The association of sociodemographic characteristics with work disability trajectories during and following long-term psychotherapy: a longitudinal register study.

PURPOSE: This register-based study examined the trajectories of depression or anxiety disorder-related work disability during and following long-term psychotherapy and identified sociodemographic factors that indicate membership in different trajectory groups. METHODS: Data were drawn from national registers (Statistics Finland, Social Insurance Institution of Finland). Participants included a random sample of Finnish working-age individuals (18-55 years) who started psychotherapy treatment between 2011 and 2014 and were followed for 5 years: 1 year before and 4 years after the onset of psychotherapy (N = 3 605 individuals; 18 025 person-observations across five time points). Group-based trajectory modeling was applied to assign individuals to work disability trajectories by the number of annual mental health-related work disability months. Multinomial logistic regression was used to examine the associations between trajectory group membership and baseline sociodemographic factors of age, gender, occupational status, and geographical area of residence. RESULTS: Four mental health-related work disability trajectories were identified: stable very low (72%), decrease (11%), persistent low (9%) and persistent high (7%). Those with older age, female gender, lower occupational status, and living in sparsely populated geographical areas were more likely to belong to the most unfavorable trajectory group of persistent high work disability. The presence of multiple risk characteristics substantially increased the probability of belonging to the most adverse trajectory group. CONCLUSIONS: Sociodemographic factors were associated with the course of mental health-related work disability in association with psychotherapy. Rehabilitative psychotherapy does not function as an equal support resource for work ability in all parts of the population.

Association of nurse understaffing and limited nursing work experience with in-hospital mortality among patients: A longitudinal register-based study.

BACKGROUND: Although nurse understaffing and limited nursing work experience may affect hospital patients' risk of mortality, relatively little longitudinal patient-level evidence on these associations is available. Hospital administrative data could provide important information about the level of staffing, nurses' work experience and patient mortality over time. OBJECTIVE: To examine whether daily exposure to nurse understaffing and limited nursing work experience is associated with patient mortality, using patient-level data with different exposure time windows and accounting for several patient-related characteristics. METHODS: This longitudinal register-based study combined administrative data on patients (clinical database Auria) and employees (Titania® shift-scheduling) from one hospital district in Finland in 2013-2019, covering a total of 254,446 hospital stays in 40 units. We quantified nurse understaffing as the number of days with low nursing hours in relation to target hours (<90 % of the annual unit median), and limited work experience as the number of days with a low proportion of nurses with >3 years of in-hospital experience, and those aged over 25 (<90 % of the annual unit median). We used two survival model designs to analyze the associations between nurse understaffing and limited nursing work experience and the in-hospital mortality of the patients: we considered these exposures during the first days in hospital and as a cumulative proportion of days with suboptimal staffing during the first 30 days. RESULTS: In total, 1.5 % (N = 3937) of the hospital stays ended in death. A 20 % increase in the proportion of days with nurse understaffing was associated with an increased, 1.05-fold mortality risk at the patient level (95 % confidence interval, 1.01-1.10). The cumulative proportion of days with limited nursing work experience, or the combination of nurse understaffing and limited work experience were not associated with increased risk of death among all patients. However, both indicators of limited nursing work experience were associated with an increased mortality risk among patients with comorbidities (HR 1.05, 95 % CI 1.02-1.08 and HR 1.05, 95 % CI 1.00-1.10, respectively). CONCLUSIONS: Nurse understaffing was associated with a slight, but a potentially critical increase in patient in-hospital mortality. Limited nursing work experience was associated with increased in-hospital mortality in a subgroup of patients with comorbidities. Increased use of administrative data on planned and realized working hours could be a routine tool for reducing avoidable in-hospital mortality.

Parkinson's disease and occupational exposure to organic solvents in Finland: a nationwide case-control study.

