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      Tall height and obesity are associated with an increased risk of aggressive prostate cancer: results from the EPIC cohort study

      research-article
      1 , , 1 , 2 , 3 , 4 , 5 ,   5 ,   6 , 7 , 7 , 8 , 8 , 9 , 10 , 9 , 10 , 11 , 9 , 12 , 13 , 14 , 15 , 4 , 16 , 17 , 18 , 19 , 20 , 20 , 21 , 20 , 22 , 23 , 20 , 24 , 25 , 26 , 27 , 28 , 27 , 29 , 30 , 31 , 1 , 32 , 32 , 4 , 4 , 4 , 1 , 1
      BMC Medicine
      BioMed Central
      Adiposity, Obesity, Height, Prostate cancer, Cohort study, Tumour characteristics, High grade

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          Abstract

          Background

          The relationship between body size and prostate cancer risk, and in particular risk by tumour characteristics, is not clear because most studies have not differentiated between high-grade or advanced stage tumours, but rather have assessed risk with a combined category of aggressive disease. We investigated the association of height and adiposity with incidence of and death from prostate cancer in 141,896 men in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

          Methods

          Multivariable-adjusted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). After an average of 13.9 years of follow-up, there were 7024 incident prostate cancers and 934 prostate cancer deaths.

          Results

          Height was not associated with total prostate cancer risk. Subgroup analyses showed heterogeneity in the association with height by tumour grade ( P heterogeneity = 0.002), with a positive association with risk for high-grade but not low-intermediate-grade disease (HR for high-grade disease tallest versus shortest fifth of height, 1.54; 95% CI, 1.18–2.03). Greater height was also associated with a higher risk for prostate cancer death (HR = 1.43, 1.14–1.80). Body mass index (BMI) was significantly inversely associated with total prostate cancer, but there was evidence of heterogeneity by tumour grade ( P heterogeneity = 0.01; HR = 0.89, 0.79–0.99 for low-intermediate grade and HR = 1.32, 1.01–1.72 for high-grade prostate cancer) and stage ( P heterogeneity = 0.01; HR = 0.86, 0.75–0.99 for localised stage and HR = 1.11, 0.92–1.33 for advanced stage). BMI was positively associated with prostate cancer death (HR = 1.35, 1.09–1.68). The results for waist circumference were generally similar to those for BMI, but the associations were slightly stronger for high-grade (HR = 1.43, 1.07–1.92) and fatal prostate cancer (HR = 1.55, 1.23–1.96).

          Conclusions

          The findings from this large prospective study show that men who are taller and who have greater adiposity have an elevated risk of high-grade prostate cancer and prostate cancer death.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12916-017-0876-7) contains supplementary material, which is available to authorized users.

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          Most cited references35

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          Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

          In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013. We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Bill & Melinda Gates Foundation. Copyright © 2014 Elsevier Ltd. All rights reserved.
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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.

            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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              The inflammation highway: metabolism accelerates inflammatory traffic in obesity.

              As humans evolved, perhaps the two strongest selection determinants of survival were a robust immune response able to clear bacterial, viral, and parasitic infection and an ability to efficiently store nutrients to survive times when food sources were scarce. These traits are not mutually exclusive. It is now apparent that critical proteins necessary for regulating energy metabolism, such as peroxisome proliferator-activated receptors, Toll-like receptors, and fatty acid-binding proteins, also act as links between nutrient metabolism and inflammatory pathway activation in immune cells. Obesity in humans is a symptom of energy imbalance: the scale has been tipped such that energy intake exceeds energy output and may be a result, in part, of evolutionary selection toward a phenotype characterized by efficient energy storage. As discussed in this review, obesity is a state of low-grade, chronic inflammation that promotes the development of insulin resistance and diabetes. Ironically, the formation of systemic and/or local, tissue-specific insulin resistance upon inflammatory cell activation may actually be a protective mechanism that co-evolved to repartition energy sources within the body during times of stress during infection. However, the point has been reached where a once beneficial adaptive trait has become detrimental to the health of the individual and an immense public health and economic burden. This article reviews the complex relationship between obesity, insulin resistance/diabetes, and inflammation, and although the liver, brain, pancreas, muscle, and other tissues are relevant, we focus specifically on how the obese adipose microenvironment can promote immune cell influx and sustain damaging inflammation that can lead to the onset of insulin resistance and diabetes. Finally, we address how substrate metabolism may regulate the immune response and discuss how fuel uptake and metabolism may be a targetable approach to limit or abrogate obesity-induced inflammation. © 2012 John Wiley & Sons A/S.
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                Author and article information

