Diet for COVID-19: real-time meta analysis of 27 studies

Table 1 summarizes the results for all studies, after exclusions, and for specific outcomes. Figure 2, 3, 4, 5, 6, 7, 8, and 9 show forest plots for random effects meta-analysis of all studies with pooled effects, mortality results, ICU admission, hospitalization, progression, recovery, cases, and viral clearance.

To avoid bias in the selection of studies, we analyze all non-retracted studies. Here we show the results after excluding studies with major issues likely to alter results, non-standard studies, and studies where very minimal detail is currently available. Our bias evaluation is based on analysis of each study and identifying when there is a significant chance that limitations will substantially change the outcome of the study. We believe this can be more valuable than checklist-based approaches such as Cochrane GRADE, which may underemphasize serious issues not captured in the checklists, overemphasize issues unlikely to alter outcomes in specific cases (for example, lack of blinding for an objective mortality outcome, or certain specifics of randomization with a very large effect size), or be easily influenced by potential bias. However, they can also be very high quality.

The studies excluded are as below. Figure 10 shows a forest plot for random effects meta-analysis of all studies after exclusions.

Hou, unadjusted results with no group details. Excluded results: severe case, moderate/severe case.

Magaña, unadjusted results with no group details.

Mahto, unadjusted results with no group details.

Mohajeri, unadjusted results with no group details.

Yamamoto, unadjusted results with no group details.

People with healthier diets have reduced risk for COVID-19. Statistically significant lower risk is seen for ICU admission, hospitalization, progression, recovery, cases, and viral clearance. 23 studies from 22 independent teams in 9 countries show statistically significant improvements. Meta analysis using the most serious outcome reported shows 50% [41‑58%] lower risk. Results are similar for higher quality studies. Results are robust — in exclusion sensitivity analysis 25 of 27 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.

Studies analyze diet quality before infection, and use different definitions of diet quality.

Rahmati present another meta analysis for diet, showing significant improvements for hospitalization and cases.

Aghajani: Case control study of 295 COVID-19 patients in Iran, showing lower risk of severe cases with higher dietary antioxidant quality scores, and with higher intake of vitamin D.

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Ahmadi: Retrospective 468,569 adults in the UK, showing significantly lower COVID-19 mortality with physical activity.

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Barania Adabi: Retrospective 500 COVID-19 patients, showing dietary inflammatory index (DII) and energy-adjusted dietary inflammatory index (E-DII) associated with COVID-19 severity.

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Ebrahimzadeh: Retrospective 250 recovered COVID-19 patients, showing lower risk of severe cases and shorter recovery and hospitalization times with a healthy diet.

Notably, all individual symptoms show lower incidence with a healthy diet with the exception of fever and chills. Fever and chills help the immune system fight infections (shivering helps to raise the body temperature).

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Firoozi: Retrospective 133 COVID-19 patients and 322 controls, showing higher risk of COVID-19 for diets that have a higher inflammatory index (E-DII).

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Hou: Retrospective 509 COVID-19 patients in Taiwan, showing higher risk of critical COVID-19 cases with non-vegetarian diets.

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Jagielski: Retrospective 95 people in Poland, showing significantly lower risk of COVID-19 with higher consumption of fruits, vegetables, and nuts. Diets with higher consumption of fruits, vegetables, and nuts had a significantly lower dietary inflammatory index.

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Kim: Retrospective healthcare workers in six countries with exposure to COVID-19 patients, showing lower risk of moderate/severe COVID-19 with plant-based diets.

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Magaña: Retrospective 89 COVID-19 patients in Spain, showing lower mortality with adherence to the Mediterranean diet.

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Mahto: Retrospective 689 healthcare workers in India, showing non-statistically significant lower risk of IgG positivity with a vegetarian diet in unadjusted results.

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Merino: Retrospective 592,571 participants in the UK and USA with 31,815 COVID-19 cases, showing lower risk or COVID-19 cases and severity for higher healthful plant-based diet scores. Notably, the assocation was less evident with higher levels of physical activity.

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Micek: Dietary analysis of 95 adults in Poland, showing lower risk of COVID-19 with higher intake of polyphenols, lignans, and phytosterols. Results were statistically significant for total phytosterols, secoisolariciresinol, β-sitosterol, matairesinol, and stigmasterol. Authors suggest that beneficial effects on gut microbiota and immune function may contribute to the lower risk.

