Characteristics of long working hours and subsequent psychological and physical responses: JNIOSH cohort study

Work type rather than working hours influences depression: a longitudinal study of middle-aged and older adults in China

BACKGROUND

Research on the impact of working hours and work types on depression among middle-aged and older adults is relatively scarce, especially in China.

METHOD

This study employs a longitudinal research design, utilizing data from the 2011-2020 China Health and Retirement Longitudinal Survey (CHARLS). Depression was measured using the 10-item CESD-10 scale. The Latent Growth Curve Models (LGCM) were used to analyze the impact of working hours on depression, while the Multilevel Generalized Estimating Equation was applied to explore the relationship between work types (including work sector and employment type) and depression.

RESULTS

A total of 3045 Chinese individuals aged ≥45 were studied. Female workers had a higher average depression score (9.6) than males (7.1; P < 0.001). The LGCM model showed no significant impact of initial working hours or their changes on depression levels or rates of change. In terms of work type sector, non-agricultural workers reported lower depression levels (β = -0.92 [-1.14, -0.70]) than agricultural workers. According to work employment type, self-employed individuals had higher depression scores (β = 0.59 [0.38, 0.81]) than employed workers. No significant gender differences were found in the effects of working hours or work type on depression.

CONCLUSION

It is not yet certain whether working hours are significantly associated with depression in middle-aged and older adults in China. However, different work types impact depression. Therefore, the government should pay more attention to the mental health of women, agricultural and self-employed workers.

The heterogeneity of insomnia symptoms for emerging workers in the digital economy: Latent profile and network analysis

Although insomnia symptoms is a common public health issue, few studies pay attention to insomnia symptoms among emerging workers in the digital economy. In this study, a total of 1093 emerging workers were recruited. Latent profile analysis was used to investigate the heterogeneity profiles and the relationship between job characteristics and these profiles. Additionally, core symptoms of insomnia were explored through network analysis. Latent profile analysis identified four insomnia profiles: severe insomnia without daytime dysfunction (8.8%), good sleepers (39.6%), mild insomnia (41.7%), and moderate to severe insomnia (9.9%). Job characteristics (e.g. daily working duration, intensity, and performance measurement system) significantly affected the profiles. Network analysis revealed that four profiles had similar network structures, but the edge and strength were varied. The implication for preventing and intervening insomnia symptoms for emerging workers in the digital economy has been discussed.

Association of long working hours with visceral adiposity index, anthropometric indices, and weight management behaviors: a study of Korean workers

BACKGROUND

Long working hours constitute a significant public health risk. They may induce psychological stress or lead to behavioral changes, which, in turn, can contribute to the development of cardiovascular diseases and metabolic disorders. This study investigated the association of working hours with visceral adiposity index, anthropometric indices, and weight management behaviors.

METHODS

In total, 32 373 adult workers were included in this cross-sectional study. Chinese Visceral Adiposity Index (CVAI), body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and body roundness index (BRI) were assessed. Weight management behaviors over the past year, including exercise, diet control, and medication use, were self-reported. Linear or logistic regression analyses were performed. Regression models were adjusted for sex, age, education level, income level, marital status, occupation type, and survey year.

RESULTS

Among the sample, 19.4% of adults worked for ≥ 55 h per week. Compared to working 35-40 h per week, working ≥ 55 h per week was associated with higher values of 2.57 (95% confidence interval [CI:] 0.95, 4.19) in CVAI, 0.29 (95% CI: 0.14, 0.43) in BMI, 0.67 (95% CI: 0.29, 1.06) in WC, 0.47 (95% CI: 0.24, 0.69) in WHtR, and 0.09 (95% CI: 0.05, 0.14) in BRI, respectively. Working ≥ 55 h per week, in comparison with working 35-40 h per week, was linked to reduced odds of engaging in exercise for weight management (odds ratio: 0.76; 95% CI: 0.70, 0.83).

