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Su Young Kim 4 Articles
The Incidence of Stroke by Socioeconomic Status, Age, Sex, and Stroke Subtype: A Nationwide Study in Korea
Su Ra Seo, Su Young Kim, Sang-Yi Lee, Tae-Ho Yoon, Hyung-Geun Park, Seung Eun Lee, Chul-Woung Kim
J Prev Med Public Health. 2014;47(2):104-112.   Published online March 31, 2014
DOI: https://doi.org/10.3961/jpmph.2014.47.2.104
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  • 29 Crossref
AbstractAbstract PDF
Objectives

To date, studies have not comprehensively demonstrated the relationship between stroke incidence and socioeconomic status. This study investigated stroke incidence by household income level in conjunction with age, sex, and stroke subtype in Korea.

Methods

Contributions by the head of household were used as the basis for income levels. Household income levels for 21 766 036 people were classified into 6 groups. The stroke incidences were calculated by household income level, both overall within income categories and further by age group, sex, and stroke subtype. To present the inequalities among the six ranked groups in a single value, the slope index of inequality and relative index of inequality were calculated.

Results

In 2005, 57 690 people were first-time stroke patients. The incidences of total stroke for males and females increased as the income level decreased. The incidences of stroke increased as the income level decreased in those 74 years old and under, whereas there was no difference by income levels in those 75 and over. Intracerebral hemorrhage for the males represented the highest inequality among stroke subtypes. Incidences of subarachnoid hemorrhage did not differ by income levels.

Conclusions

The incidence of stroke increases as the income level decreases, but it differs according to sex, age, and stroke subtype. The difference in the relative incidence is large for male intracerebral hemorrhage, whereas the difference in the absolute incidence is large for male ischemic stroke.

