Exposure Database Research Articles

Transplacental transfer of organochlorine pesticides: Concentration ratio and chiral properties

Currently, there is limited information about the mechanism of the human transplacental transfer for organochlorine pesticides (OCPs). This study aimed to evaluate the transplacental transfer of OCPs to better understand the influencing factors of exposure and transplacental efficiency. The study involved quantitative determination of OCPs and the enantiomer fraction (EF) of chiral OCPs in pregnant women from Wuhan, China. The results indicate that the exposure levels of OCPs varied in the order: maternal serum > cord serum > placenta. Chiral contaminants, such as α-HCH, o,p′-DDD and o,p′-DDT, were non-racemic in the three biological matrices, wherein EFα-HCH < 0.5, EFo,p′-DDD < 0.5, EFo,p′-DDT > 0.5. For HCHs, the concentration ratio between cord serum and maternal serum (Rcm) <1, while for DDXs, the Rcm ≈ 1, indicating that the transport efficiency of different pollutants is related to the physicochemical properties. These results showed that placenta seems to be a more efficient barrier for β-HCH than for p,p′-DDE. The concentration ratios across placenta significantly lower than 1 and the enantiomeric selective transfer imply that some OCPs may have more complicated maternal-fetus transfer mechanisms, involving both simple diffusion and active transport. To the best of our knowledge, this is the first study to investigate the transfer of OCPs and their enantiomer fractions across placenta. These findings could expand the database of chemical exposure in biological matrices and improve the understanding of the mechanisms of transplacental transfer of OCPs.

Cyber risk prediction through social media big data analytics and statistical machine learning

As a natural outcome of achieving equilibrium, digital economic progress will most likely be subject to increased cyber risks. Therefore, the purpose of this study is to present an algorithmic model that utilizes social media big data analytics and statistical machine learning to predict cyber risks. The data for this study consisted of 83,015 instances from the common vulnerabilities and exposures (CVE) database (early 1999 to March 2017) and 25,599 cases of cyber risks from Twitter (early 2016 to March 2017), after which 1000 instances from both platforms were selected. The predictions were made by analyzing the software vulnerabilities to threats, based on social media conversations, while prediction accuracy was measured by comparing the cyber risk data from Twitter with that from the CVE database. Utilizing confusion matrix, we can achieve the best prediction by using Rweka package to carry out machine learning (ML) experimentation and artificial neural network (ANN) with the accuracy rate of 96.73%. Thus, in this paper, we offer new insights into cyber risks and how such vulnerabilities can be adequately understood and predicted. The findings of this study can be used by managers of public and private companies to formulate effective strategies for reducing cyber risks to critical infrastructures.

Summarizing vulnerabilities’ descriptions to support experts during vulnerability assessment activities

Vulnerabilities affecting software and systems have to be promptly fixed, to prevent violations to integrity, availability and confidentiality policies of targeted organizations. Once a vulnerability is discovered, it is published on the Common Vulnerabilities and Exposures (CVE) database, freely available on the web. However, vulnerabilities are described using natural language, which makes them hard to be automatically interpreted by machines. As a consequence, vulnerability assessment activities tend to be time-consuming and imprecise, as the assessors must manually read the majority of the vulnerabilities concerning the perimeter to be protected, to make a decision on which vulnerabilities have the highest priority for patching. In this paper we present CVErizer, an approach able to automatically generate summaries of daily posted vulnerabilities and categorize them according to a taxonomy modeled for industry. We empirically assess the classification capabilities of the approach on a set of 3369 pre-labeled CVE records and perform an end-to-end evaluation of CVErizer summaries involving 15 cybersecurity master students and 4 professional security experts. Our study demonstrates the high performance of the proposed approach in correctly extracting and classifying information from CVE descriptions. Summaries are also considered highly useful for helping analysts during the vulnerability assessment processes.

