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      Glycemic index, glycemic load, and risk of coronary heart disease: a pan-European cohort study

      1 , 1 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 4 , 12 , 13 , 14 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 25 , 26 , 25 , 27 , 27 , 28 , 29 , 28 , 29 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 2 , 2 , 2 , 35 , 36 , 37 , 38 , 39 , 10 , 39 , 10 , 1
      The American Journal of Clinical Nutrition
      Oxford University Press (OUP)

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          ABSTRACT

          Background

          High carbohydrate intake raises blood triglycerides, glucose, and insulin; reduces HDLs; and may increase risk of coronary heart disease (CHD). Epidemiological studies indicate that high dietary glycemic index (GI) and glycemic load (GL) are associated with increased CHD risk.

          Objectives

          The aim of this study was to determine whether dietary GI, GL, and available carbohydrates are associated with CHD risk in both sexes.

          Methods

          This large prospective study—the European Prospective Investigation into Cancer and Nutrition—consisted of 338,325 participants who completed a dietary questionnaire. HRs with 95% CIs for a CHD event, in relation to intake of GI, GL, and carbohydrates, were estimated using covariate-adjusted Cox proportional hazard models.

          Results

          After 12.8 y (median), 6378 participants had experienced a CHD event. High GL was associated with greater CHD risk [HR 1.16 (95% CI: 1.02, 1.31) highest vs. lowest quintile, p-trend 0.035; HR 1.18 (95% CI: 1.07, 1.29) per 50 g/day of GL intake]. The association between GL and CHD risk was evident in subjects with BMI (in kg/m2) ≥25 [HR: 1.22 (95% CI: 1.11, 1.35) per 50 g/d] but not in those with BMI <25 [HR: 1.09 (95% CI: 0.98, 1.22) per 50 g/d) (P-interaction = 0.022). The GL–CHD association did not differ between men [HR: 1.19 (95% CI: 1.08, 1.30) per 50 g/d] and women [HR: 1.22 (95% CI: 1.07, 1.40) per 50 g/d] (test for interaction not significant). GI was associated with CHD risk only in the continuous model [HR: 1.04 (95% CI: 1.00, 1.08) per 5 units/d]. High available carbohydrate was associated with greater CHD risk [HR: 1.11 (95% CI: 1.03, 1.18) per 50 g/d]. High sugar intake was associated with greater CHD risk [HR: 1.09 (95% CI: 1.02, 1.17) per 50 g/d].

          Conclusions

          This large pan-European study provides robust additional support for the hypothesis that a diet that induces a high glucose response is associated with greater CHD risk.

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          Most cited references33

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          Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study

          The relationship between macronutrients and cardiovascular disease and mortality is controversial. Most available data are from European and North American populations where nutrition excess is more likely, so their applicability to other populations is unclear.
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            A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women.

            Little is known about the effects of the amount and type of carbohydrates on risk of coronary heart disease (CHD). The objective of this study was to prospectively evaluate the relations of the amount and type of carbohydrates with risk of CHD. A cohort of 75521 women aged 38-63 y with no previous diagnosis of diabetes mellitus, myocardial infarction, angina, stroke, or other cardiovascular diseases in 1984 was followed for 10 y. Each participant's dietary glycemic load was calculated as a function of glycemic index, carbohydrate content, and frequency of intake of individual foods reported on a validated food-frequency questionnaire at baseline. All dietary variables were updated in 1986 and 1990. During 10 y of follow-up (729472 person-years), 761 cases of CHD (208 fatal and 553 nonfatal) were documented. Dietary glycemic load was directly associated with risk of CHD after adjustment for age, smoking status, total energy intake, and other coronary disease risk factors. The relative risks from the lowest to highest quintiles of glycemic load were 1.00, 1.01, 1. 25, 1.51, and 1.98 (95% CI: 1.41, 2.77 for the highest quintile; P for trend /= 23. These epidemiologic data suggest that a high dietary glycemic load from refined carbohydrates increases the risk of CHD, independent of known coronary disease risk factors.
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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.

              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

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                Journal
                The American Journal of Clinical Nutrition
                Oxford University Press (OUP)
                0002-9165
                1938-3207
                September 2020
                September 01 2020
                July 03 2020
                September 2020
                September 01 2020
                July 03 2020
                : 112
                : 3
                : 631-643
                Affiliations
                [1 ]Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
                [2 ]International Agency for Research on Cancer, WHO, Lyon, France
                [3 ]Department of Clinical Medicine and Surgery, Federico II University, Naples, Italy
                [4 ]Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
                [5 ]Andalusian School of Public Health, Granada, Spain
                [6 ]Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
                [7 ]Instituto de Investigación Biosanitaria (ibs.GRANADA), Granada, Spain
                [8 ]Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
                [9 ]National Food Institute, Division for Diet, Disease Prevention, and Toxicology, Technical University of Denmark, Kongens Lyngby, Denmark
                [10 ]MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
                [11 ]Department of Health Sciences, University of Leicester, Leicester, United Kingdom
                [12 ]Department of Public Health and Clinical Medicine, Sustainable Health, Umeå University, Umeå, Sweden
                [13 ]Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, Umeå, Sweden
                [14 ]Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
                [15 ]Department of Public Health, Aarhus University, Aarhus, Denmark
                [16 ]Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
                [17 ]Public Health Institute of Navarra, IdiSNA, Pamplona, Spain
                [18 ]Public Health Directorate, Asturias, Spain
                [19 ]Hospital Universitario Torrecárdenas, Almería, Spain
                [20 ]Public Health Division of Gipuzkoa, BioDonostia Research Institute, San Sebastian, Spain
                [21 ]Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
                [22 ]Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
                [23 ]Department of Public Health, University of Copenhagen, Copenhagen, Denmark
                [24 ]Nutritional Epidemiology, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
                [25 ]Hellenic Health Foundation, Athens, Greece
                [26 ]2nd Pulmonary Medicine Department, School of Medicine, National and Kapodistrian University of Athens, “ATTIKON” University Hospital, Haidari, Greece
                [27 ]National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
                [28 ]Center for Research in Epidemiology and Population Health, University Paris-South, Faculty of Medicine, University Versailles-St Quentin, National Institute for Health and Medical Research, Université Paris-Saclay, Villejuif, France
                [29 ]Gustave Roussy, Villejuif, France
                [30 ]Université Lille, CHU Lille, Lille, France
                [31 ]Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
                [32 ]Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
                [33 ]DZHK (German Center for Cardiovascular Research), partner site Berlin, Berlin, Germany
                [34 ]University of Potsdam, Institute of Nutritional Sciences, Nuthetal, Germany
                [35 ]Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention, Turin, Italy
                [36 ]Cancer Risk Factors and Lifestyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network, Florence, Italy
                [37 ]Cancer Registry and Histopathology Department, “Civic-M.P.Arezzo” Hospital, ASP Ragusa, Ragusa, Italy
                [38 ]Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom
                [39 ]MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
                Article
                10.1093/ajcn/nqaa157
                32619242
                8cc7deef-c193-41b9-a212-9105cae60af9
                © 2020

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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