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.

The aim of this study is to investigate the relationship between fatigue and occupational injury.

This study was conducted at a university hospital in 2014 and 2015. In 2014, the fatigue severity scale (FSS) was used to evaluate workers' fatigue levels. Later, when the same workers were examined in 2015, a questionnaire survey was conducted to determine whether they had experienced absences or treatment for work-related accidents. The χ² test was used to analyse the relationship between demographic characteristics, fatigue levels, and occupational injuries. After controlling for confounders, a logistic regression analysis was performed to calculate the odds ratios (ORs).

In 2014, 19,218 workers were screened during health examination and their fatigue level were evaluated using FSS questionnaires. in 2015, workers' occupational injury was evaluated. In result, men in the moderate- and high-fatigue groups, after adjusting for age, smoking and drinking habits, chronic diseases, and occupational factors such as size of company industrial classification and type of work (shift or non-shift), adjusted ORs for hospital treatment due to occupational injury were 1.76 (95% confidence interval [CI]: 1.39–2.24) and 2.61 (95% CI:1.68–4.06), respectively. Among men in the medium- and high-fatigue groups, the adjusted ORs for absence due to occupational injury were 2.06 (95% CI: 1.52–2.80) and 3.65 (95% CI: 2.20–6.05), respectively. No significant association was observed between fatigue and occupational injury in women.

Male workers with high fatigue levels have a higher risk of experiencing work injuries. This study suggests that active intervention be considered to prevent injuries in workers with high scores on workplace fatigue evaluation scales.

The relationship between smoking status or second-hand smoking and occupational injuries has been the subject of considerable study, but few have studied the relationship between nicotine dependence and occupational injuries. The objective of this study was to investigate the relationship between nicotine dependence and occupational injury among employees at a range of Korean companies.

Initially, the personal and occupational characteristics and nicotine dependences of workers were measured, and 12 months later a survey was used to determine whether subjects had experienced any occupational injury. This study was conducted in several workplaces on 6,893 male workers in manufacturing and service industries that received health screening at Inha University Hospital in Incheon.

The adjusted odds ratios (ORs) of occupational injury in the low, moderate, and high nicotine dependence groups were 1.38 (95% confidence interval [CI]: 1.04–1.84), 1.52 (95% CI: 1.10–2.10), and 1.71 (95% CI: 0.92–3.19), respectively. For smokers only, adjusted ORs tended to increase linearly (p for trend < 0.05). When only smokers were included, analysis of continuous FTND (Fagerstrom Test of Nicotine Dependence) scores showed that adjusted OR increased by 1.10 (95% CI: 1.03–1.19) per FTND point. After stratifying the data by working type and working hours per week, the non-shift work group maintained this relationship (OR: 1.13, 95% CI: 1.04–1.24) and OR was higher in the group that works more than 60 hours per week with FTND score as a continuous variable (OR: 1.24, 95% CI: 1.07–1.44).

The study shows nicotine dependency might affect occupational injury. From a short-term perspective, addressing worker's nicotine dependence by giving an adequate break time or smoking area might reduce work-related injuries.

Dependent self-employment is precarious employment, which can be vulnerable to mental health problems. This study aimed to investigate the association of dependent self-employment with depression, anxiety, and sleep disorder in South Korea.

This study used data from the Fourth Korean Working Conditions Survey and included 32,691 paid workers. Dependent self-employment and self-reported depression/anxiety, and sleep disorder were investigated using a questionnaire. Logistic regression analysis was performed to investigate the association between dependent self-employment and mental health problems.

Of the 32,691 paid workers, 2,371 (7.3%) were dependent self-employed workers. The odds ratio (OR) of dependent self-employment for self-reported depression/anxiety was 1.78 (95% confidence interval [CI]: 1.29–2.45) and the OR of dependent self-employment for self-reported sleep disorder was 1.26 (95% CI: 1.01–1.59) compared to other paid workers.

Dependent self-employment is related to an increased risk of self-reported depression/anxiety and sleep disorder in South Korea.

Prospective studies on occupational stress and depression among Korean workers are scarce. This study aimed to investigate the causal relationship between changes in occupational stress and the presence of depression.

This study analyzed data from a survey conducted with workers in a large Korean company (2015–2016). Occupational stress was measured using the Korean Occupational Stress Scale, and depression was screened using the WHO-5 Well-being Index. The levels of occupational stress were grouped in quartiles based on subjects’ occupational stress scores in 2015, and changes in occupational stress were measured using the score changes between the 2015 and 2016 surveys. Subjects were divided into four groups according to the presence or absence of depression in 2015 and 2016: a non-depressed group whose mental health did not change, a non-depressed group whose mental health deteriorated, a depressed group that continued to be depressed, and a depressed group whose symptoms of depression were alleviated. Logistic regression analysis was used to calculate the odds ratios (ORs) and confidence intervals (CIs) of the subjects’ deterioration in mood or alleviation of depression by occupational stress levels and changes.

The OR for developing depressive symptoms was 2.51 (95% CI 1.46–4.33) and 2.73 (95% CI 1.39–5.36) in the third and the fourth quartiles of occupational stress, respectively, compared to the first quartile. When the occupational stress score increased by 1 point, the OR for increasing depressive symptoms was 1.07 (95% CI 1.04–1.10). There was no significant difference in the alleviation of depressive symptoms between the groups by level of occupational stress. However, when the occupational stress score decreased by 1 point, the OR for alleviating depressive symptoms was 1.08 (95% CI 1.05–1.11).

The results showed that increased occupational stress increased the presence of depressive symptoms, and that reduced occupational stress suppressed the development of depressive symptoms. More attention should be paid to stress management among workers.