Working Conditions and Long-Term Sickness Absence Due to Mental Disorders: A Prospective Record Linkage Cohort Study Among 19- to 39-Year-Old Female Municipal Employees.
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ABSTRACT: Objective
We examined associations between working conditions and long-term sickness absence due to mental disorders (LTSA-MD) among younger female public sector employees from different employment sectors.Methods
Survey data collected in 2017 (n = 3048) among 19- to 39-year-old female employees of the City of Helsinki, Finland, were used to examine job demands, job control, physical workload, computer work, and covariates. Register data on LTSA-MD were used over 1-year follow-up. Negative binomial regression models were applied.Results
Adverse psychosocial and physical working conditions were associated with higher LTSA-MD during the follow-up. Health and social care workers had the highest number of days of LTSA-MD.Conclusion
Working conditions are important factors when aiming to prevent LTSA-MD among younger employees, in the health and social care sector in particular.
SUBMITTER: Heinonen N
PROVIDER: S-EPMC8812422 | biostudies-literature | 2022 Feb
REPOSITORIES: biostudies-literature
Publications
Working Conditions and Long-Term Sickness Absence Due to Mental Disorders: A Prospective Record Linkage Cohort Study Among 19- to 39-Year-Old Female Municipal Employees.
Heinonen Noora N Lallukka Tea T Lahti Jouni J Pietiläinen Olli O Nordquist Hilla H Mänty Minna M Katainen Anu A Kouvonen Anne A
Journal of occupational and environmental medicine 20220201 2
<h4>Objective</h4>We examined associations between working conditions and long-term sickness absence due to mental disorders (LTSA-MD) among younger female public sector employees from different employment sectors.<h4>Methods</h4>Survey data collected in 2017 (n = 3048) among 19- to 39-year-old female employees of the City of Helsinki, Finland, were used to examine job demands, job control, physical workload, computer work, and covariates. Register data on LTSA-MD were used over 1-year follow-up ...[more]
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Project description:PurposePhysical work exposures are associated with sickness absence among older employees. We aimed to examine if they similarly contribute to all-cause sickness absence during early and mid-careers.MethodsWe used questionnaire data on physical work exposures linked to register data on sickness absence from 3542 municipal employees aged 19-39 years. Follow-up for the number of sickness absence days was 12 months. Exposures to physical workload, occupational environmental hazards, and sedentary work were divided into quartiles. In addition, duration of daily exposure to heavy work was included. Negative binomial regression models were used.ResultsHigher exposure to physical workload or hazardous exposures was associated with a higher number of sickness absence days. The age and gender adjusted rate ratios for sickness absence days among the participants whose exposure to physical workload was in the highest exposure quartile were 2.1 (95% CI 1.8‒2.5) compared with those whose exposure was in the lowest quartile. In addition, rate ratios for sickness absence days among participants who reported that they do heavy physical work 1.1‒2.0 h, 2.1‒4.0 h or over 4 h daily were 1.6 (1.3‒1.9), 1.5 (1.3‒1.8) and 1.7 (1.5‒2.1), respectively, compared with those who reported not doing physical work. Further adjustment for lifestyle factors or health characteristics attenuated the associations only slightly.ConclusionExposure to physically demanding work is associated with a higher number of sickness absence days among municipal employees below 40 years of age. Physical working conditions should be considered when aiming to support later work ability.
| S-EPMC8795030 | biostudies-literature
Project description:OBJECTIVES:Pain is linked to an increased risk of sickness absence (SA); however, the extent to which unmeasured time-invariant differences explain this association is yet unknown. Therefore, we determined the within-individual associations between pain and short-term (in the survey year) and long-term (2 years following the survey years) SA risk in high and low occupational classes while controlling for the potential bias due to unobservable time-invariant characteristics. METHODS:The Helsinki Health Study data consisting of midlife public sector employees with mailed surveys from up to four time points, and SA record linkage were used (3983 persons). The within-individual estimates were calculated using hybrid negative binomial regression models. RESULTS:Acute/subacute pain was associated with a 13% increase in the rate of short-term SA days (incidence rate ratio 1.13 [95% CI 1.01 to 1.27]), while the association was somewhat stronger for chronic pain (1.32 [1.19-1.47]). For the employees in the low occupational class, these associations were robust (1.29 [1.10-1.50] for acute/subacute and 1.43 [1.23-1.66] for chronic pain), whereas only chronic pain was associated with SA among those in the high occupational class (1.25 [1.08-1.46]). Chronic pain was also associated with SA days in the long term without occupational class differences. Similar results were obtained for multisite pain (pain in several locations). CONCLUSIONS:These results indicate that particularly chronic and multisite pain have a within-individual link to SA but ignoring unobservable differences between those reporting pain and those not might yield overstated effect sizes. Pain might have a different relation to SA in low and high occupational classes.
