Relation of total sugars, fructose and sucrose with incident type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies.

BACKGROUND: Sugar-sweetened beverages are associated with type 2 diabetes. To assess whether this association holds for the fructose-containing sugars they contain, we conducted a systematic review and meta-analysis of prospective cohort studies. METHODS: We searched MEDLINE, Embase, CINAHL and the Cochrane Library (through June 2016). We included prospective cohort studies that assessed the relation of fructose-containing sugars with incident type 2 diabetes. Two independent reviewers extracted relevant data and assessed risk of bias. We pooled risk ratios (RRs) using random effects meta-analyses. The overall quality of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. RESULTS: Fiffeen prospective cohort studies (251 261 unique participants, 16 416 cases) met the eligibility criteria, comparing the highest intake (median 137, 35.2 and 78 g/d) with the lowest intake (median 65, 9.7 and 25.8 g/d) of total sugars, fructose and sucrose, respectively. Although there was no association of total sugars (RR 0.91, 95% confidence interval [CI] 0.76-1.09) or fructose (RR 1.04, 95% CI 0.84-1.29) with type 2 diabetes, sucrose was associated with a decreased risk of type 2 diabetes (RR 0.89, 95% CI 0.80-0.98). Our confidence in the estimates was limited by evidence of serious inconsistency between studies for total sugars and fructose, and serious imprecision in the pooled estimates for all 3 sugar categories. INTERPRETATION: Current evidence does not allow us to conclude that fructose-containing sugars independent of food form are associated with increased risk of type 2 diabetes. Further research is likely to affect our estimates. TRIAL REGISTRATION: ClinicalTrials.gov, no. NCT01608620.

Fructose vs. glucose and metabolism: do the metabolic differences matter?

PURPOSE OF REVIEW: Fructose is seen as uniquely contributing to the pandemics of obesity and its cardiometabolic complications. Much of the evidence for this view derives from the unique biochemical, metabolic, and endocrine responses that differentiate fructose from glucose. To understand whether these proposed mechanisms result in clinically meaningful modification of cardiovascular risk in humans, we update a series of systematic reviews and meta-analyses of controlled feeding trials to assess the cardiometabolic effects of fructose in isocaloric replacement for glucose. RECENT FINDINGS: A total of 20 controlled feeding trials (n = 344) have investigated the effect of fructose in/on cardiometabolic endpoints. Pooled analyses show that although fructose may increase total cholesterol, uric acid, and postprandial triglycerides in isocaloric replacement for glucose, it does not appear to be any worse than glucose in its effects on other aspects of the lipid profile, insulin, or markers of nonalcoholic fatty liver disease. It may also have important advantages over glucose for body weight, glycemic control, and blood pressure. SUMMARY: Depending on the cardiometabolic endpoint in question, fructose has variable effects when replacing glucose. In the absence of clear evidence of net harm, there is no justification to replace fructose with glucose in the diet.

Fructose-containing sugars, blood pressure, and cardiometabolic risk: a critical review.

Excessive fructose intake from high-fructose corn syrup (HFCS) and sucrose has been implicated as a driving force behind the increasing prevalence of obesity and its downstream cardiometabolic complications including hypertension, gout, dyslidpidemia, metabolic syndrome, diabetes, and non-alcoholic fatty liver disease (NAFLD). Most of the evidence to support these relationships draws heavily on ecological studies, animal models, and select human trials of fructose overfeeding. There are a number of biological mechanisms derived from animal models to explain these relationships, including increases in de novo lipogenesis and uric acid-mediated hypertension. Differences between animal and human physiology, along with the supraphysiologic level at which fructose is fed in these models, limit their translation to humans. Although higher level evidence from large prospective cohorts studies has shown significant positive associations comparing the highest with the lowest levels of intake of sugar-sweetened beverages (SSBs), these associations do not hold true at moderate levels of intake or when modeling total sugars and are subject to collinearity effects from related dietary and lifestyle factors. The highest level of evidence from controlled feeding trials has shown a lack of cardiometabolic harm of fructose and SSBs under energy-matched conditions at moderate levels of intake. It is only when fructose-containing sugars or SSBs are consumed at high doses or supplement diets with excess energy that a consistent signal for harm is seen. The available evidence suggests that confounding by excess energy is an important consideration in assessing the role of fructose-containing sugars and SSBs in the epidemics of hypertension and other cardiometabolic diseases.

