• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.248-257
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• 2023

Because of various societal changes, such as the recent improvement in income levels and extension of the flexible work system, the demand for forest recreation activities and their use patterns are undergoing a change. Accordingly, it is necessary to identify the characteristics of each type through the segmentation of the overall forest recreation and welfare markets and to plan differentiated policies for each market type. This study classifies the forest recreation and welfare activities according to four types of users (i.e., passive usage type, ordinary type, active lover type, and indifferent type) using the Latent Class Analysis and examines their demographic and socioeconomic characteristics to explain the differences between the groups. Three policy implications were derived from the results obtained: 1) the group experiencing forest recreation welfare is subdivided; 2) the socioeconomic characteristics that distinguish the groups undertaking forest recreation activities were identified; and 3) the policy targets and characteristics that can increase the experience of forest recreation welfare were identified. This study is insightful as it suggests differentiated policies for each group and proposes policy measures to move to the desirable group.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.127-138
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• 2019

This study was a secondary data analysis using statistics from the 13th (2017) Korea Youth Risk Behavior Web-based Survey (KYRBS) to investigate the relationship between health behaviors and physical activity among Korean adolescents. A total of 62,276 adolescents in middle and high schools enrolled in this study. Physical activity utilized moderate and vigorous physical activity variables. Health behaviors used smoking, drinking, eating, sedentary behavior, and sleep duration variables. Statistical analyses were performed applying complex sample analysis method. Chi-square tests were used to compare physical activity according to health behaviors. Multivariate multinomial logistic regression analyses were conducted to examine the relationship between health behaviors and physical activity, adjusted for general characteristics. Current smoking and current drinking were associated with high levels of moderate and vigorous physical activity. Consuming fruits≥1 times/day, vegetables≥3 times/day, and sweet drinks≥3 times/week were associated with high levels of moderate and vigorous physical activity. Eating breakfast≥5 times/week was associated with high levels of moderate physical activity, but not with vigorous physical activity. Sedentary behavior≥2 hour/day was associated with low levels of moderate and vigorous physical activity. Sleep duration<7 hour/day was associated with high levels of moderate physical activity and low levels of vigorous physical activity. These findings suggest that since there is an interrelationship between health behaviors and physical activity among adolescents, intervention programs aiming at promoting physical activity and healthy lifestyles should consider a multiple behavior approach rather than an individual behavior approach.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.89-100
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• 2024

Purpose : The objective of this study was to determine the major factors influencing the onset of diabetes and prediabetes and for collection of the basic data required to reduce the prevalence of diabetes and plan for administration of an effective health care system. By classifying the level of blood sugar management according to three categories: normal, prediabetes, and diabetes diagnosis, and determining the causes of diabetes in consideration of various variables, we will conduct an analysis of the main factors to be addressed for effective management of blood sugar and for preparation of basic data for use in early management. Methods : In this study, an analysis of raw data from the 8th National Health and Nutrition Examination Survey collected over a period of three years from 2019 to 2021, including 8,110 subjects in 2019, 7,359 subjects in 2020, and 7,090 subjects in 2021 was performed. A total of 22,559 subjects were aged 19 years or older, and 15,821 subjects were classified as subjects for inclusion in the final analysis. In the analysis, categorical variables were tested for difference, analysis of continuous variables using regression was performed, and analysis of influencing factors was performed using multinomial logistic analysis. Result : Significant factors related to the onset of diabetes and prediabetes included age (p<.001), marital status (p<.001), occupation (p<.001), hypertension (p<.001), dyslipidemia (p<.001), cardiovascular disease (p=.008), alcohol (p=.030) smoking (p=.005), systolic blood pressure (p<.001), diastolic blood pressure (p<.001), body mass index (p<.001) and waist circumference (p=.037), blood triglycerides (p<.001), and blood cholesterol (p<.001). Conclusion : Diabetes, a complex disease affected by a variety of diseases, requires active management from the prediabetes stage, and providing an appropriate level of medical information and services to elderly individuals without family support is considered a long-term health care system requirement in Korean society where the demographic structure is changing. In particular, determining the causes of prediabetes and development of a preventive approach to administering the health care system will be important for efficient management of diabetic patients.

