Aims: To examine the differences between HbA1c and glucose related variables in predicting weight loss and glycaemic changes following 8 weeks of low energy diet (LED) in individuals with overweight and hyperglycaemia. Research design and methods: 2178 individuals with ADA-defined pre-diabetes -impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT) -who started an 8 week LED weight loss diet, were included in this analysis. Participants were enrolled in the PREVIEW (PREVention of diabetes through lifestyle in-terventions and population studies In Europe and around the World) clinical trial. Multivariable linear mixed effects regression models and generalised additive mixed effect logistic models were used. Results: Only 1 in 3 participants (33%) had HbA1c levels defined as pre-diabetes. Neither baseline HbA1c, IFG or IGT were associated with body weight change at 8 weeks. Higher baseline body weight, baseline fasting insulin and weight loss predicted normalisation of fasting plasma glucose (FPG), whilst higher baseline fasting insulin, C-reactive protein (hsCRP) and older age predicted normalisation of HbA1c. Additionally, male sex and higher baseline BMI, body fat and energy intake were positively associated with weight loss, whereas greater age and higher HDL-cholesterol predicted less weight loss. Conclusions: Whilst neither HbA1c nor fasting glucose predicts short-term weight loss success, both may impact the metabolic response to rapid weight loss. We propose a role of inflammation versus total body adiposity since these variables are independent predictors of the normalisation of HbA1c and fasting glucose, respectively.

Project SWEET examined the barriers and facilitators to the use of non-nutritive sweeteners and sweetness enhancers (hereafter "S&SE") alongside potential risks/benefits for health and sustainability. The Beverages trial was a double-blind multi-centre, randomised crossover trial within SWEET evaluating the acute impact of three S&SE blends (plant-based and alternatives) vs. a sucrose control on glycaemic response, food intake, appetite sensations and safety after a carbohydrate-rich breakfast meal. The blends were: mogroside V and stevia RebM; stevia RebA and thaumatin; and sucralose and acesulfame-potassium (ace-K). At each 4h visit, 60 healthy volunteers (53% male; all with overweight/obesity) consumed a 330mL beverage with either an S&SE blend (0kJ) or 8% sucrose (26g, 442kJ), shortly followed by a standardised breakfast (2600 or 1800kJ with 77 or 51g carbohydrates, depending on sex). All blends reduced the 2-h incremental area-under-the-curve (iAUC) for blood insulin (p<0.001 in mixed-effects models), while the stevia RebA and sucralose blends reduced the glucose iAUC (p<0.05) compared with sucrose. Post-prandial levels of triglycerides plus hepatic transaminases did not differ across conditions (p>0.05 for all). Compared with sucrose, there was a 3% increase in LDL-cholesterol after stevia RebA-thaumatin (p<0.001 in adjusted models); and a 2% decrease in HDL-cholesterol after sucralose-ace-K (p<0.01). There was an impact of blend on fullness and desire to eat ratings (both p<0.05) and sucralose-acesulfame K induced higher prospective intake vs sucrose (p<0.001 in adjusted models), but changes were of a small magnitude and did not translate into energy intake differences over the next 24h. Gastro-intestinal symptoms for all beverages were mostly mild. In general, responses to a carbohydrate-rich meal following consumption of S&SE blends with stevia or sucralose were similar to sucrose.

Portion control tableware has been described as a potentially effective approach for weight management, however the mechanisms by which these tools work remain unknown. We explored the processes by which a portion control (calibrated) plate with visual stimuli for starch, protein and vegetable amounts modulates food intake, satiety and meal eating behaviour. Sixty-five women (34 with overweight/obesity) participated in a counterbalanced cross-over trial in the laboratory, where they self-served and ate a hot meal including rice, meatballs and vegetables, once with a calibrated plate and once with a conventional (control) plate. A sub-sample of 31 women provided blood samples to measure the cephalic phase response to the meal. Effects of plate type were tested through linear mixed-effect models. Meal portion sizes (mean ± SD) were smaller for the calibrated compared with the control plate (served: 296 ± 69 vs 317 ± 78 g; consumed: 287 ± 71 vs 309 ± 79 g respectively), especially consumed rice (69 ± 24 vs 88 ± 30 g) (p < 0.05 for all comparisons). The calibrated plate significantly reduced bite size (3.4 ± 1.0 vs 3.7 ± 1.0 g; p < 0.01) in all women and eating rate (32.9 ± 9.5 vs 33.7 ± 9.2 g/min; p < 0.05), in lean women. Despite this, some women compensated for the reduced intake over the 8 h following the meal. Pancreatic polypeptide and ghrelin levels increased post-prandially with the calibrated plate but changes were not robust. Plate type had no influence on insulin, glucose levels, or memory for portion size. Meal size was reduced by a portion control plate with visual stimuli for appropriate amounts of starch, protein and vegetables, potentially because of the reduced self-served portion size and the resulting reduced bite size. Sustained effects may require the continued use of the plate for long-term impact.

The study aimed to evaluate the efficacy of a new nutritional intervention, focused on improving the quality of the diet in children aged 6 to 12 years. A 2-month parallel, controlled randomized trial was conducted in the Spanish child population. The children were randomized to ALINFA nutritional intervention, which consisted of a normocaloric diet that incorporates products, ready-to-eat meals and healthy recipes specifically designed for the study, or a control group, which received the usual advice on healthy eating. The change in diet quality was assessed through the Kidmed index. The secondary outcomes were anthropometry, glucose and lipid profiles, inflammation markers, dietary intake and lifestyle. The participants in the intervention group showed an increase in the mean score of the Kidmed index (p < 0.001). Alongside that, these children decreased their intake of calories (p = 0.046), and total and saturated fat (p = 0.016//p = 0.011), and increased fiber intake (p < 0.001). Likewise, the children in the ALINFA group increased the intake of white fish (p = 0.001), pulses (p = 0.004), whole grains (p < 0.001) and nuts (p < 0.001), and decreased fatty meat (p = 0.014), refined grain (p = 0.008), pastry (p < 0.001), fast food (p < 0.001) and sugar (p = 0.001) intake. Moreover, these children had a significantly decreased BMI (p < 0.001), BMI z-score (p < 0.001), waist circumference (p = 0.016) and fat mass (p = 0.011), as well as leptin (p = 0.004). Participants in the control group did not report significant changes in diet quality. In conclusion, ALINFA nutritional intervention is possibly a useful strategy to increase the diet quality in children, which is associated to improvements in the nutritional status. These results highlight the importance of developing well-designed nutritional interventions.

IntroductionIntake of free sugars in European countries is high and attempts to reduce sugar intake have been mostly ineffective. Non-nutritive sweeteners and sweetness enhancers (S&SEs) can maintain sweet taste in the absence of energy, but little is known about the impact of acute and repeated consumption of S&SE in foods on appetite. This study aims to evaluate the effect of acute and repeated consumption of two individual S&SEs and two S&SE blends in semisolid and solid foods on appetite and related behavioural, metabolic and health outcomes.Methods and analysisA work package of the SWEET Project; this study consists of five double-blind randomised cross-over trials which will be carried out at five sites across four European countries, aiming to have n=213. Five food matrices will be tested across three formulations (sucrose-sweetened control vs two reformulated products with S&SE blends and no added sugar). Participants (body mass index 25-35kg/m(2); aged 18-60 years) will consume each formulation for 14 days. The primary endpoint is composite appetite score (hunger, inverse of fullness, desire to eat and prospective food consumption) over a 3-hour postprandial incremental area under the curve during clinical investigation days on days 1 and 14.Ethics and disseminationThe trial has been approved by national ethical committees and will be conducted in accordance with the Declaration of Helsinki. Results will be published in international peer-reviewed open-access scientific journals. Research data from the trial will be deposited in an open-access online research data archive.Trial registration numberNCT04633681.

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<0.001). After the WM intervention, older adults lost more fat-free mass and bone mass and had smaller improvements in 2 h plasma glucose (adjusted difference for older vs younger adults 0.65 mmol/l [95% CI 0.50, 0.80], p<0.001) and systolic blood pressure (adjusted difference for older vs younger adults 2.57 mmHg [95% CI 1.37, 3.77], p<0.001) than younger adults. Older adults had smaller decreases in fasting and 2 h glucose, HbA(1c) and systolic blood pressure after the WM intervention than middle-aged adults. In the complete case analysis, the above-mentioned differences between middle-aged and older adults disappeared, but the direction of the effect size did not change. After the WL period, compared with men, women had less weight loss (adjusted difference for women vs men 1.78% [95% CI 1.12, 2.43], p<0.001) with greater fat-free mass and bone mass loss and smaller improvements in HbA(1c), LDL-cholesterol and diastolic blood pressure. After the WM intervention, women had greater fat-free mass and bone mass loss and smaller improvements in HbA(1c) and LDL-cholesterol, while they had greater improvements in fasting glucose, triacylglycerol (adjusted difference for women vs men -0.08 mmol/l [-0.11, -0.04], p<0.001) and HDL-cholesterol. Conclusions/interpretation Older adults benefited less from a lifestyle intervention in relation to body composition and cardiometabolic health markers than younger adults, despite greater sustained weight loss. Women benefited less from a LED followed by a lifestyle intervention in relation to body weight and body composition than men. Future interventions targeting older adults or women should take prevention of fat-free mass and bone mass loss into consideration.

