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.

Appraisal of Triglyceride-Related Markers as Early Predictors of Metabolic Outcomes in the PREVIEW Lifestyle Intervention: A Controlled Post-hoc Trial.

Background: Individuals with pre-diabetes are commonly overweight and benefit from dietary and physical activity strategies aimed at decreasing body weight and hyperglycemia. Early insulin resistance can be estimated via the triglyceride glucose index {TyG = Ln [TG (mg/dl) × fasting plasma glucose (FPG) (mg/dl)/2]} and the hypertriglyceridemic-high waist phenotype (TyG-waist), based on TyG x waist circumference (WC) measurements. Both indices may be useful for implementing personalized metabolic management. In this secondary analysis of a randomized controlled trial (RCT), we aimed to determine whether the differences in baseline TyG values and TyG-waist phenotype predicted individual responses to type-2 diabetes (T2D) prevention programs. Methods: The present post-hoc analyses were conducted within the Prevention of Diabetes through Lifestyle intervention and population studies in Europe and around the world (PREVIEW) study completers (n = 899), a multi-center RCT conducted in eight countries (NCT01777893). The study aimed to reduce the incidence of T2D in a population with pre-diabetes during a 3-year randomized intervention with two sequential phases. The first phase was a 2-month weight loss intervention to achieve ≥8% weight loss. The second phase was a 34-month weight loss maintenance intervention with two diets providing different amounts of protein and different glycemic indices, and two physical activity programs with different exercise intensities in a 2 x 2 factorial design. On investigation days, we assessed anthropometrics, glucose/lipid metabolism markers, and diet and exercise questionnaires under standardized procedures. Results: Diabetes-related markers improved during all four lifestyle interventions. Higher baseline TyG index (p < 0.001) was associated with greater reductions in body weight, fasting glucose, and triglyceride (TG), while a high TyG-waist phenotype predicted better TG responses, particularly in those randomized to physical activity (PA) of moderate intensity. Conclusions: Two novel indices of insulin resistance (TyG and TyG-waist) may allow for a more personalized approach to avoiding progression to T2D. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01777893 reference, identifier: NCT01777893.

Dietary Glycaemic Index Labelling: A Global Perspective.

The glycaemic index (GI) is a food metric that ranks the acute impact of available (digestible) carbohydrates on blood glucose. At present, few countries regulate the inclusion of GI on food labels even though the information may assist consumers to manage blood glucose levels. Australia and New Zealand regulate GI claims as nutrition content claims and also recognize the GI Foundation's certified Low GI trademark as an endorsement. The GI Foundation of South Africa endorses foods with low, medium and high GI symbols. In Asia, Singapore's Healthier Choice Symbol has specific provisions for low GI claims. Low GI claims are also permitted on food labels in India. In China, there are no national regulations specific to GI; however, voluntary claims are permitted. In the USA, GI claims are not specifically regulated but are permitted, as they are deemed to fall under general food-labelling provisions. In Canada and the European Union, GI claims are not legal under current food law. Inconsistences in food regulation around the world undermine consumer and health professional confidence and call for harmonization. Global provisions for GI claims/endorsements in food standard codes would be in the best interests of people with diabetes and those at risk.

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).

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.

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.

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.

Is there a soft drink vs. alcohol seesaw? A cross-sectional analysis of dietary data in the Australian Health Survey 2011-12.

