scholarly journals Faecalibacterium predicts postprandial glucose control following potatoes in overweight females

2021 ◽  
Author(s):  
Joy Nolte Fong ◽  
Derek Miketinas ◽  
Linda W. Moore ◽  
Duc T. Nguyen ◽  
Edward A. Graviss ◽  
...  
Keyword(s):  
Postprandial Glucose ◽  
Dietary Recommendations ◽  
Glucose Response ◽  
Overweight Women ◽  
Physiological Processes ◽  
Metabolic Outcomes ◽  
Α Diversity ◽  
Dietary Records ◽  
Baseline Characteristics ◽  
Insoluble Fiber

Abstract Background: Individual glycemic responses following dietary intake result from complex physiological processes and can be influenced by physical properties of foods, such as increased resistant starch (RS) from retrogradation of starch upon cooling after cooking. Predictive equations are needed to provide personalized recommendations for those individuals most at risk for poor metabolic outcomes. Methods: Thirty overweight women with no comorbid conditions participated in this randomized crossover trial, in which the women consumed 250g of hot (9.2 g RS) or cold (13.7 g RS) potatoes. Baseline characteristics included demographics, 10-day dietary records, body composition, and the relative abundance (RA) and α-diversity of gut microbiota. Elastic net regression using 5-fold cross-validation predicted postprandial glucose response (PPGR; incremental AUC0-120min) following the potatoes. Results: Thirty participants (29.6 ± 6.0 yrs; BMI 32.8 ± 3.7 kg/m2) participated in this trial. Most women (70%) showed a favorable PPGR to the cold potato. The model explained 32.2% of the variance in iAUC0-120min glucose with the equation: 547.65 x (0 [if cold potato], x 1 [if hot potato]) + (BMI[kg/m2] x 40.66) - (insoluble fiber[g] x 49.35) + (Bacteroides[RA] x 8.69) - (Faecalibacterium[RA] x 73.49) - (Parabacteroides[RA] x 42.08) + (α-diversity x 110.87) + 292.52.Conclusion: This model improves understanding of baseline characteristics that explain interpersonal variation in PPGR following potato intake and offers a tool to optimize dietary recommendations for a commonly consumed food. Larger studies are warranted to expand generalizability and application of the equation. Trial Registration: The National Clinical Trials number is NCT03310476, and this study was registered with clinicaltrials.gov on Oct 16, 2017.

scholarly journals Precision Nutrition Model Predicts Glucose Control of Overweight Females following the Consumption of Potatoes High in Resistant Starch

Nutrients ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 268
Author(s):  
Joy V. Nolte Fong ◽  
Derek Miketinas ◽  
Linda W. Moore ◽  
Duc T. Nguyen ◽  
Edward A. Graviss ◽  
...  
Keyword(s):  
Resistant Starch ◽  
Postprandial Glucose ◽  
Dietary Recommendations ◽  
Glucose Response ◽  
Overweight Women ◽  
Physiological Processes ◽  
Α Diversity ◽  
Dietary Records ◽  
Baseline Characteristics ◽  
Trial Participants

Individual glycemic responses following dietary intake result from complex physiological processes, and can be influenced by physical properties of foods, such as increased resistant starch (RS) from starch retrogradation. Predictive equations are needed to provide personalized dietary recommendations to reduce chronic disease development. Therefore, a precision nutrition model predicting the postprandial glucose response (PPGR) in overweight women following the consumption of potatoes was formulated. Thirty overweight women participated in this randomized crossover trial. Participants consumed 250 g of hot (9.2 g RS) or cold (13.7 g RS) potatoes on two separate occasions. Baseline characteristics included demographics, 10-day dietary records, body composition, and the relative abundance (RA) and α-diversity of gut microbiota. Elastic net regression using 5-fold cross-validation predicted PPGR after potato intake. Most participants (70%) had a favorable PPGR to the cold potato. The model explained 32.2% of the variance in PPGR with the equation: 547.65 × (0 [if cold, high-RS potato], ×1, if hot, low-RS potato]) + (BMI [kg/m2] × 40.66)—(insoluble fiber [g] × 49.35) + (Bacteroides [RA] × 8.69)—(Faecalibacterium [RA] × 73.49)—(Parabacteroides [RA] × 42.08) + (α-diversity × 110.87) + 292.52. This model improves the understanding of baseline characteristics that explain interpersonal variation in PPGR following potato intake and offers a tool to optimize dietary recommendations for a commonly consumed food.

