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Abstract: Risk managers need detailed information on (1) the type of effect, (2) the size (severity) of the expected effect(s) and (3) the fraction of the population at risk to decide on well-balanced risk reduction measures. A previously developed integrated probabilistic risk assessment (IPRA) model provides quantitative information on these three parameters. A semi-quantitative tool is presented that combines information on these parameters into easy-readable charts that will facilitate risk evaluations of exposure situations and decisions on risk reduction measures. This tool is based on a concept of health impact categorization that has been successfully in force for several years within several emergency planning programs. Four health impact categories are distinguished: No-Health Impact, Low-Health Impact, Moderate-Health Impact and Severe-Health Impact. Two different charts are presented to graphically present the information on the three parameters of interest. A bar plot provides an overview of all health effects involved, including information on the fraction of the exposed population in each of the four health impact categories. Secondly, a Health Impact Chart is presented to provide more detailed information on the estimated health impact in a given exposure situation. These graphs will facilitate the discussions on appropriate risk reduction measures to be taken. [Copyright &y& Elsevier]

Abstract: A statistical model is presented extending the integrated probabilistic risk assessment (IPRA) model of van der Voet and Slob [van der Voet, H., Slob, W., 2007. Integration of probabilistic exposure assessment and probabilistic hazard characterisation. Risk Analysis, 27, 351–371]. The aim is to characterise the health impact due to one or more chemicals present in food causing one or more health effects. For chemicals with hardly any measurable safety problems we propose health impact characterisation by margins of exposure. In this probabilistic model not one margin of exposure is calculated, but rather a distribution of individual margins of exposure (IMoE) which allows quantifying the health impact for small parts of the population. A simple bar chart is proposed to represent the IMoE distribution and a lower bound (IMoEL) quantifies uncertainties in this distribution. It is described how IMoE distributions can be combined for dose-additive compounds and for different health effects. Health impact assessment critically depends on a subjective valuation of the health impact of a given health effect, and possibilities to implement this health impact valuation step are discussed. Examples show the possibilities of health impact characterisation and of integrating IMoE distributions. The paper also includes new proposals for modelling variable and uncertain factors describing food processing effects and intraspecies variation in sensitivity. [Copyright &y& Elsevier]