Fate of UV filter Ethylhexyl methoxycinnamate in rat model and human urine: Metabolism, exposure and demographic associations

Ethylhexyl methoxycinnamate (EHMC) is one of the most frequently used UV filters in sunscreens and other cosmetic products. Its ubiquitous presence in various environmental matrices and its endocrine disrupting properties have been widely reported. However, we know little about the effect of EHMC exposure on humans, mainly due to its fast metabolism. In this study, urine and plasma of EHMC-dosed rats were analysed to identify its major metabolites. Five metabolites were found, with four firstly reported. Two metabolites were putatively identified as 4-methoxycinnamic acid (4-MCA) and 4′-methoxyacetophenone (4′-MAP). Quantitative results revealed that their excretion concentrations were much higher than the parent compound. Because of these high concentrations, for the human biomonitoring study, EHMC and these two metabolites were detected simultaneously in urine samples from Chinese children and adolescents. The results indicated wide exposure to EHMC, 4-MCA and 4′-MAP. The correlation between urinary concentration of EHMC and 4-MCA as well as 4-MCA and 4′-MAP provided important clues as to the sources and metabolic pathways among these three compounds. Several demographic factors were also assessed with the exposure level. As the first human exposure study of EHMC in a Chinese population, this report would help to establish an exposure database facilitating health risk assessment of EHMC.

Evaluating Volcanic Hazard Risk Through Numerical Simulations

As volcanic hazards induce damage with their flows of gases, liquids, and solid materials, a numerical simulation using multi-phase formulation is applicable to the analysis and evaluation of the risks from these volcanic hazards in both normal and emergent periods. A numerical simulation can also be useful for crisis management. Quick and precise evaluation is needed for upcoming and ongoing hazards, and we present here a concept for the development of a volcanic hazard evaluation system for these hazards, a system in which an input parameter database is compiled and countermeasure information is provided by considering the exposure and vulnerability database.

Older Age and Disease Duration Are Highly Associated with Hepatocellular Carcinoma in Patients with Autoimmune Hepatitis.

Hepatocellular carcinoma (HCC) is rare in patients with autoimmune hepatitis (AIH). However, the overall burden of AIH cirrhosis in causing HCC and patients' risk factors are not well understood. To characterize the proportion of HCC linked to AIH at a large academic health center, and to identify variables associated with HCC in patients with AIH in a case-control study design. Over a 14.5-year period, medical records of all patients with HCC were reviewed. Cases are AIH patients identified from the cohort, and controls are patients with AIH without HCC. Three controls were randomly chosen from the Genetic Repository of Autoimmune Liver Disease and Coexisting Exposures database for each eligible case. Out of 1250 eligible patients, 20 were linked to AIH (1.6%). Their median age was 64years, 40% men and 100% Caucasian. Ten percent of AIH patients did not have evidence of cirrhosis at HCC diagnosis. The proportion of HCCs due to AIH decreased during the time intervals of the study. Compared to controls, cases were more likely men (40.0% vs. 18%, p = 0.049), with longer AIH duration (median 16years vs. 5years, p = 0.004). Prolonged AIH duration (OR 1.68, p = 0.006) and older age (OR 1.15, p = 0.049) were risk factors for HCC. AIH is a rare cause (1.6%) for HCC in Midwestern USA with a decreasing trend over 14.5years. Ten percent of AIH-HCC patients did not have cirrhosis at time of HCC diagnosis. Patients with prolonged duration of the disease and older age are at high risk to develop HCC.

REACH Worker Exposure Model for Co-formulants Used in Plant Protection Products.

