Uncertainty analysis is an important component of dietary exposure assessments in order to understand correctly the strength and limits of its results. Often, standard screening procedures are applied in a first step which results in conservative estimates. If through those screening procedures a potential exceedance of health-based guidance values is indicated, within the tiered approach more refined models are applied. However, the sources and types of uncertainties in deterministic and probabilistic models can vary or differ.

A key objective of this work has been the mapping of different sources and types of uncertainties to better understand how to best use uncertainty analysis to generate more realistic comprehension of dietary exposure. In dietary exposure assessments, uncertainties can be introduced by knowledge gaps about the exposure scenario, parameter and the model itself. With this mapping, general and model-independent uncertainties have been identified and described, as well as those which can be introduced and influenced by the specific model during the tiered approach.

This analysis identifies that there are general uncertainties common to point estimates (screening or deterministic methods) and probabilistic exposure assessment methods. To provide further clarity, general sources of uncertainty affecting many dietary exposure assessments should be separated from model-specific uncertainties.

Acute dietary intake is one of the factors considered by Member States, the European Commission and international authorities when setting Maximum Residue Leve is (MRL S) for pesticides. The MRL is the maximum concentration of a pesticide residue (expressed as mg/kg that is legally permitted in or on a food or agricultural commodity or animal feedstuff. The measure of acute dietary exposure that is used in MRL-setting is the International Estimate of Short Term Intake (IESTI). The IESTI is calculated using one of 4 standard equations, de pending on the type of commodity involved. An MRL above the limit of detection is set for a Commodity only it is ESI does not exceed the Acute Reference Dose (ARTD) or the pesticide concerned. The re are discussions at international level about whether to change the way that IESTI equations are calculated. Therefore the European Commission asked the EFSA Scientific Panel on Plant protection products and their Residues (PPR Fane) for an opinion on how conservative the ESTI equation is, With respect to the percentage or the total European population protected from intakes above the ARTD, and how much this would be altered by changes to the way the IESTTIs calculated. However, the Panel is aware that risk managers are also interested in the special case of people who consume a commodity containing residues at the MRL. Therefore the Panel undertook two types of assessment: “total population assessments”, estimating the level of protection for the total population based on the levels of pesticides observed in monitoring programs, and “MRL-level assessments” for the special case of people who consume one commodity containing residues at the MRL and other commodities at monitoring levels. The Panel estimated acute dietary intakes by probabilistic mode ling This used dat a on food consumption and body we ight from national surveys, and took account of unit-to-unit variability of residues using variability factors. The probabilistic estimates of intakes were higher than measured intakes from a duplicate diet study, suggesting the Paneľ’s results are conservative .e. overestimating intakes and underestimating levels of protection. However, this comparison was possible for only 6 pesticides in one country and one age group, and extrapolation to others countries and age groups is uncertain. It was not possible to conduct probabilistic modelling for the entire population of the Eu, or for all pesticides. The Panel conducte  total population assessments for a number of scenarios representing different combinations of 13 pesticides, 8 countries and a range of age groups from babies to seniors. For practical reasons, the MRL-level assessments were base d on a reduce d range or scenarios, representing only two countries (Germany and The Netherlands) and 11 pesticides. For the total population, the Paneľ’s estimates suggested that the level of protection (LoP) provided by the IESTI equation as currently used in the EU (including variability factors of 5 & 7) varies quite widely between different countries, age groups and pesticides. For some pesticide/country/age group scenarios the estimated LoP was between 99 and 99.9%, i.e.

Artificial sweeteners are used in protein substitutes intended for the dietary management of inborn errors of metabolism (phenylketonuria, PKU) to improve the variety of medical foods available to patients and ensure dietary adherence to the prescribed course of dietary management. These patients can be exposed to artificial sweeteners from the combination of free and prescribed foods. Young children have a higher risk of exceeding acceptable daily intakes (ADI) for additives than adults, due to higher food intakes per kg body weight. Young patients with PKU aged 1–3 years can be exposed to higher levels of artificial sweeteners from these dual sources than normal healthy children and are at a higher risk of exceeding the ADI. Standard intake assessment methods are not adequate to assess the additive exposure of young patients with PKU. The aim of this study was to estimate the combination effect on the intake of artificial sweeteners and the impact of the introduction of new provisions for an artificial sweetener (sucralose, E955) on exposure of PKU patients using a validated probabilistic model. Food consumption data were derived from the food consumption survey data of healthy young children in the United Kingdom from the National Diet and Nutrition Survey (NDNS, 1992–2012). Specially formulated protein substitutes as foods for special medical purposes (FSMPs) were included in the exposure model to replace restricted foods. Inclusion of these protein substitutes is based on recommendations to ensure adequate protein intake in these patients. Exposure assessment results indicated the availability of sucralose for use in FSMPs for PKU leads to changes in intakes in young patients. These data further support the viability of probabilistic modelling as a means to estimate food additive exposure in patients consuming medical nutrition products.

In order to ensure the food safety, risk managers may implement measures to reduce human exposure to contaminants via food consumption. The evaluation of the effect of a measure is often an overlooked step in risk analysis process. The aim of this study was to develop a systematic approach for determining the effectiveness of mitigation measures to reduce dietary exposure to chemical contaminants. Based on expert opinion, a general framework for evaluation of the effectiveness of measures to reduce human exposure to food contaminants was developed. The general outline was refined by application to three different cases: 1) methyl mercury in fish and fish products, 2) deoxynivalenol in cereal grains, and 3) furan in heated products. It was found that many uncertainties and natural variations exist, which make it difficult to assess the impact of the mitigation measure. Whenever possible, quantitative methods should be used to describe the current variation and uncertainty. Additional data should be collected to cover natural variability and reduce uncertainty. For the time being, it is always better for the risk manager to have access to all available information, including an assessment of uncertainty; however, the proposed methodology provides a conceptual framework for addressing these systematically.