Contributors to dietary glycaemic index and glycaemic load in the Netherlands: the role of beer.

Diets high in glycaemic index (GI) and glycaemic load (GL) have been associated with a higher diabetes risk. Beer explained a large proportion of variation in GI in a Finnish and an American study. However, few beers have been tested according to International Organization for Standardization (ISO) methodology. We tested the GI of beer and estimated its contribution to dietary GI and GL in the Netherlands. GI testing of pilsner beer (Pilsner Urquell) was conducted at The University of Sydney according to ISO international standards with glucose as the reference food. Subsequently, GI and GL values were assigned to 2556 food items in the 2011 Dutch food composition table using a six-step methodology and consulting four databases. This table was linked to dietary data from 2106 adults in the Dutch National Food Consumption Survey 2007-2010. Stepwise linear regression identified contribution to inter-individual variation in dietary GI and GL. The GI of pilsner beer was 89 (SD 5). Beer consumption contributed to 9·6 and 5·3% inter-individual variation in GI and GL, respectively. Other foods that contributed to the inter-individual variation in GI and GL included potatoes, bread, soft drinks, sugar, candy, wine, coffee and tea. The results were more pronounced in men than in women. In conclusion, beer is a high-GI food. Despite its relatively low carbohydrate content (approximately 4-5 g/100 ml), it still made a contribution to dietary GL, especially in men. Next to potatoes, bread, sugar and sugar-sweetened beverages, beer captured a considerable proportion of between-person variability in GI and GL in the Dutch diet.

Postprandial glycaemic response: how is it influenced by characteristics of cereal products?

Cereal products exhibit a wide range of glycaemic indexes (GI), but the interaction of their different nutrients and starch digestibility on blood glucose response is not well known. The objective of this analysis was to evaluate how cereal product characteristics can contribute to GI and insulinaemic index and to the parameters describing glycaemic or insulinaemic responses (incremental AUC, maximum concentration and Δpeak). Moreover, interactions between the different cereal products characteristics and glycaemic response parameters were assessed for the first time. Relationships between the cereal products characteristics and the glycaemic response were analysed by partial least square regressions, followed by modelling. A database including 190 cereal products tested by the usual GI methodology was used. The model on glycaemic responses showed that slowly digestible starch (SDS), rapidly digestible starch (RDS) and fat and fibres, and several interactions involving them, significantly explain GI by 53 % and Δpeak of glycaemia by 60 %. Fat and fibres had important contributions to glycaemic response at low and medium SDS contents in cereal products, but this effect disappears at high SDS levels. We showed also for the first time that glycaemic response parameters are dependent on interactions between starch digestibility (interaction between SDS and RDS) and nutritional composition (interaction between fat and fibres) of the cereal products. We also demonstrated the non-linear effect of fat and fibres (significant effect of their quadratic terms). Hence, optimising both the formula and the manufacturing process of cereal products can improve glucose metabolism, which is recognised as strongly influential on human health.

Dose-response effect of a novel functional fibre, PolyGlycopleX(®), PGX(®), on satiety.

The objective of this research was to determine the dose-response effects of a palatable, viscous and gel forming fibre, PolyGlycopleX(®) (PGX(®)), [(α-D-glucurono-α-manno-ß-D-manno-ß-D-gluco), (α-Lgulurono-ß-D mannurono), (ß-D-gluco-ß-D-mannan)] on satiety, and to gain insight into the underlying mechanisms that lead to appetite inhibition. Healthy subjects (n = 10), aged between 20.3 and 29.2 years, consumed PGX(®), in granular form at 2.5, 5.0 and 7.5 g, and a 5g inulin control, with a standard breakfast. The PGX(®) doses of 2.5 and 7.5 g mixed with water at the start of breakfast increased satiety (iAUC of 140.0 and 157.7, P = 0.025 and 0.001, respectively) compared to the control. The most effective dose (7.5g) was palatable and corresponded to a 34% increase in fullness, measured using a visual analogue scale and incremental area under the curve, and resulted in a delayed postprandial glycaemic response when compared with the control.

Food processing according to the NOVA classification is not associated with glycemic index and glycemic load: results from an analysis of 1995 food items.

