Acute effects of non-homogenised and homogenised vegetables added to rice-based meals on postprandial glycaemic responses and in vitro carbohydrate digestion. Br J Nutr. 2018;120:1023-1033. [PMID: 30355395 DOI: 10.1017/s0007114518002489]

Effect of vegetable consumption with chewing on postprandial glucose metabolism in healthy young men: a randomised controlled study

Although thorough chewing lowers postprandial glucose concentrations, research on the effectiveness of chewing vegetables in different forms on postprandial glucose metabolism remains limited. This study examined the effects of vegetables consumed in solid versus puree forms on postprandial glucose metabolism. Nineteen healthy young men completed two 180-min trials on separate days in a random order: the chewing trial involved the consumption of shredded cabbage with chewing and the non-chewing trial involved the consumption of pureed cabbage without chewing. Energy jelly was consumed immediately after the consumption of shredded or puree cabbage. Blood samples were collected at 0, 30, 45, 60, 90, 120 and 180 min. Circulating concentrations of glucose, insulin, total glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) concentrations were measured from the plasma. Although plasma glucose concentrations did not differ between the trials, the plasma insulin and GIP incremental area under the curve values were higher in the chewing than in the non-chewing trial. Postprandial total GLP-1 concentrations were higher in the chewing than in the non-chewing trial at 45, 60 and 90 min. This study demonstrates that consuming shredded cabbage while chewing enhances postprandial incretin secretion but has no effect on postprandial glucose concentration.Trial registration: Clinical trial registration ID.: UMIN000052662, registered 31 October 2023.

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.

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 (iAUC_0–180) compared with R. The S+R curbed the IPG by 40% with comparable HOMA-IR AUC_0–180 compared with R, while the H+R elevated the HOMA-IR AUC_0–180 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.

The acute effect of incorporating lettuce or watercress into a moderately high-fat meal on postprandial lipid, glycemic response, and plasma inflammatory cytokines in healthy young men: a randomized crossover trial

BACKGROUND

Postprandial responses to food mostly depend on the composition of the meal and the consumption of vegetables may modulate this postprandial state. In this study, the effects of lettuce or watercress consumption with a moderately high-fat meal (40% kcal from fat) on postprandial lipemia, glycemia, and inflammatory cytokines were determined in healthy men.

METHODS

This randomized, 3-arm, crossover study was conducted in sixteen healthy young men with a mean ± SEM age and body mass index (in kg/m2) of 22.8 ± 0.5 years old and 23.7 ± 1.16, respectively. Lettuce and watercress were added to the test meal in portions of 100 g and cellulose was added to the control meal. Thereafter, blood samples were collected by passing 0, 1, 2, 3, and 4 h for analysis. The postprandial response was measured in plasma glucose, triglycerides (TG), total cholesterol, high-density-lipoproteins cholesterol (HDL-C), and low-density-lipoproteins cholesterol (LDL-C), as the area under the postprandial curve (AUC). Moreover, plasma tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were determined once before and once 4 h after the meal's consumption.

RESULTS

The 0-4-h AUCs for glucose (385.7, 361.9, and 382.3 mg/dL for the control, lettuce, and watercress meals, respectively) were calculated to be lower when meal was consumed with lettuce compared to the control (P < 0.05) and watercress (P < 0.01) meals. The maximum values of insulin were obtained as 43.8 ± 18.8, 33.5 ± 19.5, and 42.8 ± 17.7 μIU/mL for the control, lettuce, and watercress meals, respectively. As well, the lettuce-containing meal more reduced the AUC for insulin compared with the control (P < 0.05), but not watercress. Notably, plasma TG, total cholesterol, HDL-C, and LDL-C had no significant differences among the meals. Moreover, the levels of plasma IL-6 and TNF-α did not differ among the meals.

CONCLUSION

In this study on healthy men, the addition of lettuce to a moderately high-fat meal delayed the postprandial glycemic response. However, the effect of the consumption of these vegetables on postprandial responses in subjects with cardiometabolic risk factors remains to be elucidated yet. This clinical trial was registered at the Iran Clinical Trials Registration Office (IRCT) on March 3, 2018, with an ID of IRCT20160702028742N4 ( https://www.irct.ir/user/trial/23233/view ).

