<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.121933.2</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Effect of natural products use prior to infection with COVID-19 on disease severity and hospitalization: A self-reported cross-sectional survey study</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 2; peer review: 2 approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Nimer</surname>
                        <given-names>Refat M.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-0545-3311</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Khabour</surname>
                        <given-names>Omar F.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-3006-3104</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Swedan</surname>
                        <given-names>Samer F.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kofahi</surname>
                        <given-names>Hassan M.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Medical Laboratory Sciences, Jordan University of Science and Technology, Irbid, 22110, Jordan</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:rmnimer@just.edu.jo">rmnimer@just.edu.jo</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>11</day>
                <month>7</month>
                <year>2022</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2022</year>
            </pub-date>
            <volume>11</volume>
            <elocation-id>639</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>4</day>
                    <month>7</month>
                    <year>2022</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Nimer RM et al.</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/11-639/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> Managing coronavirus disease 2019 (COVID-19) using available resources is essential to reduce the health burden of disease. The severity of COVID-19 is affected by nutritional status. In this study the effect of natural products use prior to infection with COVID-19 on disease severity and hospitalization was explored.</p>
                <p>
                    <bold>Methods:</bold> This was a cross-sectional study. Between March and July 2021, a self-administered survey was conducted in Jordan. Individuals who recovered from COVID-19 and were &#x2265;18 years old were the study population. Study measures included the use of natural products, COVID-19 severity, and hospitalization status. A multivariate regression model was used for statistical analysis.</p>
                <p>
                    <bold>Results:</bold> The mean age (mean &#x00b1; SD) of the study sample (n=2,148) was 40.25 &#x00b1; 15.58 years. Multivariate logistic regression showed that the regular intake of carnation (OR [0.56], CI [0.37&#x2013;0.85]), onion (OR [0.69], CI [0.52&#x2013;0.92]), lemon (OR [0.68], CI [0.51&#x2013;0.90]), and citrus fruits (OR [0.66], CI [0.50&#x2013;0.89]) before infection were associated with a substantial reduction in COVID-19 severity (P&lt;0.01). Also, the consumption of carnation (OR [0.55], CI [0.34&#x2013;0.88]), lemon (OR [0.57], CI [0.42&#x2013;0.78]), and citrus fruits (OR [0.61], CI [0.44&#x2013;0.84]) were associated with a significant decrease in the frequency of COVID-19-induced hospitalization (P&lt;0.01).</p>
                <p>
                    <bold>Conclusions:</bold> Regular consumption of carnation, lemon, and citrus fruits before infection was associated with better outcomes for COVID-19. Studies on other populations are required to confirm these findings.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19</kwd>
                <kwd>natural products</kwd>
                <kwd>carnation</kwd>
                <kwd>onion</kwd>
                <kwd>lemon</kwd>
                <kwd>citrus</kwd>
                <kwd>hospitalization</kwd>
                <kwd>severity</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1" xlink:href="http://dx.doi.org/10.13039/501100019004">
                    <funding-source>Deanship of Research, Jordan University of Science and Technology</funding-source>
                    <award-id>Grantnumber20210173</award-id>
                </award-group>
                <funding-statement>This work was supported by the Deanship of Research, Jordan University of Science and Technology (Grant number 20210173; to Dr. Refat Nimer).</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 1</title>
                <p>This version was updated based on reviewers' comments. - all the results expressed as N (%) - The way of Carnation consumption was included. - The reference.PMID: 33511704 was added. - The&#x00a0;covariates in&#x00a0;multivariate logistic regression were incorporated. - Lemon is kept a separate category from citrus because some studies showed variations in their nutritional values. These studies were incorporated into the new version. - The&#x00a0;inclusion criteria were updated. -&#x00a0;The table is updated based on reviewer comments to express gender, age, and BMI in N% instead of Mean+-SD.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>Coronavirus disease 2019 (COVID-19) is a global pandemic due to the SARS-CoV-2 that causes severe acute respiratory syndrome.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Since the World Health Organization (WHO) declared the pandemic in March, 2020, the mortality toll from COVID-19 worldwide has passed six million by April 2022.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> SARS-CoV-2 can cause a wide variety of symptoms, from asymptomatic infection to severe acute respiratory syndrome and death.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>Maintaining a healthy diet has been suggested as a way to boost immune functions and protect against severe infections.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Certain foods and natural products contain bioactive constituents that have immunomodulating, anti-inflammatory, antioxidant, antibacterial, and antiviral properties. Hence, they can be used for pre- and post-exposure prophylaxis to enhance the activity and quantity of cytokines and different types of white blood cells.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Therefore, natural products may enhance viral infection outcomes by reducing inflammation and respiratory symptoms.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>Most people in the Middle East region still consume traditional medicinal herbs, immune-boosting foods, and drinks as part of their diet.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> During the pandemic, increased demand on medicinal natural products certain foods, drinks, and medicinal herbs such as ginger, garlic, turmeric, and citrus fruits, has been observed.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
            </p>
            <p>Several studies have examined the effect of consumption of certain foods, drinks, and medicinal herbs on COVID-19 progression.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> However, the method of preparing and consuming these natural products may vary for different populations, which may affect the desired benefits of these products. In addition, each geographical area or country may have unique medicinal herbs and immunomodulatory foods. In Jordan, the effect of regular consumption of certain immune-boosting foods and medicinal herbs prior to infection with COVID-19 on the clinical course has not yet been investigated. Due to the seriousness of COVID-19, we hypothesized that an increase in the use of some immune-boosting foods and medicinal herbs would be associated with a less severe form of COVID-19. Therefore, the current study examined the association between the use of many natural products prepared from natural sources at home and foods that boost the immune system (green tea, black caraway, Indian costus, cumin, turmeric, anis, chamomile, propolis, honey, carnation, star anis, onion, garlic, lemon, and citrus fruits) before infection with the risk of COVID-19 severity and hospitalization in Jordan. The selected natural products are the most widely used in Jordan.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Study design and subjects</title>
                <p>This cross-sectional survey was carried out in Jordan (between March and July 2021) as part of the Jordanian COVID-19 survey project (JCSP).
