Factors associated with coronavirus disease 2019 infection severity among a sample of Lebanese adults: Data from a cross-sectional study

Abstract

Background and aims: Identification of factors responsible for severe illness related to coronavirus disease 2019 (COVID-19) could help in the early management of patients with high risk, especially in developing countries with poor medical care systems. To date, no data have been published concerning the factors associated with COVID-19 severity in Lebanon. In this study, we aimed at investigating the relation between sociodemographic variables, health status, and the clinical outcomes of COVID-19 in a sample of Lebanese adults.

Methods: In our cross-sectional study, 1052 patients (563 male and 489 female, with the median age of 42.83 ± 17.88 years), tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between January and March 2021, were recruited from a hospital in Byblos, Lebanon. Basic demographic data, medical history, clinical data, and selfreported symptoms related to COVID-19 were collected. Clinical classification of COVID-19 severity was carried out according to the WHO interim guidance on May 27, 2020. Multi and bivariate regression analysis were performed.

Results: When comparing patients with moderate symptoms versus mild, the results showed that older age (aOR = 1.05; 95% CI: 1.03-1.06) and having dyslipidemia (aOR = 1.89; 95% CI: 1.01-3.49) were significantly associated with higher odds of having moderate symptoms. When comparing patients with severe symptoms versus mild, older age (aOR = 1.08; 95% CI: 1.06-1.10), higher body mass index (aOR = 1.09; 95% CI: 1.04-1.15) and having respiratory diseases (aOR = 2.57; 95% CI: 1.03-6.36) were significantly associated with higher odds of having severe symptoms, whereas female gender (aOR = 0.56; 95% CI: 0.32-0.98) was significantly associated with lower odds of having severe symptoms compared to males. Finally, when comparing patients with severe symptoms versus moderate, older age (aOR = 1.03; 95% CI: 1.01-1.05) was found to be significantly associated with higher odds of having severe symptoms.

Conclusion: Identification of risk factors may contribute to a better understanding of the COVID-19 pathogenesis and provide clinical reference for early prognosis and management of patients.