PURPOSE: Previous studies in older Australians have reported higher alcohol intake in those with low added sugar intake, yet the relationship between energy in liquid form [alcoholic beverages vs. sugar-sweetened beverages (SSB)] and measures of obesity has not been evaluated. We aimed to assess the association between the energy derived from SSB and alcoholic beverages, and to model the association between the substitution of SSB with alcoholic beverages and waist circumference. METHODS: In this cross-sectional analysis, dietary data from the Australian Health Survey 2011-12 were analyzed. Participants with implausible dietary intake were excluded by applying the Goldberg cut-off. Usual SSB intake of adults ≥ 19 years old was estimated using the Multiple Source Method and participants were classified into zero-, low- or high-SSB consumers according to their usual SSB intake. Energy from alcoholic beverages in the three SSB consumption groups was compared using multivariable general linear models. A substitution model was used to assess the association between the replacement of SSB with alcoholic beverages and waist circumference. RESULTS: Zero-SSB consumers made up 33% of the included participants. In all age groups, zero-SSB consumers had significantly higher energy intakes from alcoholic beverages than low- and high-SSB consumers. Low- and high-SSB consumers had similar consumption of alcoholic beverages. Substituting SSB intake with alcoholic beverage intake was not associated with significant differences in waist circumference in most age groups. CONCLUSIONS: Australian adults who avoid SSB are common but consume substantially more energy in the form of alcoholic beverages. An increase in alcoholic beverage intake could be an 'unintended consequence' of strictly discouraging SSB consumption.

Glycemic Index and Insulinemic Index of Foods: An Interlaboratory Study Using the ISO 2010 Method.

An official method for determining food glycemic index (GI) was published by the Organization for International Standardization (ISO) in 2010, but its performance has not been assessed. Therefore, we aimed to determine the intra- and inter-laboratory variation of food GI values measured using the 2010 ISO method. Three laboratories (Australia, Canada and France) determined the GI and insulinemic-index (II) of six foods in groups of 13-15 participants using the 2010 ISO method and intra- and inter-laboratory Standard Deviations (SDs) were calculated. Overall mean food GIs varied from 47 to 86 (p < 0.0001) with no significant difference among labs (p = 0.57) and no food × laboratory interaction (p = 0.20). Within-laboratory SD was similar among foods (range, 17.8-22.5; p = 0.49) but varied among laboratories (range 17.5-23.1; p = 0.047). Between-laboratory SD of mean food GI values ranged from 1.6 to 6.7 (mean, 5.1). Mean glucose and insulin responses varied among foods (p < 0.001) with insulin (p = 0.0037), but not glucose (p = 0.054), varying significantly among labs. Mean II varied among foods (p < 0.001) but not among labs (p = 0.94). In conclusion, we found that using the 2010 ISO method, the mean between-laboratory SD of GI was 5.1. This suggests that the ISO method is sufficiently precise to distinguish a mean GI = 55 from a mean GI ≥ 70 with 97-99% probability.

Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: Assessment of Causal Relations.

While dietary factors are important modifiable risk factors for type 2 diabetes (T2D), the causal role of carbohydrate quality in nutrition remains controversial. Dietary glycemic index (GI) and glycemic load (GL) have been examined in relation to the risk of T2D in multiple prospective cohort studies. Previous meta-analyses indicate significant relations but consideration of causality has been minimal. Here, the results of our recent meta-analyses of prospective cohort studies of 4 to 26-y follow-up are interpreted in the context of the nine Bradford-Hill criteria for causality, that is: (1) Strength of Association, (2) Consistency, (3) Specificity, (4) Temporality, (5) Biological Gradient, (6) Plausibility, (7) Experimental evidence, (8) Analogy, and (9) Coherence. These criteria necessitated referral to a body of literature wider than prospective cohort studies alone, especially in criteria 6 to 9. In this analysis, all nine of the Hill's criteria were met for GI and GL indicating that we can be confident of a role for GI and GL as causal factors contributing to incident T2D. In addition, neither dietary fiber nor cereal fiber nor wholegrain were found to be reliable or effective surrogate measures of GI or GL. Finally, our cost-benefit analysis suggests food and nutrition advice favors lower GI or GL and would produce significant potential cost savings in national healthcare budgets. The high confidence in causal associations for incident T2D is sufficient to consider inclusion of GI and GL in food and nutrient-based recommendations.

Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes: A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies.