OBJECTIVE: This study aimed to investigate the association between Parkinson's disease (PD) and occupational exposure to organic solvents generally and chlorinated hydrocarbons (CHC) in particular. METHODS: We assembled a Finland-wide case-control study for birth years 1930-1950 by identifying incident PD cases from the register of Reimbursement of Medical Costs and drawing two controls per case using incidence density sampling from the Population Information System, matched on sex, birth year, and residency in Finland in 1980-2014. Occupation and socioeconomic status (SES) were identified from national censuses. We assessed cumulative occupational exposures via FINJEM job-exposure matrix. Smoking was based on occupation-specific prevalence by sex from national surveys. We estimated confounder-adjusted PD incidence rate ratios (IRR) via logistic regression and evaluated their sensitivity to errors in FINJEM through probabilistic bias analysis (PBA). RESULTS: Among ever-employed, we identified 17 187 cases (16.0% potentially exposed to CHC) and 35 738 matched controls. Cases were more likely to not smoke and belong to higher SES. Cumulative exposure (CE) to CHC (per 100 ppm-years, 5-year lag) was associated with adjusted IRR 1.235 (95% confidence interval 0.986-1.547), with stronger associations among women and among persons who had more census records. Sensitivity analyses did not reveal notable associations, but stronger effects were seen in the younger birth cohort (1940-1950). PBA produced notably weaker associations, yielding a median IRR 1.097 (95% simulation interval 0.920-1.291) for CHC. CONCLUSION: Our findings imply that PD is unlikely to be related to typical occupational solvent exposure in Finland, but excess risk cannot be ruled out in some highly exposed occupations.

Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees.

OBJECTIVE: This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers. METHODS: This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up. RESULTS: The C-index of 0.73 [95% confidence interval (CI) 0.70-0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67-0.75) for an administrative records-only model, and 0.79 (95% CI 0.76-0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome. CONCLUSIONS: The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.

Occupational class differences in male suicide risk in Finland from 1970 to 2019.

BACKGROUND: In the last few decades, suicide rates have decreased in most European countries. However, periodic changes in risk by occupational class have not been studied as much in detail. METHODS: Representative cohorts of Finnish working-age men were followed for nine years on suicide mortality starting from five different census years (1970, 1980, 1990, 2000, 2010). Each cohort included between 300 970 and 332 318 men. Cox regression modelling was used to estimate hazard ratios by census year, occupational class and their interactions. Further models adjusted for age and its interactions with census year and occupational class. RESULTS: The risk of male suicide has more than halved between 1991 and 2019. The relative hazard ratio of suicide in manual workers compared to managers and professionals was around 1.6 to 1.8 times higher. The period when the suicide risk started to decline differed by occupational class: a significant decrease compared to 1970s' levels was seen for managers and professionals already in the 1990s and for lower non-manual employees around 10 years later (in the 2000s). Manual workers only reached the 1970s suicide risk of managers and professionals in the 2000s and 2010s. CONCLUSION: A delayed reduction of suicide rates among lower occupational classes suggests that the impact of social changes can occur at different speed in different population groups.

Sickness absence among migrant and non-migrant care workers in Finland: A register-based follow-up study.

AIMS: This study aimed to compare the sickness absence (SA; over 10 days) rates of migrant and non-migrant care workers in Finland. METHODS: Two cohorts were randomly sampled from nationwide registers and analysed together in a three-year follow-up design (2011-2013, 2014-2016). The pooled data consisted of 78,476 care workers, of whom 5% had a migrant background. Statistical methods included cross-tabulations and Poisson regression modelling. RESULTS: Thirty-five percent of the Finnish-born care workers had at least one SA during the follow-up. Care workers from the post-2004 EU countries (30%, at least one SA), Russia, the Former Soviet Union and the Balkan states (25%) and the Global South and East (21%) had fewer episodes of SA than the Finnish-born care workers. The two latter groups also had lower SA rates after we controlled for occupation, gender, age, income and region of residence. Care workers from Western Europe and the Global North (36%) had higher SA rates than the Finnish-born care workers. CONCLUSIONS: The following explanations were discussed: population-level health differences - migrants from lower-income non-EU countries are generally healthier than the Finnish-born population (due to, e.g., the 'healthy migrant effect'); discrimination in recruitment and employment - migrants from lower-income non-EU countries need to be healthier than Finnish-born jobseekers to gain employment (in the care sector or more broadly); and sickness presenteeism - migrants from lower-income non-EU countries underuse their right to sickness allowance (due to, e.g., job insecurity). It is likely that these mechanisms affect migrants differently depending on, for example, their countries of origin and social status in Finland.

