• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.198-209
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• 2014

Diabetes Mellitus (DM) is well known for increasing morbidity and mortality, especially related to their complications. The purpose of this study was to investigate the factors affecting the prevalence rate of DM and provide a fundamental material to develop an intervention strategy to reduce the prevalence rate of DM. The study subjects were adults aged over 19 on the basis of the primitive data of "The Fifth Korean National Health and Nutrition Examination Survey, 2012". Therefore, the data of 5995 participants were analyzed. For data process, the complex sample analysis module of SPSS 18.0 program was employed to add weighting before analysis. According to the analysis, the prevalence rate of DM of the study subjects was 10.5%. Regarding the odds ratio of DM prevalence, the subjects who graduated from middle school had the odds ratio 2.51 times higher than those who graduated from college and more; those in subjective bad health condition 4.77 times higher than those in subjective good health condition; those in obesity 1.44 times higher; those with high blood pressure 2.57 times higher; those with hyperlipidemia 2.63 times higher; those who fail to control their weight 1.31 times higher; those going on a diet 2.75 times higher. This study revealed that a level of education, perceived health status, obesity, high blood pressure, hyperlipidemia, weight control, and dietary therapy were the predictable variables of the prevalence rate of DM, and thereby suggested the nursing direction and research direction to reduce the prevalence rate of DM.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6935-6940
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• 2013

Background: This study aimed to develop a prognostic model in patients with early-stage cervical squamous cell carcinoma based on clinicopathological features, including invasive margin characteristics. Materials and Methods: Clinicopathological features and outcomes of 190 patients with FIGO stage IB-IIA cervical squamous cell carcinoma treated by surgery were collected and analyzed for factors associated with tumor recurrence. In addition to well-recognized pathological risk factors, the pathological characteristics of invasive margin (type of invasive pattern and degree of stromal desmoplasia and peritumoral inflammatory reaction) were also included in the analysis. Multiple scoring models were made by matching different clinicopathological variables and/or different weighting of the score for each variable. The model with the best performance in the prediction of recurrence and decreased survival was selected. Results: The model with the best performance was composed of a combined score of invasive pattern, lymphovascular space invasion (LVSI), and degree of inflammatory reaction and stromal desmoplasia (total score =10). Compared to those with score ${\leq}8$, the patients with score 9-10 had a significantly higher recurrence rate in the overall group (p<0.001) and the subgroup without adjuvant therapy (p<0.001), while the significance was marginal in the subgroup with adjuvant therapy (p=0.069). In addition, the patients with score 9-10 had a higher rate of tumor recurrence at distant sites (p=0.007). The disease-free survival was significantly lower in the patients with score 9-10 than those with score ${\leq}8$ among the overall patients (p<0.001), in the subgroup without adjuvant therapy (p<0.001), and the subgroup with adjuvant therapy (p=0.047). Conclusions: In this study, a prognostic model based on a combination of pathological characteristics of invasive margin and LVSI proved to be predictive of tumor recurrence and decreased disease-free survival in patients with early-stage cervical squamous cell carcinoma.

• Journal of Korea Soil Environment Society
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• v.1 no.1
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• pp.89-102
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• 1996

An integrated model is presented to describe underground flow and mass transport, using a multicomponent multiphase approach. The comprehensive governing equation is derived considering mass and force balances of chemical species over four phases(water, oil, air, and soil) in a schematic elementary volume. Compact and systemati notations of relevant variables and equations are introduced to facilitate the inclusion of complex migration and transformation processes, and variable spatial dimensions. The resulting nonlinear system is solved by a multidimensional finite element code. The developed code with dynamic array allocation, is sufficiently flexible to work across a wide spectrum of computers, including an IBM ES 9000/900 vector facility, SP2 cluster machine, Unix workstations and PCs, for one-, two and three-dimensional problems. To reduce the computation time and storage requirements, the system equations are decoupled and solved using a banded global matrix solver, with the vector and parallel processing on the IBM 9000. To avoide the numerical oscillations of the nonlinear problems in the case of convective dominant transport, the techniques of upstream weighting, mass lumping, and elementary-wise parameter evaluation are applied. The instability and convergence criteria of the nonlinear problems are studied for the one-dimensional analogue of FEM and FDM. Modeling capacity is presented in the simulation of three dimensional composite multiphase TCE migration. Comprehesive simulation feature of the code is presented in a companion paper of this issue for the specific groundwater or flow and contamination problems.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.287-297
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• 2016

This study aims to identify the relationship between climatic factors and stand mean Diameter at Breast Height (DBH) for two major tree species; Pinus densiflora and Quercus mongolica in Andong-dam basin. Forest variables such as age, diameter distribution and number of trees per hectare from the $5^{th}$ and $6^{th}$ National Forest Inventory data were used to develop a DBH estimation model. Climate data were collected from six meteorological observatory station and twelve Automatic Weather System provided by Korea Meteorological Administration to produce interpolated daily average temperature map with Inverse Distance Weighting (IDW) method. Andong-dam basin reflects rugged mountainous terrain, so temperature were adjusted by lapse rate based correction. As a result, predictions of model were consistent with the previous studies; that the rising temperature is negatively related to the growth of Pinus densiflora whereas opposing trend is observed for Quercus mongolica.

