Iris Iglesia1,2, Theodora Mouratidou3, Marcela González-Gross4, Inge Huybrechts5,6, Christina Breidenassel4,7, Javier Santabárbara8, Ligia-Esperanza Díaz9, Lena Hällström10,11, Stefaan De Henauw5, Frédéric Gottrand12, Anthony Kafatos13, Kurt Widhalm14, Yannis Manios15, Denes Molnar16, Peter Stehle7, Luis A Moreno3,17. 1. GENUD (Growth, Exercise, Nutrition and Development) Research group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, C/Pedro Cerbuna, 12, SAI Building (Servicio de Apoyo a la Investigación), 2nd floor, 50009, Zaragoza, Spain. iglesia@unizar.es. 2. Red de Salud Materno-infantil y del Desarrollo (SAMID), Madrid, Spain. iglesia@unizar.es. 3. GENUD (Growth, Exercise, Nutrition and Development) Research group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, C/Pedro Cerbuna, 12, SAI Building (Servicio de Apoyo a la Investigación), 2nd floor, 50009, Zaragoza, Spain. 4. ImFINE Research Group, Department of Health and Human Performance, Universidad Politécnica de Madrid, Madrid, Spain. 5. Department of Public Health, Ghent University, Ghent, Belgium. 6. International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372, Lyon Cedex 08, France. 7. Department of Nutrition and Food Science, University of Bonn, 53115, Bonn, Germany. 8. Department of Preventive Medicine and Public Health, Universidad de Zaragoza, Zaragoza, Spain. 9. Immunonutrition Research Group, Department of Metabolism and Nutrition, Institute of Food Science, Technology and Nutrition (ICTAN), Spanish National Research Council (CSIC), Madrid, Spain. 10. Unit for Preventive Nutrition, Department of Biosciences and Nutrition, Karolinska Institute, Stockholm (Huddinge), Sweden. 11. Sweden and School of Health, Care and Social Welfare Mälardalens University, Västerås, Sweden. 12. Inserm U995, Faculté de Médecine, Université Lille 2, Lille, France. 13. University of Crete School of Medicine, 71033, Crete, Greece. 14. Division of Clinical Nutrition and Prevention, Department of Pediatrics, Medical University of Vienna, Vienna, Austria. 15. Department of Nutrition- and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece. 16. Department of Paediatrics, University of Pécs, Pécs, Hungary. 17. Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERObn), Madrid, Spain.
Abstract
PURPOSE: To examine the association between food groups consumption and vitamin B6, folate and B12 intakes and biomarkers in adolescents. METHODS: In total 2189 individuals participating in the cross-sectional Healthy Lifestyle in Europe by Nutrition in Adolescence study met the eligibility criteria for analysis of dietary intakes (46 % males) and 632 for biomarker analysis (47 % males). Food intakes were assessed by two non-consecutive 24-h recalls. Biomarkers were measured by chromatography and immunoassay. Food groups which best discriminated participants in the extreme tertiles of the distribution of vitamins were identified by discriminant analyses. Food groups with standardised canonical coefficients higher or equal to 0.3 were selected as valid discriminators of vitamins intake and biomarkers extreme tertiles. Linear mixed model elucidated the association between food groups and vitamins intakes and biomarkers. RESULTS: Vitamin B6 intakes and biomarkers were best discriminated by meat (males and females), margarine and mixed origin lipids only in males and breakfast cereals (females). Breakfast cereals (males), and fruits, margarine and mixed origin lipids, vegetables excluding potatoes, breakfast cereals, and soups/bouillon (females) determined the most folate intakes and biomarkers. Considering vitamin B12 intakes and biomarkers, meat, and white and butter milk (males and females), snacks (males), and dairy products (females) best discriminated individual in the extremes of the distribution. Fewer associations were obtained with mixed model for biomarkers than for vitamins intakes with food groups. CONCLUSIONS: Whereas B-vitamin intakes were associated with their food sources, biomarkers did with overall food consumption. Low-nutrient-density foods may compromise adolescents' vitamin status.
