morgan Research, 2006. Benchmark research on the impact of labelling and compositional standards in the Australia New Zealand Food Standards Code on Food Industry, Enforcement Agencies and Health Professionals. Downloaded on October 23, 2009 from http://www.foodstandards.gov.au/_srcfiles/ANZ%20 Food%20Standards%20Code%20final%20report%201.pdf. Thomson, B.M., 2006. Fortification overages of the food supply. Vitamin A, Vitamin D and calcium. ESR Client Report FW 0637. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa. govt.nz/science/research-projects/FW0637_Overages_report.pdf. Thomson, B.M., 2007. Fortification overages of the food supply. Vitamin C, zinc and selenium. ESR Client Report FW 0745. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa.govt.nz/ science/research-projects/FW0745_Vit_C_zinc__selenium.pdf. Thomson, B., Jones, S., 2009. Fortification overages of the food supply. Folate. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa.govt.nz/science/research-projects/fw08030-fo late-overages.pdf.
Contents lists available at ScienceDirect
Journal of Food Composition and Analysis journal homepage: www.elsevier.com/locate/jfca
Report
Food composition databases for nutrition labelling: Experience from Australia J. Cunningham *, R. Sobolewski Food Standards Australia New Zealand, PO Box 7186, Canberra BC, ACT 2610, Australia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 4 November 2009 Received in revised form 4 June 2010 Accepted 5 July 2010 Available online 13 November 2010
Food composition databases prepared for nutrition labelling have some important differences to other food composition databases. Nutrient values must be expressed in accordance with legal requirements for nutrition labelling in the country where it will be used. The database should include all the nutrients that must be declared in labels and contain data for ingredients (including additives) used in manufacturing. Data should be as current as possible and it may be necessary to update the databases before release. Information on typical measures, indicative weight changes during processing and retention factors (if including vitamins and minerals) will be required, as will explanatory material appropriate to the audience. Challenge areas for use of a labelling database include foods prepared by soaking or packing in salt or by deep frying, and estimation of vitamin levels. Limited Australian and New Zealand research suggests that label and analytical data for proximate nutrients, fatty acids and sodium agree in around 60% of cases or more; for added micronutrients, no more than 50% of values agree. However there is no research available to show whether labels prepared from a labelling database are more or less accurate than labels prepared using analysis. The Australian experience shows that it is possible to develop a labelling database suitable for many, but not all, foods and nutrients, but there is a lack of information to assess the quality of the data produced. Crown Copyright ß 2010 Published by Elsevier Inc. All rights reserved.
Keywords: Nutrition labelling Food composition databases Australia Vitamins Legal requirements Manufacturing
1. Introduction Food Standards Australia New Zealand (FSANZ) is a binational government agency that establishes standards for the composition and labelling of foods sold in Australia and New Zealand. Although there is a binational food standards system, the two countries have separate food composition tables. In New Zealand, the national food composition tables are prepared by Plant & Food Research New Zealand. FSANZ manages the Australian food composition tables and the two countries work closely on food composition activities. Australia’s national food composition tables are called NUTTAB (FSANZ, 2007) and are available on-line and free of charge. Nutrition information panels have been mandatory for almost all packaged foods in Australia and New Zealand since late 2002 after a two year phase-in period. Energy and six nutrients (protein, total fat, saturated fat, total carbohydrate, total sugars and sodium) must be included in panels. Nutrient values must be presented per 100 g of the food and per serving, using no more than three significant figures. Other nutrients must be included in panels if specific claims are made about them in relation to that food (FSANZ, 2009a). Tolerance limits are not established.
* Corresponding author. Tel.: +61 2 6271 2213; fax: +61 2 6271 2278. E-mail address: [email protected] (J. Cunningham).
