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.