BackgroundSubstances used as co-formulants in plant protection products (PPP) may require registration under Regulation (EC) No. 1907/2006 (REACH), and additionally where an exposure assessment is required, this must take into consideration the specifics of the PPP use.ObjectivesThis work reports a customized screening level model developed to support human health risk assessment of operators, workers, and bystanders (OWB) for co-formulants used in PPP. The OWB model was designed to closely integrate with REACH generic exposure scenarios (GES) for PPP developed by the European Crop Protection Association (ECPA). The use of these tools in combination is expected to lead to a more standardized and hence efficient risk assessment of co-formulants. This study describes the basis for OWB exposure predictions as well as benchmarking against relevant REACH exposure models for equivalent tasks. The benchmarking was carried out to gain some insight into the initial assumption that the most commonly used tier 1 REACH model would be more conservative than the specific PPP models used for regulatory risk assessments under PPP legislation.MethodExisting exposure models with regulatory acceptance for the most common types of PPP and their professional and consumer uses were selected. The German BBA model was used to assess spray applications. Granule and seed dispersal was assessed using the US Environmental Protection Agency (EPA) Pesticide Handlers Exposure Database (PHED). ECETOC TRA was employed to assess exposure during certain tasks performed in seed treatment, not covered by these PPP models. Where the underlying models featured multiple exposure determinants, the exposure was calculated for all permutations, and the worst-case exposure selected and reported for use in risk assessment. The PPP models are based on measured data collected during actual application of PPP; hence, the worst-case exposure predicted was expected to reflect a realistic worst case for these tasks.ResultsOWB was implemented as an Excel spreadsheet. Exposure models, parameters, and exposure and risk estimates are reported in a REACH-compliant output format to facilitate the registration of co-formulant uses. As would be expected, benchmarking OWB against the PPP-specific exposure models demonstrated equivalence with the worst-case prediction from these underlying PPP models. For the scenarios modelled, the tier 1 ECETOC TRA gave more conservative predictions than OWB. The reduction in conservatism is attributed to the underlying PPP models being based on measured data collected specifically during the use of PPP, compared to the data underlying ECETOC TRA, based mainly on industrial workplace uses.ConclusionsOWB provides inhalation and dermal exposure estimates for co-formulants used in PPP which are equivalent to the worst-case estimates from existing specialized PPP exposure models based on measured data. OWB has simplified information requirements in comparison to higher-tier REACH or PPP models. Use of OWB in combination with the defined ECPA GES facilitates an efficient and standardized REACH risk assessment and registration of co-formulant uses in PPP. A defined assessment framework and default inputs potentially decreases the anticipated inter-user variability compared with the use of higher-tier PPP or REACH models in this screening level context.

Development of Quantitative Estimates of Wood Dust Exposure in a Canadian General Population Job-Exposure Matrix Based on Past Expert Assessments.

The CANJEM general population job-exposure matrix summarizes expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to apply quantitative concentrations to CANJEM cells using Canadian historical measurements from the Canadian Workplace Exposure Database (CWED), taking exposure to wood dust as an example. We selected 5170 personal and area wood dust measurements from 31 occupations (2011 Canadian National Occupational Classification) with a non-zero exposure probability in CANJEM between 1930 and 2005. The measurements were taken between 1981 and 2003 (median 1989). A Bayesian hierarchical model was applied to the wood dust concentrations with occupations as random effects, and sampling duration, year, sample type (area or personal), province, and the relative proportion of jobs exposed at medium and high intensity in CANJEM cells as fixed effects. The estimated geometric mean (GM) concentrations for a CANJEM cell with all jobs exposed at medium or high intensity were respectively 1.3 and 2.4 times higher relative to a cell with all jobs at low intensity. An overall trend of -3%/year in exposure was observed. Applying the model estimates to all 198 cells in CANJEM with some exposure assigned by the experts, the predicted 8-hour, personal wood dust GM concentrations by occupation for 1989 ranged from 0.48 to 1.96 mg m-3. The model provided estimates of wood dust concentrations for any CANJEM cell with exposure, applicable for quantitative risk assessment at the population level. This framework can be implemented for other agents represented in both CANJEM and CWED.

The Canadian Urban Environmental Health Research Consortium (CANUE): a national data linkage initiative

IntroductionHealth and environmental exposure databases are generally siloed in different research institutions across Canada and integrating them for environmental health research is a considerable challenge. Facilitating the linkage of these databases is essential to provide new analytical opportunities and help create efficiencies for research on environmental determinants of health.&#x0D; Objectives and ApproachCANUE is a Canadian Institutes of Health Research-funded platform for supporting environmental health research. CANUE collates and generates standardized environmental data on air and noise pollution, land use, green/natural spaces, climate change/extreme weather, and socioeconomic conditions for every postal code in Canada and makes them freely available to researchers. Systems and procedures are being developed by CANUE to facilitate the sharing and integration of these extensive geospatial exposures with existing observational cohorts and administrative health databases across Canada. This linkage will enable investigators to test hypotheses on the interdependent associations of environmental features with health impacts or benefits.&#x0D; ResultsCANUE now hosts a dozen national exposure databases and related metadata files, and actively adds new regional and national datasets. Streamlined processes for data sharing have been developed to facilitate easy merging with health data. Substantial consultation has also taken place with a wide range of health data holders to establish appropriate processes for receiving and managing environmental data, with particular focus on addressing challenges presented by differing ethics, consent and confidentiality requirements. These processes help accelerate the research process by making analysis-ready data available to investigators, create opportunities to study how multiple environmental factors are linked to a wide range of health outcomes, and generally increase the use of health and population databases for environmental health research.&#x0D; Conclusion/ImplicationsThe CANUE collaborative model illustrates how the production of policy-relevant evidence can be advanced through better coordination among environmental health researchers and linkage with health databases. CANUE is improving the scientific potential and cost-effectiveness of research in environmental epidemiology through streamlining linkage and access to standardized exposure datasets.

