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Background: Lifestyle interventions can prevent type 2 diabetes (T2D) by successfully inducing behavioral changes (eg, avoiding physical inactivity and sedentariness, increasing physical activity and/or healthy eating) that reduce body weight and normalize metabolic levels (eg, HbA1c). For interventions to be successful, it is important to influence “behavioral mechanisms” such as self-efficacy, which motivate behavioral changes. Theory-based expectations of how self-efficacy, chronic stress, and mood changed over time were investigated through a group-based behavior change intervention (PREMIT). At 8 intervention sites, PREMIT was offered by trained primary care providers in 18 group-sessions over a period of 36 months, divided into 4 intervention phases. Adherence to the intervention protocol was assessed. Method: Participants (n = 962) with overweight and prediabetes who had achieved ≥8% weight loss during a diet reduction period and completed the intervention were categorized into 3 groups: infrequent, frequent, or very frequent group sessions attendance. The interactions between participation in the group sessions and changes in self-efficacy, stress, and mood were multivariate tested. Intervention sites were regularly asked where and how they deviated from the intervention protocol. Results: There was no increase in the participants’ self-efficacy in any group. However, the level of self-efficacy was maintained among those who attended the group sessions frequently, while it decreased in the other groups. For all participants, chronic stress and the frequency of attending group sessions were inversely related. Significant differences in mood were found for all groups. All intervention centers reported specific activities, additional to intervention protocol, to promote participation in the group sessions. Conclusions: The results suggest that the behavioral changes sought by trained primary care providers are related to attendance frequency and follow complex trajectories. The findings also suggest that group-based interventions in naturalistic primary care settings aimed at preventing T2D require formats and strategies that encourage participants to attend group sessions regularly.

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.

Abstract 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

Abstract Background Physical activity, sedentary time and sleep have been shown to be associated with cardio-metabolic health. However, these associations are typically studied in isolation or without accounting for the effect of all movement behaviours and the constrained nature of data that comprise a finite whole such as a 24 h day. The aim of this study was to examine the associations between the composition of daily movement behaviours (including sleep, sedentary time (ST), light intensity physical activity (LIPA) and moderate-to-vigorous activity (MVPA)) and cardio-metabolic health, in a cross-sectional analysis of adults with pre-diabetes. Further, we quantified the predicted differences following reallocation of time between behaviours. Methods Accelerometers were used to quantify daily movement behaviours in 1462 adults from eight countries with a body mass index (BMI) ≥25 kg·m− 2, impaired fasting glucose (IFG; 5.6–6.9 mmol·l− 1) and/or impaired glucose tolerance (IGT; 7.8–11.0 mmol•l− 1 2 h following oral glucose tolerance test, OGTT). Compositional isotemporal substitution was used to estimate the association of reallocating time between behaviours. Results Replacing MVPA with any other behaviour around the mean composition was associated with a poorer cardio-metabolic risk profile. Conversely, when MVPA was increased, the relationships with cardiometabolic risk markers was favourable but with smaller predicted changes than when MVPA was replaced. Further, substituting ST with LIPA predicted improvements in cardio-metabolic risk markers, most notably insulin and HOMA-IR. Conclusions This is the first study to use compositional analysis of the 24 h movement composition in adults with overweight/obesity and pre-diabetes. These findings build on previous literature that suggest replacing ST with LIPA may produce metabolic benefits that contribute to the prevention and management of type 2 diabetes. Furthermore, the asymmetry in the predicted change in risk markers following the reallocation of time to/from MVPA highlights the importance of maintaining existing levels of MVPA. Trial registration ClinicalTrials.gov ( NCT01777893 ).

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.

Dietary protein is effective for body-weight management, in that it promotes satiety, energy expenditure, and changes body-composition in favor of fat-free body mass. With respect to body-weight management, the effects of diets varying in protein differ according to energy balance. During energy restriction, sustaining protein intake at the level of requirement appears to be sufficient to aid body weight loss and fat loss. An additional increase of protein intake does not induce a larger loss of body weight, but can be effective to maintain a larger amount of fat-free mass. Protein induced satiety is likely a combined expression with direct and indirect effects of elevated plasma amino acid and anorexigenic hormone concentrations, increased diet-induced thermogenesis, and ketogenic state, all feed-back on the central nervous system. The decline in energy expenditure and sleeping metabolic rate as a result of body weight loss is less on a high-protein than on a medium-protein diet. In addition, higher rates of energy expenditure have been observed as acute responses to energy-balanced high-protein diets. In energy balance, high protein diets may be beneficial to prevent the development of a positive energy balance, whereas low-protein diets may facilitate this. High protein-low carbohydrate diets may be favorable for the control of intrahepatic triglyceride IHTG in healthy humans, likely as a result of combined effects involving changes in protein and carbohydrate intake. Body weight loss and subsequent weight maintenance usually shows favorable effects in relation to insulin sensitivity, although some risks may be present. Promotion of insulin sensitivity beyond its effect on body-weight loss and subsequent body-weight maintenance seems unlikely. In conclusion, higher-protein diets may reduce overweight and obesity, yet whether high-protein diets, beyond their effect on body-weight management, contribute to prevention of increases in non-alcoholic fatty liver disease NAFLD, type 2 diabetes and cardiovascular diseases is inconclusive.