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Sue K Park 4 Articles
Reliability and Data Integration of Duplicated Test Results Using Two Bioelectrical Impedence Analysis Machines in the Korean Genome and Epidemiology Study.
Boyoung Park, Jae Jeong Yang, Ji Hyun Yang, Jimin Kim, Lisa Y Cho, Daehee Kang, Chol Shin, Young Seoub Hong, Bo Youl Choi, Sung Soo Kim, Man Suck Park, Sue K Park
J Prev Med Public Health. 2010;43(6):479-485.
DOI: https://doi.org/10.3961/jpmph.2010.43.6.479
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AbstractAbstract PDF
OBJECTIVES
The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. METHODS: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October 2007 and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. RESULTS: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low R2 values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all R2>0.9). CONCLUSIONS: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.
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  • Nutritional Consequences and Management After Gastrectomy
    Jae-Moon Bae
    Hanyang Medical Reviews.2011; 31(4): 254.     CrossRef
Cigarette Smoking and Mortality in the Korean Multi-center Cancer Cohort (KMCC) Study.
Eun Ha Lee, Sue K Park, Kwang Pil Ko, In Seong Cho, Soung Hoon Chang, Hai Rim Shin, Daehee Kang, Keun Young Yoo
J Prev Med Public Health. 2010;43(2):151-158.
DOI: https://doi.org/10.3961/jpmph.2010.43.2.151
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  • 31 Crossref
AbstractAbstract PDF
OBJECTIVES
The aim of this study was to evaluate the association between cigarette smoking and total mortality, cancer mortality and other disease mortalities in Korean adults. METHODS: A total of 14 161 subjects of the Korean Multi-center Cancer Cohort who were over 40 years of age and who were cancer-free at baseline enrollment reported their lifestyle factors, including the smoking status. The median follow-up time was 6.6 years. During the follow-up period from 1993 to 2005, we identified 1159 cases of mortality, including 260 cancer mortality cases with a total of 91 987 person-years, by the national death certificate. Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of cigarette smoking for total mortality, cancer mortality and disease-specific mortality, as adjusted for age, gender, the geographic area and year of enrollment, the alcohol consumption status, the education level and the body mass index (BMI). RESULTS: Cigarette smoking was significantly associated with an increased risk of total mortality, all-cancer mortality and lung cancer mortality (p-trend, <0.01, <0.01, <0.01, respectively). Compared to non-smoking, current smokers were at a higher risk for mortality [HR (95% CI)=1.3 (1.1-1.5) for total mortality; HR (95% CI)=1.6 (1.1-2.2) for all-cancer mortality; HR (95% CI)=3.9 (1.9-7.7) for lung cancer mortality]. CONCLUSIONS: This study's results suggest that cigarette smoking might be associated with total mortality, all-cancer mortality and especially lung cancer mortality among Korean adults.
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    Journal of Preventive Medicine and Public Health.2024; 57(4): 327.     CrossRef
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    Annals of Occupational and Environmental Medicine.2023;[Epub]     CrossRef
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    International Journal of Environmental Research and Public Health.2022; 19(6): 3493.     CrossRef
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    International Journal of Epidemiology.2022; 51(4): 1190.     CrossRef
  • Smoking May Affect Pulmonary Function through DNA Methylation: an Epigenome-Wide Association Study in Korean Men
    So-Young Kwak, Clara Yongjoo Park, Min-Jeong Shin
    Clinical Nutrition Research.2020; 9(2): 134.     CrossRef
  • Analysis of multidimensional factors in attempts to quit using tobacco by Korean adolescents