BACKGROUND: Ultraprocessed foods (UPFs) comprise most calories in the United States diet. Glycemic index (GI) and glycemic load (GL) are measures of the quality and quantity of carbohydrates in food based on their effect on postprandial blood glucose. Diets high in UPFs and GI/GL are associated with chronic metabolic diseases but the relationship between them is unclear. OBJECTIVES: Our objective was to examine the GI and GL of foods assigned to NOVA food processing groups. We hypothesized that GI and GL would be lowest in minimally processed foods (MPFs) compared to processed food (PRF) and UPF (with no difference between PRF and UPF). METHODS: GI and GL values produced by healthy individuals for 1995 food items were collated from published sources. Food items were manually coded by processing levels according to NOVA classification. In addition, as the effects of processing on glycemic potential may vary between types of foods, food items were coded into 8 groups (beans, nuts, and seeds; beverages; dairy; fats and sweets; fruit; grains; fish, meat, and poultry; and vegetables). Multilevel linear modeling was used to determine significance with an α value of 0.05. RESULTS: The effect of food processing on GI and GL was contrary to our hypothesis as means did not differ significantly across processing levels: GI-MPF: 54.1 ± 19.5, PRF: 53.2 ± 18.9, UPF: 49.3 ± 18.1 (P = 0.712); GL-MPF: 17.1 ± 10.3, PRF: 15.8 ± 12.4, UPF; 11.5 ± 7.9 (P = 0.890). Within food groups, there was no significant association between processing level and GI (P = 0.184), but GL was inversely associated with grains and vegetables (P < 0.001). CONCLUSIONS: Across analyzed foods, GI and GL do not differ between processing levels, whereas GL was lower in ultraprocessed grains and vegetables than MPF. Any potential adverse outcomes associated with UPF are unlikely to be related to effects on glycemia. This project was preregistered at the Open Science Framework (OSF) Registries through the Center for Open Science as 10.17605/OSF.IO/PJWG9.

Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) substudy.

BACKGROUND: Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, >50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk. OBJECTIVES: This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss. METHODS: We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over 8 wk. High-coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using differential lipid abundance comparisons and partial least squares discriminant analyses. Associations between lipid changes and clinical characteristics were determined by Spearman correlation and Bootstrap Forest of ensemble machine learning model. Baseline lipids, predictive of glycemic parameters changes postweight loss, were assessed using Bootstrap Forest analyses. RESULTS: We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids, and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine increased significantly. Changes in certain lipid species (e.g., saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids, and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and homeostasis model assessment of insulin resistance. CONCLUSIONS: Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond 1-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study was registered at clinicaltrials.gov as NCT01777893 (https://clinicaltrials.gov/study/NCT01777893).

(1)H NMR spectroscopy for the in vitro understanding of the glycaemic index.

The glycaemic index (GI) characterises foods by using the incremental area under the glycaemic response curve relative to the same amount of oral glucose. Its ability to differentiate between curves of different shapes, the peak response and other aspects of the glycaemic response is contentious. The present pilot study aimed to explore the possibility of using 1H NMR spectroscopy to better understand in vivo digestion characteristics as reflected in the glycaemic response of carbohydrate-rich foods; such an approach might be an adjunct to the in vivo GI test. The glycaemic response of two types of raw wheat flour (2005 from Griffith NSW, Chara, Row 10, Plot 6:181 and store-bought Colese Plain Flour) and a cooked store-bought flour was tested and compared with results recorded during the in vitro enzymatic digestion of the wheat flour samples by glucoamylase from Aspergillus niger (EC 3.2.1.3) as monitored by 1H NMR spectroscopy. Comparing the digestion time courses of raw and cooked wheat starch recorded in vitro strongly suggests that the initial rate of glucose release in vitro correlates with the glycaemic spike in vivo. During the in vitro time courses, approximately four times as much glucose was released from cooked starch samples than from raw starch samples in 90 min. Monitoring enzymatic digestion of heterogeneous mixtures (food) by 1H NMR spectroscopy showcases the effectiveness of the technique in measuring glucose release and its potential use as the basis of an in vitro method for a better understanding of the GI.

Glycemic index and insulin index after a standard carbohydrate meal consumed with live kombucha: A randomised, placebo-controlled, crossover trial.

