Patterns and predictors of sick leave after Covid-19 and long Covid in a national Swedish cohort.

ABSTRACT:

Background

The impact of Covid-19 and its long-term consequences is not yet fully understood. Sick leave can be seen as an indicator of health in a working age population, and the present study aimed to investigate sick-leave patterns after Covid-19, and potential factors predicting longer sick leave in hospitalised and non-hospitalised people with Covid-19.

Methods

The present study is a comprehensive national registry-based study in Sweden with a 4-month follow-up. All people who started to receive sickness benefits for Covid-19 during March 1 to August 31, 2020, were included. Predictors of sick leave ≥1 month and long Covid (≥12 weeks) were analysed with logistic regression in the total population and in separate models depending on inpatient care due to Covid-19.

Res

SUBMITTER: Westerlind E 

PROVIDER: S-EPMC8164957 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature