Long-lasting, excessive stress exposure can have serious health consequences and consequently, to identify potentially harmful consequences, it is important to develop self-report measures of long-lasting stress in everyday life. The complexity of long-lasting excessive stress also raises questions about the efficacy of widely used single-item measures to capture such harmful stress. This study examines the psychometric quality and validity of a brief eight-item scale, measuring long-lasting stress symptoms. Using data from a nationally representative sample, comprising 15,046 working individuals from the 2014 Swedish Longitudinal Occupational Survey of Health (SLOSH), the findings suggest retaining six of the original eight items, loading on two latent factors: ‘long-lasting perceived stress’ and ‘long-lasting emotional stress’. The high correlation between the two factors suggests the potential for a unified measure to address specific research objectives. The subscales demonstrate concurrent validity with well-established stress-related measures. A single-item measure of perceived stress (‘I have days when I feel stressed all the time’) also correlated with the stress-related measures, although the correlation coefficients were slightly weaker.

Aims: Employee-based flexible working hours are increasing, particularly among knowledge workers. Research indicates that women and men use work–time control (WTC; control over time off and daily hours) differently: while men work longer paid hours, women use WTC to counteract work–life interference. In a knowledge-worker sample, we examined associations between WTC and overtime, work–life interference and exhaustion and tested whether gender moderates the mediating role of overtime. Methods: The sample contained 2248 Swedish knowledge workers. Employing hierarchical regression modelling, we examined effects of control over time off/daily hours on subsequent overtime hours, work–life interference and exhaustion in general and in gender-stratified samples. Using conditional process analysis, we tested moderated mediation models. Results: Control over time off was related to less work–life interference (β_men= −0.117; 95% confidence interval (CI): −0.237 to 0.003; β_women= −0.253; 95% CI: −0.386 to −0.120) and lower exhaustion (β_men= −0.199; 95% CI: −0.347 to −0.051; β_women= −0.271; 95% CI: −0.443 to −0.100). For control over daily hours, estimates were close to zero. While men worked more overtime (42 min/week), we could not confirm gender moderating the indirect effect of control over time off/daily hours on work–life interference/exhaustion via overtime. Independent of gender, effects of control over time off on work–life interference were partly explained by working fewer overtime hours. Conclusions: Control over time off was related to lower exhaustion and better work–life balance (in particular for women). We found no evidence for men’s work–life interference increasing with higher WTC owing to working more overtime. Knowledge workers’ control over time off may help prevent work–life interference and burnout.

Objective: This paper discusses the past and present highlights of working hours and health research and identifies key research needs for the future. Method: We analyzed over 220 original articles and reviews on working hours and health in the Scandinavian Journal of Work, Environment & Health published during the last 50 years. Key publications from other journals were also included. Results: The majority of identified articles focussed on the effects of shift and night work, with fewer studying long and reduced working hours and work time control. We observed a transition from small-scale experimental and intensive field studies to large-scale epidemiological studies utilizing precise exposure assessment, reflecting the recent emergence of register -based datasets and the development of analytic methods and alternative study designs for randomized controlled designs. The cumulative findings provide convincing evidence that shift work and long working hours, which are often associated with night work and insufficient recovery, increase the risk of poor sleep and fatigue, sickness absence, occupational injuries, and several chronic health conditions such as cardiovascular diseases and cancer. The observed risks are strongly modified by individual and work -related factors. Conclusions: Although the observed health risks of shift work and long working hours are mostly low or moderate, the widespread prevalence of exposure and the hazardousness of the many associated potential outcomes makes such working time arrangements major occupational health risks. Further research is needed to identify exposure-response associations, especially in relation to the chronic health effects, and to elucidate underlying pathways and effective personalized intervention strategies.

Accelerometers placed on the thigh provide accurate measures of daily physical activity types, postures and sedentary behaviours, over 24 h and across consecutive days. However, the ability to estimate sleep duration or quality from thigh-worn accelerometers is uncertain and has not been evaluated in comparison with the 'gold-standard' measurement of sleep polysomnography. This study aimed to develop an algorithm for sleep estimation using the raw data from a thigh-worn accelerometer and to evaluate it in comparison with polysomnography. The algorithm was developed and optimised on a dataset consisting of 23 single-night polysomnography recordings, collected in a laboratory, from 15 asymptomatic adults. This optimised algorithm was then applied to a separate evaluation dataset, in which, 71 adult males (mean [SD] age 57 [11] years, height 181 [6] cm, weight 82 [13] kg) wore ambulatory polysomnography equipment and a thigh-worn accelerometer, simultaneously, whilst sleeping at home. Compared with polysomnography, the algorithm had a sensitivity of 0.84 and a specificity of 0.55 when estimating sleep periods. Sleep intervals were underestimated by 21 min (130 min, Limits of Agreement Range [LoAR]). Total sleep time was underestimated by 32 min (233 min LoAR). Our results evaluate the performance of a new algorithm for estimating sleep and outline the limitations. Based on these results, we conclude that a single device can provide estimates of the sleep interval and total sleep time with sufficient accuracy for the measurement of daily physical activity, sedentary behaviour, and sleep, on a group level in free-living settings.

