There was significant linear relationship (R2 = 0.668,p <0.000) between total tests and total deaths reported for each country (Figure 3) suggesting that the more the Covid-19 tests are conducted in a country the higher the likelihood of more reported Covid-19 deaths. Since most developing countries were struggling to carry out massive screening tests for Covid-19 in the early stages of the pandemic these countries may have higher numbers of Covid-19 cases than have been reported to date. These data, therefore, suggest that if testing is intensified by those countries currently presumed to be under-reporting, the number of deaths reported as due to Covid-19 will likely rise.
There are disproportionate mortality rates from Covid-19 across the countries. Higher Covid-19 mortality rates are reported in countries with high life expectancy (>70 years) than those countries with lower (<70 years) life expectancy16. To test this we collected data on life expectancy (years) for all the countries (n = 207) and plotted against C19DM (Figure 1). We found a significant logarithmic relationship (R2 = 0.4662, p < 0.05) between life expectancy and C19DM. The highest death rates occur for life expectancy between 75 and 85 years. We further divided countries into two groups; those with life expectancy below 75 years and those above 75 years. We found that the average death per million of population of countries with life expectancy below 75 years was 6.5 (n = 99), while for countries with life expectancy above 75 years (n = 111) C19DM was 90.4. Similarly, average total deaths in countries with life expectancy below 75 years was 102.5 (n = 99), while in countries above 75 years average total deaths was 2606.8 (n = 111) (Table 1). Unsurprisingly a large proportion of these countries are in Europe where health services are advanced. Therefore, these data suggest that the proportionally higher number of persons above 75 years may partly explain why those countries are reporting high C19DM. Due to immunosenescence, elderly persons tend to have poor immunity against infections17. In old age chronic diseases such as cancer, diabetes, hypertension, cardiovascular disease, and lung diseases are common decreasing resistance to Covid-19 infection and subsequently resulting in higher C19DM. This may partly explain why most African countries, whose populations are comparatively younger, have lower mortality rates than European countries.
There are a number of factors, both nutritional and environmental, that may lead to increased susceptibility to infection for persons over 70 years old. Good nutrition primes the immune system. Generally, diets high in fruits and vegetables are believed to be healthier due to significantly higher content of micronutrients (vitamin and minerals) and phytochemicals that are important for healthy immune systems. As noted above, fruits, vegetables, and spices are significant sources of phytochemicals some of which have antiviral properties11,12,13,14. We tested whether countries with high consumption rates of fruits, vegetables, and spices have lower C19DM. We also examined non-dietary factors that generally affect health and quality of life that could possibly explain, in part, the disproportionate death numbers among countries, such as pollution (PM 2.5), alcohol consumption (liters per capita), smoking (number of cigarettes per year), and physical inactivity. Separately or in combination, these factors are known to either increase the risk of respiratory problems (infection) or predispose individuals to obesity and diabetes and therefore have potential to increase the fatality rates of Covid-19 infections. Data to date show that total consumption of fruits and vegetables (p = 0.393), consumption of spices (p = 0.771), consumption of fruits (p = 0.601), alcohol intake (p = 0.872), smoking (p = 0.606), or physical inactivity (p = 0.815) do not have any significant effect on C19DM (Table 2), suggesting that these factors cannot explain disproportionate Covid-19 mortality across countries. However, prevalence of diabetes (p = 0.028), life expectancy (p = 0.018), and caloric intake (p = 0.036) had a significant effect on C19DM (Table 2). When we regressed for model significant factors only (prevalence of diabetes, life expectancy, and calorie intake), the significance of these factors to the model for prevalence of diabetes (p = 0.004), life expectancy (p = 0.007), or calorie intake (p =0.029) increased compared to the inclusion of other factors in the model (Table 3).
There was a significant logarithmic relationship (R2 = 0.4183, p<0.000) between calorie intake (Kcal) per person per day and C19DM (Figure 2) suggesting higher calorie intake may be related to increased mortality rates of Covid-19. There was no clear relationship between alcohol consumption, physical inactivity, or smoking and C19DM (data not shown). There was an inverse power relationship between pollution and C19DM (R2 = 0.2585, p < 0.05) (Figure 4). The higher Covid-19 death rate at lower pollution is due to lower PM 2.5 value in developed countries where mortality rate is high compared to developing countries. This may explain the inverse relationship between pollution (PM 2.5) and C19DM. Therefore it should not be interpreted as indicative that lower pollution is potentially associated with higher Covid-19 mortality. We therefore suggest use of a different parameter for air pollution and Covid-19 mortality.
Calorie intake is generally higher in developed countries where mortality rates from Covid-19 are also high. Calorie intake above 3000 Kcal per day is higher than the recommended daily requirement for most people and this may favor the development of obesity. Mortality rates generally increased above 3000 Kcal/person per day (Fig. 2) suggesting that high calorie intake may predispose people to Covid-19 infection either directly or indirectly. While high calorie intake is not a specific indicator for a particular health condition in this case, it is a risk factor for development of obesity and diabetes and may predispose people to various chronic diseases that may compromise the performance of their immune system against infections19.
Persons with diabetes are 50% more likely to die from Covid-19 infection than non-diabetic persons of the same age9. However, diabetes in older age is also associated with cardiovascular disease, which could help to explain the greater likelihood of death from Covid-19 infection9. Diabetic persons have poor glycemic control that impairs many aspects of the immune response to viral infections and this effect is related to cytokine profiles and to changes in immune-responses including T-cell and macrophage activation20. Diabetes is also known to increase the severity of Covid-19 infections due to a mechanism involving angiotensin-converting-enzyme 2 (ACE2), a receptor for the coronavirus spike protein. Acute hyperglycemia has been shown to upregulate ACE2 expression on cells that might facilitate viral cell entry. However, chronic hyperglycemia is known to downregulate ACE2 expression making the cells vulnerable to the inflammatory and damaging effect of the virus,9 suggesting that the SARS-Cov-2 may need sugar moiety to attach to a cell receptor. Prevalence of diabetes is high in the age group > 60 years and it is expected that Covid-19 mortality will be higher in countries with a larger proportion of elderly individuals. Among the factors we examine in this study, the data suggest that prevalence of diabetes, life expectancy, and calorie intake might have significant effect on C19DM and may partly explain the heterogeneity in Covid-19 mortality observed so far. However, this trend may likely change as developing countries, previously underreporting, are slowly increasing their Covid-19 screening capacity and therefore identifying increased numbers of Covid-19 infections thereby changing the current dynamics of the Covid-19 data.