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> The Institutional Review Board of Jordan University of Science and Technology granted ethical approval for the project (Ref.: 3/139/2021, dated 30/03/2021). Adults (&#x2265;18 years old) who recovered from COVID-19 were included in the current investigation. Participants were recruited from public places such as bus stations, parks, religious places, universities, and restaurants. The cover page of the questionnaire outlined the criteria for participation in the study, which included infection with COVID-19 and recovery from illness. Research assistants emphasized to participants that infection should have been confirmed by polymerase chain reaction (PCR). Exclusion criteria included current COVID-19 infection and vaccination prior to contracting the virus. Persons previously vaccinated were excluded since vaccination has a considerable influence on disease severity and may mask the potential benefits of the consumption of medicinal herbs and immune-boosting foods on the dependent variables of the study. This cross-sectional study was designed as recommended by the STROBE checklist.
                    <sup>
                        <xref ref-type="bibr" rid="ref18">18</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec4">
                <title>Study instrument</title>
                <p>The current study used a self-administered questionnaire in Arabic, which can be found translated into English as 
                    <italic toggle="yes">Underlying data.</italic>
                    <sup>
                        <xref ref-type="bibr" rid="ref67">67</xref>
                    </sup> Participants were asked about their demographics (age, gender, body mass index (BMI), and education), comorbidities, and consumption of medicinal herbs and immune-boosting foods before infection with COVID-19. Furthermore, infection symptoms and admission to hospital data were gathered. A panel of area specialists validated the questionnaire, which was then piloted on a limited number of participants. The opinions of experts and participants were gathered and utilized to assess and enhance the clarity of the questionnaire. Results of the first draft of the questionnaire were excluded from the final analysis. The principal investigators&#x2019; involvement in data collection was minimized to reduce sources of bias. Participants were chosen to represent various Jordanian geographical regions, and information was gathered from them through an online questionnaire supplied to participants by trained research assistants. We used specific techniques to reduce response bias as much as possible. First, the researcher did not interpret the questionnaire because it was self-administered. Second, we double-checked the items&#x2019; clarity by translating them into Arabic. Finally, all duplicate entries were eliminated.</p>
            </sec>
            <sec id="sec5">
                <title>Sample size calculation</title>
                <p>The sample size for our study was calculated using the online Raosoft sample size calculator (Raosoft Inc., Seattle, WA, USA). According to the world meter elaboration of the most recent United Nations data, Jordan&#x2019;s population is around 10 million people. The confidence level was set at 95%, the margin of error was set at 3%, and the response distribution was set at 50%. With 770,712 confirmed cases, including children, reported by the end of July 2021,
                    <sup>
                        <xref ref-type="bibr" rid="ref19">19</xref>
                    </sup> the recommended sample size was 1067. Of note, the number of cases under the age of 18 at the time of sample collection, which occurred before the emergence of the Omicron variant, was expected to be small compared to adult cases (no data available). Therefore, if cases under 18 years of age were subtracted from the total, it would lead to a negligible change in the sample size. However, the size of the sample recruited (n = 2,148) was larger than what was required to represent the COVID-19 cases in Jordan, even if child cases were taken into consideration.</p>
            </sec>
            <sec id="sec6">
                <title>Recruitment of subjects</title>
                <p>A convenient sampling procedure was used in the study. &#x201c;Google Forms&#x201d; was used to create and administer the survey. To ensure anonymity, the study did not collect identifying information, such as participants&#x2019; names and places of work. In addition, the data were saved in encrypted digital format that required a password to access. The first section of the questionnaire sought informed consent and confirmed recovery from COVID-19. All participants provided informed consent. Anyone could opt out and withdraw from the survey by not submitting their answers, so participation was entirely voluntary. To ensure that the Jordanian population is adequately represented, trained researchers recruited participants from various Jordanian governorates. The questionnaire was completed by a total of 2,148 participants.</p>
            </sec>
            <sec id="sec7">
                <title>Classification of COVID-19 severity</title>
                <p>Based on symptoms, the severity of COVID-19 infection was classified into two categories; severe and non-severe (asymptomatic, mild symptoms, and moderate), as previously reported.
                    <sup>
                        <xref ref-type="bibr" rid="ref20">20</xref>
                    </sup> Fever, sore throat, body pains, and nausea, with no signs or symptoms of pneumonia, were considered mild cases. Pneumonia (persistent fever and cough) but no hypoxemia (arterial oxygen saturation measured by pulse oximetry (SpO
                    <sub>2</sub>) &#x2264; 92%) were considered moderate cases.
