Among this group of university students in South Korea, smartphone dependency appeared to be associated with increased anxiety. Standards for smartphone use might help prevent deleterious health effects.

BackgroundProspective 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.MethodsThis 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.ResultsThe 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).ConclusionThe 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.

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BackgroundOn-call work is a form of work that requires the person to work at any time during the on-call period. Thus, on-call work is often regarded as one of the most severe stress factors. This study investigates the associations between on-call work and health problems, injuries.MethodsThis study was based on the 3rd Korean Working Conditions Survey. Total of 29,246 employed workers who had been working for at least 1 year were included. Logistic regression analysis was performed to investigate the association between on-call work and health problems, injuries.ResultsThe odds ratios for on-call workers in terms of physical health problems, psychological health problems, and injuries were 1.33 (95% confidence interval [CI] 1.22-1.44), 1.31 (95% CI 1.08-1.60), and 2.76 (95% CI 2.26-3.37), respectively. Analysis of the detailed symptoms revealed odds ratios in on-call workers of 2.06 for hearing problems (95% CI 1.63-2.62); 1.71 for skin problems (95% CI 1.38-2.12); 1.22 for back pain (95% CI 1.08-1.38); 1.23 for muscular pains in upper limbs (95% CI 1.12-1.34); 1.27 for muscular pains in lower limbs (95% CI 1.15-1.40); 1.46 for headache, eye fatigue (95% CI 1.32-1.60); 1.37 for abdominal pain (95% CI 1.02-1.85); 1.43 for depression or anxiety disorders (95% CI 1.07-1.93); 1.36 for fatigue (95% CI 1.24-1.49); and 1.41 for insomnia and general sleep difficulties (95% CI 1.13-1.76).ConclusionsThe present study found that on-call work results in an increased risk of health problems and injuries. This study is the result of analyses of broad range of the job spectrum in Korean employed workers; thus, future studies are necessary to determine the effects of on-call work in various job groups.

Background Long commuting times have a negative impact on mental health. However, few studies have explored the relationship between commuting time and well-being based on urbanization by region. Our study examines this relationship as well as the effect of regional differences on Korean workers. Methods We used data from the sixth Korean Working Conditions Survey. Commuting time and occupational factors were assessed using a questionnaire, and subjective well-being was assessed using the World Health Organization-5 Well-Being Index. Regions were divided into the cities and the provinces based on Korea’s administrative divisions. Logistic regression analysis was performed to investigate the association between commuting time and well-being. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for well-being were estimated, using participants commuting time of < 20 minutes as a reference group. Results The total number of workers was 29,458 (13,855 men, 15,603 women). We found higher aORs for low well-being among workers with long commuting times (aOR, 1.23; 95% CI, 1.11–1.36 and aOR, 1.28; 95% CI, 1.16–1.42 for 60–79 and ≥ 80 minutes, respectively). When stratified by sex and region, higher aORs for low well-being were found only in the workers who lived in cities. Conclusion Long commuting time was negatively associated with well-being in Korean wage workers living in the cities. Policies for reducing commuting time should be discussed to address the mental health of workers, especially those living in metropolitan cities.

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Background Owing to the coronavirus disease 2019 pandemic, being exposed to work from home and work during nonwork time simultaneously can lead to sleep disturbance; however, their combined effect is unclear. We aimed to investigate the combined effect of work from home and work during nonwork time on sleep disturbance. Methods This study used data from the Sixth Korean Working Condition Survey and included 27,473 paid workers. Logistic regression analysis was conducted to investigate the relationship between work from home, work during nonwork time, and sleep disturbance according to sex. We re-classified participants into 4 groups based on their working from home (No/Yes) and working during nonwork time (No/Yes). The relative excess risk due to interaction was calculated to examine the effect of exposure to both telecommuting and non-regular work hours on sleep disturbance. Results Workers exposed to work from home and work during nonwork time had significantly higher risks of sleep disturbance for all, men, and women workers (OR [95% CI]: 1.71 [1.46–2.02], 1.79 [1.43–2.23], and 1.64 [1.29–2.08] for work from home and 3.04 [2.70–3.42], 3.61 [3.09–4.22], and 2.41 [2.01–2.90] for work during nonwork time, respectively). Compared to those who were not exposed to both factors, when workers had both job factors, the ORs (95% CI) of sleep disturbance for all, men, and women were 3.93 (2.80–5.53), 5.08 (3.21–8.03), and 2.91 (1.74–4.87), respectively. The relative excess risk due to interaction of work from home and work during nonwork time was not significant for sleep disturbance. Conclusions Work from home and work during nonwork time were each associated with sleep disturbance, but the interaction between the two factors on sleep disturbance was not observed in both men and women.