Revisiting the Veterans Cohort Mortality Study: New results and synthesis

ABSTRACTThe Veterans Cohort Mortality Study began in 1999 in collaboration with Washington University in St. Louis, comprising ~70,000 male military veterans. We published six research papers on this cohort, considering the dynamics of all-cause mortality as the subjects aged and environmental parameters changed. This paper summarizes those results and presents new results by age group. Pollutants included monitored and modeled criteria pollutants, vehicular traffic density (annual km driven per unit of county land area), and modeled nationwide levels of hazardous species. In addition to spatial relationships, we examined the effects of exposure timing through separate analyses of sequential follow-up and exposure periods from 1976 to 2001. Risks associated with peak ozone decreased with lag between exposure and response, suggesting acute effects. Risks associated with traffic were invariant over time and consistent across five exposure databases. Associations with ozone were also coherent across databases; we found no consistent associations with particulate matter. Epidemiology considers both spatial and temporal relationships; most long-term studies focus on spatial gradients at a given time, thus masking effects of cohort aging and other trends during follow-up. Our new analyses distinguished between these temporal effects by analyzing age deciles for which separate mortality risks had been estimated for nationwide levels of nitrogen oxides (NOx), benzene, and traffic density during four sequential follow-up subperiods, thus providing 40 sets of mortality risk coefficients. We used ordinary least squares regression to define relationships with subject age and follow-up year for the data set of 40 coefficients. We found strong nonlinear relationships between subject age and mortality coefficients for smoking, climate, poverty status, and air pollution; only smoking and climate coefficients changed over time as well. We concluded that these pollutant-mortality relationships reflected differences among the veterans’ residential locations rather than changes in their pollution exposures during follow-up. We saw no evidence that cleaner air reduced mortality.Implications: Recent air pollution mortality studies emphasize PM2.5 (particulate matter with an aerodynamic diameter <2.5 μm); we show associations with many other pollutants and a measure of traffic intensity. Control policies should thus be based on multipollutant analyses. We found no reduced risks with improved air quality after distinguishing cohort aging from purely temporal effects; longitudinal studies of accountability must thus account for changes in demography and exposures. Our studies of exposure timing indicate mainly coincident responses and no evidence for cumulative effects typical of smoking; we had no information on personal exposures. We found the strongest risks were associated with high-traffic locations rather than outdoor air quality per se.

Retrospective Assessment of Respirable Quartz Exposure for a Silicosis Study of the Industrial Sand Industry