scholarly journals Breakfast Protein Source Does Not Influence Postprandial Appetite Response and Food Intake in Normal Weight and Overweight Young Women

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Christina M. Crowder ◽  
Brianna L. Neumann ◽  
Jamie I. Baum
Keyword(s):  
Metabolic Response ◽  
Postprandial Glucose ◽  
Normal Weight ◽  
Protein Source ◽  
Glucose Response ◽  
Overweight Women ◽  
Lower Glucose ◽  
Dietary Record ◽  
Daily Energy ◽  
The Impact

Breakfasts higher in protein lead to a greater reduction in hunger compared to breakfasts higher in carbohydrate. However, few studies have examined the impact of higher protein breakfasts with differing protein sources. Our objective was to determine if protein source (animal protein (AP) versus plant protein (PP)) influences postprandial metabolic response in participants consuming a high protein breakfast (~30% energy from protein). Normal weight (NW;n=12) and overweight women (OW;n=8) aging 18–36 were recruited to participate. Participants completed two visits in a randomized, cross-over design with one week between visits. Subjects had 15 minutes to consume each breakfast. Blood glucose and appetite were assessed at baseline, 15, 30, 45, 60, and 120 minutes postprandial. Participants kept a 24-hour dietary record for the duration of each test day. No difference was found between NW and OW participants or breakfasts for postprandial appetite responses. AP had a significantly lower glucose response at 30 minutes compared with PP (−11.6%; 127 ± 4 versus 112 ± 4 mg/dL;P<0.05) and a slower return to baseline. There was no difference in daily energy intake between breakfasts. These data suggest that protein source may influence postprandial glucose response without significantly impacting appetite response in breakfast consumers.

The clinical utility of the glycemic index and its application to mixed meals

1991 ◽  
Vol 69 (1) ◽  
pp. 100-107 ◽  
Author(s):  
Clarie B. Hollenbeck ◽  
Ann M. Coulston
Keyword(s):  
Glycemic Index ◽  
Clinical Utility ◽  
Postprandial Glucose ◽  
Dependent Diabetes Mellitus ◽  
Glycemic Response ◽  
Glucose Response ◽  
Number Of Factors ◽  
Carbohydrate Intolerance ◽  
Low Glycemic Index

A classification of carbohydrate-containing foods based on their glycemic response to 50-g carbohydrate portions has recently been developed. The relative glycemic potency of many of these carbohydrate-containing foods have been compared, and these data have been published in the form of a glycemic index. It has been suggested that meals containing low glycemic index foods will result in a lower postprandial glucose response than meals with a higher glycemic index. However, whether or not these data will lead to a clinically useful reduction in postprandial hyperglycemia in individuals with carbohydrate intolerance remains controversial. In this review, we will try to delineate why we believe that the glycemic index, as currently developed, may be a specious issue. In addition, we will briefly discuss a number of factors that may explain the apparent discrepancy in viewpoints on this issue.Key words: glycemic index, noninsulin-dependent diabetes mellitus, glycemic response, dietary carbohydrate.

scholarly journals Can the Sequence of Food Presentation Influence Postprandial Glycaemia? (P10-072-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Christiani Henry ◽  
Lijuan Sun ◽  
Priya Govindharajulu ◽  
Melvin Khee-Shing Leow
Keyword(s):  
Random Order ◽  
Postprandial Glucose ◽  
Food Presentation ◽  
Chinese Adults ◽  
Glycaemic Response ◽  
Glucose Response ◽  
Randomized Controlled ◽  
Funding Sources ◽  
Postprandial Glycaemia ◽  
Different Order

