AUTHOR=Huybrechts Inge , Rauber Fernanda , Nicolas Geneviève , Casagrande Corinne , Kliemann Nathalie , Wedekind Roland , Biessy Carine , Scalbert Augustin , Touvier Mathilde , Aleksandrova Krasimira , Jakszyn Paula , Skeie Guri , Bajracharya Rashmita , Boer Jolanda M. A. , Borné Yan , Chajes Veronique , Dahm Christina C. , Dansero Lucia , Guevara Marcela , Heath Alicia K. , Ibsen Daniel B. , Papier Keren , Katzke Verena , Kyrø Cecilie , Masala Giovanna , Molina-Montes Esther , Robinson Oliver J. K. , Santiuste de Pablos Carmen , Schulze Matthias B. , Simeon Vittorio , Sonestedt Emily , Tjønneland Anne , Tumino Rosario , van der Schouw Yvonne T. , Verschuren W. M. Monique , Vozar Beatrice , Winkvist Anna , Gunter Marc J. , Monteiro Carlos A. , Millett Christopher , Levy Renata Bertazzi 

TITLE=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

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2022.1035580

DOI=10.3389/fnut.2022.1035580

ISSN=2296-861X

ABSTRACT=Background
Epidemiological studies demonstrated associations between the degree of food processing in our diet and the risk of chronic diseases. Much of this evidence is based on the international Nova classification, which classifies food into four groups based on the type of processing. 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 and to validate this Nova classification through comparison with objective biomarker measurements.
Methods
A total of 476,768 EPIC participants (71.5% women) were included in the cross-sectional analysis characterizing consumption patterns based on the Nova classification. The consumption of food products classified as different Nova categories were compared to relevant circulating biomarkers denoting food processing, measured in various subsamples within the EPIC cohort via (partial) correlation analyses (unadjusted and adjusted by sex, age, BMI and country). These biomarkers included an industrial transfatty acid (ITFA) isomer (elaidic acid; exogenous fatty acid generated during oil hydrogenation/heating) and urinary 4-methyl syringol sulfate (an indicator for the consumption of smoked food and a component of liquid smoke used in UPF).  
Results
Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and contributions to overall % energy intake from 15% (Spain & Italy) to >45% (UK and Norway). The UPF pattern as defined based on the Nova classification (group 4) was strongly positively associated with blood levels of industrial elaidic acid (r=0.54) and 4-methyl syringol sulfate (r=0.43). Associations for the other 3 Nova groups with these food processing biomarkers were either inverse or non-significant (e.g. for unprocessed and minimally processed foods these correlations were -0.07 and -0.38 for elaidic acid and 4-methyl syringol sulfate respectively).
Conclusion
These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF and suggest that the Nova classification can accurately capture consumption of UPF, reflected by stronger correlations with circulating levels of industrial elaidic acid and a syringol metabolite compared to diets high in minimally processed foods.