Ignite Creation Date:
2025-12-25 @ 12:57 AM
Ignite Modification Date:
2026-02-28 @ 3:48 AM
Study NCT ID:
NCT01777893
Status:
COMPLETED
Last Update Posted:
2019-03-20
First Post:
2013-01-24
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Effect of Diet and Physical Activity on Incidence of Type 2 Diabetes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018149', 'term': 'Glucose Intolerance'}, {'id': 'D009765', 'term': 'Obesity'}, {'id': 'D009043', 'term': 'Motor Activity'}], 'ancestors': [{'id': 'D006943', 'term': 'Hyperglycemia'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D050177', 'term': 'Overweight'}, {'id': 'D044343', 'term': 'Overnutrition'}, {'id': 'D009748', 'term': 'Nutrition Disorders'}, {'id': 'D001835', 'term': 'Body Weight'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'PREVENTION', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 2500}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2013-06'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2019-03', 'completionDateStruct': {'date': '2018-12', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2019-03-18', 'studyFirstSubmitDate': '2013-01-24', 'studyFirstSubmitQcDate': '2013-01-28', 'lastUpdatePostDateStruct': {'date': '2019-03-20', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2013-01-29', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2018-03', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Direct and indirect costs.', 'timeFrame': '3 years'}], 'primaryOutcomes': [{'measure': 'Incidence of type 2 diabetes', 'timeFrame': '3 years', 'description': 'For adults by OGTT\n\nIncidence of type 2 diabetes, in high protein versus medium protein diet, measured during 3 years after baseline and based on WHO/IDF criteria:\n\nFasting plasma glucose (FPG) \\> 7.0 mmol/l (126 mg/dl) or, 75 g oral glucose tolerance test (OGTT) with FPG \\> 7.0 mmol/l (126 mg/dl) and/or 2 hour plasma glucose \\> 11.1 mmol/l (200 mg/dl) or, Glycated haemoglobin (HbA1c) \\> 6.5% (48 mmol/mol), or Random plasma glucose \\> 11.1 mmol/l (200 mg/dl) in the presence of classical diabetes symptoms.\n\nFor children and adolescents:\n\nChange in insulin resistance at 2 years after randomization to high protein versus medium protein diet, measured by insulin resistance analysed by the homeostatic model (HOMA-IR).'}], 'secondaryOutcomes': [{'measure': 'Incidence of type-2 diabetes', 'timeFrame': '2 years', 'description': 'For children by HOMA-IR The effect of high intensity vs. moderate intensity physical activity on incidence of type 2 diabetes, based on WHO/IDF criteria (adjusted for diet).\n\nFasting plasma glucose (FPG) \\> 7.0 mmol/l (126 mg/dl) or, 75 g oral glucose tolerance test (OGTT) with FPG \\> 7.0 mmol/l (126 mg/dl) and/or 2 hour plasma glucose \\> 11.1 mmol/l (200 mg/dl) or, Glycated hemoglobin (HbA1c) \\> 6.5% (48 mmol/mol), or Random plasma glucose \\> 11.1 mmol/l (200 mg/dl) in the presence of classical diabetes symptoms.\n\nFor children and adolescents:\n\nChange in insulin resistance at 2 years after randomization to high intensity vs. moderate intensity physical activity, analyzed by the homeostatic model (HOMA-IR).'}, {'measure': 'Change in HbA1c', 'timeFrame': '3 years', 'description': 'A measure of average blood glucose levels'}, {'measure': 'Change in body weight (kg or percent) and waist 8cm), hip (cm) and thigh circumference (cm)', 'timeFrame': '3 years', 'description': 'Measures of body composition'}, {'measure': 'Change in body composition - fat mass and fat-free mass (kg, proportion of body weight)', 'timeFrame': '3 years', 'description': 'DXA, BodPod, or bio-impedance'}, {'measure': 'Proportion of subjects maintaining at least 0, 5 or 10% weight loss', 'timeFrame': '3 years', 'description': 'Relative to initial body weight'}, {'measure': 'Insulin sensitivity (e.g Matsuda Index based on the OGTT, glucose area under the curve (AUC) during OGTT, beta-cell disposition index) (OGTT only adults)', 'timeFrame': '3 years', 'description': 'Measures of insulin sensitivity and glucose tolerance'}, {'measure': 'Risk factors for cardiovascular disease, with at least the following measures: blood pressure, heart rate, lipids (triglycerides, total, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol), C-reactive protein, and liver enzymes', 'timeFrame': '3 years', 'description': 'Risk factors for CVD'}, {'measure': 'Changes in dietary intake (4-d weighed food records)', 'timeFrame': '3 years'}, {'measure': 'Changes in physical activity (accelerometers and questionnaires).', 'timeFrame': '3 years'}, {'measure': 'Changes in perceived quality of life and workability, habitual well-being, sleep and chronic stress, subjective appetite sensations, dietary restraint, moderators, mediators, behavioral and social environment.', 'timeFrame': '3 years'}, {'measure': 'The effects of stature (height; proportion leg-length/height) in adults and changes in stature in children and adolescents, on the changes in relationship between reduction in body weight, body fat and insulin sensitivity', 'timeFrame': '3 years'}, {'measure': 'Safety parameters (blood samples).', 'timeFrame': 'Screening and during 3 years'}, {'measure': 'Adverse events and concomitant medication.', 'timeFrame': 'Screening and during 3 years', 'description': 'Registration by questionnaires.'