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Open Access 01-12-2021 | Long-COVID Syndrome | Research

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

Authors: Emma Westerlind, Annie Palstam, Katharina S. Sunnerhagen, Hanna C. Persson

Published in: BMC Public Health | Issue 1/2021

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.

Results

A total of 11,955 people started sick leave for Covid-19 within the inclusion period. The median sick leave was 35 days, 13.3% were on sick leave for long Covid, and 9.0% remained on sick leave for the whole follow-up period. There were 2960 people who received inpatient care due to Covid-19, which was the strongest predictor of longer sick leave. Sick leave the year prior to Covid-19 and older age also predicted longer sick leave. No clear pattern of socioeconomic factors was noted.

Conclusions

A substantial number of people are on sick leave due to Covid-19. Sick leave may be protracted, and sick leave for long Covid is quite common. The severity of Covid-19 (needing inpatient care), prior sick leave, and age all seem to predict the likelihood of longer sick leave. However, no socioeconomic factor could clearly predict longer sick leave, indicating the complexity of this condition. The group needing long sick leave after Covid-19 seems to be heterogeneous, indicating a knowledge gap.

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Title: Patterns and predictors of sick leave after Covid-19 and long Covid in a national Swedish cohort
Authors: Emma Westerlind
Annie Palstam
Katharina S. Sunnerhagen
Hanna C. Persson
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Long-COVID Syndrome
COVID-19
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11013-2

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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