Combining diaries and accelerometers to explain change in physical activity during a lifestyle intervention for adults with pre-diabetes: A PREVIEW sub-study.

Self-report and device-based measures of physical activity (PA) both have unique strengths and limitations; combining these measures should provide complementary and comprehensive insights to PA behaviours. Therefore, we aim to 1) identify PA clusters and clusters of change in PA based on self-reported daily activities and 2) assess differences in device-based PA between clusters in a lifestyle intervention, the PREVIEW diabetes prevention study. In total, 232 participants with overweight and prediabetes (147 women; 55.9 ± 9.5yrs; BMI ≥25 kg·m-2; impaired fasting glucose and/or impaired glucose tolerance) were clustered using a partitioning around medoids algorithm based on self-reported daily activities before a lifestyle intervention and their changes after 6 and 12 months. Device-assessed PA levels (PAL), sedentary time (SED), light PA (LPA), and moderate-to-vigorous PA (MVPA) were assessed using ActiSleep+ accelerometers and compared between clusters using (multivariate) analyses of covariance. At baseline, the self-reported "walking and housework" cluster had significantly higher PAL, MVPA and LPA, and less SED than the "inactive" cluster. LPA was higher only among the "cycling" cluster. There was no difference in the device-based measures between the "social-sports" and "inactive" clusters. Looking at the changes after 6 months, the "increased walking" cluster showed the greatest increase in PAL while the "increased cycling" cluster accumulated the highest amount of LPA. The "increased housework" and "increased supervised sports" reported least favourable changes in device-based PA. After 12 months, there was only minor change in activities between the "increased walking and cycling", "no change" and "increased supervised sports" clusters, with no significant differences in device-based measures. Combining self-report and device-based measures provides better insights into the behaviours that change during an intervention. Walking and cycling may be suitable activities to increase PA in adults with prediabetes.

Role of Eating Behavior and Stress in Maintenance of Dietary Changes During the PREVIEW Intervention.

OBJECTIVE: To examine whether eating behavior and perceived stress predict the maintenance of self-reported dietary change and adherence to dietary instructions during an intervention. DESIGN: A secondary analysis of the behavior maintenance stage (6-36 months) of the 3-year PREVIEW intervention (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World). PARTICIPANTS: Adults (n = 1,311) with overweight and prediabetes at preintervention baseline. VARIABLES MEASURED: Eating behavior (Three-Factor Eating Questionnaire), stress (Perceived Stress Scale), and dietary intake (4-day food records on 4 occasions) were reported. ANALYSIS: Associations between predictors and dietary outcomes were examined with linear mixed-effects models for repeated measurements. RESULTS: Eating behaviors and stress at 6 months did not predict the subsequent change in dietary outcomes, but higher cognitive restraint predicted lower energy intake, and both higher disinhibition and hunger predicted higher energy intake during the following behavior maintenance stage. In addition, higher disinhibition predicted higher saturated fat intake and lower fiber intake, and higher hunger predicted lower fiber intake. Stress was not associated with energy intake or dietary quality. Eating behaviors and stress were not consistently associated with adherence to dietary instructions. CONCLUSIONS AND IMPLICATIONS: Higher cognitive restraint predicted lower energy intake (food quantity), but disinhibition and hunger were also associated with dietary quality.

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).

BACKGROUND: Sedentary lifestyle and unhealthy diet combined with overweight are risk factors for type 2 diabetes (T2D). Lifestyle interventions with weight-loss are effective in T2D-prevention, but unsuccessful completion and chronic stress may hinder efficacy. Determinants of chronic stress and premature cessation at the start of the 3-year PREVIEW study were examined. METHODS: Baseline Quality of Life (QoL), social support, primary care utilization, and mood were examined as predictors of intervention cessation and chronic stress for participants aged 25 to 70 with prediabetes (n = 2,220). Moderating effects of sex and socio-economic status (SES) and independence of predictor variables of BMI were tested. RESULTS: Participants with children, women, and higher SES quitted intervention earlier than those without children, lower SES, and men. Lower QoL, lack of family support, and primary care utilization were associated with cessation. Lower QoL and higher mood disturbances were associated with chronic stress. Predictor variables were independent (p ≤ .001) from BMI, but moderated by sex and SES. CONCLUSIONS: Policy-based strategy in public health should consider how preventive interventions may better accommodate different individual states and life situations, which could influence intervention completion. Intervention designs should enable in-built flexibility in delivery enabling response to individual needs. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01777893.