In 2016, the OSHA PEL for crystalline silica was reduced, renewing interest in evaluating risk of silicosis from occupational exposures. The industrial sand industry, which deals with high-purity quartz sands, is the setting for a current epidemiologic investigation of silicosis risk and progression. In support of that investigation, respirable quartz (RQ) exposures were retrospectively estimated for 67 workers with silicosis and 167 matched control workers from 21 industrial sand plants, in which some started work as early as 1929. A job exposure matrix (JEM) was constructed by integrating a modern (post-1970) RQ exposure database containing more than 40000 measurements with archival particle count exposure data from a 1947 survey. A simulation algorithm was used to develop a conversion factor to convert the archival particle count data into modern measures of RQ by randomly generating 100000 virtual dust particles of varying diameters corresponding to the size distributions of 14 archival particle size distribution samples. The equivalent respirable mass and particle counts of the virtual particles were calculated, totalled, and ratioed to derive the conversion factor. The JEM was integrated with individual job histories to calculate average and cumulative exposure for each case and control. Multiple exposure estimates were derived for unprotected exposures as well as for exposures adjusted for estimated respiratory protective equipment use and efficiency. The mean of the count to respirable mass conversion factors derived from 14 archival particle size samples was 157 µg m-3 per mppcf (SD: 42; range: 96-263) with no statistical difference across process areas (drying, screening, vibrating, binning, bulk loading, bagging), P = 0.29. The JEM demonstrated an industry-wide decrease in prevailing exposures to RQ of up to about 2 orders of magnitude from the distant (1929) to the recent (2012) past. Unadjusted cumulative exposures for cases and controls were statistically different (P < 0.001) with respective medians (range) of 3764 µg m-3 year (221-25121) and 1595 µg m-3 year (0-16446). Adjustment of exposure for use of respiratory protection showed modest reductions in estimated exposure: median adjusted cumulative exposures assuming a protection factor of 5 were 86% and 77% of the unadjusted values for cases and controls, respectively. The industrial sand industry offers a unique setting for examination of silicosis risk because of the high silica content of industrial sand and a long history of radiographic silicosis surveillance of industry workers. However, the great majority of silicosis cases in this industry are found among former workers and are associated with exposures occurring in the distant past, which necessitates extensive retrospective exposure assessment and increases the likelihood of exposure misclassification. Nonetheless, the estimated cumulative exposures for silicosis cases and controls in this work were significantly different, with the median cumulative exposure for cases being more than twice that of their matched controls.

Correlation of pesticide exposure from dietary intake and bio-monitoring: The different sex and socio-economic study of children

Exposure to organophosphorus pesticides was assessed though bio-monitoring of urinary dialkyl phosphate metabolites to characterize children's exposure to pesticides. No reports have been found which evaluate exposure of pesticides among adolescents of different sexes. The primary objective was to develop a coupled exposure–dose modeling approach that can be used to determine the metabolite concentrations. Related objective was to determine any significant changes of pesticide exposure among the adolescents of different sexes. The primary objective was to develop a coupled exposure-dose modeling approach to determine the metabolites concentrations to keep children's urine metabolites levels below specified values considering exposures from water, and the food related objective was to determine any significant changes of pesticide exposure among the adolescents of different sexes. We recruited a sample of 377 children (188 boys, 189 girls) ages 6–10 and 11–15 years from Hyderabad, India for urine collection. Results showed that the mean concentrations of dialkyl phosphate metabolites in first morning first urine samples (3.05 µmol L−1) were strongly correlated with concentrations of the same-day 24-h samples (1.7 µmol L−1) ( r = 0.997, model R2 ≈ 0.994, p < 0.00) with 99.4% accuracy. Irrespective of similar amounts of conventional food consumption, girls showed 87.5% of detection frequency of DAP metabolites which was higher than the 74% detection frequency of DAP metabolites among boys. The female group showed (87%) higher pesticide metabolite levels than boys. This report may help to focus on new studies of the connection between adolescents of different sex and organophosphorus metabolite exposure and to develop an exposure database to facilitate health risk assessment in our day-to-day environment.

Availability of a New Job-Exposure Matrix (CANJEM) for Epidemiologic and Occupational Medicine Purposes.

The aim of this study was to introduce the Canadian job-exposure matrix (CANJEM). Four large case-control studies of cancer were conducted in Montreal, focused on assessing occupational exposures by means of detailed interviews followed by expert assessment of possible occupational exposures. Thirty-one thousand six hundred seventy-three jobs were assessed using a checklist of 258 agents (listed with prevalences at http://expostats.ca/chems). This large exposure database was configured as a JEM. CANJEM is available in four occupational classification systems. It provides estimates of probability of exposure among workers with a given occupation, and for those exposed, various metrics of exposure. CANJEM can be accessed online (www.canjem.ca) or in a batch version. CANJEM is a large source of retrospective exposure information, covering most occupations and many agents. CANJEM can be used to support exposure assessment efforts in epidemiology and occupational health.

NECID – nano exposure and contextual information database

Nanotechnology is a rapidly evolving field allowing to design and obtain new, previously unknown nanostructured materials with unique properties and broad application. In addition to the wide range of potential benefits, the use of nanoobjects can also endanger human health. Due to the divergent results of published studies about impact of nanoobjects on health, different exposure measurement strategies and non-uniform and limited documentation the possibilities for comparing different measurements, and as well the use of research results to simulate and construct mathematical models are limited. In order to harmonize documentation, research results, exposure indicators and context for exposure measurement, the NECID (Nano Exposure and Contextual Information Database) database, a digital documentation platform for occupational exposure to nanoparticles, has been developed.

