The effects of whey protein supplementation on indices of cardiometabolic health: A systematic review and meta-analysis of randomized controlled trials

Table of Contents

Overall Summary

Study Background and Main Findings

This meta-analysis investigated the effects of whey protein supplementation on cardiometabolic health markers in adults. The study found that whey protein supplementation significantly reduced total cholesterol (mean difference [MD]: -6.35 mg/dL, 95% CI: -11.10 to -1.61, p = 0.007) and LDL cholesterol in subgroups of individuals younger than 50 years and those who combined whey protein with exercise. Additionally, a significant reduction in triglycerides was observed after 12 weeks of supplementation. However, no significant effects were found on systolic or diastolic blood pressure, HDL cholesterol, or HOMA-IR overall.

Research Impact and Future Directions

The meta-analysis provides evidence that whey protein supplementation may reduce total cholesterol and LDL cholesterol, particularly in individuals under 50 and when combined with exercise. It also suggests a potential benefit for reducing triglycerides after 12 weeks of supplementation. However, no significant effects were found on blood pressure or insulin resistance (HOMA-IR). While the study demonstrates a correlation between whey protein supplementation and improvements in certain cardiometabolic markers, it does not establish a direct causal relationship. The observed associations could be influenced by other factors, such as lifestyle modifications or underlying health conditions.

The practical utility of the findings is promising, particularly for individuals seeking to improve their cholesterol levels through dietary interventions. The results align with existing research on the benefits of exercise and dietary modifications for cardiometabolic health. However, the lack of effect on blood pressure and insulin resistance suggests that whey protein may not be a comprehensive solution for all aspects of cardiometabolic health.

Healthcare practitioners can consider recommending whey protein supplementation as part of a broader strategy for managing cholesterol levels, especially in younger adults and those engaged in regular exercise. However, it is crucial to emphasize that whey protein is not a substitute for a healthy diet and lifestyle. The heterogeneity observed in some outcomes highlights the need for personalized approaches, considering individual factors like age, health status, and exercise habits. Further research is needed to determine the optimal dosage, duration, and long-term effects of whey protein supplementation.

Critical unanswered questions remain regarding the mechanisms underlying the observed effects, particularly the specific pathways involved in cholesterol and triglyceride reduction. Additionally, the high heterogeneity in some outcomes suggests the need for further investigation into the factors influencing individual responses to whey protein. While the methodological limitations, such as the variability in exercise protocols and the lack of a protein control group in some studies, do not fundamentally undermine the overall conclusions, they highlight the need for more standardized research approaches in future studies. Future research should also focus on long-term effects and potential side effects of whey protein supplementation to provide a more comprehensive understanding of its safety and efficacy.

Critical Analysis and Recommendations

Comprehensive search strategy (written-content)
The search strategy is comprehensive, covering multiple databases (PubMed, Scopus, Web of Science, and Cochrane Library) and spanning from each database's inception until June 2024. This thorough approach minimizes the risk of missing relevant studies and strengthens the reliability of the meta-analysis.
Section: Methods
Clear and systematic presentation of results (written-content)
The results are presented clearly and systematically, following the order established in the Methods section. This logical flow makes it easy for the reader to follow the analysis and interpret the findings.
Section: Results
Appropriate statistical methods (written-content)
The study uses appropriate statistical methods for a meta-analysis, including a random-effects model and the inverse-variance approach. The use of established statistical methods ensures that the analysis is robust and appropriate for the data, enhancing the reliability and validity of the findings.
Section: Results
Comprehensive subgroup analyses (written-content)
The study conducts subgroup analyses to explore the potential influence of various factors (age, exercise, treatment duration, dose, BMI, and control type) on the effects of whey protein. This approach allows for a more nuanced understanding of the results and identifies specific populations or conditions where whey protein may be most effective.
Section: Results
Provide full search strategies (written-content)
The Methods section should provide enough detail for another researcher to replicate the search independently. Providing the full search strategy for each database, including any filters applied, is crucial for reproducibility and transparency.
Section: Methods
State the knowledge gap (written-content)
While the introduction discusses dietary interventions, it doesn't fully articulate the specific gap in knowledge that this meta-analysis addresses. Clearly stating this gap would enhance the justification for the study and highlight its unique contribution to the field.
Section: Introduction
Provide more statistical details (written-content)
The Results section should provide sufficient detail about the statistical analyses performed, allowing other researchers to understand and potentially replicate the findings. Providing more information about the statistical methods, including the specific tests used and any adjustments made, would strengthen the transparency and reproducibility of the results.
Section: Results
Elaborate on the mechanisms of action (written-content)
While the discussion mentions potential mechanisms, it doesn't delve into the specific pathways or biological processes involved in whey protein's effects on cardiometabolic markers. A more in-depth exploration of these mechanisms would strengthen the discussion's scientific contribution and provide a more comprehensive understanding of the observed effects.
Section: Discussion
Discuss clinical implications (written-content)
While the conclusion mentions the potential benefits of whey protein for specific outcomes, it doesn't explicitly discuss the implications for dietary recommendations or clinical practice. A dedicated paragraph outlining these implications would provide valuable guidance for healthcare professionals and individuals interested in using whey protein to improve their cardiometabolic health.
Section: Conclusions