At the time mandatory nutrition labelling was introduced, there was considerable concern about the high cost of direct analysis of foods (NFO Donovan Research, 2002). Therefore in 2001 FSANZ launched an on-line product called the Nutrition Panel Calculator (NPC) to help Australian companies, particularly small companies, prepare for the introduction of mandatory nutrition labelling. The NPC is the most visited part of the organisation’s website, with more than 110,000 visitors in July 2009 alone. The NPC has two main parts – software that helps users to calculate the nutrients in their product based on its formulation, and a nutrient database. Feedback from users has been very positive and it has been an important factor in the successful introduction of mandatory nutrition labelling. Initial experience with providing the NPC itself was reviewed in 2004 (Cunningham et al., 2004). The purpose of this paper is to review the Australian experience in developing a food composition database for nutrition labelling purposes and to identify areas where such a database presents particular challenges. 2. Purpose of nutrition labelling and the role of labelling databases The Codex Alimentarius Guideline on Nutrition Labelling (CAC/ GL 2-1985, Codex Alimentarius, 2007) identifies a number of aims for nutrition labelling of foods. Apart from providing consumers with information to facilitate the choice of healthy food, nutrition
0889-1575/$ – see front matter . Crown Copyright ß 2010 Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jfca.2010.07.002
J. Cunningham, R. Sobolewski / Journal of Food Composition and Analysis 24 (2011) 682–685
labelling should ensure that a food is not described in a manner that is false, misleading, deceptive or insignificant. This suggests that the data contained in a food composition labelling database must be of high quality and sufficiently comprehensive that any results derived from its use are representative and reliable. However at the same time, it is important to recognise the innate variability in nutrient levels in foods (Greenfield and Southgate, 2003) and the uncertainty that is associated with sampling and analysis of foods (EURACHEM/CITAC, 2007) such that a nutrition label, however it is derived, will never be a perfect representation of the nutrient levels actually present in a food when it is consumed. This is recognised in the Codex Guideline where it is recommended that values used in label declarations should be weighted average values derived from data which are representative of the product being labelled and that tolerance limits should be set taking into account processing variability, inherent lability and variability of nutrients, among other factors (Codex Alimentarius, 2007). A well designed food composition database for labelling purposes can have the following roles: 1. As an alternative to direct analysis, where this is permitted in legislation. Using a database rather than direct analysis will generally be cheaper as it avoids the need for sample collection and expensive analysis and it will be quicker as it can be done immediately rather than waiting for laboratories to do their work. It also helps where laboratory capacity is limited in a region. 2. To provide guidance on when nutrients will be present at insignificant levels. Even in situations where direct analysis is required for most nutrients, analysis may not be necessary for those nutrients likely to be present at insignificant levels. Reference to a database will allow companies to identify where this is likely to be the case and to focus their resources on analysis of remaining nutrients. 3. To provide guidance on when a formulation change will affect nutrient levels. Formulations of manufactured foods can change regularly. For example, new colours may be used, salt levels may be reduced or oil type changed. Some of these changes will have no significant effect on the food’s nutrient profile and a labelling database can provide information that helps companies to decide whether or not the change warrants further analyses. 4. To assist with assessment of analytical results. It can be helpful for companies to cross check analytical results they have received against data for the same or similar foods in food composition tables as one step in assessing their own analytical data. This can help companies to identify major errors in data they have received. 5. To assist with exports. Even if countries require direct analysis of foods for labelling purposes, manufacturers may also be exporting products to other countries, such as Australia, that do allow the use of nutrient databases for label preparation; in this case a labelling database can be used to prepare nutrient data for a country-specific product formulation. Australia’s NPC was only designed for use with foods sold in Australia and New Zealand but we have had requests for assistance from companies that export food from Australia and wish to meet nutrition labelling requirements in other countries. 3. Features of a labelling database The features of a food composition database are determined by the purpose of the database. The purpose of a food composition database for nutrition labelling is to help food manufacturers and not to provide information directly for consumers or health professionals. Therefore it needs to meet the needs of manufac-
