Meta-analysis of Low-calorie Sweetened Beverages and Cardiometabolic Outcomes
Study Details
Study Description
Brief Summary
We propose to conduct a systematic literature review and meta-analysis to assess the association of low-calorie sweetened beverages (LCSBs) on cardiometabolic outcomes in prospective cohort studies. We will be using methodological approaches (change in LCSBs intake, and/or substitution analysis) that attempt to overcome the issue of reverse causality associated with studies of LCSBs and cardiometabolic disease. Ten cardiometabolic outcomes will be assessed:
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Global adiposity - body weight
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Global adiposity - BMI
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Global adiposity - body fat
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Abdominal adiposity - waist circumference
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Overweight/obesity incidence
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Metabolic syndrome incidence
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Type 2 diabetes incidence
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Cardiovascular disease incidence
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Cardiovascular disease mortality
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Total mortality
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
Background:
Low-calorie sweetened beverages (LCSBs) may provide a potentially important means for displacing excess calories from free sugars in the diet. However, prospective cohort studies suggest that the use of LCSBs may contribute to an increased risk of obesity and diabetes. These findings are likely due to methodological limitations of study design and analysis that do not account for reverse causality, where higher risk of cardiometabolic outcomes may lead to people to switch to LCSBs. There is a need for a systematic review and meta-analysis (SRMA) of prospective cohort studies to overcome these methodological limitations.
Objective:
We will conduct a SRMA of prospective cohort studies in human subjects that have assessed cardiometabolic outcomes using two analytical strategies:
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Assessment of change in intake of LCSBs with change in outcome (change analysis)
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Assessment of substitution of LCSBs for sugar-sweetened beverages (SSBs) or water.
Design:
We will conduct a SRMA according to the Cochrane Handbook for Systematic Reviews of Interventions and report the findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines.
Data sources:
MEDLINE, EMBASE, and the Cochrane Library databases will be searched using appropriate search terms, supplemented by hand searches of references of included studies. No restriction will be placed on language.
Study selection:
Prospective cohort studies reporting (a) change analysis (change in intake of LCSBs with the change in outcome), and/or (b) substitution analysis (substitution of SSBs with LCSBs or water) with more than 1-year of follow-up will be used. Cohort studies that have a follow-up duration <1 year, do not report assessment of exposure, or do not provide viable outcome data by level of exposure will be excluded.
Data extraction
Two or more investigators will independently extract relevant data and assess risk of bias using the Newcastle-Ottawa Scale (NOS) for prospective cohorts. All disagreements will be resolved by consensus. Risk ratios (RRs), odds ratios (ORs) and hazard ratios (HRs) for clinical outcomes in the prospective cohort studies will be extracted or derived from clinical event data across exposure categories.
Outcomes:
Ten cardiometabolic health outcomes will be assessed:
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Global adiposity - body weight
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Global adiposity - BMI
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Global adiposity - body fat
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Abdominal adiposity - waist circumference
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Overweight/obesity incidence
-
Metabolic syndrome incidence
-
Type 2 diabetes incidence
-
Cardiovascular disease incidence
-
Cardiovascular disease mortality
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Total mortality
Data synthesis:
Natural log-transformed RRs or HRs of clinical outcomes, comparing extreme quantiles (the highest exposure versus the lowest exposure or reference group), will be pooled separately using the generic inverse variance method with random effects models and expressed as RRs with 95% confidence intervals (CIs). Heterogeneity will be tested by Cochran's Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, we will conduct sensitivity analyses, in which each study is systematically removed. If ≥10 cohort comparisons are available, then we will perform an a-priori subgroup analyses by meta-regression for follow-up (<10 years vs. ≥10 years), sex (males vs. females, males vs. mixed, females vs. mixed), study quality (NOS <6 vs. ≥6) and funding source. Significant unexplained heterogeneity will be investigated by additional post hoc subgroup analyses and influence analysis. A study will be considered influential if it changes the direction or significance of the pooled estimates or the evidence of heterogeneity. Dose response estimates will be pooled using one-stage linear mixed model. 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, we 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 overall certainty of evidence for each outcome will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (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 to the role of the LCSBs role as a replacement strategy for SSBs, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Low-calorie Sweetened Beverages (LCSBs) Beverages exclusively using zero-energy (e.g., acesulfame-potassium, aspartame, cyclamate, saccharin, sucralose, advantame, neotame), and /or reduced-energy food additives (e.g., stevia, monk fruit). |
Other: Change in LCSBs Intake
Effect of changing LCSBs intake
Other: Substitute LCSBs for SSBs or Water
Effect of substituting LCSBs for SSBs or Water
|
Outcome Measures
Primary Outcome Measures
- Global measures of adiposity with established clinical relevance - body weight [More than 1 year]
Change in body weight
- Global measures of adiposity with established clinical relevance - BMI [More than 1 year]
Change in body mass index (BMI)
- Global measures of adiposity with established clinical relevance - body fat [More than 1 year]
Change in body fat
- Abdominal measures of adiposity with established clinical relevance - waist circumference [More than 1 year]
Change in waist circumference
- Overweight/obesity incidence [More than 1 year]
Risk ratio of Overweight/obesity incidence
- Metabolic syndrome incidence [More than 1 year]
Risk ratio of metabolic syndrome incidence
- Type 2 diabetes incidence [More than 1 year]
Risk ratio of type 2 diabetes incidence
- Cardiovascular disease incidence [More than 1 year]
Risk ratio of cardiovascular disease incidence
- Cardiovascular disease mortality [More than 1 year]
Risk ratio of Cardiovascular disease mortality
- Total mortality [More than 1 year]
Risk ratio of total mortality
Eligibility Criteria
Criteria
Inclusion Criteria:
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Prospective cohorts studies
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Duration: more than 1 year follow-up
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Exposure: LCSBs
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Change analysis or substitution analysis of exposure
Exclusion Criteria:
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Non-human studies
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Less than 1 year follow-up
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Analysis of baseline or prevalent intake of exposure only
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital | Toronto | Ontario | Canada | M5C 2T2 |
Sponsors and Collaborators
- University of Toronto
Investigators
- Principal Investigator: John L Sievenpiper, MD,PhD,FRCPC, University of Toronto
Study Documents (Full-Text)
None provided.More Information
Publications
- Azad MB, Abou-Setta AM, Chauhan BF, Rabbani R, Lys J, Copstein L, Mann A, Jeyaraman MM, Reid AE, Fiander M, MacKay DS, McGavock J, Wicklow B, Zarychanski R. Nonnutritive sweeteners and cardiometabolic health: a systematic review and meta-analysis of randomized controlled trials and prospective cohort studies. CMAJ. 2017 Jul 17;189(28):E929-E939. doi: 10.1503/cmaj.161390. Review.
- Imamura F, Fretts A, Marklund M, Ardisson Korat AV, Yang WS, Lankinen M, Qureshi W, Helmer C, Chen TA, Wong K, Bassett JK, Murphy R, Tintle N, Yu CI, Brouwer IA, Chien KL, Frazier-Wood AC, Del Gobbo LC, Djoussé L, Geleijnse JM, Giles GG, de Goede J, Gudnason V, Harris WS, Hodge A, Hu F; InterAct Consortium, Koulman A, Laakso M, Lind L, Lin HJ, McKnight B, Rajaobelina K, Risérus U, Robinson JG, Samieri C, Siscovick DS, Soedamah-Muthu SS, Sotoodehnia N, Sun Q, Tsai MY, Uusitupa M, Wagenknecht LE, Wareham NJ, Wu JH, Micha R, Forouhi NG, Lemaitre RN, Mozaffarian D; Fatty Acids and Outcomes Research Consortium (FORCE). Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies. PLoS Med. 2018 Oct 10;15(10):e1002670. doi: 10.1371/journal.pmed.1002670. eCollection 2018 Oct.
- Johnson RK, Lichtenstein AH, Anderson CAM, Carson JA, Després JP, Hu FB, Kris-Etherton PM, Otten JJ, Towfighi A, Wylie-Rosett J; American Heart Association Nutrition Committee of the Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular and Stroke Nursing; Council on Clinical Cardiology; Council on Quality of Care and Outcomes Research; and Stroke Council. Low-Calorie Sweetened Beverages and Cardiometabolic Health: A Science Advisory From the American Heart Association. Circulation. 2018 Aug 28;138(9):e126-e140. doi: 10.1161/CIR.0000000000000569. Review.
- Khan TA, Malik VS, Sievenpiper JL. Letter by Khan et al Regarding Article, "Artificially Sweetened Beverages and Stroke, Coronary Heart Disease, and All-Cause Mortality in the Women's Health Initiative". Stroke. 2019 Jun;50(6):e167-e168. doi: 10.1161/STROKEAHA.119.025571. Epub 2019 May 16.
- Malik VS. Non-sugar sweeteners and health. BMJ. 2019 Jan 3;364:k5005. doi: 10.1136/bmj.k5005.
- Rogers PJ, Hogenkamp PS, de Graaf C, Higgs S, Lluch A, Ness AR, Penfold C, Perry R, Putz P, Yeomans MR, Mela DJ. Does low-energy sweetener consumption affect energy intake and body weight? A systematic review, including meta-analyses, of the evidence from human and animal studies. Int J Obes (Lond). 2016 Mar;40(3):381-94. doi: 10.1038/ijo.2015.177. Epub 2015 Sep 14. Review.
- Toews I, Lohner S, Küllenberg de Gaudry D, Sommer H, Meerpohl JJ. Association between intake of non-sugar sweeteners and health outcomes: systematic review and meta-analyses of randomised and non-randomised controlled trials and observational studies. BMJ. 2019 Jan 2;364:k4718. doi: 10.1136/bmj.k4718. Erratum in: BMJ. 2019 Jan 15;364:l156.
- DNSG-LCSBs (cohorts)