Published meta-analyses indicate significant but inconsistent incident type-2 diabetes(T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is nowover a decade ago that a published meta-analysis used a predefined standard to identify validstudies. Considering valid studies only, and using random effects dose-response meta-analysis(DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relationswould support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit>1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). Thecombined T2D-GI RR was 1.27 (1.15-1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that forthe T2D-GL RR was 1.26 (1.15-1.37) (p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet.The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) (p < 0.001, n =10) and 1.89 (1.66-2.16) (p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GLwere robustly associated with incident T2D. Together with mechanistic and other data, thissupports that consideration should be given to these dietary risk factors in nutrition advice.Concerning the public health relevance at the global level, our evidence indicates that GI and GLare substantial food markers predicting the development of T2D worldwide, for persons ofEuropean ancestry and of East Asian ancestry.

Dietary Insulin Load and Cancer Recurrence and Survival in Patients With Stage III Colon Cancer: Findings From CALGB 89803 (Alliance).

BACKGROUND: Evidence suggests that diets inducing postprandial hyperinsulinemia may be associated with increased cancer-related mortality. The goal of this study was to assess the influence of postdiagnosis dietary insulin load and dietary insulin index on outcomes of stage III colon cancer patients. METHODS: We conducted a prospective observational study of 1023 patients with resected stage III colon cancer enrolled in an adjuvant chemotherapy trial who reported dietary intake halfway through and six months after chemotherapy. We evaluated the association of dietary insulin load and dietary insulin index with cancer recurrence and survival using Cox proportional hazards regression adjusted for potential confounders; statistical tests were two-sided. RESULTS: High dietary insulin load had a statistically significant association with worse disease-free survival (DFS), comparing the highest vs lowest quintile (adjusted hazard ratio [HR] = 2.77, 95% confidence interval [CI] = 1.90 to 4.02, Ptrend < .001). High dietary insulin index was also associated with worse DFS (highest vs lowest quintile, HR = 1.75, 95% CI = 1.22 to 2.51, Ptrend= .01). The association between higher dietary insulin load and worse DFS differed by body mass index and was strongest among patients with obesity (HR = 3.66, 95% CI = 1.88 to 7.12, Pinteraction = .04). The influence of dietary insulin load on cancer outcomes did not differ by mutation status of KRAS, BRAF, PIK3CA, TP53, or microsatellite instability. CONCLUSIONS: Patients with resected stage III colon cancer who consumed a high-insulinogenic diet were at increased risk of recurrence and mortality. These findings support the importance of dietary management following resection of colon cancer, and future research into underlying mechanisms of action is warranted.

The physiologic and phenotypic significance of variation in human amylase gene copy number.

Background: Salivary α-amylase gene (AMY1) copy number (CN) correlates with the amount of salivary α-amylase, but beyond this, the physiologic significance is uncertain. Objective: We hypothesized that individuals with higher AMY1 CN would digest starchy foods faster and show higher postprandial responses and lower breath hydrogen excretion compared with those with low CN. Design: Four linked studies were conducted. In Study 1, we genotyped 201 healthy subjects with the use of real-time quantitative polymerase chain reaction and determined glucose tolerance, insulin sensitivity, salivary α-amylase activity, body mass index (BMI), and macronutrient intake. In Study 2, a pool of 114 subjects tested 6 starchy foods, 3 sugary foods, 1 mixed meal, and 2 reference glucose solutions, containing either 50 or 25 g of available carbohydrate. In Study 3, we compared glycemic and insulin responses to starchy foods with responses to glucose in 40 individuals at extremes of high and low CN. In Study 4, we compared breath hydrogen and methane responses over 8 h in 30 individuals at extremes of CN. Results: AMY1 CN correlated positively with salivary α-amylase activity (r = 0.62, P < 0.0001, n = 201) but not with BMI, glucose tolerance, or insulin sensitivity. However, CN was strongly correlated with normalized glycemic responses to all starchy foods (explaining 26-61% of interindividual variation), but not to sucrose or fruit. Individuals in the highest compared with the lowest decile of CN produced modestly higher glycemia (+15%, P = 0.018), but not insulinemia, after consuming 2 starchy foods. Low-CN individuals displayed >6-fold higher breath methane levels in the fasting state and after starch ingestion than high-CN individuals (P = 0.001), whereas hydrogen excretion was similar. Conclusions: Starchy foods are digested faster and produce higher postprandial glycemia in individuals with high AMY1 CN. In contrast, having low CN is associated with colonic methane production. This trial was registered at www.anzctr.org.au as ACTRN12617000670370.

