Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

Aug 5, 2026

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COVID-19 has impacted nearly every country, with notable differences in mortality rates that have motivated hypotheses about factors behind the virus’s lethality. This study assesses the eating habits of 170 countries and explores correlations with COVID-19 death outcomes using machine learning. Countries are grouped based on the distribution of fat, energy, and protein across 23 food types and the ingested amount in kilograms. Findings indicate higher obesity and fat consumption in regions with the highest death rates, while lower-death-rate countries show greater cereal intake and a lower average kilocalorie intake.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Abstract

Keywords

Introduction

COVID-19 background and transmission

Clinical features and lack of cure

Machine learning in COVID-19 research

healthcare arXiv :2402 . 12558v1 [ cs .LG] 19 Feb 2024 Article Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19 María Teresa García-Ordás 1, Natalia Arias 2, Carmen Benavides 3, Oscar García-Olalla 4 and José Alberto Benítez-Andrades 3, * 1 SECOMUCI Research Group, Escuela de Ingenierías Industrial e Informática, Universidad de León, Campus de Vegazana s/n, C.P., 24071 León, Spain; [mgaro@unileon.es](mgaro@unileon.es) 2 SALBIS Research Group, Department of Nursing and Physiotherapy Health Science School, University of León, Avenida Astorga s/n, Ponferrada, 24401 León, Spain; [narir@unileon.es](narir@unileon.es) 3 SALBIS Research Group, Department of Electric, Systems and Automatics Engineering, University of León, Campus of Vegazana s/n, León, 24071 León, Spain; carmen.benavides@unileon.es 4 Artificial Intelligence Department, Xeridia S.L., Av. Padre Isla 16, 24002 León, Spain; [oscar.olalla@xeridia.com](oscar.olalla@xeridia.com) * Correspondence: jbena@unileon.es Received: 3 September 2020; Accepted: 25 September 2020; Published: date 􀀁􀀂􀀃􀀁􀀄 􀀆􀀇􀀈 􀀁􀀂􀀃􀀄􀀅􀀆􀀇 Abstract: 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. Keywords: COVID-19; countries; fat; protein; KCal; deaths; machine learning; K-Means 1. Introduction Many pneumonia cases of unknown cause emerged in Wuhan, Hubei, China in December 2019 . Deep sequencing analysis from lower respiratory tract samples indicated a previously unknown coronavirus, which was named SARS-CoV-2 [1] . COVID-19, caused by SARS-CoV-2, was first reported in Wuhan but it quickly spread throughout the world becoming a global public health emergency [2] . It is transmitted by direct contact with respiratory drops that are emitted through a sick person’s cough or sneeze [3,4] . Its contagiousness depends on the amount of the virus in the airways. These drops infect another person through the nose, eyes, or mouth directly but they can also infect by touching the nose, eyes, or mouth with hands that have previously touched surfaces contaminated by these drops [5] . Kampf et al. [3] conducted a study in which they revealed that coronaviruses can remain infectious on inanimate surfaces for up to 9 days. However, surface disinfection with 0.1% sodium hypochlorite or 62–71% ethanol significantly reduces coronavirus infectivity on surfaces within 1 min from exposure time. Transmission by air over distances greater than 2 m seems unlikely. Healthcare 2020, xx, 5; [doi:10.3390/healthcarexx010005 www.mdpi.com/journal/healthcare](doi:10.3390/healthcarexx010005 www.mdpi.com/journal/healthcare) Most people get COVID-19 from other people with symptoms. However, there is increasing evidence of the role that people have in the transmission of the virus before the development of symptoms or with mild symptoms [6,7] . Chen et al. [8] carried out a descriptive study of the epidemiological and clinical characteristics of 99 cases of COVID-19 in Wuhan. The symptoms found were as follows; fever (83%), cough (82%), shortness of breath (31%), muscle ache (11%), confusion (9%), headache (8%), sore throat (5%), rhino

FAQs

How does the study link country diet to COVID-19 deaths?

It evaluates the eating habits of 170 countries and uses machine learning to find correlations between dietary patterns and mortality rates.

How are countries grouped in the analysis?

Countries are clustered according to differences in the distribution of fat, energy, and protein across 23 food categories and the quantity ingested in kilograms.

What dietary patterns are associated with higher versus lower death rates?

Higher death rates correlate with obesity and high fat consumption, while lower death rates correlate with higher cereal consumption and a lower total average kilocalorie intake.

Aug 5, 2026

Upload by Violet