Occurrence of chemicals in food, dietary exposure, and risk characterization: a comprehensive framework for consumer health

ABSTRACT: Chemical contaminants in foods represent a persistent challenge for consumer health protection, owing to the diversity of chemical hazards, the heterogeneity of food matrices, and the methodological complexity required to translate analytical occurrence data into meaningful public health conclusions. In response to these challenges, food chemical risk assessment has progressively evolved from predominantly deterministic and substance-centred approaches toward more refined frameworks that explicitly address variability, uncertainty, and population heterogeneity. Within this context, the present doctoral thesis investigates and applies progressively refined methodologies for dietary exposure assessment, integrating mass spectrometry–based analytical data with exposure modelling and risk characterisation in scenarios of regulatory relevance. The thesis is structured around multiple case studies covering both acute and chronic exposure scenarios and different food matrices characterised by distinct contamination patterns and consumption behaviours. Acute exposure assessment is explored through incident-driven contamination of spinach with tropane alkaloids, illustrating an analytical and exposure assessment framework to support decision-making during food safety emergencies, including the identification of uncertain contamination sources, and highlighting the particular vulnerability of younger population groups. Chronic exposure assessment is investigated in case-studies focusing on inorganic contaminants, including potentially toxic metals, in botanical preparations and bovine meat, employing probabilistic modelling to characterise long-term dietary intake distributions across different age groups. In these matrices, multi-elemental analysis based on Inductively Coupled Plasma Mass Spectrometry enabled the identification and quantification of over fifty inorganic elements, providing a robust analytical basis for exposure assessment. Overall, the results reveal substantial variability in both contaminant concentrations and food consumption patterns, which cannot be adequately captured by single-point estimates. Selected case studies further incorporate background dietary exposure, cumulative exposure, and exploratory risk–benefit perspectives for inorganic elements, allowing a more comprehensive interpretation of potential health impacts. Across all applications, probabilistic exposure modelling proved effective in identifying key drivers of exposure, characterising high-end intake scenarios, and reducing conservatism while maintaining a protective approach. Overall, the results demonstrate that stepwise refinement of exposure assessment, from screening-level deterministic evaluations to higher-tier probabilistic approaches, substantially improves the relevance and interpretability of risk characterisation. By systematically integrating analytical chemistry, dietary exposure modelling, and toxicological reference points, this thesis contributes to bridging the gap between occurrence data and proportionate, health-relevant conclusions, thereby supporting more informed and transparent food safety decision-making.