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Funding: Open Access funding provided by University of Helsinki including Helsinki University Central Hospital. This research was supported by the EU Seventh Framework Programme (FP7; 2007– 2013) (grant no. 312057); National Health and Medical Research Council (EU Collaborative Grant AUS 8, ID 1067711); Glycemic Diabetologia Index Foundation Australia through royalties to the University of Sydney; Health Research Council of New Zealand (grant no. 14/191) and University of Auckland Faculty Research Development Fund; Cambridge Weight Plan, which donated all products for the 8 week weight loss period; Danish Agriculture & Food Council; Danish Meat Research Institute; National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK); Biotechnology and Biological Sciences Research Council (BBSRC) (UK); Engineering and Physical Sciences Research Council (EPSRC) (UK); Nutritics (Dublin), which donated all dietary analysis software used by the University of Nottingham; Juho Vainio Foundation (Finland); Academy of Finland (grant nos 272376, 314383, 266286 and 314135); Finnish Medical Foundation; Gyllenberg Foundation (Finland); Novo Nordisk Foundation; Finnish Diabetes Research Foundation; University of Helsinki; Government Research Funds for Helsinki University Hospital; Jenny and Antti Wihuri Foundation (Finland); Emil Aaltonen Foundation (Finland); and China Scholarship Council. The funders were not involved in the design of the study, the collection, analysis and interpretation of the data or writing of the report and did not impose any restrictions regarding the publication of the report. AIMS/HYPOTHESIS: Lifestyle interventions are the first-line treatment option for body weight and cardiometabolic health management. However, whether age groups or women and men respond differently to lifestyle interventions is under debate. We aimed to examine age- and sex-specific effects of a low-energy diet (LED) followed by a long-term lifestyle intervention on body weight, body composition and cardiometabolic health markers in adults with prediabetes (i.e. impaired fasting glucose and/or impaired glucose tolerance). METHODS: This observational study used longitudinal data from 2223 overweight participants with prediabetes in the multicentre diabetes prevention study PREVIEW. The participants underwent a LED-induced rapid weight loss (WL) period followed by a 3 year lifestyle-based weight maintenance (WM) intervention. Changes in outcomes of interest in prespecified age (younger: 25-45 years; middle-aged: 46-54 years; older: 55-70 years) or sex (women and men) groups were compared. RESULTS: In total, 783 younger, 319 middle-aged and 1121 older adults and 1503 women and 720 men were included in the analysis. In the available case and complete case analyses, multivariable-adjusted linear mixed models showed that younger and older adults had similar weight loss after the LED, whereas older adults had greater sustained weight loss after the WM intervention (adjusted difference for older vs younger adults -1.25% [95% CI -1.92, -0.58], p