| S-EPMC6475189 | biostudies-literature
Project description:Background. Decreased work ability due to mental disorders is a growing concern in Europe. We studied the role of work-family conflicts in association with long-term sickness absence due to mental disorders (LTSA-MD).Methods. Baseline data were extracted from the Helsinki Health Study for women aged 40 to 55 in full-time work in 2001 - 2002 (N = 2386). Questionnaire responses were linked with register data from the Social Insurance Institution of Finland on SA spells due to mental disorders during 2004-2010. We studied an overall question on satisfaction with combining work and family (WFS) and composite scores of work-to-family conflicts (WTFC) and family-to-work-conflicts (FTWC), and their components in association with the first certified SA spell (≥ 12 calendar days) due to a mental disorder during the follow-up. We performed Cox regression analyses with hazard ratios (HR) and their 95% confidence intervals (CI) adjusted for sociodemographic factors, work schedule, perceived mental and physical strenuousness at work, and self-rated health. First, we examined all participants, and second, only those who reported no prior mental disorder.Results. Poor work-family satisfaction (WFS) was associated with subsequent LTSA-MD, adjusting for all covariates (HR 1.60; 95% CI 1.10-2.16). Both high WTFC (1.64; 1.15-2.23), and high FTWC (1.43; 1.02-2.00) increased the probability of LTSA-MD in the full model. When participants with prior mental disorder were excluded, the association between poor WFS and WTFC with LTSA-MD retained while that between FTWC and LTSA-MD attenuated; however, two items of the FTWC were still associated with LTSA-MD: 'Family worries and problems distract you from your work' and 'Family matters prevent you from sleeping enough to do your job well'. Of the WTFC items, the following remained associated with LTSA-MD: 'Problems at work make you irritable at home' and 'Your job takes so much energy you do not feel up to doing things that need attention at home'. The experience of decreased time for work or family did not associate with LTSA-MD.Conclusions. Among female municipal employees, dissatisfaction with combining work and family and both work-to-family and family-to-work conflicts were associated with subsequent long-term sickness absence due to mental disorders.
| S-EPMC10265818 | biostudies-literature
Project description:BackgroundThe ageing work force is heterogeneous, following distinct development in work ability. This study aims to identify trajectories of long-term sickness absence (SA) in later careers and to examine potentially modifiable factors associated with the development of SA.MethodsData comprised of municipal employees of the city of Helsinki aged 50-60 years during 2004-2018 (N = 4729, 80% women). The developmental trajectories of long-term (> 10 working days) SA were examined with Group-based trajectory modelling (GBTM) using SA records of the Social Insurance Institution of Finland during 2004-2018. All-cause and diagnosis-specific (mental disorder- and musculoskeletal disease-related) SA days were analysed. The association of social and health-related factors with trajectory membership was examined using multinomial logistic regression (odds ratios and 95% confidence intervals).ResultsA model with three trajectories was selected for both all-cause and diagnosis-specific SA. Regarding all-cause long-term SA trajectories, 42% had no long-term SA, 46% had low levels of SA, and 12% had a high rate of SA during follow-up. Lower occupational class, reporting smoking, overweight or obesity, moderate or low leisure-time physical activity, and sleep problems were associated with a higher likelihood of belonging to the trajectory with a high rate of SA in both all-cause and diagnosis-specific models.ConclusionsMost ageing employees have no or little long-term SA. Modifiable factors associated with trajectories with more SA could be targeted when designing and timing interventions in occupational healthcare.
| S-EPMC10373243 | biostudies-literature
Project description:ObjectiveTo identify social and health-related predictors of the number of days lost due to sickness absence (SA) and disability pension (DP) among initially 55-year-old public-sector workers.MethodsThe data from the Finnish Helsinki Health Study included participants aged 55 years at the baseline (in 2000-2002, N = 1630, 81% women), and were enriched with register-based information on SA and DP. The cumulative number of calendar days lost due to SA ≥ 1 day or DP between ages 55 and 65 was calculated. Negative binomial regression model was used to identify the predictors of days lost.ResultsThe average calendar days lost was 316 days (about 220 working days) during a 10-year follow-up, and 44% were due to SA and 56% due to DP. Smoking [incidence rate ratio (IRR) = 1.19, 95% CI 1.01-1.40 for past and IRR = 1.30, CI 1.07-1.58 for current], binge drinking (IRR = 1.22, CI 1.02-1.46), lifting or pulling/pushing heavy loads (IRR = 1.35, CI 1.10-1.65), awkward working positions (IRR = 1.24, CI 1.01-1.53), long-standing illness limiting work or daily activities (IRR = 2.32, CI 1.93-2.79), common mental disorder (IRR = 1.52, CI 1.30-1.79), and multisite pain (IRR = 1.50, CI 1.23-1.84) increased the number of days lost, while high level of education (IRR = 0.66, CI 0.52-0.82) and moderate level of leisure-time physical activity (IRR = 0.80, CI 0.67-0.94) reduced the number of days lost.ConclusionsModifiable lifestyle risk factors, workload factors, common mental disorder, and multisite pain substantially increase the number of days lost. However, the findings of this study could be generalized to female workers in the public sector. Future research should also consider shorter SA spells in estimating working years lost and working life expectancy.
