Timing and Nutrient Type of Isocaloric Snacks Impacted Postprandial Glycemic and Insulinemic Responses of the Subsequent Meal in Healthy Subjects.

The aim of the study was to explore the impact of both the macronutrient composition and snacking timing on the postprandial glycemic insulinemic responses and food intake. Seventeen healthy female volunteers completed the randomized crossover trials. The volunteers were provided a standard breakfast and lunch at 8:00 and 13:00, respectively, and an ad libitum dinner at 18:00. Provided at either 10:30 (midmorning) or 12:30 (preload), the glycemic effects of the three types of 70 kcal snacks, including chicken breast (mid-C and pre-C), apple (mid-A and pre-A), and macadamia nut (mid-M and pre-M), were compared with the non-snack control (CON), evaluated by continuous glucose monitoring (CGM). The mid-M showed increased insulin resistance after lunch compared with CON, while the pre-M did not. The pre-A stabilized the glycemic response in terms of all variability parameters after lunch, while the mid-A had no significant effect on postprandial glucose control. Both the mid-C and pre-C improved the total area under the glucose curve, all glycemic variability parameters, and the insulin resistance within 2 h after lunch compared with CON. The pre-C attained the lowest energy intake at dinner, while the mid-A and the mid-M resulted in the highest. In conclusion, the chicken breast snack effectively stabilized postprandial glycemic excursion and reduced insulin resistance while the macadamia snack did not, regardless of ingestion time. Only as a preload could the apple snack mitigate the glucose response after the subsequent meal.

Apple preload increased postprandial insulin sensitivity of a high glycemic rice meal only at breakfast.

PURPOSE: The possible impact of preload food on insulin sensitivity has yet been reported. This study aimed to investigate the glycemic and insulinemic effect of an apple preload before breakfast, lunch and early supper, based on high glycemic index (GI) rice meals. METHODS: Twenty-three healthy participants in Group 1 and 14 participants in Group 2 were served with the reference meal (white rice containing 50 g of available carbohydrate) or experimental meals (apple preload and rice, each containing 15 and 35 g of available carbohydrate). The meals were either served at 8:00 for breakfast, 12:30 for lunch or 17:00 for early supper to explore the possible effect of time factor. The group 1 assessed the postprandial and subsequent-meal glycemic effect of the test meals by continuous glucose monitoring (CGM), along with subjective appetite; The group 2 further investigated the glycemic and insulin effect by blood collection. RESULTS: The apple preload lowered the blood glucose peak value by 33.5%, 31.4% and 31.0% in breakfast, lunch and supper, respectively, while increased insulin sensitivity by 40.5% only at breakfast, compared with the rice reference. The early supper resulted significantly milder glycemic response than its breakfast and lunch counterparts did. The result of CGM tests was consistent with that of the fingertip blood tests. CONCLUSION: Apple preload performed the best at breakfast in terms of enhancing the insulin sensitivity. The preload treatment could effectively attenuate postprandial GR without increasing the area under insulin response curve in any of the three meals.

The characteristics of postprandial glycemic response patterns to white rice and glucose in healthy adults: Identifying subgroups by clustering analysis.

Objectives: Large interpersonal variability in postprandial glycemic response (PGR) to white rice has been reported, and differences in the PGR patterns during the oral glucose tolerance test (OGTT) have been documented. However, there is scant study on the PGR patterns of white rice. We examined the typical PGR patterns of white rice and glucose and the association between them. Materials and methods: We analyzed the data of 3-h PGRs to white rice (WR) and glucose (G) of 114 normoglycemic female subjects of similar age, weight status, and same ethnic group. Diverse glycemic parameters, based on the discrete blood glucose values, were calculated over 120 and 180 min. K-means clustering based on glycemic parameters calculated over 180 min was applied to identify subgroups and representative PGR patterns. Principal factor analysis based on the parameters used in the cluster analysis was applied to characterize PGR patterns. Simple correspondence analysis was performed on the clustering categories of WR and G. Results: More distinct differences were found in glycemic parameters calculated over 180 min compared with that calculated over 120 min, especially in the negative area under the curve and Nadir. We identified four distinct PGR patterns to WR (WR1, WR2, WR3, and WR4) and G (G1, G2, G3, and G4), respectively. There were significant differences among the patterns regard to postprandial hyperglycemia, hypoglycemic, and glycemic variability. The WR1 clusters had significantly lower glycemic index (59 ± 19), while no difference was found among the glycemic index based on the other three clusters. Each given G subgroup presented multiple patterns of PGR to WR, especially in the largest G subgroup (G1), and in subgroup with the greatest glycemic variability (G3). Conclusion: Multiple subgroups could be classified based on the PGR patterns to white rice and glucose even in seemingly homogeneous subjects. Extending the monitoring time to 180 min was conducive to more effective discrimination of PGR patterns. It may not be reliable to extrapolate the patterns of PGR to rice from that to glucose, suggesting a need of combining OGTT and meal tolerance test for individualized glycemic management.

Extended Inter-Meal Interval Negatively Impacted the Glycemic and Insulinemic Responses after Both Lunch and Dinner in Healthy Subjects.

This study aimed to investigate the glycemic and insulinemic effects of lunch timing based on a fixed feeding window, and the effects of apple preload on postprandial glucose and insulin responses after nutrient-balanced lunch and the subsequent high-fat dinner in healthy participants. Twenty-six participants completed four randomized, crossover experimental trials: (1) early standardized lunch at 12:00 (12S); (2) apple preload to 12S (12A+S); (3) late standardized lunch at 14:00 (14S); and (4) apple preload to 14S (14A+S); wherein twenty participants' blood samples were collected for insulin analysis following the lunch trails. In each experimental trial, each participant equipped with a continuous glucose monitor (CGM) was provided with a standardized breakfast and a high-fat dinner to be consumed at 8:00 and 18:00, respectively. The late lunch (14S) resulted in significantly elevated glucose peak, delayed insulin peak time, decreased insulin sensitivity, and increased insulin resistance following the lunch; also decreased glycemic response following the subsequent dinner and larger blood glucose fluctuation over the 24-h period compared with the 12S. The 14A+S significantly reduced the glucose peak, the insulin peak time and the glycemic variability following the lunch, also the 24-h glycemic variability compared with the 14S. The insulin sensitivity was significantly improved in the 12A+S, compared with that of the 12S. In conclusion, the present study found that an extra 2-h inter-meal fasting before and after lunch resulted in elevated glycemic response in both macronutrient-balanced meal and high-fat meal in healthy subjects. The negative impact of a late lunch could be partly reversed by the apple preload, without a trade-off of insulin secretion.

Combination of Texture-Induced Oral Processing and Vegetable Preload Strategy Reduced Glycemic Excursion but Decreased Insulin Sensitivity.

This study aimed to investigate the effect of the oral processing of vegetables induced by texture modification on acute postprandial glycemic response (GR) and insulin response (IR) when co-ingested and ingested prior to a rice meal. In a randomized crossover trial, 14 healthy female subjects consumed (1) co-ingestion of soft broccoli and rice (SR); (2) co-ingestion of hard broccoli and rice (HR); (3) soft broccoli prior to rice (S+R); (4) hard broccoli prior to rice (H+R); (5) rice (R). Postprandial GR and IR was compared between test meals over a period of 180-min, and the oral processing behaviors were measured for each test food samples. Hard broccoli was observed to have a higher mastication time and chews than soft broccoli. All the broccoli meals resulted in reduced incremental peak glucose (IPG) and an increased incremental area under the insulin curve in 180 min (iAUC0-180) compared with R. The S+R curbed the IPG by 40% with comparable HOMA-IR AUC0-180 compared with R, while the H+R elevated the HOMA-IR AUC0-180 by 62% more than that of R. In conclusion, the soft broccoli intake prior to a rice meal effectively attenuated postprandial GR, without lowering insulin sensitivity as its hard counterpart did.

Diurnal differences in glycemic responses, insulin responses and cognition after rice-based meals.

BACKGROUND AND OBJECTIVES: The variation in glycemic responses to white rice caused by the circadian rhythm has been widely investigated but remain controversial. This study investigated diurnal differences in the effect of rice meals on glycemic responses, insulin responses, satiety, and acute cognitive function. METHODS AND STUDY DESIGN: A total of 20 healthy participants in Group 1 and 14 in Group 2 were served identical servings of cooked white rice containing 50 g of available carbohydrates at 8:00 a.m. (rice at breakfast), 12:30 p.m. (rice at lunch), and 5:00 p.m. (rice at early supper) in a randomized order. Postprandial blood glucose, insulin, satiety, and cognitive performance tests were conducted for each test meal. RESULTS: The rice at an early supper elicited significantly milder glycemic responses than did the rice at lunch and resulted in a lower insulin sensitivity than did rice at breakfast. No difference was observed among the test meals in terms of hunger and prospective food intake. Diurnal acute cognitive performance did not differ considerably among the meals. A correlation analysis indicated that low variability in glycemic responses was positively associated with superior cognitive performance. CONCLUSIONS: A high-glycemic index white rice supper at 5:00 p.m. may facilitate daily glycemic management.

Yam paste in glycemic preloads curbs peak glycemia of rice meals in apparent healthy subjects.

