JUDITH WYLIE-ROSETT, EDD, RD FOR THE DIABETES PREVENTION PROGRAM RESEARCH GROUPOBJECTIVE -Diabetes Prevention Program (DPP) participants randomized to the intensive lifestyle intervention (ILS) had significantly reduced risk of diabetes compared with placebo participants. We explored the contribution of changes in weight, diet, and physical activity on the risk of developing diabetes among ILS participants.RESEARCH DESIGN AND METHODS -For this study, we analyzed one arm of a randomized trial using Cox proportional hazards regression over 3.2 years of follow-up.RESULTS -A total of 1,079 participants were aged 25-84 years (mean 50.6 years, BMI 33.9 kg/m 2 ). Weight loss was the dominant predictor of reduced diabetes incidence (hazard ratio per 5-kg weight loss 0.42 [95% CI 0.35-0.51]; P Ͻ 0.0001). For every kilogram of weight loss, there was a 16% reduction in risk, adjusted for changes in diet and activity. Lower percent of calories from fat and increased physical activity predicted weight loss. Increased physical activity was important to help sustain weight loss. Among 495 participants not meeting the weight loss goal at year 1, those who achieved the physical activity goal had 44% lower diabetes incidence.CONCLUSIONS -Interventions to reduce diabetes risk should primarily target weight reduction. Diabetes Care 29:2102-2107, 2006T he Diabetes Prevention Program (DPP) reported a 58% reduction in the incidence of diabetes over almost 3 years in subjects treated with an intensive lifestyle intervention (ILS) compared with participants treated with placebo (1). The ILS involved changes in diet and physical activity aimed at producing weight loss, but the study did not randomly assign each component of the intervention. However, there was variation in the change in diet, physical activity, and weight loss among ILS participants (2). Thus, we analyzed the relative contributions of changes in diet, physical activity, or weight loss to the reduction in diabetes incidence and assessed the contribution of diet and activity changes on weight loss. This report extends the understanding of how the ILS resulted in lower diabetes incidence (1) by assessing the impact of meeting intervention goals and on the changes in risk factors among individuals randomized to the ILS.RESEARCH DESIGN AND METHODS -The design, methods, recruitment, and characteristics of the DPP participants have been reported elsewhere (3,4). In summary, participants were aged Ն25 years, had a BMI of Ն24 kg/m 2 (Ն22 kg/m 2 in Asian Americans), and had impaired glucose tolerance during an oral glucose tolerance test, based on DPP criteria (5). Participants were excluded if they had diabetes or a number of other conditions or medications. All participants gave written informed consent after approval by the appropriate institutional review board. ILSThe ILS has been described (6). Goals were to reduce weight by 7% from baseline, to achieve and/or maintain at least 150 min per week of moderate physical activity, and to reduce total dietary fat to Ͻ25% of calorie...

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(Figure 2c), and less than 1% of variation for postprandial triglyceride and postprandial C-peptide (Figure 2b and 2d). Gut microbiome (16S rRNA). We estimated the contribution of gut microbiome composition using relative bacterial taxonomic abundances and measures of community diversity and richness, derived from 16S rRNA high-throughput sequencing of baseline stool specimens (Supplemental Table 4). We found that without adjusting for any other individual characteristics the gut microbiome composition explained 7.5% of postprandial triglyceride6h-rise, 6.4% of postprandial glucoseiAUC0-2h and 5.8% of postprandial C-peptide1h-rise. Meal composition, habitual diet and meal context. To determine the impact of the macronutrient composition of meals, we measured triglyceride6h-rise and C-peptide1h-rise for two standardized home phase meals of contrasting macronutrient compositions (for triglyceride, comparison of meals 1 and 7: 85 vs 28g of carbohydrate and 50 vs 40 g of fat at breakfast, both followed by a lunch of 71g carbohydrate and 22g fat; for C-peptide, comparison of meal 2 and 3: 71 vs 41 g of carbohydrate and 22 vs 35 g of fat; Supplement Table 2) in subsets of participants (n=712 and n=186, respectively). GlucoseiAUC0-2h was measured for seven standardized meals (comparison of meals 1, 2, 4, 5, 6, 7 and 8: 28 -95 g carbohydrate; 0 -53 g fat) totalling 9,102 meals in 920 individuals. The proportions of variance explained by meal composition, habitual diet, and by meal context are shown for triglyceride6h-risein Figure 2b, for glucoseiAUC0-2hin Figure 2c, and for C-peptide1h-risein Figure 2d. A multivariate regression model (meals 1, 2, 4, 5, 6, 7 and 8) revealed that the Glucosei AUC0-2h (mmol/L*s) was significantly (P<0.001) reduced by 79, 142 and 185 for every 1g fat, fiber and protein respectively, after adjustment for carbohydrate consumption. Machine learning model. To estimate the unbiased predictive utility of the factors analysed, we used a machine learning approach robust to overfitting 22 . Random Forest regression models 23 were fitted using all the informative features (meal composition, habitual diet, meal context, anthropometry, genetics, microbiome, clinical and biochemical parameters) to predict triglyceride6h10 described in the Methods, we considered not only the effect of the meal macronutrient and energy content in the response (meal composition), but also considered how each individual responded on average to all their set meals relative to the population (individual glucose scaling), as well as the effect of the individual's meal-specific response, the error attributable to the glucose measurement and other sources of variation (including modifiable sources of variation such as sleep, circadian rhythm and exercise). We found that, consistent with the linear models described earlier, the ANOVA models show that there are three meal-related factors explaining individual glycemic responses. Meal macronutrient composition alters iAUC by 16.73% (95%CI 15.37 -18.92%), but the individual glucose...

This report provides a further analysis of the year 4 weight losses in the Look AHEAD (Action for Health in Diabetes) study and identifies factors associated with long-term success. A total of 5145 overweight/obese men and women with type 2 diabetes were randomly assigned to an intensive lifestyle intervention (ILI) or a usual care group, referred to as Diabetes Support and Education (DSE). ILI participants were provided approximately weekly group or individual treatment in year 1; continued but less frequent contact was provided in years 2–4. DSE participants received three group educational sessions in all years. As reported previously, at year 4, ILI participants lost an average of 4.7% of initial weight, compared with 1.1% for DSE (p<0.0001). More ILI than DSE participants lost ≥5% (46% vs 25%, p<0.0001) and ≥10% (23% vs 10%, p<0.0001) of initial weight. Within the ILI, acheivement of both the 5% and 10% categorical weight losses at year 4 was strongly related to meeting these goals at year 1. A total of 887 participants in ILI lost ≥10% at year 1, of whom 374 (42.2%) achieved this loss at year 4. Participants who maintained the loss, compared with those who did not, attended more treatment sessions and reported more favorable physical activity and food intake at year 4. These results provide critical evidence that a comprehensive lifestyle intervention can induce clinically significant weight loss (i.e., ≥5%) in overweight/obese participants with type 2 diabetes and maintain this loss in more than 45% of patients at 4 years.