}, {'measure': 'Compliance by urin samples for nitrogen analyses.', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Metabolomic profiling.', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: DNA, RNA', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Colon cancer risk markers', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Kidney safety markers, body fat and liver-fat content.', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Body and liver-fat content.', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Changes in brain responses and cortical thickness', 'timeFrame': '2 years'}, {'measure': 'In a sub-group: Changes in 48-h energy expenditure in a respiration chamber setting', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Gut microbiome', 'timeFrame': '3 years'}, {'measure': 'In a sub-group: Circulating amino acids', 'timeFrame': '8 wks'}, {'measure': 'In a sub-group: Plasma mitochondrial peptides', 'timeFrame': '8 wks'}, {'measure': 'In a sub-group: Insulin Growth factor 2 (IGF-II) and IGF-II receptor (IGF2R)', 'timeFrame': '8 wks'}]}, 'oversightModule': {'oversightHasDmc': True}, 'conditionsModule': {'keywords': ['Type-2 diabetes mellitus', 'Obesity', 'High protein diet', 'Low GI', 'Physical activity'], 'conditions': ['Pre-diabetes', 'Obesity']}, 'referencesModule': {'references': [{'pmid': '41094026', 'type': 'DERIVED', 'citation': 'Zhu R, Guo J, Huttunen-Lenz M, Silvestre M, Stratton G, Macdonald IA, Handjieva-Darlenska T, Handjiev S, Navas-Carretero S, Poppitt SD, Fogelholm M, Martinez-Urbistondo D, Martinez JA, Raben A, Brand-Miller J. Long-term effects of dietary protein and carbohydrate quality on prediabetes remission: results from the PREVIEW randomised multinational diabetes prevention trial. Diabetologia. 2026 Jan;69(1):81-92. doi: 10.1007/s00125-025-06560-x. Epub 2025 Oct 15.'}, {'pmid': '39423758', 'type': 'DERIVED', 'citation': 'Lim JJ, Prodhan UK, Silvestre MP, Liu AY, McLay J, Fogelholm M, Raben A, Poppitt SD, Cameron-Smith D. Low serum glycine strengthens the association between branched-chain amino acids and impaired insulin sensitivity assessed before and after weight loss in a population with pre-diabetes: The PREVIEW_NZ cohort. Clin Nutr. 2024 Dec;43(12):17-25. doi: 10.1016/j.clnu.2024.09.047. Epub 2024 Oct 2.'}, {'pmid': '39182617', 'type': 'DERIVED', 'citation': 'Jiang YC, Lai K, Muirhead RP, Chung LH, Huang Y, James E, Liu XT, Wu J, Atkinson FS, Yan S, Fogelholm M, Raben A, Don AS, Sun J, Brand-Miller JC, Qi Y. Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy. Am J Clin Nutr. 2024 Oct;120(4):864-878. doi: 10.1016/j.ajcnut.2024.08.015. Epub 2024 Aug 23.'}, {'pmid': '38916158', 'type': 'DERIVED', 'citation': 'Huttunen-Lenz M, Hansen S, Raben A, Westerterp-Plantenga M, Adam T, Macdonald I, Stratton G, Swindell N, Martinez JA, Navas-Carretero S, Handjieva-Darlenska T, Handjiev S, Poppitt SD, Silvestre MP, Larsen TM, Vestentoft PS, Fogelholm M, Jalo E, Brand-Miller J, Muirhead R, Schlicht W. Hybrid Evaluation of a Lifestyle Change Program to Prevent the Development of Type 2 Diabetes Among Individuals With Prediabetes: Intended and Observed Changes in Intervening Mechanisms. J Prim Care Community Health. 2024 Jan-Dec;15:21501319241248223. doi: 10.1177/21501319241248223.'}, {'pmid': '37649005', 'type': 'DERIVED', 'citation': 'Huttunen-Lenz M, Raben A, Adam T, Macdonald I, Taylor MA, Stratton G, Mackintosh K, Martinez JA, Handjieva-Darlenska T, Bogdanov GA, Poppitt SD, Silvestre MP, Fogelholm M, Jalo E, Brand-Miller J, Muirhead R, Schlicht W. Socio-economic factors, mood, primary care utilization, and quality of life as predictors of intervention cessation and chronic stress in a type 2 diabetes prevention intervention (PREVIEW Study). BMC Public Health. 2023 Aug 30;23(1):1666. doi: 10.1186/s12889-023-16569-9.'}, {'pmid': '35610522', 'type': 'DERIVED', 'citation': 'Zhu R, Craciun I, Bernhards-Werge J, Jalo E, Poppitt SD, Silvestre MP, Huttunen-Lenz M, McNarry MA, Stratton G, Handjiev S, Handjieva-Darlenska T, Navas-Carretero S, Sundvall J, Adam TC, Drummen M, Simpson EJ, Macdonald IA, Brand-Miller J, Muirhead R, Lam T, Vestentoft PS, Faerch K, Martinez JA, Fogelholm M, Raben A. Age- and sex-specific effects of a long-term lifestyle intervention on body weight and cardiometabolic health markers in adults with prediabetes: results from the diabetes prevention study PREVIEW. Diabetologia. 2022 Aug;65(8):1262-1277. doi: 10.1007/s00125-022-05716-3. Epub 2022 May 25.'}, {'pmid': '35599315', 'type': 'DERIVED', 'citation': 'Jian C, Silvestre MP, Middleton D, Korpela K, Jalo E, Broderick D, de Vos WM, Fogelholm M, Taylor MW, Raben A, Poppitt S, Salonen A. Gut microbiota predicts body fat change following a low-energy diet: a PREVIEW intervention study. Genome Med. 2022 May 23;14(1):54. doi: 10.1186/s13073-022-01053-7.'}, {'pmid': '35263691', 'type': 'DERIVED', 'citation': 'Zhu R, Fogelholm M, Jalo E, Poppitt SD, Silvestre MP, Moller G, Huttunen-Lenz M, Stratton G, Sundvall J, Macdonald IA, Handjieva-Darlenska T, Handjiev S, Navas-Carretero S, Martinez JA, Muirhead R, Brand-Miller J, Raben A. Animal-based food choice and associations with long-term weight maintenance and metabolic health after a large and rapid weight loss: The PREVIEW study. Clin Nutr. 2022 Apr;41(4):817-828. doi: 10.1016/j.clnu.2022.02.002. Epub 2022 Feb 8.'