Evidence map›Paper›PMID 36590209›Full record

ArticleFrontiers in nutrition2022

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.

Inge Huybrechts, Fernanda Rauber, Geneviève Nicolas, Corinne Casagrande, Nathalie Kliemann, Roland Wedekind, Carine Biessy, Augustin Scalbert, Mathilde Touvier, Krasimira Aleksandrova and 31 more

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. The role of ultra-processed food in obesity.Nature reviews. Endocrinology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

41 authors.

Inge HuybrechtsNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Fernanda RauberDepartment of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.
Geneviève NicolasNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Corinne CasagrandeNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Nathalie KliemannNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Roland WedekindNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Carine BiessyNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Augustin ScalbertNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Mathilde TouvierSorbonne 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 AleksandrovaDepartment of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen, Germany.
Paula JakszynUnit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain.
Guri SkeieDepartment of Community Medicine, UiT the Arctic University of Norway, Tromsø, Norway.
Rashmita BajracharyaGerman Cancer Research Center (DKFZ), Heidelberg, Germany.
Jolanda M A BoerCentre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Yan BornéDepartment of Clinical Sciences Malmö, Faculty of Medicine, Nutritional Epidemiology, Lund University, Lund, Sweden.
Veronique ChajesNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Christina C DahmDepartment of Public Health, Aarhus University, Aarhus, Denmark.
Lucia DanseroDepartment of Clinical and Biological Sciences, Centre for Biostatistics, Epidemiology, and Public Health (C-BEPH), University of Turin, Turin, Italy.
Marcela GuevaraInstituto de Salud Pública de Navarra, Pamplona, Spain.
Alicia K HeathDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.
Daniel B IbsenDepartment of Public Health, Aarhus University, Aarhus, Denmark.
Keren PapierCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Verena KatzkeGerman Cancer Research Center (DKFZ), Heidelberg, Germany.
Cecilie KyrøDanish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark.
Giovanna MasalaClinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.
Esther Molina-MontesDepartment of Nutrition and Food Science, Campus of Cartuja, University of Granada, Granada, Spain.
Oliver J K RobinsonMRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Carmen Santiuste de PablosCIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Matthias B SchulzeDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
Vittorio SimeonDipartimento di Salute Mentale e Fisica e Medicina Preventiva, Vanvitelli University, Naples, Italy.
Emily SonestedtDepartment of Clinical Sciences Malmö, Faculty of Medicine, Nutritional Epidemiology, Lund University, Lund, Sweden.
Anne TjønnelandDanish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark.
Rosario TuminoHyblean Association for Epidemiological Research, AIRE ONLUS, Ragusa, Italy.
Yvonne T van der SchouwJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
W M Monique VerschurenCentre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Beatrice VozarNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Anna WinkvistSustainable Health, Department Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Marc J GunterNutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
Carlos A MonteiroCenter for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, Brazil.
Christopher MillettDepartment of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.
Renata Bertazzi LevyDepartment of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil.

Funding

Cancer Research UK 14136Cancer Research UK 29017Cancer Research UK 29678Medical Research Council G0401527Medical Research Council G1000143Medical Research Council MR/M012190/1Medical Research Council MR/N003284/1Medical Research Council MR/S019669/1Medical Research Council MR/S03532X/1World Health Organization 001
6 · The paper itself

Abstract

Background: 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: 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: 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: 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.

Indexed as

biomarkerselaidic acidEPICfood processingNovasyringol

Identifiers

PMID36590209
PMCPMC9800919

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.