Plant origin, processing, and domestic preparation may affect the postprandial glycemic response (PGR) of starchy foods. The objective of this study was to examine the possibility of integrating domestically cooked non-cereal starchy foods commonly consumed in Northeast Asia into glycemic management diet, and compare their glycemic characteristics with those of waxy and non-waxy whole grains and starchy beans. In a randomized crossover trial, ten healthy subjects consumed dried lily bulb (LB), lotus seed (LS), adlay (AD), waxy black rice (BR), millet (MI), and adzuki bean (AB), pre-soaked and each cooked for two time durations. Acute PGR tests and in vitro carbohydrate digestion were carried out for each test food. Both the LS and AB meals achieved low glycemic index (GI 21–51), while the other starchy foods failed to show significant difference with rice (GI 83–109). The hydrolysis indexes of LS and AB were 37.7%–61.1%, significantly lower than other test foods. The in vitro tests indicated that pre-soaking resulted in high rapidly digestible starch (RDS) and low resistant starch (RS). Careful choice of whole grain materials, minimized pre-soaking, and moderate cooking may be critical factors for successful postprandial glycemic management for diabetic and pre-diabetic.

The aim of this study was to explore the glycaemic response (GR) patterns of four dried fruits (DF) and the mixed meals containing dried fruits, rice and almonds. Dried apples (DApp), dried jujubes (DJ), raisins (Ra) and dried apricots (DApr) were tested in eleven healthy subjects in random order. Test meals included the following 3 groups: (1) dried fruits containing 50 g available carbohydrates; (2) mixed meals consisting of DF and rice (DF + R), each contributing 25 g available carbohydrates; (3) Group (2) supplemented with 30 g almonds (DF + R + A). The postprandial GR and other characteristics in 240 min were investigated. The GI values of 4 DFs were 43 for DApp, 55 for DJ, 56 for both Ra and DApr. The DApp displayed the smallest amplitude of glycaemic excursion within 240 min (MAGE_0–240). Compared with rice, the DApp + R meal elicited a significantly reduced GR and a smaller MAGE_0–240 (GI 81 vs. 65). With the addition of almonds, the GIs and MAGE_0–240 decreased significantly in all DF + A + R combinations except DApp + R + A. The ratio of total fructose/glucose contents of test meals were negatively correlated to GIs. Dried fruits and nuts may have the potential to mitigate the postprandial GR when jointly introduced into glycaemic management diets.

This study aimed to investigate the possible glycemic effect of apple preload on acute postprandial glycemic responses (GRs) of a following rice meal, comparing with its co-ingestion counterpart and an apple sugar solution preload, based on equal carbohydrates intake. In a randomized crossover trial, 18 healthy female subjects consumed (1) rice, (2) co-ingestion of apple and rice (A+R), (3) apple preload and rice (PA+R), and (4) rice with sugar solution preload (same sugar profile as in apple) (PSS+R). Acute postprandial GR tests and subjective satiety tests were carried out for each test food. Compared with rice reference, the PA+R achieved a 50% reduction of the iAUC_0-120, a 51.4% reduction of the average peak value, and a 52.6% reduction of glycemic excursion in 240 min, while the PSS+R showed 29.7% and 31.6% reduction of peak value and glycemic excursion, respectively. No significant differences were found between R and PA+R in any of the satiety characteristics. Compared with rice control, apple preload of 15 g available carbohydrates remarkably lowered the acute postprandial GR without negative effect on satiety. The sugar component may partly contribute to the glycemic suppressing effect of the apple preload.

The addition of vegetable to carbohydrate-based meals was shown to contribute to glycaemic management. The aim of this study was to investigate the impact of homogenisation on vegetables added to rice meals in terms of acute glycaemic responses (GR). In a randomised crossover trial, sixteen healthy volunteers completed thirteen test sessions, which included two sessions for glucose control, two for rice and nine for different vegetable-rice mixed meals: cooked pak choi and cooked rice (CP+R); cooked cauliflower and cooked rice (CC+R); cooked eggplant and cooked rice (CE+R); and their homogenised counterparts, both raw or cooked. Postprandial GR tests, in vitro carbohydrate digestion and chemical analyses were carried out for each test meal. Compared with pure rice, CE+R, CP+R and CC+R meals achieved significantly lower glycaemic indexes (GI) of 67, 71 and 73, whereas their homogenised counterparts failed to show significant difference with rice. The hydrolysis indexes (HI) of CE+R, CP+R and CC+R were 69·6, 83·8 and 80·6 % of the HI of the rice control. CE had the greatest effect on lowering the GI, the incremental area under the blood glucose curve from 0 to 120 min, the peak glucose value, the maximum amplitude of glucose excursion in 0–120 min (MAGE0–120), the HI and rapid available starch. Both in vitro and in vivo tests demonstrated that incorporating non-homogenised cooked vegetables into a rice meal could slow the carbohydrate digestion and improve postprandial GR. Texture properties of vegetable may play an important role in underlying glycaemic control mechanisms.

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.

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.