3706738). The Cambridge Weight Plan® (Northants, UK) kindly donated all low-energy diet products. This study was also supported by grants from the University of Helsinki, the Mary and Georg Ehnrooth Foundation and the Otto A. Malm Foundation. BACKGROUND: Low-energy diets (LEDs) comprise commercially formulated food products that provide between 800 and 1200 kcal/day (3.3-5 MJ/day) to aid body weight loss. Recent small-scale studies suggest that LEDs are associated with marked changes in the gut microbiota that may modify the effect of the LED on host metabolism and weight loss. We investigated how the gut microbiota changed during 8 weeks of total meal replacement LED and determined their associations with host response in a sub-analysis of 211 overweight adults with pre-diabetes participating in the large multicentre PREVIEW (PREVention of diabetes through lifestyle intervention and population studies In Europe and around the World) clinical trial. METHODS: Microbial community composition was analysed by Illumina sequencing of the hypervariable V3-V4 regions of the 16S ribosomal RNA (rRNA) gene. Butyrate production capacity was estimated by qPCR targeting the butyryl-CoA:acetate CoA-transferase gene. Bioinformatics and statistical analyses, such as comparison of alpha and beta diversity measures, correlative and differential abundances analysis, were undertaken on the 16S rRNA gene sequences of 211 paired (pre- and post-LED) samples as well as their integration with the clinical, biomedical and dietary datasets for predictive modelling. RESULTS: The overall composition of the gut microbiota changed markedly and consistently from pre- to post-LED (P = 0.001), along with increased richness and diversity (both P < 0.001). Following the intervention, the relative abundance of several genera previously associated with metabolic improvements (e.g., Akkermansia and Christensenellaceae R-7 group) was significantly increased (P < 0.001), while flagellated Pseudobutyrivibrio, acetogenic Blautia and Bifidobacterium spp. were decreased (all P < 0.001). Butyrate production capacity was reduced (P < 0.001). The changes in microbiota composition and predicted functions were significantly associated with body weight loss (P < 0.05). Baseline gut microbiota features were able to explain ~25% of variation in total body fat change (post-pre-LED). CONCLUSIONS: The gut microbiota and individual taxa were significantly influenced by the LED intervention and correlated with changes in total body fat and body weight in individuals with overweight and pre-diabetes. Despite inter-individual variation, the baseline gut microbiota was a strong predictor of total body fat change during the energy restriction period. TRIAL REGISTRATION: The PREVIEW trial was prospectively registered at ClinicalTrials.gov ( NCT01777893 ) on January 29, 2013. publishersversion published

Additional file 3. PREVIEW study protocol.

Additional file 1. Supplementary Information consisting of eight supporting figures (Figure S1-S8). A short description of the figure and a figure caption for each figure are given within the file.

14/191 ) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-weeks LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376 , 314383 , 266286 , 314135 ), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship Council. The funding sources had no role in the study design and conduct, data analysis, or manuscript preparation. Publisher Copyright: © 2021 The Author(s) Background & aims: The association of quantity and quality of carbohydrate sources with appetite during long-term weight-loss maintenance (WLM) after intentional weight loss (WL) is unclear. We aimed to investigate longitudinal associations of quantity and quality of carbohydrate sources with changes in subjective appetite sensations during WLM. Methods: This secondary analysis evaluated longitudinal data from the 3-year WLM phase of the PREVIEW study, a 2 × 2 factorial (diet–physical activity arms), multi-center, randomized trial. 1279 individuals with overweight or obesity and prediabetes (25–70 years; BMI≥25 kg m−2) were included. Individuals were merged into 1 group to assess longitudinal associations of yearly changes in appetite sensations. Quantity and quality of carbohydrate sources including total carbohydrate, glycemic index (GI), glycemic load (GL), and total dietary fiber were assessed via 4-day food diaries at 4 timepoints (26, 52, 104, and 156 weeks) during WLM. Visual analog scales were used to assess appetite sensations in the previous week. Results: During WLM, participants consumed on average 160.6 (25th, 75th percentiles 131.1, 195.8) g·day−1 of total carbohydrate, with GI 53.8 (48.7, 58.8) and GL 85.3 (67.2, 108.9) g day−1, and 22.3 (17.6, 27.3) g·day−1 of dietary fiber. In the available-case analysis, multivariable-adjusted linear mixed models with repeated measures showed that each 30-g increment in total carbohydrate was associated with increases in hunger (1.36 mm year−1, 95% CI 0.77, 1.95, P < 0.001), desire to eat (1.10 mm year−1, 0.59, 1.60, P < 0.001), desire to eat something sweet (0.99 mm year−1, 0.30, 1.68, P = 0.005), and weight regain (0.20%·year−1, 0.03, 0.36, P = 0.022). Increasing GI was associated with weight regain, but not associated with increases in appetite sensations. Each 20-unit increment in GL was associated with increases in hunger (0.92 mm year−1, 0.33, 1.51, P = 0.002), desire to eat (1.12 mm year−1, 0.62, 1.62, P < 0.001), desire to eat something sweet (1.13 mm year−1, 0.44, 1.81, P < 0.001), and weight regain (0.35%·year−1, 0.18, 0.52, P < 0.001). Surprisingly, dietary fiber was also associated with increases in desire to eat, after adjustment for carbohydrate or GL. Conclusions: In participants with moderate carbohydrate and dietary fiber intake, and low to moderate GI, we found that higher total carbohydrate, GL, and total fiber, but not GI, were associated with increases in subjective desire to eat or hunger over 3 years. This study was registered as ClinicalTrials.gov, NCT01777893. publishersversion published

