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

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.

Anti-Diabetic Potential of Polyphenol-Rich Fruits from the Maleae Tribe-A Review of In Vitro and In Vivo Animal and Human Trials

The Maleae tribe consists of over one thousand species, including many well-known polyphenol-containing fruit crops with wide-ranging biological properties, e.g., apples (Malus), chokeberries (Aronia), pears (Pyrus), quinces (Cydonia, Chaenomeles), saskatoon (Amelanchier), loquats (Eriobotrya), medlars (Mespilus), rowans (Sorbus), and hawthorns (Crataegus). Considering the current interest in the concept of functional foods and the still-insufficient methods of diabetes management, the anti-diabetic potential of fruits has been studied intensively, including those of the Maleae tribe. This paper is the first comprehensive overview of this selected topic, covering articles published from 2000 to 2023 (131 articles in total). The first part of this review focuses on the potential mechanisms of action of fruits investigated so far (46 species), including their effects on tissue-specific glucose transport and the expression or activity of proteins in the insulin signalling pathway. The second part covers the phytocompounds responsible for particular fruits' activity-primarily polyphenols (e.g., flavonols, dihydrochalcones, proanthocyanidins, anthocyanins, phenolic acids), but also polysaccharides, triterpenes, and their additive and synergistic effects. In summary, fruits from the Maleae tribe seem promising as functional foods and anti-diabetic agents; however, their prospects for more expansive pro-health application require further research, especially more profound in vivo trials.

Food Order and Timing Effects on Glycaemic and Satiety Responses to Partial Fruit-for-Cereal Carbohydrate Exchange: A Randomized Cross-Over Human Intervention Study

Postprandial glycaemic response amplitude plays a critical role in diabetic complications, but is subject to food order and temporal separation within a meal. Effects of partial fruit-for-cereal carbohydrate exchange on glycaemic and appetite responses, as affected by food order and separation, were examined using kiwifruit (KF) and wheaten breakfast cereal biscuit (WB). In a randomized cross-over intervention study, 20 subjects ingested 51.7 g of available carbohydrate as 74 g WB alone, or as 200 g KF and 37 g WB, each delivering 25.85 g of available carbohydrate. The 200 g KF was partially exchanged for 37 g of WB, at 90 min and 30 min before, at the same time as, or 30 min after, ingesting WB. Incremental satiety responses were derived from appetite scores measured using a visual analogue scale, and capillary blood glucose responses were monitored. In all exchanges, KF reduced the glycaemic response (iAUC) by 20-30% with no loss of total satiation. The incremental glycaemic and satiety responses to food ingestion followed each other closely. Glycaemic response amplitudes were reduced almost 50% compared with 74 g WB when KF ingestion preceded WB ingestion by 30 min, and less when the KF was ingested with or 30 min after the cereal. The results suggest that fruit most effectively suppresses the digestion of cereal carbohydrates if ingested long enough before the cereal to prevent overlap of the glycaemic responses, but close enough for fruit components that impede carbohydrate digestion or uptake to interact with the ingested cereal in the gut. Ethics approval was obtained from the Human and Disabilities Ethics Committee (HDEC) of the New Zealand Ministry of Health. The trial was registered with the Australian New Zealand Clinical Trials Registry (Trial ID: ACTRN12615000744550).

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.

Effects of low-GI biscuits as pre-loads or mid-meal snacks on post-prandial glycemic excursions in women with recent gestational diabetes: A protocol for a randomized crossover trial and an extended tailored intervention

Background

Increased post-prandial glycemic excursions contribute to the development of diabetes and have been observed in women with recent gestational diabetes mellitus (GDM) and with normal glucose tolerance at post-partum. As a convenient meal replacement, low-GI biscuits are helpful for improving glycemic excursions in patients with type 2 diabetes. However, it is unknown whether low-GI biscuits as pre-loads or mid-meal snacks have a better effect in diminishing post-prandial glycemic excursions from the individual level in women with recent GDM. Therefore, the aim of this trial is to tailor a better dietary strategy utilizing low-GI biscuits (Fitmeal) to improve post-prandial glycemic excursions through within-subject comparison in such a population and observe the long-term effect of a tailored dietary approach in glycemic control.

Methods

We have designed a two-phase trial including a randomized, crossover, non-blinded trial in the first phase, followed by a 4-week tailored intervention in the second phase. A total of 52 post-partum women with recent GDM will be allocated into four meal plans: (1) Fitmeal pre-load 30 min before standard lunch meal (P+L), (2) Fitmeal as a mid-meal snack 2 h before standard lunch meal (S+L), (3) isocaloric standard control with co-ingestion of Fitmeal and standard lunch meal (CL) at the same time, and (4) placebo control with 200 ml of water taken 30 min before standard lunch meal (W + L), on four consecutive days. Acute post-prandial glycemic response (PGR) measured by continuous glucose monitoring (CGM) will be compared among the four meals. In the second phase, all participants will receive a 4-week tailored intervention using Fitmeal as pre-loads or mid-meal snacks based on within-subject PGR results from the first phase. Glycemic metrics, dietary behaviors, and psychosocial factors (e.g., quality of life, self-efficacy, perceived stress, and depression) will be examined at baseline and end-point.