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turers as much as possible and omit features that are not relevant to them. The database should only include those nutrients that are required to be declared in labels to avoid confusion. If companies require additional nutrient data they can be referred to national reference food composition tables. There should be no missing nutrient values; a value should be presented for every nutrient in every food included in the database. Nutrient values should be defined in accordance with legislation, and these definitions may not be the same as in national reference databases. For example, under the Codex Guidelines and under Australian and New Zealand nutrition labelling requirements, an energy factor of 17 kJ/g is assigned to sugars, whereas our national reference database (NUTTAB) uses a factor of 16 kJ/g (FSANZ, 2007, 2009a). If the database is to be used by companies for export purposes, the design needs to consider legal requirements in other countries. The database should include data on ingredients that are used in manufacturing (including food additives) in the country for which it is being prepared. Some of these ingredients will not be available for direct purchase by consumers and may not be included in national reference databases. Australian experience has shown that failure to include manufacturing ingredients presents difficulties for users as they need to obtain this information from other sources. Flours and oils are two ingredient categories where FSANZ has identified that additional data are required to cover the specialty products used in manufacturing. Flours and oils often make up a significant proportion of a food as sold so variation in their composition can be a major determinant of, for example, the level of dietary fibre or saturated fat in a food containing them. At present FSANZ is expanding the range of ingredients contained in the labelling database following numerous user requests for particular ingredients, such as pig blood. However it is not always easy to obtain nutrient data for specialty ingredients as ingredient suppliers may be reluctant to release information to anyone other than their own customers, or the information may not be presented in a form that assists companies. A survey of Australian food businesses in 2004 found that 6% of surveyed companies found it difficult to obtain ingredient information from suppliers (Roy Morgan Research, 2006). Because the labelling database is to assist manufacturers prepare nutrient data for their specific product formulation, the database does not need to include many of the mixed foods that are typical of home produced foods. It may also be important to update the names of the foods so that they incorporate names and terms familiar to manufacturers. If the database is derived from national food composition tables, as is the case with the Australian labelling database, it is important to consider the need to update values, particularly where it is anticipated that levels of some nutrients may have changed or methods of analysis improved. This is important not only at the time the database is first developed, but also throughout its life. In addition we have identified that sodium levels have decreased in some food groups since the labelling database was first prepared and therefore some sodium values are being updated. Fatty acid data are also being updated in cases where manufacturers have moved to reduce saturated and trans-unsaturated fatty acid levels in recent years (FSANZ, 2009b) and where improved analytical techniques have resulted in more robust estimates of saturated fat levels. It is also important to review the quality of the data in a labelling database, just as it is for a national reference database. Formal data quality guidelines have not been developed for the Australian labelling database to date. The majority of the data are derived from our published national reference database, where data are assessed for factors such as whether a representative sample was collected, appropriate methods of analysis were used,
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and adequate description of the sample including the origin of the data was provided. Where data are provided by industry or are derived from the literature, such information may not be available. The absence of formal data quality guidelines for the Australian tables has been identified as a weakness in a recent review (Castanheira, 2010) and is an issue that will be addressed in future food composition data releases. As with a reference food composition database, a labelling database needs to include more than simply nutrient values. Many manufacturers will need information on typical weight change factors, to account for loss or gain of moisture on cooking and to assist them to calculate a nutrient profile for their food; the Australian experience has shown that some manufacturers, particularly small ones, do not hold this information about their products. Data on the mass or volume of common measures can be very helpful, as can data on density if legal requirements state that liquid products must be labelled on a volume basis. No matter what the content of the labelling database is, it needs to be accompanied by simple and clear guidance for users. Those who use a database for labelling purposes may not be scientists and therefore guidance needs to be written for a non-technical audience. Guidance material should be updated when data are updated. 