Nurse Staffing Level, Length of Work Experience, and Risk of Health Care-Associated Infections Among Hospital Patients: A Prospective Record Linkage Study.

BACKGROUND: Nurse understaffing may have several adverse consequences for patients in hospitals, such as health care-associated infections (HAIs), but there is little longitudinal evidence available on staffing levels and HAIs with consideration of incubation times to confirm this. Using daily longitudinal data, we analyzed temporal associations between nurse understaffing and limited work experience, and the risk of HAIs. METHODS: The study was based on administrative data of 40 units and 261,067 inpatient periods for a hospital district in Finland in 2013-2019. Survival analyses with moving time windows were used to examine the association of nurse understaffing and limited work experience with the risk of an HAI 2 days after exposure, adjusting for individual risk factors. We reported hazard ratios (HRs) with 95% CIs. RESULTS: Neither nurse understaffing nor limited work experience were associated with the overall risk of HAIs. The results were inconsistent across staffing measures and types of HAIs, and many of the associations were weak. Regarding specific HAI types, 1-day exposure to low proportion of nurses with >3 years of in-hospital experience and low proportion of nurses more than 25 years old were associated with increased risk of bloodstream infections (HR=1.30; 95% CI: 1.04-1.62 and HR=1.40; 95% CI: 1.07-1.83). Two-day exposure to low nursing hours relative to target hours was associated with an increased risk of surgical-site infections (HR=2.64, 95% CI: 1.66-4.20). CONCLUSIONS: Data from time-varying analyses suggest that nursing staff shortages and limited work experience do not always increase the risk of HAI among patients.

Severe Infection and Risk of Cardiovascular Disease: A Multicohort Study.

BACKGROUND: The excess risk of cardiovascular disease associated with a wide array of infectious diseases is unknown. We quantified the short- and long-term risk of major cardiovascular events in people with severe infection and estimated the population-attributable fraction. METHODS: We analyzed data from 331 683 UK Biobank participants without cardiovascular disease at baseline (2006-2010) and replicated our main findings in an independent population from 3 prospective cohort studies comprising 271 329 community-dwelling participants from Finland (baseline 1986-2005). Cardiovascular risk factors were measured at baseline. We diagnosed infectious diseases (the exposure) and incident major cardiovascular events after infections, defined as myocardial infarction, cardiac death, or fatal or nonfatal stroke (the outcome) from linkage of participants to hospital and death registers. We computed adjusted hazard ratios (HRs) and 95% CIs for infectious diseases as short- and long-term risk factors for incident major cardiovascular events. We also calculated population-attributable fractions for long-term risk. RESULTS: In the UK Biobank (mean follow-up, 11.6 years), 54 434 participants were hospitalized for an infection, and 11 649 had an incident major cardiovascular event at follow-up. Relative to participants with no record of infectious disease, those who were hospitalized experienced increased risk of major cardiovascular events, largely irrespective of the type of infection. This association was strongest during the first month after infection (HR, 7.87 [95% CI, 6.36-9.73]), but remained elevated during the entire follow-up (HR, 1.47 [95% CI, 1.40-1.54]). The findings were similar in the replication cohort (HR, 7.64 [95% CI, 5.82-10.03] during the first month; HR, 1.41 [95% CI, 1.34-1.48] during mean follow-up of 19.2 years). After controlling for traditional cardiovascular risk factors, the population-attributable fraction for severe infections and major cardiovascular events was 4.4% in the UK Biobank and 6.1% in the replication cohort. CONCLUSIONS: Infections severe enough to require hospital treatment were associated with increased risks for major cardiovascular disease events immediately after hospitalization. A small excess risk was also observed in the long-term, but residual confounding cannot be excluded.

Shift work with and without night shifts and breast cancer risk in a cohort study from Finland.

