The impact of nutrition on COVID-19 susceptibility and long-term consequences

Butler, Michael J.; Barrientos, Ruth M.

doi:10.1016/j.bbi.2020.04.040

Cited by 479 publications

(511 citation statements)

References 10 publications

(15 reference statements)

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“…In ammation is at the heart of the complications caused by this virus. In addition, it is good to remember that peripheral in ammation caused by COVID-19 can have long-term consequences that can lead to neurodegenerative dementia and disease through neuroin ammatory mechanisms that can be potentiated and aggravated by an unhealthy diet, especially in the most vulnerable people [60]. In addition to investing in healthy foods, we have to restrict in ammatory foods.…”

Section: Discussionmentioning

confidence: 99%

“…The consumption of a western type diet activates the innate immune system and impairs adaptive immunity, leading to chronic in ammation, reducing the host's defences against COVID-19 [60]. It is also important to remember that the high rate of consumption of diets rich in saturated fats such as red meat, sugars and re ned carbohydrates worldwide, contributes to the prevalence of obesity and type 2 diabetes and can put these populations at increased risk for developing severe COVID-19 and lead to higher mortality [60]. At the moment when we are going through this pandemic, it is essential to consider the impact of lifestyle habits, such as the consumption of unhealthy diets, on susceptibility to COVID-19 as well as on its recovery.…”

Section: Discussionmentioning

confidence: 99%

“…At the moment when we are going through this pandemic, it is essential to consider the impact of lifestyle habits, such as the consumption of unhealthy diets, on susceptibility to COVID-19 as well as on its recovery. Therefore, individuals should refrain from eating foods rich in saturated fats and sugar and instead consume large amounts of bre, whole grains, unsaturated fats and antioxidants to increase immune function [60,61].…”

Section: Discussionmentioning

confidence: 99%

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COVID-19: Does lifestyle intervention improve the course of the disease? A case series and literature review

Rios

Chen

2020

Preprint

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The new disease COVID-19 is associated with high mortality, as the virus attacks our defences and our immune system. Despite the amount of research by scientists from around the world, currently, no specific antiviral treatment is recommended, and no vaccine is available. However, there is already robust research showing how to improve our immune systems through a balanced diet and lifestyle intervention in order to fight against the virus. We report a series of 10 cases of patients with COVID-19 from a poor community in Brazil who were monitored by telephone due to the lack of resources in the public health system. They received conventional medical drugs and were additionally instructed to change their eating patterns as well their lifestyles. These patients showed favourable results in their illnesses. Lifestyle interventions with balanced nutrition are not antagonistic to traditional medicine. They interact harmoniously to achieve a positive result faster. Although today we know little about the treatment of COVID-19 with drugs, we know a lot about how to improve our immune systems to help our bodies in this battle against COVID-19. Until new treatments and effective vaccines are discovered, perhaps we can revisit the teachings of the father of medicine, who 2500 years ago spoke of the importance of lifestyle interventions such as changes in nutrition, sleep and exercise for the prevention and treatment of diseases.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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COVID-19: Does lifestyle intervention improve the course of the disease? A case series and literature review

Rios

Chen

2020

Preprint

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“…The connection between socio-cultures, climate change, humidity and seasonal variability assume that the risk of transmission of SARS-CoV-2 does appear to be the greatest [43,44]. Additionally, variation in food availability and food intake, age, and sex are important factors which could also play a role in the SARS-CoV-2 noti cation variability [45]. Ethnicity is another key player for increased risk of acquiring SARS-CoV-2 infection, for instance, studies have revealed that the Black, Asian and Minority Ethnic individuals are more prone and worsen clinical complications from COVID-19 compared to White individuals [46][47][48].…”

Section: Identi Cation Of the Key Medical And Social Elementsmentioning

confidence: 99%

Spatial Distribution and Trend Analysis of Current Status of COVID-19 in Nepal and Global Future Preventive Perspectives

Pant

Bahadur

Bishwakarma

et al. 2020

Preprint

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Background: Coronavirus disease (COVID-19) is a recently discovered severe and contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has received worldwide attention. The risk of COVID-19 is serious for the infected persons of chronic diseases as well as vulnerable populations including elder group. Still, the present scenario of scarcity of effective treatment options and limited recovery rate of ongoing treatment are prevailed in Nepal. This study aims to analyze the spatial distribution and trends of COVID-19 with the help of geographic information system (GIS) software and outlook future preventive perspectives.Methods: In this research work, we used GIS tool ArcGIS 10.4.1 to map the distribution patterns of population of COVID-19 cases. Federal, provincial and district level daily cases data of COVID-19 confirmed, cured and death from 23rd January to 13th July 2020 were obtained from the Ministry of Health and Population (MoHP), Government of Nepal. In addition, we reviewed several peer-reviewed research papers to summarize the global scenarios and preventive perspectives on COVID-19.Results: In context to Nepal SARS-CoV-2 has spread throughout the country infecting 16,945 persons in all 77 districts, as of 13th July, 2020. Confirmed, cured and death cases experienced an upward trend up to 1st July, 2020 followed by downward trend as of 13th July, 2020. Over 70% of total confirmed cases of reported COVID-19 patients were from the lowland-plain area. Spatial clustering suggested that provinces 2 and 5 were at potentially increased risk of COVID-19, and Province 1 and Bagmati province could be grouped as future "hot spots". In addition, we proposed four strategies namely, identification of the key medical and social elements, discovery and development of treatment options for a future pandemic, investing in ethno-medicine research and epidemic preparedness of health care system to decrease the efficacy of calamities of future pandemics.Conclusion: Our study demonstrates one of the best ways to protect; control and sluggish transmission of SARS-CoV-2 could be achieved by monitoring active ties using GIS spatial analysis. And, the severity of future pandemic could be minimized by integrative action on the abovementioned four different preventive master plans.

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“…Therefore, we can guess that the above factors may be closely related to COVID-19. It is gratifying that recently some prospective studies [17][18][19] provide an association between factors (age, basic health situation, and virus transmission speed) and mortality of COVID-19. However, to our best knowledge, some relationship between environmental factors, including meteorological factors and the death risk of COVID-19 patients remain unknown, might need further investigation.…”

Section: Introductionmentioning

confidence: 99%

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: A time-series analysis

Zhu

Wang

et al. 2020

Preprint

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BackgroundThe COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19.MethodsThe Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China.ResultsDuring the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.5 % (95 % CI [3.8 %, 20.4 %]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust.ConclusionsThe relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.

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The impact of nutrition on COVID-19 susceptibility and long-term consequences

Cited by 479 publications

References 10 publications

COVID-19: Does lifestyle intervention improve the course of the disease? A case series and literature review

COVID-19: Does lifestyle intervention improve the course of the disease? A case series and literature review

Spatial Distribution and Trend Analysis of Current Status of COVID-19 in Nepal and Global Future Preventive Perspectives

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: A time-series analysis

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