4. Challenges in use of labelling databases There are some instances where a labelling database cannot be used successfully for nutrition labelling purposes, unless the user has a high degree of skill and knowledge in this area. For example the nutrient profile of deep fried foods can be difficult to predict because of varying uptake of frying fats (Mellema, 2003). Processing steps such as packing in salt or soaking in brine can result in quite different sodium contents of apparently similar products depending on the exact processing conditions. This can make it difficult to estimate sodium levels from a labelling database. Fermentation may lead to some changes in nutrient content although in practice, this may not be significant for those nutrients that must be declared in labels. Use of a labelling database will not be appropriate if the database does not contain data for an ingredient that is likely to make a significant contribution to the food’s nutrient profile. Where such data are not available, direct analysis is likely to be necessary. One of the biggest challenges for a labelling database will be in dealing with vitamins, because of their labile nature. If vitamins are included in a labelling database, it will be necessary to include data for multiple versions of the same food differing in key production parameters that affect vitamin content. For example it may be necessary to include data on foods packed or processed using novel processing technologies, on different varieties of fruits or vegetables where this affects vitamin levels (e.g. orange sweet potato and white sweet potato, dark green leafy vegetables compared to pale green leafy vegetables) and on ingredients that may be fortified or unfortified with a particular nutrient (e.g. wheat flour with and without added folic acid). Vitamin retention factors can be provided with the nutrient data although there may not be factors available to cover all included vitamins for all industrial processing conditions (e.g. modified atmosphere storage or high pressure processing). Some vitamins are added to foods in nutritionally significant amounts for non-nutrient purposes, such as vitamins C and E used as antioxidants and carotenes and riboflavin as colours. A labelling database that is intended for use in estimating vitamin levels should include these additives among its ingredients. Labelling with vitamin content is not mandatory in Australia or under Codex requirements, unless a specific claim is made about
that vitamin. Therefore the FSANZ labelling database does not include any vitamin data and users are advised to consider direct analysis if vitamin values are to be declared. However direct analysis of vitamins presents many challenges and requires laboratories to have skills and experience in this work (Ball, 2006). The Australian experience has shown that many users of a labelling database do not have strong skills in nutrition or food science. Therefore the integration of the labelling database with a calculation tool, such as our Nutrition Panel Calculator, has been particularly useful for them. 5. Accuracy of the values prepared from a labelling database There has not been any research published to date to determine how well values generated from FSANZ’s labelling database agree with results generated through direct analysis. However some government agencies in Australia and New Zealand have done small studies on the accuracy of nutrition labelling in general, comparing analysed nutrient values to values stated on the label for the same food. All of these studies examined only a small number of replicates of each brand and none assessed the source of the label data (Fabiansson, 2006; Thomson, 2006, 2007; Thomson and Jones, 2009; FSANZ, 2009c). Table 1 summarises the findings of these studies. Fabiansson (2006) analysed five replicate samples of each of 70 foods collected in Australia using established (AOAC) analytical techniques for four of these nutrients (protein, total fat, total sugars, and saturated fat) and a modified AOAC method for sodium. For five of the nutrients that must be included on labels, label vs analysed values for protein were more commonly in agreement (defined as being within 20% of the label value) than for the remaining nutrients (80% vs 59–73% agreement); energy and total carbohydrate values were not analysed. However when minor variations were excluded (less than 1 g/100 g for protein, total fat, total sugars and saturated fat, and less than 10 mg/100 g for sodium), between 80 and 95% of declared values were accurate. The paper did not report the measurement uncertainty associated with the analyses undertaken. A small study undertaken by Food Standards Australia New Zealand (2009c) found that of 165 individual food samples collected from Australian retail outlets, 85% contained a sodium content that was within 20% of, or less than, the label claim. Sodium content was measured in an accredited laboratory using inductively coupled plasma atomic emission spectroscopy with a limit of detection of 1 mg/kg. In most cases replicate purchases were not made so it is not possible to assess