The effects of fructose intake on serum uric acid vary among controlled dietary trials.

Hyperuricemia is linked to gout and features of metabolic syndrome. There is concern that dietary fructose may increase uric acid concentrations. To assess the effects of fructose on serum uric acid concentrations in people with and without diabetes, we conducted a systematic review and meta-analysis of controlled feeding trials. We searched MEDLINE, EMBASE, and the Cochrane Library for relevant trials (through August 19, 2011). Analyses included all controlled feeding trials ≥ 7 d investigating the effect of fructose feeding on uric acid under isocaloric conditions, where fructose was isocalorically exchanged with other carbohydrate, or hypercaloric conditions, and where a control diet was supplemented with excess energy from fructose. Data were aggregated by the generic inverse variance method using random effects models and expressed as mean difference (MD) with 95% CI. Heterogeneity was assessed by the Q statistic and quantified by I(2). A total of 21 trials in 425 participants met the eligibility criteria. Isocaloric exchange of fructose for other carbohydrate did not affect serum uric acid in diabetic and nondiabetic participants [MD = 0.56 µmol/L (95% CI: -6.62, 7.74)], with no evidence of inter-study heterogeneity. Hypercaloric supplementation of control diets with fructose (+35% excess energy) at extreme doses (213-219 g/d) significantly increased serum uric acid compared with the control diets alone in nondiabetic participants [MD = 31.0 mmol/L (95% CI: 15.4, 46.5)] with no evidence of heterogeneity. Confounding from excess energy cannot be ruled out in the hypercaloric trials. These analyses do not support a uric acid-increasing effect of isocaloric fructose intake in nondiabetic and diabetic participants. Hypercaloric fructose intake may, however, increase uric acid concentrations. The effect of the interaction of energy and fructose remains unclear. Larger, well-designed trials of fructose feeding at "real world" doses are needed.

'Catalytic' doses of fructose may benefit glycaemic control without harming cardiometabolic risk factors: a small meta-analysis of randomised controlled feeding trials.

Contrary to concerns that fructose may have adverse metabolic effects, there is evidence that small, 'catalytic' doses ( ≤ 10 g/meal) of fructose decrease the glycaemic response to high-glycaemic index meals in human subjects. To assess the longer-term effects of 'catalytic' doses of fructose, we undertook a meta-analysis of controlled feeding trials. We searched MEDLINE, EMBASE, CINAHL and the Cochrane Library. Analyses included all controlled feeding trials ≥ 7 d featuring 'catalytic' fructose doses ( ≤ 36 g/d) in isoenergetic exchange for other carbohydrates. Data were pooled by the generic inverse variance method using random-effects models and expressed as mean differences (MD) with 95 % CI. Heterogeneity was assessed by the Q statistic and quantified by I 2. The Heyland Methodological Quality Score assessed study quality. A total of six feeding trials (n 118) met the eligibility criteria. 'Catalytic' doses of fructose significantly reduced HbA1c (MD - 0·40, 95 % CI - 0·72, - 0·08) and fasting glucose (MD - 0·25, 95 % CI - 0·44, - 0·07). This benefit was seen in the absence of adverse effects on fasting insulin, body weight, TAG or uric acid. Subgroup and sensitivity analyses showed evidence of effect modification under certain conditions. The small number of trials and their relatively short duration limit the strength of the conclusions. In conclusion, this small meta-analysis shows that 'catalytic' fructose doses ( ≤ 36 g/d) may improve glycaemic control without adverse effects on body weight, TAG, insulin and uric acid. There is a need for larger, longer ( ≥ 6 months) trials using 'catalytic' fructose to confirm these results.

Explainable artificial intelligence to predict the risk of side-specific extraprostatic extension in pre-prostatectomy patients.

