• 한국산업보건학회지
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• 제28권4호
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• pp.416-424
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• 2018

Objective: The objective of this study was to estimate the numbers of employees occupationally exposed to noise according to their industry and size. Methods: A Delphi panel consisting of 15 occupational health experts estimated the exposure prevalence of noise in workplace. Data on Industrial Accident Compensation Insurance provided from Occupational Safety and Health Research Institute were combined to produce the exposure population. Results: In Korea, 16.0% of employees, 2,539,890 out of 15,838,926, was estimated to exposed to noise occupationally. The rate was 32.7% and 10.3% in manufacturing sector and non-manufacturing sector, respectively. The highest rate, 52.5%, was found in manufacturing industries of wood and of products of wood and cork(except furniture) and of other transport equipment. Sorted by their size of business, the rate was higher as the number of employee was larger in manufacturing sector. Conclusions: Compared to the same rate estimated in the US, 17.2%, the result of this study seems to be in a resonable range.

• 대한간호학회지
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• 제50권5호
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• pp.658-670
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• 2020

Purpose: This study aimed to identify the predictors of blood and body fluid exposure (BBFE) in multifaceted individual (sleep disturbance and fatigue), occupational (occupational stress), and organizational (hospital safety climate) factors, as well as infection prevention behavior. We also aimed to test the mediating effect of infection prevention behavior in relation to multifaceted factors and the frequency of BBFE. Methods: This study was based on a secondary data analysis, using data of 246 nurses from the Shift Work Nurses' Health and Turnover study. Based on the characteristics of zero-inflated and over-dispersed count data of frequencies of BBFE, the data were analyzed to calculate zero-inflated negative binomial regression within a generalized linear model and to test the mediating effect using SPSS 25.0, Stata 14.1, and PROCESS macro. Results: We found that the frequency of BBFE increased in subjects with disturbed sleep (IRR = 1.87, p = .049), and the probability of non-BBFE increased in subjects showing higher infection prevention behavior (IRR = 15.05, p = .006) and a hospital safety climate (IRR = 28.46, p = .018). We also found that infection prevention behavior had mediating effects on the occupational stress-BBFE and hospital safety climate-BBFE relationships. Conclusion: Sleep disturbance is an important risk factor related to frequency of BBFE, whereas preventive factors are infection prevention behavior and hospital safety climate. We suggest individual and systemic efforts to improve sleep, occupational stress, and hospital safety climate to prevent BBFE occurrence.

• 한국산업보건학회지
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• 제8권2호
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• pp.264-271
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• 1998

A pilot study was undertaken to examine the possible health effects of electromagnetic fields(EMFs). The purpose of this study was to investigate of the EMFs exposures of personal environment, 60Hz magnetic fields. An experimental study was performed for six weeks of January-February 1998 to compare changes in melatonin levels in urine of 20 subjects during their normal sleeping hours and each 20 subjects in occupational and non-occupational group measured personal 24-h continual exposure, using EMDEX II (for 40-800Hz, Enertech Consultant, Inc.). An urine samples were collected 3 times a day(before sleep or around 24:00 ; immediately after wake-up ; around noon) for an week from each subjects and analyzed by radioimmunoassay. This study did not significant difference for the subjective average melatonin levels between occupational and nonoccupational groups exposed to electromagnetic fields. The mean personal exposure levels of occupational group were $0.215{\mu}T$, whereas non-occupational group were $0.18{\mu}T$. Occupational group were exposed more highly while at work. Finally, this study would provide significant data for furture study of exposure assessment of magnetic fields. A large scale study concerning more detailed exposure assessment should provide important information on health risk assessment of MFs. Further study should provide information on the contribution of various sources and the relationship between melatonin and immune system activity.