Discussion

This trial is expected to optimize the use of low-GI biscuits as pre-loads or mid-meal snacks in improving individual post-prandial glycemic excursions among women with recent GDM. Furthermore, the findings of this study will provide novel information on how to deliver an effective dietary intervention at the individual level and guide future clinical practice of medical nutrition therapy for diabetes prevention.

Trial registration number

Chinese clinical trial registry, ChiCTR2200060923.

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.

Dietary Fibre and Organic Acids in Kiwifruit Suppress Glycaemic Response Equally by Delaying Absorption-A Randomised Crossover Human Trial with Parallel Analysis of 13C-Acetate Uptake

Non-sugar components of kiwifruit reduce the amplitude of the glycaemic response to co-consumed cereal starch. We determined the relative contribution of different non-sugar kiwifruit components to this anti-glycaemic effect. Healthy participants (n = 9) ingested equal carbohydrate meals containing 20 g starch as wheat biscuit (WB, 30 g), and the sugar equivalent of two kiwifruit (KFsug, 20.4 g), either intrinsic or added as glucose, fructose and sucrose (2:2:1). The meals were WB+KFsug (control, no non-sugar kiwifruit components), WB + whole kiwifruit pulp (WB+KF), WB + neutralised kiwifruit pulp (WB+KFneut), WB + low-fibre kiwifruit juice (WB+KFjuice) and WB+KFsug + kiwifruit organic acids (WB+KFsug+OA). All meals were spiked with 100 mg sodium [1-13C] acetate to measure intestinal absorption. Each participant ingested all meals in random order. Blood glucose and breath 13CO2 were measured at ingestion and at 15 min intervals up to 180 min. Compared with WB+KFsug, whole kiwifruit pulp (WB+KF) almost halved glycaemic response amplitude (p < 0.001), reduced incremental area under the blood glucose response curve (iAUC) at 30 min (peak) by 50% (p < 0.001), and averted late postprandial hypoglycaemia. All other treatments suppressed response amplitude half as much as whole kiwifruit and averted acute hypoglycaemia, with little effect on iAUC. Effects on 13CO2 exhalation paralleled effects on blood glucose (R2 = 0.97). Dietary fibre and organic acids contributed equally to the anti-glycaemic effect of kiwifruit by reducing intestinal absorption rate. Kiwifruit flesh effectively attenuates glycaemic response in carbohydrate exchange, as it contains fructose, dietary fibre and organic acids.

Metabolic and Blood Pressure Effects of Consuming Two Kiwifruit Daily for 7 Weeks: A Randomised Controlled Trial

Background: Eating two kiwifruit before breakfast by equi-carbohydrate partial exchange of cereal has been associated with lower postprandial glucose and insulin, but it increases the intake of fruit sugar. We assessed the effects of kiwifruit ingestion at breakfast over 7 weeks on metabolic and physiologic factors. Method: Forty-three healthy Asian participants were randomised to ingest 500 mL of carbonated water (control) or 500 mL of carbonated water plus two kiwifruit (intervention), before breakfast. Three-day weighed diet records were taken before and at week 4 during the intervention. Overnight fasting blood samples were taken at baseline and week 7. Forty-two participants completed the study (n = 22 control, n = 20 intervention). Results: The kiwifruit group consumed more fructose, vitamin C, vitamin E, and carbohydrates as a percentage of energy compared with the control group (p < 0.01). There was no evidence of between-group changes in metabolic outcomes at the end of the intervention, with the following mean (95% confidence interval) differences in fasting blood samples: glucose 0.09 (−0.06, 0.24) mmol/L; insulin −1.6 (−3.5, 0.3) μU/mL; uric acid −13 (−30, 4) μmol/L; triglycerides −0.10 (−0.22, 0.03) mmol/L; and total cholesterol −0.05 (−0.24, 0.14) mmol/L. There was a −2.7 (−5.5, 0.0) mmHg difference in systolic blood pressure for the intervention group compared with the control group. Conclusion: Eating two kiwifruit as part of breakfast increased fruit consumption and intake of antioxidant nutrients without a change in fasting insulin. There was a difference in systolic blood pressure and no adverse fructose-associated increases in uric acid, triglycerides, or total cholesterol. This simple intervention may provide health benefits to other demographic groups.