}, {'pmid': '34915273', 'type': 'DERIVED', 'citation': 'Zhu R, Larsen TM, Poppitt SD, Silvestre MP, Fogelholm M, Jalo E, Hatonen KA, Huttunen-Lenz M, Taylor MA, Simpson L, Mackintosh KA, McNarry MA, Navas-Carretero S, Martinez JA, Handjieva-Darlenska T, Handjiev S, Drummen M, Westerterp-Plantenga MS, Lam T, Vestentoft PS, Muirhead R, Brand-Miller J, Raben A. Associations of quantity and quality of carbohydrate sources with subjective appetite sensations during 3-year weight-loss maintenance: Results from the PREVIEW intervention study. Clin Nutr. 2022 Jan;41(1):219-230. doi: 10.1016/j.clnu.2021.11.038. Epub 2021 Dec 3.'}, {'pmid': '34790686', 'type': 'DERIVED', 'citation': 'Navas-Carretero S, San-Cristobal R, Siig Vestentoft P, Brand-Miller JC, Jalo E, Westerterp-Plantenga M, Simpson EJ, Handjieva-Darlenska T, Stratton G, Huttunen-Lenz M, Lam T, Muirhead R, Poppitt S, Pietilainen KH, Adam T, Taylor MA, Handjiev S, McNarry MA, Hansen S, Brodie S, Silvestre MP, Macdonald IA, Boyadjieva N, Mackintosh KA, Schlicht W, Liu A, Larsen TM, Fogelholm M, Raben A, Martinez JA. Appraisal of Triglyceride-Related Markers as Early Predictors of Metabolic Outcomes in the PREVIEW Lifestyle Intervention: A Controlled Post-hoc Trial. Front Nutr. 2021 Nov 1;8:733697. doi: 10.3389/fnut.2021.733697. eCollection 2021.'}, {'pmid': '34375397', 'type': 'DERIVED', 'citation': 'Drummen M, Adam TC, Macdonald IA, Jalo E, Larssen TM, Martinez JA, Handjiev-Darlenska T, Brand-Miller J, Poppitt SD, Stratton G, Pietilainen KH, Taylor MA, Navas-Carretero S, Handjiev S, Muirhead R, Silvestre MP, Swindell N, Huttunen-Lenz M, Schlicht W, Lam T, Sundvall J, Raman L, Feskens E, Tremblay A, Raben A, Westerterp-Plantenga MS. Associations of changes in reported and estimated protein and energy intake with changes in insulin resistance, glycated hemoglobin, and BMI during the PREVIEW lifestyle intervention study. Am J Clin Nutr. 2021 Nov 8;114(5):1847-1858. doi: 10.1093/ajcn/nqab247.'}, {'pmid': '34141717', 'type': 'DERIVED', 'citation': 'Zhu R, Fogelholm M, Larsen TM, Poppitt SD, Silvestre MP, Vestentoft PS, Jalo E, Navas-Carretero S, Huttunen-Lenz M, Taylor MA, Stratton G, Swindell N, Kaartinen NE, Lam T, Handjieva-Darlenska T, Handjiev S, Schlicht W, Martinez JA, Seimon RV, Sainsbury A, Macdonald IA, Westerterp-Plantenga MS, Brand-Miller J, Raben A. A High-Protein, Low Glycemic Index Diet Suppresses Hunger but Not Weight Regain After Weight Loss: Results From a Large, 3-Years Randomized Trial (PREVIEW). Front Nutr. 2021 Jun 1;8:685648. doi: 10.3389/fnut.2021.685648. eCollection 2021.'}, {'pmid': '34088702', 'type': 'DERIVED', 'citation': 'Adam TC, Drummen M, Macdonald I, Jalo E, Siig-Vestentoft P, Martinez JA, Handjiev-Darlenska T, Brand-Miller J, Poppitt S, Stratton G, Fogelholm M, Pietilainen KH, Taylor M, Navas-Carretero S, Winkens B, Handjiev S, Muirhead R, Silvestre M, Swindell N, Huttunen-Lenz M, Schlicht W, Lam T, Sundvall J, Raman L, Feskens E, Larssen TM, Tremblay A, Raben A, Westerterp-Plantenga M. Association of Psychobehavioral Variables With HOMA-IR and BMI Differs for Men and Women With Prediabetes in the PREVIEW Lifestyle Intervention. Diabetes Care. 2021 Jul;44(7):1491-1498. doi: 10.2337/dc21-0059. Epub 2021 Jun 4.'}, {'pmid': '34045241', 'type': 'DERIVED', 'citation': 'Zhu R, Larsen TM, Fogelholm M, Poppitt SD, Vestentoft PS, Silvestre MP, Jalo E, Navas-Carretero S, Huttunen-Lenz M, Taylor MA, Stratton G, Swindell N, Drummen M, Adam TC, Ritz C, Sundvall J, Valsta LM, Muirhead R, Brodie S, Handjieva-Darlenska T, Handjiev S, Martinez JA, Macdonald IA, Westerterp-Plantenga MS, Brand-Miller J, Raben A. Dose-Dependent Associations of Dietary Glycemic Index, Glycemic Load, and Fiber With 3-Year Weight Loss Maintenance and Glycemic Status in a High-Risk Population: A Secondary Analysis of the Diabetes Prevention Study PREVIEW. Diabetes Care. 2021 Jul;44(7):1672-1681. doi: 10.2337/dc20-3092. Epub 2021 May 27.'}, {'pmid': '33829034', 'type': 'DERIVED', 'citation': 'Buso MEC, Seimon RV, McClintock S, Muirhead R, Atkinson FS, Brodie S, Dodds J, Zibellini J, Das A, Wild-Taylor AL, Burk J, Fogelholm M, Raben A, Brand-Miller JC, Sainsbury A. Can a Higher Protein/Low Glycemic Index vs. a Conventional Diet Attenuate Changes in Appetite and Gut Hormones Following Weight Loss? A 3-Year PREVIEW Sub-study. Front Nutr. 2021 Mar 22;8:640538. doi: 10.3389/fnut.2021.640538. eCollection 2021.'}, {'pmid': '33365325', 'type': 'DERIVED', 'citation': 'Meroni A, Muirhead RP, Atkinson FS, Fogelholm M, Raben A, Brand-Miller JC. Is a Higher Protein-Lower Glycemic Index Diet More Nutritious Than a Conventional Diet? A PREVIEW Sub-study. Front Nutr. 2020 Dec 7;7:603801. doi: 10.3389/fnut.2020.603801. eCollection 2020.'}, {'pmid': '32333763', 'type': 'DERIVED', 'citation': 'Drummen M, Tischmann L, Gatta-Cherifi B, Cota D, Matias I, Raben A, Adam T, Westerterp-Plantenga M. Role of Endocannabinoids in Energy-Balance Regulation in Participants in the Postobese State-a PREVIEW Study. J Clin Endocrinol Metab. 2020 Jul 1;105(7):e2511-20. doi: 10.1210/clinem/dgaa193.'