A Review of Recent Evidence from Meal-Based Diet Interventions and Clinical Biomarkers for Improvement of Glucose Regulation

Short-Term Effects of Weight-Loss Meal Replacement Programs with Various Macronutrient Distributions on Gut Microbiome and Metabolic Parameters: A Pilot Study

It has emerged the gut microbiome is crucially linked to metabolic health and obesity. Macronutrient distribution has been discussed as a key parameter in weight-loss programs, but little is known about its impact on the gut microbiome. We investigated the effects of weight-loss meal replacement programs with different macronutrient ratios on the gut microbiota and metabolic parameters in subjects with overweight and obesity. Three low-calorie meal replacement programs with different ratios of carbohydrates, proteins, and lipids were designed: a balanced diet (Group B, 60:15:30), a high-lipid-low-carbohydrate diet (Group F, 35:20:55), and a protein-enriched diet (Group P, 40:25:35). Sixty overweight or obese participants were provided with the meals twice daily for 3 weeks. In all groups, diet intervention resulted in reduced body weight and BMI. The relative abundance of Bacteroidetes and Firmicutes phyla decreased and increased, respectively, which increased the Firmicutes/Bacteroidetes (F/B) ratio in all subjects, particularly in Groups B and P. Alpha- and beta-diversity were augmented at the phylum level in Group P. In conclusion, short-term interventions with weight-loss meal replacement programs increased butyrate-producing bacteria and the F/B ratio. Moreover, the protein-enriched diet significantly increased alpha- and beta-diversity compared to the balanced diet and the high-lipid-low-carbohydrate diet.

Meal-Based Intervention on Health Promotion in Middle-Aged Women: A Pilot Study

Middle-aged women belong to a risk group for metabolic dysregulation and menopausal symptoms, mainly due to a dramatic hormonal shift. Supplementation with functional compounds or a single nutrient has been dominantly explored as a nutritional approach for improving aging-related health parameters. However, a meal-based approach might be another strategy for promoting the overall health of the target population. This pilot study aimed to develop a meal-based intervention for middle-aged women and to evaluate its potential health benefits. Considering the nutrient intake status of Korean middle-aged women, diets enriched with four major nutrients (isoflavone, omega-3, fiber, and calcium) were designed and provided to forty-nine women aged 50 to 65 with mild levels of menopausal symptoms for 8 weeks. In the post-intervention phase, they showed reduced body weight and body fat, and improved biochemical metabolic parameters with decreased levels of cholesterol, low-density lipoprotein-cholesterol, ApoB, and fasting insulin. Moreover, bone resorption markers and menopause symptoms were lower in the post-intervention phase. In conclusion, the meal-based intervention might be a prominent strategy for overall health promotion in relatively healthy middle-aged women and further investigation is needed to test its efficacy with a randomized controlled study.

Effects of Fruit and Vegetable Polyphenols on the Glycemic Control and Metabolic Parameters in Type 2 Diabetes Mellitus: A Review

The high prevalence of diabetes in recent decades has been associated with lifestyle changes and dietary habits correlated with economic development. Fruits and vegetables are a vital source of nutraceuticals and components of the healthy diet recommended in the medical nutrition therapy for type 2 diabetes mellitus (T2DM) to prevent hyperglycemia and related complications. They are low in calories and rich in dietary fiber, consist of many polyphenols, and are an essential component of a healthy lifestyle. Recently, researchers have developed a significant interest in understanding the effects of polyphenols (flavonoids and non-flavonoids) on blood glucose levels. In this review, the authors summarize the effects of polyphenols commonly found in the fruits and vegetables, such as resveratrol and anthocyanins, on the glycemic control and metabolic parameters, based on human clinical trials. Significant reductions in fasting blood glucose, glycated hemoglobin, and low-density lipoprotein cholesterol levels were reported after resveratrol, anthocyanin, and naringin were administered to patients with prediabetes and diabetes. Decreased insulin levels were observed after resveratrol intervention but not with the other types of polyphenols. These effects of polyphenolic compounds on the glycemic and metabolic parameters might be mediated by multiple pathophysiological mechanisms, such as activating regulator proteins to increase insulin signaling and eventually suppress insulin resistance. The benefits of certain polyphenols on T2DM remain ambiguous; therefore, further studies, especially clinical trials, are required to substantiate the available evidence.

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.

Human postprandial responses to food and potential for precision nutrition

Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866.