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Br J Nutr. 2015 Feb 14;113(3):517-25. doi: 10.1017/S0007114514003663. Epub 2015 Jan 7.

Prospective associations between socio-economic status and dietary patterns in European children: the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants (IDEFICS) Study.

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GENUD (Growth, Exercise, NUtrition and Development) Research Group, Faculty of Health Sciences, University of Zaragoza, Edificio del SAI, C/Pedro Cerbuna s/n,50009Zaragoza,Spain.
Leibniz Institute for Prevention Research and Epidemiology - BIPS,Bremen,Germany.
Institute for Public Health and Nursing Sciences (IPP), University of Bremen,Bremen,Germany.
Copenhagen Business School,Copenhagen,Denmark.
Epidemiology Unit, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori,Milan,Italy.
Unit of Epidemiology and Population Genetics, Institute of Food Sciences, National Research Council,Avellino,Italy.
Public Health Epidemiology Unit (EPI), Department of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg,Gothenburg,Sweden.
Department of Chronic Diseases,National Institute for Health Development,Tallinn,Estonia.
Research and Education Institute of Child Health,Strovolos,Cyprus.
Department of Paediatrics,University of Pécs,Pécs,Hungary.
Department of Public Health,Ghent University,Ghent,Belgium.


Exploring changes in children's diet over time and the relationship between these changes and socio-economic status (SES) may help to understand the impact of social inequalities on dietary patterns. The aim of the present study was to describe dietary patterns by applying a cluster analysis to 9301 children participating in the baseline (2-9 years old) and follow-up (4-11 years old) surveys of the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants Study, and to describe the cluster memberships of these children over time and their association with SES. We applied the K-means clustering algorithm based on the similarities between the relative frequencies of consumption of forty-two food items. The following three consistent clusters were obtained at baseline and follow-up: processed (higher frequency of consumption of snacks and fast food); sweet (higher frequency of consumption of sweet foods and sweetened drinks); healthy (higher frequency of consumption of fruits, vegetables and wholemeal products). Children with higher-educated mothers and fathers and the highest household income were more likely to be allocated to the healthy cluster at baseline and follow-up and less likely to be allocated to the sweet cluster. Migrants were more likely to be allocated to the processed cluster at baseline and follow-up. Applying the cluster analysis to derive dietary patterns at the two time points allowed us to identify groups of children from a lower socio-economic background presenting persistently unhealthier dietary profiles. This finding reflects the need for healthy eating interventions specifically targeting children from lower socio-economic backgrounds.


Paternal education

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