Abstract Objectives The study was to investigate how a rice-based meal composed of rice, vegetable (green leaf) and meat (breast of chicken) when presented in different order of sequence, impacts on postprandial glycaemia. Methods In a randomized controlled crossover trial, sixteen healthy Chinese adults participated in this study (13 males and 3 females). Subjects consumed in random order 5 experimental meals. The 5 test meal were: (1) vegetables first followed by meat and rice (V-MR), (2) meat first followed by vegetables and rice (M-VR), (3) vegetables first, meat second followed by rice (V-M-R), (4) vegetables, meat and rice together (VMR), (5) rice followed by vegetables and meat (R-VM). Vegetable consumed first followed by meat and rice (V-MR), finally vegetable consumed first, followed by meat and followed by rice (V-M-R). Results In comparison to rice consumed first followed by vegetable and meat (R-VM), the overall postprandial glucose response was significantly lower after the consumption of vegetable first, followed by meat and rice (V-MR) or meat first, followed by vegetable and rice (M-VR) or vegetable followed by meat and followed by rice (V-M-R) or vegetable, meat and rice consumed together (VMR). The insulin iAUC (0–60) was significantly lower after V-M-R than M-VR, VMR and R-VM. V-M-R food sequence intake stimulated higher GLP-1 release than other meal sequence. However, GIP response was lower after V-MR and V-M-R than M-VR and R-MR food sequence. Conclusions Food sequence can considerably influence a meals response to glycaemic, insulinaemic and incretin. V-M-R food sequence intake lowered the glycaemic response significantly with an increased stimulation of GLP1. The order of food presentation has a great potential to alter the glycaemic response of rice-based diets. Our results provide a simple but effective way to reduce postprandial glucose and may help prevent the transition from pre-diabetics to diabetics Funding Sources Singapore Institute for Clinical Sciences, A*STAR, Singapore. Supporting Tables, Images and/or Graphs

scholarly journals Nutrient Extraction Lowers Postprandial Glucose Response of Fruit in Adults with Obesity as well as Healthy Weight Adults

Nutrients ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 766
Author(s):  
Rabab Alkutbe ◽  
Kathy Redfern ◽  
Michael Jarvis ◽  
Gail Rees
Keyword(s):  
Fruit Juice ◽  
Disease Risk ◽  
Risk Group ◽  
Postprandial Glucose ◽  
Glycemic Response ◽  
Healthy Weight ◽  
Glucose Response ◽  
Eating Fruit ◽  
Nutrient Extraction

Fruit consumption is recommended as part of a healthy diet. However, consumption of fruit in the form of juice is positively associated with type 2 diabetes risk, possibly due to resulting hyperglycemia. In a recent study, fruit juice prepared by nutrient extraction, a process that retains the fiber component, was shown to elicit a favorable glycemic index (GI), compared to eating the fruit whole, in healthy weight adults. The current study expanded on this to include individuals with obesity, and assessed whether the nutrient extraction of seeded fruits reduced GI in a higher disease risk group. Nutrient extraction was shown to significantly lower GI, compared to eating fruit whole, in subjects with obesity (raspberry/mango: 25.43 ± 18.20 vs. 44.85 ± 20.18, p = 0.034 and passion fruit/mango (26.30 ± 25.72 vs. 42.56 ± 20.64, p = 0.044). Similar results were found in those of a healthy weight. In summary, the current study indicates that the nutrient-extraction of raspberries and passionfruit mixed with mango lowers the GI, not only in healthy weight individuals, but also in those with obesity, and supports further investigation into the potential for nutrient extraction to enable increased fruit intake without causing a high glycemic response.

scholarly journals Twenty Minute Moderate-Intensity Post-Dinner Exercise Reduces the Postprandial Glucose Response in Chinese Patients with Type 2 Diabetes

2018 ◽  
Vol 24 ◽  
pp. 7170-7177 ◽  
Author(s):  
Zheng Li ◽  
Yun Hu ◽  
Rengna Yan ◽  
Huiqin Li ◽  
Danfeng Zhang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Postprandial Glucose ◽  
Chinese Patients ◽  
Moderate Intensity ◽  
Glucose Response

scholarly journals Application of n-of-1 Clinical Trials in Personalized Nutrition Research: A Trial Protocol for Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR)

