This umbrella review of 14 meta-analyses (45 pooled analyses, ~10 million participants) found a statistically significant direct association between higher ultra-processed food (UPF) consumption and 71% (32/45) of examined health outcomes. Convincing evidence (Class I) was found for cardiovascular mortality, type 2 diabetes (dose-response), anxiety, and common mental disorders. Highly suggestive evidence (Class II) was found for all-cause mortality, heart disease mortality, type 2 diabetes (non-dose-response), depression, adverse sleep outcomes, wheezing, and obesity.
This umbrella review synthesizes a substantial body of evidence, linking ultra-processed food consumption to adverse health outcomes. The review's methodological rigor, including a comprehensive search strategy, use of the PECOS framework, and dual assessment of evidence credibility and quality (using pre-specified criteria and GRADE), strengthens the reliability of its findings. The quantitative results, showing a statistically significant association between higher UPF consumption and 71% of the examined health outcomes (including convincing evidence for cardiovascular mortality, type 2 diabetes, anxiety, and common mental disorders), are compelling and underscore the potential public health implications. While the inherent limitations of umbrella reviews and observational studies are acknowledged, the review's comprehensive scope, large sample size (nearly 10 million participants), and transparent reporting contribute to its overall high quality of evidence. The findings significantly advance the field by providing a robust overview of existing evidence and highlighting critical areas for future research, particularly mechanistic studies and targeted interventions to reduce UPF consumption. The review's clear policy implications and actionable recommendations make it a valuable resource for informing public health strategies and promoting healthier dietary patterns.
The abstract effectively summarizes the key findings of the umbrella review, including the number of pooled analyses, the overall association between ultra-processed food consumption and adverse health outcomes, and specific outcomes with convincing or highly suggestive evidence. This concise summary allows readers to quickly grasp the main takeaways of the research.
The abstract clearly states the objective, design, data sources, and eligibility criteria of the umbrella review. This transparency allows readers to understand the scope and methodology of the research.
The abstract highlights the novelty of the research by stating that no comprehensive umbrella review has been conducted on this topic before. This emphasizes the importance and potential impact of the study.
This is a high-impact improvement that would enhance the clarity and context of the abstract. The abstract mentions the use of pre-specified evidence classification criteria and the GRADE framework but doesn't explain what these are. Briefly defining these in the abstract would provide essential context for interpreting the results and allow readers to understand the strength and quality of the evidence presented. This is crucial for a non-technical audience who may not be familiar with these frameworks. Providing this context directly in the abstract, where these terms are first introduced, would significantly improve reader comprehension and allow for a more informed interpretation of the findings. Define the evidence classification criteria (convincing, highly suggestive, etc.) and the GRADE framework (high, moderate, low, very low quality) briefly in the abstract.
Implementation: Add a brief explanation of the evidence classification criteria and the GRADE framework within the abstract. For example, "Evidence was classified as convincing (Class I), highly suggestive (Class II), etc., and quality was assessed using the GRADE framework (high, moderate, low, very low)."
The introduction effectively establishes the context and relevance of the research by highlighting the global shift towards ultra-processed food consumption and its potential health implications. This background information sets the stage for the umbrella review and underscores its importance.
The introduction clearly states the gap in the existing literature, namely the lack of a comprehensive umbrella review on the association between ultra-processed food consumption and adverse health outcomes. This justification for the research strengthens the rationale for the study.
The introduction clearly defines ultra-processed foods using the NOVA classification system, providing a clear scope for the review. This definition ensures that the reader understands the specific type of food being investigated.
This is a high-impact improvement that would enhance the introduction's engagement with the reader and clarify the scope of the review. While the introduction mentions the increasing consumption of ultra-processed foods, it lacks specific data or statistics on the prevalence of this dietary pattern in different regions or populations. Providing such data would paint a clearer picture of the problem's magnitude and underscore the urgency of the research. Quantifying the prevalence of ultra-processed food consumption would strengthen the introduction by providing concrete evidence of the issue's scope and impact. This would make the review's rationale more compelling and resonate more strongly with readers, particularly policymakers and public health professionals. Ultimately, adding prevalence data on ultra-processed food consumption would significantly improve the introduction's impact by demonstrating the real-world relevance and urgency of the research.
Implementation: Incorporate specific data or statistics on the prevalence of ultra-processed food consumption in different regions or populations. For example, "In high-income countries, ultra-processed foods contribute to X% of the average diet, while in low-income countries, this figure is Y%."
This is a medium-impact improvement that would enhance the introduction's clarity and provide a more focused context for the review. The introduction mentions several potential health concerns related to ultra-processed foods but doesn't explicitly state which specific health outcomes will be the focus of the review. Clearly listing these outcomes upfront would provide a roadmap for the reader and improve the overall organization of the introduction. Listing the specific health outcomes would strengthen the introduction by providing a clear focus and guiding the reader's expectations. This would also improve the flow of the introduction by allowing for a more targeted discussion of the existing literature and the research gap being addressed. Ultimately, specifying the health outcomes under investigation would enhance the introduction's clarity and purpose by providing a more focused and organized overview of the review's scope.
