Objective

farmaec

FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology

ФАРМАКОЭКОНОМИКА. Современная фармакоэкономика и фармакоэпидемиология

2070-49092070-4933

IRBIS LLC

10.17749/2070-4909/farmakoekonomika.2022.135

farmaec-732

Research Article

ORIGINAL ARTICLES

ОРИГИНАЛЬНЫЕ ПУБЛИКАЦИИ

Dietary factors influencing the COVID-19 epidemic process

Диетические факторы, влияющие на эпидемический процесс COVID-19

Пономаренко

С. В.

Ponomarenko

S. V.

Пономаренко София Васильевна – к.б.н., менеджер проектов компании

Сименсштрассе, д. 42, Бёнен 59199

Sophia V. Ponomarenko – Dr. Rer. Nat., Projectmanager

42 Siemensstraße, Bönen 59199

sp@sophigen.com

SophiGen inGrГерманияSophiGen inGrGermany

2022

18012023

154463471

2023

Пономаренко С.В.

Ponomarenko S.V.

This work is licensed under a Creative Commons Attribution 4.0 License.

https://www.pharmacoeconomics.ru/jour/article/view/732

Objective

Objective: to analyze the role of diet in the epidemiological parameters of the SARS-CoV-2 Coronavirus and identify factors that correlate withthe reduction in the severity of the consequences of COVID-19 disease, namely the rate of prevalence (RPr) and infection fatality rate (IFR) in different regions.

Material and methods

Material and methods. The information and data required for this study were found in scientific publications and the media available on the Internet, as well as obtained from statistical databases using specific keywords, both for a single tag and in various combinations of them. Statistical samples were managed from sources and facts available on the Internet. Pearson correlation coefficient (r) was used to understand a statistical relationship between two variables.

Results

Results. The relationship between nutritional factors and the impact of the 15-month COVID-19 pandemic in different regions was investigated using various available statistics for five continents and 47 countries. A clear relationship was found between the outcomes of the SARSCoV-2 epidemic (RPr and IFR) and the amount of consumed essential nutrients, with correlations in the negative range r=–0.98 and r=–0.66 for plant proteins and with correlation coefficients r=0.92 for animal proteins. Also, excessive sugar consumption increased the severity of COVID-19 with correlation coefficients in the range of r=0.99–0.72 in the representative samples.

Conclusion

Conclusion. Statistical analysis presented that the number of diagnosed patients with SARS-CoV-2 (RPr) and deaths from COVID-19 (IFR) was significantly lower in regions where more plant foods were consumed than animal products. A detailed study of the relationship between the Coronavirus and the host as well as the metabolism of protein and sugar may reveal the diet factors responsible for resistance to the pathogen. Edible plants can contain components responsible for suppressing the replication cycle of the SARS-CoV-2 virus. Biochemical investigation of these components would help in the development of etiological oral administrated anti-COVID-9 medicine.

Цель

Цель: проанализировать роль рациона питания в эпидемиологических параметрах коронавируса SARS-CoV-2 и выявить факторы, коррелирующие со снижением тяжести последствий заболевания COVID-19, а именно частотой заболеваемости (англ. rate of prevalence, RPr) и смертности (англ. infection fatality rate, IFR) в разных регионах.

Материал и методы

Материал и методы. Информация и данные, необходимые для этой работы, были найдены в научных публикациях и средствах массовой информации, доступных в Интернете, а также получены из баз статистических данных с использованием определенных ключевых слов для одного тега или в различных их комбинациях. Статистические выборки были сформированы из источников и фактов, доступных в Интернете. Корреляция для двух переменных определялась как коэффициент Пирсона.

Результаты

Результаты. Взаимосвязь между факторами питания и влиянием 15-месячной пандемии COVID-19 в разных регионах была исследована с использованием различных доступных статистических данных по пяти континентам и 47 странам. Обнаружена четкая связь между исходами эпидемии SARS-CoV-2 (RPr и IFR) и количеством потребленных основных нутриентов с корреляциями в отрицательном диапазоне r=–0,98 и r=–0,66 для растительных белков и коэффициентом корреляции r=0,92 для белков животного происхождения. Также чрезмерное потребление сахара увеличивало тяжесть течения COVID-19 с коэффициентами корреляции в диапазоне r=0,99–0,72 в репрезентативных выборках.

Заключение

Заключение. Статистический анализ показал, что количество диагностированных пациентов с SARS-CoV-2 (RPr) и смертей от COVID-19 (IFR) было значительно ниже в регионах, где потреблялось больше растительной пищи, чем продуктов животного происхождения. Детальное изучение взаимосвязи между коронавирусом и хозяином, а также метаболизма белков и сахаров поможет выявить факторы питания, ответственные за устойчивость к патогену. Съедобные растения могут содержать компоненты, ответственные за подавление цикла репликации вируса SARS-CoV-2. Биохимические исследования этих компонентов помогут в разработке этиологических пероральных препаратов против COVID-19.