INTRODUCTION: We aimed to develop an explainable machine learning (ML) model to predict side-specific extraprostatic extension (ssEPE) to identify patients who can safely undergo nerve-sparing radical prostatectomy using preoperative clinicopathological variables. METHODS: A retrospective sample of clinicopathological data from 900 prostatic lobes at our institution was used as the training cohort. Primary outcome was the presence of ssEPE. The baseline model for comparison had the highest performance out of current biopsy-derived predictive models for ssEPE. A separate logistic regression (LR) model was built using the same variables as the ML model. All models were externally validated using a testing cohort of 122 lobes from another institution. Models were assessed by area under receiver-operating-characteristic curve (AUROC), precision-recall curve (AUPRC), calibration, and decision curve analysis. Model predictions were explained using SHapley Additive exPlanations. This tool was deployed as a publicly available web application. RESULTS: Incidence of ssEPE in the training and testing cohorts were 30.7 and 41.8%, respectively. The ML model achieved AUROC 0.81 (LR 0.78, baseline 0.74) and AUPRC 0.69 (LR 0.64, baseline 0.59) on the training cohort. On the testing cohort, the ML model achieved AUROC 0.81 (LR 0.76, baseline 0.75) and AUPRC 0.78 (LR 0.75, baseline 0.70). The ML model was explainable, well-calibrated, and achieved the highest net benefit for clinically relevant cutoffs of 10-30%. CONCLUSIONS: We developed a user-friendly application that enables physicians without prior ML experience to assess ssEPE risk and understand factors driving these predictions to aid surgical planning and patient counselling (https://share.streamlit.io/jcckwong/ssepe/main/ssEPE_V2.py).

Food sources of fructose-containing sugars and glycaemic control: systematic review and meta-analysis of controlled intervention studies.

OBJECTIVE: To assess the effect of different food sources of fructose-containing sugars on glycaemic control at different levels of energy control. DESIGN: Systematic review and meta-analysis of controlled intervention studies. DATA SOURCES: Medine, Embase, and the Cochrane Library up to 25 April 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Controlled intervention studies of at least seven days' duration and assessing the effect of different food sources of fructose-containing sugars on glycaemic control in people with and without diabetes were included. Four study designs were prespecified on the basis of energy control: substitution studies (sugars in energy matched comparisons with other macronutrients), addition studies (excess energy from sugars added to diets), subtraction studies (energy from sugars subtracted from diets), and ad libitum studies (sugars freely replaced by other macronutrients without control for energy). Outcomes were glycated haemoglobin (HbA1c), fasting blood glucose, and fasting blood glucose insulin. DATA EXTRACTION AND SYNTHESIS: Four independent reviewers extracted relevant data and assessed risk of bias. Data were pooled by random effects models and overall certainty of the evidence assessed by the GRADE approach (grading of recommendations assessment, development, and evaluation). RESULTS: 155 study comparisons (n=5086) were included. Total fructose-containing sugars had no harmful effect on any outcome in substitution or subtraction studies, with a decrease seen in HbA1c in substitution studies (mean difference -0.22% (95% confidence interval to -0.35% to -0.08%), -25.9 mmol/mol (-27.3 to -24.4)), but a harmful effect was seen on fasting insulin in addition studies (4.68 pmol/L (1.40 to 7.96)) and ad libitum studies (7.24 pmol/L (0.47 to 14.00)). There was interaction by food source, with specific food sources showing beneficial effects (fruit and fruit juice) or harmful effects (sweetened milk and mixed sources) in substitution studies and harmful effects (sugars-sweetened beverages and fruit juice) in addition studies on at least one outcome. Most of the evidence was low quality. CONCLUSIONS: Energy control and food source appear to mediate the effect of fructose-containing sugars on glycaemic control. Although most food sources of these sugars (especially fruit) do not have a harmful effect in energy matched substitutions with other macronutrients, several food sources of fructose-containing sugars (especially sugars-sweetened beverages) adding excess energy to diets have harmful effects. However, certainty in these estimates is low, and more high quality randomised controlled trials are needed. STUDY REGISTRATION: Clinicaltrials.gov (NCT02716870).