• Health Policy and Management
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• v.34 no.1
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• pp.48-58
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• 2024

Background: The purpose of this study was to investigate the association between external medical service use and the characteristics of Chungcheongnam-do patients. We aimed to provide evidence of external medical service use enhance the healthcare delivery system in Chungcheongnam-do. Methods: We used the Health Insurance Cohort DB 2.0 of 2016-2019, and 2,570,439 patients were included in the study. Multivariate logistic regression and multinomial logistic regression were used to identify the association between external medical service use and each patient characteristic. Generalized linear model was used to identify the association between medical costs and external medical service use area. Results: During the study period, 32.2% of inpatients and 12.5% of outpatients had external medical service use in Chungcheongnam-do. In comparison to patients living in Cheonan and Asan, the odds ratio (OR) for external medical services use was higher across all regions. Specifically, hospitalized patients from Gyeryong, Nonsan, and Geumsan (OR, 116.817) and Gongju, Buyeo, and Cheongyang (OR, 72.931) demonstrated extremely high likelihood of external medical service use in the Daejeon area. Furthermore, compared to medical expenses incurred within Chungcheongnam-do, patients with external medical service use in the capitol area (outpatient=17.01%, inpatients=22.11%) and Daejeon area (outpatient=16.63%, inpatients=15.41%) spent more on healthcare services. Conclusion: This study found the evidence of external medical service use among Chungcheongnam-do patients. Further study should be conducted taking into account variables including satisfaction of local medical services, different types of patient diseases, and others. The study's findings may serve as a foundation for policy proposals aimed at ensuring the financial stability of our health insurance system, ensuring the efficient delivery of medical care, and localization of medical care.

• Journal of dental hygiene science
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• v.11 no.2
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• pp.99-105
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• 2011

In this study a survey was conducted with 431 students at the department of dental hygiene in three regions from April 2010 to investigate various actual states and levels of perception of their major commitment. Department-Climate and levels of major commitment were classified and described through cross-tabulation analysis; multinomial logistic regression analysis was used to predict the level of major commitment perceived for department climate and identify its influence. Major commitment classified into three levels about Inferiority, Normality and Superiority. Recognition factor of Major field was divided into external factor, eternal factor. External factor classified into professor, friends, facilities, administration-service and quality of education. As well as, eternal factor was department climate. Eternal factor consisted of relationship dimensions, goal-orientation dimensions, system maintenance dimensions and system change dimensions. This study was conducted to get a phenomenal understanding of students' learning in the major field and their school life. With this study, if friends and professor raise students at the Department of Dental Hygiene's department-climate recognition, their major-commitment will rise. And high major-commitment will be bring about their professional ability.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Investigative Magnetic Resonance Imaging
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• v.14 no.1
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• pp.47-55
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• 2010

Purpose : To evaluate the geometry of carotid artery by assessing the images of contrast-enhanced MR angiography (CE-MRA) and interrelationships between the geometry of carotid artery and clinical factors. Materials and Methods : 216 consecutive patients who performed supraaortic CE-MRA with fast spoiled gradient-echo imaging were included. Their medical records were reviewed for variable information including risk factors predictive of generalized atherosclerotic disease (age, hypertension (HTN), diabetes mellitus, hyperlipidema, and smoking), sex, body weight, height, and body mass index (BMI). We reviewed the CE-MRA with carotid origin (3 types), carotid artery tortuosity, angle of internal carotid artery bifurcation, the type of aortic arch branching, and the presence of the coiling of carotid artery. Results : Multinomial logistic regression analysis showed that significantly contributed clinical backgrounds for carotid origin were the age and the BMI. With an increase of age at 1, the probability that the type of carotid origin become from type 1 to type 2 was 0.9 times (p=0.004) in right carotid artery (RCA), 0.9 times (p = 0.031) in left carotid artery (LCA), 0.9 times that are likely to be type3 from type 2 (p<0.001) in RCA and 0.9 times in LCA (p=0.009). Increase in BMI at 1 increased odds of becoming type 2 as 1.1 times (p = 0.067) in RCA, 1.1 times (p=0.009) in LCA and increased chance of becoming type 3 as 1.2 times (p = 0.001) in RCA, 1.2 times (p=0.003) in LCA. Mean value of right and left carotid tortuosity were $240.9{\pm}69.0^{\circ}$and $154.4{\pm}55.0^{\circ}$, respectively. Conclusion : The BMI, age, sex and presence of HTN affects the geometry of carotid arteries, the site of origin and tortuosity of carotid artery specifically.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.591-599
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• 2016

