Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19
This research addresses public health by identifying dietary factors that may influence COVID-19 outcomes, but it is incremental as it applies existing machine learning methods to new data.
The study analyzed dietary habits across 170 countries to find correlations with COVID-19 mortality rates, revealing that obesity and high fat consumption are linked to higher death rates, while higher cereal consumption and lower calorie intake are associated with lower rates.
COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated in order to find correlations between these habits and mortality rates caused by COVID-19 using machine learning techniques that group the countries together according to the different distribution of fat, energy, and protein across 23 different types of food, as well as the amount ingested in kilograms. Results shown how obesity and the high consumption of fats appear in countries with the highest death rates, whereas countries with a lower rate have a higher level of cereal consumption accompanied by a lower total average intake of kilocalories.