}, {'pmid': '32131847', 'type': 'DERIVED', 'citation': 'Swindell N, Rees P, Fogelholm M, Drummen M, MacDonald I, Martinez JA, Navas-Carretero S, Handjieva-Darlenska T, Boyadjieva N, Bogdanov G, Poppitt SD, Gant N, Silvestre MP, Brand-Miller J, Schlicht W, Muirhead R, Brodie S, Tikkanen H, Jalo E, Westerterp-Plantenga M, Adam T, Vestentoft PS, Larsen TM, Raben A, Stratton G. Compositional analysis of the associations between 24-h movement behaviours and cardio-metabolic risk factors in overweight and obese adults with pre-diabetes from the PREVIEW study: cross-sectional baseline analysis. Int J Behav Nutr Phys Act. 2020 Mar 4;17(1):29. doi: 10.1186/s12966-020-00936-5.'}, {'pmid': '31754687', 'type': 'DERIVED', 'citation': 'Drummen M, Tischmann L, Gatta-Cherifi B, Fogelholm M, Raben A, Adam TC, Westerterp-Plantenga MS. High Compared with Moderate Protein Intake Reduces Adaptive Thermogenesis and Induces a Negative Energy Balance during Long-term Weight-Loss Maintenance in Participants with Prediabetes in the Postobese State: A PREVIEW Study. J Nutr. 2020 Mar 1;150(3):458-463. doi: 10.1093/jn/nxz281.'}, {'pmid': '31255969', 'type': 'DERIVED', 'citation': 'Drummen M, Heinecke A, Dorenbos E, Vreugdenhil A, Raben A, Westerterp-Plantenga MS, Adam TC. Reductions in body weight and insulin resistance are not associated with changes in grey matter volume or cortical thickness during the PREVIEW study. J Neurol Sci. 2019 Aug 15;403:106-111. doi: 10.1016/j.jns.2019.06.017. Epub 2019 Jun 14.'}, {'pmid': '31139889', 'type': 'DERIVED', 'citation': 'Moller G, Andersen JR, Jalo E, Ritz C, Brand-Miller J, Larsen TM, Silvestre MP, Fogelholm M, Poppitt SD, Raben A, Dragsted LO. The association of dietary animal and plant protein with putative risk markers of colorectal cancer in overweight pre-diabetic individuals during a weight-reducing programme: a PREVIEW sub-study. Eur J Nutr. 2020 Jun;59(4):1517-1527. doi: 10.1007/s00394-019-02008-2. Epub 2019 May 28.'}, {'pmid': '30088336', 'type': 'DERIVED', 'citation': 'Christensen P, Meinert Larsen T, Westerterp-Plantenga M, Macdonald I, Martinez JA, Handjiev S, Poppitt S, Hansen S, Ritz C, Astrup A, Pastor-Sanz L, Sando-Pedersen F, Pietilainen KH, Sundvall J, Drummen M, Taylor MA, Navas-Carretero S, Handjieva-Darlenska T, Brodie S, Silvestre MP, Huttunen-Lenz M, Brand-Miller J, Fogelholm M, Raben A. Men and women respond differently to rapid weight loss: Metabolic outcomes of a multi-centre intervention study after a low-energy diet in 2500 overweight, individuals with pre-diabetes (PREVIEW). Diabetes Obes Metab. 2018 Dec;20(12):2840-2851. doi: 10.1111/dom.13466. Epub 2018 Aug 7.'}, {'pmid': '30086649', 'type': 'DERIVED', 'citation': 'Drummen M, Dorenbos E, Vreugdenhil ACE, Raben A, Fogelholm M, Westerterp-Plantenga MS, Adam TC. Long-term effects of increased protein intake after weight loss on intrahepatic lipid content and implications for insulin sensitivity: a PREVIEW study. Am J Physiol Endocrinol Metab. 2018 Nov 1;315(5):E885-E891. doi: 10.1152/ajpendo.00162.2018. Epub 2018 Aug 7.'}, {'pmid': '29158249', 'type': 'DERIVED', 'citation': 'Swindell N, Mackintosh K, McNarry M, Stephens JW, Sluik D, Fogelholm M, Drummen M, MacDonald I, Martinez JA, Handjieva-Darlenska T, Poppitt SD, Brand-Miller J, Larsen TM, Raben A, Stratton G. Objectively Measured Physical Activity and Sedentary Time Are Associated With Cardiometabolic Risk Factors in Adults With Prediabetes: The PREVIEW Study. Diabetes Care. 2018 Mar;41(3):562-569. doi: 10.2337/dc17-1057. Epub 2017 Nov 20.'}]}, 'descriptionModule': {'briefSummary': 'Type-2 diabetes is one of the fastest growing chronic diseases worldwide. This trend is mainly driven by a global increase in the prevalence of obesity. The PREVIEW study has been initiated to find out the most effective lifestyle-components (diet and physical activity) in the prevention of Type-2 diabetes. The project consists of a randomized lifestyle-intervention with the more specific aim to determine the preventative impact of a high-protein and low-GI diet in combination with moderate or high intensity physical activity compared with a moderate-protein and moderate GI diet in combination with the same activity levels on the incidence of Type-2 diabetes in predisposed, pre-diabetic children, young and older adults.\n\nThe trial will be performed in 6 EU countries (Bulgaria, Denmark, Finland, Spain, Netherlands, UK) and Australia and New Zealand.\n\nA total of 2,500 overweight or obese adult participants (25-70 y) as well as 150 children and adolescents aged 10-18 y) will be recruited. All adult participants are first treated by a low-calorie diet for 8 weeks, with an aim to reach ≥ 8% weight reduction. Children and adolescents are treated separately with a conventional weight-reduction diet, with-out a specific aim for absolute weight loss.\n\nThe adult participants are randomized into two different diet interventions and two exercise interventions for a total of 148 weeks. This period aims at preventing Type-2 diabetes by weight-maintenance (prevention of relapse in reduced body weight) and by independent metabolic effects of diet and physical activity.\n\nThe primary endpoint of the study is the incidence of Type-2 diabetes in the adults during 3 years (156 weeks) according to diet (high protein/low-GI versus moderate protein/moderate-GI, adjusted for physical activity), based on a 75 g oral glucose tolerance test and/or HbA1c.\n\nFor children and adolescents:\n\nChange in insulin resistance at 2 years after randomization to high protein versus moderate protein diet, measured by insulin resistance analyzed by the homeostatic model (HOMA-IR) as well as physiological improvement of health with respect to pre-diabetic characteristics.