Effects of dietary pulse consumption on body weight: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Obesity is a risk factor for developing several diseases, and although dietary pulses (nonoil seeds of legumes such as beans, lentils, chickpeas, and dry peas) are well positioned to aid in weight control, the effects of dietary pulses on weight loss are unclear. OBJECTIVE: We summarized and quantified the effects of dietary pulse consumption on body weight, waist circumference, and body fat by conducting a systematic review and meta-analysis of randomized controlled trials. DESIGN: We searched the databases MEDLINE, Embase, CINAHL, and the Cochrane Library through 11 May 2015 for randomized controlled trials of ≥3 wk of duration that compared the effects of diets containing whole dietary pulses with those of comparator diets without a dietary pulse intervention. Study quality was assessed by means of the Heyland Methodologic Quality Score, and risk of bias was assessed with the Cochrane Risk of Bias tool. Data were pooled with the use of generic inverse-variance random-effects models. RESULTS: Findings from 21 trials (n = 940 participants) were included in the meta-analysis. The pooled analysis showed an overall significant weight reduction of -0.34 kg (95% CI: -0.63, -0.04 kg; P = 0.03) in diets containing dietary pulses (median intake of 132 g/d or ∼1 serving/d) compared with diets without a dietary pulse intervention over a median duration of 6 wk. Significant weight loss was observed in matched negative-energy-balance (weight loss) diets (P = 0.02) and in neutral-energy-balance (weight-maintaining) diets (P = 0.03), and there was low evidence of between-study heterogeneity. Findings from 6 included trials also suggested that dietary pulse consumption may reduce body fat percentage. CONCLUSIONS: The inclusion of dietary pulses in a diet may be a beneficial weight-loss strategy because it leads to a modest weight-loss effect even when diets are not intended to be calorically restricted. Future studies are needed to determine the effects of dietary pulses on long-term weight-loss sustainability. This protocol was registered at clinicaltrials.gov as NCT01594567.

Intake of saturated and trans unsaturated fatty acids and risk of all cause mortality, cardiovascular disease, and type 2 diabetes: systematic review and meta-analysis of observational studies.

OBJECTIVE: To systematically review associations between intake of saturated fat and trans unsaturated fat and all cause mortality, cardiovascular disease (CVD) and associated mortality, coronary heart disease (CHD) and associated mortality, ischemic stroke, and type 2 diabetes. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, Embase, Cochrane Central Registry of Controlled Trials, Evidence-Based Medicine Reviews, and CINAHL from inception to 1 May 2015, supplemented by bibliographies of retrieved articles and previous reviews. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Observational studies reporting associations of saturated fat and/or trans unsaturated fat (total, industrially manufactured, or from ruminant animals) with all cause mortality, CHD/CVD mortality, total CHD, ischemic stroke, or type 2 diabetes. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data and assessed study risks of bias. Multivariable relative risks were pooled. Heterogeneity was assessed and quantified. Potential publication bias was assessed and subgroup analyses were undertaken. The GRADE approach was used to evaluate quality of evidence and certainty of conclusions. RESULTS: For saturated fat, three to 12 prospective cohort studies for each association were pooled (five to 17 comparisons with 90,501-339,090 participants). Saturated fat intake was not associated with all cause mortality (relative risk 0.99, 95% confidence interval 0.91 to 1.09), CVD mortality (0.97, 0.84 to 1.12), total CHD (1.06, 0.95 to 1.17), ischemic stroke (1.02, 0.90 to 1.15), or type 2 diabetes (0.95, 0.88 to 1.03). There was no convincing lack of association between saturated fat and CHD mortality (1.15, 0.97 to 1.36; P=0.10). For trans fats, one to six prospective cohort studies for each association were pooled (two to seven comparisons with 12,942-230,135 participants). Total trans fat intake was associated with all cause mortality (1.34, 1.16 to 1.56), CHD mortality (1.28, 1.09 to 1.50), and total CHD (1.21, 1.10 to 1.33) but not ischemic stroke (1.07, 0.88 to 1.28) or type 2 diabetes (1.10, 0.95 to 1.27). Industrial, but not ruminant, trans fats were associated with CHD mortality (1.18 (1.04 to 1.33) v 1.01 (0.71 to 1.43)) and CHD (1.42 (1.05 to 1.92) v 0.93 (0.73 to 1.18)). Ruminant trans-palmitoleic acid was inversely associated with type 2 diabetes (0.58, 0.46 to 0.74). The certainty of associations between saturated fat and all outcomes was "very low." The certainty of associations of trans fat with CHD outcomes was "moderate" and "very low" to "low" for other associations. CONCLUSIONS: Saturated fats are not associated with all cause mortality, CVD, CHD, ischemic stroke, or type 2 diabetes, but the evidence is heterogeneous with methodological limitations. Trans fats are associated with all cause mortality, total CHD, and CHD mortality, probably because of higher levels of intake of industrial trans fats than ruminant trans fats. Dietary guidelines must carefully consider the health effects of recommendations for alternative macronutrients to replace trans fats and saturated fats.

