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COVID-19 and Sick Leave: An Analysis of the Ibermutua Cohort of Over 1,651,305 Spanish Workers in the First Trimester of 2020.

ABSTRACT: Objectives: The worldwide SARS-COV2 pandemic has impacted the health of workers and companies. The aim is to quantify it according to sick leave. Methods: Using ICD-9 codes, we analyzed Ibermutua records of all sick leaves during the first trimester of 2020, compared to during the same months of 2017, 2018, and 2019. We stratified the analysis by causes, patient sex, activity sectors, and regional data. All sick leaves were adjusted by the number of Ibermutua-affiliated persons in each period. Results: In March 2020, there was an unprecedented (116%) increase in total sick leaves, mainly due to infectious and respiratory diseases. Men and women were equally affected. All activity sectors were impacted, with the highest increase (457%) observed among health-related workers, especially due to contagious disease. The incidences of sick leaves were heterogeneous among different regions. Cost-analysis of sick leaves during the first trimester of 2020 compared with in previous years showed 40.3% increment (mean 2,813 vs. 2,005 € per 100 affiliated workers). Conclusions: The SARS-COV2 pandemic is having a huge impact on workers' health, as shown by data regarding sick leaves in March 2020. This is associated with greater economic burden for companies, both due to the cost associated with sick leaves and the losses in productivity due to confinement.

SUBMITTER: Calvo-Bonacho E

PROVIDER: S-EPMC7604328 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Sick leave patterns as predictors of disability pension or long-term sick leave: a 6.75-year follow-up study in municipal eldercare workers.

Project description:ObjectivesThe aim was to study whether a workplace-registered frequent short-term sick leave spell pattern was an early indicator of future disability pension or future long-term sick leave among municipal eldercare workers.SettingThe municipal healthcare sector in the city of Aarhus, which is the second largest city in Denmark.ParticipantsAll elder care employees who worked the entire year of 2004 in the municipality of Aarhus, Denmark (N=2774). The employees' sick leave days during 2004 were categorised into: 0-2 and 3-17 short (1-7 days) spells, 2-13 mixed short and long (8+ days) spells and long spells only. Student workers (n=180), employees who were absent due to maternal/paternal leave (n=536) and employees who did not work the entire year of 2004 (n=1218) were not included.Primary outcomeDisability pension and long-term sick leave (≥8 weeks) were subsequently identified in a National register. The cumulative incidence proportion as a function of follow-up weeks was estimated using the Kaplan-Meier curve. The relative cumulative incidence (RR) of experiencing events within 352 weeks was analysed in a generalised linear regression model using the pseudo values method adjusted for age, occupation, unfavourable work factors and sick leave length.ResultsA frequent short-term and a mixed sick leave pattern showed RRs of being granted a disability pension of 2.08 (95% CI 1.00 to 4.35) and 2.61 (95% CI 1.33 to 5.12) compared with 0-2 short spells. The risk of long-term sick leave was significantly increased for all sick leave patterns compared with 0-2 short spells. Adding sick leave length to the models attenuated all RRs and they became non-significant.ConclusionsSick leave length was a better indicator of future workability than spell frequency. Preventive actions should target employees engaged in homecare. The more sick leave days the greater the preventive potential seems, irrespective of spell frequency.

| S-EPMC3918999 | biostudies-literature

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

Project description:BackgroundThe 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.MethodsThe 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.ResultsA 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.ConclusionsA 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.

| S-EPMC8164957 | biostudies-literature

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

Project description:BackgroundThe 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.MethodsData 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).ResultsThe 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).ConclusionsThe 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.

| S-EPMC9884157 | biostudies-literature

Sick leave due to musculoskeletal pain: determinants of distinct trajectories over 1 year.

Project description:PURPOSE:This study aimed to identify sub-groups of workers with different trajectories of sick leave due to musculoskeletal pain over 1 year, and to investigate the extent to which the identified trajectories are associated with personal, occupational, lifestyle, and pain-related factors at baseline. METHODS:Data on 981 blue- and white-collar workers were analyzed in the DPHACTO cohort (2012-2014). The number of days on sick leave due to pain was reported using text messages at 4-week intervals across 1 year. Latent class growth analysis was used to distinguish sub-groups with different trajectories of sick leave. A web-based questionnaire at baseline was used to assess personal, occupational (physical and psychosocial), lifestyle, and pain-related factors. Multinomial regression models were constructed to determine associations between baseline factors and trajectories of sick leave (referencing no sick leave), with adjustment for potential confounders. RESULTS:Four distinct sub-groups were identified, with trajectories of sick leave due to pain ranging from no sick leave (prevalence 76%; average 0.5 days/year) to some days and increasing sick leave due to pain over 1 year (2%; 89 days/year). The increasing trajectory of sick leave was associated with higher perceived physical exertion, more time in manual work, less social community and influence at work, less leisure-time physical activity, smoking, and more severe symptoms (e.g., multisite pain, low back pain intensity, and pain interference). CONCLUSIONS:We identified four distinct trajectories of sick leave due to musculoskeletal pain. The sub-group with increasing sick leave due to pain was associated with several modifiable physical and psychosocial factors at work and outside work, which may have implications for prevention.

| S-EPMC6814632 | biostudies-literature

Cohort survey of healthcare workers with COVID-19 infection

Project description: Not available

| S-BSST563 | biostudies-other

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.

Project description:BackgroundStudies 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.MethodsThe 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.ResultsIn 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%).ConclusionIn 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.

| S-EPMC10843940 | biostudies-literature

Recurrent sick leave after COVID-19: investigating the first wave of the pandemic in a comprehensive Swedish registry-based study.

