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A conceptual framework for the collection of food products in a Total Diet Study Part A Chemistry, analysis, control, exposure & risk assessment

Turrini, Aida, Lombardi-Boccia, Ginevra, Aureli, Federica, Cubadda, Francesco, D’Addezio, Laura, D’Amato, Marilena, D’Evoli, Laura, Darnerud, PerOla, Devlin, Niamh, Dias, Maria Graça, Jurković, Marina, Kelleher, Cecily, Le Donne, Cinzia, López Esteban, Maite, Lucarini, Massimo, Martinez Burgos, Maria Alba, Martínez-Victoria, Emilio, McNulty, Breige, Mistura, Lorenza, Nugent, Anne, Oktay Basegmez, Hatice Imge, Oliveira, Luisa, Ozer, Hayrettin, Perelló, Gemma, Pite, Marina, Presser, Karl, Sokolić, Darja, Vasco, Elsa, Volatier, Jean-Luc
Food additives & contaminants 2018 v.35 no.2 pp. 171-190
European Union, Total Diet Study, chemical pollutants, data collection, dietary nutrient sources, exposure assessment, food intake, foods, models, nutrients, protocols
A total diet study (TDS) provides representative and realistic data for assessing the dietary intake of chemicals, such as contaminants and residues, and nutrients, at a population level. Reproducing the diet through collection of customarily consumed foods and their preparation as habitually eaten is crucial to ensure representativeness, i.e., all relevant foods are included and all potential dietary sources of the substances investigated are captured. Having this in mind, a conceptual framework for building a relevant food-shopping list was developed as a research task in the European Union’s 7th Framework Program project, ‘Total Diet Study Exposure’ (TDS-Exposure), aimed at standardising methods for food sampling, analyses, exposure assessment calculations and modelling, priority foods, and selection of chemical contaminants. A stepwise approach following the knowledge translation (KT) model for concept analysis is proposed to set up a general protocol for the collection of food products in a TDS in terms of steps (characterisation of the food list, development of the food-shopping list, food products collection) and pillars (background documentation, procedures, and tools). A simple model for structuring the information in a way to support the implementation of the process, by presenting relevant datasets, forms to store inherent information, and folders to record the results is also proposed. Reproducibility of the process and possibility to exploit the gathered information are two main features of such a system for future applications.