Associations of obesity phenotypes with weight change, cardiometabolic benefits, and type 2 diabetes incidence during a lifestyle intervention: results from the PREVIEW study.

BACKGROUND/OBJECTIVES: Some individuals with overweight/obesity may be relatively metabolically healthy (MHO) and have a lower risk of cardiovascular disease than those with metabolically unhealthy overweight/obesity (MUO). We aimed to compare changes in body weight and cardiometabolic risk factors and type 2 diabetes incidence during a lifestyle intervention between individuals with MHO vs MUO. METHODS: This post-hoc analysis included 1012 participants with MHO and 1153 participants with MUO at baseline in the randomized trial PREVIEW. Participants underwent an eight-week low-energy diet phase followed by a 148-week lifestyle-based weight-maintenance intervention. Adjusted linear mixed models and Cox proportional hazards regression models were used. RESULTS: There were no statistically significant differences in weight loss (%) between participants with MHO vs MUO over 156 weeks. At the end of the study, weight loss was 2.7% (95% CI, 1.7%-3.6%) in participants with MHO and 3.0% (2.1%-4.0%) in those with MUO. After the low-energy diet phase, participants with MHO had smaller decreases in triglyceride (mean difference between MHO vs MUO 0.08 mmol·L-1 [95% CI, 0.04-0.12]; P < 0.001) but similar reductions in fasting glucose and HOMA-IR than those with MUO. However, at the end of weight maintenance, those with MHO had greater reductions in triglyceride (mean difference -0.08 mmol·L-1 [-0.12--0.04]; P < 0.001), fasting glucose, 2-hour glucose (difference -0.28 mmol·L-1 [-0.41--0.16]; P < 0.001), and HOMA-IR than those with MUO. Participants with MHO had smaller decreases in diastolic blood pressure and HbA1c and greater decreases in HDL cholesterol after weight loss than those with MUO, whereas the statistically significant differences disappeared at the end of weight maintenance. Participants with MHO had lower 3-year type 2 diabetes incidence than those with MUO (adjusted hazard ratio 0.37 [0.20-0.66]; P < 0.001). CONCLUSIONS: Individuals with MUO had greater improvements in some cardiometabolic risk factors during the low-energy diet phase, but had smaller improvements during long-term lifestyle intervention than those with MHO.

Perceived stress as a predictor of eating behavior during the 3-year PREVIEW lifestyle intervention.

BACKGROUND: To better support participants to achieve long-lasting results within interventions aiming for weight loss and maintenance, more information is needed about the maintenance of behavioral changes. Therefore, we examined whether perceived stress predicts the maintenance of changes in eating behavior (flexible and rigid restraint of eating, disinhibition, and hunger). METHODS: The present study was a secondary analysis of the PREVIEW intervention including participants with overweight (BMI ≥ 25 kg/m2) at baseline and high risk of type 2 diabetes (n = 1311). Intervention included a 2-month low-energy diet phase and a 34-month subsequent weight maintenance phase. The first 6 months were considered an active behavior change stage and the remaining 2.5 years were considered a behavior maintenance stage. Eating behavior was measured using the Three Factor Eating Questionnaire and stress using the Perceived Stress Scale. The associations between stress and eating behavior were analyzed using linear mixed effects models for repeated measurements. RESULTS: Perceived stress measured after the active behavior change stage (at 6 months) did not predict changes in eating behavior during the behavior maintenance stage. However, frequent high stress during this period was associated with greater lapse of improved flexible restraint (p = 0.026). The mean (SD) change in flexible restraint from 6 to 36 months was -1.1 (2.1) in participants with frequent stress and -0.7 (1.8) in participants without frequent stress (Cohen's ds (95% CI) = 0.24 (0.04-0.43)). Higher perceived stress at 6 months was associated with less flexible restraint and more disinhibition and hunger throughout the behavior maintenance stage (all p < 0.001). CONCLUSIONS: Perceived stress was associated with features of eating behavior that may impair successful weight loss maintenance. Future interventions should investigate, whether incorporating stress reduction techniques results in more effective treatment, particularly for participants experiencing a high stress level.

