• Title/Summary/Keyword: $LPA_5$

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Predicting Healthy Lifestyle Patterns in Older Community Dwelling Adults: A Latent Profile Analysis (잠재프로파일 분석을 활용한 한국 노인 라이프스타일 유형화와 영향요인 분석)

  • Park, Kang-Hyun;Yang, Min Ah;Won, Kyung-A;Park, Ji-Hyuk
    • Therapeutic Science for Rehabilitation
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    • v.10 no.2
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    • pp.75-93
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    • 2021
  • Objective : The aim of this study was to identify subgroups of older adults with respect to their lifestyle patterns and examine the characteristics of each subgroup in order to provide a basic evidence for improving the health and quality of life. Methods : This cross-sectional study was conducted in South Korea. Community-dwelling older adults (n=184) above the age of 65 years were surveyed from April 2019 to May 2019. This study used latent profile analysis to examine the subgroups. Chi-squared (χ2) and multinomial logistic regression measures were then used to analyze individual characteristics and influencing factors. Results : The pattern of physical activity which is one of the lifestyle domains in elderly was categorized into three types: 'passive exercise type (31.1%)', 'low intensity exercise type (54.5%)', and 'balanced exercise type(14.5%)'. Activity participation was divided into three patterns: 'inactive type (12%)', 'self-management type (61%)', and 'balanced activity participation type (27%)'. In terms of nutrition, there were only two groups: 'overall malnutrition type (13.5%)' and 'balanced nutrition type (86.5%)'. Furthermore, as a result of the multinomial logistic regression analysis to understand the effects of lifestyle types on the health and quality of life of the elderly, it was confirmed that the health and quality of life were higher in those following an active and balanced lifestyle. In addition, gender, education level and residential area were analyzed as predictive factors. Conclusion : The health and quality of life of the elderly can be improved when they have balanced lifestyle. Therefore, an empirical and policy intervention strategy should be developed and implemented to enhance the health and quality of life of the elderly.

Morphologic Changes of the Pulmonary Arteries after Stent Implantation on Branch Pulmonary Artery Stenosis - Impact of Pulmonary Insufficiency - (폐동맥 분지협착에 스텐트 삽입 후 유발되는 폐동맥의 형태변화 - 폐동맥 폐쇄 부전의 역할 -)

  • Kim, Me Jin;Kang, Du Cheol;Choi, Jae Young;Lee, Jong Kyun;Sul, Jun Hee;Lee, Sung Kyu
    • Clinical and Experimental Pediatrics
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    • v.46 no.1
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    • pp.67-75
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    • 2003
  • Purpose : Intravascular stent implantation for the treatment of postoperative branch pulmonary artery(PA) stenosis has been used successfully. However, the cross sectional area of contralateral branch PA does not regress in spite of the successful dilation of the stenotic branch PA after stent implantation. We analyzed the morphologic and hemodynamic factors on the size of branch PA after successful stent implantation. Methods : The subjects in our study were 23 children who had undergone stent implantaion from Jan. 1995 to Jul. 2002 in the Division of Yonsei Pediatric Cardiology. We evaluated the cross sectional area index(CSAI) of branch PA before and after stent implantation at follow-up catheterization. We also investigated factors such as residual pulmonary stenosis, pulmonary regurgitation(PR), systolic pressure of right ventricle, and lung perfusion scan. Results : The CSAI of the RPA without stenosis changed from mean $238{\pm}17mm^2/BSA$ to mean $249{\pm}20mm^2/BSA$(P=0.47), but didn't regress. The CSAI of the LPA with stenosis was increased effectively by stent implantation from the mean $102{\pm}12mm^2/BSA$ to mean $125{\pm}11mm^2/BSA$(P< 0.05). At follow up after stent implantation, the CSAI of PA is correlated with the residual PR fraction after stent implantation. Conclusion : In a group with increased residual PR, CSAI of RPA was found to be significantly increased between the pre- and post-stages of stent implantation. So, we suspect that the pulmonary regurgitation remaining after right ventricle outlet tract(RVOT) dilatation surgery is correlated with the increase in CSAI of RPA.