Funding Information: The PREVIEW consortium would like to thank all the study participants at all intervention centers for their time and commitment and all scientists, advisors, and students for their dedication and contributions to the study. Specifically, we would like to thank Louise Dye (chairman of the Scientific Advisory Board, SAB), University of Leeds, UK, Richard Atkinson (Ethical Officer of the SAB), Virginia Commonwealth University, USA, and medical expert and consultant Stephen Colagiuri (University of Sydney, Australia). Meyers Madhus A/S is acknowledged for providing training and producing 2 cooking books. Furthermore, we gratefully thank the research staff from each center. From UCPH: Laura Pastor-Sanz, Grith M?ller, Lone Vestergaard Nielsen, Kasper Nowak, Arne Astrup, Finn Sand?-Pedersen, Morten Bo Johansen, Ulla Skovb?ch Pedersen, Maria Roed Andersen, Marianne Juhl Hansen, Jane J?rgensen, Sofie Skov Frost, and Lene Stevner. From HEL: Heikki Tikkanen, Saara Kettunen, Tiia Kunnas, Sanna Ritola, Laura Korpip??, Heini Hyv?rinen, Karoliina Himanen, Tiina Pellinen, Elina Malkam?ki, Heidi Jokinen, Pauliina Kokkonen, Liisi Korhonen, Jaana Valkeap??, Heli Pikkarainen, Martta Nieminen, Tuulia Ingman, Pihla M?kinen, and Sonja Toijonen. From UNOTT: Clare Randall, Nicky Gilbert, Shelley Archer, Sally Maitland, Melanie Marshall, Cheryl Percival, Jakki Pritchard, Laura Helm, and Peter Mansell. From UNAV: Blanca Martinez de Morentin, Maria Hernandez Ruiz de Eguilaz, Salome Perez Diez, Veronica Ciaurriz, Angels Batlle, and Maria Jose Cobo. From MU: Georgi Bogdanov, Pavlina Gateva, Rossica Metodieva, and Galia Dobrevska. From SU: Nils Swindell, Jeff Stephens, Gareth Dunseath, Steve Luzio, and Masoumeh Minou. From THL: Jouko Soundvall, Laura Ram?n, Merja Tukiainen, Ira Greinert, Laura Karjalainen, and Jukka Lauronen. From UNSYD: Fiona Atkinson, Michele Whittle, Jessica Burke, Kylie Simpson, Kimberley Way, Sally McClintock, Radhika Seimon, Shelly Keating, Kirsten Bell, Tania Markovic, Cathy Corry, Evalyn Eldering, and Ian Caterson. From UOA: Lindsay Plank, Nicholas Gant, Jon Woodhead, Anne-Thea McGill, Katya Volkova, Madhavi Bollineni, Clarence Vivar, Kelly Storey, Niamh Brennan, and Audrey Tay. Publisher Copyright: Copyright © 2021 Navas-Carretero, San-Cristobal, Siig Vestentoft, Brand-Miller, Jalo, Westerterp-Plantenga, Simpson, Handjieva-Darlenska, Stratton, Huttunen-Lenz, Lam, Muirhead, Poppitt, Pietiläinen, Adam, Taylor, Handjiev, McNarry, Hansen, Brodie, Silvestre, Macdonald, Boyadjieva, Mackintosh, Schlicht, Liu, Larsen, Fogelholm, Raben and Martinez. Background: Individuals with pre-diabetes are commonly overweight and benefit from dietary and physical activity strategies aimed at decreasing body weight and hyperglycemia. Early insulin resistance can be estimated via the triglyceride glucose index {TyG = Ln [TG (mg/dl) × fasting plasma glucose (FPG) (mg/dl)/2]} and the hypertriglyceridemic-high waist phenotype (TyG-waist), based on TyG x waist circumference (WC) measurements. Both indices may be useful for implementing personalized metabolic management. In this secondary analysis of a randomized controlled trial (RCT), we aimed to determine whether the differences in baseline TyG values and TyG-waist phenotype predicted individual responses to type-2 diabetes (T2D) prevention programs. Methods: The present post-hoc analyses were conducted within the Prevention of Diabetes through Lifestyle intervention and population studies in Europe and around the world (PREVIEW) study completers (n = 899), a multi-center RCT conducted in eight countries (NCT01777893). The study aimed to reduce the incidence of T2D in a population with pre-diabetes during a 3-year randomized intervention with two sequential phases. The first phase was a 2-month weight loss intervention to achieve ≥8% weight loss. The second phase was a 34-month weight loss maintenance intervention with two diets providing different amounts of protein and different glycemic indices, and two physical activity programs with different exercise intensities in a 2 x 2 factorial design. On investigation days, we assessed anthropometrics, glucose/lipid metabolism markers, and diet and exercise questionnaires under standardized procedures. Results: Diabetes-related markers improved during all four lifestyle interventions. Higher baseline TyG index (p < 0.001) was associated with greater reductions in body weight, fasting glucose, and triglyceride (TG), while a high TyG-waist phenotype predicted better TG responses, particularly in those randomized to physical activity (PA) of moderate intensity. Conclusions: Two novel indices of insulin resistance (TyG and TyG-waist) may allow for a more personalized approach to avoiding progression to T2D. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01777893 reference, identifier: NCT01777893. publishersversion published

