• 대한지역사회영양학회지
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• 제24권4호
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• pp.300-308
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• 2019

Objectives: This research was conducted to identify the consumers' food choice factors that affect the consumers' replacement of soft drinks with carbonated water. Methods: The present study used secondary data from a consumer panel survey conducted by the Rural Development Administration of Korea, and the data included the panel members' purchase records based on their monthly spending receipts. The survey asked the participants about their food choice factors and their personal responsibility for their health. This survey included independent variables for the consumers' food purchase factors. As a dependent variable, two types of groups were defined. The replacement group included those people who increased their purchase of carbonated water and decreased their purchase of soft drinks. The non-replacement group included those people who did not change their purchase patterns or they increased their purchase of soft drinks and they decreased their purchase of carbonated water. Logistic regression analysis was conducted to determine the consumers' food choice factors that were associated with replacing soft drinks with carbonated water. Results: The replacement group was significantly associated with (1) a younger age (OR=0.953), (2) being a housewife (OR=2.03), (3) higher income (OR=1.001) and (4) less concern about price (OR=0.819) when purchasing food. This group also showed (5) higher enjoyment (OR=1.328) when choosing food and (6) they took greater responsibly for their personal health (OR=1.233). Conclusions: This research is the first study to mainly focus on soft drinks and carbonated water. The result of this research showed that young, health-conscious consumers with a higher income and who are more interested in food have more possibilities to replace soft drinks with carbonated water. These research findings may be applied to consumers who have characteristics that are similar to the young health-conscious consumers and the results can help to suggest ways to reduce sugar intake and improve public health. However, this research has a limitation due to the application of secondary data. Therefore, a future study is needed to develop detailed survey questions about food choice factors and to extend these factors to all beverages, including soft drinks made with sugar substitutes, so as to reflect the growth of alternative industries that use artificial sweeteners or different types of sugar to make commercially available drinks.

• International Journal of Safety
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• 제11권2호
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• pp.15-21
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• 2012

This paper is aimed to develop an electrical fire detection system (EFDS) which can analyze the possibility of electrical fire for overcurrent, leakage current and arc signals of panel board in traditional market shop. The EFDS adopted fuzzy logic and precursory data for overcurrent, leakage current and arc signals to evaluate the possibility of electrical fire. The signals are obtained directly from panel board in traditional market shops and fuzzy membership function is obtained from experiment, simulation, expert's advice. The overcurrent data is acquired by thermal data of normal and abnormal states (partial disconnection) on the insulated electrical wire, in accordance with the increase of the current signal, The leakage current data is obtained under various environments. The arc signal is acquisited by waveforms of instantaneous value in time domain and frequency band in frequency domain. The Fuzzy algorithm for DB of EFDS consists of fuzzification, inference engine by Mamdani's method and defuzzification by center of gravity method. In order to verify the performance and reliability of EFDS, it was applied to Jeon-Ju traditional market shops (90 shops) in Korea. Results show that EFDS in this paper is useful in alarming the fire case, which will prevent severe damage to human beings and properties, and reduce the electrical fires in a vulnerable area of electrical disaster.

• 보건행정학회지
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• 제33권3호
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• pp.273-294
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• 2023

Background: Most developed countries are working to improve their universal health coverage systems. This study investigates regional disparities in unmet healthcare needs and their causes in South Korea. Additionally, it compares the unmet healthcare needs rate in South Korea with that of 33 European countries. Methods: The analysis incorporates information from 13,359 adults aged 19 or older, using data from the Korea Health Panel. The dependent variables encompass the experience of unmet healthcare needs and the three causes of occurrence: "burden of medical expenses," "time constraints," and "lack of care." The primary variable of interest is the region of residence, while control variables encompass 14 socio-demographic, health, and functional characteristics. Multivariable binary logistic regression analysis, accounting for the sampling design, is conducted. Results: The rate of unmet healthcare needs in Korea is 11.7% (95% confidence interval [CI], 11.0%-13.3%), which is approximately 30 times higher than that of Austria (0.4%). The causes of unmet healthcare needs, ranked in descending order, are "lack of care," "time constraints," and "burden of medical expenses." Predictive probabilities for experiencing unmet healthcare needs and each cause differ significantly between regions. For instance, the probability of experiencing unmet healthcare needs due to "lack of care" is approximately 10 times higher in Gangwon-do (13.5%; 95% CI, 13.0%-14.1%) than in Busan (1.3%; 95% CI, 1.3%-1.4%). The probability due to "burden of medical expenses" is approximately 14 times higher in Seoul (4.1%; 95% CI, 3.6%-4.6%) compared to Jeollanam-do (0.3%; 95% CI, 0.2%-0.4%). Conclusion: Amid rapid sociodemographic transitions, South Korea must make significant efforts to alleviate unmet healthcare needs and the associated regional disparities. To effectively achieve this, it is recommended that South Korea involves the National Assembly in healthcare policy-making, while maintaining a centralized financing model and delegating healthcare planning and implementation to regional authorities for their local residents-similar to the approaches of the United Kingdom and France.

