The Association Between Dietary Flavonoid and Lignan Intakes and Incident Type 2 Diabetes in European Populations

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Abstract

OBJECTIVE

To study the association between dietary flavonoid and lignan intakes, and the risk of development of type 2 diabetes among European populations.

RESEARCH DESIGN AND METHODS

The European Prospective Investigation into Cancer and Nutrition-InterAct case-cohort study included 12,403 incident type 2 diabetes cases and a stratified subcohort of 16,154 participants from among 340,234 participants with 3.99 million person-years of follow-up in eight European countries. At baseline, country-specific validated dietary questionnaires were used. A flavonoid and lignan food composition database was developed from the Phenol-Explorer, the U.K. Food Standards Agency, and the U.S. Department of Agriculture databases. Hazard ratios (HRs) from country-specific Prentice-weighted Cox regression models were pooled using random-effects meta-analysis.

RESULTS

In multivariable models, a trend for an inverse association between total flavonoid intake and type 2 diabetes was observed (HR for the highest vs. the lowest quintile, 0.90 [95% CI 0.77–1.04]; P valuetrend = 0.040), but not with lignans (HR 0.88 [95% CI 0.72–1.07]; P valuetrend = 0.119). Among flavonoid subclasses, flavonols (HR 0.81 [95% CI 0.69–0.95]; P valuetrend = 0.020) and flavanols (HR 0.82 [95% CI 0.68–0.99]; P valuetrend = 0.012), including flavan-3-ol monomers (HR 0.73 [95% CI 0.57–0.93]; P valuetrend = 0.029), were associated with a significantly reduced hazard of diabetes.

CONCLUSIONS

Prospective findings in this large European cohort demonstrate inverse associations between flavonoids, particularly flavanols and flavonols, and incident type 2 diabetes. This suggests a potential protective role of eating a diet rich in flavonoids, a dietary pattern based on plant-based foods, in the prevention of type 2 diabetes.

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Most cited references 22

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Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

Nicholas J. Wareham, Rupert W. Jakes, Kirsten L Rennie … (2003)

To assess the validity and repeatability of a simple index designed to rank participants according to their energy expenditure estimated by self-report, by comparison with objectively measured energy expenditure assessed by heart-rate monitoring with individual calibration. Energy expenditure was assessed over one year by four separate episodes of 4-day heart-rate monitoring, a method previously validated against whole-body calorimetry and doubly labelled water. Cardio-respiratory fitness was assessed by four repeated measures of sub-maximum oxygen uptake. At the end of the 12-month period, participants completed a physical activity questionnaire that assessed past-year activity. A simple four-level physical activity index was derived by combining occupational physical activity together with time participating in cycling and other physical exercise (such as keep fit, aerobics, swimming and jogging). One hundred and seventy-three randomly selected men and women aged 40 to 65 years. The repeatability of the physical activity index was high (weighted kappa=0.6, ). There were positive associations between the physical activity index from the questionnaire and the objective measures of the ratio of daytime energy expenditure to resting metabolic rate and cardio-respiratory fitness As an indirect test of validity, there was a positive association between the physical activity index and the ratio of energy intake, assessed by 7-day food diaries, to predicted basal metabolic rate. The summary index of physical activity derived from the questions used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study suggest it is useful for ranking participants in terms of their physical activity in large epidemiological studies. The index is simple and easy to comprehend, which may make it suitable for situations that require a concise, global index of activity.

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Impact of Dietary Polyphenols on Carbohydrate Metabolism

Kati Hanhineva, Riitta Törrönen, Isabel Bondia-Pons … (2010)

Polyphenols, including flavonoids, phenolic acids, proanthocyanidins and resveratrol, are a large and heterogeneous group of phytochemicals in plant-based foods, such as tea, coffee, wine, cocoa, cereal grains, soy, fruits and berries. Growing evidence indicates that various dietary polyphenols may influence carbohydrate metabolism at many levels. In animal models and a limited number of human studies carried out so far, polyphenols and foods or beverages rich in polyphenols have attenuated postprandial glycemic responses and fasting hyperglycemia, and improved acute insulin secretion and insulin sensitivity. The possible mechanisms include inhibition of carbohydrate digestion and glucose absorption in the intestine, stimulation of insulin secretion from the pancreatic β–cells, modulation of glucose release from the liver, activation of insulin receptors and glucose uptake in the insulin-sensitive tissues, and modulation of intracellular signalling pathways and gene expression. The positive effects of polyphenols on glucose homeostasis observed in a large number of in vitro and animal models are supported by epidemiological evidence on polyphenol-rich diets. To confirm the implications of polyphenol consumption for prevention of insulin resistance, metabolic syndrome and eventually type 2 diabetes, human trials with well-defined diets, controlled study designs and clinically relevant end-points together with holistic approaches e.g., systems biology profiling technologies are needed.

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The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study.

