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Record W4393141769 · doi:10.1101/2024.03.24.24304597

Relevance of Mediterranean diet as a nutritional strategy in diminishing COVID-19 risk: A systematic review

2024· review· en· W4393141769 on OpenAlexaboutno aff
Ceria Halim, Miranda Howen, Athirah Amirah Nabilah binti Fitrisubroto, Timotius Pratama, Indah Ramadhani Harahap, Lacman Jaya Ganesh, Andre Marolop Pangihutan Siahaan

Bibliographic record

VenuemedRxiv · 2024
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
Fundersnot available
KeywordsMediterranean dietObservational studySystematic reviewMedicineCoronavirus disease 2019 (COVID-19)Inclusion and exclusion criteriaMeta-analysisMEDLINEPopulationSample size determinationDemographyEnvironmental healthInternal medicineAlternative medicineBiologyPathologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Mediterranean Diet has been reported to possess immunomodulatory and anti-inflammatory properties. These properties are closely associated with the immunopathogenesis of COVID-19. Objective The present systematic review aimed to determine the association between Mediterranean Diet and COVID-19, COVID-19 symptoms, and COVID-19 severity. Methods The protocol for this systematic review was registered in International Prospective Register of Systematic Reviews (PROSPERO) with identification number CRD42023451794. The literature search was conducted through Pubmed, Proquest, and Google Scholar on August 2023. The inclusion criteria were studies with a population of human subjects, reported the association between Mediterranean diet adherence with risk of COVID-19 infection, COVID-19 symptoms, or COVID-19 severity, and full text must be available in English. The exclusion criteria were reviews, editorials, letters, replies, systematic reviews, meta-analyses, studies on animals, and duplicates. Risk of bias in included studies was assessed using Newcastle Ottawa Scale (NOS). Data was synthesized narratively. Each study was compared and a structured summary was developed. Results After selection process, 6 articles were included, with a sample size of 55,489 patients. All studies were observational studies and assessed Mediterranean diet adherence using food frequency questionnaires (FFQ), with scoring system varied between each study. Four studies found a significant correlation between increased adherence to Mediterranean Diet and reduced COVID-19 risk, while one study indicated non-significant association. One study reported a significant association between higher adherence to Mediterranean Diet and COVID-19 symptoms, but three studies reported non-significant association. One study found that individuals with higher adherence to Mediterranean Diet had reduced likelihood of developing severe COVID-19, however, two studies yielded inconclusive findings. Limitations All studies used self-administrated food frequency questionnaires (FFQs), which were prone to biased responses, such as recall and estimation bias. Discussion Lower trends of odds ratios (ORs) were consistently observed in higher Mediterranean diet adherence. In every outcome of the included studies, ORs ranged between 0.06-0.992, however, differing levels of significance were reported in each outcome. Conclusion Overall analyses suggest that high adherence to Mediterranean Diet is a protective factor against COVID-19, with unclear benefits against COVID-19 symptoms and severity. Primary Funding Source The author(s) received no specific funding for this work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.100
GPT teacher head0.400
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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