This study explores the prevalence of attributed causes of disturbed sleep and the association between stress-disturbed sleep and age, sex, and sleep duration on weekdays as well as weekends in a representative sample. A nationally representative sample (n = 1,128, response rate 72.8%), stratified for sex and age, completed a computer-assisted phone survey that included questions about sleep disturbances and attributed causes. Stress was the main attributed cause of sleep disturbance (35.1%), most frequently attributed by younger women (χ² = 26.5, p < 0.001). Prevalence of stress-disturbed sleep was higher with lower age (B = −0.05, odds ratio (OR) = 0.94, CI = 0.91, 0.98). There was a trend, however, toward a significant interaction between age and sex, with women in the older age-groups more frequently reporting stress-disturbed sleep than older men (B = −0.02, OR = 1.022, CI = 1.003, 1.042). Weekday sleep duration decreased with increased stress-disturbed sleep, with an inverse relationship on weekends except for those reporting stress-disturbed sleep more than 5 days per week (F = 10.5, p < 0.001), who also had the shortest weekend sleep duration. Sleep disturbances were commonly attributed to stress, and more strongly so in women younger than 46 years. Stress-disturbed sleep during weekdays seems to be potentially compensated for with extended sleep on weekends, except for those with continuous stress-disturbed sleep. 

Objective: Sleep is pivotal to health, wellbeing and functioning in daily life, but sleep difficulties are common and may be affected by modifiable qualities in the residential surrounding environment, in terms of greenspace. However, population-based studies on individual-level greenspace and sleep are limited. The objective of the current study was thus to investigate prospective associations between fine-grained individual-level residential greenspace and sleep, and moderating effects of life style (physical activity, work status) and sex, in a nationwide population-based Swedish cohort.

Methods: Participants of the Swedish Longitudinal Occupational Survey of Health (SLOSH)-a population-based sample of adults in Sweden-were studied during 2014-2018 (19,375 individuals; 43,062 observations). Residential greenspace land cover, and coherent green area size, were assessed via high resolution geographic information systems, at 50, 100, 300, 500 and 1000 m buffers around residences. Prospective greenspace and sleep associations were assessed via multilevel general linear models, adjusting for demographic, socioeconomic (individual and neighborhood), life style and urban factors.

Results: Higher greenspace availability in the immediate residential surroundings (50 m and 100 m buffer zones) was associated with less sleep difficulties, even after adjustment for confounders. Greenspace effects were generally greater among non-working individuals. Among the physically active, and among non-working, greenspace and green area size further away from home (300, 500 and 1000 m, i.e. dependent on mobility) were also associated with less sleep difficulties.

Conclusions: Residential greenspace in the immediate residential surroundings is associated with significantly less sleep difficulties. Greenspace further away from home was associated with better sleep especially among the physically active, and non-working individuals. The results highlight the importance of greenspace in the immediate residential-surrounding environment for sleep, and the need to integrate health and environmental policies, urban planning and greening.

Measuring operator fatigue is an important component of fatigue management in transport. To do it in a meaningful and reliable manner, it is essential before actual measurements to (a) define the main purpose of the measurements, (b) identify the target group and setting, and (c) make a plan for utilisation of the measured data. These steps will help one choose the right method(s) for the job. Generally, it is recommended to choose more than one method, for none of the methods available capture all manifestations of fatigue. When measuring operator fatigue in field settings, it is a good idea to have more than one measurement point per duty period and a well-rested reference condition (e.g., day trip) against to which compare the potentially fatiguing condition (e.g., night trip). Finally, sufficient knowledge of the strengths and weaknesses of fatigue measurement methods makes is possible to interpret the results obtained in a correct way and thus draw reliable conclusions from measurements.

