• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 춘계학술대회
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• pp.117-125
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• 2010

Cerebrovascular and cardiovascular diseases (CVDs) are a major cause of deaths among workers as well as in general population in Korea. Occupational stress like long working hours or overwork can cause sudden unexpected death in a worker who had been suffering from an aggravated preexisting condition such as hypertensive or arteriosclerotic diseases, The Korean government has compensated the cases of cerebrovascular disease and cardiovascular disease due to overwork, but neither a resonable definition of overwork nor detailed evaluation guideline has been officially provided to verify overwork, so that the prevention of, as well as compensation for workers' occupational stress-related cardiovascular attacks, cannot be carried out efficiently. A thorough understanding of the etiopathology of WR-CVDs can be very helpful in developing a prevention strategy.

• Annals of Occupational and Environmental Medicine
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• 제35권
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• pp.35.1-35.11
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• 2023

Background: Cardio-cerebrovascular diseases (CVDs) are the most common cause of death worldwide. Various CVD risk assessment tools have been developed. In South Korea, the Korea Occupational Safety & Health Agency (KOSHA) and the National Health Insurance Service (NHIS) have provided CVD risk assessments with health checkups. Since 2018, the KOSHA guide has stated that NHIS CVD risk assessment tool could be used as an alternative of KOSHA assessment tool for evaluating CVD risk of workers. The objective of this study was to determine the correlation and agreement between the KOSHA and the NHIS CVD risk assessment tools. Methods: Subjects of this study were 17,485 examinees aged 20 to 64 years who had undergone medical examinations from January 2021 to December 2021 at a general hospital. We classified subjects into low-risk, moderate-risk, high-risk, and highest-risk groups according to KOSHA and NHIS's CVD risk assessment tools. We then compared them with cross-analysis, Spearman correlation analysis, and linearly weighted kappa coefficient. Results: The correlation between KOSHA and NHIS tools was statistically significant (p-value < 0.001), with a correlation coefficient of 0.403 and a kappa coefficient of 0.203. When we compared risk group distribution using KOSHA and NHIS tools, CVD risk of 6,498 (37.1%) participants showed a concordance. Compared to the NHIS tool, the KOSHA tool classified 9,908 (56.7%) participants into a lower risk category and 1,079 (6.2%) participants into a higher risk category. Conclusions: In this study, KOSHA and NHIS tools showed a moderate correlation with a fair agreement. The NHIS tool showed a tendency to classify participants to higher CVD risk group than the KOSHA tool. To prevent CVD more effectively, a higher estimation tool among verified CVD risk assessment methods should be selected and managements such as early intervention and treatment of risk factors should be performed targeting the high-risk group.