\n\nOur hypothesis is that a high-protein, low-GI diet will be superior in preventing type-2 diabetes, compared with a moderate protein, moderate GI diet, and that high-intensity physical activity will be superior compared to moderate-intensity physical activity.', 'detailedDescription': 'Type-2 diabetes is one of the fastest growing chronic diseases worldwide. This trend is mainly driven by a global increase in the prevalence of obesity. The PREVIEW study has been initialized to find the most effective lifestyle-components (diet and physical activity) in the prevention of T2D. The project is a randomized lifestyle-intervention. The main aim is to determine the preventative impact of a high-protein and low-GI diet in combination with moderate or high intensity physical activity on the incidence of T2D in predisposed, pre-diabetic children, younger and older adults (both gender). In substudies following will be assessed; changes in fat distribution (adults), risk of colon cancer by biomarkers (fecal samples in adults), change in physical fitness (VO2 max in adults), metabolomics profile (adults), food reward (children and adolescents) and sleep architecture (children and adolescents).\n\nObjective: The project addresses prevention in individuals with high risk for T2D. The trial will be performed in 6 EU countries (Bulgaria, Denmark, Finland, Spain, Netherlands, United Kingdom), as well as in Australia and New Zealand.\n\nStudy design: The PREVIEW intervention study will be carried out as a 3-year randomized, clinical intervention consisting of an initial 8-week weight loss period and a 148 week randomized weight maintenance intervention.\n\nStudy population: A total of 2500 adult as well as 150 children and adolescent participants will participate in the intervention. All adult participants are first treated by a low-calorie diet for 8 weeks, with an aim to reach \\>8% weight reduction. In skeletal immature children weight loss is not desirable and the goal is to maintain weight (while gaining length) during the initial 8 weeks.\n\nIntervention: The two diet interventions for participants are:\n\nHP = high-protein: protein 25 E%, carbohydrates 45 E%, dietary glycaemic index (GI) \\<50.\n\nMP = moderate-protein: protein intake 15% in total energy intake (E%), carbohydrates 55 E%, GI \\>56;\n\nBoth diets are composed by using healthy food items.\n\nThe two exercise interventions are:\n\nMI = moderate-intensity: 60-75% of maximal heart rate (HRmax), e.g., brisk walking;\n\nHI = high intensity: 76-90% HRmax, e.g., running.\n\nThe randomization for the adults is stratified by sex and age group, and by sex in children.\n\nThe participants are supervised in groups during the LCD (4 times) and throughout the weight-maintenance period. Children are being supervised separately. Meeting frequency is reduced towards the end of the study. The main assessment points (clinical investigation days, CID) are at week 0 (start of weight reduction), week 8 (end of weight reduction/start of randomized intervention), week 26 (6 months from baseline), week 52 (12 months from baseline), week 78 (18 months from baseline) week 104 (24 months from baseline) and week 156 (36 months from baseline / End of Trial, EOT). For the children and adolescents the last assessment point is at week 104 (24 months from baseline/ End of Trial, EOT).\n\nMain study endpoints: The primary endpoint of the intervention study is for adults the incidence of Type-2 diabetes during 3 years (156 weeks) according to diet (high protein versus moderate protein, adjusted for physical activity), based on a 75 g oral glucose tolerance test (OGTT). The incidence of diabetes will be assessed annually by participant self-report of medication requiring diabetes, doctor informed (and confirmed) diabetes diagnosis or diabetes diagnosed by fasting plasma glucose (FPG) and/or OGTT according to IDF guidelines.\n\nFor children and adolescents: Change in insulin resistance at 2 years after randomization to high protein versus medium protein diet, measured by insulin resistance analyzed by the homeostatic model (HOMA-IR) as well as physiological improvement of health with respect to pre-diabetic characteristics.\n\nSecondary endpoints are (tested against the four possible combinations of diet and physical activity if not stated otherwise) the effects of high intensity vs. moderate intensity physical activity on incidence of type 2 diabetes, based on WHO/IDF criteria (adjusted for diet); changes in HbA1c (a measure of average blood glucose levels), body weight and waist, hip and thigh circumference; change in body fat mass (kg, proportion of body weight); proportion of subjects maintaining at least 0, 5 or 10% weight loss (relative to initial body weight); insulin sensitivity (Matsuda Index based on the OGTT, glucose and insulin area under the curve (AUC) during OGTT, beta-cell disposition index)(only adults); risk factors for cardiovascular disease, with at least the following measures: blood pressure, lipids (triglycerides, total, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol), C-reactive protein, and liver enzymes; changes in perceived quality of life and workability, habitual well-being and chronic stress, sleep duration and quality (accelerometer and questionnaire), appetite sensations, and habitual (long-term) physical activity.