Higher adiposity predicts greater intra-individual inconsistencies in postprandial glycemic measurements-an analysis of three randomized controlled trials in Asian populations.

BACKGROUND/OBJECTIVES: Acute glycemic responses offer important insights into glucose homeostasis although the repeatability of these measurements particularly in Asian populations remains unclear. This research aimed to critically investigate the inconsistencies of the postprandial glycemic profile within individuals, and identify potential variables predicting greater inconsistencies. SUBJECTS/METHODS: This was a secondary analysis of three randomized controlled trials which fed subjects with glucose (and other carbohydrate-rich foods), and measured postprandial blood glucose at regular intervals. Intra-individual rank-order consistency in the glycemic profile between acute glucose treatments was evaluated and compared against demographic, anthropometric and cardio-metabolic health related indicators to delineate potential confounding variables. Correlations between the incremental area under curve at 120 min (iAUC120 min) for glucose and the carbohydrate-rich foods were further explored. RESULTS: Rank-order consistency was identified to be moderate, with intra-individual inconsistencies marginally lower than inter-individual inconsistencies. Notably, greater inconsistencies within individuals were directly correlated with BMI and fat-mass index (P < 0.01) albeit non-significant for age, ethnicity, and other cardio-metabolic health-related risk indicators. Across the trials, there were positive monotonic correlations between the iAUC120 min for glucose and simple sugars (sucrose, isomaltulose), as well as different varieties of rice (jasmine white, Bapatla brown, Bapatla white; p < 0.05). However, there were a lack of associations between iAUC120 min for glucose with pastas (semolina and wholegrain penne, spaghetti) and mee pok noodles. CONCLUSION: There are inherent inconsistencies in postprandial glycemic measurements within individuals, particularly among those with higher adiposity. These confounders need to be kept in mind for appropriate and meaningful interpretations of glycemia.

Posture economy: the importance of metabolic state on metabolic phenotype assessment and the energy cost of sitting and standing. A whole body calorimetry trial.

BACKGROUND: Metabolic state (fed vs fasted) can result in marked differences in exercise metabolism, fat, and carbohydrate oxidation. In addition, a large inter-individual range in metabolic response to sitting and standing when fasted has been observed. Here, we examined the effect of metabolic state on the energy cost of posture allocation. METHODS: Thirty male participants were recruited and followed a 1 h sit-stand protocol in a fasted and fed state inside a whole body calorimeter to measure energy expenditure (EE) and respiratory quotient (RQ). Body composition and resting metabolic rate were measured before the start. Fasted EE response was used to phenotype participants as energy savers (≤5% ΔEE from sitting to standing) or energy spenders (>5% ΔEE). RESULTS: In a fasted state, ΔEE from sitting to standing in energy spenders was 10.2 ± 2.7% compared to 2.6 ± 1.9% in energy savers (p < 0.001). Postprandial, there was no difference in ΔEE between energy spenders and energy savers (10.8 ± 5.1% vs 9.4 ± 5.7%). In a fasted state, significant correlations were observed between body fat (%) and ΔEE (%) (R2 = 0.55, p < 0.001), body fat (%) and ΔRQ (R2 = 0.28, p < 0.001) and ΔEE (%) and ΔRQ (R2 = 0.43, p < 0.001); these correlations were not present after the meal. CONCLUSIONS: The current study showed for the first time, that the observed difference between energy spenders and energy savers in a fasted state, disappeared after the consumption of a meal. Therefore, metabolic state may be important to consider when assessing metabolic phenotypes. Differences in body composition were observed between the energy spender and energy saver phenotype. The current findings may have implications on health and weight management recommendations on posture to increase non-exercise activity thermogenesis. This trial was retrospectively registered on 19 December 2017 as NCT03378115 on Clinicaltrials.gov .

Improved Glycemic Control and Variability: Application of Healthy Ingredients in Asian Staples.