Summary

Citations

Citations to this article as recorded by  
  • The relationship of income on stroke incidence in Finland and China
    Honghui Yao, Liina Junna, Yaoyue Hu, Xinping Sha, Pekka Martikainen
    European Journal of Public Health.2023; 33(3): 360.     CrossRef
  • Exploring the bidirectional causal link between household income status and genetic susceptibility to neurological diseases: findings from a Mendelian randomization study
    Weidong Nong, Gui Mo, Chun Luo
    Frontiers in Public Health.2023;[Epub]     CrossRef
  • Associations between socioeconomic status and stroke in American adults: A population-based study
    Jinming Fan, Wuqin Ma, Junbin Liu, Wenhan Li, Wenhao Wang, Jinyan Gu, Bin Zhou
    Preventive Medicine Reports.2023; 35: 102354.     CrossRef
  • Effect of income level on stroke incidence and the mediated effect of simultaneous diagnosis of metabolic syndrome diseases; a nationwide cohort study in South Korea
    Seungmin Jeong, Sung-il Cho, So Yeon Kong
    Diabetology & Metabolic Syndrome.2022;[Epub]     CrossRef
  • Temporal trend of first-ever ischaemic stroke incidence from 2010 to 2019 in South Korea: a nationwide retrospective cohort study
    Jeehye Lee, Hyeongsu Kim, Jusun Moon, Jinyoung Shin, Hojin Jeong, Youngtaek Kim
    BMJ Open.2022; 12(8): e059956.     CrossRef
  • Effect of Income Level on Stroke Incidence and Mediated Effects of Medication Adherence in Newly Diagnosed Hypertensive Patients: A Causal Mediation Analysis Using a Nationwide Cohort Study in South Korea
    Seungmin Jeong, So Yeon Kong, Seung-sik Hwang, Sung-il Cho
    Journal of Health Informatics and Statistics.2022; 47(4): 268.     CrossRef
  • Association Between Carbon Monoxide Intoxication and Incidence of Ischemic Stroke: A Retrospective Nested Case-Control Study in South Korea
    Kyeongmin Kwak, Min Kim, Won-Jun Choi, Young-Su Ju, Jong-Tae Park
    Journal of Stroke and Cerebrovascular Diseases.2021; 30(2): 105496.     CrossRef
  • Socioeconomic Disparities in Cardiovascular Health in South Korea
    Chi-Young Lee, Eun-Ok Im
    Journal of Cardiovascular Nursing.2021; 36(1): 8.     CrossRef
  • Sex-based differences in and risk factors for metabolic syndrome in adults aged 40 years and above in Northeast China: Results from the cross-sectional China national stroke screening survey
    Feng-E Li, Fu-Liang Zhang, Peng Zhang, Dong Liu, Hao-Yuan Liu, Zhen-Ni Guo, Yi Yang
    BMJ Open.2021; 11(3): e038671.     CrossRef
  • Risk of major bleeding by ethnicity and socioeconomic deprivation among 488,107 people in primary care: a cohort study
    Wai Chung Tse, Corina Grey, Matire Harwood, Rod Jackson, Andrew Kerr, Suneela Mehta, Katrina Poppe, Romana Pylypchuk, Sue Wells, Vanessa Selak
    BMC Cardiovascular Disorders.2021;[Epub]     CrossRef
  • Epidemiology of cardiovascular disease and its risk factors in Korea
    Hyeon Chang Kim
    Global Health & Medicine.2021; 3(3): 134.     CrossRef
  • Korea Heart Disease Fact Sheet 2020: Analysis of Nationwide Data
    Hyeok-Hee Lee, So Mi Jemma Cho, Hokyou Lee, Jongmin Baek, Jang-Ho Bae, Wook-Jin Chung, Hyeon Chang Kim
    Korean Circulation Journal.2021; 51(6): 495.     CrossRef
  • The Contribution of Material, Behavioral, Psychological, and Social-Relational Factors to Income-Related Disparities in Cardiovascular Risk Among Older Adults
    Chiyoung Lee, Qing Yang, Eun-Ok Im, Eleanor Schildwachter McConnell, Sin-Ho Jung, Hyeoneui Kim
    Journal of Cardiovascular Nursing.2021; 36(4): E38.     CrossRef
  • Socioeconomic status and lifestyle in young ischaemic stroke patients: a possible relationship to stroke recovery and risk of recurrent event
    David Franc, Daniel Šaňák, Petra Divišová, Lucie Lysková, Andrea Bártková, Jana Zapletalová, Michal Král, Tomáš Dorňák, Petr Polidar, Tomáš Veverka, Petr Kaňovský
    Central European Journal of Public Health.2021; 29(3): 223.     CrossRef
  • A cohort study on the relationship between education level and high‐risk population of stroke
    Yan‐Yan Yu, Dan Lei, Qiong He, Wei Chen
    Ibrain.2021; 7(3): 181.     CrossRef
  • Comparing Activity and Participation between Acquired Brain Injury and Spinal-Cord Injury in Community-Dwelling People with Severe Disability Using WHODAS 2.0
    Seo Yeon Yoon, Ja-Ho Leigh, Jieun Lee, Wan Ho Kim
    International Journal of Environmental Research and Public Health.2020; 17(9): 3031.     CrossRef
  • Lifetime risks and health impacts of hemorrhagic and ischemic stroke in South Korea
    Soyeon Cheon, Hyangsook Lee, Jiyoon Won, Bo-Hyoung Jang, Jung-Der Wang
    Scientific Reports.2020;[Epub]     CrossRef
  • Association between socioeconomic status and incident stroke in China
    Weiju Zhou, Ruoling Chen, Alex Hopkins, Yulong Wang, Jie Tang, Xiangyan Chen, Angela Clifford, Yuesong Pan, Ken Forthby, Jindong Ni, Duolao Wang, Eric Brunner