Laboratory based sleep deprivation studies demonstrate that lack of sleep impairs well-being and performance ability, but suggest that these effects are mitigated in older adults. Yet, much less is known whether day-to-day variations of sleep have similar consequences in the context of everyday life. This project uses an intensive longitudinal design to investigate the occurrence of day-to-day variations in sleep and their impact on mood and performance in everyday life and to examine whether effects differ between young and older adults. We aim to include 160 young (18–30 years) and 160 older adults (55–75 years) to complete a 21-day experience sampling method (ESM) protocol. During the ESM period, participants are asked to fill in (i) a brief morning questionnaire, (ii) 8 short daytime questionnaires addressing momentary well-being, sleepiness, stress, and mind wandering, followed by a 1 min cognitive task and (iii) a brief evening questionnaire, all delivered via a mobile phone application. Sleep will be measured using self-reports (daily questions) and objectively with wrist actigraphy. The impact of adult age on mean levels and intraindividual variability of sleep will be analyzed using mixed-effects location scale models. The impact of sleep on daily cognitive performance will be analyzed using multilevel linear mixed models. The relationship of sleep to mean values and variability of positive and negative affect in young and older adults will be analyzed using mixed-effects location scale modeling. The overarching purpose of the project is improving the current knowledge on the occurrence of day-to-day variations in sleep and their relationship to performance as well as positive and negative affect in young and older adults.

Importance: Workplace psychosocial resources naturally tend to cluster in some work teams. To inform work-related sleep health promotion interventions, it is important to determine the associations between clustering of workplace resources and sleep disturbances when some resources are high while others are low and to mimic an actual intervention using observational data.

Objective: To examine whether clustering of and changes in workplace psychosocial resources are associated with sleep disturbances among workers.

Design, Setting, and Participants: This population-based cohort study used data from the Swedish Longitudinal Occupational Survey of Health (2012-2018), the Work Environment and Health in Denmark study (2012-2018), and the Finnish Public Sector Study (2008-2014), collected biennially. Statistical analysis was conducted from November 2020 to June 2022.

Exposure: Questionnaires were distributed measuring leadership quality and procedural justice (ie, vertical resources) as well as collaboration culture and coworker support (ie, horizontal resources). Resources were divided into clusters of general low, intermediate vertical and low horizontal, low vertical and high horizontal, intermediate vertical and high horizontal, and general high.

Main Outcomes and Measures: Odds ratios (ORs) and 95% CIs were reported from logistic regression models for the associations between the clustering of resources and concurrent and long-term sleep disturbances. Sleep disturbances were measured by self-administered questionnaires.

Results: The study identified 114 971 participants with 219 982 participant-observations (151 021 [69%] women; mean [SD] age, 48 [10] years). Compared with participants with general low resources, other groups showed a lower prevalence of sleep disturbances, with the lowest observed in the general high group concurrently (OR, 0.38; 95% CI, 0.37-0.40) and longitudinally after 6 years (OR, 0.52; 95% CI, 0.48-0.57). Approximately half of the participants (27 167 participants [53%]) experienced changes in resource clusters within 2 years. Improvements in vertical or horizontal dimensions were associated with reduced odds of persistent sleep disturbances, and the lowest odds of sleep disturbances was found in the group with improvements in both vertical and horizontal dimensions (OR, 0.53; 95% CI, 0.46-0.62). A corresponding dose-response association with sleep disturbances was observed for decline in resources (eg, decline in both dimensions: OR, 1.74; 95% CI, 1.54-1.97).

Conclusions and Relevance: In this cohort study of workplace psychosocial resources and sleep disturbances, clustering of favorable resources was associated with a lower risk of sleep disturbances.

Objective

The prognosis of coronary artery disease (CAD) is related to its severity and cardiovascular risk factors in both sexes. In women, social isolation, marital stress, sedentary lifestyle and depression predicted CAD progression and outcome within 3 to 5 years. We hypothesised that these behavioral factors would still be associated with all-cause mortality in female patients after 26 years.

Methods

We examined 292 patients with CAD and 300 healthy controls (mean age of 56 ± 7 y) within the Fem-Cor-Risk-Study at baseline. Their cardiac, behavioral, and psychosocial risk profiles, exercise, smoking, and dietary habits were assessed using standardized procedures. Physiological characteristics included a full lipid profile, the coagulation cascade and autonomic dysfunction (heart rate variability, HRV). A new exploratory analysis using machine-learning algorithms compared the effects of social and behavioral mechanisms with standard risk factors. Results: All-cause mortality records were completed in 286 (97.9%) patients and 299 (99.7%) healthy women. During a median follow-up of 26 years, 158 (55.2%) patients and 101 (33.9%) matched healthy controls died. The annualized mortality rate was 2.1% and 1.3%, respectively. After controlling for all available confounders, behavioral predictors of survival in patients were social integration (HR 0.99, 95% CI 0.99–1.0) and physical activity (HR 0.54, 95% CI 0.37–0.79). Smoking acted as a predictor of all-cause mortality (HR 1.56, 95% CI 1.03–2.36). Among healthy women, moderate physical activity (HR 0.42, 95% CI 0.24–0.74) and complete HRV recordings (≥50%) were found to be significant predictors of survival.

Conclusions

CAD patients with adequate social integration, who do not smoke and are physically active, have a favorable long-term prognosis. The exact survival times confirm that behavioral risk factors are associated with all-cause mortality in female CAD patients and healthy controls.