VN: Systematic Review Methods (2024)

VN: Systematic Review Methods (2024)

Methods for the Systematic Review on Vegetarian Nutrition for Disease Management

Systematic Review Objective: To determine the efficacy of vegetarian diets, compared to non-vegetarian diets on outcomes of interest in adults with risk factors for cardiovascular disease (CVD), type 2 diabetes (T2DM) or CVD. 

This systematic review followed methods from the Academy of Nutrition and Dietetics and the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) method and was registered a priori at PROSPERO (CRD42023396453).1,2  

Eligibility Criteria

All included studies examined the effect of vegetarian or vegan diets, compared to non-vegetarian diets or on each other, outcomes of interest in adults with risk of CVD, T2DM or CVD. Studies were required to be randomized controlled trials (RCTs) with at least four weeks duration. A full description of eligibility criteria can be found in the Eligibility Criteria section of the search plan.

Database Search

The database searches were conducted by an information Specialist. The information specialist searched MEDLINE, CINAHL, Cochrane CENTRAL Database of Controlled Trials, Food Science Source and SportsDiscus databases. The search aimed to identify studies that examined vegetarian diets as an intervention and included terms including but not limited to “vegetarian”, “vegan”, “plant-base”, with limits on language (published in the English language), publication date (1998-May 6, 2013) and study design (RCTs). The information specialist documented the search in each database and de-duplicated results. Relevant systematic reviews were searched for potentially included articles not identified in the database search. The full search strategy can be found in Search Plan.

Selection Process

Each title/abstract identified in the search was screened independently by two reviewers using Rayyan software.3 Each potentially included title/abstract advanced to full-text review, and each article was independently assessed by two reviewers to determine eligibility criteria. Any discrepancies in inclusion between reviewers were settled through consensus or a third reviewer.

Data Collection

A standardized data extraction sheet was created to extract data for each article. Data was extracted by trained evidence analysts and included bibliographic information, participant health status and characteristics, and intervention details [eg, sub-category of vegetarian diet, study duration, if the intervention included nutrition counseling or energy restriction, etc.], funding source, and outcomes of interest reported. 

Quantitative data will be extracted for each outcome of interest. Data was extracted for each included study that reported a particular outcome of interest on a standardized template. For continuous variables, analysts extracted mean change and variance for each group (within group change). If within group change was not available, analysts extracted pre- and post- intervention mean and variance. If quantitative results were not reported, corresponding authors were contacted and asked to provide the missing values. If missing values were not provided, study results were described narratively only. If a study reported results for multiple time points, the results closest to the end of the intervention were used in analysis. 

Risk of Bias

Risk of bias was conducted using RoB2: A revised Cochrane risk-of-bias tool for randomized trials.4 Each article was assessed by two trained, independent reviewers and discrepancies were settled through consensus. The RoB2 tool assesses the risk of bias due to the randomization process, deviations from intended interventions, missing outcome data, measurement in the outcome and selection of the reported results. Studies are rated as having low risk, some concerns or high risk of bias.4 

Synthesis of Results

Evidence for each question was summarized for each outcome of interest. For each summary, evidence was described narratively, and a concise conclusion statement was written to directly answer the research question. Certainty of evidence was determined using the GRADE method and a summary of findings table considering study design, number of participants, consistency of findings, effect size, precision of findings, directness of evidence and other factors. Certainty of evidence will be rated as HIGH, MODERATE, LOW or VERY LOW.2 Risk of bias will be described in a figure produced by robvis.5 

When possible, each outcome was analyzed in meta-analysis using a random-effects model due to heterogeneity in diets and populations between studies. Mean change (within group differences) for each group was imputed to determine mean difference (95% confidence interval) for continuous variables. Differences in change between groups was reported on a forest plot. Publication bias was assessed using a funnel plot and Begg’s and Egger’s statistics for outcomes with at least ten studies included. Heterogeneity will be measured using the I2 measure. Mets-analyses and publication bias was conducted using OpenMeta Analyst and RStudio software.6,7 Sub-group analyses was conducted for each outcome for which at least five RCTs are included. Subgroup and sensitivity analyses were specified a priori and included type of vegetarian diet, comparison group, if nutrition counseling and energy restriction were included in the intervention, study duration and study quality.  


  1. Handu D, Moloney L, Wolfram T, Ziegler P, Acosta A, Steiber A. Academy of Nutrition and Dietetics Methodology for Conducting Systematic Reviews for the Evidence Analysis Library. J Acad Nutr Diet. 2016;116(2):311-318.
  2. Higgins JPT TJ, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors), Cochrane Handbook for Systematic Reviews of Interventions version 6.3 Cochrane. Published 2022. Updated February 2022. Accessed.
  3. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210.
  4. Sterne JAC, Savovic J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898.
  5. McGuinness LA, Higgins JPT. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021;12(1):55-61.
  6. RStudio: Integrated Development for R [computer program]. Boston, MA, USA,: RStudio, PBC; 2020.
  7. Wallace BC, Dahabreh IJ, Trikalinos TA, Lau J, Trow P, Schmid CH. Closing the Gap between Methodologists and End-Users: R as a Computational Back-End. J Statistical Software. 2012;49(5):1 - 15.