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J. Nutr. First published January 21, 2009; doi:10.3945/jn.108.097121
Journal of Nutrition, doi:10.3945/jn.108.097121
Vol. 139, No. 3, 568-575, March 2009

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© 2009 American Society for Nutrition


Nutritional Epidemiology

Methodological Challenges in the Application of the Glycemic Index in Epidemiological Studies Using Data from the European Prospective Investigation into Cancer and Nutrition1–3,

Marit M. E. van Bakel4, Nadia Slimani4,*, Edith J. M. Feskens5, Huaidong Du6,7, Joline W. J. Beulens8, Yvonne T. van der Schouw8, Furio Brighenti9, Jytte Halkjaer10, Anne E. Cust4,26, Pietro Ferrari4,27, Jennie Brand-Miller11, H. Bas Bueno-de-Mesquita7, Petra Peeters7, Eva Ardanaz12, Miren Dorronsoro13, Francesca L. Crowe14, Sheila Bingham15, Sabine Rohrmann16, Heiner Boeing17, Ingegerd Johansson18, Jonas Manjer19, Anne Tjonneland10, Kim Overvad20, Eiliv Lund21, Guri Skeie21, Amalia Mattiello22, Simonetta Salvini23, Françoise Clavel-Chapelon24 and Rudolf Kaaks25

4 Nutritional and Database Resource Team, International Agency for Research on Cancer, 63372 Lyon, France; 5 Division of Human Nutrition, Wageningen University, The Netherlands 6700 EV; 6 Nutrition and Toxicology Research Institute of Maastricht, Maastricht University, Maastricht, The Netherlands 6200 MD; 7 National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands; 8 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 85550 Utrecht, The Netherlands; 9 Human Nutrition Unit, Department of Public Health, University of Parma, IT-43100 Parma, Italy; 10 Danish Cancer Society, Institute of Cancer Epidemiology, 2100 Copenhagen, Denmark; 11 School of Molecular and Microbial Biosciences, University of Sydney, NSW 2006 Sydney, Australia; 12 Institute of Public Health of Navarra, Pamplona and CIBER en Epidemiología y Salud Pública, E-30008 Pamplona, Spain; 13 Public Health Division of Gipuzkoa, 4-20013 San Sebastian, Spain; 14 Cancer Epidemiology Unit, University of Oxford, OX3 7LF Oxford, UK; 15 Department of Public Health and Primary Care, MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival, CB1 8RN Cambridge, UK; 16 Division of Cancer Epidemiology, German Cancer Research Center, 69120 Heidelberg, Germany; 17 Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbrücke, Germany; 18 Department of Odontology, Cariology, Umeå University Hospital, 30187 Umeå, Sweden; 19 Department of Surgery, Malmo University Hospital, 20502 Malmo, Sweden; 20 Department of Cardiology and Department of Clinical Epidemiology, Aarhus University Hospital, 8200 Aalborg, Denmark; 21 Institute of Community Medicine, University of Tromsø, N 9037 Tromsø, Norway; 22 Department of Clinical and Experimental Medicine, Federico II University, I-80131 Naples, Italy; 23 Molecular and Nutritional Epidemiology Unit, ISPO Cancer Prevention and Research Institute, 50135 Florence, Italy; 24 Inserm, ERI 20, Université Paris-Sud, EA 4045, IFR 69, Institut Gustave Roussy, 94805 Villejuif, France; and 25 Division of Cancer Epidemiology, DKFZ, 69120 Heidelberg, Germany

Associations between the glycemic index (GI) or glycemic load (GL) and diseases are heterogeneous in epidemiological studies. Differences in assigning GI values to food items may contribute to this inconsistency. Our objective was to address methodological issues related to the use of current GI and GL values in epidemiological studies. We performed ecological comparison and correlation studies by calculating dietary GI and GL from country-specific dietary questionnaires (DQ) from 422,837 participants from 9 countries participating in the European Prospective Investigation into Cancer and Nutrition study and single standardized 24-h dietary recalls (24-HDR) obtained from a representative sample (n = 33,404) using mainly Foster Powell's international table as a reference source. Further, 2 inter-rater and 1 inter-method comparison were conducted, comparing DQ GI values assigned by independent groups with values linked by us. The ecological correlation between DQ and 24-HDR was good for GL (overall r = 0.76; P < 0.005) and moderate for GI (r = 0.57; P < 0.05). Mean GI/GL differences between DQ and 24-HDR were significant for most centers. GL but not GI from DQ was highly correlated with total carbohydrate (r = 0.98 and 0.15, respectively; P < 0.0001) and this was higher for starch (r = 0.72; P < 0.0001) than for sugars (r = 0.36; P < 0.0001). The inter-rater and inter-method variations were considerable for GI (weighted {kappa} coefficients of 0.49 and 0.65 for inter-rater and 0.25 for inter-method variation, respectively) but only mild for GL (weighted {kappa} coefficients > 0.80). A more consistent methodology to attribute GI values to foods and validated DQ is needed to derive meaningful GI/GL estimates for nutritional epidemiology.


* To whom correspondence should be addressed. E-mail: slimani{at}iarc.fr.

Manuscript received 25 August 2008. Initial review completed 8 October 2008. Revision accepted 23 December 2008.

Published online 21 January 2009.







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