14/191) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-week LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376, 314383, 266286, 314135), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship Council. Plant-based diets are recommended by dietary guidelines. This secondary analysis aimed to assess longitudinal associations of an overall plant-based diet and specific plant foods with weight-loss maintenance and cardiometabolic risk factors. Longitudinal data on 710 participants (aged 26–70 years) with overweight or obesity and pre-diabetes from the 3-year weight-loss maintenance phase of the PREVIEW intervention were analyzed. Adherence to an overall plant-based diet was evaluated using a novel plant-based diet index, where all plant-based foods received positive scores and all animal-based foods received negative scores. After adjustment for potential confounders, linear mixed models with repeated measures showed that the plant-based diet index was inversely associated with weight regain, but not with cardiometabolic risk factors. Nut intake was inversely associated with regain of weight and fat mass and increments in total cholesterol and LDL cholesterol. Fruit intake was inversely associated with increments in diastolic blood pressure, total cholesterol, and LDL cholesterol. Vegetable intake was inversely associated with an increment in diastolic blood pressure and triglycerides and was positively associated with an increase in HDL cholesterol. All reported associations with cardiometabolic risk factors were independent of weight change. Long-term consumption of nuts, fruits, and vegetables may be beneficial for weight management and cardiometabolic health, whereas an overall plant-based diet may improve weight management only. publishersversion published

