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      PREVIEW: Prevention of Diabetes through Lifestyle Intervention and Population Studies in Europe and around the World. Design, Methods, and Baseline Participant Description of an Adult Cohort Enrolled into a Three-Year Randomised Clinical Trial

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          Abstract

          Type-2 diabetes (T2D) is one of the fastest growing chronic diseases worldwide. The PREVIEW project has been initiated to find the most effective lifestyle (diet and physical activity) for the prevention of T2D, in overweight and obese participants with increased risk for T2D. The study is a three-year multi-centre, 2 × 2 factorial, randomised controlled trial. The impact of a high-protein, low-glycaemic index (GI) vs. moderate protein, moderate-GI diet in combination with moderate or high-intensity physical activity on the incidence of T2D and the related clinical end-points are investigated. The intervention started with a two-month weight reduction using a low-calorie diet, followed by a randomised 34-month weight maintenance phase comprising four treatment arms. Eight intervention centres are participating (Denmark, Finland, United Kingdom, The Netherlands, Spain, Bulgaria, Australia, and New Zealand). Data from blood specimens, urine, faeces, questionnaires, diaries, body composition assessments, and accelerometers are collected at months 0, 2, 6, 12, 18, 24, and 36. In total, 2326 adults were recruited. The mean age was 51.6 (SD 11.6) years, 67% were women. PREVIEW is, to date, the largest multinational trial to address the prevention of T2D in pre-diabetic adults through diet and exercise intervention. Participants will complete the final intervention in March, 2018.

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          Effect of the volume and intensity of exercise training on insulin sensitivity.

          Physical activity enhances insulin action in obese/overweight individuals. However, the exercise prescription required for the optimal enhancement is not known. The purpose of this study was to test the hypothesis that exercise training consisting of vigorous-intensity activity would enhance insulin sensitivity more substantially than moderate-intensity activity. Sedentary, overweight/obese subjects (n = 154) were randomly assigned to either control or an exercise group for 6 mo: 1) low-volume/moderate-intensity group [ approximately 12 miles walking/wk at 40-55% peak O2 consumption (Vo2 peak)], 2) low-volume/high-intensity group ( approximately 12 miles jogging/wk at 65-80% Vo2 peak), and 3) high-volume/high-intensity group ( approximately 20 miles jogging/wk at 65-80% Vo2 peak). Training volume (miles/wk) was achieved by exercising approximately 115 min/wk (low-volume/high-intensity group) or approximately 170 min/wk (low-volume/moderate-intensity and high-volume/high-intensity groups). Insulin action was measured with an insulin sensitivity index (SI) from an intravenous glucose tolerance test. In the control group, there was a decrement (P < 0.05) in SI. In contrast, all the exercise groups significantly (P < 0.05) increased SI; the relative increment in the low-volume/moderate-intensity and high-volume/high-intensity groups ( approximately 85%) were greater than in the low-volume/high-intensity group ( approximately 40%). In conclusion, physical activity encompassing a wide range of intensity and volume minimizes the insulin resistance that develops with a sedentary lifestyle. However, an exercise prescription that incorporated approximately 170 min of exercise/wk improved insulin sensitivity more substantially than a program utilizing approximately 115 min of exercise/wk, regardless of exercise intensity and volume. Total exercise duration should thus be considered when designing training programs with the intent of improving insulin action.
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            Predictors of progression from impaired glucose tolerance to NIDDM: an analysis of six prospective studies.