    Mi-Jung Kang, Hyunjin Lee, Mirae Jo
    Environmental Health and Preventive Medicine.2020;[Epub]     CrossRef
  • The impact of basic livelihoods condition on the current smoking: Applying the counterfactual model
    Minhyeok Choi
    Korean Journal of Health Education and Promotion.2019; 36(1): 53.     CrossRef
  • Levels of Health and Subjective Life Expectancy among Community-dwelling Elders in Korea
    Ji Yeon An
    Journal of Korean Gerontological Nursing.2018; 20(1): 22.     CrossRef
  • Association and affecting factor between smoking and suicide idea: Focusing on comparison between district
    Seonhwa Yu, So Young Kim, Bo Ram Park, Mi-na Jo, Siekeyong Kim, Jong Hyock Park
    Korean Journal of Health Education and Promotion.2018; 35(3): 1.     CrossRef
  • The relationship between smoking and stroke by general characteristics: using the 6th Korea national health and nutrition examination survey
    Younghee Nam, Hyunjung Jung, Yesoon Kim
    Journal of Digital Contents Society.2018; 19(7): 1323.     CrossRef
  • Gender-related difference in the relationship between smoking status and periodontal diseases: the propensity score matching approach
    Eun-Sil Choi, Hae-Young Kim
    Journal of Korean Academy of Oral Health.2017; 41(2): 122.     CrossRef
  • The association between smoking or passive smoking and cardiovascular diseases using a Bayesian hierarchical model: based on the 2008-2013 Korea Community Health Survey
    Whanhee Lee, Sung-Hee Hwang, Hayoung Choi, Ho Kim
    Epidemiology and Health.2017; 39: e2017026.     CrossRef
  • Psychosocial Factors Associated With Smoking Intention in Korean Male Middle School Students
    Jin Suk Ra, Yoon Hee Cho
    The Journal of School Nursing.2017; 33(5): 355.     CrossRef
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    Sang Eun Lee, Cheol Woong Yu, Kyungil Park, Kyung Woo Park, Jung-Won Suh, Young-Seok Cho, Tae-Jin Youn, In-Ho Chae, Dong-Ju Choi, Ho-Jun Jang, Jin-Shik Park, Sang-Hoon Na, Hyo-Soo Kim, Ki-Bong Kim, Bon-Kwon Koo
    Heart.2016; 102(2): 114.     CrossRef
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    Sounghoon Chang, Hyeongsu Kim, Vitna Kim, Kunsei Lee, Hyoseon Jeong, Jung-Hyun Lee, Soon-Ae Shin, Eunyoung Shin, Minsu Park, Eunjung Ko
    International Journal of Environmental Research and Public Health.2016; 13(2): 158.     CrossRef
  • The relationship between smoking and depressive symptoms among Korean adults
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    Korean Journal of Health Education and Promotion.2016; 33(2): 57.     CrossRef
  • C-reactive Protein Concentration Is Associated With a Higher Risk of Mortality in a Rural Korean Population
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    Journal of Preventive Medicine and Public Health.2016; 49(5): 275.     CrossRef
  • A Study on the Factors Related to Smoking and Smoking Conditions among College Students in Some Area
    Kyeong-Ah Kim
    Journal of the Korea Academia-Industrial cooperation Society.2016; 17(8): 465.     CrossRef
  • Comparison of the Health Status Between Korean Seniors and Overseas Korean Seniors in China and Japan
    Mi-Kyoung Cho, Ogcheol Lee, Gisoo Shin
    Journal of the Korea Academia-Industrial cooperation Society.2015; 16(3): 2079.     CrossRef
  • Combined Influence of Smoking Frequency and Intensity on Suicidal Ideation and Attempts in Korean High School Students
    Jin Suk Ra, Yoon Hee Cho, Hye Sun Kim
    Journal of the Korean Society of School Health.2015; 28(3): 168.     CrossRef
  • Factor Analysis of Effect on Cardiovascular Disease of Korean Police Officers
    Jingu Lee, Woojin Jeon, Jaehwan Cho
    Journal of the Korean Society of Radiology.2014; 8(1): 11.     CrossRef
  • How Computed Tomography Contrast Media and Magnetic Resonance Imaging Contrast Media Affect the Changes of Uptake Counts of201Tl
    Jin-Hyeok Lee, Hae-Kag Lee, Jae-Hwan Cho, Miju Cheon