\n\nSubstudies. Fat distribution: Assessment of fat distribution by MRI (Magnetic Resonance Imaging) and H-MRS (Hydrogen Magnetic Resonance Spectroscopy) is done in a sub-group of subjects at University of Maastricht: 20 from HPMI and 20 from MPMI group. MRI/H-MRS is a non-invasive and non-irradiant imaging technique, which will be used to determine abdominal fat and muscle mass of the upper part of the lower limbs (MRI), muscle and liver fat (H-MRS). MRI and H-MRS measurements take place at weeks 0, 26 and 104.\n\nSampling and analyses of DNA and RNA: The intended use of the samples is epi/genetic analyses in relation to obesity and associated diseases. Genetic sampling will take place at week 0, 52 and 156.\n\nMetabolomics profile: In a sub-group of subjects, urine from baseline week 0 and week 52 will be analyzed for metabolomics profile.\n\nFecal samples: Full fecal samples from 3 consecutive days are collected from a sub-group. The samples are used for assessment of colon cancer risk markers, ie phenolic metabolites, short-chain fatty acids (SCFA), nitrogenous compounds. Subjects are recruited from all four groups on a consecutive invitation basis. Moreover, samples from the same subjects are stored for potential analysis of microbiota. Fecal samples will be collected during weeks 0 and 52.\n\nSleep architecture: In a sub-study we will identify the mediating role of sleeping patterns (sleep quality and duration), stress and brain plasticity on the protein/ activity intervention and the outcome parameters. The sub-study assessing the role of sleep and brain plasticity will be conducted as a repeated measures design embedded in the main intervention study. Measurements will be taken at 0, 26 and 104 weeks.\n\nFood reward: A possible relationship of peripheral insulin sensitivity and brain reward activation will be assessed in a sub-group of pre-diabetic adults, consisting of 2 stratified intervention groups. The sub-study will take place in University of Maastricht and will use functional magnetic resonance imaging (fMRI) in a block design with high calorie/ low calorie food images and control images. Measurements of food reward will be done at weeks 0, 26, and 104.\n\nSub-group of elderly (+55 y): Serum creatinine and urinary albumine assessments for kidney safety measures.\n\nCost-effectiveness: All adult participants will fill in a short questionnaire on medicine use, days absent from work, "less than optimal" workability etc. These answers are used to estimate cost-effectiveness of the life-style programs in PREVIEW. Cost-effectiveness will be assessed in week 0, 52, 104, 156.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'maximumAge': '70 Years', 'minimumAge': '10 Years', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\nFor adults:\n\n1. Age 25 - 70 years:\n\n From mid 2013 - mid 2014, subjects aged 25-45 and 55-70 years were enrolled. From mid 2014, subjects aged 46-54 years were also enrolled.\n2. Overweight or obesity status BMI\\>25 kg/m2\n3. Pre-diabetes The criteria from WHO/IDF (International Diabetes Foundation) for assessing pre-diabetes will be used as the formal inclusion criteria (at screening), i.e. having:\n\n Impaired Fasting Glucose (IFG): Fasting venous plasma glucose concentration 5.6 - 6.9 mmol/l or Impaired Glucose Tolerance (IGT): Venous Plasma glucose concentration of 7.8 - 11.0 mmol/l at 2 h after oral administration of 75 g glucose (oral glucose tolerance test, OGTT), with fasting plasma glucose less than 7.0 mmol/l.\n\n Due to potential between-lab variation (local assessments), HbA1c is not used as an inclusion criteria in the screening.\n4. Informed consent required\n5. Ethnic group - No restrictions\n6. Smoking - Smoking is allowed, provided subjects have not recently (within 1 month) changed habits. However, smoking status is monitored throughout the study and used as a confounding variable.\n7. Motivation - Motivation and willingness to be randomized to any of the groups and to do his/hers best to follow the given protocol\n8. Other - Able to participate at CID's during normal working hours.\n\nFor children and adolescents:\n\n1. Age 10-18 years\n2. Age-adjusted value corresponding to BMI\\>25 kg/m2 (Cole et al. 2000)\n3. Since the prevalence of pre-diabetes among children with overweight or obesity is low, it is not feasible to include exclusively pre-diabetic children (according to criteria of the IDF).\n\n Therefore, insulin resistant over-weight/obese children will be included, defined as: HOMA-IR ≥ 2.0 for Tanner stage \\> 2. No HOMA criteria is used for Tanner stage 1 and 2.\n4. Informed consent required\n5. Ethnic group - No restrictions\n6. Smoking - Smoking is allowed, provided subjects have not recently (within 1 month) changed habits. However, smoking status is monitored throughout the study and used as a confounding variable.\n7. Motivation - Motivation and willingness to be randomized to any of the groups and to do his/hers best to follow the given protocol\n8. Other - Able to participate at CID's during normal school/working hours.