            Risk factors associated with the progression from impaired glucose tolerance (IGT) to NIDDM were examined in data from six prospective studies. IGT and NIDDM were defined in all studies by World Health Organization (WHO) criteria, and baseline risk factors were measured at the time of first recognition of IGT. The studies varied in size from 177 to 693 participants with IGT, and included men and women followed from 2 to 27 years after the recognition of IGT. Across the six studies, the incidence rate of NIDDM was 57.2/1,000 person-years and ranged from 35.8/1,000 to 87.3/1,000 person-years. Although baseline measures of fasting and 2-h postchallenge glucose levels were both positively associated with NIDDM incidence, incidence rates were sharply higher for those in the top quartile of fasting plasma glucose levels, but increased linearly with increasing 2-h postchallenge glucose quartiles. Incidence rates were higher among the Hispanic, Mexican-American, Pima, and Nauruan populations than among Caucasians. The effect of baseline age on NIDDM incidence rates differed among the studies; the rates did not increase or rose only slightly with increasing baseline age in three of the studies and formed an inverted U in three studies. In all studies, estimates of obesity (including BMI, waist-to-hip ratio, and waist circumference) were positively associated with NIDDM incidence. BMI was associated with NIDDM incidence independently of fasting and 2-h post challenge glucose levels in the combined analysis of all six studies and in three cohorts separately, but not in the three studies with the highest NIDDM incidence rates. Sex and family history of diabetes were generally not related to NIDDM progression. This analysis indicates that persons with IGT are at high risk and that further refinement of risk can be made by other simple measurements. The ability to identify persons at high risk of NIDDM should facilitate clinical trials in diabetes prevention.
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              Stages of change in the modification of problem behaviors.

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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                20 June 2017
                June 2017
                : 9
                : 6
                : 632
                Affiliations
                [1 ]Department of Food and Environmental Sciences, University of Helsinki, 00014 Helsinki, Finland; elli.jalo@ 123456helsinki.fi
                [2 ]Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 30, Frederiksberg C, DK-1958 Copenhagen, Denmark; tml@ 123456nexs.ku.dk (T.M.L.); piach@ 123456nexs.ku.dk (P.C.); laura.pastor@ 123456adm.ku.dk (L.P.-S.); ara@ 123456nexs.ku.dk (A.R.)
                [3 ]Department of Human Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands; m.westerterp@ 123456maastrichtuniversity.nl (M.W.-P.); m.drummen@ 123456maastrichtuniversity.nl (M.D.)
                [4 ]School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham NG7 2UH, UK; Ian.Macdonald@ 123456nottingham.ac.uk (I.M.); liz.simpson@ 123456nottingham.ac.uk (E.S.)
                [5 ]Center for Nutrition Research, University of Navarra, 31008 Pamplona, Spain; jalfmtz@ 123456unav.es (J.A.M.); snavas@ 123456unav.es (S.N.-C.)
                [6 ]CIBERobn, Instituto de Salud Carlos III, 28029 Madrid, Spain
                [7 ]Department of pharmacology and toxicology, Medical University of Sofia, 1431 Sofia, Bulgaria; nadkaboyadjieva@ 123456gmail.com (N.B.); teodorah@ 123456abv.bg (T.H.-D.)
                [8 ]Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland 1024, New Zealand; s.poppitt@ 123456auckland.ac.nz (S.P.); m.silvestre@ 123456auckland.ac.nz (M.P.S.)
                [9 ]Department of Exercise and Health Sciences, University of Stuttgart, 70569 Stuttgart, Germany; wolfgang.schlicht@ 123456inspo.uni-stuttgart.de
                [10 ]School of Sport and Exercise Sciences, A.STEM Research Centre, Swansea University, Swansea SA1 8EN, UK; g.stratton@ 123456swansea.ac.uk
                [11 ]National Institute for Health and Welfare THL, 00300 Helsinki, Finland; jouko.sundvall@ 123456thl.fi
                [12 ]NetUnion sarl, Ave des Figuires 20, 1007 Lausanne, Switzerland; lam@ 123456netunion.com
                [13 ]Charles Perkins Centre, University of Sydney, Sydney 2006, Australia; roslyn.muirhead@ 123456sydney.edu.au (R.M.); jennie.brandmiller@ 123456sydney.edu.au (J.B.-M.)
                [14 ]Department of Health Science, University of Education Schwäbisch Gmünd, 73525 Gmünd, Germany; daniela.kahlert@ 123456ph-gmuend.de
                Author notes
                [* ]Correspondence: mikael.fogelholm@ 123456helsinki.fi ; Tel.: +358-503180302
                Article
                nutrients-09-00632
                10.3390/nu9060632
                5490611
                28632180
                601e408f-5d02-40e2-b710-669f3bae42a4
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 May 2017
                : 16 June 2017
                Categories
                Article

                Nutrition & Dietetics
                diet,protein,carbohydrate,glycaemic index,physical activity,obesity
                Nutrition & Dietetics
                diet, protein, carbohydrate, glycaemic index, physical activity, obesity

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