| S-EPMC8238732 | biostudies-literature
Project description:ObjectivesData mining can complement traditional hypothesis-based approaches in characterizing unhealthy work exposures. We used it to derive a hypothesis-free characterization of working hour patterns in shift work and their associations with sickness absence (SA).MethodsIn this prospective cohort study, complete payroll-based work hours and SA dates were extracted from a shift-scheduling register from 2008 to 2019 on 6029 employees from a hospital district in Southwestern Finland. We applied permutation distribution clustering to time series of successive shift lengths, between-shift rest periods, and shift starting times to identify clusters of similar working hour patterns over time. We examined associations of clusters spanning on average 23 months with SA during the following 23 months.ResultsWe identified eight distinct working hour patterns in shift work: (i) regular morning (M)/evening (E) work, weekends off; (ii) irregular M work; (iii) irregular M/E/night (N) work; (iv) regular M work, weekends off; (v) irregular, interrupted M/E/N work; (vi) variable M work, weekends off; (vii) quickly rotating M/E work, non-standard weeks; and (viii) slowly rotating M/E work, non-standard weeks. The associations of these eight working-hour clusters with risk of future SA varied. The cluster of irregular, interrupted M/E/N work was the strongest predictor of increased SA (days per year) with an incidence rate ratio of 1.77 (95% confidence interval 1.74-1.80) compared to regular M/E work, weekends off.ConclusionsThis data-mining suggests that hypothesis-free approaches can contribute to scientific understanding of healthy working hour characteristics and complement traditional hypothesis-driven approaches.
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Project description:OBJECTIVE: There is no information on the duration of absence of depressed Dutch workers. The aim of this study was to determine the duration of sickness absence due to depressive symptoms in the working population. METHODS: In this observational study of 15% of the Dutch working population, all absence episodes (n = 9,910) starting between April 2002 and November 2005 diagnosed as depression were selected. For these episodes, Kaplan-Meier survival curves were computed. RESULTS: The mean (and median) duration of sickness absence due to depressive symptoms was 200 (179) days in men and 213 (201) days in women. In both sexes, older employees had longer absence durations. Depressive symptoms had an estimated rate of chronicity (1 year of absence) of 24%. Employees in educational and public services (232 days in men and 242 days in women), commercial services (213 days in men and 219 days in women) and health care (212 days in men and 214 days in women) had the longest mean duration of absence with depressive symptoms. Men in the industrial sector (189 days) had the shortest absence periods. Employees in large sized companies (188 days in men and 208 days in women) had shorter absence episodes as compared to companies with less than 75 employees (214 days in men and 226 days in women). CONCLUSIONS: Workers with depressive symptoms were absent for a long time. Explanations for the long duration are discussed. It is recommended to develop and apply tools for recognizing employees at risk for chronic depression.
