SRMA of the Effect of Soy Milk vs Cow's Milk on Cardiometabolic Outcomes

• ClinicalTrials.gov Identifier: NCT05637866
• Recruitment Status: Active, not recruiting
• First Posted: December 5, 2022
• Last Update Posted: December 5, 2022
• Sponsor: University of Toronto
• Information provided by (Responsible Party): John Sievenpiper, University of Toronto

Study Description

Brief Summary:

Dairy consumption has shown associations with decreased incidence of cardiometabolic diseases. With the growing interest in plant-based eating, and the mounting evidence for the cardiovascular benefits of plant forward diets, national dietary guidelines have pivoted away from promoting exclusive daily dairy consumption. Soy milk, the most nutritionally comparable plant-based milk alternative to cow's milk, is a commonly consumed source of heart-healthy soy protein. Though the beneficial effect of soy protein on lipid markers is well established, the impact on other cardiometabolic outcomes is unclear. To address this question and better inform health claims and guideline development, the investigators will conduct a systematic review and meta-analysis of randomized controlled trials of the effect of soy protein as soy milk, in substitution for cow's milk, on various intermediate cardiometabolic mediators.

Condition or disease	Intervention/treatment
Cardiovascular Diseases; Lipid Disorder; Metabolic Disease; Non-Alcoholic Fatty Liver Disease	Other: Soy milk

Detailed Description:

RATIONALE. Dairy consumption has shown associations with decreased incidence of cardiometabolic diseases. With the growing interest in plant-based eating, and the mounting evidence for the cardiovascular benefits of plant forward diets, national dietary guidelines have pivoted away from promoting exclusive daily dairy consumption. Soy milk, the most nutritionally comparable plant-based milk alternative to cow's milk, is a commonly consumed source of heart-healthy soy protein. Though the beneficial effect of soy protein on lipid markers is well established, the impact on other cardiometabolic outcomes is unclear. To address this question and better inform health claims and guideline development, the investigators will conduct a systematic review and meta-analysis of randomized controlled trials of the effect of soy protein as soy milk, in substitution for cow's milk, on various intermediate cardiometabolic mediators.

OBJECTIVES. To conduct a systematic review of the effect of soy protein as soy milk, in substitution for cow's milk, on various intermediate cardiometabolic mediators and assess the certainty of the evidence using the Grading of Recommendations Assessment Development and Evaluation (GRADE) system.

DESIGN. The systematic review and meta-analyses 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 manual searches of references of included studies.

STUDY SELECTION. Randomized controlled trials of ≥3-weeks assessing the effect of soy milk, in substitution for cow's milk, on various intermediate cardiometabolic mediators will be included.

DATA EXTRACTION. Two or more investigators will independently extract relevant data. Authors will be contacted for additional information and any missing data will be computed/imputed using standard formulae.

RISK OF BIAS. Two or more investigators will independently assess risk of bias using the Cochrane Risk of Bias Tool 2. All disagreements will be resolved by consensus.

OUTCOMES. The outcomes will be:

1. Established blood lipids: LDL-Cholesterol (LDL-C), HDL-Cholesterol (HDL-C), triglycerides (TG), Non-HDL-Cholesterol (Non-HDL-C), and apolipoprotein B(Apo B)
2. Markers of glycemic control: hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), fasting plasma insulin (FPI), plasma glucose area under the curve (AUC), and 2h plasma glucose (2hPG)
3. Adiposity markers: body weight, body mass index (BMI), body fat, and waist circumference
4. Blood pressure: systolic blood pressure (SBP), and diastolic blood pressure (DBP)
5. Markers of non-alcoholic fatty liver disease (NAFLD): intrahepatocellular lipids (IHCL), alanine transaminase (ALT), aspartate aminotransferase (AST), and fatty liver index (FLI)
6. Markers of inflammation: C-reactive protein (CRP)

DATA SYNTHESIS. Data will be pooled using the Generic Inverse Variance method for each outcome. 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 design trials. Heterogeneity will be assessed (Cochran Q statistic) and quantified (I2 statistic). Sources of heterogeneity will be explored (if there are >=10 trial comparisons) by sensitivity analyses and a priori subgroup analyses (dose, comparator, follow-up, baseline levels, design, age, health status, funding and risk of bias). Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. Publication bias will be assessed (if there are >=10 trial comparisons) by inspection of funnel plots and the Egger and Begg tests. Adjustment for evidence of funnel plot asymmetry or small study effects will be conducted by the Duval and Tweedie trim-and-fill method.

