Modified Reference Point Index (mRPI) and a decision tree for deriving uncertainty factors: A practical approach to cumulative risk assessment of food contaminant mixtures. (December 2019) - Vejdovszky, Katharina; Mihats, Daniela; Griesbacher, Antonia; Wolf, Josef; Steinwider, Johann; Lueckl, Johannes; Jank, Bernhard; Kopacka, Ian; Rauscher-Gabernig, Elke
Abstract: Risk assessment of chemical mixtures remains a challenging task in all areas of food and consumer safety. So far, no general method has been developed that is best suited to several subject areas (e.g. food contaminants, additives and supplements, plant protection products). Especially for mixtures of food contaminants sophisticated methods are typically not applicable due to a general lack of complete toxicological data sets. We developed a new approach, the modified Reference Point Index (mRPI), that combines the advantages of the Hazard Index and the Reference Point Index . Furthermore, we developed a decision tree for the determination of specific uncertainty factors that makes the mRPI an easy to use method for cumulative risk assessment even in a data poor field such as food contaminants. To further characterise the estimated cumulative risks, the Maximum Cumulative Ratio (MCR) was adapted to be applied on the mRPI, and the modified Maximum Cumulative Ratio (mMCR) was established to identify whether the risks are dominated by a single substance. We present two case studies assessing the nephrotoxic and neurotoxic risks for the Austrian population originating from food contaminant mixtures. Calculations could not rule out potential cumulative risks, yet, they seemed to be dominated by single substances. Highlights: The modified Reference Point Index combines the advantages of the Hazard Index and the Reference Point Index. A decision tree was developed to facilitate the use of the mRPI to determine specific uncertainty factors. The mRPI provides a transparent approach to cumulative risk assessment, even in a data poor field such as food contaminants. Calculated risks can be characterised by the Maximum Cumulative Ratio to identify major contributing substances.