Forming new health behavior habits during weight loss maintenance-The PREVIEW study.

INTRODUCTION: Changing lifestyle habits to achieve and maintain weight loss can be effective in prevention of Type II diabetes. Ability to resist temptations is considered one of the key factors in behavior change. This study examined how habit strength, motivation, and temptations for an energy-dense diet developed during the maintenance stage of a behavior modification intervention tool. METHOD: Participants with prediabetes and overweight/obesity were recruited in the two-phase trial PREVIEW with the aim to achieve ≥ 8% body weight loss over 2 months and maintain weight loss over a subsequent 34-month period. The four-stage intervention (PREVIEW Behavior Modification Intervention Toolbox, or PREMIT) supported participants in weight maintenance. Uni- and multivariate analyses were completed from the beginning of the PREMIT maintenance stage (Week 26 of the PREVIEW trial) with 962 individuals who completed the trial. RESULTS: Habit strength and ability to resist temptations increased during the early PREMIT adherence stage (Weeks 26 to 52) before plateauing during middle (Weeks 52 to 104) and late (Weeks 104 to 156) PREMIT adherence stages. Higher habit strength for energy-dense diet was significantly associated with larger weight regain (p ≤ .007). No changes in motivation or interactions with PREMIT attendance were observed. DISCUSSION: Changing diet habits is a complex, multifactorial process, with participants struggling at least with some aspects of weight maintenance. Habits against consuming energy-dense, sweet, and fatty food appeared effective in protecting against weight regain. The observed effect sizes were small, reflecting the complexity of breaking old habits and forming new ones to support long-term maintenance of weight loss. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Does the Effect of a 3-Year Lifestyle Intervention on Body Weight and Cardiometabolic Health Differ by Prediabetes Metabolic Phenotype? A Post Hoc Analysis of the PREVIEW Study.

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 A1c (HbA1c; <39 mmol ⋅ mol-1) and 25% had intermediate HbA1c (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 HbA1c had similar weight loss over 3 years and minor differences in cardiometabolic benefits during weight loss, whereas those with normal HbA1c 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 HbA1c had greater improvements than those with intermediate HbA1c.

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.

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, HbA1c 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 HbA1c, LDL-cholesterol and diastolic blood pressure. After the WM intervention, women had greater fat-free mass and bone mass loss and smaller improvements in HbA1c 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. CLINICAL TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT01777893.

Animal-based food choice and associations with long-term weight maintenance and metabolic health after a large and rapid weight loss: The PREVIEW study.

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, HbA1c, and triacylglycerols. The associations of processed meat with HbA1c 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·year-1 of weight regain, respectively (all P < 0.001) and significant improvements in HbA1c, 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. This study was registered as ClinicalTrials.gov, NCT01777893.

Associations of quantity and quality of carbohydrate sources with subjective appetite sensations during 3-year weight-loss maintenance: Results from the PREVIEW intervention study.

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.

What Is the Profile of Overweight Individuals Who Are Unsuccessful Responders to a Low-Energy Diet? A PREVIEW Sub-study.

This study was performed to evaluate the profile of overweight individuals with pre-diabetes enrolled in PREVIEW who were unable to achieve a body weight loss of ≥8% of the baseline value in response to a 2-month low-energy diet (LED). Their baseline profile reflected potential stress-related vulnerability that predicted a reduced response of body weight to a LED programme. The mean daily energy deficit maintained by unsuccessful weight responders of both sexes was less than the estimated level in successful female (656 vs. 1,299 kcal, p < 0.01) and male (815 vs. 1,659 kcal, p < 0.01) responders. Despite this smaller energy deficit, unsuccessful responders displayed less favorable changes in susceptibility to hunger and appetite sensations. They also did not benefit from the intervention regarding the ability to improve sleep quality. In summary, these results show that some individuals display a behavioral vulnerability which may reduce the ability to lose weight in response to a diet-based weight loss program. They also suggest that this vulnerability may be accentuated by a prolonged diet restriction.

