Impact of pre-pandemic sick leave diagnoses on the length of COVID-19-related sick leave: a nationwide registry-based study

BMC Public Health. 2023 Jan 29;23(1):195. doi: 10.1186/s12889-023-15115-x.


Background: The COVID-19 pandemic has caused difficulties and changes in many aspects of people's health and lives. Although infection affected work capacity, during the first wave policies for sick leave due to COVID-19 were unclear. The aim of this study was to investigate the impact of sick leave diagnoses in the year before the COVID-19 diagnosis on sick leave duration due to COVID-19 in a nationwide non-hospitalised population.

Methods: Data from three Swedish registries were analysed for sick leave commencing between 1 March and 31 August 2020, with a follow-up period of 4 months. Sick leave due to COVID-19 was considered the number of days that sickness benefits were used and included at least one registered COVID-19 diagnosis. Sick leave in the year before COVID-19 diagnosis were categorised into five diagnostic groups and one reference group (participants without prior sick leave).

Results: The study comprised 8935 individuals who received sickness benefits due to COVID-19 in Sweden during the first pandemic wave (mean age 46.7 years, 67% females, and 24% had diagnoses for sick leave in the year before COVID-19 diagnosis). The duration of sick leave due to COVID-19 was significantly higher in the groups with prior sick leave owing to musculoskeletal system diseases (odds ratio [OR]: 1.08, 95% confidence interval [CI]: 1.01-1.15); respiratory system diseases (OR: 1.22, 95% CI: 1.14-1.31); all other isolated diagnoses (OR: 1.08, 95% CI: 1.03-1.14); and multiple diagnoses (OR: 1.32, 95% CI: 1.21-1.43).

Conclusions: The results of this nationwide registry-based study indicate that individuals with premorbid conditions are more prone to longer sick leave durations due to COVID-19. Prediction of sick leave duration during the first wave of the COVID-19 pandemic is complex and several factors played a role.

Keywords: Epidemiology; Registry-based study; Return to work; SARS-CoV-2 infection; Sick leave.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19 Testing
  • COVID-19* / epidemiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Pandemics*
  • Registries
  • Sick Leave
  • Sweden / epidemiology