CONCLUSIONS

Working hours are positively associated with CVAI, anthropometric indices, and a lower intention to engage in exercise for weight management.

Gender differences in the association between long working hours and the onset of depressive symptoms in middle-aged and older workers in Korea: A population-based longitudinal study (2006-2022)

BACKGROUND

Korean society is projected to undergo a rapid aging of its workforce. We explored gender differences in the association between working hours and the onset of depressive symptoms among middle-aged and older workers.

STUDY DESIGN

This study included workers aged ≥45 years from a nationwide panel study with biennial follow-ups (n = 4941, observations = 18,531). Weekly working hours were self-reported. We employed generalized estimating equations with log link function to explore the association between working hours and the onset of depressive symptoms at the two-year follow-up.

MAIN OUTCOME MEASURES

The 10-item version of the Center for Epidemiologic Studies Depression Scale.

RESULTS

The incidence of onset of depressive symptoms was 10.7 % among those working 35-40 h/week and 13.0 % among those working ≥55 h/week. In the overall sample, those working ≥55 h/week had increased risk of the onset of depressive symptoms at the two-year follow-up (risk ratio: 1.12, 95 % confidence interval: 1.01-1.24). There was a positive interaction between being female and working ≥55 h/week in their effect on the risk of onset depressive symptom (P = 0.010). In the gender-stratified analysis, working ≥55 h/week was associated with an increased risk of the onset of depressive symptoms at the two-year follow-up among women (risk ratio: 1.29, 95 % confidence interval: 1.08-1.53); however, we observed no clear associations among men.

CONCLUSION

Long working hours are positively associated with the of onset depressive symptoms in middle-aged and older workers, and this association is pronounced among women.

Wearable EEG-Based Brain-Computer Interface for Stress Monitoring

Detecting stress is important for improving human health and potential, because moderate levels of stress may motivate people towards better performance at cognitive tasks, while chronic stress exposure causes impaired performance and health risks. We propose a Brain-Computer Interface (BCI) system to detect stress in the context of high-pressure work environments. The BCI system includes an electroencephalogram (EEG) headband with dry electrodes and an electrocardiogram (ECG) chest belt. We collected EEG and ECG data from 40 participants during two stressful cognitive tasks: the Cognitive Vigilance Task (CVT), and the Multi-Modal Integration Task (MMIT) we designed. We also recorded self-reported stress levels using the Dundee Stress State Questionnaire (DSSQ). The DSSQ results indicated that performing the MMIT led to significant increases in stress, while performing the CVT did not. Subsequently, we trained two different models to classify stress from non-stress states, one using EEG features, and the other using heart rate variability (HRV) features extracted from the ECG. Our EEG-based model achieved an overall accuracy of 81.0% for MMIT and 77.2% for CVT. However, our HRV-based model only achieved 62.1% accuracy for CVT and 56.0% for MMIT. We conclude that EEG is an effective predictor of stress in the context of stressful cognitive tasks. Our proposed BCI system shows promise in evaluating mental stress in high-pressure work environments, particularly when utilizing an EEG-based BCI.

Long Working Hours, Work-life Imbalance, and Poor Mental Health: A Cross-sectional Mediation Analysis Based on the Sixth Korean Working Conditions Survey, 2020-2021

BACKGROUND

There has been growing concern about the negative mental health impact of long working hours and overwork. Our study examined how work-life imbalance (WLI) could be a mediator between working hours and poor mental well-being.

METHODS

We included 34,968 individuals from a nationwide cross-sectional survey in Korea. Self-reported working hours per week were collected, and mental health was assessed using the World Health Organization (WHO)-5 Well-Being Index. Counterfactual-based mediation models were employed to disentangle the total effects into a direct effect (work hour - poor mental health) and an indirect effect (work hour - WLI - poor mental health).