• 보건행정학회지
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• 제21권2호
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• pp.159-178
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• 2011

Korea ranks high among the OECD member countries with a high out-of-pocket share. In 2006, the government implemented in full scale the policy of extending the health insurance benefit coverage. Included in the policy are lowering the out-of-pocket share of patients of serious case and expanding the medical bill ceiling system to mention just a few. This study proposes to confirm effectiveness of the benefit extension policy by identifying changes in 'out-of-pocket expenditure as a share of the ability to pay' and 'incidence rate of catastrophic health care expenditure' of each individual household as manifested before and after the benefit extension policy was implemented. The 1st and 3rd year data from the Korea Welfare Panel Study (KoWePS), conducted by the Korea Institute for Health and Social Affairs (KIHASA), were used for the analysis, where low-income households and ordinary households are sampled separately. While the absolute amount of 'out-of-pocket expenditure' occurred to the average household increased for the period 2005-2007, the 'out-of-pocket expenditure as a share of the ability to pay' decreased. At the same time, the share decreased in the case of low-income households and households with patients of chronic or serious case as contrasted with ordinary households. 'Incidence rates of catastrophic health care expenditure' of ordinary households for 2007 stood at 14.6%, 5.9% and 2.8% at the threshold of 10%, 20% and 30%, respectively. The rates decreased overall between 2005 and 2007, while those of low-income households with patients of serious case statistically significantly increased. An analysis of this study indicates that it is related with the medical bill ceiling system regardless of incomes introduced in 2007.

• 지능정보연구
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• 제24권2호
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• pp.111-124
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• 2018

본 연구는 만성질환 중의 하나인 고지혈증 유병을 예측하는 분류모형을 개발하고자 한다. 이를 위해 SVM과 meta-learning 알고리즘을 이용하여 성과를 비교하였다. 또한 각 알고리즘에서 성과를 향상시키기 위해 변수선정 방법을 통해 유의한 변수만을 선정하여 투입하여 분석하였고 이 결과 역시 각각 성과를 비교하였다. 본 연구목적을 달성하기 위해 한국의료패널 2012년 자료를 이용하였고, 변수 선정을 위해 세 가지 방법을 사용하였다. 먼저 단계적 회귀분석(stepwise regression)을 실시하였다. 둘째, 의사결정나무(decision tree) 알고리즘을 사용하였다. 마지막으로 유전자 알고리즘을 사용하여 변수를 선정하였다. 한편, 이렇게 선정된 변수를 기준으로 SVM, meta-learning 알고리즘 등을 이용하여 고지혈증 환자분류 예측모형을 비교하였고, TP rate, precision 등을 사용하여 분류 성과를 비교분석하였다. 이에 대한 분석결과는 다음과 같다. 첫째, 모든 변수를 투입하여 분류한 결과 SVM의 정확도는 88.4%, 인공신경망의 정확도는 86.7%로 SVM의 정확도가 좀 더 높았다. 둘째, stepwise를 통해 선정된 변수만을 투입하여 분류한 결과 전체 변수를 투입하였을 때보다 각각 정확도가 약간 높았다. 셋째, 의사결정나무에 의해 선정된 변수 3개만을 투입하였을 때 인공신경망의 정확도가 SVM보다 높았다. 유전자 알고리즘을 통해 선정된 변수를 투입하여 분류한 결과 SVM은 88.5%, 인공신경망은 87.9%의 분류 정확도를 보여 주었다. 마지막으로, 본 연구에서 제안하는 meta-learning 알고리즘인 스태킹(stacking)을 적용한 결과로서, SVM과 MLP의 예측결과를 메타 분류기인 SVM의 입력변수로 사용하여 예측한 결과, 고지혈증 분류 정확도가 meta-learning 알고리즘 중에서는 가장 높은 것으로 나타났다.

