Dataset Information

The sociodemographic patterning of sick leave and determinants of longer sick leave after mild and severe COVID-19: a nationwide register-based study in Sweden.

ABSTRACT:

Background

Studies on sociodemographic differences in sick leave after coronavirus disease 2019 (COVID-19) are limited and research on COVID-19 long-term health consequences has mainly addressed hospitalized individuals. The aim of this study was to investigate the social patterning of sick leave and determinants of longer sick leave after COVID-19 among mild and severe cases.

Methods

The study population, from the Swedish multi-register observational study SCIFI-PEARL, included individuals aged 18-64 years in the Swedish population, gainfully employed, with a first positive polymerase chain reaction (PCR) test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from 1 January 2020 until 31 August 2021 (n = 661 780). Using logistic regression models, analyses were adjusted for sociodemographic factors, vaccination, prior sick leave, comorbidities and stratified by hospitalization.

Results

In total, 37 420 (5.7%) individuals were on sick leave due to COVID-19 in connection with their first positive COVID-19 test. Individuals on sick leave were more often women, older, had lower income and/or were born outside Sweden. These differences were similar across COVID-19 pandemic phases. The highest proportion of sick leave was seen in the oldest age group (10.3%) with an odds ratio of 4.32 (95% confidence interval 4.18-4.47) compared with the youngest individuals. Among individuals hospitalized due to COVID-19, the sociodemographic pattern was less pronounced, and in some models, even reversed. The intersectional analysis revealed considerable variability in sick leave between sociodemographic groups (range: 1.5-17.0%).

Conclusion

In the entire Swedish population of gainfully employed individuals, our findings demonstrated evident sociodemographic differences in sick leave due to COVID-19. In the hospitalized group, the social patterning was different and less pronounced.

SUBMITTER: Spetz M

PROVIDER: S-EPMC10843940 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

The sociodemographic patterning of sick leave and determinants of longer sick leave after mild and severe COVID-19: a nationwide register-based study in Sweden.

Spetz Malin M Natt Och Dag Yvonne Y Li Huiqi H Nwaru Chioma C Santosa Ailiana A Nyberg Fredrik F Rosvall Maria M

European journal of public health 20240201 1

<h4>Background</h4>Studies on sociodemographic differences in sick leave after coronavirus disease 2019 (COVID-19) are limited and research on COVID-19 long-term health consequences has mainly addressed hospitalized individuals. The aim of this study was to investigate the social patterning of sick leave and determinants of longer sick leave after COVID-19 among mild and severe cases.<h4>Methods</h4>The study population, from the Swedish multi-register observational study SCIFI-PEARL, included i ...[more]

PMID: 37889580

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Project description:BackgroundStudies on sociodemographic disparities in Covid-19 vaccination uptake in the general population are still limited and mostly focused on older adults. This study examined sociodemographic differences in Covid-19 vaccination uptake in the total Swedish population aged 18-64 years.MethodsNational Swedish register data within the SCIFI-PEARL project were used to cross-sectionally investigate sociodemographic differences in Covid-19 vaccination among Swedish adults aged 18-64 years (n = 5,987,189) by 12 October 2021. Using logistic regression models, analyses were adjusted for sociodemographic factors, region of residence, history of Covid-19, and comorbidities. An intersectional analysis approach including several cross-classified subgroups was used to further address the complexity of sociodemographic disparities in vaccination uptake.FindingsBy 12 October 2021, 76·0% of the Swedish population 18-64 years old had received at least two doses of Covid-19 vaccine, an additional 5·5% had received only one dose, and 18·5% were non-vaccinated. Non-vaccinated individuals were, compared to vaccinated, more often younger, male, had a lower income, were not gainfully employed, and/or were born outside Sweden. The social patterning for vaccine dose two was similar, but weaker, than for dose one. After multivariable adjustments, findings remained but were attenuated indicating the need to consider different sociodemographic factors simultaneously. The intersectional analysis showed a large variation in vaccine uptake ranging from 32% to 96% in cross-classified subgroups, reflecting considerable sociodemographic heterogeneity in vaccination coverage.InterpretationOur study, addressing the entire Swedish population aged 18-64 years, showed broad sociodemographic disparities in Covid-19 vaccine uptake but also wide heterogeneities in coverage. The intersectional analysis approach indicates that focusing on specific sociodemographic factors in isolation and group average risks without considering the heterogeneity within such groups will risk missing the full variability of vaccine coverage.FundingSciLifeLab / Knut & Alice Wallenberg Foundation, Swedish Research Council, Swedish government ALF agreement, FORMAS.

Project description:BackgroundAdverse economic consequences of antibiotic resistance, both in health care systems and in society at large, have been estimated to emerge and significantly affect the global economy. To date, most studies of the societal costs of antibiotic resistance have had a macroeconomic perspective, using the number of attributable deaths as a quantifier for production loss. In contrast, there have been few studies of the consequences of antibiotic resistance in terms of the length of sick leave and hence the impact of morbidity on production loss. The aim of our study was to estimate the production loss from ill health caused by antibiotic resistance.MethodTo estimate additional production loss due to antibiotic resistance, we used Swedish register-based cohort data to determine days of long-term sick leave (LTSL) for episodes of infection caused by resistant and susceptible bacteria respectively. We collected patient data for four common infection types (bloodstream infection, urinary tract infection, skin and soft tissue infection, and pneumonia), as well as, antibiotic susceptibility test data, and total days of LTSL. We used a two-part model to estimate the number of LTSL days attributable to resistance, and controlled for comorbidities and demographic variables such as age and gender.ResultsThe results show that antibiotic resistance adds an additional 8.19 days of LTSL compared with a similar infection caused by susceptible bacteria, independent of infection type and resistance type. Furthermore, the results suggest that production loss due to temporary sick leave caused by antibiotic resistance in a working-age population amounts to about 7% of total health care costs attributable to antibiotic resistance in Sweden.ConclusionEstimating the effect of antibiotic resistance in terms of temporary production loss is important to gain a better understanding of the economic consequences of antibiotic resistance in society and, by extension, enable more effective resource allocation to combat further emergence of resistance. Society's economic costs of antibiotic resistance are, however, probably much greater than those of sick leave due to disease alone.

Dataset Information

The sociodemographic patterning of sick leave and determinants of longer sick leave after mild and severe COVID-19: a nationwide register-based study in Sweden.

Background

Methods

Results

Conclusion

Publications

The sociodemographic patterning of sick leave and determinants of longer sick leave after mild and severe COVID-19: a nationwide register-based study in Sweden.

Similar Datasets

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