Gender differences in occupational exposure to carcinogens among Italian workers

BackgroundMany carcinogenic chemicals are still used or produced in several economic sectors. The aim of this study is to investigate differences in occupational exposure patterns to carcinogens by gender in Italy.MethodsInformation about the most common carcinogens recorded in the Italian occupational exposures database (SIREP) for the period 1996–2015 was retrieved. Descriptive statistics were calculated for exposure-related variables (carcinogenic agent, occupational group, economic activity sector, and workforce size). The chi-square(χ2) test was used to verify differences between genders, and logistic regression analysis was performed to evaluate the association between gender and risk of having higher exposure levels, after adjusting for age. Concurrent exposures to multiple carcinogens were investigated using the two-step cluster analysis.ResultsA total of 166,617 exposure measurements were selected for 40 different carcinogens. Exposed workers were only in a small proportion women (9%), and mostly aged 20–44 years (70%) in both genders. Women were more likely to be exposed than men to higher levels for several carcinogens even after correction for age at exposure, and the exposure level was significantly (p < 0.01) associated with occupation, economic sector and workforce size. The five main clusters of co-exposures identified in the entire dataset showed a differential distribution across economic sectors between genders.ConclusionsThe exposures to occupational carcinogens have distinguishing characteristics in women, that are explained in part by work and job segregation. Because of the presence of high-exposed groups of female workers in many industrial sectors, further research and prevention efforts are recommended.

Occupational exposure monitoring data collection, storage, and use among state-based and private workers' compensation insurers

ABSTRACTDespite substantial financial and personnel resources being devoted to occupational exposure monitoring (OEM) by employers, workers' compensation insurers, and other organizations, the United States (U.S.) lacks comprehensive occupational exposure databases to use for research and surveillance activities. OEM data are necessary for determining the levels of workers' exposures; compliance with regulations; developing control measures; establishing worker exposure profiles; and improving preventive and responsive exposure surveillance and policy efforts. Workers' compensation insurers as a group may have particular potential for understanding exposures in various industries, especially among small employers. This is the first study to determine how selected state-based and private workers' compensation insurers collect, store, and use OEM data related specifically to air and noise sampling. Of 50 insurers contacted to participate in this study, 28 completed an online survey. All of the responding private and the majority of state-based insurers offered industrial hygiene (IH) services to policyholders and employed 1 to 3 certified industrial hygienists on average. Many, but not all, insurers used standardized forms for data collection, but the data were not commonly stored in centralized databases. Data were most often used to provide recommendations for improvement to policyholders. Although not representative of all insurers, the survey was completed by insurers that cover a substantial number of employers and workers. The 20 participating state-based insurers on average provided 48% of the workers' compensation insurance benefits in their respective states or provinces. These results provide insight into potential next steps for improving the access to and usability of existing data as well as ways researchers can help organizations improve data collection strategies. This effort represents an opportunity for collaboration among insurers, researchers, and others that can help insurers and employers while advancing the exposure assessment field in the U.S.

HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870

Abstract. The influence of social and economic change on the consequences of natural hazards has been a matter of much interest recently. However, there is a lack of comprehensive, high-resolution data on historical changes in land use, population, or assets available to study this topic. Here, we present the Historical Analysis of Natural Hazards in Europe (HANZE) database, which contains two parts: (1) HANZE-Exposure with maps for 37 countries and territories from 1870 to 2020 in 100 m resolution and (2) HANZE-Events, a compilation of past disasters with information on dates, locations, and losses, currently limited to floods only. The database was constructed using high-resolution maps of present land use and population, a large compilation of historical statistics, and relatively simple disaggregation techniques and rule-based land use reallocation schemes. Data encompassed in HANZE allow one to "normalize" information on losses due to natural hazards by taking into account inflation as well as changes in population, production, and wealth. This database of past events currently contains 1564 records (1870–2016) of flash, river, coastal, and compound floods. The HANZE database is freely available at https://data.4tu.nl/repository/collection:HANZE.

Estimation of Lead Exposure Prevalence in Korean Population through Combining Multiple Experts' Judgment based on Objective Data Sources.

