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Interventions and public health nutrition

Country-specific dietary patterns and associations with socioeconomic status in European children: the IDEFICS study

European Journal of Clinical Nutrition volume 68, pages 811–821 (2014)Cite this article

Subjects

Abstract

Background/objectives:

Children from lower socioeconomic status (SES) may be at higher risk of unhealthy eating. We described country-specific dietary patterns among children aged 2–9 years from eight European countries participating in the IDEFICS study and assessed the association of dietary patterns with an additive SES indicator.

Subjects/Methods:

Children aged 2–9 years from eight European countries were recruited in 2007–2008. Principal component analysis was applied to identify dietary country-specific patterns. Linear regression analyses were applied to assess their association with SES.

Results:

Two to four dietary patterns were identified in the participating regions. The existence of a ‘processed’ pattern was found in the eight regions. Also, a ‘healthy’ pattern was identified in seven of the eight regions. In addition, region-specific patterns were identified, reflecting the existing gastronomic and cultural differences in Europe. The ‘processed’ pattern was significantly inversely associated with the SES additive indicator in all countries except Sweden, whereas the ‘healthy’ pattern was positively associated with SES in the Belgian, Estonian, German and Hungarian regions, but was not significant in the Italian, Spanish and Swedish regions.

Conclusions:

A ‘processed’ pattern and a ‘healthy‘ pattern were found in most of the participating countries in the IDEFICS study, with comparable food item profiles. The results showed a strong inverse association of SES with the ‘processed’ pattern, suggesting that children of parents with lower SES may be at higher risk of unhealthy eating. Therefore, special focus should be given to parents and their children from lower SES levels when developing healthy eating promotion strategies.

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References

  1. Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M et al. Socioeconomic inequalities in health in 22 European countries. N Engl J Med 2008; 358: 2468–2481.

    Article  CAS  Google Scholar 

  2. Mackenbach JP, Kunst AE . Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med 1997; 44: 757–771.

    Article  CAS  Google Scholar 

  3. Galobardes B, Lynch J, Smith GD . Measuring socioeconomic position in health research. Br Med Bull 2007; 81-82: 21–37.

    Article  Google Scholar 

  4. Darmon N, Drewnowski A . Does social class predict diet quality? Am J Clin Nutr 2008; 87: 1107–1117.

    Article  CAS  Google Scholar 

  5. Fernandez-Alvira JM, Mouratidou T, Bammann K, Hebestreit A, Barba G, Sieri S et al. Parental education and frequency of food consumption in European children: the IDEFICS study. Public Health Nutr 2013; 16: 487–498.

    Article  Google Scholar 

  6. Lioret S, Touvier M, Lafay L, Volatier JL, Maire B . Dietary and physical activity patterns in French children are related to overweight and socioeconomic status. J Nutr 2008; 138: 101–107.

    Article  CAS  Google Scholar 

  7. Cutler GJ, Flood A, Hannan P, Neumark-Sztainer D . Multiple sociodemographic and socioenvironmental characteristics are correlated with major patterns of dietary intake in adolescents. J Am Diet Assoc 2011; 111: 230–240.

    Article  Google Scholar 

  8. Sausenthaler S, Kompauer I, Mielck A, Borte M, Herbarth O, Schaaf B et al. Impact of parental education and income inequality on children’s food intake. Public Health Nutr 2007; 10: 24–33.

    Article  Google Scholar 

  9. Pala V, Lissner L, Hebestreit A, Lanfer A, Sieri S, Siani A et al. Dietary patterns and longitudinal change in body mass in European children: a follow-up study on the IDEFICS multicenter cohort. Eur J Clin Nutr 2013; 67: 1042–1049.

    Article  CAS  Google Scholar 

  10. Hu FB . Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 2002; 13: 3–9.

    Article  CAS  Google Scholar 

  11. Moeller SM, Reedy J, Millen AE, Dixon LB, Newby PK, Tucker KL et al. Dietary patterns: challenges and opportunities in dietary patterns research an Experimental Biology workshop, April 1, 2006. J Am Diet Assoc 2007; 107: 1233–1239.

    Article  Google Scholar 

  12. Michels KB, Schulze MB . Can dietary patterns help us detect diet-disease associations? Nutr Res Rev 2005; 18: 241–248.

    Article  Google Scholar 

  13. Jacques PF, Tucker KL . Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr 2001; 73: 1–2.

    Article  CAS  Google Scholar 

  14. Naska A, Fouskakis D, Oikonomou E, Almeida MD, Berg MA, Gedrich K et al. Dietary patterns and their socio-demographic determinants in 10 European countries: data from the DAFNE databank. Eur J Clin Nutr 2006; 60: 181–190.

