Evaluation of Country Dietary Habits Using Machine Learning Techniques
  in Relation to Deaths from COVID-19
María Teresa García-Ordás Natalia Arias Carmen Benavides Oscar García-Olalla José Alberto Benítez-Andrades
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.