Introduction: Kombucha is a complex probiotic beverage made from fermented tea, yet despite extensive historical, anecdotal, and in-vivo evidence for its health benefits, no controlled trials have been published on its effect on humans. Methods: We conducted a randomised placebo-controlled, cross-over study that examined the Glycemic Index (GI) and Insulin Index (II) responses after a standardised high-GI meal consumed with three different test beverages (soda water, diet lemonade soft drink and an unpasteurised kombucha) in 11 healthy adults. The study was prospectively registered with the Australian New Zealand Clinical Trials Registry (anzctr.org.au: 12620000460909). Soda water was used as the control beverage. GI or II values were calculated by expressing the 2-h blood glucose or insulin response as a percentage of the response produced by 50 g of glucose dissolved in water. Results: There was no statistically significant difference in GI or II between the standard meal consumed with soda water (GI: 86 and II: 85) or diet soft drink (GI: 84 and II: 81, (p = 0.929 for GI and p = 0.374 for II). In contrast, when kombucha was consumed there was a clinically significant reduction in GI and II (GI: 68, p = 0.041 and II: 70, p = 0.041) compared to the meal consumed with soda water. Discussion: These results suggest live kombucha can produce reductions in acute postprandial hyperglycemia. Further studies examining the mechanisms and potential therapeutic benefits of kombucha are warranted.

Complementary Nutritional Improvements of Cereal-Based Products to Reduce Postprandial Glycemic Response.

High glycemic response (GR) is part of cardiometabolic risk factors. Dietary polyphenols, starch digestibility, and dietary fibers could play a role in modulating GR. We formulated cereal products with high dietary fibers, polyphenols, and slowly digestible starch (SDS) contents to test their impact on the glycemic index (GI) and insulin index (II). Twelve healthy subjects were randomized in a crossover-controlled study to measure the GI and II of four biscuits according to ISO-26642(2010). Two types of biscuits were enriched with dietary fibers and polyphenols and high in SDS, and two similar control biscuits with low levels of these compounds were compared. The subjects consumed 50 g of available carbohydrates from the biscuits or from a glucose solution (reference). Glycemic and insulinemic responses were monitored for 2 h after the start of the consumption. The two enriched biscuits led to low GI and II (GI: 46 ± 5 SEM and 43 ± 4 SEM and II: 54 ± 5 SEM and 45 ± 3 SEM) when controls had moderate GI and II (GI: 57 ± 5 SEM and 58 ± 5 SEM and II: 61 ± 4 SEM and 61 ± 4 SEM). A significant difference of 11 and 15 units between the GI of enriched and control products was obtained. These differences may be explained by the polyphenol contents and high SDS levels in enriched products as well as potentially the dietary fiber content. This study provides new proposals of food formulations to induce beneficial health effects which need to be confirmed in a longer-term study in the context of the SINFONI consortium.

Effects of added PGX®, a novel functional fibre, on the glycaemic index of starchy foods.

The development of lower-glycaemic index (GI) foods requires simple, palatable and healthy strategies. The objective of the present study was to determine the most effective dose of a novel viscous fibre supplement (PGX®) to be added to starchy foods to reduce their GI. Healthy subjects (n 10) consumed glucose sugar (50 g in water × 3) and six starchy foods with a range of GI values (52-72) along with 0 (inert fibre), 2.5 or 5 g granular PGX® dissolved in 250 ml water. GI testing according to ISO Standard 26,642-2010 was used to determine the reduction in GI. PGX® significantly reduced the GI of all six foods (P < 0.001), with an average reduction of 19 % for the 2.5 g dose and 30 % for the 5 g dose, equivalent to a reducing the GI by 7 and 15 units, respectively. Consuming small quantities of the novel functional fibre PGX®, mixed with water at the start of a meal, is an effective strategy to reduce the GI of common foods.

High-glycaemic index and -glycaemic load meals increase the availability of tryptophan in healthy volunteers.

The purpose of the present study was to determine the influence of the glycaemic index (GI) and glycaemic load (GL) on the ratio of tryptophan (TRP) relative to other large neutral amino acids (LNAA). Ten healthy men (age 22·9 (sd 3·4) years; BMI 23·5 (sd 1·6) kg/m2) underwent standard GI testing, and later consumed each of a mixed-macronutrient (1915 kJ; 66·5 % carbohydrate (CHO), 17 % protein and 16·5 % fat) high-GI (MHGI), an isoenergetic, mixed-macronutrient low-GI (MLGI) and a CHO-only (3212 kJ; 90 % CHO, 8 % protein, 2 % fat) high-GI (CHGI) meal on separate days. The GI, GL and insulin index values (e.g. area under the curve) were largest after the CHGI meal (117, 200, 158), followed by the MHGI (79, 59, 82) and MLGI (51, 38, 56) meals, respectively (all values were significantly different, P < 0·05). After the MHGI and MLGI meals but not after the CHGI meal, TRP was elevated at 120 and 180 min (P < 0·05). After the CHGI, LNAA was lower compared with the MLGI (P < 0·05); also the rate of decline in LNAA was higher after CHGI compared with MHGI and MLGI (both comparisons P < 0·05). The percentage increase from baseline in TRP:LNAA after CHGI (23 %) was only marginally higher than after the MHGI meal (17 %; P = 0·38), but it was threefold and nearly significantly greater than MLGI (8 %; P = 0·05). The present study demonstrates that the postprandial rise in TRP:LNAA was increased by additional CHO ingestion and higher GI. Therefore, the meal GL appears to be an important factor influencing the postprandial TRP:LNAA concentration.

