Meta-analyses of Dietary Pulses and Cardiometabolic Risk

Overview

Dietary pulses, more commonly known as "legumes", are generally recognized as healthy components of the diet. Canada's Food Guide encourages consumptions of meat alternatives, such as beans "more often"; and the dietary guidelines for Americans both recommend consumption of 3 cups of legumes per week. However, there still remain insufficient information on the usefulness of these foods in protecting heart health. To improve evidence-based guidance for non-oil-seed pulse recommendations, the investigators propose to conduct a systematic review of clinical studies to assess the effect of eating pulses in exchange for other foods on measures of heart disease risk and blood sugar control in humans. The systematic review process allows the combining of the results from many small studies in order to arrive at a pooled estimate, similar to a weighted average, of the true effect. The investigators will be able to explore whether eating pulses has different effects between men and women, in different age groups, in people with high or normal sugar or blood fat levels, and whether or not the effect of pulses depends on how much/often they are eaten. The findings of this proposed knowledge synthesis will help improve the health of Canadians through informing recommendations for the general public, as well as those at risk of heart disease and diabetes.

Background: Dietary non-oil-seed pulses (chick peas, beans, lentils, peas) are a source of slowly digestible carbohydrate, vegetable protein, and fibre. Canada's Food Guide encourages consumption of meat alternatives, such as beans, "more often", and the dietary guidelines for Americans recommend 3-cups of legumes per week. The American Heart Association (AHA) recommends the consumption of legumes at least twice a week for cardiovascular health, while the European (EASD), Canadian (CDA), and American (ADA) Diabetes Associations recommend the consumption of dietary pulses as a means of improving diabetes control. The evidence on which these recommendations are based, however, has been graded as low. The evidence to support cardiovascular risk reduction health claims for pulses has also been deemed insufficient, and obesity, blood pressure, and dyslipidemia guidelines have not addressed pulses in their recommendations. Need for a review: The low-grade of evidence on which heart and diabetes association recommendations are based and the lack of data to support health claims and other cardiometabolic recommendations represent an urgent call for stronger evidence. A systematic review and meta-analysis of controlled feeding trials remains the "Gold Standard" of evidence for nutrition guidelines development. Objectives: To provide evidence-based guidance for public health policy, health claims, and nutrition guidelines relating to dietary pulses, we will conduct a series of systematic reviews and meta-analyses (knowledge synthesis) of controlled feeding trials to assess the effect of pulses on markers of cardiometabolic risk in humans, specifically lipid endpoints with therapeutic targets, glycemia, blood pressure and body weight. 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 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Data sources: MEDLINE, EMBASE, CINAHL and The Cochrane Central Register of Controlled Trials will be searched using appropriate search terms. Study selection: Intervention trials that investigate the effect of exchanging dietary pulses for other diets on cardiometabolic risk outcomes in humans will be included. Studies that are \<3-wks duration, lack a control, or report non-isocaloric comparisons will be excluded. Data extraction: Independent investigators (≥2) will extract information about study design, sample size, subject characteristics, pulse form, dose, follow-up, and the composition of the background diets. Mean±SEM values will be extracted for all outcomes. Standard computations and imputations will be used to derive missing variance data. Risk of bias and study quality will be assessed using the risk of bias tool and the Heyland Methodological Quality Score (MQS), respectively. Outcomes: The 4 proposed analyses will each assess a set of outcomes related to a different area of cardiometabolic control: (1) lipid control (LDL-C, ApoB, TC:HDL, non-HDL-C, ApoB:ApoA-1), (2) glycemic control (fasting glucose and insulin, HOMA-IR, glycated blood proteins), (3) body weight control, and (4) blood pressure control. Where data for both change-from-baseline differences and end differences are equally available, we will use the difference in change from baseline as the primary end point for analyses. Data synthesis: Separate pooled analyses stratified by underlying disease status will be conducted for each area of metabolic control using the Generic Inverse Variance method with random effects models. 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. Paired analyses will be applied to all crossover trials. Heterogeneity will be tested by Cochrane's Q and quantified by I2. Sources of heterogeneity will be explored by sensitivity and subgroup analyses. A priori subgroup analyses will include pulse type, pulse dose, duration of follow-up, absolute and change in saturated fat intake, absolute and change in dietary fibre intake, design (crossover, parallel), study quality, and baseline endpoint values. An a priori subgroup analysis for absolute and change in sodium intake will replace that for absolute and change in saturated fat intake in the blood pressure analysis. 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, absolute and change in glycemic index, etc.). Meta-regression analyses will assess the significance of subgroups analyses. Publication bias will be investigated by the inspection of funnel plots and application of Egger's and Begg's tests. Knowledge translation plan: Results will be disseminated through traditional means such as interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Innovative means such as webcasts with e-mail feedback mechanisms will also be used. Knowledge Users will act as knowledge brokers networking among opinion leaders and different adopter groups to increase awareness at each stage. Four Knowledge Users will also participate directly as members of nutrition guidelines committees. Target adopters will include the clinical practice, public health, industry, research communities, and patient groups. Feedback will be incorporated and used to guide analyses and improve key messages at each stage. Preliminary findings: We conducted a systematic review and meta-analysis of the effect of dietary pulses on glycemic control in 41 controlled feeding trials. We found that pulses alone or in low-glycemic index or high-fibre diets improved markers of glycemic control. Although the improvement was clinically significant, it came at the expense of substantial inter-study heterogeneity. Knowledge translation from this preliminary project has already begun. It has provided a rationale for a large trial of the effect of pulses in type 2 diabetes to address some of the identified sources of heterogeneity and is being used in the development of the 2013 CDA Clinical Practice Guidelines (CPG) for Nutrition Therapy. Significance: The proposed project will aid in knowledge translation related to the effects of dietary pulses on cardiometabolic risk, strengthening the evidence-base for dietary recommendations and health claims and improving health outcomes through informing healthcare providers and patients, stimulating industry innovation, and guiding future research.