Meta-analysis of Low-calorie Sweetened Beverages and Cardiometabolic Outcomes

NCT ID: NCT04245826

Last Updated: 2020-02-25

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 1 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-05-16
• Study Completion Date: 2020-05-01

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:

1. Global adiposity - body weight

2. Global adiposity - BMI

3. Global adiposity - body fat

4. Abdominal adiposity - waist circumference

5. Overweight/obesity incidence

6. Metabolic syndrome incidence

7. Type 2 diabetes incidence

8. Cardiovascular disease incidence

9. Cardiovascular disease mortality

10. Total mortality

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:

i) Assessment of change in intake of LCSBs with change in outcome (change analysis)

ii) 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:

1. Global adiposity - body weight

2. Global adiposity - BMI

3. Global adiposity - body fat

4. Abdominal adiposity - waist circumference

5. Overweight/obesity incidence

6. Metabolic syndrome incidence

7. Type 2 diabetes incidence

8. Cardiovascular disease incidence

9. Cardiovascular disease mortality

10. 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.

Conditions

Adiposity; Metabolic Syndrome; Type 2 Diabetes; Cardiovascular Diseases; Mortality

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

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).

Change in LCSBs Intake

Intervention Type: OTHER

Effect of changing LCSBs intake

Substitute LCSBs for SSBs or Water

Intervention Type: OTHER

Effect of substituting LCSBs for SSBs or Water

Interventions

Change in LCSBs Intake

Effect of changing LCSBs intake

Intervention Type: OTHER

Substitute LCSBs for SSBs or Water

Effect of substituting LCSBs for SSBs or Water

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Prospective cohorts studies
• Duration: more than 1 year follow-up
• Exposure: LCSBs
• Change analysis or substitution analysis of exposure

Exclusion Criteria

• Non-human studies
• Less than 1 year follow-up
• Analysis of baseline or prevalent intake of exposure only

• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Toronto

OTHER

Sponsor Role: lead

Responsible Party

John Sievenpiper

Associate Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

John L Sievenpiper, MD,PhD,FRCPC

Role: PRINCIPAL_INVESTIGATOR

University of Toronto

Locations

Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital

Toronto, Ontario, Canada

Countries

Canada

References

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. No abstract available.

Reference Type: BACKGROUND

PMID: 31092156 (View on PubMed)

Malik VS. Non-sugar sweeteners and health. BMJ. 2019 Jan 3;364:k5005. doi: 10.1136/bmj.k5005. No abstract available.

Reference Type: BACKGROUND

PMID: 30606710 (View on PubMed)

Johnson RK, Lichtenstein AH, Anderson CAM, Carson JA, Despres 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.

Reference Type: BACKGROUND

PMID: 30354445 (View on PubMed)

Toews I, Lohner S, Kullenberg 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.

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Reference Type: BACKGROUND

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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, Djousse 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, Riserus 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.

Reference Type: BACKGROUND

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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.

Reference Type: BACKGROUND

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Reference Type: DERIVED

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Other Identifiers

DNSG-LCSBs (cohorts)

Identifier Type: -

Identifier Source: org_study_id