A reduction in carbohydrate intake and low-carbohydrate diets are often advocated to prevent and manage diabetes. However, limiting or eliminating carbohydrates may not be a long-term sustainable and maintainable approach for everyone. Alternatively, diet strategies to modulate glycemia can focus on the glycemic index (GI) of foods and glycemic load (GL) of meals. To assess the effect of a reduction in glycemic load of a 24 h diet by incorporating innovative functional ingredients (ß-glucan, isomaltulose) and alternative low GI Asian staples (noodles, rice)on glycemic control and variability, twelve Chinese men (Age: 27.0 ± 5.1 years; BMI:21.6 ± 1.8kg/m2) followed two isocaloric, typically Asian, 24h diets with either a reduced glycemic load (LGL) or high glycemic load (HGL) in a randomized, single-blind, controlled, cross-over design. Test meals included breakfast, lunch, snack and dinner and the daily GL was reduced by 37% in the LGL diet. Continuous glucose monitoring provided 24 h glycemic excursion and variability parameters: incremental area under the curve (iAUC), max glucose concentration (Max), max glucose range, glucose standard deviation (SD), and mean amplitude of glycemic excursion (MAGE), time in range (TIR). Over 24h, the LGL diet resulted in a decrease in glucose Max (8.12 vs. 6.90 mmol/L; p = 0.0024), glucose range (3.78 vs. 2.21 mmol/L; p = 0.0005), glucose SD (0.78 vs. 0.43 mmol/L; p = 0.0002), mean amplitude of glycemic excursion (2.109 vs. 1.008; p < 0.0001), and increase in 4.5-6.5mmol/L TIR (82.2 vs. 94.6%; p = 0.009), compared to the HGL diet. The glucose iAUC, MAX, range and SD improved during the 2 h post-prandial window of each LGL meal, and this effect was more pronounced later in the day. The current results validate the dietary strategy of incorporating innovative functional ingredients (ß-glucan, isomaltulose) and replacing Asian staples with alternative low GI carbohydrate sources to reduce daily glycemic load to improve glycemic control and variability as a viable alternative to the reduction in carbohydrate intake alone. These observations provide substantial public health support to encourage the consumption of staples of low GI/GL to reduce glucose levels and glycemic variability. Furthermore, there is growing evidence that the role of chrononutrition, as reported in this paper, requires further examination and should be considered as an important addition to the understanding of glucose homeostasis variation throughout the day.

The Glycaemic and Insulinaemic Response of Pasta in Chinese and Indians Compared to Asian Carbohydrate Staples: Taking Spaghetti Back to Asia.

In this study, we compared the metabolic properties of the Asian staples rice and noodles, which are typically high in glycaemic index (GI), to two types of spaghetti. It is hypothesised that pasta can be a healthy replacement, particularly amongst the Asian population. Thirty Chinese and Indian subjects (17 men, 13 women; BMI: 18.5-25 kg/m2) participated in this randomised crossover trial. On seven occasions, they consumed a glucose reference drink (3 times), white rice, wheat-based mee pok noodles, semolina spaghetti and wholegrain spaghetti. Blood samples were taken to measure glucose and insulin response over a period of 3 h. The current evaluation showed that semolina spaghetti and wholegrain spaghetti can be classified as low GI products, with a GI of 53 and 54, respectively, significantly lower than wheat based mee pok noodles (74) and rice (80) (p < 0.005). In addition, both spaghettis had a lower insulin response compared to rice (p < 0.05). Furthermore, there was no difference in glucose or insulin response between semolina and wholegrain spaghetti. After controlling for gender, ethnicity, fat and fat free mass (kg), the glucose and insulin results did not change. In conclusion, wheat-based pasta can be helpful to modify the carbohydrate-rich Asian diet. Notably, there was no effect of gender, ethnicity and body composition on the glycaemic and insulinaemic response. We speculate that the starch-protein structure as a result of the spaghetti production process is a major driver of its favourable metabolic properties.

A fructose-based meal challenge to assess metabotypes and their metabolic risk profile: A randomized, crossover, controlled trial.