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Mohajeri: Retrospective 600 COVID-19 patients in Iran with moderate/severe CT scans, showing lower prevalence of dyspnea, fever, taste/smell abnormalities, and cough with high adherence to the Mediterranean diet in unadjusted results.

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Moludi: Retrospective 60 COVID-19 hospitalized patients and 60 controls in Iran, showing pro-inflammatory diets associated with COVID-19 cases and severity. IR.KUMS.REC.1399·444, IR.TBZMED.REC.1399·225.

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Naushin: Retrospective 10,427 volunteers in India, 1,058 anti-nucleocapsid antibody positive, showing lower risk of seropositivity with a vegetarian diet.

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Nguyen: Analysis of 3,947 participants in Vietnam, showing significantly lower risk of COVID-19-like symptoms with physical activity and with a healthy diet. The combination of being physically active and eating healthy reduced risk further compared to either alone. The analyzed period was Feb 14 to Mar 2, 2020, which may have been before testing was widely available.

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Perez-Araluce: Retrospective 5,194 participants in Spain with 382 COVID-19 cases, showing lower risk of COVID-19 with high adherence to a Mediterranean diet, with statistical significance only when excluding healthcare professionals.

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Reis: Retrospective 546 COVID+ patients in the USA, showing lower risk of hospitalization with higher consumption of vegetables.

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Tadbir Vajargah: Retrospective 250 hospitalized patients in Iran, showing higher consumption of fruits, vegetables, and fiber associated with lower COVID-19 severity.

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Wang: Retrospective 148 hospitalized COVID-19 patients in China, showing lower severity and faster viral clearance with improved nutrition.

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Wang (B): Prospective analysis of 32,249 women from the Nurses’ Health Study II in the USA, showing lower risk of PASC with a healthy lifestyle, and in a dose-dependent manner. Participants with 5 or 6 healthy lifestyle factors had significantly lower COVID-19 hospitalization and PASC. BMI and sleep were independently associated with risk of PASC.

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Yamamoto: Retrospective 84 flight attendants, 52 reporting COVID-19 status and diet quality, showing higher risk of COVID-19 with lower self-reported diet quality.

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Yue: Analysis of 42,935 participants showing lower risk of COVID-19 with healthier diets. Risk of severe cases was also lower with healthier diets, while not reaching statistical significance. Severity results are only provided with diet indices as a continuous variable.

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Zamanian: Case control study with 53 inpatients and 88 outpatients in Iran, showing lower risk of hospitalization with increased adherence to the DASH (Dietary Approach to Stop Hypertension) diet. Increased intake of fruits, vegetables and low-fat dairy products, and lower intake of sodium and processed/red meat were significantly associated with reduced risk of hospitalization due to COVID-19.

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Zargarzadeh: Retrospective 250 COVID-19 patients in Iran, showing lower risk of severe disease with greater adherence to a Mediterranean diet.

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Zhao: UK Biobank retrospective 196,154 participants with 11,288 COVID-19 cases, showing lower COVID-19 mortality, severity, and incidence for lower dietary inflammatory scores.

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Zhou: Prospective study of 41,012 UK Biobank participants, showing higher risk of COVID-19 cases with ultra-processed food consumption.

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We performed ongoing searches of PubMed, medRxiv, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19early.org. Search terms were diet AND COVID-19. Automated searches are performed every few hours with notification of new matches. All studies regarding the use of diet for COVID-19 that report a comparison with a control group are included in the main analysis. Sensitivity analysis is performed, excluding studies with major issues, epidemiological studies, and studies with minimal available information. This is a living analysis and is updated regularly.

We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days are used. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms were not used (the next most serious outcome is used — no studies were excluded). For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcome is considered more important than PCR testing status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available (after most or all patients have recovered there is no room for an effective treatment to do better). If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO₂ is more important than cough. When results provide an odds ratio, we computed the relative risk when possible, or converted to a relative risk according to Zhang. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported including propensity score matching (PSM), the PSM results are used. Adjusted primary outcome results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed Altman, Altman (B), and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1 Sweeting. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.11.4) with scipy (1.11.1), pythonmeta (1.26), numpy (1.25.0), statsmodels (0.14.0), and plotly (5.15.0).

Forest plots are computed using PythonMeta Deng with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor (3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.

We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.

We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective McLean, Treanor.

Effect extraction follows pre-specified rules as detailed above and gives priority to more serious outcomes. For pooled analyses, the first (most serious) outcome is used, which may differ from the effect a paper focuses on. Other outcomes are used in outcome specific analyses.

Supplementary Data