Section Analysis

Abstract

Key Aspects

Strengths

Suggestions for Improvement

Introduction

Key Aspects

Strengths

Suggestions for Improvement

Methods

Key Aspects

Strengths

Suggestions for Improvement

Results

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Fig. 1. Flowchart of the employed literature search.
Figure/Table Image (Page 4)
Fig. 1. Flowchart of the employed literature search.
First Reference in Text
Finally, 21 RCTs were included in the systematic review and meta-analysis [28-48] (Fig. 1).
Description
  • Identification: The flowchart visually depicts the literature search process, starting with the identification stage where searches were performed across multiple databases (PubMed, Cochrane Library, Web of Science, and Scopus). Each database search yielded a specific number of initial records.
  • Duplicate Removal: After identifying records from databases, duplicate records were removed.
  • Screening: After removing duplicate records, the remaining records were screened for eligibility based on titles and abstracts.
  • Retrieval: Full-text articles were sought for the records that passed the initial screening.
  • Eligibility Assessment: The full-text articles were assessed to determine if they met pre-defined inclusion criteria for the review. Studies that met all inclusion criteria were included in the systematic review and meta-analysis; those that did not were excluded, with reasons for exclusion documented.
  • Inclusion: This stage represents the final set of studies included for analysis. The flowchart specifies the final number (21) of randomized controlled trials (RCTs) that met all inclusion criteria and were used in the meta-analysis.
  • Randomized Controlled Trials (RCTs): Randomized controlled trials (RCTs) are a type of scientific study where participants are randomly assigned to different intervention groups. This design helps minimize bias and allows for stronger causal inferences between the intervention and outcomes.
Scientific Validity
  • Transparency and Reproducibility: The transparent presentation of the literature search process is crucial for evaluating the comprehensiveness and potential biases of the review. The flowchart facilitates this by clearly outlining the search strategy, databases used, and the number of studies included and excluded at each stage. This allows readers and peer reviewers to critically assess the search methodology and its potential impact on the review's conclusions.
  • Comprehensiveness of Search: The use of multiple databases (PubMed, Cochrane Library, Web of Science, Scopus) strengthens the validity of the search strategy by minimizing the risk of missing relevant studies. Each database has its own coverage and indexing protocols, so searching across multiple platforms increases the chance of capturing a broader range of relevant literature.
  • Justification of Exclusions: The explicit documentation of exclusion criteria is essential for scientific rigor. The flowchart indicates the reasons for excluding studies, allowing readers to evaluate the appropriateness and objectivity of these decisions. This transparency minimizes the risk of selection bias, ensuring that the included studies represent a fair and unbiased sample of the relevant literature.
Communication
  • Clarity and Transparency: The flowchart clearly presents the step-by-step process of the literature search, which is crucial for transparency and reproducibility in systematic reviews. The visual representation enhances the communication of the search strategy and the number of studies included/excluded at each step.
  • Adherence to PRISMA Guidelines: The flowchart adheres to PRISMA guidelines, which are widely accepted standards for reporting systematic reviews and meta-analyses. This strengthens the credibility and rigor of the presented research.
  • Specificity of Search Terms: While the flowchart effectively communicates the overall search process, providing more specific search terms within each database could further enhance transparency. For instance, indicating whether the search was limited to specific publication types (e.g., clinical trials) or date ranges would be beneficial.
Fig. 2. Effects of whey protein supplementation on systolic blood pressure.
Figure/Table Image (Page 6)
Fig. 2. Effects of whey protein supplementation on systolic blood pressure.
First Reference in Text
Our meta-analysis revealed no statistically significant effects of whey protein (n = 326) on SBP (n = 371) (k = 12; MD: -1.52, 95% CI: -3.51 0.47, I2 = 76 %, P = 0.14) (Fig. 2) or DBP (n = 371) (k = 12; MD: 1.05, 95% CI: -2.58 0.49, I2 = 81 %, P = 0.18) (Fig. 3) vs. placebo or carbohydrate-based control.
Description
  • Individual Study Results: The forest plot displays the effect of whey protein supplementation on systolic blood pressure (SBP) across multiple studies. Each horizontal line represents a single study. The square on each line indicates the mean difference (MD) in SBP between the whey protein group and the control group in that specific study. The size of the square is proportional to the weight of the study in the meta-analysis, reflecting its sample size and precision.