    Article  CAS  Google Scholar 

  15. Ahrens W, Bammann K, Siani A, Buchecker K, De Henauw S, Iacoviello L et al. The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obes 2011; 35: S3–S15.

    Article  Google Scholar 

  16. Ahrens W, Bammann K, de Henauw S, Halford J, Palou A, Pigeot I et al. Understanding and preventing childhood obesity and related disorders–IDEFICS: a European multilevel epidemiological approach. Nutr Metab Cardiovasc Dis 2006; 16: 302–308.

    Article  CAS  Google Scholar 

  17. Bammann K, Peplies J, Pigeot I, Ahrens W . (IDEFICS: a multicenter European project on diet- and lifestyle-related disorders in children). Med Klin 2007; 102: 230–235.

    Article  Google Scholar 

  18. United Nations Educational Scientific and Cultural Organization (UNESCO) Institute for Statistics. International Standard Classification of Education (ISCED) 1997. UNESCO: Montreal, 2006.

  19. Harrison E Rose D . The European Socioeconomic Classification (ESeC). In: User Guide. University of Essex: Colchester, 2006.

    Google Scholar 

  20. OECD. Growing Unequal? Income Distribution and Poverty in OECD Countries. OCED Publishing, 2008.

  21. Bammann K, Gwozdz W, Lanfer A, Barba G, De Henauw S, Eiben G et al. Socioeconomic factors and childhood overweight in Europe: results from the multi-centre IDEFICS study. Pediatr Obes 2012; 8: 1–12.

    Article  Google Scholar 

  22. Huybrechts I, Bornhorst C, Pala V, Moreno LA, Barba G, Lissner L et al. Evaluation of the Children’s Eating Habits Questionnaire used in the IDEFICS study by relating urinary calcium and potassium to milk consumption frequencies among European children. Int J Obes 2011; 35: S69–S78.

    Article  CAS  Google Scholar 

  23. Lanfer A, Hebestreit A, Ahrens W, Krogh V, Sieri S, Lissner L et al. Reproducibility of food consumption frequencies derived from the Children’s Eating Habits Questionnaire used in the IDEFICS study. Int J Obes 2011; 35: S61–S68.

    Article  Google Scholar 

  24. Balder HF, Virtanen M, Brants HA, Krogh V, Dixon LB, Tan F et al. Common and country-specific dietary patterns in four European cohort studies. J Nutr 2003; 133: 4246–4251.

    Article  CAS  Google Scholar 

  25. Martinez ME, Marshall JR, Sechrest L . Invited commentary: factor analysis and the search for objectivity. Am J Epidemiol 1998; 148: 17–19.

    Article  CAS  Google Scholar 

  26. Hoffmann K, Schulze MB, Schienkiewitz A, Nothlings U, Boeing H . Application of a new statistical method to derive dietary patterns in nutritional epidemiology. Am J Epidemiol 2004; 159: 935–944.

    Article  Google Scholar 

  27. Cole TJ, Lobstein T . Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes 2012; 7: 284–294.

    Article  CAS  Google Scholar 

  28. Oellingrath IM, Svendsen MV, Brantsaeter AL . Eating patterns and overweight in 9- to 10-year-old children in Telemark County, Norway: a cross-sectional study. Eur J Clin Nutr 2010; 64: 1272–1279.

    Article  CAS  Google Scholar 

  29. North K, Emmett P . Multivariate analysis of diet among three-year-old children and associations with socio-demographic characteristics. The Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC) Study Team. Eur J Clin Nutr 2000; 54: 73–80.

    Article  CAS  Google Scholar 

  30. Craig LC, McNeill G, Macdiarmid JI, Masson LF, Holmes BA . Dietary patterns of school-age children in Scotland: association with socio-economic indicators, physical activity and obesity. Br J Nutr 2010; 103: 319–334.

    Article  CAS  Google Scholar 

  31. Fisk CM, Crozier SR, Inskip HM, Godfrey KM, Cooper C, Robinson SM . Influences on the quality of young children’s diets: the importance of maternal food choices. Br J Nutr 2011; 105: 287–296.

    Article  CAS  Google Scholar 

  32. Aranceta J, Perez-Rodrigo C, Ribas L, Serra-Majem L . Sociodemographic and lifestyle determinants of food patterns in Spanish children and adolescents: the enKid study. Eur J Clin Nutr 2003; 57: S40–S44.

    Article  Google Scholar 

  33. Varraso R, Garcia-Aymerich J, Monier F, Le Moual N, De Batlle J, Miranda G et al. Assessment of dietary patterns in nutritional epidemiology: principal component analysis compared with confirmatory factor analysis. Am J Clin Nutr 2012; 96: 1079–1092.

