Covid Analysis, May 22, 2022, DRAFT
https://c19early.com/dtmeta.html
•Statistically significant improvement is seen for cases. 5 studies from 5 independent teams in 3 different countries show statistically significant
improvements in isolation.
•Meta analysis using the most serious outcome reported shows
54% [27‑71%] improvement. Results are similar after exclusions.
•Studies analyze diet quality before infection, and use different definitions of diet quality.
•No treatment, vaccine, or intervention is 100%
available and effective for all variants. All practical, effective, and safe
means should be used.
Denying the efficacy of treatments increases mortality, morbidity, collateral
damage, and endemic risk.
•All data to reproduce this paper and
sources are in the appendix.
Highlights
A healthier diet reduces
risk for COVID-19 with very high confidence for cases and in pooled analysis.
We show traditional outcome specific analyses and combined
evidence from all studies.
Real-time updates and corrections,
transparent analysis with all results in the same format, consistent protocol
for 42
treatments.
Figure 1. A. Random effects
meta-analysis. This plot shows pooled effects, discussion can be found in the heterogeneity section,
and results for specific outcomes can be found in the individual outcome analyses.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the appendix.
B. Scatter plot showing the
distribution of effects reported in studies. C. History of all reported
effects (chronological within treatment stages).
Introduction
We analyze all significant studies
reporting COVID-19 outcomes as a function of diet quality and providing adjusted results.
Search methods, inclusion criteria, effect
extraction criteria (more serious outcomes have priority), all individual
study data, PRISMA answers, and statistical methods are detailed in
Appendix 1. We present random effects meta-analysis results for all
studies, for studies within each treatment stage, for individual outcomes, for
peer-reviewed studies, for Randomized Controlled Trials (RCTs), and after
exclusions.
Results
Figure 2 shows a visual overview of the results, with details in
Table 1 and Table 2.
Figure 3, 4, and 5
show forest plots for a random effects meta-analysis of
all studies with pooled effects, mortality results, and cases.
Figure 2. Overview of results.
Treatment time | Number of studies reporting positive effects | Total number of studies | Percentage of studies reporting positive effects | Random effects meta-analysis results |
Prophylaxis | 6 | 7 | 85.7% |
54% improvement RR 0.46 [0.29‑0.73] p = 0.00099 |
All studies | 6 | 7 | 85.7% |
54% improvement RR 0.46 [0.29‑0.73] p = 0.00099 |
Table 1. Results by treatment stage.
Studies | Prophylaxis | Patients | Authors | |
All studies | 7 | 54% [27‑71%] | 585,031 | 77 |
With exclusions | 6 | 55% [25‑73%] | 584,942 | 71 |
Table 2. Results by treatment stage for all studies and with different exclusions.
Figure 3. Random effects meta-analysis for all studies with pooled effects.
This plot shows pooled effects, discussion can be found in the heterogeneity section,
and results for specific outcomes can be found in the individual outcome analyses.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the appendix.
Figure 4. Random effects meta-analysis for mortality results.
Figure 5. Random effects meta-analysis for cases.
Exclusions
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 6 shows a forest plot for random
effects meta-analysis of all studies after exclusions.
[Magaña], unadjusted results with no group details.
Figure 6. Random effects meta-analysis for all studies after exclusions.
This plot shows pooled effects, discussion can be found in the heterogeneity section,
and results for specific outcomes can be found in the individual outcome analyses.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the appendix.
Conclusion
People with healthier diets have reduced risk for COVID-19.
Statistically significant improvement is seen for cases. 5 studies from 5 independent teams in 3 different countries show statistically significant
improvements in isolation.
Meta analysis using the most serious outcome reported shows
54% [27‑71%] improvement. Results are similar after exclusions.
Studies analyze diet quality before infection, and use different definitions of diet quality.
Study Notes
[Ahmadi]
Retrospective 468,569 adults in the UK, showing significantly lower COVID-19 mortality with physical activity.
[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.
[Magaña]
Retrospective 89 COVID-19 patients in Spain, showing lower mortality with adherence to the Mediterranean diet.
[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.
[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.
[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.
[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.
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.com. 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
(3.9.12) with
scipy (1.8.0), pythonmeta (1.26), numpy (1.22.2), statsmodels (0.14.0), and plotly (5.6.0).
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].
A summary of study results is below. Please submit
updates and corrections at https://c19early.com/dtmeta.html.
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.
[Ahmadi], 8/31/2021, retrospective, United Kingdom, Europe, peer-reviewed, 5 authors. | risk of death, 3.0% higher, RR 1.03, p = 0.85, adjusted per study, good vs. poor, model 2, multivariable. |
[Kim], 6/7/2021, retrospective, multiple countries, multiple regions, peer-reviewed, survey, 8 authors, study period 17 July, 2020 - 25 September, 2020. | risk of moderate/severe case, 72.0% lower, OR 0.28, p = 0.02, higher quality diet 41, lower quality diet 527, adjusted per study, plant-based diets, multivariable, RR approximated with OR. |
risk of moderate/severe case, 59.0% lower, OR 0.41, p = 0.05, higher quality diet 46, lower quality diet 522, adjusted per study, plant-based or pescatarian diets, multivariable, RR approximated with OR. | |
risk of case, 19.0% lower, OR 0.81, p = 0.24, higher quality diet 41, lower quality diet 527, adjusted per study, plant-based diets, multivariable, RR approximated with OR. | |
risk of case, 23.0% lower, OR 0.77, p = 0.14, higher quality diet 46, lower quality diet 522, adjusted per study, plant-based or pescatarian diets, multivariable, RR approximated with OR. | |
[Magaña], 12/31/2021, retrospective, Spain, Europe, peer-reviewed, 6 authors, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 53.0% lower, HR 0.47, p = 0.049, higher quality diet 58, lower quality diet 31. |
[Merino], 6/25/2021, retrospective, multiple countries, multiple regions, peer-reviewed, survey, 30 authors, study period 24 March, 2020 - 2 December, 2020. | risk of severe case, 41.0% lower, HR 0.59, p < 0.001, higher quality diet 148,142, lower quality diet 148,143, adjusted per study, model 3, high vs. low hPDI, multivariable, Cox proportional hazards. |
risk of case, 18.0% lower, HR 0.82, p < 0.001, higher quality diet 148,142, lower quality diet 148,143, adjusted per study, model 3, high vs. low hPDI, PCR+, multivariable, Cox proportional hazards. | |
risk of case, 9.0% lower, HR 0.91, p < 0.001, higher quality diet 148,142, lower quality diet 148,143, adjusted per study, model 3, high vs. low hPDI, multivariable, Cox proportional hazards. | |
[Moludi], 8/23/2021, retrospective, Iran, Middle East, peer-reviewed, 7 authors, study period June 2020 - July 2020. | risk of case, 91.6% lower, OR 0.08, p < 0.001, case control OR, model 3, E-DII tertile 1 vs. tertile 3. |
[Nguyen], 9/18/2021, retrospective, Vietnam, South Asia, peer-reviewed, survey, 17 authors, study period 14 February, 2020 - 2 March, 2020. | risk of symptomatic case, 15.2% lower, RR 0.85, p = 0.006, higher quality diet 345 of 1,054 (32.7%), lower quality diet 433 of 1,082 (40.0%), NNT 14, adjusted per study, odds ratio converted to relative risk, high vs. low HES, COVID-19-like symptoms, multivariable. |
[Perez-Araluce], 1/24/2022, retrospective, Spain, Europe, peer-reviewed, survey, 4 authors, study period March 2020 - December 2020. | risk of severe case, 77.9% lower, RR 0.22, p = 0.15, higher quality diet 1 of 1,103 (0.1%), lower quality diet 10 of 3,300 (0.3%), NNT 471, odds ratio converted to relative risk, high vs. low adherence. |
risk of symptomatic case, 15.1% lower, RR 0.85, p = 0.31, higher quality diet 52 of 1,103 (4.7%), lower quality diet 214 of 3,300 (6.5%), odds ratio converted to relative risk, high vs. low adherence. | |
risk of case, 19.7% lower, RR 0.80, p = 0.14, higher quality diet 58 of 1,103 (5.3%), lower quality diet 248 of 3,300 (7.5%), odds ratio converted to relative risk, high vs. low adherence. |
Supplementary Data
References
Ahmadi et al., Brain, Behavior, and Immunity, doi:10.1016/j.bbi.2021.04.022,
Lifestyle risk factors and infectious disease mortality, including COVID-19, among middle aged and older adults: Evidence from a community-based cohort study in the United Kingdom,
https://www.sciencedirect.com/science/article/pii/S088915912100180X.
Altman, D., BMJ, doi:10.1136/bmj.d2304,
How to obtain the P value from a confidence interval,
https://www.bmj.com/content/343/bmj.d2304.
Altman (B) et al., BMJ, doi:10.1136/bmj.d2090,
How to obtain the confidence interval from a P value,
https://www.bmj.com/content/343/bmj.d2090.
Kim et al., BMJ Nutrition, Prevention & Health, doi:10.1136/bmjnph-2021-000272,
Plant-based diets, pescatarian diets and COVID-19 severity: a population-based case–control study in six countries,
https://nutrition.bmj.com/content/4/1/257.
Magaña et al., Clinical Nutrition ESPEN, doi:10.1016/j.clnesp.2021.09.606,
Influence of mediterranean diet on survival from covid-19 disease,
https://www.sciencedirect.com/science/article/pii/S2405457721009293.
McLean et al., Open Forum Infect. Dis. September 2015, 2:3, doi:10.1093/ofid/ofv100,
Impact of Late Oseltamivir Treatment on Influenza Symptoms in the Outpatient Setting: Results of a Randomized Trial,
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525010/.
Merino et al., Gut, doi:10.1136/gutjnl-2021-325353 (preprint 6/25/2021),
Diet quality and risk and severity of COVID-19: a prospective cohort study,
https://gut.bmj.com/content/70/11/2096.
Moludi et al., British Journal of Nutrition, doi:10.1017/S0007114521003214,
The relationship between Dietary Inflammatory Index and disease severity and inflammatory status: a case–control study of COVID-19 patients,
https://www.cambridge.org/core/ser..ore/content/view/S0007114521003214.
Nguyen et al., Nutrients, doi:10.3390/nu13093258,
Single and Combinative Impacts of Healthy Eating Behavior and Physical Activity on COVID-19-like Symptoms among Outpatients: A Multi-Hospital and Health Center Survey,
https://www.mdpi.com/2072-6643/13/9/3258.
Perez-Araluce et al., Frontiers in Nutrition, doi:10.3389/fnut.2021.805533,
Components of the Mediterranean Diet and Risk of COVID-19,
https://www.frontiersin.org/articles/10.3389/fnut.2021.805533/full.
Sweeting et al., Statistics in Medicine, doi:10.1002/sim.1761,
What to add to nothing? Use and avoidance of continuity corrections in meta‐analysis of sparse data,
https://onlinelibrary.wiley.com/doi/10.1002/sim.1761.
Please send us corrections, updates, or comments. Vaccines and
treatments are both valuable and complementary. All practical, effective, and
safe means should be used. No treatment, vaccine, or intervention is 100%
available and effective for all current and future variants. Denying the
efficacy of any method increases mortality, morbidity, collateral damage, and
the risk of endemic status. We do not provide medical advice. Before taking
any medication, consult a qualified physician who can provide personalized
advice and details of risks and benefits based on your medical history and
situation. FLCCC and WCH
provide treatment protocols.