  • Confidence Intervals: The horizontal lines extending from each square represent the 95% confidence intervals (CIs) for the MD. The CI indicates the range within which the true effect is likely to lie with 95% certainty. If the CI crosses the vertical line of no effect (MD = 0), the study result is considered statistically non-significant.
  • Pooled Effect Estimate: The diamond at the bottom represents the overall pooled effect estimate from the meta-analysis. The center of the diamond indicates the overall MD, and its width represents the 95% CI for the pooled effect.
  • Heterogeneity: The figure also presents heterogeneity statistics (I² = 76%) which quantifies the variability in effect sizes between studies. A high I² value suggests substantial heterogeneity, indicating that the studies are not all measuring the same underlying effect.
Scientific Validity
  • Appropriateness of Meta-Analysis: The meta-analysis methodology appears appropriate for synthesizing results from multiple RCTs. The use of a random-effects model is justified given the high heterogeneity (I² = 76%), acknowledging potential variations in true effect sizes between studies.
  • Addressing Heterogeneity: The high heterogeneity (I² = 76%) warrants further investigation. Subgroup analyses or meta-regression could explore potential sources of heterogeneity (e.g., study design, participant characteristics, intervention protocols). Simply reporting the I² value without exploring the reasons for heterogeneity limits the interpretability of the pooled effect estimate.
  • Interpretation of Non-Significance: The confidence interval for the pooled effect (-3.51 to 0.47) includes zero, indicating that the overall effect is not statistically significant. This conclusion is supported by the p-value (0.14). However, the authors should avoid overinterpreting non-significance as evidence of no effect. The observed MD of -1.52 mmHg suggests a potential, albeit non-significant, reduction in SBP with whey protein supplementation.
Communication
  • Effective Visualization: The forest plot effectively visualizes the results of the meta-analysis, displaying individual study results and the overall pooled effect. The use of graphical elements like confidence intervals and the summary diamond enhances understanding.
  • Clarity of Caption: The figure caption clearly describes the outcome measure (systolic blood pressure) and the intervention (whey protein supplementation). However, explicitly stating the comparator (placebo or carbohydrate control) in the caption itself would enhance clarity. Currently, this information is only present in the main text.
  • Accessibility to Non-Experts: The use of standard meta-analysis conventions (forest plot, summary diamond, heterogeneity statistics) facilitates interpretation for a scientific audience. Non-experts, however, may find the plot challenging to fully grasp without prior knowledge of meta-analysis principles.
Fig. 3. Effects of whey protein supplementation on diastolic blood pressure.
Figure/Table Image (Page 6)
Fig. 3. Effects of whey protein supplementation on diastolic blood pressure.
First Reference in Text
Our meta-analysis revealed no statistically significant effects of whey protein (n = 326) on SBP (n = 371) (k = 12; MD: -1.52, 95% CI: -3.51 0.47, I2 = 76 %, P = 0.14) (Fig. 2) or DBP (n = 371) (k = 12; MD: 1.05, 95% CI: -2.58 0.49, I2 = 81 %, P = 0.18) (Fig. 3) vs. placebo or carbohydrate-based control.
Description
  • Individual Study Effects: The forest plot visually summarizes the effects of whey protein supplementation on diastolic blood pressure (DBP) from multiple studies. Each horizontal line corresponds to a single study, and the square on each line marks the mean difference (MD) in DBP between the whey protein group and the control group in that study. The size of the square reflects the study's weight in the meta-analysis, which is determined by its sample size and precision.
  • Confidence Intervals: The horizontal lines extending from each square depict the 95% confidence intervals (CIs) for the MD. The CI provides a range within which the true effect is estimated to lie with 95% confidence. If a CI crosses the vertical line of no effect (MD=0), the result is not statistically significant.
  • Overall Pooled Effect: The diamond at the bottom of the plot represents the overall pooled effect estimate from all included studies. The center of the diamond indicates the pooled MD, while its width corresponds to the 95% CI for this pooled estimate.
  • Heterogeneity: The figure includes the I² statistic (81%), which measures the heterogeneity or inconsistency between the studies' results. A high I² value suggests substantial variability in effect sizes across the studies.
Scientific Validity
  • Meta-Analysis Model: The use of a random-effects model for the meta-analysis is appropriate, considering the substantial heterogeneity (I² = 81%) observed between studies. This model accounts for variation in true effect sizes across different studies, providing a more robust estimate of the overall effect.
  • Heterogeneity Investigation: The high heterogeneity (I² = 81%) raises concerns about the comparability of the included studies. Further exploration of potential sources of heterogeneity through subgroup analysis or meta-regression would strengthen the validity of the findings.