    Article  CAS  Google Scholar 

  34. Northstone K, Emmett P, Rogers I . Dietary patterns in pregnancy and associations with socio-demographic and lifestyle factors. Eur J Clin Nutr 2008; 62: 471–479.

    Article  CAS  Google Scholar 

  35. Slimani N, Fahey M, Welch AA, Wirfalt E, Stripp C, Bergstrom E et al. Diversity of dietary patterns observed in the European Prospective Investigation into Cancer and Nutrition (EPIC) project. Public Health Nutr 2002; 5: 1311–1328.

    Article  CAS  Google Scholar 

  36. Margetts BM, Martinez JA, Saba A, Holm L, Kearney M, Moles A . Definitions of 'healthy' eating: a pan-EU survey of consumer attitudes to food, nutrition and health. Eur J Clin Nutr 1997; 51: S23–S29.

    PubMed  Google Scholar 

  37. Northstone K, Emmett P . Multivariate analysis of diet in children at four and seven years of age and associations with socio-demographic characteristics. Eur J Clin Nutr 2005; 59: 751–760.

    Article  CAS  Google Scholar 

  38. Singh GK, Siahpush M, Kogan MD . Rising social inequalities in US childhood obesity, 2003–2007. Ann Epidemiol 2010; 20: 40–52.

    Article  Google Scholar 

  39. Groves R . Nonresponse rates and nonresponse bias in household surveys. Public Opin Q 2006; 70: 646–675.

    Article  Google Scholar 

  40. Hulshof KF, Brussaard JH, Kruizinga AG, Telman J, Lowik MR . Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. Eur J Clin Nutr 2003; 57: 128–137.

    Article  CAS  Google Scholar 

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Acknowledgements

We thank the IDEFICS children and their parents for their participation. The information in this document reflects the author’s view and is provided as is. This work was performed as part of the IDEFICS Study (http://www.idefics.eu). We gratefully acknowledge the financial support of the European Community within the Sixth RTD Framework Programme Contract no. 016181 (FOOD) and the European Regional Development Fund (ICINN-FEDER).

Author information

Authors and Affiliations

  1. GENUD (Growth, Exercise, NUtrition and Development) research group, Faculty of Health Sciences, University of Zaragoza, Zaragoza, Spain

    J M Fernández-Alvira & L A Moreno

  2. Institute for Public Health and Nursing Sciences (ipp), University of Bremen, Bremen, Germany

    K Bammann

  3. Leibniz Institute for Prevention Research and Epidemiology BIPS GmbH, Bremen, Germany

    K Bammann & A Hebestreit

  4. Department of Preventive and Predictive Medicine, Nutritional Epidemiology Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

    V Pala & V Krogh

  5. Unit of Epidemiology and Population Genetics, Institute of Food Sciences, National Reseach Council, Avellino, Italy

    G Barba

  6. Department of Public Health and Community Medicine, Public Health Epidemiology Unit, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

    G Eiben

  7. Department of Chronic Diseases, National Institute for Health Development, Tallinn, Estonia

    T Veidebaum

  8. Copenhagen Business School, Copenhagen, Denmark

    L Reisch

  9. Research and Education Institute of Child Health, Strovolos, Cyprus

    M Tornaritis

  10. Department of Paediatrics, University of Pécs, Pécs, Hungary

    E Kovacs

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

    I Huybrechts

  12. International Agency for research on Cancer, Dietary Exposure assessment group, Lyon, France

    I Huybrechts

Authors
  1. J M Fernández-Alvira
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  2. K Bammann
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  3. V Pala
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  4. V Krogh
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  5. G Barba
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  6. G Eiben
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  7. A Hebestreit
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  8. T Veidebaum
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  9. L Reisch
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  10. M Tornaritis
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  11. E Kovacs
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  12. I Huybrechts
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  13. L A Moreno
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Corresponding author

Correspondence to J M Fernández-Alvira.

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Competing interests

The authors declare no conflict of interest.

Appendix

Appendix

Table A1 Components and factor loadings for Belgium
Full size table
Table A2 Components and factor loadings for Cyprus
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Table A3 Components and factor loadings for Estonia
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Table A4 Components and factor loadings for Germany
Full size table
Table A5 Compoments and factor loadings for Hungary
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Table A6 Components and factor loadings for Italy
Full size table
Table A7 Components and factor loadings for Spain
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Table A8 Components and factor loadings for Sweden
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Fernández-Alvira, J., Bammann, K., Pala, V. et al. Country-specific dietary patterns and associations with socioeconomic status in European children: the IDEFICS study. Eur J Clin Nutr 68, 811–821 (2014). https://doi.org/10.1038/ejcn.2014.78

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  • DOI: https://doi.org/10.1038/ejcn.2014.78

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