Effect of Fructose on Established Lipid Targets: A Systematic Review and Meta-Analysis of Controlled Feeding Trials.

BACKGROUND: Debate over the role of fructose in mediating cardiovascular risk remains active. To update the evidence on the effect of fructose on established therapeutic lipid targets for cardiovascular disease (low-density lipoprotein cholesterol [LDL]-C, apolipoprotein B, non-high-density lipoprotein cholesterol [HDL-C]), and metabolic syndrome (triglycerides and HDL-C), we conducted a systematic review and meta-analysis of controlled feeding trials. METHODS AND RESULTS: MEDLINE, EMBASE, CINHAL, and the Cochrane Library were searched through July 7, 2015 for controlled feeding trials with follow-up ≥7 days, which investigated the effect of oral fructose compared to a control carbohydrate on lipids (LDL-C, apolipoprotein B, non-HDL-C, triglycerides, and HDL-C) in participants of all health backgrounds. Two independent reviewers extracted relevant data. Data were pooled using random effects models and expressed as mean difference with 95% CI. Interstudy heterogeneity was assessed (Cochran Q statistic) and quantified (I(2) statistic). Eligibility criteria were met by 51 isocaloric trials (n=943), in which fructose was provided in isocaloric exchange for other carbohydrates, and 8 hypercaloric trials (n=125), in which fructose supplemented control diets with excess calories compared to the control diets alone without the excess calories. Fructose had no effect on LDL-C, non-HDL-C, apolipoprotein B, triglycerides, or HDL-C in isocaloric trials. However, in hypercaloric trials, fructose increased apolipoprotein B (n=2 trials; mean difference = 0.18 mmol/L; 95% CI: 0.05, 0.30; P=0.005) and triglycerides (n=8 trials; mean difference = 0.26 mmol/L; 95% CI: 0.11, 0.41; P<0.001). The study is limited by small sample sizes, limited follow-up, and low quality scores of the included trials. CONCLUSIONS: Pooled analyses showed that fructose only had an adverse effect on established lipid targets when added to existing diets so as to provide excess calories (+21% to 35% energy). When isocalorically exchanged for other carbohydrates, fructose had no adverse effects on blood lipids. More trials that are larger, longer, and higher quality are required. CLINICAL TRIALS REGISTRATION: URL: https://www.clinicaltrials.gov/. Unique Identifier: NCT01363791.

The Role of Fructose, Sucrose and High-fructose Corn Syrup in Diabetes.

Concerns are growing regarding the role of dietary sugars in the development of obesity and cardiometabolic diseases, including diabetes. High-fructose corn syrup (HFCS) and sucrose are the most important dietary sweeteners. Both HFCS and sucrose have overlapping metabolic actions with adverse effects attributed to their fructose moiety. Ecological studies have linked the rise in fructose availability with the increases in obesity and diabetes worldwide. This link has been largely underpinned by animal models and select human trials of fructose overfeeding at high levels of exposure. Although prospective cohort studies have shown significant associations comparing the highest with the lowest levels of intake sugar-sweetened beverages, these associations are small, do not hold at moderate levels of intake and are subject to collinearity effects from related dietary and lifestyle factors. Most systematic reviews and meta-analyses from controlled feeding trials have shown that fructose-containing sugars in isocaloric exchange for other carbohydrates do not show evidence of harm and, in the case of fructose, may even have advantages for glycaemic control, especially at small doses. Nevertheless, trials in which fructose-containing sugars supplement diets with excess energy have shown adverse effects, effects that appear more attributable to the excess energy than the sugar. There is no unequivocal evidence that fructose intake at moderate doses is directly related with adverse metabolic effects, although there is potentially cause for concern where fructose is provided at high doses or contributes excess energy to diets. Further investigation is warranted due to the significant knowledge gaps and weaknesses in existing research.

The effect of ginseng (the genus panax) on glycemic control: a systematic review and meta-analysis of randomized controlled clinical trials.