PURPOSE: To examine the association between food groups consumption and vitamin B6, folate and B12 intakes and biomarkers in adolescents. METHODS: In total 2189 individuals participating in the cross-sectional Healthy Lifestyle in Europe by Nutrition in Adolescence study met the eligibility criteria for analysis of dietary intakes (46 % males) and 632 for biomarker analysis (47 % males). Food intakes were assessed by two non-consecutive 24-h recalls. Biomarkers were measured by chromatography and immunoassay. Food groups which best discriminated participants in the extreme tertiles of the distribution of vitamins were identified by discriminant analyses. Food groups with standardised canonical coefficients higher or equal to 0.3 were selected as valid discriminators of vitamins intake and biomarkers extreme tertiles. Linear mixed model elucidated the association between food groups and vitamins intakes and biomarkers. RESULTS:Vitamin B6 intakes and biomarkers were best discriminated by meat (males and females), margarine and mixed origin lipids only in males and breakfast cereals (females). Breakfast cereals (males), and fruits, margarine and mixed origin lipids, vegetables excluding potatoes, breakfast cereals, and soups/bouillon (females) determined the most folate intakes and biomarkers. Considering vitamin B12 intakes and biomarkers, meat, and white and butter milk (males and females), snacks (males), and dairy products (females) best discriminated individual in the extremes of the distribution. Fewer associations were obtained with mixed model for biomarkers than for vitamins intakes with food groups. CONCLUSIONS: Whereas B-vitamin intakes were associated with their food sources, biomarkers did with overall food consumption. Low-nutrient-density foods may compromise adolescents' vitamin status.
Authors: Josephine M Wills; Stefan Storcksdieck genannt Bonsmann; Magdalena Kolka; Klaus G Grunert Journal: Proc Nutr Soc Date: 2012-03-05 Impact factor: 6.297
Authors: M Kersting; W Sichert-Hellert; C A Vereecken; J Diehl; L Béghin; S De Henauw; E Grammatikaki; Y Manios; M I Mesana; A Papadaki; K Phillipp; M Plada; E Poortvliet; S Sette Journal: Int J Obes (Lond) Date: 2008-11 Impact factor: 5.095
Authors: H McNulty; J Eaton-Evans; G Cran; G Woulahan; C Boreham; J M Savage; R Fletcher; J J Strain Journal: Arch Dis Child Date: 1996-12 Impact factor: 3.791
Authors: Pamela L Lutsey; Lyn M Steffen; Henry A Feldman; Deanna H Hoelscher; Larry S Webber; Russell V Luepker; Leslie A Lytle; Michelle Zive; Stavroula K Osganian Journal: Am J Clin Nutr Date: 2006-06 Impact factor: 7.045
Authors: L A Moreno; M Kersting; S de Henauw; M González-Gross; W Sichert-Hellert; C Matthys; M I Mesana; N Ross Journal: Int J Obes (Lond) Date: 2005-09 Impact factor: 5.095
Authors: Fábio V Ued; Mariana G Mathias; Roseli B D Toffano; Tamiris T Barros; Maria Olímpia R V Almada; Roberta G Salomão; Carolina A Coelho-Landell; Elaine Hillesheim; Joyce M Camarneiro; José Simon Camelo-Junior; Davi C Aragon; Sofia Moco; Martin Kussmann; Jim Kaput; Jacqueline P Monteiro Journal: Nutrients Date: 2019-12-02 Impact factor: 5.717
Authors: Roseli B D Toffano; Elaine Hillesheim; Mariana G Mathias; Carolina A Coelho-Landell; Roberta G Salomão; Maria O R V Almada; Joyce M Camarneiro; Tamiris T Barros; José S Camelo-Junior; Serge Rezzi; Laurence Goulet; Maria P Giner; Laeticia Da Silva; Francois-Pierre Martin; Ivan Montoliu; Sofia Moco; Sebastiano Collino; Jim Kaput; Jacqueline P Monteiro Journal: Nutrients Date: 2018-01-30 Impact factor: 5.717