A Series of Systematic Reviews and Meta-analyses of the Effect of Vegetarian/Vegan Diets on Cardiometabolic Risk

Diabetes Clinical Trial

Official title: Effect of Vegetarian/Vegan Diets on Cardiometabolic Risk: Systematic Reviews and Meta-analyses of Randomized Controlled Dietary Trials to Provide Evidence-based Guidance for Nutrition Guidelines Development

Status Active, not recruiting

Clinical Trial Summary

Vegetarian and vegan diets have been shown to reduce chronic disease risk, including diabetes and cardiovascular disease, as well as several cardiometabolic risk factors. Whether vegetarian and/or vegan dietary patterns improve cardiometabolic risk factors in individuals with diabetes remains unclear. To address the uncertainties, the investigators propose to conduct a series of systematic reviews and meta-analyses of the totality of the evidence from randomized controlled trials to distinguish the effect of vegetarian and/or vegan diets on the prevention and management of diabetes. The findings generated by this proposed knowledge synthesis will help improve the health of consumers through informing evidence-based guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design

Clinical Trial Description

Background: Vegetarian and/or vegan dietary patterns have been shown in prospective cohort and cross-sectional studies to be associated with lower diabetes risk and all-cause mortality. Evidence from systematic reviews and meta-analyses of controlled trials also suggest that vegetarian diets may be beneficial for glycemic control, blood lipids, weight loss, and blood pressure. On the contrary, evidence from previous meta-analyses of prospective cohort studies, as well as more recent prospective cohort studies have shown that diets higher in animal protein, specifically in red meat, are associated with an increased incidence of T2D. The effect of following a vegetarian/vegan dietary pattern on cardiometabolic risk factors in individuals with diabetes is less clear. Furthermore, not all diabetes guidelines recommend following a vegetarian and/or vegan dietary pattern for the management of diabetes or they provide a low-grade evidence rating.

Need for proposed research: High quality systematic reviews and meta-analyses of randomized controlled trials represent the highest level of evidence to support dietary guidelines and public health policy development. As dietary guidelines and public health policy have shifted toward food and dietary-pattern based recommendations, there is a need for systematic reviews and meta-analyses comparing the role of vegetarian/vegan diets in the prevention and management of diabetes.

Objective: To improve evidence-based guidance for diabetes guidelines and public health policy development, the investigators will conduct a series of systematic reviews and meta-analyses of the effects of vegetarian/vegan diets on cardiometabolic risk factors in individuals with diabetes including measures of (1) glycemic control, (2) blood lipids, (3) adiposity and (4) blood pressure.

Design: Each systematic review and meta-analysis will be conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms supplemented by manual searches of references of included studies.

Study selection: Dietary randomized controlled trials conducted in humans with a follow-up duration ≥ 3 weeks investigating the effect of vegetarian/vegan diets on measures of (1) glycemic control, (2) blood lipids, (3) adiposity, and (4) blood pressure will be included. Studies that are not conducted in humans, not randomized, have an acute feeding design (<3 weeks), lack a suitable control (non-isocaloric) and/or do not report viable endpoint data will not be included.

Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Cochrane Risk of Bias Tool. All disagreements will be resolved by consensus. Standard computations and imputations will be used to derive missing variance data.

Outcomes: The proposed syntheses will each assess a set of outcomes related to a different area of cardiometabolic risk: (1) glycemic control (HbA1c, fasting glucose, fasting insulin), (2) blood lipids (LDL-C, non-HDL-C, HDL-C, triglycerides), (3) adiposity (body weight, BMI, waist circumference), (4) blood pressure (systolic and diastolic blood pressure).

Data synthesis: Separate pooled analyses will be conducted for each area of cardiometabolic control using the Generic Inverse Variance method. Random-effects models will be used even in the absence of statistically significant between-study heterogeneity, as they yield more conservative summary effect estimates in the presence of residual heterogeneity. Exceptions will be made for the use of fixed-effects models where there is <5 included trials irrespective of heterogeneity or small trials are being pooled with larger more precise trials in the absence of statistically significant heterogeneity. Paired analyses will be applied to all crossover trials. Heterogeneity will be tested by Cochran's Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, the investigators will conduct sensitivity analyses, in which each study is systematically removed. If there are >=10 studies, then the investigators will also explore sources of heterogeneity by a priori subgroup analyses by study design (parallel or crossover), follow-up duration (<12 weeks or ≥12 weeks), comparator diet, baseline measurements, risk of bias and diabetes duration. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses (e.g. age, sex, level of feeding control [metabolic, supplemented, dietary advice], washout in crossover trials, energy balance of the background diet, composition of the background diet [total % energy from fat, carbohydrate, protein], change in cholesterol intake, change in glycemic index, etc.). Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. When >=10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger and Begg tests. If publication bias is suspected, then the investigators will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method.

Evidence assessment: The strength of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).

Knowledge translation plan: The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Target audiences will include the public health and scientific communities with interest in nutrition, diabetes, obesity, and cardiovascular disease. Feedback will be incorporated and used to improve the public health message and key areas for future research will be defined. Applicant/Co-applicant Decision Makers will network among opinion leaders to increase awareness and participate directly as committee members in the development of future guidelines.

Significance: The proposed project will aid in knowledge translation related to the role of vegetarian/vegan diets in the prevention and management of diabetes, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design. ;

Study Design

Time Perspective: Prospective

Related Conditions & MeSH terms

• Diabetes

• NCT number: NCT02600377
• Study type: Observational
• Source: University of Toronto
• Status: Active, not recruiting
• Phase: N/A
• Start date: November 2015
• Completion date: November 2016