| S-EPMC2254471 | biostudies-other
Project description:BackgroundFrequent sickness absence-that is, 3 or more episodes of sickness absence in 1 year-is a problem for employers and employees. Many employees who have had frequent sickness absence in a prior year also have frequent sickness absence in subsequent years: 39% in the first follow-up year and 61% within 4 years. Moreover, 19% have long-term sickness absence (≥6 weeks) in the first follow-up year and 50% within 4 years. We developed an electronic health (eHealth) intervention, consisting of fully automated feedback and advice, to use either as a stand-alone tool (eHealth intervention-only) or combined with consultation with an occupational physician (eHealth intervention-occupational physician).ObjectiveThis study aimed to evaluate the effect of the eHealth intervention, with or without additional occupational physician consultation, to reduce sickness absence frequency for employees with frequent sickness absence, versus care as usual (CAU).MethodsThis study was a three-armed randomized controlled trial. Employees with frequent sickness absence received invitational letters, which were distributed by their employers. The primary outcome measure was the number of register-based sickness absence episodes 12 months after completing the baseline questionnaire. Secondary outcome measures were register-based total sickness absence days and self-assessed burnout, engagement, and work ability. In a process evaluation 3 months after baseline, we examined adherence to the intervention and additional actions such as general practitioner and occupational physician visit, communication with the manager, and lifestyle change.ResultsA total of 82 participants were included in the analyses, 21 in the eHealth intervention-only group, 31 in the eHealth intervention-occupational physician group, and 30 in the CAU group. We found no significant difference in sickness absence frequency between the groups at 1-year follow-up. Sickness absence frequency decreased in the eHealth intervention-only group from 3 (interquartile range, IQR 3-4) to 1 episode (IQR 0.3-2.8), in the eHealth intervention-occupational physician group from 4 (IQR 3-5) to 3 episodes (IQR 1-4), and in the CAU group from 3 (IQR 3-4) to 2 episodes (IQR 1-3). For secondary outcomes, we found no significant differences between the intervention groups and the control group. The process evaluation showed that only 3 participants from the eHealth intervention-occupational physician group visited the occupational physician on invitation.ConclusionsAmong employees with frequent sickness absence, we found no effect from the eHealth intervention as a stand-alone tool in reducing sickness absence frequency, nor on total sickness absence days, burnout, engagement, or work ability. This might be due to low adherence to the intervention because of insufficient urgency to act. We cannot draw any conclusion on the effect of the eHealth intervention tool combined with an occupational physician consultation (eHealth intervention-occupational physician), due to very low adherence to the occupational physician consultation. An occupational physician consultation could increase a sense of urgency and lead to more focus and appropriate support. As this was the first effectiveness study among employees with frequent sickness absence, strategies to improve recruitment and adherence in occupational eHealth are included.Trial registrationNetherlands Trial Register NTR4316; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4316 (Archived by WebCite at http://www.webcitation.org/713DHhOFU).
| S-EPMC6231854 | biostudies-literature
Project description:AimsAlthough seasonality has been documented for mental disorders, it is unknown whether similar patterns can be observed in employee sickness absence from work due to a wide range of mental disorders with different severity level, and to what extent the rate of change in light exposure plays a role. To address these limitations, we used daily based sickness absence records to examine seasonal patterns in employee sickness absence due to mental disorders.MethodsWe used nationwide diagnosis-specific psychiatric sickness absence claims data from 2006 to 2017 for adult individuals aged 16-67 (n = 636,543 sickness absence episodes) in Finland, a high-latitude country with a profound variation in daylength. The smoothed time-series of the ratio of observed and expected (O/E) daily counts of episodes were estimated, adjusted for variation in all-cause sickness absence rates during the year.ResultsUnipolar depressive disorders peaked in October-November and dipped in July, with similar associations in all forms of depression. Also, anxiety and non-organic sleep disorders peaked in October-November. Anxiety disorders dipped in January-February and in July-August, while non-organic sleep disorders dipped in April-August. Manic episodes reached a peak from March to July and dipped in September-November and in January-February. Seasonality was not dependent on the severity of the depressive disorder.ConclusionsThese results suggest a seasonal variation in sickness absence due to common mental disorders and bipolar disorder, with high peaks in depressive, anxiety and sleep disorders towards the end of the year and a peak in manic episodes starting in spring. Rapid changes in light exposure may contribute to sickness absence due to bipolar disorder. The findings can help clinicians and workplaces prepare for seasonal variations in healthcare needs.
| S-EPMC7615330 | biostudies-literature
Project description:Aims: The aim was to examine whether the contribution of physical work exposures to the risk of sickness absence (SA) is different between those with and without common mental disorders (CMD). Methods: We used questionnaire data on four work exposures and CMD from 6159 participants of the Helsinki Health Study cohort with 12,458 observations from three surveys (2000-2002, 2007 and 2012). We formed combination exposures for the work exposures (hazardous exposures, physical workload, computer and shift work) with CMD. Associations with SA of different length were examined with negative binomial regression models. Results: We observed stronger associations for CMD with SA than for the individual work exposures. The strength of the associations for hazardous exposures and physical workload increased with length of SA, especially when the participant also had CMD. The strongest associations for the combined exposures were observed for SA ⩾15 days, the rate ratios being 2.63 (95% CI 2.27-3.05) among those with hazardous exposure and CMD, and 3.37 (95% CI 2.93-3.88) among those with heavy physical workload and CMD. Conclusions: Employees with hazardous exposures or physical workload combined with CMD were at the highest risk of SA compared with those without these exposures or with only one exposure.
| S-EPMC7917561 | biostudies-literature