Estimating carcinogen exposure prevalence is important for preventing occupational cancers. To develop the Korean version of CARcinogen EXposure (CAREX), a carcinogen surveillance system used in many countries, we estimated lead exposure prevalence in the Korean working population. We used three Korean nationwide data sources to obtain objective database-derived prevalences of lead exposure across industries: airborne lead measurement data from the work environment measurement database (WEMD), blood lead measurement data from the special health examination database (SHED), and lead exposure prevalence computed using data from the work environment condition survey (WECS), which is a nationwide occupational exposure survey. We also asked a panel of 52 experts with ≥20 years of experience in industrial hygiene practice for their judgment about lead exposure prevalence across industries after they reviewed the database-derived prevalences computed from the three exposure databases. We developed and compared various estimation methods for combining the experts' judgments. The 2010 census was used as the reference population to estimate the number of lead-exposed workers in 228 industries by multiplying the exposure prevalence by the number of workers in each industry. The database-derived prevalences of lead exposure in the 228 industries were calculated using data collected between 2009 and 2011 from the WEMD and SHED and from the 2009 WECS. From the various estimation methods assessed, the median values of experts' responses were selected as our estimates of lead exposure prevalence in each industry. As a result, it was estimated that 129,250 Korean workers were exposed to lead in 2010. Based on objective databases, we developed a method for estimating exposure prevalence for the CAREX system by combining experts' judgments. This work may offer an unbiased approach to the development process that accounts for the uncertainty in exposure.

Enhancing the Secured Software Framework using Vulnerability Patterns and Flow Diagrams

This article describes the process of simplifying the software security classification. The inputs of this process include a reference model from previous researcher and existing Common Vulnerabilities and Exposure (CVE) database. An interesting aim is to find out how we can make the secured software framework implementable in practice. In order to answer this question, some inquiries were set out regarding reference model and meta-process for classification to be a workable measurement system. The outputs of the process are the results discussion of experimental result and expert’s validation. The experimental result use the existing CVE database which serves as an analysis when a) the framework is applied on three mix datasets, and b) when the framework is applied on two focus datasets. The first explains the result when the framework is applied on the CVE data randomly which consist mix of vendors and the latter is applied on the CVE data randomly but on selective vendors. The metric used in this assessment are precision and recall rate. The result shows there is a strong indicator that the framework can produce acceptable output accuracy. Apart from that, several experts’ views were discussed to show the correctness and eliminate the ambiguity of classification rules and to prove the whole framework process.

Occupational Burden of Asbestos-Related Diseases in Korea, 1998-2013: Asbestosis, Mesothelioma, Lung Cancer, Laryngeal Cancer, and Ovarian Cancer.

BackgroundAsbestos exposure causes asbestos-related diseases (ARDs) including asbestosis, malignant mesothelioma, lung cancer, laryngeal cancer, and ovarian cancer. Although Korea used substantial amounts of asbestos in the past, no study has focused on its occupational burden of disease (OBD). Therefore, this study aimed to determine the OBDs of ARDs in Korea.MethodsThe CARcinogen Exposure (CAREX) database was used to determine the proportion of exposed population. Relative risks for lung cancer, laryngeal cancer, and ovarian cancer were used to determine the population-attributable fraction. Data for deaths caused by ARDs during 1998–2013 were obtained from the World Health Organization mortality database. The potential years of life lost (PYLL) and annual average PYLL (APYLL) indicated OBDs.ResultsIn Korea, the number of ARD-attributable deaths and PYLL due to all ARDs during 1998–2013 were 4,492 and 71,763.7, respectively. The number of attributable deaths and PYLL due to asbestosis, malignant mesothelioma, lung cancer, laryngeal cancer, and ovarian cancer were 37 and 554.2, 808 and 15,877.0, 3,256 and 47,375.9, 120 and 1,605.5, and 271 and 6,331.1, respectively; additionally, the APYLL were 15.0, 19.7, 14.6, 13.4, and 23.4, respectively, and the average age at death was 70.4, 62.6, 69.1, 69.9, and 61.8, respectively. Our study showed that although the use of asbestos has ceased in Korea, the incidence of ARDs tends to increase.ConclusionTherefore, efforts to reduce future OBDs of ARDs, including early detection and proper management of ARDs, are needed in Korea.