Some natural hypomethylating agents in food, water and environment are against distribution and risks of COVID-۱۹ pandemic: Results of a big-data research

Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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JR_AJP-12-3_009

تاریخ نمایه سازی: 28 فروردین 1401

Abstract:

Objective: This study analyzes the effects of lifestyle, nutrition, and diets on the status and risks of apparent (symptomatic) COVID-۱۹ infection in Iranian families.Materials and Methods: A relatively extensive questionnaire survey was conducted on more than ۲۰,۰۰۰ Iranian families (residing in more than ۱۰۰۰ different urban and rural areas in the Islamic Republic of Iran) to collect the big data of COVID-۱۹ and develop a lifestyle dataset. The collected big data included the records of lifestyle effects (e.g. nutrition, water consumption resources, physical exercise, smoking, age, gender, health and disease factors, etc.) on the status of COVID-۱۹ infection in families (i.e. residents of homes). Therefore, an online self-reported questionnaire was used in this retrospective observational study to analyze the effects of lifestyle factors on the COVID-۱۹ risks. The data collection process spanned from May ۱۰, ۲۰۲۰ to March ۱۹, ۲۰۲۱ by selecting ۱۳۲ samples from more than ۴۰ different social network communities.Results: The research results revealed that food and water sources, which contain some natural hypomethylating agents, mitigated the risks of apparent (symptomatic) COVID-۱۹ infection. Furthermore, the computations on billions of permutations of nutrition conditions and dietary regime items, based on the data collected from people’s diets and infection status, showed that there were many dietary conditions alleviating the risks of apparent (symptomatic) COVID-۱۹ infection by ۹۰%. However, some other diets tripled the infection risk.Conclusion: Some natural hypomethylating agents in food, water, and environmental resources are against the spread and risks of COVID-۱۹. 

Authors

Mohammad Reza Besharati

Department of Computer Engineering, Sharif University of Technology, Tehran, Iran. Quran Miracle Research Institute, Shahid Beheshti University, Tehran, Iran

Mohammad Izadi

Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

Alireza Talebpour

Department of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran. Quran Miracle Research Institute, Shahid Beheshti University, Tehran, Iran