Коронавирус SARS-CoV-2пандемия COVID-19эпидемияпатогенездиетафакторы риска

Сoronavirus SARS-CoV-2COVID-19 pandemicepidemicpathogenesisdietrisk factors.

References1

WHO Director-General's opening remarks at the media briefing on COVID-19 – 11 March 2020. Available at: https://www.who.int/directorgeneral/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-covid-19---11-march-2020 (accessed 20.07.2022).

Hu B., Guo H., Zhou P., et al. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021; 19 (3): 141–54. https://doi.org/10.1038/s41579-020-00459-7.

To K.K., Sridhar S., Chiu K.H., et al. Lessons learned 1 year after SARS-CoV-2 emergence leading to COVID-19 pandemic. Emerg Microbes Infect. 2021; 10 (1): 507–35. https://doi.org/10.1080/22221751.2021.1898291.

V’kovski P., Kratzel A., Steiner S., et al. Coronavirus biology and replication: implications for SARS-CoV-2. Nat Rev Microbiol. 2021; 19 (3): 155–70. https://doi.org/10.1038/s41579-020-00468-6.

Coronavirus disease (COVID-19) pandemic. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (accessed 20.07.2022).

Worldometer. Coronavirus Updates. Available at: https://www.worldometers.info (accessed 20.07.2022).

Centers for Disease Control Prevention. COVID-19. Understanding risk. Available at: https://www.cdc.gov/coronavirus/2019-ncov/coviddata/investigations-discovery/assessing-risk-factors.html (accessed 20.08.2022).

Geng M.J., Wang L.P., Ren X., et al. Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data. Infect Dis Poverty. 2021; 10 (1): 48. https://doi.org/10.1186/s40249-021-00820-9.

Booth A., Reed A.B., Ponzo S., et al. Population risk factors for severe disease and mortality in COVID19: a global systematic review and metaanalysis. PLoS One. 2021; 16 (3): e0247461. https://doi.org/10.1371/journal.pone.0247461.

Jin J., Agarwala N., Kundu P., et al. Individual and community-level risk for COVID-19 mortality in the United States. Nat Med. 2021; 27 (2): 264–9. https://doi.org/10.1038/s41591-020-01191-8.

Mathur R., Rentsch C.T., Morton C.E., et al. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet. 2021; 397 (10286): 1711–24. https://doi.org/10.1016/S0140-6736(21)00634-6.

Roy S., Ghosh P. Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking. PLoS One. 2020; 15 (10): e0241165. https://doi.org/10.1371/journal.pone.0241165.

Tan A.X., Hinman J.A., Abdel Magid H.S., et al. Association between income inequality and county-level COVID-19 cases and deaths in the US. JAMA Netw Open. 2021; 4 (5): e218799. https://doi.org/10.1001/jamanetworkopen.2021.8799.

Van Damme W., Dahake R., Delamou A., et al. The COVID-19 pandemic: diverse contexts; different epidemics-how and why? BMJ Glob Health. 2020; 5 (7): e003098. https://doi.org/10.1136/bmjgh-2020-003098.

Wamai R.G., Hirsch J.L., Van Damme W., et al. What could explain the lower COVID-19 burden in Africa despite considerable circulation of the SARS-CoV-2 virus? Int J Environ Res Public Health. 2021; 18 (16): 8638. https://doi.org/10.3390/ijerph18168638.

Williamson E.J., Walker A.J., Bhaskaran K., et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020; 584 (7821): 430–6. https://doi.org/10.1038/s41586-020-2521-4.

Zhang W., Zhang C., Bi Y., et al. Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model. Results Phys. 2021; 22: 103881. https://doi.org/10.1016/j.rinp.2021.103881.

Abdelrahman Z., Li M., Wang X. Comparative Review of SARS‑CoV-2, SARS-CoV, MERS-CoV, and Influenza A respiratory viruses. Front Immunol. 2020; 11: 552909. https://doi.org/10.3389/fimmu.2020.552909.

Hoffmann M., Kleine-Weber H., Schroeder S., et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020; 181 (2): 271–80.e8. https://doi.org/10.1016/j.cell.2020.02.052.

Wu S.C., Arthur C.M., Wang J., et al. The SARS-CoV-2 receptorbinding domain preferentially recognizes blood group A. Blood Adv. 2021; 5 (5): 1305–9. https://doi.org/10.1182/bloodadvances.2020003259.

Mokhtari T., Hassani F., Ghaffari N., et al. COVID-19 and multiorgan failure: a narrative review on potential mechanisms. J Mol Histol. 2020; 51 (6): 613–28. https://doi.org/10.1007/s10735-020-09915-3.

