ReviewEuropean journal of clinical nutrition2024
Reporting quality and risk of bias of systematic reviews of ultra-processed foods: a methodological study.
Review in European journal of clinical nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ultra-processed foods consumption and health-related outcomes: a systematic review of randomized controlled trials.Frontiers in nutrition · 2024Pooled it
- Acupuncture treatment of diabetic peripheral neuropathy: an overview of systematic reviews based on evidence mapping.Frontiers in neurology · 2024Pooled it
- Ultra-processed foods and cardiometabolic risk: from evidence to policy.npj metabolic health and disease · 2026Article
- Trend, application, and reporting of Mini-health technology assessment: an evidence mapping.International journal of technology assessment in health care · 2025Article
- Mapping Crohn's Disease Pathogenesis with Mycobacterium paratuberculosis: A Hijacking by a Stealth Pathogen.Digestive diseases and sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A dramatic shift in the global food system is occurring with the rapid growth of ultra-processed foods (UPFs) consumption, which poses potentially serious health risks. Systematic review (SR) method has been used to summarise the association between UPF consumption and multiple health outcomes; however, a suboptimal-quality SR may mislead the decision-making in clinical practices and health policies. Therefore, a methodological review was conducted to identify the areas that can be improved regarding the risk of bias and reporting quality of relevant SRs. Systematic searches to collect SRs with meta-analyses of UPFs were performed using four databases from their inception to April 14, 2023. The risk of bias and reporting quality were evaluated using ROBIS and PRISMA 2020, respectively. The key characteristics of the included SRs were summarised descriptively. Excel 2019 and R 4.2.3 were used to analyse the data and draw graphs. Finally, 16 relevant SRs written in English and published between 2020 and 2023 in 12 academic journals were included. Only one SR was rated as low risk of bias, and the others were rated as higher risk of bias mainly because the risk of bias in the original studies was not explicitly addressed when synthesising the evidence. The reporting was required to be advanced significantly, involving amendments of registration and protocol, data and analytic code statement, and lists of excluded studies with justifications. The reviews' results could improve the quality, strengthen future relevant SRs' robustness, and further underpin the evidence base for supporting clinical decisions and health policies.
Indexed as
Identifiers
38093096What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.