Project description:BackgroundSick-leave due to COVID-19 vary in length and might lead to re-current episodes. The aim was to investigate recurrent sick leave due to COVID-19 during the first wave.MethodsThis is a registry-based cohort study. The study comprises all people with sickness benefit due to COVID-19 in Sweden in March 1-August 31, 2020. Data from the Swedish Social Insurance Agency, the Swedish National Board of Health and Welfare, and Statistics Sweden were merged.ResultsWithin the follow-up period of 4 months, 11,955 people were subject to sickness benefit due to COVID-19, whereof 242 people (2.0%) took recurrent sick leave due to COVID-19, and of those 136 (56.2%) remained on sick leave at the end of follow-up. People with recurrent sick leave were older, more often women, and more likely to have been on sick leave prior to the COVID-19 pandemic.ConclusionA group of people presented with recurrent sick leave due to COVID-19. For half of them, the second sick leave lasted throughout the follow-up. People with recurrent sick leave differ in several aspects from those with shorter sick leave. To capture long-term sick-leave patterns due to COVID-19, a longer period of follow-up is needed.

| S-EPMC8530010 | biostudies-literature

Sick leave and work-related accidents of social workers in Germany: an analysis of routine data.

Project description:PurposeThe study aimed to explore the prevalence of sick leave and the risk of work-related accidents among German social workers and to describe causes and time trends in sick leave and accident claims.MethodsA retrospective analysis of routine data was carried out. Aggregated sick leave data of 195,100 social workers from four health insurance funds and 3037 accident claims of social workers from an accident insurance institution were analysed. Causes of accidents were examined by statistics of the German Social Accident Insurance (DGUV). Sick leave rates per 100 insured person-years were calculated. Relative risks (RR) of accidents were calculated in a multivariate analysis for three occupational groups (social workers and therapists, caregivers in sheltered workshops and teachers in residential institutions) and compared to other health and welfare service workers.ResultsMental disorders caused about one-fifth of the sick leave days of social workers. Sick leave due to mental disorders slightly increased in 2015 compared to 2012 (+ 3% and + 18%). Among the three subgroups of social workers, caregivers in sheltered workshops (RR 1.30; 95% CI 1.14-1.49) and teachers in residential institutions (RR 1.41; 95% CI 1.17-1.70) were at an increased risk of accidents at the workplace. Accidents were mostly caused by slipping (30%) and by violence (22%).ConclusionsThis study confirms that sick leave of social workers is frequently caused by mental disorders. Future studies could further examine differences between practice fields, long-term effects of work hazards and effective workplace interventions.

| S-EPMC6341039 | biostudies-literature

Sick leave, disability, and mortality in acute hepatic porphyria: a nationwide cohort study.

Project description:BACKGROUND:Acute hepatic porphyria (AHP) consists of three rare metabolic disorders. We investigated the risk of long-term sick leave, disability pension, and premature death in individuals with AHP compared to the general population. METHODS:In a nationwide cohort study from 1992 to 2017, records of 333 persons (total person-years?=?6728) with a confirmed AHP diagnosis were linked to several national compulsory registries (reference population =?5,819,937). We conducted survival analyses to assess additional risk. RESULTS:Persons with AHP had higher risks of accessing long-term sick leave (adjusted hazard ratio (aHR): 1.5, 95% confidence interval (CI): 1.3, 1.7) and disability pension (aHR: 1.9, CI: 1.5, 2.4). The risk was highest in persons who had been hospitalised for acute attacks, while no additional risk was observed in asymptomatic AHP gene mutation carriers. The median age when accessing disability pension was 45?years, 21?years younger than the general population. AHP was associated with increased risk of mortality due to hepatocellular carcinoma (adjusted mortality rate ratio (aMRR): 84.4, CI: 37.8, 188.2), but no overall increased risk of premature death was observed. CONCLUSIONS:Persons with symptomatic AHP were at increased risk of accessing long-term sick leave and disability pension but not of premature death.

| S-EPMC7035738 | biostudies-literature

School environment as predictor of teacher sick leave: data-linked prospective cohort study.

Project description:BackgroundPoor indoor air quality (IAQ) and psychosocial problems are common in schools worldwide, yet longitudinal research on the issue is scarce. We examined whether the level of or a change in pupil-reported school environment (IAQ, school satisfaction, and bullying) predicts recorded sick leaves among teachers.MethodsChanges in the school environment were assessed using pupil surveys at two time points (2001/02 and 2004/05) in 92 secondary schools in Finland. Variables indicating change were based on median values at baseline. We linked these data to individual-level records of teachers' (n?=?1678) sick leaves in 2001-02 and in 2004-05.ResultsMultilevel multinomial logistic regression models adjusted for baseline sick leave and covariates showed a decreased risk for short-term (one to three days) sick leaves among teachers working in schools with good perceived IAQ at both times (OR?=?0.6, 95% CI: 0.5-0.9), and for those with a positive change in IAQ (OR?=?0.6, 95% CI: 0.4-0.9), compared to teachers in schools where IAQ was constantly poor. Negative changes in pupil school satisfaction (OR?=?1.8, 95% CI: 1.1-2.8) and bullying (OR?=?1.5, 95% CI: 1.0-2.3) increased the risk for short-term leaves among teachers when compared to teachers in schools where the level of satisfaction and bullying had remained stable. School environment factors were not associated with long-term sick leaves.ConclusionsGood and improved IAQ are associated with decreased teacher absenteeism. While pupil-related psychosocial factors also contribute to sick leaves, no effect modification or mediation of psychosocial factors on the association between IAQ and sick leave was observed.

| S-EPMC3490775 | biostudies-literature

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