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Development and evolution of risk assessment for food allergens

  • Rene' W. R. Crevel
  • , Joseph L. Baumert
  • , Athanasia Baka
  • , Geert F. Houben
  • , Andre C. Knulst
  • , Astrid G. Kruizinga
  • , Stefano Luccioli
  • , Stephen L. Taylor
  • , Charlotte Bernhard Madsen
  • Unilever
  • University of Nebraska
  • International Life Sciences Institute Europe
  • Netherlands Organisation for Applied Scientific Research
  • University Medical Centre Utrecht
  • Center for Food Safety and Applied Nutrition

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The need to assess the risk from food allergens derives directly from the need to manage effectively this food safety hazard. Work spanning the last two decades dispelled the initial thinking that food allergens were so unique that the risk they posed was not amenable to established risk assessment approaches and methodologies. Food allergens possess some unique characteristics, which make a simple safety assessment approach based on the establishment of absolute population thresholds inadequate. Dose distribution modelling of MEDs permitted the quantification of the risk of reaction at the population level and has been readily integrated with consumption and contamination data through probabilistic risk assessment approaches to generate quantitative risk predictions. This paper discusses the strengths and limitations of this approach and identifies important data gaps, which affect the outcomes of these predictions. These include consumption patterns among allergic individuals, analytical techniques and their application, severity-dose relationships, and the impact of extraneous factors which alter an individual’s physiology, such as infection or exercise. Nevertheless, application of these models has provided valuable insights, leading to further refinements and generating testable hypotheses. Their application to estimate the risk posed by the concurrent consumption of two potentially contaminated foods illustrates their power.
Original languageEnglish
JournalFood and Chemical Toxicology
Volume67
Pages (from-to)262-276
ISSN0278-6915
DOIs
Publication statusPublished - 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Food allergy
  • Public health
  • Risk Assessment
  • Probabilistic modelling
  • Reference close
  • Thresholds

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