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      Differences in the prospective association between individual plasma phospholipid saturated fatty acids and incident type 2 diabetes: the EPIC-InterAct case-cohort study

      , Dr, FFPHM a , * , , PhD b , , MSc a , , PhD a , , DrPH c , , Prof, DrPH c , , PhD d ,   , PhD e , f , , MD f , g , , PhD h , , PhD i , , PhD b , , BSc b , , DPhil b , , Prof, PhD i , , MSc f , j , k , , Prof, PhD c , , PhD l , m , n , , MSc l , m , n , , PhD l , m , n , , Prof, PhD o , p , , PhD q , , PhD r , , Prof, PhD s , , Prof, DPhil d , , Prof, FRCP t , , PhD s , , PhD u , , Prof, PhD o ,   , Prof, PhD r , v , , PhD w , , MD x , , MD y , , PhD p , , PhD z ,   , PhD aa , ab , , PhD f , ac , ad , , PhD ae , , PhD af , , Prof, DrMedSci ag , , PhD e , f , ah , , MD ai , aj , , PhD af , , Prof, PhD h , , PhD a , , Prof, ScM ak , , Prof, FRCP a

      The Lancet. Diabetes & Endocrinology

      The Lancet, Diabetes & Endocrinology

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          Conflicting evidence exists regarding the association between saturated fatty acids (SFAs) and type 2 diabetes. In this longitudinal case-cohort study, we aimed to investigate the prospective associations between objectively measured individual plasma phospholipid SFAs and incident type 2 diabetes in EPIC-InterAct participants.


          The EPIC-InterAct case-cohort study includes 12 403 people with incident type 2 diabetes and a representative subcohort of 16 154 individuals who were selected from a cohort of 340 234 European participants with 3·99 million person-years of follow-up (the EPIC study). Incident type 2 diabetes was ascertained until Dec 31, 2007, by a review of several sources of evidence. Gas chromatography was used to measure the distribution of fatty acids in plasma phospholipids (mol%); samples from people with type 2 diabetes and subcohort participants were processed in a random order by centre, and laboratory staff were masked to participant characteristics. We estimated country-specific hazard ratios (HRs) for associations per SD of each SFA with incident type 2 diabetes using Prentice-weighted Cox regression, which is weighted for case-cohort sampling, and pooled our findings using random-effects meta-analysis.


          SFAs accounted for 46% of total plasma phospholipid fatty acids. In adjusted analyses, different individual SFAs were associated with incident type 2 diabetes in opposing directions. Even-chain SFAs that were measured (14:0 [myristic acid], 16:0 [palmitic acid], and 18:0 [stearic acid]) were positively associated with incident type 2 diabetes (HR [95% CI] per SD difference: myristic acid 1·15 [95% CI 1·09–1·22], palmitic acid 1·26 [1·15–1·37], and stearic acid 1·06 [1·00–1·13]). By contrast, measured odd-chain SFAs (15:0 [pentadecanoic acid] and 17:0 [heptadecanoic acid]) were inversely associated with incident type 2 diabetes (HR [95% CI] per 1 SD difference: 0·79 [0·73–0·85] for pentadecanoic acid and 0·67 [0·63–0·71] for heptadecanoic acid), as were measured longer-chain SFAs (20:0 [arachidic acid], 22:0 [behenic acid], 23:0 [tricosanoic acid], and 24:0 [lignoceric acid]), with HRs ranging from 0·72 to 0·81 (95% CIs ranging between 0·61 and 0·92). Our findings were robust to a range of sensitivity analyses.


          Different individual plasma phospholipid SFAs were associated with incident type 2 diabetes in opposite directions, which suggests that SFAs are not homogeneous in their effects. Our findings emphasise the importance of the recognition of subtypes of these fatty acids. An improved understanding of differences in sources of individual SFAs from dietary intake versus endogenous metabolism is needed.


          EU FP6 programme, Medical Research Council Epidemiology Unit, Medical Research Council Human Nutrition Research, and Cambridge Lipidomics Biomarker Research Initiative.

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          Most cited references 23

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          Saturated Fat and Cardiometabolic Risk Factors, Coronary Heart Disease, Stroke, and Diabetes: a Fresh Look at the Evidence

          Dietary and policy recommendations frequently focus on reducing saturated fatty acid consumption for improving cardiometabolic health, based largely on ecologic and animal studies. Recent advances in nutritional science now allow assessment of critical questions about health effects of saturated fatty acids (SFA). We reviewed the evidence from randomized controlled trials (RCTs) of lipid and non-lipid risk factors, prospective cohort studies of disease endpoints, and RCTs of disease endpoints for cardiometabolic effects of SFA consumption in humans, including whether effects vary depending on specific SFA chain-length; on the replacement nutrient; or on disease outcomes evaluated. Compared with carbohydrate, the TC:HDL-C ratio is nonsignificantly affected by consumption of myristic or palmitic acid, is nonsignificantly decreased by stearic acid, and is significantly decreased by lauric acid. However, insufficient evidence exists for different chain-length-specific effects on other risk pathways or, more importantly, disease endpoints. Based on consistent evidence from human studies, replacing SFA with polyunsaturated fat modestly lowers coronary heart disease risk, with ~10% risk reduction for a 5% energy substitution; whereas replacing SFA with carbohydrate has no benefit and replacing SFA with monounsaturated fat has uncertain effects. Evidence for the effects of SFA consumption on vascular function, insulin resistance, diabetes, and stroke is mixed, with many studies showing no clear effects, highlighting a need for further investigation of these endpoints. Public health emphasis on reducing SFA consumption without considering the replacement nutrient or, more importantly, the many other food-based risk factors for cardiometabolic disease is unlikely to produce substantial intended benefits.
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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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              Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study.