Adherence to a Plant-Based Diet and Consumption of Specific Plant Foods-Associations with 3-Year Weight-Loss Maintenance and Cardiometabolic Risk Factors: A Secondary Analysis of the PREVIEW Intervention Study.

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.

Appraisal of Triglyceride-Related Markers as Early Predictors of Metabolic Outcomes in the PREVIEW Lifestyle Intervention: A Controlled Post-hoc Trial.

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.

Corrigendum: 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).

[This corrects the article DOI: 10.3389/fnut.2021.685648.].

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.

BACKGROUND: Observed associations of high-protein diets with changes in insulin resistance are inconclusive. OBJECTIVES: We aimed to assess associations of changes in both reported and estimated protein (PRep; PEst) and energy intake (EIRep; EIEst) with changes in HOMA-IR, glycated hemoglobin (HbA1c), and BMI (in kg/m2), in 1822 decreasing to 833 adults (week 156) with overweight and prediabetes, during the 3-y PREVIEW (PREVention of diabetes through lifestyle intervention and population studies In Europe and around the World) study on weight-loss maintenance. Eating behavior and measurement errors (MEs) of dietary intake were assessed. Thus, observational post hoc analyses were applied. METHODS: Associations of changes in EIEst, EIRep, PEst, and PRep with changes in HOMA-IR, HbA1c, and BMI were determined by linear mixed-model analysis in 2 arms [high-protein-low-glycemic-index (GI) diet and moderate-protein-moderate-GI diet] of the PREVIEW study. EIEst was derived from energy requirement: total energy expenditure = basal metabolic rate × physical activity level; PEst from urinary nitrogen, and urea. MEs were calculated as [(EIEst - EIRep)/EIEst] × 100% and [(PRep - PEst)/PEst] × 100%. Eating behavior was determined using the Three Factor Eating Questionnaire, examining cognitive dietary restraint, disinhibition, and hunger. RESULTS: Increases in PEst and PRep and decreases in EIEst and EIRep were associated with decreases in BMI, but not independently with decreases in HOMA-IR. Increases in PEst and PRep were associated with decreases in HbA1c. PRep and EIRep showed larger changes and stronger associations than PEst and EIEst. Mean ± SD MEs of EIRep and PRep were 38% ± 9% and 14% ± 4%, respectively; ME changes in EIRep and En% PRep were positively associated with changes in BMI and cognitive dietary restraint and inversely with disinhibition and hunger. CONCLUSIONS: During weight-loss maintenance in adults with prediabetes, increase in protein intake and decrease in energy intake were not associated with decrease in HOMA-IR beyond associations with decrease in BMI. Increases in PEst and PRep were associated with decrease in HbA1c.This trial was registered at clinicaltrials.gov as NCT01777893.

Association of Psychobehavioral Variables With HOMA-IR and BMI Differs for Men and Women With Prediabetes in the PREVIEW Lifestyle Intervention.