Implementation: Explicitly list the specific health outcomes that will be the focus of the review. For example, "This review will focus on the association between ultra-processed food consumption and outcomes such as cardiovascular disease, type 2 diabetes, certain cancers, and mental health disorders."
The methods section clearly outlines the search strategy, including the databases used, search terms, and date range. This level of detail ensures transparency and allows for replication of the search process by other researchers.
The inclusion and exclusion criteria are well-defined using the PECOS framework, specifying the population, exposure, comparisons, outcomes, and study design. This structured approach ensures clarity and reduces ambiguity in the selection of studies.
The methods section describes the process of data extraction, including the use of a pre-piloted Excel spreadsheet and duplicate extraction by multiple researchers. This rigorous approach minimizes the risk of errors and biases in data collection.
This is a high-impact improvement that would enhance the reproducibility and transparency of the review. The methods section lacks detail on how disagreements between reviewers during the screening process were resolved. While consensus is mentioned, the specific process for achieving consensus isn't described. This information is crucial for understanding how potential biases were minimized during study selection. Providing a detailed explanation of the consensus process, such as whether a third reviewer was consulted or if a specific set of criteria was used to resolve disagreements, would strengthen the review's methodological rigor and allow others to replicate the process. Ultimately, clarifying the conflict resolution process would enhance the review's transparency and reproducibility, increasing confidence in the study's findings.
Implementation: Describe the specific process for resolving disagreements between reviewers during screening. For example, "Disagreements were resolved through discussion and consensus between the two reviewers. If consensus could not be reached, a third reviewer was consulted to make the final decision."
This is a medium-impact improvement that would enhance the transparency and comprehensiveness of the review. The methods section mentions prioritizing pooled estimates with the largest number of prospective cohorts but doesn't explain how this prioritization was operationalized. Specifically, the criteria used to select the "largest" cohort when multiple prospective studies were available for the same outcome is unclear. Providing a clear definition of "largest" (e.g., based on sample size, number of events, or study duration) would improve the transparency of the review process and allow readers to understand how the included studies were selected. This clarification would strengthen the methods section by providing a more detailed and reproducible account of the study selection process. Ultimately, defining the criteria for selecting the "largest" prospective cohort would enhance the review's methodological rigor and transparency.
Implementation: Specify the criteria used to define the "largest" prospective cohort. For example, "When multiple prospective cohorts were available for the same outcome, the cohort with the largest sample size was prioritized."
The Results section effectively presents the main findings of the umbrella review in a clear and organized manner. The use of forest plots (Figures 2 and 3) visually summarizes the direction and magnitude of the associations between ultra-processed food consumption and various health outcomes, making the data easily interpretable.
This is a high-impact improvement that would enhance the clarity and interpretability of the forest plots. The current forest plots lack a clear visual representation of the statistical significance of the effect estimates. Adding symbols or color-coding to indicate which effect estimates are statistically significant would improve the readability of the plots and allow readers to quickly identify the key findings. This enhancement would strengthen the Results section by making the visual representation of the data more informative and accessible to a wider audience. Ultimately, improving the visual clarity of the forest plots would enhance the communication of the study's findings and facilitate a more informed interpretation of the results.
Implementation: Add symbols or color-coding to the forest plots to clearly indicate which effect estimates are statistically significant (e.g., asterisks for p<0.05, bold text for p<0.01).
This is a medium-impact improvement that would enhance the transparency and reproducibility of the results. The Results section mentions the use of a random-effects model for re-analyzing the effect estimates but doesn't provide sufficient detail about the specific software or package used for this analysis. Providing the name and version of the software, along with any relevant parameters or settings used, would allow other researchers to replicate the analysis and verify the findings. This additional information would strengthen the Results section by enhancing the transparency and reproducibility of the statistical analysis. Ultimately, providing more detail about the random-effects model analysis would increase confidence in the study's findings and facilitate future research in this area.
Implementation: Specify the name and version of the software or package used for the random-effects model analysis. Include any relevant parameters or settings used in the analysis.
This is a medium-impact improvement that would enhance the clarity and context of the results. The Results section provides the number of participants included in the pooled analyses but doesn't specify the number of participants for each individual outcome. Providing the sample size for each outcome would allow readers to better understand the precision of the effect estimates and the potential influence of sample size on the findings. This additional information would strengthen the Results section by providing more context for interpreting the effect estimates and assessing the strength of the evidence for each outcome. Ultimately, providing sample sizes for each outcome would enhance the transparency and interpretability of the results.
Implementation: Include the sample size for each individual outcome in the Results section, either in the text or in supplementary materials.
Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart.
Fig. 2. Forest plot of non-dose-response relations between greater exposure to ultra-processed foods and risk of adverse health outcomes, with credibility and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) quality assessments.
Fig. 3. Forest plot of dose-response relations between greater exposure to ultra-processed foods and risk of adverse health outcomes, with credibility and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) quality assessments.
