Browsing RIVM official reports by Publisher "Biometris"
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Integrated Probabilistic Risk Assessment (IPRA) for carcinogens : A first exploration(Rijksinstituut voor Volksgezondheid en Milieu RIVMBiometrisWageningen University and Research Centre, 2011-10-10)In 2007 the National Institute for Public Health and the Environment (RIVM) and Wageningen University developed the IPRA-method (Integrated Probabilistic Risk Assessment) to estimate which fraction of the population is affected by non-carcinogenic substances in food. Following research commissioned by the Dutch Food and Consumer Product Safety Authority (nVWA) the RIVM shows that the IPRA-method can also be applied to carcinogenic substances. In the IPRA-method the uncertainty in the available data is translated into confidence limits of the results. This gives a more realistic view on the potential health effect. This report describes how the required input data for the IPRAmethod and the results thereof need to be interpreted. As a result of the severe nature of the effect 'cancer' it is desirable that the extra risk of cancer following exposure to substances is very small, for example 1 in a million. Measuring such low cancer incidences would require animal testing at a scale that is too large to be feasible. Therefore, these low risks cannot be measured in animal studies. In practice, measurable cancer incidences from animal experiments are linearly extrapolated to the desired low (non-measurable) cancer incidences. A case study with the carcinogenic mycotoxin aflatoxin B1 illustrates that the uncertainties in risk estimates related to carcinogenic substances are indeed very large. The currently applied linear extrapolation technique results in a single, supposedly conservative, risk estimate, without showing the associated uncertainties. The IPRA-method on the other hand does provide an indication of the uncertainty in the risk estimate. As such it may be a very promising tool for risk managers. The outcome of the method more realistically reflects to what extent quantitative statements on the risk can be made, given the available information. This allows the risk manager to make better informed decisions.
Model-Then-Add : Usual intake modelling of multimodal intake distributions(Rijksinstituut voor Volksgezondheid en Milieu RIVMBiometrisDLOWageningen University and Research centre, 2014-03-20)The National Institute for Public Health and the Environment (RIVM) and Wageningen University and Research Centre (WUR) have jointly developed software to estimate the amount of chemicals ingested via the diet (Monte Carlo Risk Assessment, MCRA). Examples of such chemicals include contaminants (e.g. acrylamide, dioxins, lead) and micronutrients. To estimate the intake of these chemicals in the long run, a module called Model-Then-Add has been added to the software. The long-term intake is relevant for chemicals that exert their beneficial or adverse health effect over a long period of ingestion. The Model-Then-Add module can be used when the distribution of individual mean intakes of the chemical in a population does not display a normal statistical distribution after a logarithmic transformation. This may, for example, be the case when the chemical is present in only a limited number of foods. In such cases, the module can be used to obtain a more realistic estimation of the longterm intake. A case study was performed to assess the long-term intake of smoke aromas, a group of chemicals that is potentially adverse at high intakes, using the Model- Then-Add module and the presently used methodology, which is known to overestimate the long-term exposure. The Model-Then-Add module resulted in lower intakes. The use of this module may thus result in less risk mitigation or environmental policy measures that need to be taken to reduce possible health risks. To estimate the intake of chemicals via the diet using MCRA, concentrations of chemicals in foods and beverages are linked to information on the consumption of these foods during a limited number of days. In the Netherlands, food consumption data are typically obtained from the Dutch National Food Consumption Surveys (Voedselconsumptiepeiling, VCP), in which information on food consumption is collected during two days. Statistical models are necessary to assess the long-term intake of chemicals based on these data.
The practicability of the integrated probabilistic risk assessment (IPRA) approach for substances in food(Rijksinstituut voor Volksgezondheid en Milieu RIVMRIKILTBiometris, 2009-09-04)In the Netherlands, the National Institute for Public Health and the Environment (RIVM) has successfully applied the IPRA approach to assess the human health risks of five substances in food. This method has been developed so that health risks can be described in more detail when a classical risk assessment has shown either that there is a risk or a risk cannot be excluded. Using the IPRA approach enables more information to be gained on the fraction of the affected population in relation to the severity of the effect. Based on this information, authorities can then take targeted measures to prevent any risk to human health. It is expected that the IPRA methodology will be suitable for use with other substances. The above has been concluded from research performed by the RIVM in collaboration with Biometris and RIKILT - organizations that fall under Wageningen University and Research Centre. The research was commissioned by the Dutch Food and Consumer Product Safety Authority (VWA). In the present study, the risks of two mycotoxins (DON and T-2/HT-2), one heavy metal (cadmium), one group of pesticides (OPs), and one compound (acrylamide) which is formed during the heating of food containing high levels of starch are described. The IPRA approach enables the amount of a substance with which a population is exposed to that substance through food to be compared with the maximum safe level. Differences between individuals and possible calculation errors have been accounted for. The IPRA showed that the exposure of the five substances studied was below the levels considered safe. The health risks can therefore be considered negligible. Furthermore, the method can provide more insight on which additional information could be gathered in order to improve the risk assessment. This would help targeted follow-up research to take place.