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.

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.

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.

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.

Weight Loss and Usage of an Online Commercial Weight Loss Program (the CSIRO Total Wellbeing Diet Online) Delivered in an Everyday Context: Five-Year Evaluation in a Community Cohort.

BACKGROUND: Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer-term, sustained weight loss. OBJECTIVE: This study used data from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Total Wellbeing Diet Online program to determine the reach and weight loss results over its first 5 years. METHODS: Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height, weight, and usage data (eg, entries into the food diary, views of the menu, and program content). Weight loss and percentage of starting body weight lost were calculated. Members were divided into 2 groups for analysis: "stayers" were members who signed up for at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program, while "starters" began the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss. RESULTS: Data were available from 59,686 members for analysis. Members were predominately female (48,979/59,686, 82.06%) with an average age of 50 years (SD 12.6). The average starting weight was 90.2 kg (SD 19.7), and over half of all members (34,195/59,688, 57.29%) were classified as obese. At week 12, 94.56% (56,438/59,686) of the members had a paid program membership, which decreased to 41.48% (24,756/59,686) at 24 weeks. At week 12, 52.03% (29,115/55,958) of the remaining members were actively using the platform, and by week 24, 26.59% (14,880/55,958) were using the platform. The average weight loss for all members was 2.8 kg or 3.1% of their starting body weight. Stayers lost 4.9 kg (5.3% of starting body weight) compared to starters, who lost 1.6 kg (1.7% of starting body weight). Almost half (11,082/22,658, 48.91%) the members who stayed on the program lost 5% or more of their starting body weight, and 15.48% (3507/22,658) achieved a weight loss of 10% or more. Of the members who were classified as class 1 obese when they joined the program, 41.39% (3065/7405) who stayed on the program were no longer classified as obese at the end, and across all categories of obesity, 24% (3180/13,319) were no longer classified as obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss (ß=.263; P<.001), with higher usage associated with greater weight loss. CONCLUSIONS: This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant.

Compositional analysis of the associations between 24-h movement behaviours and cardio-metabolic risk factors in overweight and obese adults with pre-diabetes from the PREVIEW study: cross-sectional baseline analysis.

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).

Is there a soft drink vs. alcohol seesaw? A cross-sectional analysis of dietary data in the Australian Health Survey 2011-12.

PURPOSE: Previous studies in older Australians have reported higher alcohol intake in those with low added sugar intake, yet the relationship between energy in liquid form [alcoholic beverages vs. sugar-sweetened beverages (SSB)] and measures of obesity has not been evaluated. We aimed to assess the association between the energy derived from SSB and alcoholic beverages, and to model the association between the substitution of SSB with alcoholic beverages and waist circumference. METHODS: In this cross-sectional analysis, dietary data from the Australian Health Survey 2011-12 were analyzed. Participants with implausible dietary intake were excluded by applying the Goldberg cut-off. Usual SSB intake of adults ≥ 19 years old was estimated using the Multiple Source Method and participants were classified into zero-, low- or high-SSB consumers according to their usual SSB intake. Energy from alcoholic beverages in the three SSB consumption groups was compared using multivariable general linear models. A substitution model was used to assess the association between the replacement of SSB with alcoholic beverages and waist circumference. RESULTS: Zero-SSB consumers made up 33% of the included participants. In all age groups, zero-SSB consumers had significantly higher energy intakes from alcoholic beverages than low- and high-SSB consumers. Low- and high-SSB consumers had similar consumption of alcoholic beverages. Substituting SSB intake with alcoholic beverage intake was not associated with significant differences in waist circumference in most age groups. CONCLUSIONS: Australian adults who avoid SSB are common but consume substantially more energy in the form of alcoholic beverages. An increase in alcoholic beverage intake could be an 'unintended consequence' of strictly discouraging SSB consumption.

Men and women respond differently to rapid weight loss: Metabolic outcomes of a multi-centre intervention study after a low-energy diet in 2500 overweight, individuals with pre-diabetes (PREVIEW).