Food intake, postprandial glucose, insulin and subjective satiety responses to three different bread-based test meals.

The effect of bread consumption on overall food intake is poorly understood. The aim of this study was to measure postprandial food intake after a set breakfast containing three different breads. Ten males and 10 females aged 20.1-44.8 years, BMI 18.4-24.8 kg/m(2), consumed two slices of White Bread, Bürgen Wholemeal and Seeds Bread or Lupin Bread (all 1300 kJ) with 10 g margarine and 30 g strawberry jam. Fullness and hunger responses and were measured before and during the test breakfasts. Glucose and insulin responses (incremental area under each two-hour curve (iAUC)) were calculated. Food intake was measured and energy and nutrient intake determined at a buffet meal two hours later. Subjects consumed significantly less energy after the Bürgen Bread meal compared to the White Bread meal (2548 ± 218 vs. 3040±328kJ, Bürgen Bread vs. White Bread, P<0.05). There were higher fullness responses for the Lupin Bread (P<0.01), and the Bürgen Bread (P<0.05) compared with the White Bread. Lupin Bread and Bürgen Bread produced smaller postprandial glucose responses (79 ± 7, 74 ± 4, 120 ± 10 mmol/L min iAUC, Lupin, Bürgen and White Bread respectively, P<0.01). Differences in insulin responses were also observed (6145 ± 1048, 6471 ± 976, 9674 ± 1431 pmol/L min iAUC, Lupin, Bürgen and White Bread respectively, P<0.01). Equal-energy portions of three different commercially available breads differed in their short-term satiation capacity. Further studies are needed to demonstrate any potential benefit for weight management.

Deep Dive Into the Effects of Food Processing on Limiting Starch Digestibility and Lowering the Glycemic Response.

During processing of cereal-based food products, starch undergoes dramatic changes. The objective of this work was to evaluate the impact of food processing on the starch digestibility profile of cereal-based foods using advanced imaging techniques, and to determine the effect of preserving starch in its native, slowly digestible form on its in vivo metabolic fate. Four different food products using different processing technologies were evaluated: extruded products, rusks, soft-baked cakes, and rotary-molded biscuits. Imaging techniques (X-ray diffraction, micro-X-ray microtomography, and electronic microscopy) were used to investigate changes in slowly digestible starch (SDS) structure that occurred during these different food processing technologies. For in vivo evaluation, International Standards for glycemic index (GI) methodology were applied on 12 healthy subjects. Rotary molding preserved starch in its intact form and resulted in the highest SDS content (28 g/100 g) and a significantly lower glycemic and insulinemic response, while the three other technologies resulted in SDS contents below 3 g/100 g. These low SDS values were due to greater disruption of the starch structure, which translated to a shift from a crystalline structure to an amorphous one. Modulation of postprandial glycemia, through starch digestibility modulation, is a meaningful target for the prevention of metabolic diseases.

The Impact of Carbohydrate Quality on Dental Plaque pH: Does the Glycemic Index of Starchy Foods Matter for Dental Health?