The discussion effectively synthesizes the findings of the umbrella review, providing a clear and concise summary of the main takeaways. It highlights the overall association between ultra-processed food consumption and adverse health outcomes, emphasizing the specific outcomes with the strongest evidence. This summary allows readers to quickly grasp the key findings and their implications.
The discussion acknowledges the limitations of the umbrella review methodology, such as the high-level overview and the lack of specific confounder or mediator adjustments. This transparency strengthens the review's credibility by addressing potential weaknesses and acknowledging the need for further research.
The discussion provides valuable insights into the potential mechanisms linking ultra-processed food consumption to adverse health outcomes. It explores factors like nutrient profile, displacement of nutritious foods, food matrix alterations, additives, contaminants, and energy intake, offering a comprehensive perspective on the complex interplay of factors involved.
The discussion effectively connects the findings of the review to policy implications, offering concrete recommendations for public health interventions. It discusses the role of food classification systems, existing public health measures, and the need for comprehensive strategies to reduce ultra-processed food consumption, demonstrating the practical relevance of the research.
This is a high-impact improvement that would enhance the discussion's practical relevance and provide specific guidance for future research. While the discussion mentions the need for further research, it lacks specific research questions or directions. Formulating specific research questions would provide a roadmap for future studies and facilitate targeted investigations to address the remaining uncertainties. This would strengthen the discussion by translating the review's findings into actionable steps for advancing the field. Ultimately, outlining specific research questions would enhance the discussion's impact by guiding future research and accelerating progress in understanding the complex relationship between ultra-processed food consumption and health.
Implementation: Formulate specific research questions or directions for future research. For example, "Future research should investigate the specific mechanisms by which ultra-processed foods contribute to inflammation and explore the role of individual food additives in adverse health outcomes."
This is a medium-impact improvement that would enhance the discussion's clarity and provide a more nuanced perspective on the findings. The discussion primarily focuses on the negative health outcomes associated with ultra-processed foods but doesn't adequately address the potential benefits or neutral effects observed for certain subcategories of ultra-processed foods. Acknowledging these nuances would provide a more balanced perspective and avoid oversimplifying the complex relationship between ultra-processed food and health. This would strengthen the discussion by presenting a more complete picture of the evidence and acknowledging the limitations of current knowledge. Ultimately, discussing the potential benefits or neutral effects of certain subcategories would enhance the discussion's objectivity and provide a more nuanced understanding of the findings.
Implementation: Expand the discussion to address the potential benefits or neutral effects observed for certain subcategories of ultra-processed foods. For example, "While the review found overall negative associations, some subcategories, such as ultra-processed cereals and dairy-based desserts, showed inverse or null associations with certain outcomes. Further research is needed to understand these discrepancies."
Fig. 4. Credibility and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) ratings for associations between greater exposure to ultra-processed foods and risks of each adverse health outcome
The conclusion effectively summarizes the key findings of the umbrella review, clearly stating the observed association between ultra-processed food consumption and adverse health outcomes. It emphasizes the outcomes with the strongest evidence, providing a concise overview of the review's main results.
This is a high-impact improvement that would enhance the conclusion's contribution to the broader scientific discourse. The conclusion focuses on summarizing the findings but doesn't explicitly discuss their implications for future research or clinical practice. Briefly outlining potential research directions or clinical recommendations based on the review's findings would provide valuable insights and guide future efforts in the field. Elaborating on these implications would strengthen the conclusion by demonstrating the practical relevance of the research and its potential to inform future studies and clinical interventions. This would also enhance the review's impact by providing a clear roadmap for future work and translating the findings into actionable recommendations. Ultimately, discussing the implications for future research and clinical practice would significantly improve the conclusion's contribution to the field by providing valuable guidance and stimulating further investigation.
Implementation: Add a brief discussion of the implications for future research and clinical practice. For example, "These findings suggest that reducing ultra-processed food consumption may be a promising strategy for preventing or managing chronic diseases. Future research should focus on developing and evaluating interventions to reduce UPF intake and explore the long-term health effects of such interventions."
This is a medium-impact improvement that would enhance the conclusion's clarity and provide a more nuanced perspective on the findings. The conclusion mentions the need for further investigation for certain outcomes but doesn't specify the types of studies needed or the specific research questions to be addressed. Providing more detail about the required research would strengthen the conclusion by offering concrete directions for future studies and facilitating targeted investigations to address the remaining uncertainties. This would also enhance the review's impact by guiding future research efforts and accelerating progress in the field. Ultimately, specifying the types of studies and research questions needed would improve the conclusion's contribution to the field by providing a more focused and actionable roadmap for future research.
Implementation: Specify the types of studies needed and the specific research questions to be addressed for outcomes requiring further investigation. For example, "Future research, including prospective cohort studies and randomized controlled trials, should investigate the dose-response relationship between ultra-processed food consumption and asthma, exploring the role of specific food additives and processing methods in the development of respiratory conditions."