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].