TY  - JOUR
AU  - Huybrechts, Inge
AU  - Rauber, Fernanda
AU  - Nicolas, Geneviève
AU  - Casagrande, Corinne
AU  - Kliemann, Nathalie
AU  - Wedekind, Roland
AU  - Biessy, Carine
AU  - Scalbert, Augustin
AU  - Touvier, Mathilde
AU  - Aleksandrova, Krasimira
AU  - Jakszyn, Paula
AU  - Skeie, Guri
AU  - Bajracharya, Rashmita
AU  - Boer, Jolanda M A
AU  - Borné, Yan
AU  - Chajes, Veronique
AU  - Dahm, Christina C
AU  - Dansero, Lucia
AU  - Guevara, Marcela
AU  - Heath, Alicia K
AU  - Ibsen, Daniel B
AU  - Papier, Keren
AU  - Katzke, Verena
AU  - Kyrø, Cecilie
AU  - Masala, Giovanna
AU  - Molina-Montes, Esther
AU  - Robinson, Oliver J K
AU  - Santiuste de Pablos, Carmen
AU  - Schulze, Matthias B
AU  - Simeon, Vittorio
AU  - Sonestedt, Emily
AU  - Tjønneland, Anne
AU  - Tumino, Rosario
AU  - van der Schouw, Yvonne T
AU  - Verschuren, W M Monique
AU  - Vozar, Beatrice
AU  - Winkvist, Anna
AU  - Gunter, Marc J
AU  - Monteiro, Carlos A
AU  - Millett, Christopher
AU  - Levy, Renata Bertazzi
TI  - Characterization of the degree of food processing in the European Prospective Investigation into Cancer and Nutrition: Application of the Nova classification and validation using selected biomarkers of food processing.
JO  - Frontiers in nutrition
VL  - 9
SN  - 2296-861X
CY  - Lausanne
PB  - Frontiers Media
M1  - DKFZ-2023-00004
SP  - 1035580
PY  - 2022
AB  - Epidemiological studies have demonstrated an association between the degree of food processing in our diet and the risk of various chronic diseases. Much of this evidence is based on the international Nova classification system, which classifies food into four groups based on the type of processing: (1) Unprocessed and minimally processed foods, (2) Processed culinary ingredients, (3) Processed foods, and (4) 'Ultra-processed' foods (UPF). The ability of the Nova classification to accurately characterise the degree of food processing across consumption patterns in various European populations has not been investigated so far. Therefore, we applied the Nova coding to data from the European Prospective Investigation into Cancer and Nutrition (EPIC) in order to characterize the degree of food processing in our diet across European populations with diverse cultural and socio-economic backgrounds and to validate this Nova classification through comparison with objective biomarker measurements.After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5
KW  - EPIC (Other)
KW  - Nova (Other)
KW  - biomarkers (Other)
KW  - elaidic acid (Other)
KW  - food processing (Other)
KW  - syringol (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:36590209
C2  - pmc:PMC9800919
DO  - DOI:10.3389/fnut.2022.1035580
UR  - https://inrepo02.dkfz.de/record/186551
ER  -