Associations of Diet and Physical Activity with Risk for Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Rising rates of gestational diabetes mellitus (GDM) and related complications have prompted calls to identify potentially modifiable risk factors that are associated with gestational diabetes mellitus (GDM). We systematically reviewed the scientific literature for observational studies examining specific dietary and/or physical activity (PA) factors and risk of GDM. Our search included PubMed, Medline, CINAHL/EBSCO, Science Direct and EMBASE, and identified 1167 articles, of which 40 met our inclusion criteria (e.g., singleton pregnancy, reported diet or PA data during pre-pregnancy/early pregnancy and GDM as an outcome measure). Studies were assessed for quality using a modified Quality Criteria Checklist from American Dietetic Association. Of the final 40 studies, 72% obtained a positive quality rating and 28% were rated neutral. The final analysis incorporated data on 30,871 pregnant women. Dietary studies were categorised into either caffeine, carbohydrate, fat, protein, calcium, fast food and recognized dietary patterns. Diets such as Mediterranean Diet (MedDiet), Dietary Approaches to Stop Hypertension (DASH) diet and Alternate Healthy Eating Index diet (AHEI) were associated with 15­38% reduced relative risk of GDM. In contrast, frequent consumption of potato, meat/processed meats, and protein (% energy) derived from animal sources was associated with an increased risk of GDM. Compared to no PA, any pre-pregnancy or early pregnancy PA was associated with 30% and 21% reduced odds of GDM, respectively. Engaging in >90 min/week of leisure time PA before pregnancy was associated with 46% decreased odds of GDM. We conclude that diets resembling MedDiet/DASH diet as well as higher PA levels before or in early pregnancy were associated with lower risks or odds of GDM respectively. The systematic review was registered at PROSPERO (www.crd.york.ac.uk/PROSPERO) as CRD42016027795.

Hypoglycaemia in cystic fibrosis: An analysis of a single centre adult cystic fibrosis clinic.

BACKGROUND: Hypoglycaemia in cystic fibrosis (CF) is known to occur during oral glucose tolerance tests (OGTT) and continuous glucose monitoring, however demographic, clinical and mechanistic data are limited. The aims of this study were to review patient electronic medical records (EMR) in order to 1) describe patient characteristics of a university teaching hospital CF clinic, 2) determine the prevalence of hypoglycaemia on OGTT and explore associations with demographic and clinical characteristics, and 3) explore patient reported symptoms suggestive of hypoglycaemia documented in the EMR. METHODS: Adults who attended the RPA CF clinic between January 2009 to April 2016 were included in the study. The prevalence of hypoglycaemia on OGTT was determined and clinical and demographic data were compared to age, sex and glucose tolerance matched controls. Reported symptoms suggestive of hypoglycaemia documented in EMR were qualitatively explored. RESULTS: Hypoglycaemia on OGTT was prevalent in 25 (3 fasting and 22 reactive) of 169 patients who had an OGTT. They were heavier, less likely to have pancreatic insufficiency and had a lower insulin response at 2-h. Another 14 patients reported symptoms suggestive of hypoglycaemia in their EMR. No patient appropriately suppressed insulin at 2-h on OGTT. CONCLUSIONS: This study identified two potentially different presentations of hypoglycaemia occur in different clinic sub-populations. Knowledge gaps in the aetiology and triggers of hypoglycaemia remain.