Relation of Vegetarian Diets With Incident Cardiovascular Outcomes: A Systematic Review and Meta-analysis of Prospective Cohort Studies
Relation of Vegetarian Diets With Incident Cardiovascular Outcomes: A Systematic Review and Meta-analysis of Prospective Cohort Studies
Vegetarian and vegan diets have been shown to reduce cardiometabolic risk factors for chronic diseases, such as cardiovascular disease and diabetes, and have been associated with decreased risk of these chronic diseases. The role of vegetarian and/or vegan dietary patterns and incident cardiovascular outcomes still remains unclear. To address these uncertainties, the investigators propose to conduct a systematic review and meta-analysis of the totality of evidence from prospective cohort studies to distinguish the association of vegetarian and/or vegan dietary patterns on the prevention and management of cardiovascular diseases. This proposed knowledge synthesis was commissioned by the Diabetes and Nutrition Study Group (DNSG) of the European Association for the Study of Diabetes (EASD) and will be used to inform clinical practice and dietary guidelines, help improve health outcomes, and guide future research design.
Background: Cardiovascular disease (CVD) is the number 1 cause of death worldwide, representing 31% of all deaths. Vegetarian and/or vegan dietary patterns have been shown in prospective cohort and cross-sectional studies to be associated with lower coronary heart disease and ischemic heart disease risk. Evidence from randomized controlled trials also suggest that vegetarian and vegan diets may be beneficial for cardiovascular disease risk factors, such as LDL cholesterol, weight, blood pressure and type 2 diabetes (glycemic control). Moreover, evidence from meta-analyses of prospective cohort studies have shown that diets high in red and processed meat consumption are associated with an increased incidence of stroke and cardiovascular mortality. The evidence for a vegetarian dietary pattern is promising for prevention and management of cardiovascular diseases, however, not all CVD guidelines recommend following a vegetarian and/or vegan dietary pattern for the prevention and management of these diseases, or the guidelines grade the evidence as low quality.
Need for proposed research: High quality systematic reviews and meta-analyses of prospective cohort studies represent 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 cardiovascular diseases.
Objective: The investigators will conduct a systematic reviews and meta-analysis to assess vegan/vegetarian diets with cardiovascular disease outcomes (cardiovascular disease (CVD), coronary heart disease (CHD) and stroke incidence and mortality) in prospective cohort studies.
Design: The planning and conduct of the proposed meta-analyses will follow the Cochrane handbook for systematic reviews of interventions. The reporting will follow the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines.
Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials databases will be searched using appropriate search terms supplemented by hand searches of references of included studies.
Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Newcastle-Ottawa Scale (NOS) for observational studies. Risk ratios, odds ratios and hazard ratios for clinical outcomes will be extracted or derived from clinical event data across exposure to either vegetarian or non-vegetarian diets. All disagreements will be resolved by consensus.
Outcomes: Six outcomes will be assessed: CVD incidence and mortality, coronary heart disease (CHD) incidence and mortality, stroke incidence and mortality
Data synthesis: The natural log-transformed relative risks or hazard ratios of clinical outcomes comparing the exposure to the reference group from each cohort will be pooled using the generic inverse variance method with random effects models. Heterogeneity will be assessed by Cochrane's Q and quantified by I2. Sensitivity analyses and a priori subgroup analyses will be undertaken to explore sources of heterogeneity including the effect of the cohorts, sex, type of vegetarian diet, underlying disease status, follow-up (<10-years, >=10-years), level of adjustment of models, quality of the studies (NOS), and validation of the dietary assessment instruments. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses. Meta-regression analyses will assess the significance of subgroups analyses. Publication bias will be assessed by the inspection of funnel plots and using Begg's and Egger's tests.
Evidence Assessment: The certainty 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, cardiovascular diseases and diabetes. 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 cardiovascular diseases, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.
Inclusion Criteria:
Exclusion Criteria: