Health Inequalities Among Korean Employees

Choi, Eunsuk

doi:10.1016/j.shaw.2017.03.002

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…The aforementioned women who work mainly in the sales and service sectors, were often referred to as “pink collar workers”. Pink collar workers and unskilled workers both have poorer physical and mental health, than those who are not in this category [ 37 , 38 , 39 ]. In addition, service sector workers also have long working hours.…”

Section: Discussionmentioning

confidence: 99%

The Change of Self-Rated Health According to Working Hours for Two Years by Gender

Ryu

Yoon

Kim

et al. 2018

IJERPH

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Objective: The aim of this study was to confirm the association between working hours and self-rated health, and to find the degree of changes in health level by working hours according to gender. Methods: This study was based on the 929 workers (571 men and 358 women) from the Korean Labor and Income Panel Study during 2004–2006. To minimize the healthy worker effects, the study subjects included only those who did not have any chronic diseases, and who answered their health status as “moderate” or above in the baseline. Logistic regression analysis was used to confirm the associations between working hours and self-rated health. Results: In men, working hours per week of 47–52 h, 53–68 h, and >68 h were associated with 1.2, 1.3, and 1.1 times increases, respectively, in the odds ratio on worsened self-rated health, compared with the reference group (40–46 h). On the other hand, the risks were 1.0, 2.2, and 2.6 times increases in women. However, the results were different according to gender in the group with less than 40 h. The men with less than 40 h had a 0.9 times odds ratio on worsened self-rated health. For the women with less than 40 h, the odds ratio on self-rated health was 5.4 times higher than the reference group. Conclusions: Working more than 52 h per week had a negative effect on health, regardless of gender. However, in the group with less than 40 h, the negative association between working hours and self-rated health were shown only in women. Health outcomes due to working hours may differ by gender. Therefore, further studies are needed to explore the causes of these results.

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Section: Discussionmentioning

confidence: 99%

The Change of Self-Rated Health According to Working Hours for Two Years by Gender

Ryu

Yoon

Kim

et al. 2018

IJERPH

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“… 17 According to a study on the health inequality of Korean wage workers, female workers reported a higher risk of work-related musculoskeletal disease than male workers. 18 In 2006, the World Health Organization published an extensive list of recommendations on sex-disaggregated data collection and analysis for occupational exposures, diseases, and injuries. 19 In the ILO report, 20 the lack of sex-disaggregated data makes it more difficult to identify hazards, risks, and types of occupational injuries and diseases that specifically affect each gender, thereby impeding the development of effective OSH policies.…”

Section: Discussionmentioning

confidence: 99%

Distribution of Korean safety and health professionals from the perspective of gender equality

Park

Choi

Chung

et al. 2022

Ann Occup Environ Med

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Background Gender equality in the workplace remains a challenge. This study aimed to investigate the gender gap of human resources in the field of occupational safety and health (OSH) in Korea. Methods Several national statistical data that can confirm the gender distribution of personnel in the OSH sector were reviewed. The gender distribution of industrial technical manpower statistics, professional certificate holders in the OSH field, and the status of the appointment of safety and health managers by industry was analyzed. Results The distribution of professionals in the OSH sector in Korea had a large gender gap with a small number of women. In particular, the proportion of women in the safety field was lower than that in the health field. In the younger age group, while the proportion of women is increasing, the gender gap tends to decrease. Conclusions Few data are available to understand the gender-related aspects of OSH professions. Nevertheless, our results provide basic information for initiating a discussion on the necessity of establishing gender-sensitive culture and policies in the OSH sector.

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“…An amazing feature of machine learning is its strong predictive ability. Machine learning has been widely used in various fields [5][6][7][8][9][10][11][12][13][14][15][16]. Support vector machine regression is originally proposed by Vapnik in 1995, and were widely used in all walks of life.…”

Section: Introductionmentioning

confidence: 99%

Predicting China's Economic Running State Using Machine Learning

Luo

2018

MATEC Web Conf.

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China's business index of macro-economic includes early warning index, coincidence index, leading index and lagging index, among which early warning index reflects the economic running state. However, obtaining these indexes is a complex and daunting task. To simplify the task, this article mainly explores how to use machine learning algorithms including multiple linear regression (MLR), support vector machine regression (SVM), random forest (RF), artificial neural network (ANN) and extreme learning machine (ELM) to accurately predict early warning index. Finally, it can be found that the warning index can be well predicted by above machine learning algorithms with coincidence index, leading index and lagging index to be variables, furthermore, extreme learning machine and random forest are superior to other methods.

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Health Inequalities Among Korean Employees

Cited by 5 publications

References 30 publications

The Change of Self-Rated Health According to Working Hours for Two Years by Gender

The Change of Self-Rated Health According to Working Hours for Two Years by Gender

Distribution of Korean safety and health professionals from the perspective of gender equality

Predicting China's Economic Running State Using Machine Learning

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