within-brand variation or to determine reasonable average values for a specific product. The selected samples did not cover all categories of processed foods available in Australia and therefore can only be considered to be indicative. These small studies suggests that educating consumers to check label values for protein, sugars, fat, saturated fat and sodium should assist them to make appropriate food choices. A recent Australian study of education measures to reduce salt intake supports this. Ireland et al. (2010) found that advising adult participants to select processed foods where the label declaration of sodium was less than 120 mg/100 g (qualifying the food to be labelled as low in sodium) led to significant reductions in urinary sodium excretion. For added vitamins and minerals, for which inclusion in nutrition information panels is voluntary, label and analysed values are less likely to be in agreement than for the nutrients that must be included in labels. Three small scale New Zealand studies of levels of retinol, vitamin D, vitamin C, folate, calcium and zinc in foods to which these nutrients were added found that between 27% (retinol) and 50% (calcium) of label values agreed with analysed
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Table 1 Agreement between analysed and label values for 11 nutrients in foods analysed in Australia and New Zealand. Nutrient (method of analysis cited by authors)
Mandatory nutrients (Australian samples) (Fabiansson, 2006) Protein (AOAC 935.36 and 923.03) Sodium (‘modified’ AOAC 984.27) Saturated fat (AOAC 969.33) Sugars, total (HPLC, further detail not provided) Total fat (AOAC 954.02, 922.06, 960.39 and AS 2300.1.3) Sodium (Australian samples) (FSANZ, 2009a,b,c) Sodium (ICPAES, further detail not provided) Added micronutrients, voluntary declaration (New Zealand samples) Retinol (modifications of published HPLC method with fluorescence detection) Vitamin D (HPLC, published method) Vitamin C (HPLC with fluorescence detection, published method) Folate, total (Tri-enzyme, microbiological, published method) Calcium (atomic absorption spectroscopy, further details not provided) Zinc (ICP-MS, further detail not provided)
Sample source
70 70 70 70 70
samples, samples, samples, samples, samples,
5 5 5 5 5
replicate replicate replicate replicate replicate
% of labels in agreement with analysed valuea samples samples samples samples samples
of of of of of
each each each each each
80 73 65 61 59
165 samples, primarily single samples only
60
22 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 18 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 25 samples of fortified foods, 5 replicate samples of each (Thomson, 2007) 29 samples of fortified foods, up to 5 replicate samples of each (Thomson and Jones, 2009) 18 samples of fortified foods, 5 replicate samples of each (Thomson, 2006) 20 samples of fortified foods, 5 replicate samples of each (Thomson, 2007)
27 33 28 45 51 50
a Agreement assessed as label values falling within 20% of the analysed value for Fabiansson (2006) and FSANZ (2009a,b,c), within 1.2 standard deviations of the analysed value for Thomson (2006) and Thomson (2007), or within the 95% confidence interval for the analysed product for Thomson and Jones (2009).
values; ‘agreement’ was defined as the label value being within 1.2 times the standard deviation for analysed values, or within the 95% confidence interval for analysed values in the case of folate. Analyses were conducted using published methods by accredited laboratories The lower agreement between analysed and label values for vitamins and minerals may reflect factors such as the practice of using ‘overages’ to ensure a product maintains, at a minimum, the amount claimed on the label for the duration of a product’s shelf life, loss of vitamins during storage, variation in the rate of addition of micronutrients, natural variation in intrinsic levels of the nutrient and greater measurement uncertainty for these nutrients. However between 59% (retinol) and 93% (folate) of products contained levels of added nutrients that were at or above the label claim, which suggests that the label information would assist consumers to correctly select foods that are sources of these nutrients in the majority of cases. 6. Conclusions Generating accurate nutrition labels is challenging, whether by direct analysis or from food composition databases. Food composition databases can provide an alternative to direct analysis that can be successfully used for many foods, provided the database is comprehensive, industry focussed and aligned with regulation. Regardless of the quality of the database, there will be some production methods and some nutrients that are unsuited to estimation from a database, and would be better suited to direct laboratory analysis. There is a need for additional research to assess how well labelling databases work compared to direct analysis, with the aim of providing guidance for improving labelling databases. References Ball, G.F.M., 2006. Vitamins in Foods: Analysis, Bioavailability, and Stability. CRC Press, Boca Raton. Castanheira, I. Auditing the Australian Food Composition Program, 2010 (unpublished). Codex Alimentarius, 2007. Guidelines on Nutrition Labelling. CAC/GL 2-1985. In: FAO, WHO, (Eds.), Food Labelling. 5th ed. FAO, Rome, pp. 25–31.
