The current regulatory framework within the European Union mandates the declaration of 14 allergens which are deliberately added as ingredients. However, it does not cover the unintentional cross-contamination with allergens or resultant use of advisory labelling. Food manufacturers often use advisory labelling such as ’may contain X allergen‘ to inform allergic consumers of the potential risk of cross-contamination in a food product. While there is some voluntary guidance which includes qualitative advice for industry on how to assess and manage risk from allergenic foods (published by the FSA in 2006), there is currently no quantitative advice from regulatory bodies on the levels of allergen cross-contamination above which advisory labelling should be used.
Probabilistic modelling is considered to be the most promising approach to estimate the risk of any allergic reaction following consumption of a food product that contains an allergen due to (unintended) cross-contamination.
The Australian Allergen Bureau’s Voluntary Incidental Trace Allergen Labelling (VITAL) programme has produced a quantitative guideline based on probabilistic principles. It is hoped that this guideline will support food producers in assessing the impact of allergen cross-contamination in a food manufacturing environment. The guideline has been positively reviewed by the International Life Sciences Institute’s (ILSI) European Food Allergy Task Force. However, it is yet to be accepted by regulatory bodies such as the European Food Safety Authority (EFSA).
The purpose of this research is to quantitatively assess the public health risks posed by the levels of peanut, hazelnut, milk and wheat cross-contamination detected in UK retail products sampled and tested as part of the FSA-funded survey of allergen advisory labelling. This will be done using probabilistic risk assessment techniques.
Several input variables are required to undertake food allergy risk assessments. These include:
- the consumption of the food at an individual meal/eating occasion
- the concentration of the allergen in the food (ie whether the food contains the allergen and in which concentration)
These input variables together determine the exposure to the allergen. Additionally, data on the distribution of minimum eliciting doses (ie threshold distribution) is also required. By combining the threshold distribution and the exposure distribution, the probability of an allergic reaction is determined.
The inputs for the probabilistic risk assessment will be based on UK food consumption data, and the combined food allergic threshold datasets developed by the contractors. Furthermore, the allergen cross-contamination data will be based on the FSA’s survey of allergen advisory labelling and allergen content of UK retail pre-packed foods (further information about the FSA survey is available at: FS241038.
The level of peanut, hazelnut, milk and wheat cross-contamination in UK retail foods sampled as part of the FSA survey will also be compared to the action levels proposed by the VITAL programme. This will be done by setting a product-specific action level for samples that tested positive.
The results of this project will be used to help inform the FSA’s work to develop risk-based, proportionate action levels. Specifically, the results will help the FSA to:
- Quantitatively assess the public health risks posed by the levels of allergen cross-contamination found to be present in foods sold on the UK retail market (as identified by the FSA survey) to which UK food allergic consumers are currently being exposed.
- Give an indication as to whether the proposed levels developed by the VITAL programme are practical in relation to the actual levels of cross-contamination detected in the FSA survey samples. Such information will help the FSA to determine whether the levels UK food allergic consumers would be exposed to if such actions levels were implemented, are comparable to the levels currently being used for allergen control by industry (as identified by the FSA survey) and whether these action levels are likely to be achievable by industry.