• Journal of Digital Convergence
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• v.20 no.4
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• pp.469-482
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• 2022

The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.

• Journal of Microbiology and Biotechnology
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• v.31 no.11
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• pp.1501-1507
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• 2021

Lagerstroemia ovalifolia Teijsm. & Binn. (LO) (crape myrtle) has reportedly been used as traditional herbal medicine (THM) in Java, Indonesia. Our previous study revealed that the LO leaf extract (LOLE) exerted anti-inflammatory effects on lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. Based on this finding, the current study aimed to evaluate the protective effects of LOLE in a mouse model of LPS-induced acute lung injury (ALI). The results showed that treatment with LPS enhanced the inflammatory cell influx into the lungs and increased the number of macrophages and the secretion of the inflammatory cytokines in the bronchoalveolar lavage fluid (BALF) of mice. However, these effects were notably abrogated with LOLE pretreatment. Furthermore, the increase of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2) and monocyte chemoattractant protein-1 (MCP-1) expression in the lung tissues of mice with ALI was also reversed by LOLE. In addition, LOLE significantly suppressed the LPS-induced activation of the MAPK/NF-κB signaling pathway and led to heme oxygenase-1 (HO-1) induction in the lungs. Additionally, in vitro experiments showed that LOLE enhanced the expression of HO-1 in RAW264.7 macrophages. The aforementioned findings collectively indicate that LOLE exerts an ameliorative effect on inflammatory response in the airway of ALI mice.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.45-51
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• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• Journal of the Korean Orthopaedic Association
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• v.56 no.4
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• pp.305-309
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• 2021

Purpose: This study analyzed the increase in disposal rate of femoral heads in the bone bank of a single hospital from medical disease and drug history, as assessed by the Korean health insurance review and assessment service. Materials and Methods: The disposal rate and cause of 340 femoral heads were analyzed according to the regulations of the bone bank based on the standard model of the Ministry of food and drug safety. Results: One hundred and seven (33%) of 323 femoral heads collected from 2009 to 2018, and 65 (46%) of 142 femoral heads collected from 2015 to 2018 were discarded. The most common causes were related to the history of dementia and the administration of radioisotope for nuclear medicine. Conclusion: The current methods and screening tools can lead to errors in disposing of the available tissues in a bone bank. Thus, improved standards and screening methods are needed.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.601-610
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• 2022

Although the number of people insured by private health insurance in Korea is steadily increasing, the household burden or the status of multiple purchasing for private health insurance has not been addressed. In this study, data of the 2011-2018 Korea Health Panel Survey was used to examine the purchasing trend of Korean households' private health insurance. Households with more than three private health insurance per household member were defined as the 'poly-purchases'. The logit model was applied to analyze factors associated with poly-purchase of private health insurance using 2018 cross-sectional data. From 2011 to 2018, the number of insurances purchased by Korean households increased (4.0 to 4.6), the number of insurances per capita increased (1.3 to 1.6), and the proportion of the poly-purchasing households increased (5.2% to 10.8%). As a result of logit analysis, the probability of poly-purchasing was increased when the household head was a woman, with a high level of education and income, and when the job of the household head was a service or sales. Poly-purchasing was less likely when the family was subsidized with Medical Aids and suffered with more chronic diseases. The results of this study serve basic evidence for establishing policies regarding private health insurance, such as establishing the relationship between public and private insurance.

• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.428-435
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• 2022

Objectives: The Indonesian Ministry of Health launched isoniazid preventive therapy (IPT) in 2016, with general practitioners (GPs) at the frontline of this program. However, the extent to which GPs have internalized this program remains uncertain. The aim of this study was to identify the knowledge and attitudes of GPs towards the IPT program in Indonesia. Methods: This study used an online, self-administered questionnaire distributed via e-mail and social messaging services. A logistic regression model was employed to identify the explanatory variables influencing the level of knowledge and attitudes toward IPT among GPs in Indonesia. An empirical analysis was conducted separately for each response variable (knowledge and attitudes). Results: Of the 418 respondents, 128 (30.6%) had a good knowledge of IPT. Working at a public hospital was the only variable associated with good knowledge, with an adjusted odds ratio (aOR) of 1.69 (95% confidence interval [CI], 1.02 to 2.81). Furthermore, 279 respondents (66.7%) had favorable attitudes toward IPT. In the adjusted logistic regression analysis, good knowledge (aOR, 0.55; 95% CI, 0.34 to 0.89), 1-5 years of work experience (aOR, 2.09; 95% CI, 1.21 to 3.60), and having experienced IPT training (aOR, 0.48; 95% CI, 0.25 to 0.93), were significantly associated with favorable attitudes. Conclusions: In general, GPs in Indonesia had favorable attitudes toward IPT. However, their knowledge of IPT was limited. GPs are an essential element of the IPT program in the country, and therefore, adequate information dissemination to improve their understanding is critical for the long-term viability and quality of the IPT program in Indonesia.