RESULTS

Out of 34,968 participants, 52.6% worked 35-40 hours/week, 20.0% worked 41-48 hours/week, 11.7% worked 49-54 hours/week, and 15.6% worked ≥55 hours/week. The odds ratios (ORs) of the total impact of working hours on poor mental health were 1.08 (95% confidence interval [CI], 1.01-1.16) for 41-48 hours/week, 1.28 (95% CI, 1.17-1.39) for 49-54 hours/week, and 1.60 (95% CI, 1.48-1.74) for ≥55 hours/week in comparison to 35-40 hours/week. The ORs of the indirect effects were 1.04 (95% CI, 1.03-1.05) for 41-48 hours/week, 1.08 (95% CI, 1.07-1.09) for 49-54 hours/week, and 1.14 (95% CI, 1.12-1.16) for ≥55 hours/week, accounting for 51%, 31%, and 28% of the total effects, respectively.

CONCLUSION

Our findings suggest that WLI can partially mediate the association of long working hours with mental health deterioration. Policy efforts are required to mitigate the adverse mental health effects of overwork.

Impact of Long Working Hours on Mental Health Status in Japan: Evidence from a National Representative Survey

Using the 2010-2019 Comprehensive Survey of Living Conditions (CSLC) conducted in Japan, we examined the impact of long working hours on mental health in Japan while addressing the endogeneity issue arising from non-random selection bias. We assessed the variations in the effects of long working hours on mental health across different groups. The results show that first, individuals working longer hours (55 h or more per week) exhibited a higher likelihood of developing mental illness than those working regular hours or fewer hours. Second, the negative effect of long working hours on mental health is more pronounced among non-regular workers than among regular workers. Third, the effect of long working hours on mental health varies among different demographic groups, with a greater impact observed among women, managers, non-regular workers, employees in small- or large-sized firms, and those in smaller cities compared to their counterparts. Thus, to enhance worker productivity, the Japanese government should address the issue of long working hours to improve employees' mental well-being. Initiatives aimed at promoting work-life balance, family-friendly policies, and measures to ameliorate working conditions are expected to help mitigate the challenges associated with long working hours and mental health issues, especially among non-regular workers.

Working hours of full-time hospital physicians in Japan: a cross-sectional nationwide survey

BACKGROUND

The culture of excessively long overtime work in Japan has not been recently addressed. New legislation on working hours, including a limitation on maximum overtime work for physicians, will be enforced in 2024. This study was performed to elucidate the working conditions of full-time hospital physicians and discuss various policy implications.

METHODS

A facility survey and a physician survey regarding physicians' working conditions were conducted in July 2022. The facility survey was sent to all hospitals in Japan, and the physician survey was sent to all physicians working at half of the hospitals. The physicians were asked to report their working hours from 11 to 17 July 2022. In addition to descriptive statistics, a multivariate logistic regression analysis on the factors that lead to long working hours was conducted.

RESULTS

In total, 11,466 full-time hospital physicians were included in the analysis. Full-time hospital physicians worked 50.1 h per week. They spent 45.6 h (90.9%) at the main hospital and 4.6 h (9.1%) performing side work. They spent 43.8 h (87.5%) on clinical work and 6.3 h (12.5%) on activities outside clinical work, such as research, teaching, and other activities. Neurosurgeons worked the longest hours, followed by surgeons and emergency medicine physicians. In total, 20.4% of physicians were estimated to exceed the annual overtime limit of 960 h, and 3.9% were estimated to exceed the limit of 1860 h. A total of 13.3% and 2.0% exceeded this level only at their primary hospital, after excluding hours performing side work. Logistic regression analysis showed that male, younger age, working at a university hospital, working in clinical areas of practice with long working hours, and undergoing specialty training were associated with long working hours after controlling for other factors.

CONCLUSIONS

With the approaching application of overtime regulations to physicians, a certain reduction in working hours has been observed. However, many physicians still work longer hours than the designated upper limit of overtime. Work reform must be further promoted by streamlining work and task-shifting while securing the functions of university hospitals such as research, education, and supporting healthcare in communities.