OBJECTIVE: Stress, sleep, eating behavior, and physical activity are associated with weight change and insulin resistance (IR). The aim of this analysis was the assessment of the overall and sex-specific associations of psychobehavioral variables throughout the 3-year PREVIEW intervention using the homeostatic model assessment of IR (HOMA-IR), BMI, and length of time in the study. RESEARCH DESIGN AND METHODS: Associations of psychobehavioral variables, including stress, mood, eating behavior, physical activity (PA), and sleep, with BMI, HOMA-IR, and time spent in the study were assessed in 2,184 participants with prediabetes and overweight/obesity (n = 706 men; n = 1,478 women) during a 3-year lifestyle intervention using linear mixed modeling and general linear modeling. The study was a randomized multicenter trial using a 2 × 2 diet-by-PA design. RESULTS: Overall, cognitive restraint and PA increased during the intervention compared with baseline, whereas BMI, HOMA-IR, disinhibition, hunger, and sleepiness decreased (all P < 0.05). Cognitive restraint and PA were negatively, whereas disinhibition, hunger, stress, and total mood disturbance were positively, associated with both BMI and HOMA-IR. Sleep duration, low sleep quality, total mood disturbance, disinhibition, and hunger scores were positively associated with HOMA-IR for men only. Participants who dropped out at 6 months had higher stress and total mood disturbance scores at baseline and throughout their time spent in the study compared with study completers. CONCLUSIONS: Eating behavior and PA, control of stress, mood disturbance, and sleep characteristics were associated with BMI, HOMA-IR, and time spent in the study, with different effects in men and women during the PREVIEW lifestyle intervention study.

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).

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 (P time × diet = 0.018, P dietgroup = 0.021). Although there was no difference in weight regain between the diet groups (P time × 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.

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.

OBJECTIVE: To examine longitudinal and dose-dependent associations of dietary glycemic index (GI), glycemic load (GL), and fiber with body weight and glycemic status during 3-year weight loss maintenance (WLM) in adults at high risk of type 2 diabetes. RESEARCH DESIGN AND METHODS: In this secondary analysis we used pooled data from the PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) randomized controlled trial, which was designed to test the effects of four diet and physical activity interventions. A total of 1,279 participants with overweight or obesity (age 25-70 years and BMI ≥25 kg ⋅ m-2) and prediabetes at baseline were included. We used multiadjusted linear mixed models with repeated measurements to assess longitudinal and dose-dependent associations by merging the participants into one group and dividing them into GI, GL, and fiber tertiles, respectively. RESULTS: In the available-case analysis, each 10-unit increment in GI was associated with a greater regain of weight (0.46 kg ⋅ year-1; 95% CI 0.23, 0.68; P < 0.001) and increase in HbA1c. Each 20-unit increment in GL was associated with a greater regain of weight (0.49 kg ⋅ year-1; 0.24, 0.75; P < 0.001) and increase in HbA1c. The associations of GI and GL with HbA1c were independent of weight change. Compared with those in the lowest tertiles, participants in the highest GI and GL tertiles had significantly greater weight regain and increases in HbA1c. Fiber was inversely associated with increases in waist circumference, but the associations with weight regain and glycemic status did not remain robust in different analyses. CONCLUSIONS: Dietary GI and GL were positively associated with weight regain and deteriorating glycemic status. Stronger evidence on the role of fiber is needed.

The PREVIEW intervention study: Results from a 3-year randomized 2 x 2 factorial multinational trial investigating the role of protein, glycaemic index and physical activity for prevention of type 2 diabetes.

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 < .0001). At 3 years, normoglycaemia was lowest in HP-HI (11.9%) compared with the other three groups (20.0%-21.0%, P < .05). There were no group differences in body weight change (-11% after 8-week weight reduction; -5% after 3-year weight maintenance) or in other secondary outcomes. CONCLUSIONS: Three-year incidence of T2D was much lower than predicted and did not differ between diets, PA or their combination. Maintaining the target intakes of protein and GI over 3 years was difficult, but the overall protocol combining weight loss, healthy eating and PA was successful in markedly reducing the risk of T2D. This is an important clinically relevant outcome.

Goal achievement and adaptive goal adjustment in a behavioral intervention for participants with prediabetes.

Participants with prediabetes were supported to achieve and maintain weight loss with a stage-based behavior change group program named PREview behavior Modification Intervention Toolbox (PREMIT). The tendency to engage in a process of goal adjustment was examined in relation to PREMIT attendance. Analyses were based on 1857 participants who had achieved ⩾8percent weight loss. Tendency to engage in a process of goal adjustment appeared not to be influenced by PREMIT attendance. Instead, results suggested that when unsure about reaching an intervention goal, participants were more likely to engage in a process of goal adjustment, possibly lessening distress due to potentially unachievable goals, either weight loss or maintenance.