    Journal of Magnetics.2014; 19(4): 372.     CrossRef
  • Influence of Physical Activity on Smoking Experience and Smoking Intensity in Korean High School Students
    Jin Suk Ra, Yoon Hee Cho
    Journal of the Korean Society of School Health.2014; 27(3): 181.     CrossRef
  • Attributable fraction of tobacco smoking on cancer using population-based nationwide cancer incidence and mortality data in Korea
    Sohee Park, Sun Ha Jee, Hai-Rim Shin, Eun Hye Park, Aesun Shin, Kyu-Won Jung, Seung-Sik Hwang, Eun Shil Cha, Young Ho Yun, Sue Kyung Park, Mathieu Boniol, Paolo Boffetta
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  • Risk Factors for Smoking Behaviors Among Adolescents
    Sung Suk Chung, Kyoung Hwa Joung
    The Journal of School Nursing.2014; 30(4): 262.     CrossRef
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    Shin Kyum Kim, Joon Hyuck Park, Jung Jae Lee, Seok Bum Lee, Tae Hui Kim, Ji Won Han, Jong Chul Youn, Jin Hyeong Jhoo, Dong Young Lee, Ki Woong Kim
    Archives of Gerontology and Geriatrics.2013; 56(1): 214.     CrossRef
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    Sang-Yeon Suh, Ju Hyun Lee, Sang Shin Park, Ah-Ram Seo, Hong-Yup Ahn, Woo Kyung Bae, Yong Joo Lee, Eunji Yim
    Journal of Korean Medical Science.2013; 28(6): 869.     CrossRef
  • The Association between Smoking, Alcohol Intake, and Low-Salt Diet: Results from the 2008 Community Health Survey
    In-Ae Chun, Jong Park, Mi-Ah Han, Seong-Woo Choi, So-Yeon Ryu
    Journal of the Korean Dietetic Association.2013; 19(3): 223.     CrossRef
  • Impact of Individual and Combined Health Behaviors on All Causes of Premature Mortality Among Middle Aged Men in Korea: The Seoul Male Cohort Study
    Chul Woo Rhee, Ji Young Kim, Byung Joo Park, Zhong Min Li, Yoon-Ok Ahn
    Journal of Preventive Medicine and Public Health.2012; 45(1): 14.     CrossRef
  • Mortality and Potential Years of Life Lost of lung cancer between Korea and OECD countries before and after the year 2000
    Dong-Seok Kim, Ji-Won Park, Soo-Won Kang
    Journal of the Korea Academia-Industrial cooperation Society.2011; 12(7): 3138.     CrossRef
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    Journal of the Korean Society for Research on Nicotine and Tobacco.2011; 2(1): 30.     CrossRef
Erratum.
Sue K Park, Ji Yeob Choi
J Prev Med Public Health. 2010;43(1):96-97.
DOI: https://doi.org/10.3961/jpmph.2010.43.1.96
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AbstractAbstract PDF
There was an error in the numbering of the references in page 375-376: Sue K. Park, Ji-Yeob Choi. Risk Assessment and Pharmacogenomics in Molecular and Genomic Epidemiology. J Prev Med Public Health 2009; 42(6): 371-6.
Summary
Risk Assessment and Pharmacogenetics in Molecular and Genomic Epidemiology.
Sue K Park, Ji Yeob Choi
J Prev Med Public Health. 2009;42(6):371-376.
DOI: https://doi.org/10.3961/jpmph.2009.42.6.371
  • 5,358 View
  • 61 Download
  • 3 Crossref
AbstractAbstract PDF
In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.
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Citations

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  • Selected LDLR and APOE Polymorphisms Affect Cognitive and Functional Response to Lipophilic Statins in Alzheimer’s Disease
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    Journal of Molecular Neuroscience.2020; 70(10): 1574.     CrossRef
  • Towards a personalized risk assessment for exposure of humans to toxic substances
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  • Effect of genetic and environmental influences on cardiometabolic risk factors: a twin study
    György Jermendy, Tamás Horváth, Levente Littvay, Rita Steinbach, Ádám L Jermendy, Ádám D Tárnoki, Dávid L Tárnoki, Júlia Métneki, János Osztovits
    Cardiovascular Diabetology.2011; 10(1): 96.     CrossRef

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