\n\nExclusion Criteria:\n\nBased on interview and/or questionnaire, individuals with the following problems will be excluded:\n\nMedical conditions as known by the subjects:\n\n1. Diabetes mellitus (other than gestational diabetes mellitus);\n2. Significant cardiovascular disease including current angina; myocardial infarction or stroke within the past 6 months; heart failure; symptomatic peripheral vascular disease ;\n3. Systolic blood pressure above 160 mmHg and/or diastolic blood pressure above 100 mmHg whether on or off treatment for hypertension. If being treated, no change in drug treatment within last 3 months;\n4. Advanced chronic renal impairment;\n5. Significant liver disease e.g. cirrhosis (fatty liver disease allowed);\n6. Malignancy which is currently active or in remission for less than five years after last treatment (local basal and squamous cell skin cancer allowed);\n7. Active inflammatory bowel disease, celiac disease, chronic pancreatitis or other disorder potentially causing malabsorption;\n8. Previous bariatric surgery;\n9. Chronic respiratory, neurological, musculoskeletal or other disorders where, in the judgement of the investigator, participants would have unacceptable risk or difficulty in complying with the protocol (e.g. physical activity program);\n10. A recent surgical procedure until after full convalescence (investigators judgement);\n11. Transmissible blood-borne diseases e.g. hepatitis B, HIV;\n12. Psychiatric illness (e.g. major depression, bipolar disorder).\n\n Medication:\n13. Use currently or within the previous 3 months of prescription medication that has the potential of affecting body weight or glucose metabolism such as glucocorticoids (but excluding inhaled and topical steroids; bronchodilators are allowed), psychoactive medication, epileptic medication, or weight loss medications (either prescription, over the counter or herbal). Low dose antidepressants are allowed if they, in the judgement of the investigator, do not affect weight or participation to the study protocol. Levothyroxine for treatment of hypothyroidism is allowed if the participant has been on a stable dose for at least 3 months.\n\n Personal/Other:\n14. Engagement in competitive sports;\n15. Self-reported weight change of \\>5 % (increase or decrease) within 2 months prior to screening;\n16. Special diets (e.g. vegan, Atkins) within 2 months prior to study start. A lacto-vegetarian diet is allowed;\n17. Severe food intolerance expected to interfere with the study;\n18. Regularly drinking \\> 21 alcoholic units/week (men), or \\> 14 alcoholic units/week (women);\n19. Use of drugs of abuse within the previous 12 months;\n20. Blood donation or transfusion within the past 1 month before baseline or CID's;\n21. Self-reported eating disorders;\n22. Pregnancy or lactation, including plans to become pregnant within the next 36 months.\n23. No access to either phone or Internet (this is necessary when being contacted by the instructor's during the maintenance phase);\n24. Adequate understanding of national language;\n25. Psychological or behavioral problems which, in the judgement of the investigator, would lead to difficulty in complying with the protocol.\n\n Laboratory screening:\n\n If all of the above criteria are satisfied, the participant is eligible for a glucose tolerance test (blood at 0 and 120 mins), and blood glucose concentrations are analyzed immediately (Haemocue). In addition full blood count, urea, and electrolytes may be analyzed as a further safety evaluation. Having normal (i.e. not prediabetic) glucose concentrations at 0 and 2h of OGTT at any stage of the study is not an exclusion criterion.\n\n ONLY IF the glucose tolerance test meets the entry criteria for the study, the remaining samples are sent to the local laboratory for a safety check, with the following exclusion criteria:\n26. Hemoglobin concentration below local laboratory reference values (i.e. anemia).\n27. Creatinine \\>1.5 times Upper Limit of Normal (local laboratory reference values).\n28. Alanine Transaminase (ALT) and/or Aspartate Transaminase (AST) \\>3 times the Upper Limit of Normal (local laboratory reference values) Or any other significant abnormality on these tests which in the investigators opinion may be clinically significant and require further assessment\n29. Electrocardiography (ECG). Any abnormality which in the opinion of the investigator might indicate undiagnosed cardiac disease requiring further assessment (e.g. significant conduction disorder, arrhythmia, pathological Q waves). This is done in adults 55-70 years of age.\n\n After LCD phase (in adults):\n30. Failure to reach at least 8% weight reduction during the LCD phase. This leads to exclusion from the intervention.