AIMS: The PREVIEW lifestyle intervention study (ClinicalTrials.gov Identifier: NCT01777893) is, to date, the largest, multinational study concerning prevention of type-2 diabetes. We hypothesized that the initial, fixed low-energy diet (LED) would induce different metabolic outcomes in men vs women. MATERIALS AND METHODS: All participants followed a LED (3.4 MJ/810 kcal/daily) for 8 weeks (Cambridge Weight Plan). Participants were recruited from 8 sites in Europe, Australia and New Zealand. Those eligible for inclusion were overweight (BMI ≥ 25 kg/m2 ) individuals with pre-diabetes according to ADA-criteria. Outcomes of interest included changes in insulin resistance, fat mass (FM), fat-free mass (FFM) and metabolic syndrome Z-score. RESULTS: In total, 2224 individuals (1504 women, 720 men) attended the baseline visit and 2020 (90.8%) completed the follow-up visit. Following the LED, weight loss was 16% greater in men than in women (11.8% vs 10.3%, respectively) but improvements in insulin resistance were similar. HOMA-IR decreased by 1.50 ± 0.15 in men and by 1.35 ± 0.15 in women (ns). After adjusting for differences in weight loss, men had larger reductions in metabolic syndrome Z-score, C-peptide, FM and heart rate, while women had larger reductions in HDL cholesterol, FFM, hip circumference and pulse pressure. Following the LED, 35% of participants of both genders had reverted to normo-glycaemia. CONCLUSIONS: An 8-week LED induced different effects in women than in men. These findings are clinically important and suggest gender-specific changes after weight loss. It is important to investigate whether the greater decreases in FFM, hip circumference and HDL cholesterol in women after rapid weight loss compromise weight loss maintenance and future cardiovascular health.

Demographic and Social-Cognitive Factors Associated with Weight Loss in Overweight, Pre-diabetic Participants of the PREVIEW Study.

PURPOSE: Weight loss has been demonstrated to be a successful strategy in diabetes prevention. Although weight loss is greatly influenced by dietary behaviors, social-cognitive factors play an important role in behavioral determination. This study aimed to identify demographic and social-cognitive factors (intention, self-efficacy, outcome expectancies, social support, and motivation with regard to dietary behavior and goal adjustment) associated with weight loss in overweight and obese participants from the PREVIEW study who had pre-diabetes. METHOD: Prospective correlational data from 1973 adult participants were analyzed. The participants completed psychological questionnaires that assessed social-cognitive variables with regard to dietary behavior. Stepwise multiple regression analyses were performed to identify baseline demographic and social-cognitive factors associated with weight loss. RESULTS: Overall, being male, having a higher baseline BMI, having a higher income, perceiving fewer disadvantages of a healthy diet (outcome expectancies), experiencing less discouragement for healthy eating by family and friends (social support), and lower education were independently linked to greater weight loss. When evaluating females and males separately, education was no longer associated with weight loss. CONCLUSION: The results indicate that a supportive environment in which family members and friends avoid discouraging healthy eating, with the application of a strategy that uses specific behavior change techniques to emphasize the benefits of outcomes, i.e., the benefits of a healthy diet, may support weight loss efforts. Weight loss programs should therefore always address the social environment of persons who try to lose body weight because family members and friends can be important supporters in reaching a weight loss goal.

Influence of dietary insulin scores on survival in colorectal cancer patients.

BACKGROUND: Although hyperinsulinemia is hypothesised to be involved in colorectal carcinogenesis, it remains unclear whether a diet inducing an elevated insulin response influences colorectal cancer (CRC) survival. METHODS: We examined the association of post-diagnosis dietary insulin scores with survival among 2006 patients from two large prospective cohorts who were diagnosed with CRC from 1976 to 2010. Dietary insulin load was calculated as a function of the food insulin index. Dietary insulin index was calculated by dividing insulin load by total energy intake. Cox proportional hazards models were used to calculate hazard ratios (HRs) for CRC-specific mortality and overall mortality, adjusted for other risk factors for cancer survival. RESULTS: The adjusted HRs for CRC-specific mortality comparing the highest to the lowest quintiles were 1.82 (95% CI: 1.20-2.75, Ptrend=0.006) for dietary insulin load and 1.66 (95% CI: 1.10-2.50, Ptrend=0.004) for dietary insulin index. We also observed an increased risk for overall mortality, with adjusted HRs of 1.33 (95% CI: 1.03-1.72, Ptrend=0.03) for dietary insulin load and 1.32 (95% CI: 1.02-1.71, Ptrend=0.02) for dietary insulin index, comparing extreme quintiles. The increase in CRC-specific mortality associated with higher dietary insulin scores was more apparent among patients with body mass index (BMI)⩾25 kg m-2 than BMI<25 kg m-2 (Pinteraction=0.01). CONCLUSIONS: Higher dietary insulin scores after CRC diagnosis were associated with a statistically significant increase in CRC-specific and overall mortality.