GRADE ASSESSMENT. To assess the certainty of the evidence, the investigators will use the GRADE system, an evidence-based grading system adopted by >100 organizations (http://www.gradeworkinggroup.org/). It grades the evidence as high, moderate, low or very low quality based on the study design and a series of downgrades (risk of bias, imprecision, inconsistency, indirectness, publication bias) and upgrades (large magnitude of the effect, dose-response gradient, and attenuation by confounding). The investigators will follow the GRADE handbook (https://gdt.gradepro.org/app/handbook/ handbook.html) and use the GRADEpro GDT (gradepro.org) software.

KNOWLEDGE TRANSLATION PLAN. The investigators will follow the Ottawa model of Research for knowledge translation. The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact journals. Target audiences will include public health and clinical communities with an interest in nutrition and cardiometabolic diseases. Feedback will be incorporated and used to improve public health messages and key areas for future research will be defined. The PIs will network among opinion leaders to increase awareness and participate directly in the development of future guidelines.

SIGNIFICANCE. The proposed evidence synthesis will determine soy milk as an alternative to cow's milk for cardiometabolic health, informing guidelines development and improving health outcomes, by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.

Study Design

• Study Type: Observational
• Estimated Enrollment: 1 participants
• Observational Model: Other
• Time Perspective: Other
• Official Title: Effect of Soy Milk for Cow's Milk on Intermediate Cardiometabolic Outcomes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
• Actual Study Start Date: October 1, 2022
• Estimated Primary Completion Date: March 30, 2023
• Estimated Study Completion Date: October 1, 2023

Groups and Cohorts

Group/Cohort	Intervention/treatment
Soy Milk; Soy milk beverage	Other: Soy milk; Soya milk or soymilk, a plant-based beverage that can be sweetened or unsweetened.

Outcome Measures

Primary Outcome Measures :

1. Blood lipids - LDL-Cholesterol (LDL-C) [ Time Frame: Immediately after the intervention ]
   LDL-C mean difference and 95% CIs in mmol/L
2. Blood lipids - HDL-Cholesterol (HDL-C) [ Time Frame: Immediately after the intervention ]
   HDL-C mean difference and 95% CIs in mmol/L
3. Blood lipids - Triglycerides (TG) [ Time Frame: Immediately after the intervention ]
   TG mean difference and 95% CIs in mmol/L
4. Blood lipids - non-HDL-Cholesterol (Non HDL-C) [ Time Frame: Immediately after the intervention ]
   Non-HDL-C mean difference and 95% CIs in mmol/L
5. Blood lipids - Apolipoprotein B (ApoB) [ Time Frame: Immediately after the intervention ]
   ApoB mean difference and 95% CIs in g/L
6. Glycemic control - Hemoglobin A1c (HbA1c) [ Time Frame: Immediately after the intervention ]
   HbA1c mean difference and 95% CIs in %
7. Glycemic control - fasting plasma glucose (FPG) [ Time Frame: Immediately after the intervention ]
   FPG mean difference and 95% CIs in mmol/L
8. Glycemic control - fasting plasma insulin (FPI) [ Time Frame: Immediately after the intervention ]
   FPI mean difference and 95% CIs in mmol/L
9. Glycemic control - glucose tolerance - plasma glucose area under the curve (AUC) [ Time Frame: Immediately after the intervention ]
   AUC mean difference and 95% CIs in mmol x min/l
10. Glycemic control - glucose tolerance - 2h plasma glucose (2h-PG) [ Time Frame: Immediately after the intervention ]
    2h plasma glucose (2h-PG) during a 75g oral glucose tolerance test (OGTT) in mmol/L
11. Adiposity - Body weight [ Time Frame: Immediately after the intervention ]
    Body weight mean difference and 95% CIs in kg
12. Adiposity - Body mass index (BMI) [ Time Frame: Immediately after the intervention ]
    BMI mean difference and 95% CIs in kg/m2
13. Adiposity - Body fat [ Time Frame: Immediately after the intervention ]
    Body fat mean difference and 95% CIs in %
14. Adiposity - Waist circumference [ Time Frame: Immediately after the intervention ]
    Waist circumference mean difference and 95% CIs in cm
15. Blood pressure - systolic blood pressure (SBP) [ Time Frame: Immediately after the intervention ]
    SBP mean difference and 95% CIs in mmHg
16. Blood pressure - diastolic blood pressure (DBP) [ Time Frame: Immediately after the intervention ]
    DBP mean difference and 95% CIs in mmHg
17. Markers of non-alcoholic fatty liver disease (NAFLD) - Intrahepatocellular lipids (IHCL) [ Time Frame: Up to 20 years ]
    IHCL mean difference and 95% CIs in %
18. Markers of non-alcoholic fatty liver disease (NAFLD) - alanine transaminase (ALT) [ Time Frame: Immediately after the intervention ]
    ALT mean difference and 95% CIs in U/L
19. Markers of non-alcoholic fatty liver disease (NAFLD) - aspartate aminotransferase (AST) [ Time Frame: Immediately after the intervention ]
    AST mean difference and 95% CIs in U/L
20. Markers of non-alcoholic fatty liver disease (NAFLD) - fatty liver index (FLI) [ Time Frame: Immediately after the intervention ]
    FLI mean difference and 95% CIs
21. Markers of inflammation - C-reactive protein (CRP) [ Time Frame: Immediately after the intervention ]
    CRP mean difference and 95% CIs in mg/dL