  • Interpretation of Results: While the overall effect on DBP is not statistically significant (MD: 1.05, 95% CI: -2.58 to 0.49, p = 0.18), the authors should refrain from concluding that there is "no effect." The observed MD suggests a slight increase in DBP, and the wide confidence interval indicates considerable uncertainty around this estimate. Further research with larger sample sizes may be needed to definitively determine the effect of whey protein on DBP.
Communication
  • Clear Presentation of Results: The forest plot effectively communicates the results of the meta-analysis on diastolic blood pressure (DBP). The visual representation of individual study results and the overall pooled effect, along with confidence intervals and heterogeneity statistics, provides a clear overview of the findings.
  • Completeness of Caption: While the figure caption mentions diastolic blood pressure, it lacks explicit mention of the comparator (placebo or carbohydrate control). Including this information directly in the caption would improve clarity and make the figure more self-explanatory.
  • Accessibility to Broader Audience: The figure assumes familiarity with forest plots and meta-analysis terminology. While appropriate for a scientific audience, non-experts may find it challenging to interpret without additional context or explanation.
Fig. 4. Effects of whey protein supplementation on HDL-cholesterol levels.
Figure/Table Image (Page 6)
Fig. 4. Effects of whey protein supplementation on HDL-cholesterol levels.
First Reference in Text
No statistically significant effects of whey protein were observed (n = 300) on HDL-cholesterol (n = 327) (k = 13; MD: -0.82, 95% CI: -2.17 0.53, I2 = 43 %, P = 0.23) (Fig. 4) or LDL-cholesterol (n = 318) (k = 12; MD: −2.07, 95% CI: -4.10 to −0.03, I2 = 6 %, P = 0.05) (Fig. 5) profiles vs. placebo or carbohydrate-based control.
Description
  • Individual Study Results: The forest plot shows the effect of whey protein supplementation on HDL cholesterol levels across multiple studies. Each horizontal line represents an individual study. The square box on each horizontal line represents the mean difference (MD) between the whey protein group and the control group in that study. The size of the square corresponds to the weight given to each study in the meta-analysis, reflecting factors like sample size and precision. Larger squares indicate greater influence on the pooled result.
  • Confidence Intervals: The horizontal lines extending from each square represent the 95% confidence intervals (CIs) for the MD. The CI provides a range of values within which the true effect is likely to fall 95% of the time. If a CI crosses the vertical line at zero MD, it indicates that the effect is not statistically significant.
  • Overall Pooled Effect: The diamond at the bottom represents the pooled effect estimate across all studies. Its center marks the overall MD, and its width represents the 95% CI for the pooled effect. In this figure, the diamond overlaps the zero MD line, suggesting no statistically significant overall effect.
  • Heterogeneity: The I² value (43%) quantifies the heterogeneity, or inconsistency, among the included studies' results. This value suggests moderate heterogeneity in the effects of whey protein on HDL cholesterol.
Scientific Validity
  • Meta-Analysis Model: A random-effects model is likely appropriate for the meta-analysis due to the observed moderate heterogeneity (I² = 43%). This approach acknowledges potential variations in true effect sizes across studies.
  • Exploration of Heterogeneity: While the I² value suggests moderate heterogeneity, investigating potential sources of this variability (e.g., study design, participant characteristics, whey protein dose) through subgroup analyses or meta-regression would provide a more nuanced understanding of the results.
  • Interpretation of Non-Significance: The lack of statistical significance (p = 0.23) should not be interpreted as evidence of *no* effect. The confidence interval (-2.17 to 0.53) includes a range of clinically relevant changes in HDL. Further research with larger sample sizes or longer intervention durations may be needed to clarify the effect of whey protein on HDL cholesterol.
Communication
  • Appropriate Use of Forest Plot: The forest plot visually represents the meta-analysis results clearly, showing the effect of whey protein on HDL cholesterol. The use of a forest plot is standard for meta-analyses and effectively communicates the individual study results and the overall pooled effect.
  • Clarity of Caption: The figure caption clearly states the analyzed outcome (HDL-cholesterol levels) and intervention (whey protein supplementation). However, it would benefit from explicitly mentioning the comparator/control group (e.g., placebo or carbohydrate) within the caption for enhanced clarity.
  • Effective Visual Elements: The visual elements, such as the summary diamond and confidence intervals, are well-presented and aid in understanding the data. The I² value provides a quick assessment of heterogeneity. Labeling the x-axis with units (mg/dL) improves interpretability.
Fig. 5. Effects of whey protein supplementation on LDL-cholesterol levels.
Figure/Table Image (Page 7)