Meta-analyses of the Effect of Important Food Sources of Sugars on Cardiometabolic Risk Factors
NCT ID: NCT02716870
Last Updated: 2020-06-25
Study Results
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Basic Information
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UNKNOWN
1 participants
OBSERVATIONAL
2015-06-30
2020-12-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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OTHER
OTHER
Interventions
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Fructose-containing Sugars
An intervention in which calories from fructose-containing sugars are substituted, added, or subtracted in the diet
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Oral fructose-containing sugars intervention
* Presence of an adequate comparator (substitution, addition, subtraction, or ad libitum control)
* Diet duration \>=7 days
* Viable outcome data
Exclusion Criteria
* Observational studies
* IV or parenteral fructose-containing sugars
* Lack of suitable comparator (i.e. a comparator arm that contains substantial fructose-containing sugars)
* Diet duration \<7 days
* No viable outcome data
ALL
Yes
Sponsors
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Canadian Diabetes Association
OTHER
The Physicians' Services Incorporated Foundation
OTHER
Banting & Best Diabetes Centre
OTHER
University of Toronto
OTHER
Responsible Party
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John Sievenpiper
Associate Professor
Principal Investigators
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John L Sievenpiper, MD,PhD,FRCPC
Role: PRINCIPAL_INVESTIGATOR
University of Toronto
Locations
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The Toronto 3D (Diet, Digestive tract and Disease) Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital
Toronto, Ontario, Canada
Countries
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References
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Sievenpiper JL, de Souza RJ, Mirrahimi A, Yu ME, Carleton AJ, Beyene J, Chiavaroli L, Di Buono M, Jenkins AL, Leiter LA, Wolever TM, Kendall CW, Jenkins DJ. Effect of fructose on body weight in controlled feeding trials: a systematic review and meta-analysis. Ann Intern Med. 2012 Feb 21;156(4):291-304. doi: 10.7326/0003-4819-156-4-201202210-00007.
Ha V, Sievenpiper JL, de Souza RJ, Chiavaroli L, Wang DD, Cozma AI, Mirrahimi A, Yu ME, Carleton AJ, Dibuono M, Jenkins AL, Leiter LA, Wolever TM, Beyene J, Kendall CW, Jenkins DJ. Effect of fructose on blood pressure: a systematic review and meta-analysis of controlled feeding trials. Hypertension. 2012 Apr;59(4):787-95. doi: 10.1161/HYPERTENSIONAHA.111.182311. Epub 2012 Feb 13.
Cozma AI, Sievenpiper JL, de Souza RJ, Chiavaroli L, Ha V, Wang DD, Mirrahimi A, Yu ME, Carleton AJ, Di Buono M, Jenkins AL, Leiter LA, Wolever TM, Beyene J, Kendall CW, Jenkins DJ. Effect of fructose on glycemic control in diabetes: a systematic review and meta-analysis of controlled feeding trials. Diabetes Care. 2012 Jul;35(7):1611-20. doi: 10.2337/dc12-0073.
Chiavaroli L, de Souza RJ, Ha V, Cozma AI, Mirrahimi A, Wang DD, Yu M, Carleton AJ, Di Buono M, Jenkins AL, Leiter LA, Wolever TM, Beyene J, Kendall CW, Jenkins DJ, Sievenpiper JL. Effect of Fructose on Established Lipid Targets: A Systematic Review and Meta-Analysis of Controlled Feeding Trials. J Am Heart Assoc. 2015 Sep 10;4(9):e001700. doi: 10.1161/JAHA.114.001700.
Wang DD, Sievenpiper JL, de Souza RJ, Chiavaroli L, Ha V, Cozma AI, Mirrahimi A, Yu ME, Carleton AJ, Di Buono M, Jenkins AL, Leiter LA, Wolever TM, Beyene J, Kendall CW, Jenkins DJ. The effects of fructose intake on serum uric acid vary among controlled dietary trials. J Nutr. 2012 May;142(5):916-23. doi: 10.3945/jn.111.151951. Epub 2012 Mar 28.
Chiu S, Sievenpiper JL, de Souza RJ, Cozma AI, Mirrahimi A, Carleton AJ, Ha V, Di Buono M, Jenkins AL, Leiter LA, Wolever TM, Don-Wauchope AC, Beyene J, Kendall CW, Jenkins DJ. Effect of fructose on markers of non-alcoholic fatty liver disease (NAFLD): a systematic review and meta-analysis of controlled feeding trials. Eur J Clin Nutr. 2014 Apr;68(4):416-23. doi: 10.1038/ejcn.2014.8. Epub 2014 Feb 26.
Liu Q, Chiavaroli L, Ayoub-Charette S, Ahmed A, Khan TA, Au-Yeung F, Lee D, Cheung A, Zurbau A, Choo VL, Mejia SB, de Souza RJ, Wolever TMS, Leiter LA, Kendall CWC, Jenkins DJA, Sievenpiper JL. Fructose-containing food sources and blood pressure: A systematic review and meta-analysis of controlled feeding trials. PLoS One. 2023 Aug 15;18(8):e0264802. doi: 10.1371/journal.pone.0264802. eCollection 2023.
Qi X, Chiavaroli L, Lee D, Ayoub-Charette S, Khan TA, Au-Yeung F, Ahmed A, Cheung A, Liu Q, Blanco Mejia S, Choo VL, de Souza RJ, Wolever TMS, Leiter LA, Kendall CWC, Jenkins DJA, Sievenpiper JL. Effect of Important Food Sources of Fructose-Containing Sugars on Inflammatory Biomarkers: A Systematic Review and Meta-Analysis of Controlled Feeding Trials. Nutrients. 2022 Sep 26;14(19):3986. doi: 10.3390/nu14193986.
Ayoub-Charette S, Chiavaroli L, Liu Q, Khan TA, Zurbau A, Au-Yeung F, Cheung A, Ahmed A, Lee D, Choo VL, Blanco Mejia S, de Souza RJ, Wolever TM, Leiter LA, Kendall CW, Jenkins DJ, Sievenpiper JL. Different Food Sources of Fructose-Containing Sugars and Fasting Blood Uric Acid Levels: A Systematic Review and Meta-Analysis of Controlled Feeding Trials. J Nutr. 2021 Aug 7;151(8):2409-2421. doi: 10.1093/jn/nxab144.
Choo VL, Viguiliouk E, Blanco Mejia S, Cozma AI, Khan TA, Ha V, Wolever TMS, Leiter LA, Vuksan V, Kendall CWC, de Souza RJ, Jenkins DJA, Sievenpiper JL. Food sources of fructose-containing sugars and glycaemic control: systematic review and meta-analysis of controlled intervention studies. BMJ. 2018 Nov 21;363:k4644. doi: 10.1136/bmj.k4644.
Other Identifiers
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CDA-Sugars 2015
Identifier Type: -
Identifier Source: org_study_id
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