• Journal of Preventive Medicine and Public Health
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• v.39 no.4
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• pp.317-324
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• 2006

Objectives: This study was conducted to estimate the unbiased smoking prevalence and its standard errors among adolescents in a large city in Korea, by design-based analysis. Methods: All the students in Daegu city were stratified by grade, gender and region, and then schools as primary sampling units (PSU) were selected by probability proportional to size (PPS) sampling. One or two classes were sampled randomly from each grade, from 5th grade in elementary schools to the 3rd grade in high schools. The students anonymously completed a standardized self-administered questionnaire from October to December 2004. The total number of respondents was 8,480 in the final analysis, excluding the third graders in the general high schools because of incomplete sampling. The sampling weight was calculated for each student after post-stratification adjustment, with adjustment being made for the missing cases. The data were analyzed with Stata 8.0 with consideration of PSU, weighting and the strata variables. Results: The smoking prevalence (%) and standard errors for male students from the fifth grade in elementary schools to the second grade in high schools were $0.93{\pm}0.47,\;1.83{\pm}0.74,\;3.16{\pm}1.00,\;5.12{\pm}1.02,\;10.86{\pm}1.13,\;15.63{\pm}2.44\;and\;17.96{\pm}2.67$, and those for the female students were $0.28{\pm}0.28,\;1.17{\pm}0.73,\;3.13{\pm}0.60,\;1.45{\pm}0.58,\;3.94{\pm}0.92,\;8.75{\pm}1.86\;and\;10.04{\pm}1.70$, sequentially. Conclusions: The smoking prevalence from this study was much higher than those from the other conventional studies conducted in Korea. The point estimates and standard errors from the design-based analysis were different from those of the model-based analysis. These findings suggest the importance of design-based analysis to estimate unbiased prevalence and standard errors in complex survey data and this method is recommended to apply to future surveys for determining the smoking prevalence for specific population.

• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• Korean Journal of Radiology
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• v.24 no.12
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• pp.1284-1292
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• 2023

Objective: We investigated the impacts of computed tomography (CT) added to ultrasound (US) for preoperative evaluation of patients with papillary thyroid carcinoma (PTC) on staging, surgical extent, and postsurgical survival. Materials and Methods: Consecutive patients who underwent surgery for PTC between January 2015 and December 2015 were retrospectively identified. Of them, 584 had undergone preoperative additional thyroid CT imaging (CT + US group), and 859 had not (US group). Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were used to adjust for 14 variables and balance the two groups. Changes in nodal staging and surgical extent caused by CT were recorded. The recurrence-free survival and distant metastasis-free survival after surgery were compared between the two groups. Results: In the CT + US group, discordant nodal staging results between CT and US were observed in 94 of 584 patients (16.1%). Of them, CT accurately diagnosed nodal staging in 54 patients (57.4%), while the US provided incorrect nodal staging. Ten patients (1.7%) had a change in the extent of surgery based on CT findings. Postsurgical recurrence developed in 3.6% (31 of 859) of the CT + US group and 2.9% (17 of 584) of the US group during the median follow-up of 59 months. After adjustment using IPTW (580 vs. 861 patients), the CT + US group showed significantly higher recurrence-free survival rates than the US group (hazard ratio [HR], 0.52 [95% confidence interval {CI}, 0.29-0.96]; P = 0.037). PSM analysis (535 patients in each group) showed similar HR without statistical significance (HR, 0.60 [95% CI, 0.31-1.17]; P = 0.134). For distant metastasis-free survival, HRs after IPTW and PSM were 0.75 (95% CI, 0.17-3.36; P = 0.71) and 0.87 (95% CI, 0.20-3.80; P = 0.851), respectively. Conclusion: The addition of CT imaging for preoperative evaluation changed nodal staging and surgical extent and might improve recurrence-free survival in patients with PTC.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.183-196
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• 2017

Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.281-293
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• 2020

Recently, large and small fires have been happening more often in Korea. Fire is one of the most frequent disasters along with traffic accidents in korean cities, and this frequency is closely related to the land use and the type of facilities. Therefore, in this study, the significance of fires was analyzed by considering land use, facility types, human and social factors and using 10 years of fire data in Jinju city. Based on this, OLS (Ordinary Least Square) regression analysis, SLM (Spatial Lag Model) and SEM (Spatial Error Model) using space weights, were compared and analyzed considering the location of the fire and each factor, then a statistical model with high suitability was presented. As a result, LISA analysis of spatial distribution patterns of fires in Jinju city was conducted, and it was proved that the frequency of fires was high in the order as follow, central commercial area, industrial area and residential area. Multiple regression analysis was performed by integrating demographic, social, and physical variables. Therefore, the three models were compared and analyzed by applying spatial weighting to the derived factors. As a result of the significance test, the spatial error model was analyzed to be the most significant. The facilities that have the highest correlation with fire occurrence were second type neighborhood facilities, followed by detached house, first type neighborhood facilities, number of households, and sales facilities. The results of this study are expected to be used as significant data to identify factors and manage fire safety in urban areas. Also, through the analysis of the standard deviation ellipsoid, the distribution characteristics of each facility in the residential area, industrial area, and central commercial area among the use areas were analyzed. In, the second type neighborhood facility with the highest fire risk was concentrated in the center. The results of these studies are expected to be used as useful data for identifying factors and managing fire safety in urban areas.