OBJECTIVES: The first aim of this study was to determine the metabolic type of individuals based on the postprandial metabolic response after the ingestion of a meal challenge that was high protein and either high glucose (high GI) or fructose (low GI). The second aim was to compare the baseline characteristics between the different metabolic types (metabotypes). The third aim was to assess whether the inclusion of fructose or glucose in a high-protein breakfast modulated the glucose, insulin, and TG response over a 4-h period. METHODS: The study included 46 Asian women with a body mass index between 17 and 28 kg/m2 in a randomized crossover design. Metabolic typing was based on the assessment of the postprandial glycemic, insulin and triacylglycerol (TG) response after the ingestion of two high-protein meal challenges either high in fructose or glucose. Baseline characteristics were compared between the different metabolic types. Baseline and 4-h postprandial blood samples were collected and glucose, insulin, and TG levels were analyzed. Cluster analysis was used to phenotype the participants in distinct groups. Baseline characteristics including anthropometry, glycemic, and lipid profiles and resting metabolic rate were compared among the metabolic types. RESULTS: Cluster analysis revealed that women could be grouped into three metabolic types based on postprandial glucose, insulin, and TG response after the fructose meal challenge: cluster 1 with an average glucose + high TG response (highTG; n = 12), cluster 2 with a high glucose + average TG response (highGLU; n = 8), and cluster 3 with an average glucose + average TG response (Avg; n = 26). Post hoc analysis revealed significantly greater waist-to-hip ratio and a worse lipid profile for the highTG cluster and a higher fasting blood glucose, body mass index, fat percentage, and hip circumference in the highGLU cluster. CONCLUSIONS: Three metabolic types with a distinct metabolic response could be distinguished after a high fructose meal. The results suggest a different risk profile and may indicate why some people develop diabetes in an obesogenic environment. Improved metabolic-type assessments will enable us to develop and optimize nutritional and medical interventions for individuals with differing diabetes risk.

High fructose consumption with a high-protein meal is associated with decreased glycemia and increased thermogenesis but reduced fat oxidation: A randomized controlled trial.

OBJECTIVES: Fructose is often recommended due to its ability to lower glycemic response and its increased thermogenic effect. Additionally, proteins can reduce the glycemic response of carbohydrate-rich foods and have a high diet-induced thermogenesis (DIT). The aim of this study was to investigate whether the inclusion of fructose in a high-protein meal would demonstrate metabolic advantages. METHODS: Nineteen Asian women (body mass index 17-28 kg/m2) consumed a low-glycemic index (GI; fructose) or high GI (glucose), high-protein breakfast followed by a standardized lunch in a randomized crossover design. Simultaneously, 8-h continuous glucose monitoring provided incremental area under the curve (iAUC) and 4-h indirect calorimetry provided DIT and respiratory quotient (RQ). RESULTS: The low GI diet resulted in a lower glucose iAUC (135 ± 25 versus 212 ± 23 mmol/L, P < 0.05) following breakfast, but no second-meal effect after the standardized lunch (217 ± 37 versus 228 ± 27 mmol/L, P < 0.05) compared with the high GI diet. Furthermore, 4-h DIT was greater (40.6 ± 2.3 versus 34.9 ± 1.8 kcal, P < 0.05) and RQ was increased after the fructose high-protein breakfast (0.047 ± 0.009 versus 0.028 ± 0.009, P < 0.05) compared with the glucose meal. CONCLUSIONS: Fructose is an effective sweetener in reducing glycemia and increasing DIT in the presence of a high-protein diet. However, the reduced fat oxidation after high fructose consumption might present a risk for increased lipogenesis.

Co-Ingestion of Rice Bran Soymilk or Plain Soymilk with White Bread: Effects on the Glycemic and Insulinemic Response.

The regular consumption of soy products is associated with inverse incidence of type 2 diabetes, and there has been an increasing interest in the glycemia reducing potential of rice bran and its components. In this study, we investigated whether consuming soymilk with the addition of rice bran (fiber) can reduce the glycemic response of a carbohydrate meal. Seventeen healthy Asian men (BMI: 18.5-29 kg/m²) participated in this randomized crossover trial. On four occasions, they consumed white bread (two times) and white bread with two different soymilks differing in protein and rice bran content. Blood samples were taken to measure glucose and insulin response over a period of 3 hours. Taking the glycemic index (GI) value of white bread as a reference value of 100, the GI of white bread when co-ingested with rice bran soymilk (RBS) was 83.1 (±7.7) and sugar-free soymilk (SFS) was 77.5 (±10.1), both were lower than white bread (p < 0.05). The insulin response of both soymilk treatments was similar to white bread (p > 0.05). The glucose/insulin ratio of RBS and SFS were respectively 43.1 (± 6.1) and 60.0 (± 17.0) and were lower (p < 0.05) than white bread (123.5 ± 21.1) during the first 30 min. In conclusion, co-ingestion of low amounts of soy protein with a carbohydrate meal stimulated early-phase insulin secretion and thereby increased blood glucose clearance effectiveness. Furthermore, rice bran-fortified soymilk reduced the glycemic response similarly to soymilk with a greater dose of soy protein. Rice bran and its components offer therapeutic potential for glycemic and insulinemic control.

