Variables
Six covariates were included in the association model, gender, age, body mass index (BMI), COVID severity, and comorbidity. Age was grouped into more or less equal group sizes to be able to identify trends in the data while BMI was grouped according to the World Health Organization (WHO) classification [24]. COVID severity was determined using the National Early Warning Score 2 (NEWS 2) at hospital admission and could be categorized as low, low-medium, medium, and high [25]. Due to the relatively small sample size of the dataset, comorbidities were coded into the broadest parent term according to the International Statistical Classification of Diseases and Related Health Problems (ICD-11) after which the comorbidities were grouped into having a direct or indirect influence on COVID-19, based on literature. This was done to better capture the effect of the variable comorbidity by increasing the effect size of said variable. Diseases of the circulatory system, the respiratory system, the immune system, and endocrine, nutritional, or metabolic diseases were considered as having a potential direct influence on COVID-19. While diseases of the blood or blood-forming organs, the genitourinary system, the musculoskeletal system or connective tissue, the nervous system, neoplasms, sleep-wake disorders, factors influencing health status or contact with health services and mental, behavioral, or neurodevelopmental disorders were considered as having a potential indirect influence on COVID-19 [26,27].