Sugary carbohydrate foods have long been associated with increased risk of dental caries formation, but the dental health impact of starchy carbohydrates, particularly those with a high glycemic index (GI), has not been well examined. AIM: To investigate the effect of different starchy foods varying in their GI, on acute changes in dental plaque pH. METHODS: In a series of sub-studies in healthy adults, common starchy carbohydrate foods, including white bread, instant mashed potatoes, canned chickpeas, pasta, breakfast cereals, white rice, and an oral glucose solution were consumed in fixed 25 g available carbohydrate portions. The change in dental plaque pH was assessed postprandially over 1 h and capillary plasma glucose was measured at regular intervals over 2 h. RESULTS: Higher GI starchy foods produced greater acute plaque pH decreases and larger overall postprandial glucose responses compared to lower GI starchy foods (white bread compared with canned chickpeas: -1.5 vs. -0.7 pH units, p = 0.001, and 99 ± 8 mmol/L min vs. 47 ± 7 mmol/L min, p = 0.026). Controlling for other food factors (food form and nutritional composition), lower GI versions of matched food pairs produced smaller plaque pH excursions compared to higher GI versions of the same food. Using linear regression analysis, the GI value of starchy carbohydrate foods explained 60% of the variation in maximum plaque pH nadir and 64% of the variation in overall acute dental plaque pH excursion (p < 0.01). CONCLUSION: The findings imply that starchy foods, in particular those with a higher GI, may play a role in increasing the risk of dental caries.

International tables of glycemic index and glycemic load values 2021: a systematic review.

BACKGROUND: Reliable tables of glycemic indexes (GIs) and glycemic loads (GLs) are critical to research examining the relationship between glycemic qualities of carbohydrate in foods, diets, and health. In the 12 years since the last edition of the tables, a large amount of new data has become available. OBJECTIVES: To systematically review and tabulate published and unpublished sources of reliable GI values, including an assessment of the reliability of the data. METHODS: This edition of the tables lists over 4000 items, a 61% increase in the number of entries compared to the 2008 edition. The data have been separated into 2 lists. The first represents more precise values derived using the methodology recommended by the International Standards Organization (∼2100 items). The second list contains values determined using less robust methods, including using limited numbers of healthy subjects or with a large SEM (∼1900 food items). RESULTS: Dairy products, legumes, pasta, and fruits were usually low-GI foods (≤55 on the 100-point glucose scale) and had consistent values around the world. Cereals and cereal products, however, including whole-grain or whole-meal versions, showed wide variation in GI values, presumably arising from variations in manufacturing methods. Breads, breakfast cereals, rice, savory snack products, and regional foods were available in high-, medium-, and low-GI versions. Most varieties of potato were high-GI foods, but specific low-GI varieties have now been identified. CONCLUSIONS: The availability of new data on the GIs of foods will facilitate wider research and application of the twin concepts of GI and GL. Although the 2021 edition of the tables improves the quality and quantity of GI data available for research and clinical practice, GI testing of regional foods remains a priority. This systematic review was registered in PROSPERO as #171204.

Can a Higher Protein/Low Glycemic Index vs. a Conventional Diet Attenuate Changes in Appetite and Gut Hormones Following Weight Loss? A 3-Year PREVIEW Sub-study.

Background: Previous research showed that weight-reducing diets increase appetite sensations and/or circulating ghrelin concentrations for up to 36 months, with transient or enduring perturbations in circulating concentrations of the satiety hormone peptide YY. Objective: This study assessed whether a diet that is higher in protein and low in glycemic index (GI) may attenuate these changes. Methods: 136 adults with pre-diabetes and a body mass index of ≥25 kg/m2 underwent a 2-month weight-reducing total meal replacement diet. Participants who lost ≥8% body weight were randomized to one of two 34-month weight-maintenance diets: a higher-protein and moderate-carbohydrate (CHO) diet with low GI, or a moderate-protein and higher-CHO diet with moderate GI. Both arms involved recommendations to increase physical activity. Fasting plasma concentrations of total ghrelin and total peptide YY, and appetite sensations, were measured at 0 months (pre-weight loss), at 2 months (immediately post-weight loss), and at 6, 12, 24, and 36 months. Results: There was a decrease in plasma peptide YY concentrations and an increase in ghrelin after the 2-month weight-reducing diet, and these values approached pre-weight-loss values by 6 and 24 months, respectively (P = 0.32 and P = 0.08, respectively, vs. 0 months). However, there were no differences between the two weight-maintenance diets. Subjective appetite sensations were not affected by the weight-reducing diet nor the weight-maintenance diets. While participants regained an average of ~50% of the weight they had lost by 36 months, the changes in ghrelin and peptide YY during the weight-reducing phase did not correlate with weight regain. Conclusion: A higher-protein, low-GI diet for weight maintenance does not attenuate changes in ghrelin or peptide YY compared with a moderate-protein, moderate-GI diet. Clinical Trial Registry: ClinicalTrials.gov registry ID NCT01777893 (PREVIEW) and ID NCT02030249 (Sub-study).