Does the ingestion of a 24 hour low glycaemic index Asian mixed meal diet improve glycaemic response and promote fat oxidation? A controlled, randomized cross-over study.

BACKGROUND: The health benefits of consuming a low glycaemic index (GI) diet to reduce the risk of type 2 Diabetes are well recognized. In recent years the GI values of various foods have been determined. Their efficacy in constructing and consuming a low GI diet over 24 h in modulating glycaemic response has not been fully documented. The translation of using single-point GI values of foods to develop a 24 h mixed meal diet can provide valuable information to consumers, researchers and dietitians to optimize food choice for glycaemic control. By using GI values of foods to develop mixed meals, our study is the first to determine how both blood glucose and substrate oxidation may be modulated over 24 h. METHODS: The study included 11 Asian men with a BMI between 17-24 kg/m2 who followed both a 1-day low GI and 1-day high GI diet in a randomized, controlled cross-over design. Test meals included breakfast, lunch, snack and dinner. Glycaemic response was measured continuously for over 24 h and postprandial substrate oxidation for 10 h inside a whole body calorimeter. RESULTS: The low GI diet resulted in lower 24 h glucose iAUC (860 ± 440 vs 1329 ± 614 mmol/L.min; p = 0.014) with lower postprandial glucose iAUC after breakfast (p < 0.001), lunch (p = 0.009), snack (p = 0.012) and dinner (p = 0.003). Moreover, 24 h mean amplitude of glycaemic excursion was lower during the low GI vs high GI diet (1.44 ± 0.63 vs 2.33 ± 0.82 mmol/L; p < 0.001). Simultaneously, decrease in 10 h fat oxidation was less during the low vs high GI diet (-0.033 ± 0.021 vs -0.050 ± 0.017 g/min; p < 0.001), specifically after breakfast (p < 0.001) and lunch (p < 0.001). CONCLUSIONS: Our study corroborates that using low GI local foods to construct a 24 h low GI diet, is able to reduce glycaemic response and variability as recorded by continuous glucose monitoring. Our observations also confirm that a low GI diet promotes fat oxidation over carbohydrate oxidation when compared to a high GI diet. These observations provide public health support for the encouragement of healthier nutrition choices by consuming low GI foods. TRIAL REGISTRATION: NCT 02631083 (Clinicaltrials.gov).

A Low Glycaemic Index Diet Incorporating Isomaltulose Is Associated with Lower Glycaemic Response and Variability, and Promotes Fat Oxidation in Asians.

Low glycaemic index (GI) foods minimize large blood glucose fluctuations and have been advocated to enhance fat oxidation and may contribute to weight management. We determined whether the inclusion of isomaltulose compared to sucrose in a low/high GI meal sequence can modulate the glycaemic response and substrate oxidation in an Asian population. Twenty Chinese men (body mass index (BMI): 17-28 kg/m²) followed a 24 h low GI (isomaltulose, PalatinoseTM) or high GI (sucrose) diet in a randomized double-blind, controlled cross-over design. Treatment meals included dinner (day 1), breakfast, lunch, and snack (day 2). Continuous glucose monitoring provided incremental area under the curve (iAUC) and mean amplitude of glycaemic excursion (MAGE) and 10 h indirect calorimetry (whole body calorimeter) (day 2) provided energy expenditure and substrate oxidation. Our results demonstrated that the low GI diet resulted in lower 24 h glucose iAUC (502.5 ± 231.4 vs. 872.6 ± 493.1 mmol/L; p = 0.002) and lower 24 h glycaemic variability (MAGE: 1.67 ± 0.53 vs. 2.68 ± 1.13 mmol/L; p < 0.001). Simultaneously, 10 h respiratory quotient increased more during high GI (p = 0.014) and fat oxidation was higher after low GI breakfast (p = 0.026), lunch (p < 0.001) and snack (p = 0.013). This indicates that lower GI mixed meals incorporating isomaltulose are able to acutely reduce the glycaemic response and variability and promote fat oxidation.