Meta-analyses of the Effect of Tree Nuts on Glycemic Control and Features of the Metabolic Syndrome

Background: Tree nuts (almonds, Brazil nuts, cashews, hazelnuts, macadamia nuts, pecans, pine nuts, pistachios and walnuts)are an important source of unsaturated fatty acids, vegetable protein, and fibre, as well as minerals, vitamins, and phytonutrients. Although the dietary guidelines for Americans and American Heart Association (AHA) recommend the consumption of nuts for cardiovascular risk reduction and the US Food and Drug Administration (FDA) issued a qualified coronary heart disease (CHD) risk reduction claim for nuts, none of the diabetes associations have addressed nuts in their most recent recommendations. This omission is despite CHD being a major cause of death in diabetes. Several trials have been undertaken in diabetes, some of which, including the largest to date by our group, have demonstrated advantages in glycemic control. Although the remaining trials have failed to show a significant improvement in glycemic control, the direction of the effect has favored nuts, along with improvements in complementary markers of metabolic control.

Need for a review: The lack of high quality data in this area to support diabetes recommendations represents 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.

Objective: To provide evidence-based guidance for diabetes guidelines, we will conduct two systematic reviews and meta-analyses of controlled feeding trials to assess the effect of tree nuts (almonds, Brazil nuts, cashews, hazelnuts, macadamia nuts, pecans, pine nuts, pistachios and walnuts) on cardiometabolic control: (1) "Tree nuts and glycemic control" and (2) "Tree nuts and features of the metabolic syndrome".

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 nuts for other diets on cardiometabolic risk outcomes in humans will be included. Studies that are <3-weeks diet 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, nut form, dose, follow-up, and the composition of the background diets. Mean±SEM values will be extracted for all endpoints. 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 two proposed analyses will assess a set of outcomes related to a different area of cardiometabolic control: (1) glycemic control (glycated blood proteins[HbA1c, fructosamine, glycated albumin], fasting glucose, fasting insulin, and the homeostasis model assessment of insulin resistance [HOMA-IR]) and (2) harmonized metabolic syndrome features (waist circumference, TG, HDL-C, blood pressure, fasting glucose).

Data synthesis: Pooled analyses will be conducted 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. 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 Cochrane's Q and quantified by I2. Sources of heterogeneity will be explored by sensitivity and subgroup analyses. A priori subgroup analyses will include nut type, nut dose, duration of follow-up, change in saturated fat intake, change in dietary fibre intake, design (crossover, parallel), study quality, and baseline endpoint values. 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 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 from the two systematic reviews and meta-analyses 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. Two of the applicants (JLS, CWCK) will also participate directly as members of nutrition guidelines committees the 2013 CDA Clinical Practice Guidelines (CPG) for nutrition therapy by one of the applicants (JLS) and 2015 European Association for the Study of Diabetes (EASD) CPG for nutrition therapy (JLS, CWCK). 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.

Significance: The two proposed systematic reviews and meta-analyses will aid in knowledge translation related to the effects of tree nuts in diabetes and metabolic syndrome, strengthening the evidence-base for dietary recommendations and health claims.