Meta-analyses of the Effect of Important Food Sources of Sugars on Cardiometabolic Risk Factors

Summary

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Background: Sugars have emerged as one of the most important public health concerns. Attention has focused particularly on fructose-containing sugars (fructose, sucrose, high fructose corn syrup, honey, etc), which collectively have been indicted as drivers of various cardiometabolic complications. ...

Background: Sugars have emerged as one of the most important public health concerns. Attention has focused particularly on fructose-containing sugars (fructose, sucrose, high fructose corn syrup, honey, etc), which collectively have been indicted as drivers of various cardiometabolic complications. This special view rests on the unique metabolic and endocrine responses to fructose. Unlike glucose, fructose is thought to bypasses negative feedback controls acting as an unregulated substrate for de novo lipogenesis and impair satiety signaling resulting in weight gain. In support of these mechanisms, animal models, low-quality ecological studies, and select human trials of overfeeding at levels of exposure far beyond population intakes have reported adverse metabolic effects of sugars. Higher level evidence from systematic reviews and meta-analyses of controlled trials, however, suggests that any effects of sugars are mediated by excess calories rather than the sugars per se. It remains unclear whether fructose-containing sugars contribute to cardiometabolic complications independent of their calories. Need for proposed research: High quality systematic reviews and meta-analyses of controlled trials represent the highest level of 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 an urgent need for systematic reviews and meta-analyses comparing the role of different food sources of sugars in the development of cardiometabolic diseases. Objective: The investigators will conduct a series systematic reviews and meta-analyses to distinguish the effect of fructose-containing sugars from that of energy on measures of cardiometabolic risk in controlled trials. 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). 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 randomized and non-randomized controlled trials >= 7-days in duration to assess the effect of fructose-containing sugars (fructose, sucrose, high fructose corn syrup, honey, etc) on measures of cardiometabolic risk. To allow for the separation of the effect of sugars from that of energy, 4 trial designs will be considered: (1) 'substitution' trials, in which fructose-containing sugars added to foods and beverages are compared with other macronutrient sources (usually starch or other sugars) under energy matched conditions; (2) 'addition' trials, in which fructose-containing sugars supplement a diet with excess energy compared to the same diet alone without the excess energy; (3) 'subtraction' trials, in which energy from fructose-containing sugars (usually in the form of sugars-sweetened beverages) is reduced by displacing it with water and/or no-calorie or low-calorie sweeteners or by eliminating it altogether from the background diet; and (4) 'ad libitum' trials, in which energy from fructose-containing sugars are freely replaced with other sources of energy (usually complex carbohydrates or fat) without any strict control of either the study foods or the background diet. Trials will be categorized by sources of fructose-containing sugars (fruits, fruit juices, sugars-sweetened beverages, liquid meal replacements, dairy products, sweets/desserts/baked goods, mixed sources) and chi squared tests will be used to determine between-group differences. 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: Five sets of outcomes will be assessed: (1) glycemic control (glycated blood proteins [HbA1c, fructosamine, glycated albumin], fasting glucose, and fasting insulin), (2) blood lipids (Established therapeutic lipid targets [LDL-cholesterol, non-HDL-cholesterol, apolipoprotein B (apo B), HDL-cholesterol, triglycerides]), (3) blood pressure (systolic blood pressure and diastolic blood pressure), (4) uric acid, (5) non-alcoholic fatty liver disease (NAFLD) (intrahepatocellular lipids [IHCL], alanine aminotransferase [ALT], aspartate aminotransferase [AST]) and inflammation (c-reactive protein [CRP], IL-6, TNF-alpha). Data synthesis: Mean differences will be pooled using the generic inverse variance method for each food source of fructose-containing sugars. 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 age (children [=<18 years of age], adults), health status (metabolic syndrome criteria, diabetes, overweight/ obese, healthy), comparator type, fructose- containing sugar form (sucrose, high fructose corn syrup [HFCS], honey, fructose), dose (=<10% energy, >10%), baseline measurements, randomization, study design (parallel, crossover), energy balance (positive, neutral, negative), follow-up (<8-weeks, >=8-weeks), feeding control (metabolic, supplemented, dietary advice), funding (agency, industry, agency+industry, not reported), 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). 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 dietary fructose-containing sugars and important food sources of these sugars in the development of cardiometabolic 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.

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