Dietary intake in cystic fibrosis and its role in glucose metabolism.

BACKGROUND: Dietary intervention in cystic fibrosis (CF) has historically focused on high-energy diets to address malnutrition, with little attention on diet quality. With increased survival, CF complications such as impaired glucose tolerance (IGT) and cystic fibrosis related diabetes (CFRD) have increased in prevalence. In the absence of consensus on the management of IGT, the role of dietary intake, specifically carbohydrate quality, requires consideration. AIMS: The aims of this study were to: 1) determine nutritional quality of dietary intake at an adult CF clinic and compare this to the Australian Dietary Guidelines 2) explore relationships between dietary intake, including glycaemic index (GI) and glycaemic load (GL), and glucose response variables using continuous glucose monitoring (CGM). METHODS: Adults attending a Sydney hospital were recruited to undergo CGM for five-seven days and record dietary intake using a food record over the CGM period. The relationship between variables of dietary intake, including GI and GL and variables of glycaemic response, including mean amplitude of glycaemic excursions (MAGE), percentage of time in hyperglycaemic and euglycaemic range, were determined. RESULTS: Eighteen participants completed the study with 87 full days of dietary and CGM data. Dietary intake was higher than recommendations in the Australian Dietary Guidelines in relation to grains and protein foods and only slightly higher in saturated fat. Bivariate correlations showed dietary GI was significantly positively associated with percentage of time in hyperglycaemic range. Dietary GL was significantly associated with SD, MAGE and percentage of time in euglycaemic range on CGM. Results remained significant when controlled for energy intake in partial correlation analyses. CONCLUSIONS: This study suggests GI and GL may be important dietary factors influencing glucose metabolism in CF. Further studies exploring low GI or GL diets as a dietary intervention in CF are the next step.

Is a Higher Protein-Lower Glycemic Index Diet More Nutritious Than a Conventional Diet? A PREVIEW Sub-study.

High protein diets and low glycemic index (GI) diets have been associated with improved diet quality. We compared the changes in nutrient intakes of individuals at high risk of developing type-2 diabetes over 3 y who followed either a higher protein-lower GI diet (HPLG) or a conventional moderate protein-moderate GI diet (MPMG). This post hoc analysis included 161 participants with overweight and pre-diabetes from the Australian cohort of the PREVIEW study (clinical trial registered in https://www.clinicaltrials.gov/ct2/show/NCT01777893?term=NCT01777893&draw=2&rank=1) who were randomly assigned to a HPLG diet (25% energy from protein, dietary GI ≤ 50, n = 85) or a MPMG diet (15% energy from protein, dietary GI ≥ 56, n = 76). Food records were collected at 0-mo (baseline) and at 6-, 12-, 24-, and 36-mo (dietary intervention period). Linear mixed models were used to compare the differences in total energy, macro- and micronutrients, dietary GI, glycemic load (GL) and body weight between the two diet groups at the 4 dietary intervention time points. At 3 y, 74% participants from the HPLG diet and 74% participants from the MPMG diet completed the trial. The HPLG group showed significantly higher protein intake and lower dietary GI and GL than the MPMG group (group fixed effect P < 0.001 for all three parameters). By 6-, 12-, 24-, and 36-mo there was a 3.0, 2.7, 2.2, and 1.4% point difference in protein intake and 6.2, 4.1, 4.8, and 3.9 GI unit difference between the groups. The intake of energy and saturated fat decreased (mostly in the first 6-mo), while the intake of dietary fiber increased (from mo-0 to mo-12 only) in both diets, with no significant differences between the diets. The dietary intakes of zinc (group fixed effect P = 0.05), selenium (P = 0.01), niacin (P = 0.01), vitamin B12 (P = 0.01) and dietary cholesterol (group by time fixed effect P = 0.001) were higher in the HPLG group than in the MPMG group. Despite both diets being designed to be nutritionally complete, a HPLG diet was found to be more nutritious in relation to some micronutrients, but not cholesterol, than a MPMG diet.

Extending the Overnight Fast: Sex Differences in Acute Metabolic Responses to Breakfast.