IMPORTANCE: Despite the widespread use of ginseng in the management of diabetes, supporting evidence of its anti-hyperglycemic efficacy is limited, necessitating the need for evidence-based recommendations for the potential inclusion of ginseng in diabetes management. OBJECTIVE: To elucidate the effect of ginseng on glycemic control in a systematic review and meta-analysis of randomized controlled trials in people with and without diabetes. DATA SOURCES: MEDLINE, EMBASE, CINAHL and the Cochrane Library (through July 3, 2013). STUDY SELECTION: Randomized controlled trials ≥30 days assessing the glycemic effects of ginseng in people with and without diabetes. DATA EXTRACTION: Relevant data were extracted by 2 independent reviewers. Discrepancies were resolved by consensus. The Heyland Methodological Quality Score and the Cochrane risk of bias tool were used to assess study quality and risk of bias respectively. DATA SYNTHESIS: Sixteen trials were included, in which 16 fasting blood glucose (n = 770), 10 fasting plasma insulin (n = 349), 9 glycated hemoglobin (n = 264), and 7 homeostasis model assessment of insulin resistance (n = 305) comparisons were reported. Ginseng significantly reduced fasting blood glucose compared to control (MD =  -0.31 mmol/L [95% CI: -0.59 to -0.03], P = 0.03). Although there was no significant effect on fasting plasma insulin, glycated hemoglobin, or homeostasis model assessment of insulin resistance, a priori subgroup analyses did show significant reductions in glycated hemoglobin in parallel compared to crossover trials (MD = 0.22% [95%CI: 0.06 to 0.37], P = 0.01). LIMITATIONS: Most trials were of short duration (67% trials<12wks), and included participants with a relatively good glycemic control (median HbA1c non-diabetes = 5.4% [2 trials]; median HbA1c diabetes = 7.1% [7 trials]). CONCLUSIONS: Ginseng modestly yet significantly improved fasting blood glucose in people with and without diabetes. In order to address the uncertainty in our effect estimates and provide better assessments of ginseng's anti-diabetic efficacy, larger and longer randomized controlled trials using standardized ginseng preparations are warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT01841229.

Dietary pulses, satiety and food intake: a systematic review and meta-analysis of acute feeding trials.

OBJECTIVE: To assess the effect of dietary pulses (beans, peas, chickpeas, lentils) on acute satiety and second meal intake, a systematic review and meta-analysis was conducted. METHODS: MEDLINE, EMBASE, CINAHL, and the Cochrane Registry (through May 6, 2013) were searched for acute controlled trials examining the effect of dietary pulses on postprandial satiety or second meal intake compared with isocaloric controls. Two independent reviewers extracted data and assessed methodological quality and risk of bias. Data were pooled by generic inverse variance random effects models and expressed as ratio of means (RoMs) for satiety and mean differences (MDs) for second meal food intake, with 95% confidence intervals (95% CIs). Heterogeneity was assessed (Q statistic) and quantified (I(2) statistic). Protocol registration: clinicaltrials.gov identifier, NCT01605422. RESULTS: Nine trials met the eligibility criteria. Dietary pulses produced a 31% greater satiety incremental area under the curve (IAUC) (RoM = 1.31, 95% CI: 1.09 to 1.58, P = 0.004; Phet = 0.96; I(2) = 0%) without affecting second meal intake (MD = -19.94, 95% CI: -75-35, P = 0.48; Phet = 0.01; I(2) = 63%). Our data are limited by the small sample sizes, narrow participant characteristics and significant unexplained heterogeneity among the available trials. CONCLUSIONS: Pooled analyses show that dietary pulses contribute to acute satiety but not second meal intake.

Effect of tree nuts on glycemic control in diabetes: a systematic review and meta-analysis of randomized controlled dietary trials.

