Meta-analyses of Nuts and Risk of Obesity

Overview

Peanuts and tree nuts (almonds, pistachios, walnuts, pecans, pine nuts, Brazil nuts, cashews, hazelnuts, macadamia nuts) (herein referred to as "nuts") are a good source of unsaturated fatty acids, vegetable protein, fibre, and polyphenolics. Nut intake has been associated with reduced cardiovascular disease risk and claims for this association have been permitted by the FDA; however, intake of tree nuts is low in Canada. One of the barriers to increasing the consumption of nuts is the perception that they may contribute to weight gain more than other "healthy foods" owing to their high energy density. The evidence supporting this concern, however, is lacking. In a series of earlier systematic reviews and meta-analyses, we have shown that nuts improve glycemic control and metabolic syndrome criteria, findings which run contrary to any expected weight gain. However, it remains unclear whether nuts have an increasing, neutral, or even decreasing effect on body weight. To address the uncertainties, the investigators propose to conduct a series of systematic reviews and meta-analyses of the totality of the evidence from randomized controlled trials and prospective cohort studies to investigate the effect of nut consumption on body weight and adiposity. The findings generated by this proposed knowledge synthesis will help improve the health of consumers through informing evidence-based guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design

Background: Peanuts and 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. The FDA has permitted health claims for tree nuts for cardiovascular disease risk reduction and the cardiovascular benefits of nuts is acknowledged \[FDA, 2015; Bao et al., 2013; Sabate et al., 2010\]; however, intake of tree nuts is low in Canada. Based on the 2004 Canadian Community Health Survey (CCHS), \<5% of Canadians consumed nuts on any given day with a mean intake of 18 g/day in those consuming nuts \[PHAC, 2004\]. This intake level is far below the 42 g/day amount recommended by the FDA for cardiovascular risk reduction. One of the barriers to increasing the consumption of nuts is the perception that they may contribute to weight gain more than other "healthy foods" owing to their high energy density. With the rise in overweight and obesity and its downstream cardiometabolic complications, heart and diabetes associations have cautioned against the over consumption of nuts at the same time that they recommend them for heart health \[Sievenpiper et al., 2013; Evert et al., 2014; Anderson et al., 2013\]. In a series of earlier systematic reviews and meta-analyses, we have shown that nuts improve glycemic control and metabolic syndrome criteria, findings which run contrary to any expected weight gain \[Viguiliouk et al., 2014; Blanco Mejia et al., 2014\]. Although an earlier systematic review and meta-analysis of controlled trials showed a lack of effect of nut intake on body weight \[Flores-Mateo et al., 2013\], it remains unclear whether nuts have an increasing, neutral, or even decreasing effect on a broader set of markers of adiposity. Need for proposed research:The lack of high quality syntheses and knowledge translation to reconcile the benefits of nuts with potential weight gain represents an urgent call for stronger evidence. High quality systematic reviews and meta-analyses of randomized controlled trials and prospective cohort studies represent the highest level of evidence to support dietary guidelines and public health policy development. Objective: The investigators will conduct a series of systematic reviews and meta-analyses to (1) distinguish the effect of peanuts and tree nuts on body weight and markers of adiposity in randomized controlled trials and (2) assess peanut and tree nut consumption with incident overweight/obesity and changes in weight and markers of adiposity in prospective cohort studies. Design: Each systematic review and meta-analysis 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) \[Higgins et al., 2011; Moher et al., 2009\]. Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms supplemented by hand searches of references of included studies. Study selection: The investigators will include either randomized controlled dietary trials or prospective cohort studies. Randomized controlled trials that investigate the effect of including and/or exchanging nuts for other nutrients on changes in body weight or markers of adiposity outcomes in adults (\>= 18 years) will be included. Studies that are \<3-weeks diet duration, lack a control, include individuals \<18 years, or assess intake during wasting conditions/malnourished populations, pregnancy or lactation will be excluded. Prospective cohort studies will be included if they are \>= 1-year duration, involving adults (\>=18 years) and assess the relation of tree nuts and/or peanuts with incident overweight/obesity or changes in body weight or markers of adiposity. Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Cochrane Risk of Bias Tool. All disagreements will be resolved by consensus. Standard computations and imputations will be used to derive missing variance data. Outcomes: Three sets of outcomes will be assessed: (1) incidence of overweight/obesity, (2) measures of global adiposity (body weight, body mass index (BMI), body fat), (3) measures of abdominal adiposity (waist circumference, waist-to-hip ratio, visceral adipose tissue). Data synthesis: Mean differences will be pooled for the trials and risk ratios for the cohorts using the generic inverse variance method. 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. Fixed-effects models will only be used where there is \<5 included studies. Paired analyses will be applied for crossover trials. Heterogeneity will be assessed by the Cochran Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, the investigators will conduct sensitivity analyses, in which each study is systematically removed. If there are \>=10 studies, then the investigators will also explore sources of heterogeneity by a priori subgroup analyses by health status (metabolic syndrome/diabetes, overweight, normal weight), comparator (carbohydrate, other fat source, animal protein, mixed macronutrient, other), nut type, nut dose, baseline measurements, randomization, study design (parallel, crossover), energy balance (positive, neutral, negative), duration of follow-up, and risk of bias. Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. When \>=10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger and Begg tests. If publication bias is suspected, then the investigators will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method. Evidence Assessment: The strength of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) \[Guyatt et al., 2011a, 2011b, 2011c, 2011d, 2011e, 2011f, 2011g, 2011h, 2011i; Balshem et al., 2011; Brunetti et al., 2013; Guyatt et al., 2013a, 2013b, 2013c\]. 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, diabetes, obesity, and cardiovascular disease. 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 peanuts and tree nuts in relation to body weight, in particular adiposity and the development of overweight and obesity, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.