                    <sup>
                        <xref ref-type="bibr" rid="ref20">20</xref>
                    </sup> Confirmed severe pneumonia and hypoxemia were considered severe cases. It is worth noting that during peak COVID-19 waves, several patients were not admitted to hospitals because of the increased burden on hospitals.
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> As a result, such cases received medical care at home through private doctor visits, and some used medical oxygen supply systems in their homes.</p>
            </sec>
            <sec id="sec8">
                <title>Statistical analysis</title>
                <p>In this study, the independent variables were the use of natural products (medicinal herbs, immune-boosting foods), whereas the dependent variables were COVID-19 severity and hospitalization. All data with missing values were excluded from the analysis. For different variables, percentages, frequencies, means, and standard deviations (SD), were used as appropriate. The Chi-squared test was utilized to determine any differences in severity/hospitalization between users of natural products. Multivariate logistic regression was applied to examine the impact of natural food use on the severity/hospitalization while controlling for different confounders. The adjusted odds ratios (OR) and 95% confidence interval (CI) were presented. P&lt;0.05 indicates statistical significance. The data were analyzed using IBM SPSS Statistics v23 (RRID:SCR_016479).</p>
            </sec>
        </sec>
        <sec id="sec9" sec-type="results">
            <title>Results</title>
            <sec id="sec10">
                <title>Demographic characteristics of the participants</title>
                <p>The questionnaire was completed by 2,148 participants. The demographics of the sample are summarized in 
                    <xref ref-type="table" rid="T1">Table 1</xref>.
                    <sup>
                        <xref ref-type="bibr" rid="ref67">67</xref>
                    </sup> Women comprised 58.2% of participants. The participants&#x2019; mean age was 40.25&#x00b1;15.58 years. The majority of participants had non-severe COVID-19 infection and were not admitted to hospitals (87.9% and 89.8%, respectively). Among the participants, 16.9% were smokers, and 23.1% had at least one comorbidity (
                    <xref ref-type="table" rid="T1">Table 1</xref>).</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Demographics of the sample.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">n (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Reported age (years)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">18-40</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1203 (56.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">41-60</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">684 (31.8)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">More than 60</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">261 (12.2)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sex</td>
                                <td align="left" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">903 (42.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1245 (58.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Body mass index</td>
                                <td align="left" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;24.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">723 (33.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">25-29.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">786 (36.6)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;30</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">639 (29.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Tobacco use </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">362 (16.85)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Chronic diseases</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">496 (23.09)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">COVID-19
                                    <xref ref-type="table-fn" rid="tfn1">*</xref> infection status</td>
                                <td align="left" colspan="1" rowspan="1" valign="top"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Severe disease</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">260 (12.10)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Non-severe disease</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,888 (87.89)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Admitted to hospital</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">219 (10.19)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>*</label>
                                <p>COVID-19, coronavirus disease 2019. Total n=2148.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec11">
                <title>Association of natural products use with COVID-19 severity and hospitalization</title>
                <p>COVID-19 severity/hospitalizations were investigated in relation to the use of medicinal herbs and immune-boosting foods (
                    <xref ref-type="table" rid="T2">Table 2</xref>). Lemon and citrus fruits were associated with lower incidence of severe COVID-19 and hospitalization (P&lt;0.01). Moreover, intake of ginger and green tea was associated with reduced disease severity (P=0.018 and P=0.036, respectively). However, no significant effects on severe COVID-19 and hospitalization outcomes were observed due to consumption of anise, chamomile, propolis, honey, onions, garlic, carnation, star anise, black caraway, Indian costus, and turmeric, prior to infection.</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>Table 2. </label>
                    <caption>
                        <title>Severe COVID-19 and hospitalization cases based on natural product use prior to infection.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="2" rowspan="3" valign="top"/>
                                <th align="left" colspan="5" rowspan="1" valign="top">COVID-19 classification</th>
                                <th align="left" colspan="5" rowspan="1" valign="top">Hospitalized</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="2" rowspan="1" valign="top">Non-severe</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">Severe</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">P-value</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">No</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">Yes</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">P-value</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">n</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">n</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">n</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">n</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume anise before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,029</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">148</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.6%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.43</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,053</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">124</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.40</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">827</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">107</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">846</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.4%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume chamomile before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,229</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">173</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,263</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">139</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.9%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.85</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">628</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">79</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">635</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.2%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume propolis before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,714</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">235</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,755</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">194</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.0%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.30</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">101</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">101</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.9%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume honey before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,023</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">135</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.7%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.69</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,050</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">108</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.27</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">840</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">117</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">854</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">103</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.8%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume onions before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">993</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">147</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.9%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,023</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">117</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.78</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">863</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">108</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">875</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">96</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.9%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume garlic before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,075</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">144</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.8%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,100</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">119</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.8%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.57</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">784</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">109</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">799</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">94</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume carnation before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,515</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">217</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.5%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,552</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">180</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.4%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.21</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">320</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">325</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.2%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume star anise before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,580</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">224</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.4%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.20</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,619</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">185</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.40</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">251</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">254</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">24</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.6%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume ginger before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,157</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">175</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13.1%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.02</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,189</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">143</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.7%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.10</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">708</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">76</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">717</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.5%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume green tea before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1450</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">211</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.7%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.04</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,486</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.5%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">175</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.08</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">393</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">39</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">399</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">92.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.6%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume lemons before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">674</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">109</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13.9%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.02</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">687</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">96</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.003</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,194</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">139</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,223</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">110</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.3%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume citrus fruits before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">574</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">84.