A systematic review and metaanalysis of energy intake and weight gain in pregnancy.

BACKGROUND: Gestational weight gain within the recommended range produces optimal pregnancy outcomes, yet many women exceed the guidelines. Official recommendations to increase energy intake by ∼ 1000 kJ/day in pregnancy may be excessive. OBJECTIVE: To determine by metaanalysis of relevant studies whether greater increments in energy intake from early to late pregnancy corresponded to greater or excessive gestational weight gain. DATA SOURCES: We systematically searched electronic databases for observational and intervention studies published from 1990 to the present. The databases included Ovid Medline, Cochrane Library, Excerpta Medica DataBASE (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Science Direct. In addition we hand-searched reference lists of all identified articles. STUDY ELIGIBILITY CRITERIA: Studies were included if they reported gestational weight gain and energy intake in early and late gestation in women of any age with a singleton pregnancy. Search also encompassed journals emerging from both developed and developing countries. STUDY APPRAISAL AND SYNTHESIS METHODS: Studies were individually assessed for quality based on the Quality Criteria Checklist obtained from the Evidence Analysis Manual: Steps in the academy evidence analysis process. Publication bias was plotted by the use of a funnel plot with standard mean difference against standard error. Identified studies were meta-analyzed and stratified by body mass index, study design, dietary methodology, and country status (developed/developing) by the use of a random-effects model. RESULTS: Of 2487 articles screened, 18 studies met inclusion criteria. On average, women gained 12.0 (2.8) kg (standardized mean difference = 1.306, P < .0005) yet reported only a small increment in energy intake that did not reach statistical significance (∼475 kJ/day, standard mean difference = 0.266, P = .016). Irrespective of baseline body mass index, study design, dietary methodology, or country status, changes in energy intake were not significantly correlated to the amount of gestational weight gain (r = 0.321, P = .11). CONCLUSION: Despite rapid physiologic weight gain, women report little or no change in energy intake during pregnancy. Current recommendations to increase energy intake by ∼ 1000 kJ/day may, therefore, encourage excessive weight gain and adverse pregnancy outcomes.

Dietary glycaemic index and glycaemic load among Australian children and adolescents: results from the 2011-2012 Australian Health Survey.

This study aimed to examine the dietary glycaemic index (GI) and glycaemic load (GL) of Australian children and adolescents, as well as the major food groups contributing to GL, in the recent 2011-2012 Australian Health Survey. Plausible food intake data from 1876 children and adolescents (51 % boys), collected using a multiple-pass 24-h recall, were analysed. The GI of foods was assigned based on a step-wise published method using values from common GI databases. Descriptive statistics were calculated for dietary GI, GL and contribution to GL by food groups, stratified by age group and sex. Linear regression was used to test for trends across age groups for BMI, dietary GI and GL, and intakes of energy, nutrients and food groups. Pearson's χ 2 test was used to test for differences between age groups for categorical subject characteristic variables. Mean dietary GI and GL of participants were 55·5 (sd 5·3) and 137·4 (sd 50·8), respectively. The main contributors to dietary GL were starchy foods: breads, cereal-based dishes, breakfast cereals, flours, grains and potatoes accounted for 41 % of total GL. Sweetened beverages, fruit and vegetable juices/drinks, cake-type desserts and sweet biscuits contributed 15 %. No significant difference (at P<0·001) was observed between sexes. In conclusion, Australian children and adolescents appear to consume diets with a lower GI than European children. Exchanging high-GI foods for low-GI alternatives within core and non-core foods may improve diet quality of Australian children and adolescents.

Contributors to dietary glycaemic index and glycaemic load in the Netherlands: the role of beer.

Diets high in glycaemic index (GI) and glycaemic load (GL) have been associated with a higher diabetes risk. Beer explained a large proportion of variation in GI in a Finnish and an American study. However, few beers have been tested according to International Organization for Standardization (ISO) methodology. We tested the GI of beer and estimated its contribution to dietary GI and GL in the Netherlands. GI testing of pilsner beer (Pilsner Urquell) was conducted at The University of Sydney according to ISO international standards with glucose as the reference food. Subsequently, GI and GL values were assigned to 2556 food items in the 2011 Dutch food composition table using a six-step methodology and consulting four databases. This table was linked to dietary data from 2106 adults in the Dutch National Food Consumption Survey 2007-2010. Stepwise linear regression identified contribution to inter-individual variation in dietary GI and GL. The GI of pilsner beer was 89 (SD 5). Beer consumption contributed to 9·6 and 5·3% inter-individual variation in GI and GL, respectively. Other foods that contributed to the inter-individual variation in GI and GL included potatoes, bread, soft drinks, sugar, candy, wine, coffee and tea. The results were more pronounced in men than in women. In conclusion, beer is a high-GI food. Despite its relatively low carbohydrate content (approximately 4-5 g/100 ml), it still made a contribution to dietary GL, especially in men. Next to potatoes, bread, sugar and sugar-sweetened beverages, beer captured a considerable proportion of between-person variability in GI and GL in the Dutch diet.