• Safety and Health at Work
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• 제2권4호
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• pp.348-354
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• 2011

Objectives: This cross-sectional study was performed in the Dental School of Prince of Songkla University to ascertain noise exposure of dentists, dental assistants, and laboratory technicians. A noise spectral analysis was taken to illustrate the spectra of dental devices. Methods: A noise evaluation was performed to measure the noise level at dental clinics and one dental laboratory from May to December 2010. Noise spectral data of dental devices were taken during dental practices at the dental services clinic and at the dental laboratory. A noise dosimeter was set following the Occupational Safety and Health Administration criteria and then attached to the subjects' collar to record personal noise dose exposure during working periods. Results: The peaks of the noise spectrum of dental instruments were at 1,000, 4,000, and 8,000 Hz which depended on the type of instrument. The differences in working areas and job positions had an influence on the level of noise exposure (p < 0.01). Noise measurement in the personal hearing zone found that the laboratory technicians were exposed to the highest impulsive noise levels (137.1 dBC). The dentists and dental assistants who worked at a pedodontic clinic had the highest percent noise dose (4.60 ${\pm}$ 3.59%). In the working areas, the 8-hour time-weighted average of noise levels ranged between 49.7-58.1 dBA while the noisiest working area was the dental laboratory. Conclusion: Dental personnel are exposed to noise intensities lower than occupational exposure limits. Therefore, these dental personnel may not experience a noise-induced hearing loss.

• 한국산업보건학회지
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• 제17권4호
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• pp.310-321
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• 2007

Status of benzene exposure was evaluated upon petrochemical workers in the Yeosu Industrial Complex, based on questionnaire responses by workers, review of previous work environment assessment reports between 1996 and 2004, in addition to short-term exposure measurements for unit tasks in the field. Questionnaire results showed that workers in the field were suffering concern on and symptoms of respiratory diseases, cancers or other illnesses of unknown causes. In particular, workers were highly worried about the risk of exposure to chemical hazards including benzene, while conducting specific tasks (e.g. sampling, draining, gauging) among normal operations during which equipments are opened and contents are exposedin the air, as well as periodic turnaround (TA) task. However, the review of previous work environment assessment reports found out that short-term exposure assessment data for unit tasks accounted for less than 1% of total data, and most of them were on 8-hr average exposure level. It also turned out that benzene was not detected in 83% of total samples, suggesting routine but pointless sampling has been repeated. Short-term exposure level was assessed focusing on tasks with high level of complaints on the exposure risk, based on the questionnaire responses. As predicted, a maximum of 741 ppm benzene exposure was reached depending on types and conditions of operations involved. In conclusion, these findings suggest that the evaluation and management on the short-term high exposure tasks including turnaround are crucial in reducing benzene exposure and preventing haematopoietic cancer in workers in the petrochemical industry.

• 한국산업보건학회지
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• 제24권2호
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• pp.219-228
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• 2014

Objectives: The major objective of this study was to develop a tier 2 exposure model combining tier 1 exposure model estimates and worker monitoring data and suggesting narrower exposure ranges than tier 1 results. Methods: Bayesian statistics were used to develop a tier 2 exposure model as was done for the European Union (EU) tier 2 exposure models, for example Advanced REACH Tools (ART) and Stoffenmanager. Bayesian statistics required a prior and data to calculate the posterior results. In this model, tier 1 estimated serving as a prior and worker exposure monitoring data at the worksite of interest were entered as data. The calculation of Bayesian statistics requires integration over a range, which were performed using a Riemann sum algorithm. From the calculated exposure estimates, 95% range was extracted. These algorithm have been realized on Excel spreadsheet for convenience and easy access. Some fail-proof features such as locking the spreadsheet were added in order to prevent errors or miscalculations derived from careless usage of the file. Results: The tier 2 exposure model was successfully built on a separate Excel spreadsheet in the same file containing tier 1 exposure model. To utilize the model, exposure range needs to be estimated from tier 1 model and worker monitoring data, at least one input are required. Conclusions: The developed tier 2 exposure model can help industrial hygienists obtain a narrow range of worker exposure level to a chemical by reflecting a certain set of job characteristics.

• 한국환경과학회지
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• 제22권1호
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• pp.47-57
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• 2013

Studies evaluating the health effects of hazardous air pollutants assume that people's exposure to typical pollutant level is the same as specific regional pollutant level. However, depending on social and demographic factors, time-activity pattern of people can vary widely. Since most people live in indoor environments over 88% of the day, evaluating exposure to hazardous air pollutants is hard to characterize. Objective of this study was to estimate the exposure levels of university students of $NO_2$, VOCs(BTEX) and $PM_{10}$ using the scenarios with time-activity pattern and indoor concentrations. Using data from time-use survey of National Statistical Office in 2009, we investigated time-activity pattern of university students and hourly major action. A total of 1,057 university students on weekday and 640 on weekend spent their times at indoor house 13.04 hr(54.32%), other indoors 7.70 hr(32.06%), and transportation 2.36 hr(9.83%). Indoor environments in which university students spent their times were mainly house and school. Air pollutants concentrations of other indoor environments except house and school such as bar, internet cafe and billiard hall were higher than outdoors, indicating that indoor to outdoor ratios were above 1. According to three types of exposure scenarios, exposure to air pollutants could be reduced by going home after school.

