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Prospective associations between dietary patterns and high sensitivity C-reactive protein in European children: the IDEFICS study

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Abstract

Purpose

This prospective study explores high sensitivity C-reactive protein (hs-CRP) levels in relation to dietary patterns at two time points in European children.

Methods

Out of the baseline sample of the IDEFICS study (n = 16,228), 4020 children, aged 2–9 years at baseline, with available hs-CRP levels and valid data from a food frequency questionnaire (FFQ) at baseline (T0) and 2 years later (T1) were included. K-means clustering algorithm based on the similarities between relative food consumption frequencies of the FFQ was applied. hs-CRP was dichotomized according to sex-specific cutoff points. Multilevel logistic regression was performed to assess the relationship between dietary patterns and hs-CRP adjusting for covariates.

Results

Three consistent dietary patterns were found at T0 and T1: ‘animal protein and refined carbohydrate’, ‘sweet and processed’ and ‘healthy’. Children allocated to the ‘protein’ and ‘sweet and processed’ clusters at both time points had significantly higher odds of being in the highest category of hs-CRP (OR 1.47; 95% CI 1.03–2.09 for ‘animal protein and refined carbohydrate’ and OR 1.44; 95% CI 1.08–1.92 for ‘sweet and processed’) compared to the ‘healthy’ cluster. The odds remained significantly higher for the ‘sweet and processed’ pattern (OR 1.39; 95% CI 1.05–1.84) when covariates were included.

Conclusions

A dietary pattern characterized by frequent consumption of sugar and processed products and infrequent consumption of vegetables and fruits over time was independently related with inflammation in European children. Efforts to improve the quality of the diet in childhood may prevent future diseases related with chronic inflammation.

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Acknowledgements

This work was done as part of the IDEFICS Study and was published on behalf of its European Consortium (http://www.idefics.eu). The information in this document reflects the author’s view and is provided as is. We gratefully acknowledge the financial support of the European Community within the Sixth RTD Framework Programme Contract No. 016181 (FOOD).

Author information

Authors and Affiliations

  1. GENUD (Growth, Exercise, NUtrition and Development) Research Group, Faculty of Health Sciences, Universidad de Zaragoza, C/ Pedro Cerbuna, 12, 50009, Zaragoza, Spain

    Esther María González-Gil, Juan Miguel Fernández-Alvira & Luis Alberto Moreno Aznar

  2. Instituto Agroalimentario de Aragón (IA2), Zaragoza, Spain

    Esther María González-Gil & Luis Alberto Moreno Aznar

  3. Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain

    Esther María González-Gil & Luis Alberto Moreno Aznar

  4. Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERObn), Madrid, Spain

    Esther María González-Gil, Catalina Picó & Luis Alberto Moreno Aznar

  5. Section for Epidemiology and Social Medicine (EPSO), Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

    Gianluca Tognon & Lauren Lissner

  6. Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany

    Timm Intemann & Maike Wolters

  7. Department of Preventive Medicine, Nutritional Epidemiology Unit, Fondazione IRCSS Istituto Nazionale dei Tumori, Milan, Italy

    Valeria Pala

  8. Department of Pharmacological Sciences, University of Milan, Milan, Italy

    Claudio Galli

  9. Unit of Epidemiology and Population Genetics, Institute of Food Sciences, National Research Council, Avellino, Italy

    Alfonso Siani

  10. National Institute for Health Development, Estonian Centre of Behavioral and Health Sciences, Tallinn, Estonia

    Toomas Veidebaum

  11. Department of Public Health, Ghent University, Ghent, Belgium

    Nathalie Michels

  12. Department of Paediatrics, Medical Faculty, University of Pécs, Pécs, Hungary

    Denes Molnar

  13. Department of Public Health and Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland

    Jaakko Kaprio

  14. Research and Education Institute of Child health, REF, Strovolos, Cyprus

    Yannis Kourides

  15. Laboratoriumsmedizin Dortmund, Eberhard & Partner, Dortmund, Germany

    Arno Fraterman

  16. IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Molise, Italy

    Licia Iacoviello

  17. Laboratory of Molecular Biology, Nutrition and Biotechnology, University of the Balearic Islands, Palma de Mallorca, Spain