BACKGROUND AND OBJECTIVES: People with dental problems and dysphagia frequently consume foods in paste form. A strategy is required to mitigate the glycemic responses of these foods. METHODS AND STUDY DESIGN: The effect of yam paste ingestion on postprandial glycemic responses was assessed using a two-arm study design for yam paste ingestion: (1) as low- and medium-glycemic index food and (2) as preload and coingested food in a rice meal. In a randomized crossover trial, 18 healthy volunteers consumed (1) low-intensity-cooked yam paste; (2) medium-intensity-cooked yam paste; (3) cooked white rice; (4) coingested low-intensity-cooked yam paste with rice; (5) coingested medium-intensity-cooked yam paste with rice; (6) a preload of low-intensity-cooked yam paste before rice; (7) a preload of medium-intensity-cooked yam paste before rice. Postprandial glycemic responses and satiety assessments were conducted for each food approach. The glycemic characteristics of yam paste were manipulated with the preparatory treatment. RESULTS: Ingesting a preload of 10 g of yam paste before a rice meal resulted in better glycemic responses for 0-60 min in terms of peak glucose value and positive increments under the curve than co-ingesting yam paste with rice, with no adverse effect on satiety, irrespective of the glycemic index of the yam paste. CONCLUSIONS: Regarding isocarbohydrates, both low- and medium-glycemic index yam paste preloads curbed the glucose peak value of a rice meal and lowered the glycemic index value of mixed meals in young healthy people.

Both Isocarbohydrate and Hypercarbohydrate Fruit Preloads Curbed Postprandial Glycemic Excursion in Healthy Subjects.

This study aimed to investigate the impact of fruit preloads on the acute postprandial glycemic response (PGR) and satiety response of a rice meal in healthy female subjects based on iso-carbohydrate (IC) and hyper-carbohydrate (HC) contents, respectively. The IC test meals including (1) rice preload (R + 35R), (2) orange preload (O + 35R), (3) apple preload (A + 35R) and (4) pear preload (P + 35R), contained 50.0 g available carbohydrates (AC) where the preload contributed 15.0 g and rice provided 35.0 g. The HC meals included (1) orange preload (O + 50R), (2) apple preload (A+50R) and (3) pear preload (P + 50R), each containing 65.0 g AC, where the fruits contributed 15.0 g and rice provided 50.0 g. Drinking water 30 min before the rice meal was taken as reference (W + 50R). All the preload treatments, irrespective of IC or HC meals, resulted in remarkable reduction (p < 0.001) in terms of incremental peak glucose (IPG) and the maximum amplitude of glycemic excursion in 180 min (MAGE0-180), also a significant decrease (p < 0.05) in the area of PGR contributed by per gram of AC (AAC), compared with the W + 50R. Apple elicited the lowest PGR among all test meals, as the A + 35R halved the IPG and slashed the incremental area under the curve in 180 min (iAUC0-180) by 45.7%, while the A + 50R reduced the IPG by 29.7%, compared with the W + 50R. All the preload meals and the reference meal showed comparable self-reported satiety in spite of the difference in AC. In conclusion, pre-meal consumption of three fruits effectively curbed post-meal glycemia even in the case of a 30% extra carbohydrate load.

Potato Preload Mitigated Postprandial Glycemic Excursion in Healthy Subjects: An Acute Randomized Trial.

This study investigated the preload effect of the medium and high glycemic index (GI) potato, as well as the combination of partially hydrolyzed guar gum (HG) and potato, when ingested prior to a rice meal, on the iso-carbohydrate basis. In a randomized crossover trial, 17 healthy female subjects consumed (1) rice; (2) co-ingestion of highly cooked potato (HP), and rice (HP + R); (3) co-ingestion of minimally cooked potato (MP) and rice (MP + R); (4) preload HP prior to rice meal (PHP + R); (5) preload MP prior to rice meal (PMP + R); (6) co-ingestion of partially hydrolyzed guar gum (HG), HP and rice (HG + HP + R); (7) preload HG prior to co-ingestion of HP and rice (PHG + HP + R); (8) co-preload of HG and HP prior to rice (PHG + PHP + R); and (9) preload of HP prior to co-ingestion of HG and rice (PHP + HG + R). Postprandial glycemic response (GR) tests and subjective satiety tests were conducted for each test food. Cooked potato as a preload to a rice meal could significantly cut the acute postprandial glycemic excursion by around 1.0 mmol/L, irrespective of the GI of the preload. Co-preload of partial hydrolyzed guar gum and highly cooked potato (PHG + PHP + R) resulted in improved acute GR in terms of peak glucose value and glycemic excursion compared with either HG preload or HP preload. All the meals with preload showed comparable or improved self-reported satiety. Within an equicarbohydrate exchange framework, both high-GI and medium-GI potato preload decreased the postprandial glycemic excursion in young healthy female subjects. The combination of HG and HP as double preload resulted in better GR than both single HG or HP preload did.