• 한국병원경영학회지
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• 제21권4호
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• pp.55-62
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• 2016

Purposes: The industry has specialized and fragmented than in the past. As a factor of economic growth and industrialization, the number of people employed in primary industry decreased and the number of people employed in secondary and third industry continuously increased. In modern times, incidence of chronic disease is increasing according to industrial development. So, the purpose of this study was to analyze the chronic disease according to Clark's industrial classification. Methodology: Data were derived from the 2012 Korea Health Panel. The sample was made up of 7,132 adult participants aged 20 or over selected Korea Health Panel by probability sampling from Korea. Binary logistic regression analysis was conducted to examine the main factors associated with chronic disease. Findings: The significant factors associated with chronic disease were gender, age, marital status, household member, education level, insurance type, disability, BMI, and industrial classification. Female, elderly, divorced(including bereavement, missing and separation), one-person households, less than high school graduation, medical aid, disability, obese and primary industry were confirmed chronic disease increases. Practical Implications: The study finds that primary industry's prevalence of chronic disease was higher than secondary and third industry. Therefore, this study aims to management and effort of the worker who engaged in the primary industry. Policy development is required to address inequality or popularization of the differences in these factors by conducting a study to define the working conditions and socio-economic factors between industry.

• 약학회지
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• 제56권1호
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• pp.66-69
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• 2012

This study aims to assess the aggregate contribution of new drugs to the increase in life expectancy. We constructed a panel data combining mortality data in KOSIS and a drug dataset generated by assigning new drugs listed in 2000~2009 to their respective ICD codes. We found that 10% increase in stock of new drug led to 0.13~0.27% increase in the probability of survival to age 65. Due to lack of disease-specific life table, we used indirect approach to estimate the effect of new drugs on longevity. Using ordinary least squares, the estimate of the probability of survival to age 65 (logarithm) on life expectancy for all ages was 24.92. In conclusion, the increase in life expectancy of the entire population in Korea between 2000 and 2009 resulting from NMEs is 1.95 years, which explains 46.6% of real increase in life expectancy.

• 보건의료산업학회지
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• 제10권3호
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• pp.185-197
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• 2016

Objectives : The purpose of this study was to identify the influencing factors of cell phone addiction in adolescents and to construct a cell phone addiction model for adolescents. Methods : Data from the 5th Korean Child-Youth Panel Survey (KCYPS) was analyzed with the SPSS 20.0 and 23.0 AMOS programs. Results : According to the model of this study, depression had statistically significant direct effects while emotional characteristics and parental abuse had statistically significant indirect effects on cell phone addiction in adolescents. School life adjustment had statistically significant direct and indirect effects on cell phone addiction in adolescents. Conclusions : Based on the results of this study, it is necessary to develop prevention and intervention programs to combat cell phone addiction in Korean adolescents.

• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.31-39
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• 2021

This study empirically examines the proposition that the domestic fundamentals of a nation can emerge as absorptive capacity factors to reap the benefits of inward FDI. The study is contextualized in Asia, set from1982 to 2017, and data is grouped into low-income and lower-middle-income economies, in comparison to high-income and upper-middle-income economies, catering to different geographical regions within Asia. The investigation is based on a series of absorptive capacity factors such as infrastructure, human capital, domestic credit, and health indicator. The methodological analysis is premised on dynamic panel structure and employs the Generalized Method of Moments (GMM) estimation technique. The empirical findings suggest that that the infrastructure variable appears to be the major absorptive capacity factor for both groups of countries. The health indicator, on the other hand, can help reap the benefits of inward FDI, but only if the threshold level is met. The selected economies must achieve this threshold level to reap the benefits of FDI. To absorb the benefits of inward FDI, countries must be proactive in providing sound infrastructure and implementing proper healthcare measures.

• 지역사회간호학회지
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• 제30권4호
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• pp.449-459
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• 2019

Purpose: The aim of this study is to explore different types of self-rated health trajectories among one-person households in Korea. Methods: We used five time-point data derived from Korea Health Panel (2011~2015). A latent growth curve modeling was used to assess the overall feature of self-rated health trajectory in one-person households, and a latent class growth modeling was used to determine the number and shape of trajectories. We then applied multinomial logistic regression on each class to explore the predicting variables. Results: We found that the overall slope of self-rated health in one-person households decreases. In addition, latent class analysis demonstrated three classes: 1) High-Decreasing class (i.e., high intercept, significantly decreasing slope), 2) Moderate-Decreasing class (i.e., average intercept, significantly decreasing slope), and 3) Low-Stable class (i.e., low intercept, flat and nonsignificant slope). The multinomial logistic regression analysis showed that the predictors of each class were different. Especially, one-person households with poor health condition early were at greater risk of being Low-Stable class compared with High-Decreasing class group. Conclusion: The findings of this study demonstrate that more attentions to one-person households are needed to promote their health status. Policymakers may develop different health and welfare programs depending on different characteristics of one-person household trajectory groups in Korea.