• Safety and Health at Work
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• 제9권1호
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• pp.84-94
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• 2018

Background: This paper describes a simple-to-use and reliable screening tool called Critical Task Exposure Screening (CTES), developed by a chemical company. The tool assesses if the exposure to a chemical for a task is likely to be within acceptable levels. Methods: CTES is a Microsoft Excel tool, where the inhalation risk score is calculated by relating the exposure estimate to the corresponding occupational exposure limit (OEL) or occupational exposure band (OEB). The inhalation exposure is estimated for tasks by preassigned ART1.5 activity classes and modifying factors. Results: CTES requires few inputs. The toxicological data, including OELs, OEBs, and vapor pressure are read from a database. Once the substance is selected, the user specifies its concentration and then chooses the task description and its duration. CTES has three outputs that may trigger follow-up: (1) inhalation risk score; (2) identification of the skin hazard with the skin warnings for local and systemic adverse effects; and (3) status for carcinogenic, mutagenic, or reprotoxic effects. Conclusion: The tool provides an effective way to rapidly screen low-concern tasks, and quickly identifies certain tasks involving substances that will need further review with, nevertheless, the appropriate conservatism. This tool shows that the higher-tier ART1.5 inhalation exposure assessment model can be included effectively in a screening tool. After 2 years of worldwide extensive use within the company, CTES is well perceived by the users, including the shop floor management, and it fulfills its target of screening tool.

• 한국산업보건학회지
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• 제25권2호
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• pp.146-155
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• 2015

Objectives: The aims of this study were to set up benzene exposure matrices according to industry and process and to assess the risk of those occupational exposure to benzene. Methods: The benzene exposure matrices were assembled depending on industry and process, based on an exposure database provided by KOSHA(the Korean Occupational Safety and Health Agency), which was gathered from a workplace hazards evaluation program in Korea. These exposure matrices were assessed by Hallmark Risk Assessment tool. Results: The benzene was treated 412 industries sector(36%), 2,747 business places, and 471 industrial processes according to database. The arithmetic mean of past decade 8 hours time-weighted average of airborne benzene concentrations in the workplace was 0.10722 ppm. 1.07% of the total sample were greater than OEL, and 59.8% were showed less than the limit of detection. The highest risk values(Danger Value) were seen 36 industries including manufacture of general paints and similar product and 12 processes, such as other painting of manufacture of metal fabricated members. Exposure matrices based on employee exposure data base may provide exposure histories and can be used in epidemiological studies. Conclusions: It was found that more attentions should be paid to 36 among 412 industries and 12 of 471 processes, with a higher risk value.

• 한국산업보건학회지
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• 제22권4호
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• pp.316-328
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• 2012

Objectives: This study was designed to provide the information regarding chemicals classification and health hazard by evaluating the toxicological effect through repeated inhalation exposure of methyl acrylate(MA) in Sprague-Dawley(SD) rat for 13 weeks. Methods: According to the notification with Ministry of Labor(No. 2009-68) and OECD Test Guideline 413, the rats were exposed to MA at concentration of 0, 56, 168, 280 ppm via whole body inhalation for 6 hours per day, 5 days per week, for 13 weeks. All animals were observed for mortality, morbidity and the change of body weight and food consumption were determined during the exposure period. Necropsy finding, organ weight, hematology, clinical biochemistry and histopathological examination following exposure were also performed. Results: There were no death and abnormal clinical signs relate to exposure MA. However, At 160 ppm and 280 ppm exposure groups, body weight and food consumption showed statistically significant decrease and histopathological changes in lung, trachea, nasal cavity, larynx were observed. Conclusions: MA was mainly affected respiratory tract. It is consequently provided to be classified as category 2(0.2 mg/L/6h < category 2 ${\leq}$ 1.0 mg/L/6h) for specific target organ toxicity following repeated exposure according to Standard for Classification and Labeling of Chemical Substance and Material Safety Data Sheet. The NOAEL(no observable adverse effect level) of MA was also determined to be lower than 56 ppm.