A systematic review and meta-analysis of randomized trials of substituting soymilk for cow’s milk and intermediate cardiometabolic outcomes: understanding the impact of dairy alternatives in the transition to plant-based diets on cardiometabolic health
Bibliographic record
Abstract
BACKGROUND: Dietary guidelines recommend a shift to plant-based diets. Fortified soymilk, a prototypical plant protein food used in the transition to plant-based diets, usually contains added sugars to match the sweetness of cow's milk and is classified as an ultra-processed food. Whether soymilk can replace minimally processed cow's milk without the adverse cardiometabolic effects attributed to added sugars and ultra-processed foods remains unclear. We conducted a systematic review and meta-analysis of randomized controlled trials, to assess the effect of substituting soymilk for cow's milk and its modification by added sugars (sweetened versus unsweetened) on intermediate cardiometabolic outcomes. METHODS: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched (through June 2024) for randomized controlled trials of ≥ 3 weeks in adults. Outcomes included established markers of blood lipids, glycemic control, blood pressure, inflammation, adiposity, renal disease, uric acid, and non-alcoholic fatty liver disease. Two independent reviewers extracted data and assessed risk of bias. The certainty of evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). A sub-study of lactose versus sucrose outside of a dairy-like matrix was conducted to explore the role of sweetened soymilk which followed the same methodology. RESULTS: Eligibility criteria were met by 17 trials (n = 504 adults with a range of health statuses), assessing the effect of a median daily dose of 500 mL of soymilk (22 g soy protein and 17.2 g or 6.9 g/250 mL added sugars) in substitution for 500 mL of cow's milk (24 g milk protein and 24 g or 12 g/250 mL total sugars as lactose) on 19 intermediate outcomes. The substitution of soymilk for cow's milk resulted in moderate reductions in non-HDL-C (mean difference, - 0.26 mmol/L [95% confidence interval, - 0.43 to - 0.10]), systolic blood pressure (- 8.00 mmHg [- 14.89 to - 1.11]), and diastolic blood pressure (- 4.74 mmHg [- 9.17 to - 0.31]); small important reductions in LDL-C (- 0.19 mmol/L [- 0.29 to - 0.09]) and c-reactive protein (CRP) (- 0.82 mg/L [- 1.26 to - 0.37]); and trivial increases in HDL-C (0.05 mmol/L [0.00 to 0.09]). No other outcomes showed differences. There was no meaningful effect modification by added sugars across outcomes. The certainty of evidence was high for LDL-C and non-HDL-C; moderate for systolic blood pressure, diastolic blood pressure, CRP, and HDL-C; and generally moderate-to-low for all other outcomes. We could not conduct the sub-study of the effect of lactose versus added sugars, as no eligible trials could be identified. CONCLUSIONS: Current evidence provides a good indication that replacing cow's milk with soymilk (including sweetened soymilk) does not adversely affect established cardiometabolic risk factors and may result in advantages for blood lipids, blood pressure, and inflammation in adults with a mix of health statuses. The classification of plant-based dairy alternatives such as soymilk as ultra-processed may be misleading as it relates to their cardiometabolic effects and may need to be reconsidered in the transition to plant-based diets. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT05637866.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.036 | 0.006 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".