Cunningham, J., Trevisan, L., Milligan, G., 2004. Lessons learned from providing a free nutrition labelling tool for industry—the Australian experience. Journal of Food Composition & Analysis 17, 565–574. EURACHEM/CITAC, 2007. Measurement Uncertainty Arising from Sampling—A Guide to Methods and Approaches, 1st ed. EURACHEM Secretariat, BAM, Berlin. Fabiansson, S.U., 2006. Precision in nutritional information declarations on food labels in Australia. Asia Pacific Journal Clinical Nutrition 15 (4), 451–458. Food Standards Australia New Zealand (FSANZ), 2007. NUTTAB 06. Retrieved October 23, 2009 from http://www.foodstandards.gov.au/monitoringandsur veillance/nuttab2006/index.cfm. Food Standards Australia New Zealand (FSANZ), 2009a. Standard 1.2.8 Nutrition Information Requirements. Australia New Zealand Food Standards Code, Amendment 112. Retrieved October 23, 2009 from http://www.foodstandards. gov.au/thecode/foodstandardscode/standard128nutrition4235.cfm. Food Standards Australia New Zealand (FSANZ), 2009b. Intakes of trans fatty acids in New Zealand and Australia. Retrieved October 23, 2009 from http:// www.foodstandards.gov.au/_srcfiles/TFAs_intakes_2009.pdf. Food Standards Australia New Zealand (FSANZ), 2009c. Sodium levels in a range of packaged and takeaway foods. Retrieved 28 May, 2010 from http://www.food standards.gov.au/scienceandeducation/publications/sodiumlevelsinaran ge4648.cfm. Greenfield, H., Southgate, D.A.T., 2003. Food Composition Data—Production, Management and Use, 2nd ed. Food and Agricultural Organization, Rome. Ireland, D.-M., Clifton, P.M., Keogh, J.B., 2010. Achieving the salt intake target of 6 g/ day in the current food supply in free-living adults using two dietary education strategies. Journal of the American Dietetic Association 10, 763–767. Mellema, M., 2003. Mechanism and reduction of fat uptake in deep-fat fried foods. Trends in Food Science & Technology 14, 364–373. NFO Donovan Research, 2002. Food labelling issues—stakeholder qualitative research. Report to ANZFA. Downloaded on October 23, 2009 from http:// www.foodstandards.gov.au/_srcfiles/Stakeholder_REsearch_Food_labels_April02.pdf. Roy Morgan Research, 2006. Benchmark research on the impact of labelling and compositional standards in the Australia New Zealand Food Standards Code on Food Industry, Enforcement Agencies and Health Professionals. Downloaded on October 23, 2009 from http://www.foodstandards.gov.au/_srcfiles/ANZ%20 Food%20Standards%20Code%20final%20report%201.pdf. Thomson, B.M., 2006. Fortification overages of the food supply. Vitamin A, Vitamin D and calcium. ESR Client Report FW 0637. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa. govt.nz/science/research-projects/FW0637_Overages_report.pdf. Thomson, B.M., 2007. Fortification overages of the food supply. Vitamin C, zinc and selenium. ESR Client Report FW 0745. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa.govt.nz/ science/research-projects/FW0745_Vit_C_zinc__selenium.pdf. Thomson, B., Jones, S., 2009. Fortification overages of the food supply. Folate. Wellington: New Zealand Food Safety Authority. Downloaded on October 23, 2009 from http://www.nzfsa.govt.nz/science/research-projects/fw08030-fo late-overages.pdf.