\n\nNote:\n\n* The listed inclusion and exclusion criteria are applied at screening;\n* Having normal (i.e. not pre-diabetic) glucose concentrations at 0 and 2 h of OGTT at any stage of the study after screening is not an exclusion criterion"}, 'identificationModule': {'nctId': 'NCT01777893', 'acronym': 'PREVIEW', 'briefTitle': 'Effect of Diet and Physical Activity on Incidence of Type 2 Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'University of Copenhagen'}, 'officialTitle': 'PREVention of Diabetes Through Lifestyle Intervention and Population Studies in Europe and Around the World', 'orgStudyIdInfo': {'id': 'B303'}, 'secondaryIdInfos': [{'id': '312057', 'type': 'OTHER_GRANT', 'domain': 'European Union Seventh Framework Programme (FP7/2007-2013)'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'HP-HI', 'description': 'High protein/ high intensity physical activity', 'interventionNames': ['Behavioral: High protein/ high intensity physical activity (HP-HI)']}, {'type': 'EXPERIMENTAL', 'label': 'HP-MI', 'description': 'High protein/ moderate intensity physical activity', 'interventionNames': ['Behavioral: High protein / moderate intensity physical activity (HP-MI)']}, {'type': 'EXPERIMENTAL', 'label': 'MP-HI', 'description': 'Moderate protein/ high intensity physical activity', 'interventionNames': ['Behavioral: Moderate protein/ high intensity physical activity (MP-HI)']}, {'type': 'EXPERIMENTAL', 'label': 'MP-MI', 'description': 'Moderate protein/ moderate intensity physical activity', 'interventionNames': ['Behavioral: Moderate protein/ moderate intensity physical activity (MP-MI)']}], 'interventions': [{'name': 'High protein/ high intensity physical activity (HP-HI)', 'type': 'BEHAVIORAL', 'description': 'Participants follow a high protein diet and a high intensity physical activity intervention', 'armGroupLabels': ['HP-HI']}, {'name': 'High protein / moderate intensity physical activity (HP-MI)', 'type': 'BEHAVIORAL', 'description': 'Participants follow a high protein diet and moderate intensity physical activity intervention', 'armGroupLabels': ['HP-MI']}, {'name': 'Moderate protein/ high intensity physical activity (MP-HI)', 'type': 'BEHAVIORAL', 'description': 'Participants follow a moderate protein diet and a high intensity physical activity intervention', 'armGroupLabels': ['MP-HI']}, {'name': 'Moderate protein/ moderate intensity physical activity (MP-MI)', 'type': 'BEHAVIORAL', 'description': 'Participants follow a moderate protein diet and moderate intensity physical activity intervention', 'armGroupLabels': ['MP-MI']}]}, 'contactsLocationsModule': {'locations': [{'zip': 'NSW 2006', 'city': 'Sydney', 'country': 'Australia', 'facility': 'University of Sydney', 'geoPoint': {'lat': -33.86785, 'lon': 151.20732}}, {'zip': '1403', 'city': 'Sofia', 'country': 'Bulgaria', 'facility': 'Medical University Sofia', 'geoPoint': {'lat': 42.69751, 'lon': 23.32415}}, {'zip': '1958', 'city': 'Frederiksberg', 'country': 'Denmark', 'facility': 'University of Copenhagen', 'geoPoint': {'lat': 55.67938, 'lon': 12.53463}}, {'zip': '00014', 'city': 'Helsinki', 'country': 'Finland', 'facility': 'University of Helsinki', 'geoPoint': {'lat': 60.16952, 'lon': 24.93545}}, {'zip': '6200', 'city': 'Maastricht', 'country': 'Netherlands', 'facility': 'University of Maastricht', 'geoPoint': {'lat': 50.84833, 'lon': 5.68889}}, {'zip': '1024', 'city': 'Auckland', 'country': 'New Zealand', 'facility': 'University of Auckland', 'geoPoint': {'lat': -36.84853, 'lon': 174.76349}}, {'zip': '31008', 'city': 'Pamplona', 'country': 'Spain', 'facility': 'University of Navarra', 'geoPoint': {'lat': 42.81687, 'lon': -1.64323}}, {'zip': 'NG7 2UH', 'city': 'Nottingham', 'country': 'United Kingdom', 'facility': 'University of Nottingham Medical School', 'geoPoint': {'lat': 52.9536, 'lon': -1.15047}}, {'zip': 'SA1 8EN', 'city': 'Swansea', 'country': 'United Kingdom', 'facility': 'Swansea University', 'geoPoint': {'lat': 51.62079, 'lon': -3.94323}}], 'overallOfficials': [{'name': 'Thomas M Larsen, Ass. Prof.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Copenhagen'}, {'name': 'Mikael Fogelholm, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Helsinki'}, {'name': 'Margriet Westerterp-Plantenga, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Maastricht University'}, {'name': 'Ian Macdonald, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Nottingham Medical School'}, {'name': 'J. Alfredo Martinez, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Navarra'}, {'name': 'Svetoslav Handjiev, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Medical University Sofia'}, {'name': 'Jennie Brand-Miller, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Sydney'}, {'name': 'Sally D. Poppitt, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Auckland, New Zealand'}, {'name': 'Gareth Stratton, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Swansea University'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Anne Birgitte Raben', 'class': 'OTHER'}, 'collaborators': [{'name': 'University of Helsinki', 'class': 'OTHER'}, {'name': 'Maastricht University', 'class': 'OTHER'}, {'name': 'University of Nottingham', 'class': 'OTHER'}, {'name': 'University of Navarra', 'class': 'OTHER'}, {'name': 'Clinical Center of Endocrinology, Medical University, Sofia, Bulgaria', 'class': 'OTHER'}, {'name': 'University of Sydney', 'class': 'OTHER'}, {'name': 'University of Auckland, New Zealand', 'class': 'OTHER'}, {'name': 'University of Stuttgart', 'class': 'OTHER'}, {'name': 'Swansea University', 'class': 'OTHER'}, {'name': 'Cambridge Manufacturing Company Limited', 'class': 'INDUSTRY'}, {'name': 'European Union', 'class': 'OTHER'}, {'name': 'Wageningen University', 'class': 'OTHER'}, {'name': 'Meyers Madhus', 'class': 'UNKNOWN'}, {'name': 'NetUnion SARL', 'class': 'UNKNOWN'}, {'name': 'Terveyden Ja Hyvinvoinnin Laitos', 'class': 'UNKNOWN'}, {'name': 'Laval University', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Professor', 'investigatorFullName': 'Anne Birgitte Raben', 'investigatorAffiliation': 'University of Copenhagen'}}}}