Studies on the association between occupational stress and depression have been frequently reported. However, the cross-sectional designs of studies limited insight into causal associations. In this study, we investigated the longitudinal association between occupational stress and new-onset depression among employees in a single manufacturing plant.

The annual health checkup data of employees at a manufacturing plant in Korea were collected. A total of 1,837 male employees without depression who completed a health checkup during two consecutive years were included. Occupational stress was measured using a short form of the Korea Occupational Stress Scale (KOSS-SF), and depression was assessed using a Patient Health Questionnaire-2. The association between occupational stress change over the two years and newly developed depression was investigated using two logistic regression models.

Across all sub-factors of KOSS-SF, employees who reported increased occupational stress had a higher risk of new-onset depression. Newly developed depression was significantly associated with job demand (odds ratio [OR]: 4.34; 95% confidence interval [CI]: 2.37–7.96), job insecurity (OR: 3.21; 95% CI: 1.89–5.48), occupational climate (OR: 3.18; 95% CI: 1.91–5.31), lack of reward (OR: 2.28; 95% CI: 1.26–4.12), interpersonal conflict (OR: 2.14; 95% CI: 1.18–3.86), insufficient job control (OR: 1.93; 95% CI: 1.05–3.56), and the organizational system (OR: 1.84; 95% CI: 1.01–3.36).

For every sub-factor of the KOSS-SF, occupational stress increase and persistent high stress were associated with the risk of developing new-onset depression. Among the seven sub-factors, job demand had the most significant effect. Our results show that occupational stress should be managed to promote employee mental healthcare.

Although many studies have been conducted on worker fatigue and sickness absence, the association between fatigue and sickness absence is unclear in Korean workers. This study was conducted to investigate the effect of worker fatigue on future sickness absence.

The study was conducted on workers who received medical check-ups at a university hospital for two consecutive years (2014–2015). During check-ups in the first year, the Fatigue Severity Scale (FSS) was used to assess fatigue levels, and during check-ups in the second year, sickness absence was surveyed to determine whether they had been absent from work due to physical or mental illness during previous 12 months. The χ² test was used to analyze relationships between sociodemographic and occupational characteristics, fatigue levels, and sickness absence. Odds ratios (ORs) were calculated by logistic regression analysis controlled for confounding factors.

A total of 12,250 workers were included in the study, and 396 (3.2%) workers experienced more than one day of sickness absence during the study period. Adjusted ORs for sickness absence were 3.35 (95% confidence interval [CI]: 2.64–4.28) in the moderate-fatigue group and 6.87 (95% CI: 4.93–9.57) in the high-fatigue group versus the low-fatigue group. For men in the moderate- and high-fatigue groups, adjusted ORs for sickness absence were 3.40 (95% CI: 2.58–4.48) and 8.94 (95% CI: 6.12–13.07), and for women in the moderate- and high-fatigue groups, adjusted ORs for sickness absence were 2.93 (95% CI: 1.68–5.10) and 3.71 (95% CI: 1.84–7.49), respectively.

Worker fatigue is associated with sickness absence during the following 12 months, and this association appears to be stronger for men than women. These results support the notion that sickness absence can be reduced by evaluating and managing work-related fatigue.

Many studies have been conducted on presenteeism and absenteeism, but the relationship between presenteeism and absenteeism is unclear. This study was undertaken to investigate the effect of presenteeism on future absenteeism.

This study was conducted on non-white collar workers that underwent general health examinations in 2014 and 2015. We asked subjects to fill out a questionnaire about their experiences of presenteeism for the past one year in 2014. In 2015, it was checked whether the same subjects had any experience of absence from work due to injury or disease during the past year. The χ² test was used to analyze relationships between sociodemographic and occupational characteristics, presenteeism, and absence. Odds ratios (ORs) were calculated by logistic regression analysis controlled for confounding factors.

A total of 12,572 workers were included in the study. For workers who experienced presenteeism, the OR for injury absence was 2.705 (95% confidence interval [CI]: 2.044–3.581), and the OR for disease absence was 4.906 (95% CI: 3.996–6.024) after adjusting for sociodemographic and occupational confounding factors. For men that experienced presenteeism, the OR for injury absence was 3.035 (95% CI: 2.258–4.081), and the OR for disease absence was 5.508 (95% CI: 4.340–6.989). For women that experienced presenteeism, the OR for injury absence was 1.322 (95% CI: 0.577–3.028), which was not significant, and the OR for disease absence was 3.629 (95% CI: 2.405–5.475).

This study suggests that presenteeism can influence future absenteeism. The effect of presenteeism may depend on cause of absence. Men who experienced presenteeism showed greater effects on injury and disease absence than women. For women, experience of presenteeism had a significant effect on disease absence but not on injury absence.