    Catalina Picó

  18. Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC) Carlos III, Madrid, Spain

    Juan Miguel Fernández-Alvira

Authors
  1. Esther María González-Gil
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  2. Gianluca Tognon
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  3. Lauren Lissner
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  4. Timm Intemann
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  5. Valeria Pala
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  6. Claudio Galli
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  8. Alfonso Siani
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  9. Toomas Veidebaum
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  15. Licia Iacoviello
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  18. Luis Alberto Moreno Aznar
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Consortia

on behalf of the IDEFICS Consortium

Corresponding author

Correspondence to Esther María González-Gil.

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Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

J. M. Fernández-Alvira and L. A. M. Aznar equally contributed to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

394_2017_1419_MOESM1_ESM.png

Supplementary figure 1. Z-Scores of relative consumption frequencies in the ‘healthy’ pattern in baseline (T0). Highest mean values per food item in comparison with the other two patterns. (PNG 199 KB)

394_2017_1419_MOESM2_ESM.png

Supplementary figure 2. Z-Scores of relative consumption frequencies in the ‘healthy’ pattern in baseline (T0). Lowest mean values per food item in comparison with the other two patterns. (PNG 208 KB)

394_2017_1419_MOESM3_ESM.png

Supplementary figure 3. Z-Scores of relative consumption frequencies in the ‘healthy’ pattern in follow-up (T1). Highest mean values per food item in comparison with the other two patterns. (PNG 171 KB)

394_2017_1419_MOESM4_ESM.png

Supplementary figure 4. Z-Scores of relative consumption frequencies in the ‘healthy’ pattern in follow-up (T1). Lowest mean values per food item in comparison with the other two patterns. (PNG 186 KB)

394_2017_1419_MOESM5_ESM.png

Supplementary figure 5. Z-Scores of relative consumption frequencies in the ‘animal protein and refined carbohydrate’ pattern in baseline (T0). Highest mean values per food item in comparison with the other two patterns. (PNG 196 KB)

394_2017_1419_MOESM6_ESM.png

Supplementary figure 6. Z-Scores of relative consumption frequencies in the ‘animal protein and refined carbohydrate’ pattern in baseline (T0). Lowest mean values per food item in comparison with the other two patterns. (PNG 177 KB)

394_2017_1419_MOESM7_ESM.png

Supplementary figure 7. Z-Scores of relative consumption frequencies in the ‘animal protein and refined carbohydrate’ pattern in follow-up (T1). Highest mean values per food item in comparison with the other two patterns. (PNG 204 KB)

394_2017_1419_MOESM8_ESM.png

Supplementary figure 8. Z-Scores of relative consumption frequencies in the ‘animal protein and refined carbohydrate’ pattern in follow-up (T1). Lowest mean values per food item in comparison with the other two patterns. (PNG 181 KB)

394_2017_1419_MOESM9_ESM.png

Supplementary figure 9. Z-Scores of relative consumption frequencies in the ‘sweet and processed’ pattern in baseline (T0). Highest mean values per food item in comparison with the other two patterns. (PNG 226 KB)

394_2017_1419_MOESM10_ESM.png

Supplementary figure 10. Z-Scores of relative consumption frequencies in the ‘sweet and processed’ pattern in baseline (T0). Lowest mean values per food item in comparison with the other two patterns. (PNG 173 KB)

394_2017_1419_MOESM11_ESM.png

Supplementary figure 11. Z-Scores of relative consumption frequencies in the ‘sweet and processed’ pattern in follow-up (T1). Highest mean values per food item in comparison with the other two patterns. (PNG 243 KB)

394_2017_1419_MOESM12_ESM.png

Supplementary figure 12. Z-Scores of relative consumption frequencies in the ‘sweet and processed’ pattern in follow-up (T1). Lowest mean values per food item in comparison with the other two patterns. (PNG 179 KB)

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González-Gil, E.M., Tognon, G., Lissner, L. et al. Prospective associations between dietary patterns and high sensitivity C-reactive protein in European children: the IDEFICS study. Eur J Nutr 57, 1397–1407 (2018). https://doi.org/10.1007/s00394-017-1419-x

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