Epidemiology and Health

Original Article

Association between the safety climate and occupational injury in the Korean working population: a cross-sectional study: Jeehee Min, Tae-Won Jang, Hye-Eun Lee, Mo-Yeol Kang, Seong-Sik Cho; Epidemiol Health. 2024;46:e2024082. Published online October 1, 2024; DOI: https://doi.org/10.4178/epih.e2024082

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Abstract Summary PDF Supplementary Material

Abstract

OBJECTIVES
Preventing occupational injuries remains a significant challenge in Korea. A positive safety climate can contribute to reducing workplace injuries. However, the impact of safety climate on preventing occupational injuries among the Korean workforce has not been adequately explored. Therefore, this study aimed to investigate the relationship between the perceived safety climate and occupational injuries within the Korean working population.

METHODS

This study used baseline data from the Korean Work, Sleep, and Health Study (KWSH). The safety climate was measured using the brief version of the Nordic Safety Climate Questionnaire. Occupational injury was determined by whether injuries or accidents had occurred at workplaces in the past year. Logistic regression analysis was performed to examine the association between the safety climate and occupational injury.

RESULTS

Participants who reported an unfavorable workplace safety climate were more likely to experience occupational injuries. Multiple logistic regression analysis revealed that the adjusted odds ratio (OR) for occupational injuries in an unfavorable safety climate was 2.20 (95% confidence interval [CI], 1.38 to 3.51) compared to a favorable safety climate. Specifically, factors such as “not encouraging employees to follow safety rules when on a tight schedule” (OR, 2.02; 95% CI, 1.25 to 3.24) and “not helping each other work safely” (OR, 1.98; 95% CI, 1.17 to 3.25) were significantly associated with occupational injuries.

CONCLUSIONS

An unfavorable safety climate was associated with increased occupational injuries among Korean workers. Improving the safety climate in the workplace may reduce occupational injuries in Korea.

Summary

Korean summary
한국 노동인구집단에서도 안전풍토는 직업성 손상과 관련성이 관찰되었다. 이 같은 결과는 작업장의 안전풍토를 개선함으로써 직업성 손상을 예방할 수 있음을 시사한다.

Key Message
Safety climate was related to occupational injuries in the Korean working population. This result may indicate that occupational injuries can be prevented by improving the workplace safety climate. Workplace safety should be a high priority goal for management, and workers need to help each other for workplace safety.

Citations

Citations to this article as recorded by

Data profile: Korean Work, Sleep, and Health Study (KWSHS)
Seong-Sik Cho, Jeehee Min, Heejoo Ko, Mo-Yeol Kang
Ann Occup Environ Med.2025; 37: e3. CrossRef

Data Profile

Data profile: the Korean Workers’ Compensation-National Health Insurance Service (KoWorC-NHIS) cohort: Jeehee Min, Eun Mi Kim, Jaiyong Kim, Jungwon Jang, Youngjin Choi, Inah Kim; Epidemiol Health. 2024;46:e2024071. Published online August 19, 2024; DOI: https://doi.org/10.4178/epih.e2024071

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Abstract Summary PDF: Abstract
The Korean Workers’ Compensation-National Health Insurance Service (KoWorC-NHIS) cohort was established to investigate the longitudinal health outcomes of Korean workers who have been compensated for occupational injuries or diseases. This cohort study, which utilized data spanning from 2004 to 2015, merged workers’ compensation insurance claim data with the National Health Insurance Database (NHID), encompassing 858,793 participants. The data included socio-demographic factors such as age, sex, income, address, insurance type, and disability grade. It also covered the types of occupational accidents, International Classification of Diseases, 10th revision codes for diseases or accidents, work tenure, industry, occupation code, and company size. Additional details such as the occupational hire date, date of claim, date of recognition, and affected body parts were recorded. The cohort predominantly consisted of male workers (80.0%), with the majority experiencing their first occupational accident in their 40s (27.6%) or 50s (25.3%). Notably, 93.1% of the cases were classified as occupational injuries. By integrating this data with that from the NHID, updates on health utilization, employment status, and income changes were made annually. The follow-up period for this study is set to conclude in 2045.; Summary

Korean summary
KoWorC-NHIS Cohort (산재보험-국민건강보험공단 코호트) 는 2004년부터 2015년까지 산업재해를 경험한 근로자들의 장기적인 건강 결과를 추적 조사하기 위해 구축된 코호트이다. 이 코호트에는 총 858,793명의 근로자가 등록되었으며, 대다수는 남성 (80%)이었고, 업무상 사고 (93.1%)를 경험한 것으로 나타났다. 이 코호트를 활용하여 산업재해 피해 근로자들의 장기적인 건강영향을 분석할 수 있으며, 취약 계층 근로자의 건강을 보호하기 위한 예방 정책 수립의 근거로 활용할 수 있다.