              Studying gene-lifestyle interaction may help to identify lifestyle factors that modify genetic susceptibility and uncover genetic loci exerting important subgroup effects. Adequately powered studies with prospective, unbiased, standardised assessment of key behavioural factors for gene-lifestyle studies are lacking. This case-cohort study aims to investigate how genetic and potentially modifiable lifestyle and behavioural factors, particularly diet and physical activity, interact in their influence on the risk of developing type 2 diabetes. Incident cases of type 2 diabetes occurring in European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts between 1991 and 2007 from eight of the ten EPIC countries were ascertained and verified. Prentice-weighted Cox regression and random-effects meta-analyses were used to investigate differences in diabetes incidence by age and sex. A total of 12,403 verified incident cases of type 2 diabetes occurred during 3.99 million person-years of follow-up of 340,234 EPIC participants eligible for InterAct. We defined a centre-stratified subcohort of 16,154 individuals for comparative analyses. Individuals with incident diabetes who were randomly selected into the subcohort (n = 778) were included as cases in the analyses. All prevalent diabetes cases were excluded from the study. InterAct cases were followed-up for an average of 6.9 years; 49.7% were men. Mean baseline age and age at diagnosis were 55.6 and 62.5 years, mean BMI and waist circumference values were 29.4 kg/m(2) and 102.7 cm in men, and 30.1 kg/m(2) and 92.8 cm in women, respectively. Risk of type 2 diabetes increased linearly with age, with an overall HR of 1.56 (95% CI 1.48-1.64) for a 10 year age difference, adjusted for sex. A male excess in the risk of incident diabetes was consistently observed across all countries, with a pooled HR of 1.51 (95% CI 1.39-1.64), adjusted for age. InterAct is a large, well-powered, prospective study that will inform our understanding of the interplay between genes and lifestyle factors on the risk of type 2 diabetes development.

                Author and article information

                Lancet Diabetes Endocrinol
                Lancet Diabetes Endocrinol
                The Lancet. Diabetes & Endocrinology
                The Lancet, Diabetes & Endocrinology
                1 October 2014
                October 2014
                : 2
                : 10
                : 810-818
                [a ]MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
                [b ]MRC Human Nutrition Research, Cambridge, UK
                [c ]German Institute of Human Nutrition Potsdam-Rehbruecke, Potsdam, Germany
                [d ]Nuffield Department of Medicine, University of Oxford, Oxford, UK
                [e ]Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
                [f ]CIBER Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
                [g ]Navarre Public Health Institute (ISPN), Pamplona, Spain
                [h ]University Medical Center Utrecht, Utrecht, Netherlands
                [i ]Wageningen University, Wageningen, Netherlands
                [j ]Public Health Division of Gipuzkoa, San Sebastian, Spain
                [k ]Instituto BIO-Donostia, Basque Government, San Sebastian, Spain
                [l ]Inserm, CESP, U1018, Villejuif, France
                [m ]Univ Paris-Sud, UMRS 1018, Villejuif, France
                [n ]Gustave Roussy Institute, F-94800 Villejuif, France
                [o ]Lund University, Malmö, Sweden
                [p ]Umeå University, Umeå, Sweden
                [q ]Catalan Institute of Oncology (ICO), Barcelona, Spain
                [r ]Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
                [s ]German Cancer Research Centre (DKFZ), Heidelberg, Germany
                [t ]Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
                [u ]Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
                [v ]Aalborg University Hospital, Aalborg, Denmark
                [w ]Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
                [x ]Cancer Research and Prevention Institute (ISPO), Florence, Italy
                [y ]Public Health Directorate, Asturias, Spain
                [z ]Danish Cancer Society, Copenhagen, Denmark
                [aa ]Unit of Cancer Epidemiology, Citta' della Salute e della Scienza Hospital—University of Turin and Centre for Cancer Prevention (CPO), Turin, Italy
                [ab ]Human Genetics Foundation (HuGeF), Turin, Italy
                [ac ]Andalusian School of Public Health, Granada, Spain
                [ad ]Instituto de Investigación Biosanitaria de Granada (Granada.ibs), Granada, Spain
                [ae ]International Agency for Research on Cancer, Lyon, France
                [af ]National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
                [ag ]Danish Cancer Society Research Center, Copenhagen, Denmark
                [ah ]Department of Health and Social Sciences, Universidad de Murcia, Spain
                [ai ]Associazione Italiana Registri Tumori, Dipartimento di Prevenzione Medica, Azienda Sanitaria Provinciale, Ragusa, Italy
                [aj ]Aire Onlus, Ragusa, Italy
                [ak ]School of Public Health, Imperial College London, London, UK
                Author notes
                [* ]Correspondence to: Dr Nita G Forouhi, MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK nita.forouhi@
                © 2014 Forouhi et al. Open Access article distributed under the terms of CC BY

                This document may be redistributed and reused, subject to certain conditions.



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