    Journal of Epidemiology and Community Health.2020; 74(6): 519.     CrossRef
  • Effects of socioeconomic status on risk of ischemic stroke: a case-control study in the Guangzhou population
    Siping Wang, Binyan Shen, Meiting Wu, Ciyu Chen, Juan Wang
    BMC Public Health.2019;[Epub]     CrossRef
  • Is androgen deprivation therapy associated with cerebral infarction in patients with prostate cancer? A Korean nationwide population‐based propensity score matching study
    Bum Sik Tae, Byeong Jo Jeon, Hoon Choi, Jae Hyun Bae, Jae Young Park
    Cancer Medicine.2019; 8(9): 4475.     CrossRef
  • Measurement of Socioeconomic Position in Research on Cardiovascular Health Disparities in Korea: A Systematic Review
    Chi-Young Lee, Yong-Hwan Lee
    Journal of Preventive Medicine and Public Health.2019; 52(5): 281.     CrossRef
  • Factors influencing return to work after stroke: the Korean Stroke Cohort for Functioning and Rehabilitation (KOSCO) Study
    Junhee Han, Hae In Lee, Yong-Il Shin, Ju Hyun Son, Soo-Yeon Kim, Deog Young Kim, Min Kyun Sohn, Jongmin Lee, Sam-Gyu Lee, Gyung-Jae Oh, Yang-Soo Lee, Min Cheol Joo, Eun Young Han, Won Hyuk Chang, Yun-Hee Kim
    BMJ Open.2019; 9(7): e028673.     CrossRef
  • Selected Food Consumption Mediates the Association between Education Level and Metabolic Syndrome in Korean Adults
    Oh Yoen Kim, So-Young Kwak, Boeun Kim, Young-Sun Kim, Hye Young Kim, Min-Jeong Shin
    Annals of Nutrition and Metabolism.2017; 70(2): 122.     CrossRef
  • Temporal trends in educational inequalities in non-communicable diseases in Korea, 2007-2015
    Gyu Ri Kim, Chung Mo Nam, C. Mary Schooling
    PLOS ONE.2017; 12(12): e0190143.     CrossRef
  • Impact of Patients' Income on Stroke Prognosis
    Ali Seifi, Ross-Jordon Elliott, Marwah A. Elsehety
    Journal of Stroke and Cerebrovascular Diseases.2016; 25(9): 2308.     CrossRef
  • Promoter Polymorphism (-174, G/C) of Interleukin-6 and Arterial Thromboembolic Events: A Meta-Analysis
    Su Kang Kim, Joo-Ho Chung, Oh Young Kwon
    Medical Science Monitor.2016; 22: 4345.     CrossRef
  • The ACC/AHA 2013 pooled cohort equations compared to a Korean Risk Prediction Model for atherosclerotic cardiovascular disease
    Keum Ji Jung, Yangsoo Jang, Dong Joo Oh, Byung-Hee Oh, Sang Hoon Lee, Seong-Wook Park, Ki-Bae Seung, Hong-Kyu Kim, Young Duk Yun, Sung Hee Choi, Jidong Sung, Tae-Yong Lee, Sung hi Kim, Sang Baek Koh, Moon Chan Kim, Hyeon Chang Kim, Heejin Kimm, Chungmo Na
    Atherosclerosis.2015; 242(1): 367.     CrossRef
  • The effects of socioeconomic status on stroke risk and outcomes
    Iain J Marshall, Yanzhong Wang, Siobhan Crichton, Christopher McKevitt, Anthony G Rudd, Charles D A Wolfe
    The Lancet Neurology.2015; 14(12): 1206.     CrossRef
  • Carotid Plaque Morphology Is Significantly Associated With Sex, Age, and History of Neurological Symptoms
    Carina Wendorff, Heiko Wendorff, Jaroslav Pelisek, Pavlos Tsantilas, Alexander Zimmermann, Alma Zernecke, Andreas Kuehnl, Hans-Henning Eckstein
    Stroke.2015; 46(11): 3213.     CrossRef
Medical Expenditure of National Health Insurance Attributable to Smoking among the Korean Population.
Sang Yi Lee, Sun Ha Jee, Ji Eun Yun, Su Young Kim, Jakyung Lee, Jonathan M Samet, Il Soon Kim
J Prev Med Public Health. 2007;40(3):227-232.
DOI: https://doi.org/10.3961/jpmph.2007.40.3.227
  • 4,813 View
  • 46 Download
  • 9 Crossref
AbstractAbstract PDF
OBJECTIVES
The purpose of this study was to determine the population-attributable risk (PAR) and estimate the total medical expenditure of the Korean National Health Insurance (KNHI) due to smoking. METHODS: We used data from the Korean Cancer Prevention Study of 1,178,138 Koreans aged 30 to 95. These data were available from 1992 to 2003 and covered a long-term follow-up period among the Korean population. RESULTS: The total medical expenditure of KNHI related to smoking increased by 27% from $324.9 million in 1999 to $413.7 million in 2003. By specific diseases, smokingattributable KNHI medical expenditure was the highest for lung cancer ($74.2 million), followed by stroke ($65.3 million), COPD ($50.1 million), CHD ($49 million) and stomach cancer ($30 million). A total of 1.3 million KNHI patients were suffering from smoking-related diseases in 2003. We predicted rises in total KNHI medical expenditure related to smoking to $675.1 million (63% increase compared with that of 2003) and in the total number of KNHI patients suffering from smoking-related diseases to about 2.6million (an approximate 100% increase compared with those in 2003) in 2015. CONCLUSIONS: We found a substantial economic burden related to the high smoking prevalence in South Korea.
Summary