BACKGROUND: Tree nut consumption has been associated with reduced diabetes risk, however, results from randomized trials on glycemic control have been inconsistent. OBJECTIVE: To provide better evidence for diabetes guidelines development, we conducted a systematic review and meta-analysis of randomized controlled trials to assess the effects of tree nuts on markers of glycemic control in individuals with diabetes. DATA SOURCES: MEDLINE, EMBASE, CINAHL, and Cochrane databases through 6 April 2014. STUDY SELECTION: Randomized controlled trials ≥3 weeks conducted in individuals with diabetes that compare the effect of diets emphasizing tree nuts to isocaloric diets without tree nuts on HbA1c, fasting glucose, fasting insulin, and HOMA-IR. DATA EXTRACTION AND SYNTHESIS: Two independent reviewer's extracted relevant data and assessed study quality and risk of bias. Data were pooled by the generic inverse variance method and expressed as mean differences (MD) with 95% CI's. Heterogeneity was assessed (Cochran Q-statistic) and quantified (I2). RESULTS: Twelve trials (n = 450) were included. Diets emphasizing tree nuts at a median dose of 56 g/d significantly lowered HbA1c (MD = -0.07% [95% CI:-0.10, -0.03%]; P = 0.0003) and fasting glucose (MD = -0.15 mmol/L [95% CI: -0.27, -0.02 mmol/L]; P = 0.03) compared with control diets. No significant treatment effects were observed for fasting insulin and HOMA-IR, however the direction of effect favoured tree nuts. LIMITATIONS: Majority of trials were of short duration and poor quality. CONCLUSIONS: Pooled analyses show that tree nuts improve glycemic control in individuals with type 2 diabetes, supporting their inclusion in a healthy diet. Owing to the uncertainties in our analyses there is a need for longer, higher quality trials with a focus on using nuts to displace high-glycemic index carbohydrates. TRIAL REGISTRATION: ClinicalTrials.gov NCT01630980.

Effect of tree nuts on metabolic syndrome criteria: a systematic review and meta-analysis of randomised controlled trials.

OBJECTIVE: To provide a broader evidence summary to inform dietary guidelines of the effect of tree nuts on criteria of the metabolic syndrome (MetS). DESIGN: We conducted a systematic review and meta-analysis of the effect of tree nuts on criteria of the MetS. DATA SOURCES: We searched MEDLINE, EMBASE, CINAHL and the Cochrane Library (through 4 April 2014). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included relevant randomised controlled trials (RCTs) of ≥3 weeks reporting at least one criterion of the MetS. DATA EXTRACTION: Two or more independent reviewers extracted all relevant data. Data were pooled using the generic inverse variance method using random effects models and expressed as mean differences (MD) with 95% CIs. Heterogeneity was assessed by the Cochran Q statistic and quantified by the I(2) statistic. Study quality and risk of bias were assessed. RESULTS: Eligibility criteria were met by 49 RCTs including 2226 participants who were otherwise healthy or had dyslipidaemia, MetS or type 2 diabetes mellitus. Tree nut interventions lowered triglycerides (MD=-0.06 mmol/L (95% CI -0.09 to -0.03 mmol/L)) and fasting blood glucose (MD=-0.08 mmol/L (95% CI -0.16 to -0.01 mmol/L)) compared with control diet interventions. There was no effect on waist circumference, high-density lipoprotein cholesterol or blood pressure with the direction of effect favouring tree nuts for waist circumference. There was evidence of significant unexplained heterogeneity in all analyses (p<0.05). CONCLUSIONS: Pooled analyses show a MetS benefit of tree nuts through modest decreases in triglycerides and fasting blood glucose with no adverse effects on other criteria across nut types. As our conclusions are limited by the short duration and poor quality of the majority of trials, as well as significant unexplained between-study heterogeneity, there remains a need for larger, longer, high-quality trials. TRIAL REGISTRATION NUMBER: NCT01630980.

Effect of fructose on postprandial triglycerides: a systematic review and meta-analysis of controlled feeding trials.

BACKGROUND: In the absence of consistent clinical evidence, concerns have been raised that fructose raises postprandial triglycerides. PURPOSE: A systematic review and meta-analysis was conducted to assess the effect of fructose on postprandial triglycerides. DATA SOURCES: Relevant studies were identified from MEDLINE, EMBASE, and Cochrane databases (through September 3, 2013). DATA SELECTION: Relevant clinical trials of ≥ 7-days were included in the analysis. DATA EXTRACTION: Two independent reviewers extracted relevant data with disagreements reconciled by consensus. The Heyland Methodological Quality Score (MQS) assessed study quality. Data were pooled by the generic inverse variance method using random effects models and expressed as standardized mean differences (SMD) with 95% confidence intervals (CI). Heterogeneity was assessed (Cochran Q statistic) and quantified (I(2) statistic). DATA SYNTHESIS: Eligibility criteria were met by 14 isocaloric trials (n = 290), in which fructose was exchanged isocalorically for other carbohydrate in the diet, and two hypercaloric trials (n = 33), in which fructose supplemented the background diet with excess energy from high-dose fructose compared with the background diet alone (without the excess energy). There was no significant effect in the isocaloric trials (SMD: 0.14 [95% CI: -0.02, 0.30]) with evidence of considerable heterogeneity explained by a single trial. Hypercaloric trials, however, showed a significant postprandial triglyceride raising-effect of fructose (SMD: 0.65 [95% CI: 0.30, 1.01]). LIMITATIONS: Most of the available trials were small, short, and of poor quality. Interpretation of the isocaloric trials is complicated by the large influence of a single trial. CONCLUSIONS: Pooled analyses show that fructose in isocaloric exchange for other carbohydrate does not increase postprandial triglycerides, although an effect cannot be excluded under all conditions. Fructose providing excess energy does increase postprandial triglycerides. Larger, longer, and higher-quality trials are needed. PROTOCOL REGISTRATION: ClinicalTrials.gov identifier, NCT01363791.