                Contributors
                +44 (0)1865 289600 , aurora.perez-cornago@ceu.ox.ac.uk
                paul.appleby@ceu.ox.ac.uk
                tobias.pischon@mdc-berlin.de
                ktsilidis@gmail.com
                annet@cancer.dk
                anja@cancer.dk
                ko@soci.au.dk
                r.kaaks@dkfz-heidelberg.de
                t.kuehn@dkfz-heidelberg.de
                boeing@dife.de
                annika.steffen@dife.de
                atrichopoulou@hhf-greece.gr
                plagiou@hsph.harvard.edu
                maria.kritikou@hhf-greece.gr
                vittorio.krogh@istitutotumori.mi.it
                d.palli@ispo.toscana.it
                carlotta.sacerdote@cpo.it
                rtumino@tin.it
                bas.bueno.de.mesquita@rivm.nl
                a.agudo@iconcologia.net
                epidem3-san@euskadi.eus
                elena.molina.easp@juntadeandalucia.es
                aurelio.barricarte.gurrea@cfnavarra.es
                mdolores.chirlaque@carm.es
                epic_asturias@asturias.org
                par.stattin@umu.se
                christel.haggstrom@umu.se
                nick.wareham@mrc-epid.cam.ac.uk
                kk101@medschl.cam.ac.uk
                julie.schmidt@ceu.ox.ac.uk
                gunterm@iarc.fr
                freislingh@iarc.fr
                d.aune@imperial.ac.uk
                heather.ward@imperial.ac.uk
                e.riboli@imperial.ac.uk
                tim.key@ceu.ox.ac.uk
                ruth.travis@ceu.ox.ac.uk
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                13 July 2017
                13 July 2017
                2017
                : 15
                : 115
                Affiliations
                [1 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Cancer Epidemiology Unit, Nuffield Department of Population Health, , University of Oxford, ; Oxford, OX3 7LF United Kingdom
                [2 ]ISNI 0000 0001 1942 5154, GRID grid.211011.2, , Molecular Epidemiology Group, Max Delbrueck Center for Molecular Medicine in the Helmholtz Association (MDC), ; Berlin, Germany
                [3 ]ISNI 0000 0001 2108 7481, GRID grid.9594.1, Department of Hygiene and Epidemiology, , University of Ioannina School of Medicine, ; Ioannina, Greece
                [4 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Epidemiology and Biostatistics, School of Public Health, , Imperial College London, ; London, United Kingdom
                [5 ]ISNI 0000 0001 2175 6024, GRID grid.417390.8, , Danish Cancer Society Research Center, ; Copenhagen, Denmark
                [6 ]ISNI 0000 0001 1956 2722, GRID grid.7048.b, Department of Public Health, Section for Epidemiology, , Aarhus University, ; Aarhus, Denmark
                [7 ]ISNI 0000 0004 0492 0584, GRID grid.7497.d, , Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), ; Heidelberg, Germany
                [8 ]ISNI 0000 0004 0390 0098, GRID grid.418213.d, Department of Epidemiology, , German Institute of Human Nutrition Potsdam-Rehbrücke, ; Nuthetal, Germany
                [9 ]GRID grid.424637.0, , Hellenic Health Foundation, ; Athens, Greece
                [10 ]ISNI 0000 0001 2155 0800, GRID grid.5216.0, WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, , University of Athens Medical School, ; Athens, Greece
                [11 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Epidemiology, , Harvard School of Public Health, ; Boston, USA
                [12 ]ISNI 0000 0001 0807 2568, GRID grid.417893.0, Epidemiology and Prevention Unit, , Fondazione IRCCS Istituto Nazionale dei Tumori, ; Milano, Italy
                [13 ]ISNI 0000 0004 1758 0566, GRID grid.417623.5, , Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, ; Florence, Italy
                [14 ]ISNI 0000 0004 1756 876X, GRID grid.420240.0, , Unit of Cancer Epidemiology, AO Citta’ della Salute e della Scienza-University of Turin and Center for Cancer Prevention (CPO-Piemonte), ; Turin, Italy
                [15 ]Cancer Registry and Histopathology Unit, “Civic - M.P. Arezzo” Hospital, Azienda Sanitaria Provinciale, Ragusa, Italy
                [16 ]ISNI 0000 0001 2208 0118, GRID grid.31147.30, Department for Determinants of Chronic Diseases (DCD), , National Institute for Public Health and the Environment (RIVM), ; Bilthoven, The Netherlands
                [17 ]ISNI 0000 0001 2308 5949, GRID grid.10347.31, Department of Social & Preventive Medicine, Faculty of Medicine, , University of Malaya, ; Kuala Lumpur, Malaysia
                [18 ]GRID grid.417656.7, , Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L’Hospitalet de Llobregat, ; Barcelona, Spain
                [19 ]Public Health Division of Gipuzkoa, Regional Government of the Basque Country, Donostia, Spain
                [20 ]CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
                [21 ]Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs, GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
                [22 ]Navarra Public Health Institute, Pamplona, Spain
                [23 ]Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
                [24 ]GRID grid.452553.0, Department of Epidemiology, Regional Health Council, , IMIB-Arrixaca, ; Murcia, Spain
                [25 ]ISNI 0000 0001 2287 8496, GRID grid.10586.3a, Department of Health and Social Sciences, , Universidad de Murcia, ; Murcia, Spain
                [26 ]Public Health Directorate, Asturias, Spain
                [27 ]ISNI 0000 0004 1936 9457, GRID grid.8993.b, Department of Surgical Sciences, , Uppsala University, ; Uppsala, Sweden
                [28 ]ISNI 0000 0001 1034 3451, GRID grid.12650.30, Department of Surgical and Perioperative Sciences, Urology and Andrology, , Umeå University, ; Umeå, Sweden
                [29 ]ISNI 0000 0001 1034 3451, GRID grid.12650.30, Department of Biobank Research, , Umeå University, ; Umeå, Sweden
                [30 ]ISNI 0000000121885934, GRID grid.5335.0, MRC Epidemiology Unit, , University of Cambridge, ; Cambridge, United Kingdom
                [31 ]ISNI 0000000121885934, GRID grid.5335.0, , University of Cambridge School of Clinical Medicine, ; Cambridge, United Kingdom
                [32 ]ISNI 0000000405980095, GRID grid.17703.32, , Section of Nutrition and Metabolism, International Agency for Research on Cancer, ; Lyon, France
                Article
                876
                10.1186/s12916-017-0876-7
                5508687
                28701188
                be77d2b7-cc1e-4c5b-9817-afab6f2d2b2e
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 December 2016
                : 16 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000289, Cancer Research UK;
                Award ID: C570/A16491
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Medicine
                adiposity,obesity,height,prostate cancer,cohort study,tumour characteristics,high grade
                Medicine
                adiposity, obesity, height, prostate cancer, cohort study, tumour characteristics, high grade

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