Key Message
The KoWorC-NHIS Cohort (Workers' Compensation Insurance-National Health Insurance Service Cohort) was established to track the long-term health outcomes of workers who experienced occupational injuries and illnesses from 2004 to 2015. The cohort includes a total of 858,793 workers, with the majority being male (80%) and having experienced occupational accidents (93.1%). This cohort can be used to analyze the long-term health effects on workers who have suffered occupational injuries, and can serve as evidence for establishing preventive policies to protect the health of vulnerable workers.

Original Article

Analysis of the severity of occupational injuries in the mining industry using a Bayesian network: Mostafa Mirzaei Aliabadi, Hamed Aghaei, Omid kalatpuor, Ali Reza Soltanian, Asghar Nikravesh; Epidemiol Health. 2019;41:e2019017. Published online May 11, 2019; DOI: https://doi.org/10.4178/epih.e2019017

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248 Download
15 Web of Science
9 Crossref

Abstract PDF

Abstract

OBJECTIVES
Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis.

METHODS

The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents.

RESULTS

Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers’ experience had the strongest influence on the severity of accidents.

CONCLUSIONS

Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.

Summary

Citations

Citations to this article as recorded by

Effects of positive and negative cyberloafing on safety behaviors and occupational incidents during the COVID-19 pandemic: a Bayesian network analysis
Harun Yildiz, Bora Yildiz
International Journal of Occupational Safety and Ergonomics.2025; 31(1): 248. CrossRef
Global prevalence of occupational injuries among sanitation workers: a systematic review and meta-analysis
Sina Temesgen Tolera, Tesfaye Gobena, Nega Assefa, Abraham Geremew
Frontiers in Public Health.2024;[Epub] CrossRef
A fuzzy Bayesian network DEMATEL model for predicting safety behavior
Mohsen Mahdinia, Iraj Mohammadfam, Ahmad Soltanzadeh, Mostafa Mirzaei Aliabadi, Hamed Aghaei
International Journal of Occupational Safety and Ergonomics.2023; 29(1): 36. CrossRef
Analysis of occupational accidents among nurses working in hospitals based on safety climate and safety performance: a Bayesian network analysis
Fakhradin Ghasemi, Hamed Aghaei, Taleb Askaripoor, Farhad Ghamari
International Journal of Occupational Safety and Ergonomics.2022; 28(1): 440. CrossRef
Retrospective assessment of the association between noise exposure and nonfatal and fatal injury rates among miners in the United States from 1983 to 2014
Abas Shkembi, Lauren M. Smith, Richard L. Neitzel
American Journal of Industrial Medicine.2022; 65(1): 30. CrossRef
Contributing effects of individual characteristics, behavioural and job-related factors on occurrence of mining-related injuries: A systematic review
Michael Mayom Ajith, Apurna Kumar Ghosh, Janis Jansz
Work.2022; 71(1): 87. CrossRef
Human Error Analysis for Hydraulic Engineering: Comprehensive System to Reveal Accident Evolution Process with Text Knowledge
Dan Tian, Hao Liu, Shu Chen, Mingchao Li, Chengzhao Liu
Journal of Construction Engineering and Management.2022;[Epub] CrossRef
Analysis of occupational accidents in Spain using shrinkage regression methods
Vicente Gallego, Ana Sánchez, Isabel Martón, Sebastián Martorell
Safety Science.2021; 133: 105000. CrossRef
Research trends in mining accidents study: A systematic literature review
Siti Noraishah Ismail, Azizan Ramli, Hanida Abdul Aziz
Safety Science.2021; 143: 105438. CrossRef

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