Effect of fructose on glycemic control in diabetes: a systematic review and meta-analysis of controlled feeding trials.

OBJECTIVE: The effect of fructose on cardiometabolic risk in humans is controversial. We conducted a systematic review and meta-analysis of controlled feeding trials to clarify the effect of fructose on glycemic control in individuals with diabetes. RESEARCH DESIGN AND METHODS: We searched MEDLINE, EMBASE, and the Cochrane Library (through 22 March 2012) for relevant trials lasting ≥7 days. Data were aggregated by the generic inverse variance method (random-effects models) and expressed as mean difference (MD) for fasting glucose and insulin and standardized MD (SMD) with 95% CI for glycated hemoglobin (HbA(1c)) and glycated albumin. Heterogeneity was assessed by the Cochran Q statistic and quantified by the I(2) statistic. Trial quality was assessed by the Heyland methodological quality score (MQS). RESULTS: Eighteen trials (n = 209) met the eligibility criteria. Isocaloric exchange of fructose for carbohydrate reduced glycated blood proteins (SMD -0.25 [95% CI -0.46 to -0.04]; P = 0.02) with significant intertrial heterogeneity (I(2) = 63%; P = 0.001). This reduction is equivalent to a ~0.53% reduction in HbA(1c). Fructose consumption did not significantly affect fasting glucose or insulin. A priori subgroup analyses showed no evidence of effect modification on any end point. CONCLUSIONS: Isocaloric exchange of fructose for other carbohydrate improves long-term glycemic control, as assessed by glycated blood proteins, without affecting insulin in people with diabetes. Generalizability may be limited because most of the trials were <12 weeks and had relatively low MQS (<8). To confirm these findings, larger and longer fructose feeding trials assessing both possible glycemic benefit and adverse metabolic effects are required.

Effect of fructose on blood pressure: a systematic review and meta-analysis of controlled feeding trials.

Concerns have been raised about the adverse effect of fructose on blood pressure. International dietary guidelines, however, have not addressed fructose intake directly. A systematic review and meta-analysis was conducted to assess the effect of fructose in isocaloric exchange for other carbohydrates on systolic, diastolic, and mean arterial blood pressures. Studies were identified using Medline, Embase, and Cochrane databases (through January 9, 2012). Human clinical trials of isocaloric oral fructose exchange for other carbohydrate sources for ≥7 days were included in the analysis. Data were pooled by the generic inverse variance method using random-effects models and expressed as mean differences with 95% CI. Heterogeneity was assessed by the Q-statistic and quantified by I(2). Study quality was assessed using the Heyland Methodological Quality Score. Thirteen isocaloric (n=352) and 2 hypercaloric (n=24) trials met the eligibility criteria. Overall, fructose intake in isocaloric exchange for other carbohydrates significantly decreased diastolic (mean difference: -1.54 [95% CI: -2.77 to -0.32]) and mean arterial pressure (mean difference: -1.16 [95% CI: -2.15 to -0.18]). There was no significant effect of fructose on systolic blood pressure (mean difference: -1.10 [95% CI: -2.46 to 0.44]). The hypercaloric fructose feeding trials found no significant overall mean arterial blood pressure effect of fructose in comparison with other carbohydrates. To confirm these results, longer and larger trials are needed. Contrary to previous concerns, we found that isocaloric substitution of fructose for other carbohydrates did not adversely affect blood pressure in humans.