There was significant linear relationship (R2 = 0.668,p <0.000) between total tests and total deaths reported for each country (Supplementary figure 1) suggesting that the more the Covid-19 tests are conducted in a particular country the higher the likelihood of reporting more 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 Covid-19 cases than are reported to date. This data, therefore, suggests that if testing is intensified by those countries currently presumed to be under-reporting, number of death due to Covid-19 may likely rise.
There are disproportionate mortality rates from Covid-19 across the countries. High Covid-19 mortality rates are reported in countries with high life expectancy (>70 years) than those countries with shorter (<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 occurs between 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. Clearly, countries that have significantly higher number of persons above 75 years were hard hit by Covid-19 pandemic (Table 1). For example the average death per million populations of countries with life expectancy below 75 years was 6.5 (n = 99) while countries with life expectancy above 75 years (n = 111) was 90.4. Similarly, average total death in country below 75 years was 102.5 (n = 99) while above 75 years was 2606.8 (n = 111). Unsurprisingly, a large proportion of these countries are in Europe where health services are advanced. Therefore, this data suggest that the proportionally high 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 which may worsen Covid-19 disease and subsequently results in higher C19DM. This may partly explain why most African countries, whose population is comparatively younger, have lower mortality rate than European countries.
There are a number of factors, nutritional and environmental, that may lead to increased susceptibility to infection by persons above 70 years. Good nutrition primes the immune system. Generally, diet high in fruits and vegetables is believed to be healthier than diet low in fruits and vegetables due to significantly high content of micronutrients (vitamin and minerals) and phytochemicals which are important for immunity. Fruits, vegetables and spices are significant sources of phytochemicals some of which have antiviral properties11,12,13,14. In this respect we tested whether countries with high consumption 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. In this respect, we examined factors that are highly variable across countries such as pollution (PM 2.5), alcohol consumption (liters per capita), smoking (number of cigarettes per year) and physical inactivity. These factors are known to either increase the risk of respiratory problems (infection) or predispose individual to obesity and diabetes and therefore has potential to increase the fatality of Covid-19. Data to date shows that 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 calorie intake (p = 0.036) had 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 when other factors were included in the model (Supplementary Table 1).
There was 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 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) (Supplementary Figure 2). 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-10 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 rate from Covid-19 is also high. Calorie intake above 3000 Kcal per day is higher than recommended daily requirement for most people and this may favor development of obesity. Mortality rate generally increased above 3000 Kcal/person per day (Figure 2) suggesting that high calorie intake may predispose people to Covid-19 either directly or indirectly. While high calorie intake is not a specific indicator for a particular health condition in this case, high energy intake is a risk factor for development of obesity and diabetes and may predispose people to various chronic diseases which may reduce the performance of immune system against infections19.
Person with diabetes is 50% more likely to have fatal outcome from Covid-19 than non-diabetic person of the same age9. However, diabetes in older age is associated with cardiovascular disease, which in itself, could help to explain the association with fatal outcomes of Covid-199. Diabetic persons have poor glycemic control that impairs many aspects of the immune response to viral infection 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 increases the severity of Covid-19 due to a mechanism involving angiotensin-converting-enzyme 2 (ACE2), receptor for the coronavirus spike protein. Acute hyperglycemia has been shown to upregulate ACE2 expression on cells which 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 virus9 suggesting that the SARS-Cov-2 may need sugar moiety to attach to a cell receptor. Prevalence of diabetes is high in age group > 60 years and is expected that Covid-19 mortality will be higher in countries with a larger proportion of elderly. Among the factors examined in this study, the data suggests 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 Covid-19 cases may likely rise thereby changing the dynamics of the Covid-19 data.