OBJECTIVES: To examine the association of shift work with and without night work with breast cancer among women in the public sector. METHODS: Using the Finnish Public Sector cohort study (N=33 359, mean age of 40.6 years at baseline), we investigated the associations of shift work and potential confounders with incident breast cancer. Exposure to permanent day work or shift work was defined from first two consecutive surveys from 2000, 2004, 2008 or 2012 and past information on exposure in a subcohort (n=20 786). Incident cases of breast cancer (n=1129) were retrieved from the National Cancer Register and the cohort members were followed to the end of 2016. HR and 95% CI from Cox proportional hazard regression models were calculated. RESULTS: Shift work with and without night shifts was not overall associated with breast cancer. When stratified according to age, both shift work without nights (HR 2.01, 95% CI 1.12 to 3.60) and shift work with nights (OR 2.05, 95% CI 1.04 to 4.01) were associated with an increased risk after a period of 10 years or more follow-up among women aged 50 years or older, when adjusted for age, socioeconomic status, children, smoking, alcohol and body mass index. In a subgroup with past information on exposure to shift work, the increased risk by longer exposure to shift work was not significant. CONCLUSIONS: This study provides support for an increased risk of breast cancer among elderly shift workers. However, insufficient information on exposure and intensity of night work may attenuate the risk estimates.

The association between the use of shift schedule evaluation tool with ergonomics recommendations and occupational injuries: A 4-year prospective cohort study among healthcare workers.

OBJECTIVE: This study aimed to find out whether utilizing a shift schedule evaluation tool with ergonomics recommendations for working hours has favorable effects on the incidence of occupational injuries. METHODS: This 4-year prospective cohort study (2015-2018) consisted of a dynamic cohort of healthcare shift workers (N=29 237) from ten hospital districts and six cities in Finland. Working hour characteristics and occupational injuries were measured with daily registry data. Multilevel generalized linear model was used for the analyses, and the estimates were controlled for hierarchical structure of the data and confounders. RESULTS: Ward heads of the cities used the shift schedule evaluation tool 3.2 times more often than ward heads of the hospital districts. Overall incidence of workplace and commuting injuries did not differ between users and non-users of the evaluation tool. The incidence of dislocations, sprains, and strains was lower in the users than non-users [adjusted odds ratio (OR) 0.88, 95% confidence interval (CI) 0.78-0.99]. Approximately 13% of this association was mediated by increase in realized shift wishes and 10% by increase in single days off. In subgroup analyses, the incidence of workplace injury (OR 0.83, 95% CI 0.69-0.99), and among types of injuries, the incidence of dislocations, sprains, and strains (OR 0.69, 95% CI 0.55-0.85) and falling, slipping, tripping, or overturning (OR 0.75, 95% CI 0.58-0.99) were lower in users than non-users among employees of the cities, but no association was found among employees of the hospital districts. CONCLUSION: The use of ergonomics recommendations for working hours is associated with a reduced risk of occupational injuries.

The Time-Varying Effect of Participatory Shift Scheduling on Working Hour Characteristics and Sickness Absence: Evidence from a Quasi-Experiment in Hospitals.

Participatory shift scheduling for irregular working hours can influence shift schedules and sickness absence. We investigated the effects of using participatory shift scheduling and shift schedule evaluation tools on working hour characteristics and sickness absence. We utilized a panel data for 2015-2019 with 16,557 hospital employees (6143 in the intervention and 10,345 in the control group). Difference-in-differences regression with ward-level clustered standard errors was used to estimate the average treatment effect on the treated coefficients relative to timing of the intervention with 95% confidence intervals (CI). Using participatory scheduling tool increased long working hours and weekend work and had delayed effects on the short (1-3 days) sickness absences. Increased effects were observed: 0.2 [95% CI 0.0-0.4] days for the second, and 0.8 [95% CI 0.5-1.0] for the third year after the onset of intervention. An average increase of 0.5 [95% CI 0.1-0.9] episodes on all sickness absence episodes was observed for the third year. Using the shift schedule evaluation tool with the participatory shift scheduling tool attenuated the adverse effects. To conclude, participatory shift scheduling increased some potentially harmful working hour characteristics but its effects on sickness absence were negligible, and further attenuated by using the shift schedule evaluation tool.

Concurrent trajectories of self-rated health and working hour patterns in health care shift workers: A longitudinal analysis with 8-year follow-up.

