Apple Preload Halved the Postprandial Glycaemic Response of Rice Meal on in Healthy Subjects

Effects of apples (Malus domestica) and their derivatives on metabolic conditions related to inflammation and oxidative stress and an overview of by-products use in food processing

Apple (Malus domestica) is the third most produced fruit worldwide. It is a well-known source of bioactive compounds mainly represented by hydroxycinnamic acids, flavan-3-ols, dihydrochalcones, dehydroascorbic acid, carotenoids, chlorogenic acid, epicatechin, and phloridzin. Due to the lack of a recent evaluation of the clinical trials associated with apple consumption, this review investigated the effects of this fruit on metabolic conditions related to inflammation and oxidative stress and reviewed the applications of apple waste on food products. Thirty-three studies showed that apples or its derivatives exhibit anti-inflammatory and antioxidant actions, improve blood pressure, body fat, insulin resistance, dyslipidemia, and reduce cardiovascular risks. Apples have a great economic impact due to its several applications in the food industry and as a food supplement since it has impressive nutritional value. Dietary fiber from the fruit pomace can be used as a substitute for fat in food products or as an improver of fiber content in meat products. It can also be used in bakery and confectionary products or be fermented to produce alcohol. Pomace phytocompounds can also be isolated and applied as antioxidants in food products. The potential for the use of apples and by-products in the food industry can reduce environmental damage.

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.

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.

Validity of food additive maltodextrin as placebo and effects on human gut physiology: systematic review of placebo-controlled clinical trials

PURPOSE

Maltodextrin (MDX) is a polysaccharide food additive commonly used as oral placebo/control to investigate treatments/interventions in humans. The aims of this study were to appraise the MDX effects on human physiology/gut microbiota, and to assess the validity of MDX as a placebo-control.

METHODS

We performed a systematic review of randomized-placebo-controlled clinical trials (RCTs) where MDX was used as an orally consumed placebo. Data were extracted from study results where effects (physiological/microbial) were attributed (or not) to MDX, and from study participant outcomes data, before-and-after MDX consumption, for post-publication 're-analysis' using paired-data statistics.

RESULTS

Of two hundred-sixteen studies on 'MDX/microbiome', seventy RCTs (n = 70) were selected for analysis. Supporting concerns regarding the validity of MDX as a placebo, the majority of RCTs (60%, CI 95% = 0.48-0.76; n = 42/70; Fisher-exact p = 0.001, expected < 5/70) reported MDX-induced physiological (38.1%, n = 16/42; p = 0.005), microbial metabolite (19%, n = 8/42; p = 0.013), or microbiome (50%, n = 21/42; p = 0.0001) effects. MDX-induced alterations on gut microbiome included changes in the Firmicutes and/or Bacteroidetes phyla, and Lactobacillus and/or Bifidobacterium species. Effects on various immunological, inflammatory markers, and gut function/permeability were also documented in 25.6% of the studies (n = 10/42). Notably, there was considerable variability in the direction of effects (decrease/increase), MDX dose, form (powder/pill), duration, and disease/populations studied. Overall, only 20% (n = 14/70; p = 0.026) of studies cross-referenced MDX as a justifiable/innocuous placebo, while 2.9% of studies (n = 2/70) acknowledged their data the opposite.

CONCLUSION

Orally-consumed MDX often (63.9% of RCTs) induces effects on human physiology/gut microbiota. Such effects question the validity of MDX as a placebo-control in human clinical trials.

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.

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 (MAGE_0–180), 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 (iAUC_0–180) 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.

Impact of processing techniques on the glycemic index of rice

Rice is an important starchy staple food and generally, rice varieties are known to have a higher glycemic index (GI). Over the years, the significance of GI on human health is being better understood and is known to be associated with several lifestyle disorders. Apart from the intrinsic characteristics of rice, different food processing techniques are known to have implications on the GI of rice. This work details the effect of domestic and industrial-level processing techniques on the GI of rice by providing an understanding of the resulting physicochemical changes. An attempt has been made to relate the process-dependent digestion behavior, which in turn reflects on the GI. The role of food constituents is elaborated and the various in vitro and in vivo approaches that have been used to determine the GI of foods are summarized. Considering the broader perspective, the effect of cooking methods and additives is explained. Given the significance of the cereal grain, this work concludes with the challenges and key thrust areas for future research.

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.

Co-ingested vinegar-soaked or preloaded dried apple mitigated acute postprandial glycemia of rice meal in healthy subjects under equicarbohydrate conditions

This study investigated 2 possible approaches to dietary control of acute postprandial responses to a rice-based meal under equicarbohydrate conditions: (1) a dried apple (DA) preload and (2) co-ingestion of vinegar-soaked DA. We hypothesized that both approaches would counteract hyperglycemia with no negative effect on satiety, possibly explained by an inhibitory effect on digestive enzyme activity and/or the effect of the sugar component of the DA. Fifteen healthy female subjects consumed (1) rice, (2) co-ingestion of DA and rice (DA + R), (3) DA preload and rice (PDA + R), (4) rice with sugar solution (same sugar profile as in DA) preloaded (PSS + R), or (5) co-ingestion of rice with vinegar-soaked DA (VDA + R) in a randomized crossover trial. Acute postprandial glycemic response tests and subjective satiety tests were conducted for each test meal. Compared with rice reference, the PA + R and PSS + R achieved 31.4% and 36.3% reduction of the incremental area under the curve_0-120, 24.3% and 27.0% decreases in the average glucose peak, along with 21.6% and 27.0% decreases in glycemic excursion in 240 minutes, whereas the VDA + R resulted 42.4%, 27.0%, and 29.7% reductions in the incremental area under the curve_0-120, peak, and glycemic excursion, respectively. The DA-containing meals had no effect or a favorable effect on satiety. The in vitro assay found larger resistant starch and smaller rapid digestible starch fractions in DA + R and VDA + R meals compared to those of the rice reference (P < .001). The result of this study supported the research hypothesis, and the DA-containing meals could be considered as a potential dietary approach for glycemic management.