• The Korea Journal of Herbology
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• v.33 no.2
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• pp.59-67
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• 2018

Objective : Plantago asiatica L. has been used for many years in Korea, China, and Japan for the treatment of many diseases such as anti-inflammatory, anti-asthma and diuretic. But the anti-obesity effect of Plantaginis asiaticae Folium has not been studied yet. Thus, this study aimed to demonstrate the anti-obesity efficacy of Plantaginis asiaticae Folium water extract (PAF) in high fat diet-induced obesity animal model. Method : Male, five-weeks old C57BL/6 mice were divided into 5 groups; ND (normal diet + 0.9% saline), HFD (high-fat diet + 0.9% saline), PC (high-fat diet + Garcinia cambogia 500 mg/kg), PAF 100, 300 (high-fat diet + PAF 100, 300 mg/kg. Treatments were performed daily for 6 weeks per os. We evaluated the changes of body weight, white adipose tissues weight, hepatic and fecal lipids level, pancreatic lipase activity and lipid profiles in plasma. Result : Body weights, adipose tissue weights and FER were significantly lower in mice fed the high-fat diet with PAF treatment than in mice fed the high-fat diet alone. In plasma, TG, TC, LDL-C, ATS and ALT levels significantly decreased in PAF groups compared with HFD group. Also, hepatic triglyceride (TG) levels decreased and fecal TG increased in PAF groups compared to HFD group. In addition, the activity of pancreatic lipase was decreased in the PAF groups compared to that of HFD group. Conclusion: These results suggest PAF extract is effective in preventing and improvement obesity, so it might be a potential and safe material for anti-obesity agent of weight control or functional supplements.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.55-65
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• 2022

Recently, deep learning-based automated systems for identifying and detecting landmarks have been proposed. In order to train such a deep learning-based model without overfitting, a large amount of image and labeling data is required. Conventionally, an experienced reader manually identifies and labels landmarks in a patient's image. However, such measurement is not only expensive, but also has poor reproducibility, so the need for an automated labeling method has been raised. In addition, in the X-ray image, since various human tissues on the path through which the photons pass are displayed, it is difficult to identify the landmark compared to a general natural image or a 3D image modality image. In this study, we propose a geometric data augmentation technique that enables the generation of a large amount of labeling data in X-ray images. In addition, the optimal attention mechanism for landmark detection was presented through the implementation and application of various attention techniques to improve the detection performance of 16 major landmarks in the skull. Finally, among the major cranial landmarks, markers that ensure stable detection are derived, and these markers are expected to have high clinical application potential.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.151-168
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• 2021

This study compared and analyzed the effect of the burden of household expenditure in the metropolitan and non-metropolitan areas on the intention to childbirth intention to married women using a panel logit model. To this end, this analysis targeted married women aged 25 to 39 who are highly likely to be fertile. The main results are as follows; First of all, it was confirmed that the economic power of spouse can be an important factor in the childbirth intention regardless of region. Second, it was found that the higher the satisfaction of marriage had a positive effect on the childbirth intention, and also higher the value that children must have, the higher the childbirth intention. Third, it was confirmed that the burden of household expenditure is the most important factor in the willingness to childbirth intention, excluding factors such as the number of existing children. In particular, the burden on education spending in both the capital region and non-capital region was found to be a key reason for the decrease in the childbirth intention. Lastly, the burden of household expenditure showed different effects on childbirth intention on depending on the region. Specifically, in the capital region, medical spending and loans had a greater impact, while, in the non-capital region, transportation and communication costs had a greater impact on childbirth intentions. Through the results, this study confirmed the implication that easing the burden on household expenditure is continuously necessary to enhance childbirth, and that discriminatory policy approaches are required depending on the area of residence.

• Journal of Environmental Health Sciences
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• v.48 no.4
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• pp.236-243
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• 2022

Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.