2020 ◽  
Vol 4 (9) ◽  
Author(s):  
Yunyi Tian ◽  
Yue Ma ◽  
Yuanqing Fu ◽  
Ju-Sheng Zheng
Keyword(s):  
Dietary Intervention ◽  
Population Level ◽  
Postprandial Blood Glucose ◽  
Macronutrient Intake ◽  
Dietary Recommendations ◽  
Carbohydrate Diet ◽  
Glucose Response ◽  
Low Carbohydrate Diet ◽  
Nutrition Research ◽  
The Individual

ABSTRACT Personalized dietary recommendations can help with more effective disease prevention. This study aims to investigate the individual postprandial glucose response to diets with diverse macronutrient proportions at both the individual level and population level, and explore the potential of the novel single-patient (n-of-1) trial for personalization of diet. Secondary outcomes include individual phenotypic responses and the effects of dietary ingredients on the composition of gut microbiota. Westlake N-of-1 Trials for Macronutrient Intake is a multiple crossover feeding trial consisting of 3 successive 12-d dietary intervention pairs including a 6-d washout period before each 6-d isocaloric dietary intervention: a 6-d high-fat, low-carbohydrate diet, and a 6-d low-fat, high-carbohydrate diet. The results will help provide personalized dietary recommendations for macronutrients in terms of postprandial blood glucose responses. The proposed n-of-1 trial methods could help in optimizing individual health and advancing health care. This trial was registered with clinicaltrials.gov (NCT04125602).

scholarly journals 3068 Effects of exercise and a very low fat diet in metabolically abnormal obese adults

2019 ◽  
Vol 3 (s1) ◽  
pp. 40-40
Author(s):  
George Schweitzer ◽  
Monica Kearney ◽  
Gordon Smith ◽  
Samuel Klein
Keyword(s):  
Weight Loss ◽  
Insulin Sensitivity ◽  
Exercise Training ◽  
Comparative Trial ◽  
Left Ventricular Diastolic Function ◽  
Postprandial Glucose ◽  
Left Ventricular ◽  
Low Fat ◽  
Glucose Response ◽  
Skeletal Muscle Insulin Sensitivity

OBJECTIVES/SPECIFIC AIMS: People with metabolically abnormal obesity (MAO), defined as those with insulin resistance and high intrahepatic triglyceride, are at high risk for developing type 2 diabetes and cardiovascular disease. Weight loss through reduced energy intake and increased physical activity has profound impacts on improving cardiometabolic function. However, the specific additional effects of exercise training with diet-induced weight loss on metabolic function are equivocal. METHODS/STUDY POPULATION: A comparative trial is ongoing in MAO adults undergoing 8-10% weight loss induced by a very-low fat plant-based (PB) diet with structured exercise training (n=8) compared to the same weight loss induced by the PB diet alone (n=3). RESULTS/ANTICIPATED RESULTS: Preliminary results indicate that, PB diet with or without exercise training results in significant weight loss concomitant with enhanced insulin sensitivity, reduced intrahepatic triglyceride, reduced 24-hour postprandial glucose response, reduced fat mass, and reduced diastolic blood pressure. Those undergoing PB diet with exercise training had greater improvements in muscular strength and cardiorespiratory fitness than those undergoing PB diet alone. Differences between intervention groups for other cardiometabolic measures are not yet known. DISCUSSION/SIGNIFICANCE OF IMPACT: Each of the interventions resulted in improved cardiometabolic measures; however the extent of the differences between the interventions is not yet clear. It is hypothesized that compared with weight loss induced by a PB diet, the same weight loss induced by a PB diet and structured exercise training will i) cause greater improvement in skeletal muscle insulin sensitivity, ii) will attenuate the usual decline in muscle mass while increasing strength, and iii) result in greater increases in left ventricular diastolic function. The long-term objective of this proposal is to provide a foundation for future studies evaluating mechanisms for the effects of exercise in cardiometabolic disease prevention and therapy.

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