Background: The association between health and working hours is hypothesized to be reciprocal, but few longitudinal studies have examined changes in both health and working hour patterns over time. We examined combined trajectories of self-related health and two working hour patterns (working <35 h/week and working night shifts) and the extent to which these trajectories were predicted by employees' lifestyle and mental health. Methods: Participants of this cohort study with a 8-year follow-up were 5,947 health care shift workers. We linked self-reports of health from three repeated surveys with objective pay-roll based data on working hours. Using group-based multi-trajectory analysis we identified concurrent trajectories for self-rated health and working hour patterns. We examined their associations with baseline lifestyle-related factors (smoking, at-risk alcohol use, obesity, and physical inactivity) and mental health (sleep problems and psychological distress) using multinomial regression analysis. Results: Three combined trajectories of self-rated health and working <35 h/week and four combined trajectories of self-rated health and night work were identified. Unhealthy lifestyle and poor mental health were associated with trajectories of moderate and declining health. Sleep problems were linked with working <35 h/week. Younger age and good mental health were associated with a combined trajectory of good health and continued night shift work. Conclusion: Trajectories of suboptimal and declining health are associated with trajectories of reducing working hours and leaving night work, and are more common in employees with unhealthy lifestyle, sleep problems, and psychological distress.

A Longitudinal Study on Trajectories of Night Work and Sickness Absence among Hospital Employees.

This study aimed to investigate trajectories of night shift work in irregular shift work across a 12-year follow-up among hospital employees with and without sickness absence (SA). The payroll-based register data of one hospital district in Finland included objective working hours and SA from 2008 to 2019. The number of night shifts per year was used in group-based trajectory modeling (GBTM). The results indicate that, among those who had any sickness absence episodes, the amount of night work decreased prior to the first SA. In general, trajectories of night shift work varied from stably high to low-but-increasing trajectories in terms of the number of shifts. However, a group with decreasing pattern of night work was identified only among those with sickness absence episodes but not among those without such episodes. To conclude, the identified trajectories of night work with or without sickness absences may indicate that, among those with sickness absence episodes, night work was reduced due to increasing health problems. Hence, the hospital employees working night shifts are likely a selected population because the employees who work at night are supposed to be healthier than those not opting for night work.

Hospital physicians´ working hour characteristics and sleep quality: a cross-sectional analysis of realized working hour and survey data.

BACKGROUND: Hospital physicians' work includes on-call duties to provide 24/7 health care. Previous studies using self-reported survey data have associated long working hours and on-call work with sleep difficulties. To reduce recall bias, we complemented survey data with payroll-based objective data to study whether hospital physicians' realized working hours are associated with sleep. METHODS: The study was nested within the Finnish Public Sector study. We used survey data on 728 hospital physicians (mean age 43.4 years, 62% females) from 2015 linked to realized daily working hour data from 3 months preceding the survey. The associations of working hour characteristics with sleep quantity and quality were studied with multinomial logistic regression analysis adjusted for demographics, overall stressfulness of life situation, control over scheduling of shifts, and hospital district. RESULTS: One fourth (26%) of the participants reported short (≤6.5 h) average sleep duration. Frequent night work (> 6 shifts/91 days) was associated with short sleep (OR 1.87 95%CI 1.23-2.83) compared to no night work. Approximately one third (32%) of the physicians reported insufficient sleep. Physicians with long weekly working hours (> 48 hours) had higher odds for insufficient sleep (OR 1.78 95%CI 1.15-2.76) than physicians with short weekly working hours (< 40 hours). Insufficient sleep was also associated with frequent on-call duties (> 12 shifts/3 months OR 2.00 95%CI 1.08-3.72), frequent night work (OR 1.60 95%CI 1.09-2.37), and frequent short shift intervals (≤11 hours; > 12 times/3 months OR 1.65 95%CI 1.01-2.69) compared to not having these working hour characteristics. Nearly half of the physicians (48%) reported at least one sleep difficulty at least two times a week and frequent night work increased odds for difficulties in initiating sleep (OR 2.43 95%CI 1.04-5.69). Otherwise sleep difficulties were not associated with the studied working hour characteristics. CONCLUSION: We used realized working hour data to strengthen the evidence on on-call work and sleep quality and our results advice to limit the frequency of night work, on-call shifts, short shift intervals and long weekly working hours to promote hospital physicians' sufficient sleep.

National recommendations for shift scheduling in healthcare: A 5-year prospective cohort study on working hour characteristics.