Eligibility Criteria

• Ages Eligible for Study: 18 Years and older (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes
• Sampling Method: Probability Sample

Study Population

Adults with or without cardiovascular risk factors

Criteria

Inclusion Criteria:

• Randomized controlled trials
• Soy milk intervention
• Cow's milk comparator
• Intervention duration ≥ 3 weeks
• Data for at least 1 outcome

Exclusion Criteria:

• Non-human studies
• Observational studies
• Acute single-bolus feeding studies
• Participants < 18 years of age
• Multimodal interventions
• Lack of suitable comparator
• Intervention duration < 3 weeks
• No viable outcome data

Contacts and Locations

Locations

Canada, Ontario

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

More Information

Additional Information:

Canada's Food Guide 

Publications:

Malik VS, Sun Q, van Dam RM, Rimm EB, Willett WC, Rosner B, Hu FB. Adolescent dairy product consumption and risk of type 2 diabetes in middle-aged women. Am J Clin Nutr. 2011 Sep;94(3):854-61. doi: 10.3945/ajcn.110.009621. Epub 2011 Jul 13.

Maersk M, Belza A, Stodkilde-Jorgensen H, Ringgaard S, Chabanova E, Thomsen H, Pedersen SB, Astrup A, Richelsen B. Sucrose-sweetened beverages increase fat storage in the liver, muscle, and visceral fat depot: a 6-mo randomized intervention study. Am J Clin Nutr. 2012 Feb;95(2):283-9. doi: 10.3945/ajcn.111.022533. Epub 2011 Dec 28.

McGregor RA, Poppitt SD. Milk protein for improved metabolic health: a review of the evidence. Nutr Metab (Lond). 2013 Jul 3;10(1):46. doi: 10.1186/1743-7075-10-46.

• Responsible Party: John Sievenpiper, Associate Professor, University of Toronto
• ClinicalTrials.gov Identifier: NCT05637866
• Other Study ID Numbers: CIHR - Soy vs cow's milk
• First Posted: December 5, 2022
• Last Update Posted: December 5, 2022
• Last Verified: November 2022

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No
• Plan Description: There is no individual data collected. However, data from all included studies will be published in the manuscript and supplementary material

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by John Sievenpiper, University of Toronto:

Cholesterol; triglycerides; apolipoprotein B; hemoglobin A1c; fasting plasma glucose; fasting plasma insulin; 2hr plasma glucose; body weight; body mass index; body fat; waist circumference; blood pressure; adiposity; fatty liver; NAFLD; CRP; Inflammation; HDL-C; LDL-C; Non-HDL-c; Intrahepatocellular lipids; ALT; AST

Additional relevant MeSH terms:

Liver Diseases; Fatty Liver; Non-alcoholic Fatty Liver Disease; Cardiovascular Diseases; Metabolic Diseases; Lipid Metabolism Disorders; Digestive System Diseases