Among the employer-supported subscribers to the National Health Insurance Service, 6,797 people with mild disabilities with western ages of 20 and up and who received health checkups were investigated. Of these 6,797 people, 3,186 and 3,611 received health checkups in 2009 and 2013, respectively. Those people who were diagnosed with physical handicaps, brain lesions, visual impairment, hearing impairment, intellectual disabilities, mental disorders, kidney disorders or other disorders according to the classification standard for people with disabilities were classified into disability groups of the 3rd through 6th degrees. The purpose of this study was to examine the dangerous influence of obesity of people with mild disabilities on their hyperglycemia, hypertension and high cholesterol. The items measured in this study were abdominal obesity, body mass index, fasting glucose, total cholesterol, systolic blood pressure and diastolic blood pressure. To look for connections between the obesity level and at-risk groups for each disease, cross tabulation and multinomial logistic regression analyses were utilized. Higher levels of abdominal obesity and BMI were found among those who were male, were younger and had higher incomes. The risks of abdominal obesity and BMI were higher in the abnormal groups for each disease. In 2009, the obesity group whose BMI was higher had a 1.51-fold higher risk of hypertension than the normal group. The abdominal obesity group had a 1.59-fold higher risk of high cholesterol, a 1.26-fold higher risk of hypertension and a 1.54-fold higher risk of hyperglycemia than the normal group. In 2013, the obesity group whose BMI was higher had a 1.72-fold higher risk of high cholesterol and a 1.43-fold higher risk of hypertension than the normal group. Those with abdominal obesity had a 1.59-fold higher risk of hyperglycemia than the normal subjects. As the risk of obesity was higher in those with disabilities than in those without disabilities, the former should be encouraged to undergo health checkups on a regular basis, and the coverage of the health checkups should be extended to keep track of their illness. In addition, appropriate education and concern are both required to prevent obesity.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.561-584
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• 2021

This study was conducted to classify 601 Korean adults into latent classes according to their love types and identify the differences in depression and find variables that affect the latent classes classification. As a result of the latent class analysis, the latent group for love types of Korean adults were classified into the L-H (7.7%) group, which showed the highest level of all three factors of intimacy, passion, and commitment, and the L-MH (33.6%) group, which all three factors were higher than the average, the L-M (39.8%) group with the mean of all three factors, the L-ML (14.6%) group with all three factors lower than the mean, and the L-L (4.3%) group with the lowest all three factors. Also, as a result of ANOVA, the L-MH group was psychologically healthier and more adaptive than the L-ML group. As a result of multinomial logistic analysis, females were more likely to belong to L-M, L-ML and L-L groups than males. In addition, singles were more likely to belong to the L-M and L-ML groups than those who were married. Also, the higher the anxiety attachment level, the higher the likelihood of belonging to the L-M, L-ML, and L-L groups than the L-H and L-MH groups, the L-ML and L-L groups than the L-M groups, and the L-L group rather than the L-ML groups. However, age, neuroticism, and emotional regulation did not affect the classification of latent classes. This study is meaningful in that it identified the various latent classes for the love types of Korean adults more three-dimensionally and suggested the possibility of differential interventions according to the characteristics of each group.