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.

EPIC Nova biomarkers elaidic acid food processing syringol

Journal

Frontiers in nutrition
ISSN: 2296-861X
Titre abrégé: Front Nutr
Pays: Switzerland
ID NLM: 101642264

Informations de publication

Date de publication:
2022
Historique:
received: 02 09 2022
accepted: 17 11 2022
entrez: 2 1 2023
pubmed: 3 1 2023
medline: 3 1 2023
Statut: epublish

Résumé

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% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25-p75: 58-66] years) were included in the cross-sectional analysis that characterised 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 (N between 417 and 9,460) 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 and heating) and urinary 4 Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid ( These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results 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.

Sections du résumé

Background UNASSIGNED
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.
Methods UNASSIGNED
After grouping foods in the EPIC dataset according to the Nova classification, a total of 476,768 participants in the EPIC cohort (71.5% women; mean age 51 [standard deviation (SD) 9.93]; median age 52 [percentile (p)25-p75: 58-66] years) were included in the cross-sectional analysis that characterised 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 (N between 417 and 9,460) 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 and heating) and urinary 4
Results UNASSIGNED
Contributions of UPF intake to the overall diet in % grams/day varied across countries from 7% (France) to 23% (Norway) and their contributions to overall % energy intake from 16% (Spain and Italy) to >45% (in the UK and Norway). Differences were also found between sociodemographic groups; participants in the highest fourth of UPF consumption tended to be younger, taller, less educated, current smokers, more physically active, have a higher reported intake of energy and lower reported intake of alcohol. The UPF pattern as defined based on the Nova classification (group 4;% kcal/day) was positively associated with blood levels of industrial elaidic acid (
Conclusion UNASSIGNED
These results, based on a large pan-European cohort, demonstrate sociodemographic and geographical differences in the consumption of UPF. Furthermore, these results 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.

Identifiants

pubmed: 36590209
doi: 10.3389/fnut.2022.1035580
pmc: PMC9800919
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1035580

Subventions

Organisme : Medical Research Council
ID : MR/N003284/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0401527
Pays : United Kingdom
Organisme : Medical Research Council
ID : G1000143
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 14136
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S019669/1
Pays : United Kingdom

Commentaires et corrections

Type : ErratumIn

Informations de copyright

Copyright © 2022 Huybrechts, Rauber, Nicolas, Casagrande, Kliemann, Wedekind, Biessy, Scalbert, Touvier, Aleksandrova, Jakszyn, Skeie, Bajracharya, Boer, Borné, Chajes, Dahm, Dansero, Guevara, Heath, Ibsen, Papier, Katzke, Kyrø, Masala, Molina-Montes, Robinson, Santiuste de Pablos, Schulze, Simeon, Sonestedt, Tjønneland, Tumino, van der Schouw, Verschuren, Vozar, Winkvist, Gunter, Monteiro, Millett and Levy.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Inge Huybrechts (I)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Fernanda Rauber (F)

Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.
Center for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, Brazil.

Geneviève Nicolas (G)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Corinne Casagrande (C)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Nathalie Kliemann (N)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Roland Wedekind (R)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Carine Biessy (C)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Augustin Scalbert (A)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Mathilde Touvier (M)

Sorbonne Paris Nord University, INSERM U1153, INRAE U1125, CNAM, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University Paris Cité (CRESS), Paris, France.

Krasimira Aleksandrova (K)

Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen, Germany.
Human and Health Sciences, University of Bremen, Bremen, Germany.

Paula Jakszyn (P)

Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain.
Blanquerna School of Health Sciences, Ramon Llull University, Barcelona, Spain.

Guri Skeie (G)

Department of Community Medicine, UiT the Arctic University of Norway, Tromsø, Norway.

Rashmita Bajracharya (R)

German Cancer Research Center (DKFZ), Heidelberg, Germany.

Jolanda M A Boer (JMA)

Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.

Yan Borné (Y)

Department of Clinical Sciences Malmö, Faculty of Medicine, Nutritional Epidemiology, Lund University, Lund, Sweden.

Veronique Chajes (V)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Christina C Dahm (CC)

Department of Public Health, Aarhus University, Aarhus, Denmark.

Lucia Dansero (L)

Department of Clinical and Biological Sciences, Centre for Biostatistics, Epidemiology, and Public Health (C-BEPH), University of Turin, Turin, Italy.

Marcela Guevara (M)

Instituto de Salud Pública de Navarra, Pamplona, Spain.
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Navarra Institute for Health Research (IdiSNA), Pamplona, Spain.

Alicia K Heath (AK)

Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.

Daniel B Ibsen (DB)

Department of Public Health, Aarhus University, Aarhus, Denmark.
Steno Diabetes Center Aarhus, Aarhus, Denmark.
MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.
Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark.

Keren Papier (K)

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.

Verena Katzke (V)

German Cancer Research Center (DKFZ), Heidelberg, Germany.

Cecilie Kyrø (C)

Danish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark.

Giovanna Masala (G)

Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.

Esther Molina-Montes (E)

Department of Nutrition and Food Science, Campus of Cartuja, University of Granada, Granada, Spain.
CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain.
Biomedical Research Centre, Institute of Nutrition and Food Technology (INYTA) "José Mataix", University of Granada, Granada, Spain.

Oliver J K Robinson (OJK)

MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.

Carmen Santiuste de Pablos (C)

CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.

Matthias B Schulze (MB)

Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
Institute of Nutritional Science, University of Potsdam, Potsdam, Germany.

Vittorio Simeon (V)

Dipartimento di Salute Mentale e Fisica e Medicina Preventiva, Vanvitelli University, Naples, Italy.

Emily Sonestedt (E)

Department of Clinical Sciences Malmö, Faculty of Medicine, Nutritional Epidemiology, Lund University, Lund, Sweden.

Anne Tjønneland (A)

Danish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark.

Rosario Tumino (R)

Hyblean Association for Epidemiological Research, AIRE ONLUS, Ragusa, Italy.

Yvonne T van der Schouw (YT)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

W M Monique Verschuren (WMM)

Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

Beatrice Vozar (B)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Anna Winkvist (A)

Sustainable Health, Department Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Marc J Gunter (MJ)

Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.

Carlos A Monteiro (CA)

Center for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, Brazil.
Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil.

Christopher Millett (C)

Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.
Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, London, United Kingdom.

Renata Bertazzi Levy (RB)

Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.
Center for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, Brazil.

Classifications MeSH