14/191) and University of Auckland Faculty Research Development Fund. The Cambridge Weight Plan© donated all products for the 8-weeks LED period. The Danish Agriculture & Food Council. The Danish Meat and Research Institute. National Institute for Health Research Biomedical Research Centre (NIHR BRC) (UK). Engineering and Physical Sciences Research Council (EPSRC) (UK). Nutritics (Dublin) donated all dietary analyses software used by UNOTT. Juho Vainio Foundation (FIN), Academy of Finland (grant numbers: 272376, 314383, 266286, 314135), Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation, Finnish Diabetes Research Foundation, University of Helsinki, Government Research Funds for Helsinki University Hospital (FIN), Jenny and Antti Wihuri Foundation (FIN), Emil Aaltonen Foundation (FIN). China Scholarship .The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.. Background: Previous studies have shown an increase in hunger during weight-loss maintenance (WLM) after diet-induced weight loss. Whether a combination of a higher protein, lower glycemic index (GI) diet and physical activity (PA) can counteract this change remains unclear. Aim: To compare the long-term effects of two diets [high protein (HP)-low GI vs. moderate protein (MP)-moderate GI] and two PA programs [high intensity (HI) vs. moderate intensity (MI)] on subjective appetite sensations during WLM after ≥8% weight loss (WL). Methods: Data derived from the 3-years PREVIEW randomized intervention study. An 8-weeks WL phase using a low-energy diet was followed by a 148-weeks randomized WLM phase. For the WLM phase, participants were assigned to one of the four groups: HP-MI, HP-HI, MP-MI, and MP-HI. Available data from 2,223 participants with overweight or obesity (68% women; BMI ≥ 25 kg/m2). Appetite sensations including satiety, hunger, desire to eat, and desire to eat something sweet during the two phases (at 0, 8 weeks and 26, 52, 104, and 156 weeks) were assessed based on the recall of feelings during the previous week using visual analogue scales. Differences in changes in appetite sensations from baseline between the groups were determined using linear mixed models with repeated measures. Results: There was no significant diet × PA interaction. From 52 weeks onwards, decreases in hunger were significantly greater in HP-low GI than MP-moderate GI (Ptime × diet = 0.018, Pdietgroup = 0.021). Although there was no difference in weight regain between the diet groups (Ptime × diet = 0.630), hunger and satiety ratings correlated with changes in body weight at most timepoints. There were no significant differences in appetite sensations between the two PA groups. Decreases in hunger ratings were greater at 52 and 104 weeks in HP-HI vs. MP-HI, and greater at 104 and 156 weeks in HP-HI vs. MP-MI. Conclusions: This is the first long-term, large-scale randomized intervention to report that a HP-low GI diet was superior in preventing an increase in hunger, but not weight regain, during 3-years WLM compared with a MP-moderate GI diet. Similarly, HP-HI outperformed MP-HI in suppressing hunger. The role of exercise intensity requires further investigation. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT01777893. publishersversion published

© 2020 John Wiley & Sons Ltd Aim: To compare the impact of two long-term weight-maintenance diets, a high protein (HP) and low glycaemic index (GI) diet versus a moderate protein (MP) and moderate GI diet, combined with either high intensity (HI) or moderate intensity physical activity (PA), on the incidence of type 2 diabetes (T2D) after rapid weight loss. Materials and Methods: A 3-year multicentre randomized trial in eight countries using a 2 x 2 diet-by-PA factorial design was conducted. Eight-week weight reduction was followed by a 3-year randomized weight-maintenance phase. In total, 2326 adults (age 25-70 years, body mass index ≥ 25 kg/m2) with prediabetes were enrolled. The primary endpoint was 3-year incidence of T2D analysed by diet treatment. Secondary outcomes included glucose, insulin, HbA1c and body weight. Results: The total number of T2D cases was 62 and the cumulative incidence rate was 3.1%, with no significant differences between the two diets, PA or their combination. T2D incidence was similar across intervention centres, irrespective of attrition. Significantly fewer participants achieved normoglycaemia in the HP compared with the MP group (P

Additional file 2. Participant characteristics.

Additional file 6. Sensitivity analysis of long and short sleepers.

Additional file 3. Variation matrix.

Additional file 4. Comparison of the sample distribution of each DV and predicted values following the reallocation of time from ST to LIPA.

Additional file 1. Data flow chart and covariates.

Additional file 5. Asymmetry of predicted change in outcome variables.