Background & aims: Low-energy diet replacement is an effective tool to induce large and rapid weight loss and improve metabolic health, but in the long-term individuals often experience significant weight regain. Little is known about the role of animal-based foods in weight maintenance and metabolic health. We aimed to examine longitudinal associations of animal-based foods with weight maintenance and glycaemic and cardiometabolic risk factors. We also modelled replacement of processed meat with other high-protein foods. Methods: In this secondary analysis, longitudinal data were analysed from 688 adults (26-70 years) with overweight and prediabetes after 8-week low-energy diet-induced weight loss (>= 8% of initial body weight) in a 3-year, multi-centre, diabetes prevention study (PREVIEW). Animal-based food consumption, including unprocessed red meat, processed red meat, poultry, dairy products, fish and seafood, and eggs, was repeatedly assessed using 4-day food records. Multi-adjusted linear mixed models and isoenergetic substitution models were used to examine the potential associations. Results: The available-case analysis showed that each 10-g increment in processed meat, but not total meat, unprocessed red meat, poultry, dairy products, or eggs, was positively associated with weight regain (0.17 kg . year(-1), 95% CI 0.10, 0.25, P < 0.001) and increments in waist circumference, HbA(1c), and triacylglycerols. The associations of processed meat with HbAic or triacylglycerols disappeared when adjusted for weight change. Fish and seafood consumption was inversely associated with triacylglycerols and triacylglycerol-glucose index, independent of weight change. Modelled replacement of processed meat with isoenergetic (250-300 kJ . day(-1) or 60-72 kcal . day(-1)) dairy, poultry, fish and seafood, grains, or nuts was associated with -0.59 (95% CI -0.77, -0.41), -0.66 (95% CI -0.93, -0.40), -0.58 (95% CI -0.88, -0.27), and -0.69 (95% CI -0.96, -0.41) kg . day(-1) of weight regain, respectively (all P < 0.001) and significant improvements in HbA(1c), and triacylglycerols. Conclusions: Higher intake of processed meat, but not total or unprocessed red meat, poultry, dairy products, or eggs may be associated with greater weight regain and more adverse glycaemic and cardiometabolic risk factors. Replacing processed meat with a wide variety of high-protein foods, including unprocessed red meat, poultry, dairy products, fish, eggs, grains, and nuts, could improve weight maintenance and metabolic health after rapid weight loss.

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. Keywords: Desire to eat; Dietary fiber; Glycemic index; Glycemic load; Hunger; Satiety.

To fully understand the causes and mechanisms involved in overeating and obesity, measures of both cognitive and physiological determinants of eating behavior need to be integrated. Effectively synchronizing behavioral measures such as meal micro-structure (e.g., eating speed), cognitive processing of sensory stimuli, and metabolic parameters, can be complex. However, this step is central to understanding the impact of food interventions on body weight. In this paper, we provide an overview of the existing gaps in eating behavior research and describe the development and validation of a new methodological platform to address some of these issues. As part of a controlled trial, 76 men and women self-served and consumed food from a buffet, using a portion-control plate with visual stimuli for appropriate amounts of main food groups, or a conventional plate, on two different days, in a random order. In both sessions participants completed behavioral and cognitive tests using a novel methodological platform that measured gaze movement (as a proxy for visual attention), eating rate and bite size, memory for portion sizes, subjective appetite and portion-size perceptions. In a sub-sample of women, hormonal secretion in response to the meal was also measured. The novel platform showed a significant improvement in meal micro-structure measures from published data (13 vs. 33% failure rate) and high comparability between an automated gaze mapping protocol vs. manual coding for eye-tracking studies involving an eating test (ICC between methods 0.85; 90% CI 0.74, 0.92). This trial was registered at Clinical Trials.gov with Identifier NCT03610776.

OBJECTIVE To examine whether the effect of a 3-year lifestyle intervention on body weight and cardiometabolic risk factors differs by prediabetes metabolic phenotype. RESEARCH DESIGN AND METHODS This post hoc analysis of the multicenter, randomized trial, PREVention of diabetes through lifestyle interventions and population studies In Europe and around the World (PREVIEW), included 1,510 participants with prediabetes (BMI >= 25 kg . m(-2); defined using oral glucose tolerance tests). Of these, 58% had isolated impaired fasting glucose (iIFG), 6% had isolated impaired glucose tolerance (iIGT), and 36% had IFG+IGT; 73% had normal hemoglobin A(1c) (HbA(1c); <39 mmol . mol(-1)) and 25% had intermediate HbA(1c) (39-47 mmol . mol(-1)). Participants underwent an 8-week diet-induced rapid weight loss, followed by a 148-week lifestyle-based weight maintenance intervention. Linear mixed models adjusted for intervention arm and other confounders were used. RESULTS In the available-case and complete-case analyses, participants with IFG+IGT had greater sustained weight loss after lifestyle intervention (adjusted mean at 156 weeks -3.5% [95% CI, -4.7%, -2.3%]) than those with iIFG (mean -2.5% [-3.6%, -1.3%]) relative to baseline (P = 0.011). Participants with IFG+IGT and iIFG had similar cardiometabolic benefits from the lifestyle intervention. The differences in cardiometabolic benefits between those with iIGT and IFG+IGT were minor or inconsistent in different analyses. Participants with normal versus intermediate HbA(1c) had similar weight loss over 3 years and minor differences in cardiometabolic benefits during weight loss, whereas those with normal HbA(1c) had greater improvements in fasting glucose, 2-h glucose (adjusted between-group difference at 156 weeks -0.54 mmol . L-1 [95% CI -0.70, -0.39], P < 0.001), and triglycerides (difference -0.07 mmol . L-1 [-0.11, -0.03], P < 0.001) during the lifestyle intervention. CONCLUSIONS Individuals with iIFG and IFG+IGT had similar improvements in cardiometabolic health from a lifestyle intervention. Those with normal HbA(1c) had greater improvements than those with intermediate HbA(1c).