BACKGROUND: National recommendations to decrease the health and safety risks of working hours are often given based on the increasing knowledge of the associations between working hour characteristics and health. However, the utilization of the recommendations, and their potential to change the actual working time patterns in healthcare sector is unclear. OBJECTIVE: We investigated the extent to which the national recommendations are utilized in shift scheduling, when they are integrated as a shift schedule evaluation tool into the shift scheduling software. Second, we examined whether the use of the tool results in changes that are in line with the recommendations. DESIGN: A prospective cohort study with a 5-year follow-up. PARTICIPANTS: A total of 36,663 healthcare workers with objective data on daily working hours in 10 hospital districts and 6 large cities. METHODS: We investigated the annual use of the evaluation tool, and the effects of using the tool on annual changes in working hour characteristics from 2015 to 2019 while adjusting for the hierarchical structure of the data, age, sex, shift work, night work, work contract days and the type of shift scheduling software. Utilizing intention-to-treat principle, the employees in wards using the tool were compared to non-users by multi-level generalized linear models. RESULTS: Continuous use (during at least 10 scheduling periods) of the evaluation tool increased from 2% in 2015 to 20% in 2018. In the fully adjusted model, the use of the evaluation tool was associated with the decrease of >6 consecutive workdays (OR 0.73, 95% CI 0.66, 0.81), >4 consecutive night shifts (OR 0.86, 95% CI 0.77, 0.95), and proportion of <11-hour shift intervals (difference 0.63, 95% CI 0.43, 0.83). The proportion of single days off (difference 0.33, 95% CI 0.15, 0.51), and >40-hour work weeks (OR 1.16, 95% CI 1.10, 1.22), as well as the proportion of ≥12-hour work shifts (OR 1.22, 95% CI 1.07, 1.38) increased. Realized shift wishes decreased (difference 0.76, 95% CI 0.12, 1.41). The use of the tool was associated with more frequent changes towards the recommendations in the cities compared to the hospital districts, and among the older age groups compared to the ≤30-year-old employees. CONCLUSIONS: National recommendations embedded in the shift schedule evaluation tool were used continuously by one fifth of the employees, and were associated with several, albeit modest changes towards the given recommendations. Changes in working hour characteristics depended on organization indicating for differences in the implementation of the recommendations. TWEETABLE ABSTRACT: The national recommendations for safer working hour characteristics embedded in a shift schedule evaluation tool are associated with several, albeit modest changes in working hour characteristics.

Association of alcohol use with years lived without major chronic diseases: A multicohort study from the IPD-Work consortium and UK Biobank.

Background: Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use. Methods: In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines - non-drinking (never or former drinkers); moderate consumption (1-14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study. Findings: During 1·73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29·3 (95%CI 27·9-30·8) years, women 29·8 (29·2-30·4) years)] and moderate drinkers with no binge drinking habit [men 28·7 (28·4-29·0) years, women 29·6 (29·4-29·7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23·4 (20·9-26·0) years, women 24·0 (21·4-26·5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26·0 (25·3-26·8), women 27·5 (26·4-28·5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1·5 years or less. Interpretation: Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller. Funding: Medical Research Council, National Institute on Aging, NordForsk, Academy of Finland, Finnish Work Environment Fund.

Working hours, on-call shifts, and risk of occupational injuries among hospital physicians: A case-crossover study.

OBJECTIVE: To investigate the association of hospital physicians' working hours and on-call shifts with the risk of occupational injuries. METHODS: In this nested cohort study of 556 Finnish hospital physicians, we linked electronic records from working-hour and on-call duty payroll data to occupational injury data obtained from the Finnish Workers' Compensation Center for the period 2005-2019. We used a case-crossover design with matched intervals for a 7-day 'case window' immediately prior to occupational injury and a 'control window' 7 days prior to the beginning of the case window, and analyzed their associations using conditional logistic regression models. RESULTS: We noted 556 occupational injuries, 281 at the workplace and 275 while commuting. Having three to four long (>12 h) work shifts on the preceding 7 days was associated with a higher probability of an occupational injury (odds ratio [OR] 2.14, 95% confidence interval [CI] 1.11, 4.09), and the OR for three to four on-call shifts was 3.54 (95%CI 2.11, 5.92) in comparison to having none of these work shift types. A higher number of several consecutive working days was associated with a higher probability of injury in a dose-response manner. Moreover, increasing weekly working hours was associated with an increased likelihood of injury (OR 1.03, 95%CI 1.01, 1.04), whereas the number of normal (≤12 h) work shifts reduced this likelihood (OR 0.79, 95%CI 0.64, 0.98). CONCLUSIONS: Our findings suggest that accumulated working-hour load, as opposed to single, very long (>24 h) work shifts, may increase the risk of occupational injury among hospital physicians.