Kordzadeh-Kermani E., Khalili H., Karimzadeh I. Pathogenesis, clinical manifestations and complications of coronavirus disease 2019 (COVID-19). Future Microbiol. 2020; 15: 1287–305. https://doi.org/10.2217/fmb-2020-0110.

Al-Aly Z., Xie Y., Bowe B. High-dimensional characterization of postacute sequelae of COVID-19. Nature. 2021; 594 (7862): 259–64. https://doi.org/10.1038/s41586-021-03553-9.

Sudre C.H., Murray B., Varsavsky T., et al. Attributes and predictors of long COVID. Nat Med. 2021; 27 (4): 626–31. https://doi.org/10.1038/s41591-021-01292-y.

Karlinsky A., Kobak D. Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. Elife. 2021; 10: e69336. https://doi.org/10.7554/eLife.69336.

Fan J., Han F., Liu H. Challenges of Big Data analysis. Natl Sci Rev. 2014; 1 (2): 293–314. https://doi.org/10.1093/nsr/nwt032.

Kontis V., Bennett J.E., Rashid T., et al. Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries. Nat Med. 2020; 26 (12): 1919–28. https://doi.org/10.1038/s41591-020-1112-0.

Ponomarenko S. Economic and social factors affecting the epidemiological process of the SARS-CoV-2 coronavirus. Available at: https://doi.org/10.21055/preprints-3111965 (accessed 20.08.2022).

Hashim M.J., Alsuwaidi A.R., Khan G. Population risk factors for COVID-19 mortality in 93 countries. J Epidemiol Glob Health. 2020; 10 (3): 204–8. https://doi.org/10.2991/jegh.k.200721.001.

World Bank Open Data. Available at: https://data.worldbank.org/ (accessed 20.07.2022).

Our World in Data. Research and data to make progress against the world’s largest problems. Available at: https://ourworldindata.org (accessed 20.07.2022).

World per Capita Consumption of Sugar, 2012 to 2018. Available at: https://www.indiansugar.com/PDFS/World_per_Capita_Consumption_of_Sugar.pdf (accessed 20.08.2022).

WHO sugar recommendations. Available at: https://www.ages.at/en/human/nutrition-food/nutrition-recommendations/who-sugarrecommendations (accessed 20.08.2022).

Ali A.M., Kunugi H. Approaches to nutritional screening in patients with coronavirus disease 2019 (COVID-19). Int J Environ Res Public Health. 2021; 18 (5): 2772. https://doi.org/10.3390/ijerph18052772.

Allard L., Ouedraogo E., Molleville J., et al. Malnutrition: percentage and association with prognosis in patients hospitalized for coronavirus disease 2019. Nutrients. 2020; 12 (12): 3679. https://doi.org/10.3390/nu12123679.

Akhtar S., Das J.K., Ismail T., et al. Nutritional perspectives for the prevention and mitigation of COVID-19. Nutr Rev. 2021; 79 (3): 289– 300. https://doi.org/10.1093/nutrit/nuaa063.

Mentella M.C., Scaldaferri F., Gasbarrini A., Miggiano G.A.D. The role of nutrition in the COVID-19 pandemic. Nutrients. 2021; 13 (4): 1093. https://doi.org/10.3390/nu13041093.

Morais A., Aquino J.S., da Silva-Maia J.K., et al. Nutritional status, diet and viral respiratory infections: perspectives for severe acute respiratory syndrome coronavirus 2. Br J Nutr. 2021; 125 (8): 851–62. https://doi.org/10.1017/S0007114520003311.

Sahin E., Orhan C., Uckun F.M., Sahin K. Clinical impact potential of supplemental nutrients as adjuncts of therapy in high-risk COVID-19 for obese patients. Front Nutr. 2020; 7: 580504. https://doi.org/10.3389/fnut.2020.580504.

Clemente-Suárez V.J., Ramos-Campo D.J., Mielgo-Ayuso J., et al. Nutrition in the actual COVID-19 pandemic. A narrative review. Nutrients. 2021; 13 (6): 1924. https://doi.org/10.3390/nu13061924.

James P.T., Ali Z., Armitage A.E., et al. The role of nutrition in COVID-19 susceptibility and severity of disease: a systematic review. J Nutr. 2021; 151 (7): 1854–78. https://doi.org/10.1093/jn/nxab059.

Mortaz E., Bezemer G., Alipoor S.D., et al. Nutritional impact and its potential consequences on COVID-19 severity. Front Nutr. 2021; 8: 698617. https://doi.org/10.3389/fnut.2021.698617.

Protein and amino acid requirements in human nutrition. World Health Organ Tech Rep Ser. 2007; 935: 1–265.

Rothenberg E. Coronavirus disease 19 from the perspective of ageing with focus on nutritional status and nutrition management – a narrative review. Nutrients. 2021; 13 (4): 1294. https://doi.org/10.3390/nu13041294.

Food and Agriculture Organization of the United Nations. Eating healthy before, during and after COVID-19. Available at: http://www.fao.org/fao-stories/article/en/c/1392499/ (accessed 20.07.2022).

Greene M.W., Roberts A.P., Frugé A.D. Negative association between Mediterranean diet adherence and COVID-19 cases and related deaths in Spain and 23 OECD countries: an ecological study. Front Nutr. 2021; 8: 591964. https://doi.org/10.3389/fnut.2021.591964.

Kim H., Rebholz C.M., Hegde S., et al. Plant-based diets, pescatarian diets and COVID-19 severity: a population-based case-control study in six countries. BMJ Nutr Prev Health. 2021; June 7. https://doi.org/10.1136/bmjnph-2021-000272.

Food and Agriculture Organization of the United Nations. Food Balances (2010-). Available at: https://FAO.org/faostat/en/#data/FBS (accessed 20.07.2022).

Barberis E., Amede E., Tavecchia M., et al. Understanding protection from SARS-CoV-2 using metabolomics. Sci Rep. 2021; 11 (1): 13796. https://doi.org/10.1038/s41598-021-93260-2.

Schüler R., Osterhof M.A., Frahnow T., et al. High-saturated-fat diet increases circulating angiotensin-converting enzyme, which is enhanced by the rs4343 polymorphism defining persons at risk of nutrient-dependent increases of blood pressure. J Am Heart Assoc. 2017; 6 (1): e004465. https://doi.org/10.1161/JAHA.116.004465.

Bousquet J., Anto J.M., Iaccarino G., et al. Is diet partly responsible for differences in COVID-19 death rates between and within countries? Clin Transl Allergy. 2020; 10: 16. https://doi.org/10.1186/s13601-020-00323-0.

Paoli A., Gorini S., Caprio M. The dark side of the spoon – glucose, ketones and COVID-19: a possible role for ketogenic diet? J Transl Med. 2020; 18 (1): 441. https://doi.org/10.1186/s12967-020-02600-9.

Csapó J., Csilla A. Methods and procedures for reducing soy trypsin inhibitor activity by means of heat treatment combined with chemical methods. Acta Universitatis Sapientiae, Alimentaria. 2018; 11 (1): 58– 80. https://doi.org/10.2478/ausal-2018-0004.

Losso J.N. The biochemical and functional food properties of the bowman-birk inhibitor. Crit Rev Food Sci Nutr. 2008; 48 (1): 94–118. https://doi.org/10.1080/10408390601177589.

Srikanth S., Chen Z. Plant protease inhibitors in therapeutics-focus on cancer therapy. Front Pharmacol. 2016; 7; 470. https://doi.org/10.3389/fphar.2016.00470.

Billinger E., Zuo S., Johansson G. Characterization of serine protease inhibitor from Solanum tuberosum conjugated to soluble dextran and particle carriers. ACS Omega. 2019; 4 (19): 18456–64. https://doi.org/10.1021/acsomega.9b02815.

Komarnytsky S., Cook A., Raskin I. Potato protease inhibitors inhibit food intake and increase circulating cholecystokinin levels by a trypsindependent mechanism. Int J Obes (Lond). 2011; 35 (2): 236–43. https://doi.org/10.1038/ijo.2010.192.

Ali S.G., Ansari M.A., Alzohairy M.A., et al. Natural products and nutrients against different viral diseases: prospects in prevention and treatment of SARS-CoV-2. Medicina (Kaunas). 2021; 57 (2): 169. https://doi.org/10.3390/medicina57020169.

Fuzimoto A.D., Isidoro C. The antiviral and coronavirus-host protein pathways inhibiting properties of herbs and natural compounds – additional weapons in the fight against the COVID-19 pandemic? J Tradit Complement Med. 2020; 10 (4): 405–19. https://doi.org/10.1016/j.jtcme.2020.05.003.

Li Z., Li X., Huang Y.Y., et al. Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs. Proc Natl Acad Sci. 2020; 3; 117 (44): 27381–7. https://doi.org/10.1073/pnas.2010470117.

Chitsike L., Duerksen-Hughes P. Keep out! SARS-CoV-2 entry inhibitors: their role and utility as COVID-19 therapeutics. Virol J. 2021; 18 (1): 154. https://doi.org/10.1186/s12985-021-01624-x.

Guedes I.A., Costa L.S.C., dos Santos K.B., et al. Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants. Sci Rep. 2021; 11 (1): 5543. https://doi.org/10.1038/s41598-021-84700-0.

Riva L., Yuan S., Yin X., et al. Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing. Nature. 2020; 586 (7827): 113–9. https://doi.org/10.1038/s41586-020-2577-1.

The authors declare that there are no conflicts of interest present.