Fasting for over 24 h is associated with worsening glucose tolerance, but the effect of extending the overnight fast period (a form of time-restricted feeding) on acute metabolic responses and insulin sensitivity is unclear. The aim of this pilot study was to determine the acute impact of an increased fasting period on postprandial glycaemia, insulinemia, and acute insulin sensitivity responses to a standard meal. Twenty-four lean, young, healthy adults (12 males, 12 females) consumed a standard breakfast after an overnight fast of 12, 14, and 16 h. Each fast duration was repeated on three separate occasions (3 × 3) in random order. Postprandial glucose and insulin responses were measured at regular intervals over 2 h and quantified as incremental area under the curve (iAUC). Insulin sensitivity was determined by homeostatic modelling assessment (HOMA). After 2 h, ad libitum food intake at a buffet meal was recorded. In females, but not males, insulin sensitivity improved (HOMA%S +35%, p = 0.016, marginally significant) with longer fast duration (16 h vs. 12 h), but paradoxically, postprandial glycaemia was higher (glucose iAUC +37%, p = 0.002). Overall, males showed no differences in glucose or insulin homeostasis. Both sexes consumed more energy (+28%) at the subsequent meal (16 h vs. 12 h). Delaying the first meal of the day by 4 h by extending the fasting period may have adverse metabolic effects in young, healthy, adult females, but not males.

Effects of a modestly lower carbohydrate diet in gestational diabetes: a randomized controlled trial.

BACKGROUND: Lower carbohydrate diets have the potential to improve glycemia but may increase ketonemia in women with gestational diabetes (GDM). We hypothesized that modestly lower carbohydrate intake would not increase ketonemia. OBJECTIVE: To compare blood ketone concentration, risk of ketonemia, and pregnancy outcomes in women with GDM randomly assigned to a lower carbohydrate diet or routine care. METHODS: Forty-six women aged (mean ± SEM) 33.3 ± 0.6 y and prepregnancy BMI 26.8 ± 0.9 kg/m2 were randomly assigned at 28.5 ± 0.4 wk to a modestly lower carbohydrate diet (MLC, ∼135 g/d carbohydrate) or routine care (RC, ∼200 g/d) for 6 wk. Blood ketones were ascertained by finger prick test strips and 3-d food diaries were collected at baseline and end of the intervention. RESULTS: There were no detectable differences in blood ketones between completers in the MLC group compared with the RC group (0.1 ± 0.0 compared with 0.1 ± 0.0 mmol/L, n = 33, P = 0.31, respectively), even though carbohydrate and total energy intake were significantly lower in the intervention group (carbohydrate 165 ± 7 compared with 190 ± 9 g, P = 0.04; energy 7040 ± 240 compared with 8230 ± 320 kJ, P <0.01, respectively). Only 20% of participants in the MLC group met the target intake compared with 65% in the RC group (P <0.01). There were no differences in birth weight, rate of large-for-gestational-age infants, percent fat mass, or fat-free mass between groups. CONCLUSIONS: An intervention to reduce carbohydrate intake in GDM did not raise ketones to clinical significance, possibly because the target of 135 g/d was difficult to achieve in pregnancy. Feeding studies with food provision may be needed to assess the benefits and risks of low-carbohydrate diets. This trial was registered at www.anzctr.org.au as ACTRN12616000018415.

Dietary Fibre Consensus from the International Carbohydrate Quality Consortium (ICQC).

Dietary fibre is a generic term describing non-absorbed plant carbohydrates and small amounts of associated non-carbohydrate components. The main contributors of fibre to the diet are the cell walls of plant tissues, which are supramolecular polymer networks containing variable proportions of cellulose, hemicelluloses, pectic substances, and non-carbohydrate components, such as lignin. Other contributors of fibre are the intracellular storage oligosaccharides, such as fructans. A distinction needs to be made between intrinsic sources of dietary fibre and purified forms of fibre, given that the three-dimensional matrix of the plant cell wall confers benefits beyond fibre isolates. Movement through the digestive tract modifies the cell wall structure and may affect the interactions with the colonic microbes (e.g., small intestinally non-absorbed carbohydrates are broken down by bacteria to short-chain fatty acids, absorbed by colonocytes). These aspects, combined with the fibre associated components (e.g., micronutrients, polyphenols, phytosterols, and phytoestrogens), may contribute to the health outcomes seen with the consumption of dietary fibre. Therefore, where possible, processing should minimise the degradation of the plant cell wall structures to preserve some of its benefits. Food labelling should include dietary fibre values and distinguish between intrinsic and added fibre. Labelling may also help achieve the recommended intake of 14 g/1000 kcal/day.