Effect of a low glycaemic index diet in gestational diabetes mellitus on post-natal outcomes after 3 months of birth: a pilot follow-up study.

A low glycaemic index (LGI) diet during pregnancy complicated by gestational diabetes mellitus (GDM) may offer benefits to the mother and infant pair beyond those during pregnancy. We aimed to investigate the effect of an LGI diet during pregnancy complicated with GDM on early post-natal outcomes. Fifty-eight women (age: 23-41 years; mean ± SD pre-pregnancy body mass index: 24.5 ± 5.6 kg m(-2) ) who had GDM and followed either an LGI diet (n = 33) or a conventional high-fibre diet (HF; n = 25) during pregnancy had a 75-g oral glucose tolerance test and blood lipid tests at 3 months post-partum. Anthropometric assessments were conducted for 55 mother-infant pairs. The glycaemic index of the antenatal diets differed modestly (mean ± SD: 46.8 ± 5.4 vs. 52.4 ± 4.4; P < 0.001), but there were no significant differences in any of the post-natal outcomes. In conclusion, an LGI diet during pregnancy complicated by GDM has outcomes similar to those of a conventional healthy diet. Adequately powered studies should explore the potential beneficial effects of LGI diet on risk factors for chronic disease.

Discovery of a low-glycaemic index potato and relationship with starch digestion in vitro.

Potatoes are usually a high-glycaemic index (GI) food. Finding a low-GI potato and developing a screening method for finding low-GI cultivars are both health and agricultural priorities. The aims of the present study were to screen the commonly used and newly introduced cultivars of potatoes, in a bid to discover a low-GI potato, and to describe the relationship between in vitro starch digestibility of cooked potatoes and their in vivo glycaemic response. According to International Standard Organisation (ISO) guidelines, seven different potato cultivars were tested for their GI. In vitro enzymatic starch hydrolysis and chemical analyses, including amylose content analysis, were carried out for each potato cultivar, and correlations with the respective GI values were sought. The potato cultivars had a wide range of GI values (53-103). The Carisma cultivar was classified as low GI and the Nicola cultivar (GI = 69) as medium GI and the other five cultivars were classified as high GI according to ISO guidelines. The GI values were strongly and positively correlated with the percentage of in vitro enzymatic hydrolysis of starch in the cooked potatoes, particularly with the hydrolysis percentage at 120 min (r 0·91 and P <0·01). Amylose, dietary fibre and total starch content was not correlated with either in vitro starch digestibility or GI. The findings suggest that low-GI potato cultivars can be identified by screening using a high-throughput in vitro digestion procedure, while chemical composition, including amylose and fibre content, is not indicative.

Dose-response effect of a novel functional fibre, PolyGlycopleX(®), PGX(®), on satiety.

The objective of this research was to determine the dose-response effects of a palatable, viscous and gel forming fibre, PolyGlycopleX(®) (PGX(®)), [(α-D-glucurono-α-manno-ß-D-manno-ß-D-gluco), (α-Lgulurono-ß-D mannurono), (ß-D-gluco-ß-D-mannan)] on satiety, and to gain insight into the underlying mechanisms that lead to appetite inhibition. Healthy subjects (n = 10), aged between 20.3 and 29.2 years, consumed PGX(®), in granular form at 2.5, 5.0 and 7.5 g, and a 5g inulin control, with a standard breakfast. The PGX(®) doses of 2.5 and 7.5 g mixed with water at the start of breakfast increased satiety (iAUC of 140.0 and 157.7, P = 0.025 and 0.001, respectively) compared to the control. The most effective dose (7.5g) was palatable and corresponded to a 34% increase in fullness, measured using a visual analogue scale and incremental area under the curve, and resulted in a delayed postprandial glycaemic response when compared with the control.

Hybrid Evaluation of a Lifestyle Change Program to Prevent the Development of Type 2 Diabetes Among Individuals With Prediabetes: Intended and Observed Changes in Intervening Mechanisms.

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.

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.