• Advances in environmental research
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• v.6 no.4
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• pp.241-254
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• 2017

This study was conducted to investigate the levels of heavy metals in twelve species of vegetables and assessment of health risk. Samples were analyzed using inductively coupled plasma mass spectrometer (ICP-MS). The ranges of Cr, Ni, Cu, As, Cd and Pb in vegetables species were 0.37-5.4, 0.03-17, 0.35-45, 0.01-2.6, 0.001-2.2, and 0.04-8.8 [mg/kg, fresh weight (fw)], respectively. The concentrations of As, Cd and Pb in most vegetable species exceeded the maximum permissible levels, indicating unsafe for human consumption. Health risks associated with the intake of these metals were evaluated in terms of estimated daily intake (EDI), and carcinogenic and non-carcinogenic risks by target hazard quotient (THQ). Total THQ of the studied metals from most of the vegetables species were higher than 1, indicated that these types of vegetables might pose health risk due to metal exposure. The target carcinogenic risk (TR) for As ranged from 0.03 to 0.48 and 0.0004 to 0.025 for Pb which were higher than the USEPA acceptable risk limit (0.000001) indicating that the inhabitants consuming these vegetables are exposed to As and Pb with a lifetime cancer risk. The findings of this study reveal the health risks associated with the consumption of heavy metals through the intake of selected vegetables in adult population of Bangladesh.

• Analytical Science and Technology
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• v.14 no.2
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• pp.1025-1032
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• 2001

• Safety and Health at Work
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• v.15 no.1
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• pp.33-41
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• 2024

Background: Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods: First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results: The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m³. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m³. Conclusion: ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m³; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m³.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.159-166
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• 2022

Background: A quantitative structure-activity relationship (QSAR) model was adopted in the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH, EU) regulations as well as the Act on Registration, Evaluation, etc. of Chemicals (AREC, Republic of Korea). It has been previously used in the registration of chemicals. Objectives: In this study, we investigated the correlation between the predicted data provided by three prediction programs using a QSAR model and actual experimental results (acute fish, daphnia magna toxicity). Through this approach, we aimed to effectively conjecture on the performance and determine the most applicable programs when designating toxic substances through the AREC. Methods: Chemicals that had been registered and evaluated in the Toxic Chemicals Control Act (TCCA, Republic of Korea) were selected for this study. Two prediction programs developed and operated by the U.S. EPA - the Ecological Structure-Activity Relationship (ECOSAR) and Toxicity Estimation Software Tool (T.E.S.T.) models - were utilized along with the TOPKAT (Toxicity Prediction by Komputer Assisted Technology) commercial program. The applicability of these three programs was evaluated according to three parameters: accuracy, sensitivity, and specificity. Results: The prediction analysis on fish and daphnia magna in the three programs showed that the TOPKAT program had better sensitivity than the others. Conclusions: Although the predictive performance of the TOPKAT program when using a single predictive program was found to perform well in toxic substance designation, using a single program involves many restrictions. It is necessary to validate the reliability of predictions by utilizing multiple methods when applying the prediction program to the regulation of chemicals.

• Safety and Health at Work
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• v.8 no.2
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• pp.206-211
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• 2017

Background: Self-reported low back pain (LBP) has been evaluated in relation to material handling lifting tasks, but little research has focused on relating quantifiable stressors to LBP at the individual level. The National Institute for Occupational Safety and Health (NIOSH) Composite Lifting Index (CLI) has been used to quantify stressors for lifting tasks. A chemical exposure can be readily used as an exposure metric or stressor for chemical risk assessment (RA). Defining and quantifying lifting nonchemical stressors and related adverse responses is more difficult. Stressor-response models appropriate for CLI and LBP associations do not easily fit in common chemical RA modeling techniques (e.g., Benchmark Dose methods), so different approaches were tried. Methods: This work used prospective data from 138 manufacturing workers to consider the linkage of the occupational stressor of material lifting to LBP. The final model used a Bayesian random threshold approach to estimate the probability of an increase in LBP as a threshold step function. Results: Using maximal and mean CLI values, a significant increase in the probability of LBP for values above 1.5 was found. Conclusion: A risk of LBP associated with CLI values > 1.5 existed in this worker population. The relevance for other populations requires further study.

• Journal of Korean society of Dental Hygiene
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• v.13 no.5
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• pp.713-726
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• 2013

Objectives : The purpose of this study is to develop a job performance assessment tool for dental hygienists. Methods : The development consisted of three steps. The first step was to construct the contents of the assessment tool and a pretest questionnaire. In the second step, validity and reliability tests were done and modified for the pretest questionnaires and an assessment tool was made. The third step was verification of the assessment tool. A total of 678 data from the dental hygienists were analyzed to verify the validity and reliability. The assessment tool consisted of two areas such as job performance and competency/attitude: the job performance area covered four sub-areas including oral health education, preventive dental care, assistance for dental treatment, and administrative management. Results : The number of questions and reliability test result for each sub-area were as follows. Reliability coefficient for oral health education (10 questions) was 0.899, preventive dental care (8 questions) was 0.861, assistance for dental treatment (18 questions) was 0.915, administrative management (8 questions) was 0.919, competency of dental hygienists (11 questions) was 0.947, and attitude of dental hygienists (15 questions) was 0.955. Cronbach ${\alpha}$ coefficient for reliability of total 70 questions of the assessment tool was 0.980. Conclusions : The validity of the assessment tool was verified by three steps and the reliability proved to be significant. Consequently the assessment tool was found to be useful as an objective and valid job performance assessment tool for the dental hygienists.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3233-3239
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• 2015

