Studies on the association between job satisfaction and depression have often been reported. However, no study has examined how job satisfaction impacts depression while considering satisfaction with other aspects of life. In this study, we evaluated the effect of job satisfaction on depression after adjusting for satisfaction with other domains of life.

We used data from the 16th wave of the Korean Welfare Panel Study. A total of 3568 current employees without depression who completed a survey were included. Depression was measured using the abbreviated version of the CES-D scale. Various types of satisfaction, including job satisfaction, were measured using single-item questions and a 5-point Likert scale. The association between job satisfaction and depression after considering satisfaction with other life domains was analyzed using a multiple logistic regression model.

Crude models showed a significant association between job satisfaction and depression in males (odds ratio [OR]: 7.90; 95% confidence interval [CI]: 4.11–15.23) and females (OR: 7.12; 95% CI: 4.40–11.50). When adjusted for sociodemographic factors, health-related factors, and work-related factors, the association remained significant in males (OR: 6.20; 95% CI: 3.10–12.41) and females (OR: 6.28; 95% confidence interval (CI): 3.79–10.40). However, when satisfaction with other life domains was included, the association remained significant only in females (OR: 3.55; 95% CI: 1.93–6.50).

This study shows an association between job satisfaction and depression in Korean employees. However, when satisfaction with other life domains was considered, this association remained significant only in women. Regular screening of job satisfaction should be considered as a means of preventing and managing depression among female employees.

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.