Meta-analyses of Soy Protein and Its Food Sources for Cholesterol Reduction

Summary

Participation Requirements

Description

RATIONALE. Although soy protein has approved health claims in Canada and the US and is recognized by major cardiovascular clinical practice guidelines for the reduction of cholesterol and risk of coronary heart disease (CHD), these claims are based almost exclusively on evidence from foods containin...

RATIONALE. Although soy protein has approved health claims in Canada and the US and is recognized by major cardiovascular clinical practice guidelines for the reduction of cholesterol and risk of coronary heart disease (CHD), these claims are based almost exclusively on evidence from foods containing isolated soy protein (ISP). The role of other non-ISP food sources of soy protein (e.g Tofu, tempeh, edamame) in these effects is unclear. The role of food form and matrix (e.g soy beverage versus meat analogue) on the effects of ISP is also unclear. As national dietary guidelines and clinical practice guidelines for nutrition therapy shift from a focus on single nutrients to a focus on foods and dietary patterns, it is important to understand whether non-ISP food sources of soy protein and ISP food sources with different food matrices produce the same reductions in LDL-cholesterol and CHD risk. The investigators are not aware of any systematic reviews and meta-analyses of randomized controlled trials that have addressed this important question. OBJECTIVES. To conduct a systematic review of the effect of soy protein with prespecified analyses by food source on established lipid targets in individuals with and without dyslipidemia and assess the certainty of the evidence using the Grading of Recommendations Assessment Development and Evaluation (GRADE) system. A sub-objective is to conduct a targeted systematic review and meta-analysis of the effect of exclusively ISP on established lipid targets in individuals with and without dyslipidemia for use in the development of Health Claims submissions in Australia and New Zealand by co-investigator, Dr. Alan Barclay. DESIGN. The systematic review and meta-analyses 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. Randomized controlled trials of ?3-weeks (based on the FDA minimum follow-up requirement) assessing the effect of soy protein food sources compared with a suitable non-soy-containing control on lipids will be included. DATA EXTRACTION. Two or more investigators will independently extract relevant data. Authors will be contacted for additional information and any missing data will be computed/imputed using standard formulae. RISK OF BIAS. Two or more investigators will independently assess risk of bias using the Cochrane Risk of Bias Tool. OUTCOMES. The primary outcome will be LDL-C and secondary outcomes will be other established therapeutic lipid targets: HDL-C, TG, non-HDL-D and apo B. DATA SYNTHESIS. Data will be pooled using the Generic Inverse Variance method with prespecified analyses by food source. Separate pooled analyses will be conducted for ISP to meet the subobjective of assessing the effect of ISP. Random effects models will be used with paired analyses applied to crossover designs. Heterogeneity will be assessed (Cochran Q statistic) and quantified (I2 statistic). Sources of heterogeneity will be explored by sensitivity analyses and a priori subgroup analyses (dose, comparator, follow-up, baseline levels, design, body weight change, saturated fat intake, and risk of bias). Meta-regression will assess the significance of subgroup analyses. Linear and nonlinear dose-response analyses will be assessed by generalized least squares trend (GLST) estimation models and spline curve modelling (MKSPLINE procedure), respectively. Publication bias will be assessed by inspection of funnel plots and the Egger and Begg tests. Adjustment for evidence of funnel plot asymmetry or small study effects will be conducted by the Duval and Tweedie trim-and-fill method. GRADE ASSESSMENT. To assess the certainty of the evidence, the investigators will use the GRADE system, an evidence-based grading system adopted by >100 organizations (http://www.gradeworkinggroup.org/). It grades the evidence as high, moderate, low or very low quality based on the study design and a series of downgrades (risk of bias, imprecision, inconsistency, indirectness, publication bias) and upgrades (large magnitude of the effect, dose-response gradient, and attenuation by confounding). The investigators will follow the GRADE handbook (https://gdt.gradepro.org/app/handbook/handbook.html) and use the GRADEpro GDT (gradepro.org) software. KNOWLEDGE TRANSLATION PLAN. The investigators will follow the Ottawa model of Research for knowledge translation. The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact journals. Target audiences will include public health and clinical communities with an interest in nutrition and cardiovascular disease. Feedback will be incorporated and used to improve public health messages and key areas for future research will be defined. The PIs will network among opinion leaders to increase awareness and participate directly in the development of future guidelines. SIGNIFICANCE. The proposed project will reinforce the role of the all soy protein food sources (not just ISP-containing food sources) for cholesterol and CHD risk reduction, strengthening the evidence-base for health claims and guidelines development in the U.S., Canada, Europe, and beyond and improving health outcomes, by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.

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