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">103</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.2%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">587</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13.3%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>&lt;0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn3">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,299</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">149</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,327</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">121</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.4%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume black caraway before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,503</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">208</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.2%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,537</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">174</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.2%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.65</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">333</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">40</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">338</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.4%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume Indian costus before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,736</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">238</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.56</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,773</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">201</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.2%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.53</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">97</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">99</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.7%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.3%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume cumin before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,502</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.1%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">202</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.9%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,533</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">171</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.0%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.98</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">341</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.4%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">49</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">351</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">39</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.0%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">Did you consume turmeric before COVID infection to boost your immune system</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,554</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">211</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.0%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,586</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89.9%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">179</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.1%</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.46</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">289</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.8%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">40</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">300</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.2%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.8%</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>COVID-19, coronavirus disease 2019.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn3">
                                <label>*</label>
                                <p>P &#x2264; 0.05.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec12">
                <title>Regression model</title>
                <p>The multivariate logistic regression model was performed to account for potential confounders and comorbidities. The data are shown in 
                    <xref ref-type="table" rid="T3">Table 3</xref> for two outcomes: COVID-19 severity and hospitalization status with the use of each natural product. After controlling for covariates (age, gender, BMI, cigarette smoking status, and the number of comorbidities), the findings (
                    <xref ref-type="table" rid="T3">Table 3</xref>) showed that consumption of carnation (P&lt;0.01), onion (P&lt;0.01), lemon (P&lt;0.01), and citrus fruits (P&lt;0.01) were predictors of lower disease severity. In addition, the consumption of carnation (P&lt;0.01), lemon (P&lt;0.001), and citrus fruits (P&lt;0.01), were predictors of reduced hospitalizations due to COVID-19 infection (
                    <xref ref-type="table" rid="T3">Table 3</xref>).</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>Table 3. </label>
                    <caption>
                        <title>Logistic regression analyses for medicinal herbals, natural products, and immune-boosting foods used with COVID-19 severity and hospitalization as the output.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Substance consumed before COVID-19</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">Total number of users</th>
                                <th align="left" colspan="3" rowspan="1" valign="top">Severity</th>
                                <th align="left" colspan="3" rowspan="1" valign="top">Hospitalization</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">P-value</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Odds ratio (OR)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">95% CI of OR</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">P-value</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Odds ratio (OR)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">95% CI of OR</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Green Tea</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">432</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.75</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.51&#x2013;1.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.26</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.52&#x2013;1.19</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Black caraway</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">373</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.48&#x2013;1.04</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.71</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.47&#x2013;1.08</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Indian costus</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">108</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.09</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.55</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.27&#x2013;1.09</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.08</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.24&#x2013;1.08</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cumin</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">390</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.98</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.68&#x2013;1.40</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.56</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.89</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.60&#x2013;1.33</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Turmeric</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">329</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.47</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.58&#x2013;1.28</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.08</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.42&#x2013;1.04</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Anis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">934</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.65&#x2013;1.15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.62&#x2013;1.16</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Chamomile</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">707</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.57&#x2013;1.06</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.54</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.65&#x2013;1.25</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Propolis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">116</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.54</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.83</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.45&#x2013;1.51</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.99</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.54&#x2013;1.85</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Honey</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">957</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.33</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.87</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.65&#x2013;1.16</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.96</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.70&#x2013;1.31</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Carnation</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">354</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.01
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.56</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.37&#x2013;0.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.01
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.55</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.35&#x2013;0.87</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Star Anis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">278</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.06</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.65</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.41&#x2013;1.03</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.43&#x2013;1.13</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Onion</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">971</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.01
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.69</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.52&#x2013;0.92</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.75</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.55&#x2013;1.02</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Garlic</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">893</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.25</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.63&#x2013;1.13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.31</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.62&#x2013;1.16</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Lemon</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1333</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.01
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.68</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.51&#x2013;0.90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.57</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.42&#x2013;0.78</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Citrus fruits</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1448</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.01
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.66</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.50&#x2013;0.89</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.002
                                    <xref ref-type="table-fn" rid="tfn4">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.61</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.44&#x2013;0.84</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Each independent variable was adjusted for confounders, and comorbidities.</p>
                        <p>COVID-19, coronavirus disease 2019.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn4">
                                <label>*</label>
                                <p>P&#x2264;0.05.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec13" sec-type="discussion">
            <title>Discussion</title>
            <p>COVID-19 can show a spectrum of clinical symptoms from mild to severe respiratory distress and death. It is suggested that the nutritional status of people may influence COVID-19 clinical severity.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> In the current study, the effects of using natural products prior to infection with COVID-19 on disease severity and hospitalization were examined. Previous studies have examined the associations between the severity of infection with the intake of immune-boosting foods and medicinal herbs.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> According to the literature, there is no evidence that natural products and medicinal herbs impart protection from or cure COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> However, consumption of natural products before becoming infected with COVID-19 may boost the immune system and lead to favored disease outcomes. The current study found that regular consumption of carnation, lemon, and citrus fruits, before infection was associated with better outcomes for COVID-19. Of note, lemon was kept as a separate category from citrus because some studies have shown differences in their nutritional values.
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup>
            </p>
            <p>This study found that carnation use by the participants reduced COVID-19 hospitalizations and disease severity. Due to its therapeutic uses, carnation is nominated as a candidate for the management of COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> During the COVID-19 pandemic, the consumption of carnation as an additive to food or drink to relieve throat pain has increased.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> A randomized clinical trial of a blend that contains carnation buds demonstrated a boost in energy levels among post-COVID-19 female patients.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> In addition, carnation has antibacterial, antiviral, and antifungal effects, and is used to kill germs in dental creams, toothpaste, mouthwash formulations, and throat sprays.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> The mechanism by which carnation may reduce the severe form of COVID-19 involves interference of SARS-CoV-2 S1-protein binding to the angiotensin-converting enzyme 2 (ACE2) receptor.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup> Moreover, carnation has been shown to increase the availability of oxygen by improving blood supply to both the heart and the brain.
                <sup>
                    <xref ref-type="bibr" rid="ref35">35</xref>
                </sup> Carnation has also been reported to be beneficial for the management of chronic coughs, shortness of breath, and maintaining a normal heart rate.
                <sup>
                    <xref ref-type="bibr" rid="ref36">36</xref>
                </sup>
            </p>
            <p>The current study also showed a significant decrease in the frequency of the severe form of COVID-19 and hospitalization due to the consumption of lemon and citrus. Citrus fruits are known to contain a variety of bioactive constituents, including vitamin C, anthocyanin, and flavanones,
                <sup>
                    <xref ref-type="bibr" rid="ref37">37</xref>
                </sup> which offer a variety of health benefits, such as the normalization of oxidants and inflammation.
                <sup>
                    <xref ref-type="bibr" rid="ref38">38</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref39">39</xref>
                </sup> Furthermore, citrus fruits, such as oranges and grapefruits, are grown in Jordan, making them a readily available natural source of vitamin C.
                <sup>
                    <xref ref-type="bibr" rid="ref40">40</xref>
                </sup> Citrus fruits are commonly used by Jordanians to improve the body&#x2019;s immunity against COVID-19 infection.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Similar to carnation, active ingredients in citrus fruits can interfere with binding of SARS-CoV-2 to the ACE2 receptor.
                <sup>
                    <xref ref-type="bibr" rid="ref41">41</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref42">42</xref>
                </sup> Moreover, naringin of citrus fruits has been shown to suppress the expression of proinflammatory cytokines during the inflammatory response.
                <sup>
                    <xref ref-type="bibr" rid="ref41">41</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref43">43</xref>
                </sup> Furthermore, hesperidin, a biologically active molecule in orange fruit, was shown to inactivate the SARS-CoV-2 RNA polymerase complex.
                <sup>
                    <xref ref-type="bibr" rid="ref44">44</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref45">45</xref>
                </sup> The antioxidant components of citrus fruits can also protect against oxidative stress associated with COVID-19 infection.
                <sup>
                    <xref ref-type="bibr" rid="ref46">46</xref>
                </sup>
            </p>
            <p>Onion has been shown to significantly reduce the frequency of severe illness among participants who consumed it regularly. Onion has antiviral, antifibrotic, antioxidant, and anti-inflammatory bioactive compounds, such as quercetin, apigenin, and selenium.
                <sup>
                    <xref ref-type="bibr" rid="ref39">39</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref47">47</xref>
                </sup> In several studies, onion and its bioactive components reduced inflammation in the lungs and protected against various respiratory illnesses.
                <sup>
                    <xref ref-type="bibr" rid="ref48">48</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref50">50</xref>
                </sup> It is suggested that phytochemicals derived from onions can interfere with the function of the main protease of SARS-CoV-2.
                <sup>
                    <xref ref-type="bibr" rid="ref51">51</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref53">53</xref>
                </sup> In addition, anti-inflammatory diets that incorporate onions were recommended to reduce the severity of COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref54">54</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref55">55</xref>
                </sup>
            </p>
            <p>Although honey and ginger were among the most consumed natural products for the prevention or mitigation of COVID-19 symptoms in Jordan,
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> results showed no impact of ginger and honey on the rate of hospitalization and disease severity. Ginger is suggested as a natural product for the management of COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref56">56</xref>
                </sup> In contrast to the current findings, Aldwihi 
                <italic toggle="yes">et al</italic>., showed that patients who consumed ginger were less likely to be hospitalized.
                <sup>
                    <xref ref-type="bibr" rid="ref57">57</xref>
                </sup> Moreover, a decrease in COVID-19 severity was observed among patients who consumed ginger as treatment.
                <sup>
                    <xref ref-type="bibr" rid="ref58">58</xref>
                </sup> According to clinical trials, honey (propolis), a resinous substance made by bees, may help reduce viral clearance time and improve clinical COVID-19 outcomes by interfering with viral replication and entry.
                <sup>
                    <xref ref-type="bibr" rid="ref59">59</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref61">61</xref>
                </sup> However, the effects of honey were observed in a limited number of studies involving small sample sizes.
                <sup>
                    <xref ref-type="bibr" rid="ref62">62</xref>
                </sup> Thus, more investigations are required to confirm the role of bee products in the management of COVID-19.</p>
            <p>According to the logistic regression analysis, no associations were observed due to consumption of green tea, black caraway, Indian costus, cumin, turmeric, anis, chamomile, star anis, and garlic with COVID-19 hospitalizations and severity. While several studies have revealed the anti-inflammatory and antiviral effects of many of these natural products,
                <sup>
                    <xref ref-type="bibr" rid="ref63">63</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref65">65</xref>
                </sup> their contribution toward reducing COVID-19 severity is highly controversial, and requires preclinical and clinical trial evaluations, and validation using models of the disease.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref66">66</xref>
                </sup> Among the study&#x2019;s limitations is that the total number and quantity of natural products used by the subjects were unknown. In addition, the method of consuming carnation, the most active natural product to protect against severe COVID-19, was not investigated.</p>
            <p>Furthermore, data on the duration of COVID-19 and hospitalization were not collected. Finally, since the study collected retrospective data, the data may be subject to recall bias. As a result, more studies are required to verify the study findings.</p>
        </sec>
        <sec id="sec14" sec-type="conclusions">
            <title>Conclusions</title>
            <p>The study findings showed that the regular consumption of lemon, citrus fruits, and carnation lowers the rates of COVID-19 severity and hospitalization. Studies in other populations are required to confirm these findings.</p>
        </sec>
        <sec id="sec15">
            <title>Data availability</title>
            <sec id="sec16">
                <title>Underlying data</title>
                <p>Figshare: Natural Products Raw Data. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.19758820">https://doi.org/10.6084/m9.figshare.19758820</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref67">67</xref>
                    </sup>
                </p>
                <p>This project contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>Natural products Raw Data.xlsx (survey responses from all participants)</p>
                        </list-item>
                        <list-item>
                            <label>-</label>
                            <p>Questionnaire in English.docx</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
    </body>
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                            <given-names>A</given-names>
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                        <name name-style="western">
                            <surname>Hu</surname>
                            <given-names>X</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Curcumin attenuates pulmonary inflammation in lipopolysaccharide induced acute lung injury in neonatal rat model by activating peroxisome proliferator-activated receptor &#x03b3; (PPAR&#x03b3;) pathway.</article-title>
                    <source>

                        <italic toggle="yes">Medical Science Monitor: International Medical Journal of Experimental and Clinical Research.</italic>
</source>
                    <year>2018</year>;<volume>24</volume>:<fpage>1178</fpage>&#x2013;<lpage>1184</lpage>.
                    <pub-id pub-id-type="pmid">29480285</pub-id>
                    <pub-id pub-id-type="doi">10.12659/MSM.908714</pub-id>
                    <pub-id pub-id-type="pmcid">PMC5839073</pub-id>
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                        </name>

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                            <surname>Sheorey</surname>
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                        </name>

                        <name name-style="western">
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</person-group>:
                    <article-title>Analgesic and anti-inflammatory plants: an updated review.</article-title>
                    <source>

                        <italic toggle="yes">Int. J. Pharm. Sci. Rev. Res.</italic>
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                    <year>2012</year>;<volume>12</volume>:<fpage>114</fpage>&#x2013;<lpage>119</lpage>.</mixed-citation>
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                        </name>

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                            <surname>Ridwansyah</surname>
                            <given-names>H</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Ghozali</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Traditional Herbal Medicine Candidates as Complementary Treatments for COVID-19: A Review of Their Mechanisms, Pros and Cons.</article-title>
                    <source>

                        <italic toggle="yes">Evid. Based Complement. Alternat. Med.</italic>
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                    <year>2020</year>;<volume>2020</volume>:<fpage>2560645</fpage>.</mixed-citation>
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                <label>67</label>
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                        <name name-style="western">
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                    <article-title>Natural Products Raw Data. figshare. [Dataset].</article-title>
                    <year>2022</year>.
                    <pub-id pub-id-type="doi">10.6084/m9.figshare.19758820.v2</pub-id>
                </mixed-citation>
            </ref>
        </ref-list>
    </back>
    <sub-article article-type="reviewer-report" id="report143818">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.135778.r143818</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Vicidomini</surname>
                        <given-names>Caterina</given-names>
                    </name>
                    <xref ref-type="aff" rid="r143818a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r143818a1">
                    <label>1</label>Istituto di Biostrutture e Bioimmagini IBB-CNR, Naples, Italy</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>18</day>
                <month>7</month>
                <year>2022</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Vicidomini C</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport143818" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.121933.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The changes made are satisfactory. I have no further comments to add. The paper is approved.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Environmental chemistry &amp; human health. Computational studies. Synthesis of small molecules</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report143817">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.135778.r143817</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Atrooz</surname>
                        <given-names>Fatin Y.</given-names>
                    </name>
                    <xref ref-type="aff" rid="r143817a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r143817a1">
                    <label>1</label>Department of Pharmacological and Pharmaceutical Sciences, College of Pharmacy, University of Houston, Houston, TX, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>13</day>
                <month>7</month>
                <year>2022</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Atrooz FY</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport143817" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.121933.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Approved.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Behavioral neuroscience, cytogenetics, public health research.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report140506">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.133852.r140506</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Vicidomini</surname>
                        <given-names>Caterina</given-names>
                    </name>
                    <xref ref-type="aff" rid="r140506a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r140506a1">
                    <label>1</label>Istituto di Biostrutture e Bioimmagini IBB-CNR, Naples, Italy</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>28</day>
                <month>6</month>
                <year>2022</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Vicidomini C</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport140506" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.121933.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>In this paper, the authors retrospectively explored the effect of a series of natural products use prior to infection with COVID-19 on disease severity and hospitalization. The authors hypothesized that an increase in the use of some immune-boosting foods and medicinal herbs would be associated with a less severe form of COVID-19 infection. Study measures included the use of selected natural products, COVID-19 severity, and hospitalization status. A multivariate regression model was used for statistical analysis.</p>
            <p> </p>
            <p> In my opinion, this paper has some limitations including those the authors have described in the text. The total number and quantity of natural products used by the subjects were unknown, and also, I didn't find any information on whether the participants consumed these natural products as commercial supplements, or if they prepared them from natural sources at home, for example.</p>
            <p> </p>
            <p> In any case, the work seems interesting and provides ideas for research insights. In my opinion it is therefore worthy of indexing.</p>
            <p> </p>
            <p> I have just a few suggestions: 
                <list list-type="bullet">
                    <list-item>
                        <p>Provide some information on the recruitment method adopted.</p>
                    </list-item>
                    <list-item>
                        <p>Specify, at least for the most active products such as carnation, how it is usually consumed.</p>
                    </list-item>
                    <list-item>
                        <p>Reading the questionnaire, I saw that the authors collected data on potential confounders and comorbidities, but they didn't specify anything on this aspect. Please, add what they considered confounders. If possible, it would be interesting to evaluate whether, for example, the cigarette smoking modified the beneficial effect of natural substances intake.</p>
                    </list-item>
                    <list-item>
                        <p>I know that there are other natural substances traditionally used to boost the immune system, but they were not mentioned or considered in the study. Please add a comment in the text and cite at least the following reference.
                            <sup>
                                <xref ref-type="bibr" rid="rep-ref-140506-1">1</xref>
                            </sup>
                        </p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Environmental chemistry &amp; human health. Computational studies. Synthesis of small molecules</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-140506-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Spices and herbs: Potential antiviral preventives and immunity boosters during COVID-19.</article-title>
                        <source>
                            <italic>Phytother Res</italic>
                        </source>.<year>2021</year>;
                        <elocation-id>10.1002/ptr.7019</elocation-id>
                        <pub-id pub-id-type="pmid">33511704</pub-id>
                        <pub-id pub-id-type="doi">10.1002/ptr.7019</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment8463-140506">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Nimer</surname>
                            <given-names>Refat</given-names>
                        </name>
                        <aff>Jordan University of Science and Technology, Jordan</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>2</day>
                    <month>7</month>
                    <year>2022</year>
                </pub-date>
            </front-stub>
            <body>
                <p>We would like to thank the reviewers for careful and thorough reading of this manuscript and for the thoughtful comments and constructive suggestions, which helped to improve the quality of this manuscript.</p>
                <p> Please find attached a point-by-point response to reviewers&#x2019; concerns. We hope that you find our responses satisfactory and that the manuscript is now acceptable for publication.</p>
                <p> </p>
                <p> 
                    <underline>Reviewer #2 (Comments to the Author):</underline>&#x00a0;</p>
                <p> In my opinion, this paper has some limitations including those the authors have described in the text. The total number and quantity of natural products used by the subjects were unknown,..</p>
                <p> 
                    <bold>Authors' response:</bold> We agree with the reviewer that the rate of consumption of these natural products was unknown. However, this point was mentioned in the limitations (highlighted in red).</p>
                <p> </p>
                <p> And also, I didn&#x2019;t find any information on whether the participants consumed these natural products as commercial supplements, or if they prepared them from natural sources at home, for example.</p>
                <p> 
                    <bold>Authors&#x2019; response:</bold> This study focuses on natural products, not commercial supplements.&#x00a0; However, the point raised by the reviewer is now incorporated in the revised manuscript.</p>
                <p> </p>
                <p> Provide some information on the recruitment method adopted.</p>
                <p> 
                    <bold>Authors' response:</bold> More information was added at &#x201c;Study design and subjects&#x201d; section.</p>
                <p> </p>
                <p> Specify, at least for the most active products such as carnation, how it is usually consumed.</p>
                <p> 
                    <bold>&#x00a0;</bold>
                    <bold>Authors&#x2019; response:</bold> Your suggestion is now incorporated in the updated version of the manuscript.</p>
                <p> </p>
                <p> Reading the questionnaire, I saw that the authors collected data on potential confounders and comorbidities, but they didn't specify anything on this aspect. Please, add what they considered confounders. If possible, it would be interesting to evaluate whether, for example, the cigarette smoking modified the beneficial effect of natural substances intake.</p>
                <p> 
                    <bold>Authors&#x2019; response:</bold> COVID-19 was reported to be more severe in people having high BMI or comorbidities. However, the aim of this study was to explore the effect of using natural products on the severity of the disease, regardless of the confounding factors. Therefore, multivariate regression analysis was applied to control for possible confounding factors such as age, gender, cigarette smoking, and the number of comorbidities (Table 3). The analysis without adjusted confounding factors is shown in Table 2.</p>
                <p> The point raised by the reviewer is now discussed in the revised manuscript.&#x00a0;</p>
                <p> </p>
                <p> I know that there are other natural substances traditionally used to boost the immune system, but they were not mentioned or considered in the study. Please add a comment in the text and cite at least the following reference. PMID: 33511704</p>
                <p> 
                    <bold>Authors&#x2019; response: </bold>We agree with the reviewer's comment. However, this study covered the broadest range of natural products used by the Jordanian population.</p>
                <p> The point raised by the reviewer is now incorporated in the revised manuscript the last sentence in the introduction) and the proposed reference was added (ref no. 14).</p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report140507">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.133852.r140507</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Atrooz</surname>
                        <given-names>Fatin Y.</given-names>
                    </name>
                    <xref ref-type="aff" rid="r140507a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r140507a1">
                    <label>1</label>Department of Pharmacological and Pharmaceutical Sciences, College of Pharmacy, University of Houston, Houston, TX, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>22</day>
                <month>6</month>
                <year>2022</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2022 Atrooz FY</copyright-statement>
                <copyright-year>2022</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
                <license>
                    <license-p>The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport140507" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.121933.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>
                <bold>Summary</bold>: The study explored the association between using specific natural products prior to COVID-19 infection and the severity of the disease and hospitalization status in a sample of Jordanian adults.</p>
            <p> </p>
            <p> 
                <bold>Title</bold>: This is a retrospective study, the study design included a survey about prior COVID-19 infection and natural products consumption prior to infection.</p>
            <p> </p>
            <p> 
                <bold>Methods</bold>:</p>
            <p> - Recruitment method is not clear, how the investigators reached out to the potential participants is not stated. The study suggests that only people who were previously infected with COVID-19 were included in the study. This assumption should be discussed in the inclusion criteria.</p>
            <p> - Calculation of the study sample assumed that the total population is the number of COVID-19 infected people as reported by the end of July 2021. Does this report include only adults or total confirmed cases? As the survey targeted only adults, the authors should identify precisely the study population as a reference for sample size calculation.</p>
            <p> </p>
            <p> 
                <bold>Results</bold>:&#x00a0;</p>
            <p> - Why is lemon considered a separate category from citrus? I suggest including all citrus fruit, including lemon as one category.</p>
            <p> - In table 1, the results were expressed in a different format, I suggest having all the results expressed as N (%). For this purpose, age can be categorized into 2-3 categories, and same for BMI.</p>
            <p> - In the multivariate logistic regression, the authors mentioned that after controlling for covariate, the findings...</p>
            <p> What are the covariates? The authors should list the covariates here, and if that includes controlling for age and gender.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Behavioral neuroscience, cytogenetics, public health research.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment8464-140507">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Nimer</surname>
                            <given-names>Refat</given-names>
                        </name>
                        <aff>Jordan University of Science and Technology, Jordan</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>2</day>
                    <month>7</month>
                    <year>2022</year>
                </pub-date>
            </front-stub>
            <body>
                <p>We would like to thank the reviewers for careful and thorough reading of this manuscript and for the thoughtful comments and constructive suggestions, which helped to improve the quality of this manuscript.</p>
                <p> Please find attached a point-by-point response to reviewers&#x2019; concerns. We hope that you find our responses satisfactory and that the manuscript is now acceptable for publication.</p>
                <p> </p>
                <p> 
                    <underline>Reviewer #1 (Comments to the Author):</underline>&#x00a0;</p>
                <p> - Recruitment method is not clear, how the investigators reached out to the potential participants is not stated. The study suggests that only people who were previously infected with COVID-19 were included in the study. This assumption should be discussed in the inclusion criteria.</p>
                <p> 
                    <bold>Authors&#x2019; response:</bold> The recruitment method has now been illustrated in the revised manuscript. In the cover page for the questionnaire, we outlined the criteria for participation in the study, which includes infection with COVID-19 and recovery from illness. The research assistance emphasized that participants' infection should have been confirmed by polymerase chain reaction (PCR). Participants were approached in public places such as bus stations, parks, religious places, universities and restaurants.</p>
                <p> </p>
                <p> - Calculation of the study sample assumed that the total population is the number of COVID-19 infected people as reported by the end of July 2021. Does this report include only adults or total confirmed cases? As the survey targeted only adults, the authors should identify precisely the study population as a reference for sample size calculation.</p>
                <p> 
                    <bold>Authors' response:</bold> The sample size for our study was calculated using Raosoft Online Sample Size Calculator (Raosoft Inc., Seattle, WA, USA). 770,712 is the total confirmed cases reported by the end of July 2021, and the recommended sample size was 1067. However, this calculation is to check whether the sample size in our study is sufficient and representative. The number of cases under 18 years of age during the time of sample collection (before the emergence of the Omicron variant) was expected to be small compared to the adult cases (no data available). Therefore, if patients under 18 years are subtracted from the total cases, this would lead to a negligible change in the sample size. Nonetheless, the study sample size was larger than required (n= 2,148) even if child cases are considered. This point is now clarified in the Method section.</p>
                <p> </p>
                <p> - Why is lemon considered a separate category from citrus? I suggest including all citrus fruit, including lemon as one category.</p>
                <p> 
                    <bold>Authors&#x2019; response:&#x00a0; </bold>Thank you for your comment. We prefer to keep lemon as a separate category from citrus because some studies showed variations in their nutritional values. This was clarified in the revised manuscript.</p>
                <p> </p>
                <p> - In table 1, the results were expressed in a different format, I suggest having all the results expressed as N (%). For this purpose, age can be categorized into 2-3 categories, and same for BMI.</p>
                <p> 
                    <bold>Authors' response: </bold>Done as suggested.
                    <bold> </bold>
                </p>
                <p> </p>
                <p> - In the multivariate logistic regression, the authors mentioned that after controlling for covariate, the findings...</p>
                <p> What are the covariates? The authors should list the covariates here, and if that includes controlling for age and gender.</p>
                <p> 
                    <bold>Authors' response:</bold> The point raised by the reviewer is now incorporated in the revised manuscript.</p>
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