Background: Whether depression causes increased risk of the development of breast cancer has long been debated. We conducted an updated meta-analysis of cohort studies to assess the association between depression and risk of breast cancer. Materials and Methods: Relevant literature was searched from Medline, Embase, Web of Science (up to April 2014) as well as manual searches of reference lists of selected publications. Cohort studies on the association between depression and breast cancer were included. Data abstraction and quality assessment were conducted independently by two authors. Random-effect model was used to compute the pooled risk estimate. Visual inspection of a funnel plot, Begg rank correlation test and Egger linear regression test were used to evaluate the publication bias. Results: We identified eleven cohort studies (182,241 participants, 2,353 cases) with a follow-up duration ranging from 5 to 38 years. The pooled adjusted RR was 1.13(95% CI: 0.94 to 1.36; $I^2=67.2%$, p=0.001). The association between the risk of breast cancer and depression was consistent across subgroups. Visual inspection of funnel plot and Begg's and Egger's tests indicated no evidence of publication bias. Regarding limitations, a one-time assessment of depression with no measure of duration weakens the test of hypothesis. In addition, 8 different scales were used for the measurement of depression, potentially adding to the multiple conceptual problems concerned with the definition of depression. Conclusions: Available epidemiological evidence is insufficient to support a positive association between depression and breast cancer.

• The Journal of Health Technology Assessment
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• v.1 no.1
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• pp.22-26
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• 2013

Objectives: Balancing benefits and risks through the drug life cycle has been discussed for many decades. The objective of this study was to review the processes and tools currently proposed for benefit-risk assessment of medicinal drugs. It aimed to establish scientific and efficient drug safety management system based on the synthetic analysis of benefit-risk evidence. Methods: We conducted a review of exiting literatures published by regulatory agencies or initiatives. Not only quantitative methodologies but also qualitative method were compared to understand their key characteristics for the benefit and risk assessment of drugs. Results: Recently, benefit-risk assessments have more structured approaches to decision making as part of regulatory science. Regulatory agencies such as European Medicines Agency, FDA have prepared plans to apply benefit-risk assessment to regulatory decision making. Also many initiatives such as IMI (Innovative Medicine Initiative) have conducted research and published reports about benefit-risk assessment. For benefit-risk assessment, four kinds of methods are necessary. Frameworks such as BRAT (Benefit Risk Action Team) framework, PrOACT-URL provide guidance for the whole process of decision-making. Metrics are measurements of risk benefit. The estimation techniques are methods to synthesis and combine evidences from various sources. The utility survey techniques are necessary to explicit preferences of various outcome from stakeholders. Conclusion: There is the lack of widely accepted, validated model for benefit-risk assessment. Nor there is an agreement among academia, industry, and government on methods for the quantitative valuation. It is also limited by available evidence and underlying assumptions. Nevertheless, benefit-risk assessment is fundamental to improve transparency, consistency and predictability for decision making through the structured systematic approaches.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.2
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• pp.99-108
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• 2020

Objectives: This study aimed to compare the regulatory systems for laboratory safety and health management between Korea and Germany and discuss the implications. Methods: Laboratory safety and health regulations for legal enforcement and relevant technical guidelines in Korea and Germany were reviewed. Results: Lab safety and health management is enforced by the Act on the Establishment of Safe Laboratory Environment in Korea. Most provisions focus on supervisory control, that is, the principal's liability is emphasized. In addition, there is a lack of laboratory-specific procedures for safety and health management in the act since it is stipulated that other relevant regulations apply to some technical contents. Non-compulsory technical guidelines for lab safety and health management are also provided by the Korea Occupational Safety and Health Agency (KOSHA) in order to enable researchers to follow safe procedures. There is no independent regulation for lab safety and health in Germany, and it is also governed by several regulations. The German Social Accident Insurance Institute provides technical guidelines on lab safety and health, and these contain more specific content to allow them to be followed more easily compared to the KOSHA guidelines. The most remarkable differences between the regulation of each country were contents of the risk assessment and specific protect measures from hazardous agents. Conclusions: Regulatory control is an essential way to prevent accidents, but it is more important to create an environment in which all stakeholders, including individual lab members, are allowed to participate actively in safety and health management activities.

• Structural Engineering and Mechanics
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• v.23 no.1
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• pp.75-95
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• 2006

Two-step identification approaches for effective bridge health monitoring are proposed to alleviate the issues associated with many unknown parameters faced in real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the damage assessment is not always needed to be carried out whereas the alarming for damages is to be continuously monitored. In the first step for screening potentially damaged members, a damage indicator method based on modal strain energy, probabilistic neural networks and the conventional neural networks using grouping technique are utilized and then the conventional neural networks technique is utilized for damage assessment on the screened members in the second step. The effectiveness of the proposed methods is investigated through a field test on the northern-most span of the old Hannam Grand Bridge over the Han River in Seoul, Korea.