Michael W. Becker, M. Dam, A Farrán Codina … (2007)

This paper describes the ad hoc methodological concepts and procedures developed to improve the comparability of Nutrient databases (NDBs) across the 10 European countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). This was required because there is currently no European reference NDB available. A large network involving national compilers, nutritionists and experts on food chemistry and computer science was set up for the 'EPIC Nutrient DataBase' (ENDB) project. A total of 550-1500 foods derived from about 37,000 standardized EPIC 24-h dietary recalls (24-HDRS) were matched as closely as possible to foods available in the 10 national NDBs. The resulting national data sets (NDS) were then successively documented, standardized and evaluated according to common guidelines and using a DataBase Management System specifically designed for this project. The nutrient values of foods unavailable or not readily available in NDSs were approximated by recipe calculation, weighted averaging or adjustment for weight changes and vitamin/mineral losses, using common algorithms. The final ENDB contains about 550-1500 foods depending on the country and 26 common components. Each component value was documented and standardized for unit, mode of expression, definition and chemical method of analysis, as far as possible. Furthermore, the overall completeness of NDSs was improved (>or=99%), particularly for beta-carotene and vitamin E. The ENDB constitutes a first real attempt to improve the comparability of NDBs across European countries. This methodological work will provide a useful tool for nutritional research as well as end-user recommendations to improve NDBs in the future.

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Author and article information

Journal

Journal ID (nlm-ta): Diabetes Care

Journal ID (iso-abbrev): Diabetes Care

Journal ID (hwp): diacare

Journal ID (pmc): dcare

Journal ID (publisher-id): Diabetes Care

Title: Diabetes Care

Publisher: American Diabetes Association

ISSN (Print): 0149-5992

ISSN (Electronic): 1935-5548

Publication date (Print): December 2013

Publication date (Electronic): 13 November 2013

Volume: 36

Issue: 12

Pages: 3961-3970

Affiliations

[1] ¹Medical Research Council, Epidemiology Unit, Cambridge, U.K.

[2] ²Unit of Nutrition, Environment and Cancer, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, Barcelona, Spain

[3] ³Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany

[4] ⁴Navarre Public Health Institute, Pamplona, Spain

[5] ⁵CIBER Epidemiología y Salud Pública, Madrid, Spain

[6] ⁶Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands

[7] ⁷Public Health Department of Gipuzkoa, BioDonostia Research Institute, Health Department of Basque Region, San Sebastián, Spain

[8] ⁸National Food Institute, Technical University of Denmark, Moerkhoej, Denmark

[9] ⁹INSERM, Centre for Research in Epidemiology and Population Health, U1018, Nutrition, Hormones and Women's Health, Villejuif, France

[10] ¹⁰Paris South University, Unité Mixte de Recherche 1018, Villejuif, France

[11] ¹¹Division of Human Nutrition, Section of Nutrition and Epidemiology, University of Wageningen, Wageningen, the Netherlands

[12] ¹²Genetic and Molecular Epidemiology Unit, Clinical Research Center, Skåne University Hospital, Lund University, Malmö, Sweden

[13] ¹³Nutritional Epidemiology Unit, Fondazione Istituto Di Ricovero e Cura a Carattere Scientifico, Istituto Nazionale dei Tumori, Milan, Italy

[14] ¹⁴Department of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany

[15] ¹⁵Cancer Epidemiology Unit, University of Oxford, Oxford, U.K.

[16] ¹⁶Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K.

[17] ¹⁷Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute, Florence, Italy

[18] ¹⁸Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy

[19] ¹⁹Andalusian School of Public Health. Granada, Spain

[20] ²⁰Department of Clinical Sciences, Lund University, Malmö, Sweden

[21] ²¹Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark

[22] ²²Public Health Directorate, Asturias, Spain

[23] ²³Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France

[24] ²⁴Center for Cancer Prevention in Piemonte, and Human Genetic Foundation, Torino, Italy

[25] ²⁵National Institute for Public Health and the Environment, Bilthoven, the Netherlands

[26] ²⁶Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark

[27] ²⁷Epidemiology Department, Murcia Regional Health Council, Murcia, Spain

[28] ²⁸Department of Health and Social Sciences, Universidad de Murcia, Spain

[29] ²⁹Cancer Registry and Histopathology Unit, “Civile M.P. Arezzo” Hospital, ASP Ragusa, Italy

[30] ³⁰School of Public Health, Imperial College, London, U.K.

Author notes

Corresponding author: Nita G. Forouhi, nita.forouhi@ 123456mrc-epid.cam.ac.uk .

R.Z.-R. and N.G.F. contributed equally to this study.

Article

Publisher ID: 0877

DOI: 10.2337/dc13-0877

PMC ID: 3836159

PubMed ID: 24130345

SO-VID: 86ea4c00-1409-4106-8e7f-37ce4d6d361a

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Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

History

Date received : 15 April 2013

Date accepted : 21 July 2013

Page count

Pages: 10

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The Association Between Dietary Flavonoid and Lignan Intakes and Incident Type 2 Diabetes in European Populations : The EPIC-InterAct study

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Abstract

OBJECTIVE

RESEARCH DESIGN AND METHODS

RESULTS

CONCLUSIONS

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Bioscientifica Open Endocrinology

Most cited references 22

Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

Impact of Dietary Polyphenols on Carbohydrate Metabolism

The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study.

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Cited by 57