Potential contributions of the methodology to the variability of glycaemic index of foods

Glycaemic index (GI) testing provides a useful point of comparison between carbohydrate sources. For this comparison to be meaningful, the methods used to determine GI values need to be rigorous and consistent between testing events. This requirement has led to increasing standardization of the GI methodology, with an international standard developed in joint consultation with FAO/WHO (ISO 26642:2010) currently the most up to date document. The purpose of this review is to compare the international standard to methods of published studies claiming to have performed a GI test. This analysis revealed that the international standard permits a wide range of choices for researchers when designing a GI testing plan, rather than a single standardized protocol. It has also been revealed that the literature contains significant variation, both between studies and from the international standard for critical aspects of GI testing methodology. The primary areas of variation include; what glucose specification is used, which reference food is used, how much reference food is given, what drink is given during testing, the blood sampling site chosen and what assay and equipment is used to measure blood glucose concentration. For each of these aspects we have explored some of the methodological and physiological implications of these variations. These insights suggest that whilst the international standard has assisted with framing the general parameters of GI testing, further stan-dardization to testing procedures is still required to ensure the continued relevance of the GI to clinical nutrition.

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.

A glycaemic index compendium of non-western foods

Current international tables published on the glycaemic index (GI) of foods represent valuable resources for researchers and clinicians. However, the vast majority of published GI values are of Western origin, notably European, Australian and North American. Since these tables focus on Western foods with minimal inclusion of other foods from non-Western countries, their application is of limited global use. The objective of this review is to provide the GI values for a variety of foods that are consumed in non-Western countries. Our review extends and expands on the current GI tables in an attempt to widen its application in many other regions of the world.

Postprandial Glycemic and Insulinemic Effects of the Addition of Aqueous Extracts of Dried Corn Silk, Cumin Seed Powder or Tamarind Pulp, in Two Forms, Consumed with High Glycemic Index Rice

Several plant-based traditional ingredients in Asia are anecdotally used for preventing and/or treating type 2 diabetes. We investigated three such widely consumed ingredients, namely corn silk (CS), cumin (CU), and tamarind (TA). The aim of the study was to determine the effects of aqueous extracts of these ingredients consumed either as a drink (D) with high-glycemic-index rice or added to the same amount of rice during cooking (R) on postprandial glycemia (PPG), insulinemia (PPI), and blood pressure (BP), over a 3 h measurement period. Eighteen healthy Chinese men (aged 37.5 ± 12.5 years, BMI 21.8 ± 1.67 kg/m²) took part in a randomized crossover trial, each completing up to nine sessions. Compared to the control meal (plain rice + plain water), the addition of test extracts in either form did not modulate PPG, PPI, or BP. However, the extracts when added within rice while cooking gave rise to significantly lower PPI than when consumed as a drink (p < 0.01). Therefore, the form of consumption of phytochemical-rich ingredients can differentially modulate glucose homeostasis. This study also highlights the need for undertaking randomized controlled clinical trials with traditional foods/components before claims are made on their specific health effects.

A comparison between whole grain and pearled oats: acute postprandial glycaemic responses and in vitro carbohydrate digestion in healthy subjects

PURPOSE

To compare the glycaemic response of whole grain oat kernels and pearled oats cooked under normal pressure or higher pressure and examine whether replacing half of the rice in a given meal with either of the two oat grains could make a difference in acute glycaemic responses.

METHODS

In a randomised crossover trial, ten healthy subjects consumed two groups of test meals: (1) oat grain-only, including whole grain oats cooked under normal pressure (WONP) and higher pressure (WOHP) as well as their pearled oat counterparts, PONP and POHP; and (2) mixed meals of aforementioned oat grains and cooked rice (OG + R), including WONP + R, WOHP + R, PONP + R and POHP + R. A postprandial blood glucose test, texture profile analysis and in vitro carbohydrate digestion assay were carried out for each test meal.

RESULTS

Compared with the rice reference, oat grain-only meals induced lower glucose levels at all time points, lower peak values and smaller glucose excursions at 120 min (P < 0.05), but OG + Rs did not have the abovementioned effects. The oat grain-only meals had glycaemic indexes (GIs) ranging from 51 to 58, while those of OG + Rs ranged from 59 to 70. WONP + R had a 21% lower iAUC_0-60 and a 40% lower iAUC_60-120 value than those of rice (P < 0.05). Oat-rice mixed meals had lower iAUC_0-60 values compared with that of the rice control (P < 0.05), except for POHP + R. Excellent consistency between the hydrolysis index and the GI was observed (r = 0.969, P < 0.001) in oat grain-only meals.

CONCLUSIONS

All oat grain-only meals could be included in the glycaemic management diet, regardless of the oat grain type or cooking treatment. In oat-rice mixed meals, whole grain oats and normal pressure cooking ensured a favourable glycaemic effect.