Working hour characteristics in the Finnish retail sector - a registry study on objective working hour data.

Earlier research is lacking on the prevalence and nature of objective working hour characteristics in the retail sector. We developed a codification in the retail sector and investigated differences in objective working hour characteristics by part-time work, sex and age. The payroll-based registry data of objective working hours consisted >12,000 employees of the retail sector in Finland for 2018-2020. Descriptive statistics for means, standard deviations (SD) and range of annual working hour characteristics were calculated, the differences in means were tested, partially based on the protocol established for health care sector. The final sample had 60-63% part-time employees and 23% men. Morning shifts were more frequent (48-51%) among full-time employees compared to 27-30% of the part-time employees. Evening shifts, 43-46%, were frequent among part-time employees vs. 26% in full-time. No sex differences were detected, and age group differences only among part-time employees. To conclude, the codification for registry-based working hour data enables us to identify individual differences in working hour characteristics. The working hour characteristics differed between part-time and full-time employees, not between sexes, whereas age differences were minor and among part-time employees. The codification could be used in studies of the retail sector in association with health and wellbeing.

Association of working hour characteristics and on-call work with risk of short sickness absence among hospital physicians: A longitudinal cohort study.

Physicians often work long hours and on-call shifts, which may expose them to circadian misalignment and negative health outcomes. However, few studies have examined whether these working hour characteristics, ascertained using objective working hour records, are associated with the physicians' risk of sickness absence. We investigated the associations of 14 characteristics of payroll-based working hours and on-call work with the risk of short sickness absence among hospital physicians. In this cohort study, 2845 physicians from six Finnish hospital districts were linked to electronic payroll-based records of daily working hours, on-call duty and short (1-3 days) sickness absence between 2005 and 2019. A case-crossover design was applied using conditional logistic regression with the 28 day case and control windows to estimate odds ratios (ORs) and 95% confidence intervals (CI) for short sickness absence. After controlling for weekly working hours and the number of normal (≤12 h) shifts, a higher number of long (>12 h) shifts (ORs for ≥5 versus none: 2.54, 95% CI 1.68-3.84), very long (>24 h) shifts (ORs for ≥5 versus none: 2.62, 95%CI 1.61-4.27), and on-call shifts (OR for ≥5 versus none: 2.15, 95% CI 1.44-3.21) and a higher number of short (<11 h) shift intervals (OR for ≥5 versus none: 12.61, 95% CI 8.88-17.90) were all associated with the increased risk of short sickness absence. These associations did not differ between male and female physicians or between age groups. To conclude, the findings from objective working hour records show that long work shifts, on-call shifts and short shift intervals are related to the risk of short (1-3 days) sickness absence among hospital physicians.

Length of exposure to long working hours and night work and risk of sickness absence: a register-based cohort study.

BACKGROUND: There is inconsistent evidence that long working hours and night work are risk factors for sickness absence, but few studies have considered variation in the length of exposure time window as a potential source of mixed findings. We examined whether the association of long working hours and night work with sickness absence is dependent on the length of exposure to the working hour characteristics. METHODS: We analysed records of working hours, night work and sickness absence for a cohort of 9226 employees in one hospital district in Finland between 2008 and 2019. The exposure time windows ranged from 10 to 180 days, and we used Cox's proportional hazards models with time-dependent exposures to analyse the associations between working-hour characteristics and subsequent sickness absence. RESULTS: Longer working hours for a period of 10 to 30 days was not associated with the risk of sickness absence whereas longer working hours for a period of 40 to 180 days was associated with a lower risk of sickness absence. Irrespective of exposure time window, night work was not associated with sickness absence. CONCLUSIONS: It is important to consider the length of exposure time window when examining associations between long working hours and sickness absence, whereas the association between night work and sickness absence is not similarly sensitive to exposure times.