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.

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.

Most of the studies that have examined the association between the sub-factors of occupational stress and depressive symptoms have used cross-sectional data. However, our study has longitudinally measured the occupational stress and depressive symptoms of Korean workers of a semiconductor manufacturing company across six years to intending to investigate the associations between the sub-factors of occupational stress and depressive symptoms using longitudinal data.

Data collected from the workers of a semiconductor manufacturing company. Out of 1,013 recruited workers, 405 (40.0%) completed the survey questionnaires at 3 and 6-year follow-ups. Occupational stress was measured using a shorter version of the Korean Occupational Stress Scale (KOSS), whereas depressive symptoms were assessed using the Korean version of the Center for Epidemiological Studies-Depressive Symptoms Scale (CES-D). The data of male and female participants independently analyzed. Longitudinal associations were analyzed using panel data analysis with fixed effects.

In panel data analysis with fixed effects, job insecurity (B = 0.048, p-value = 0.004) was associated with depressive symptoms among male workers. In female workers, inadequate social support (B = 0.080, p-value < 0.001), job insecurity (B = 0.039, p-value = 0.004), lack of reward (B = 0.059, p-value = 0.004) and discomfort in occupational climate (B = 0.074, p-value < 0.001) were associated with depressive symptoms among female workers.

Temporal changes in the sub-factors of occupational stress were associated with changes in depressive symptoms within the same period. There was a gender difference in occupational stress sub-factors related to depressive symptoms.

The global labor market is moving towards increasing job instability. Relatively few studies have examined the relationship between precarious employment and subjective well-being using quantitative scales. We evaluated the association between wage workers' employment status and their subjective well-being through the Cantril ladder scale using Korean Welfare Panel Survey data (KOWEPS).

This study used KOWEPS data. A total of 4,423 wage workers were divided into permanently employed workers, temporarily employed workers and daily employed workers. The relationship between precarious employment and subjective well-being was analyzed by multiple linear regression adjusted for potential confounding factors.

The more unstable the employment status, the lower the subjective well-being, which can be expressed by the Cantril ladder scale. The mean score of both temporarily employed and daily employed workers were statistically significantly lower (B = −0.454, p < 0.001; B = −0.994, p < 0.001, respectively) than permanently employed workers. This appeared to be the same when occupational and sociodemographic factors were adjusted (B = −0.153, p = 0.002 for temporarily employed, B = −0.610, p < 0.001 for daily employed).

The more unstable the employment status, the lower the subjective well-being score according to the Cantril ladder scale.

The risk factors for renal cancer include smoking, obesity, hypertension, and exposure to trichloroethylene. Recent studies have shown that low sunlight exposure increases the risk of developing a range of cancers, including renal cancer. Given that most of the daytime is spent at work, a lack of occupational sunlight exposure can be a risk factor for renal cancer. Therefore, this study examined the relationship between occupational sunlight exposure and the incidence of renal cancer.

This was a university hospital-based case-control study on renal cancer. Of the 706 newly diagnosed patients with renal cell carcinoma (RCC), 633 cases were selected; 73 who had no occupational history were excluded. In addition, 633 controls were selected from the general population after 1:1 matching with respect to sex, age (within 5 years), and residential area (constituency-level). Information on sunlight exposure by the occupational group was referred to data from France. To estimate the association between occupational sunlight exposure and the RCC risk, the odds ratios (ORs) were calculated using conditional logistic regression analysis.

Sunlight exposure was divided into quartiles and the risk of RCC was analyzed. The adjusted OR of RCC (OR: 0.664, 95% confidence interval: 0.449–0.983) was significantly lower for the Q4 group than Q1 group but the Q2 and Q3 groups did not show significant results. The risk of RCC tended to decrease with increasing exposure to sunlight (p for trend < 0.028).

Higher occupational sunlight exposure reduces the risk of RCC.