Citations

Citations to this article as recorded by  
  • Estimates of the Prevalence, Intensity and the Number of Workers Exposed to Cigarette Smoking across Occupations and Industries in Korea
    Hyejung Jung, Dong-Hee Koh, Sangjun Choi, Ju-Hyun Park, Hwan-Cheol Kim, Sang-Gil Lee, Donguk Park
    Journal of Korean Medical Science.2019;[Epub]     CrossRef
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    Journal of the Korean Society for Research on Nicotine and Tobacco.2015; 6(1): 1.     CrossRef
  • The association between inhaled long-acting bronchodilators and less in-hospital care in newly-diagnosed COPD patients
    Jinhee Kim, Kyungjoo Kim, Yuri Kim, Kwang-Ha Yoo, Chin Kook Lee, Hyoung Kyu Yoon, Young Sam Kim, Young Bum Park, Jin Hwa Lee, Yeon-Mok Oh, Sang-Do Lee, Sei Won Lee
    Respiratory Medicine.2014; 108(1): 153.     CrossRef
  • Predictors of success at six-month follow-up at a public smoking cessation clinic in South Korea
    Soo-Young Bhang, Sam-Wook Choi, Joon-Ho Ahn, Kunwoo Kim, Hano Kim, Hye-Kyeong Park
    Asia-Pacific Psychiatry.2013; 5(3): 197.     CrossRef
  • Cost and effectiveness of the nationwide government-supported Smoking Cessation Clinics in the Republic of Korea
    Jin-Kyoung Oh, Min Kyung Lim, E Hwa Yun, Sang Hwa Shin, Eun Young Park, Eun-Cheol Park
    Tobacco Control.2013; 22(e1): e73.     CrossRef
  • Health and Economic Burden of Major Cancers Due to Smoking in Korea
    In-Hwan Oh, Seok-Jun Yoon, Tai-Young Yoon, Joong-Myung Choi, Bong-Keun Choe, Eun-Jung Kim, Young-Ae Kim, Hye-Young Seo, Yoon-Hyung Park
    Asian Pacific Journal of Cancer Prevention.2012; 13(4): 1525.     CrossRef
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    Seungji Lim, Woojin Chung, Hanjoong Kim, Sunmi Lee
    Health Policy.2010; 94(2): 101.     CrossRef
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Educational Differences in Health Care Utilization in the Last Year of Life among South Korean Cancer Patients.
Soo Young Choo, Sang Yi Lee, Chul Woung Kim, Su Young Kim, Tae Ho Yoon, Hai Rim Shin, Ok Ryun Moon
J Prev Med Public Health. 2007;40(1):36-44.
DOI: https://doi.org/10.3961/jpmph.2007.40.1.36
  • 4,963 View
  • 42 Download
  • 10 Crossref
AbstractAbstract PDF
OBJECTIVES
There have been few studies examining the differences in health care utilization across social classes during the last year of life. Therefore, in this study we analyzed the quantitative and qualitative differences in health care utilization among cancer patients across educational classes in their last year of life, and derived from it implications for policy. METHODS: To evaluate health care utilization by cancer patients in the last year of life, Death certificate data from 2004 were merged with National Health Insurance data (n=60,088). In order to use educational level as a social class index, we selected the individuals aged 40 and over as study subjects (n=57,484). We analyzed the differences in the medical expenditures, admission days, and rates of admission experience across educational classes descriptively. Multiple regression analysis was conducted to evaluate the association between medical expenditures and independent variables such as sex, age, education class, site of death and type of cancer. RESULTS: The upper educational class spent much more on medical expenditures in the last one year of life, particularly during the last month of life, than the lower educational class did. The ratio of monthly medical expenditures per capita between the college class and no education class was 2.5 in the last 6-12 months of life, but the ratio was 1.6 in the last 1 month. Also, the lower the educational class, the higher the proportion of medical expenditures during the last one month of life, compared to total medical expenditures in the last one year of life. The college educational class had a much higher rate of admission experiences in tertiary hospitals within Seoul than the other education classes did. CONCLUSIONS: This study shows that the lower educational classes had qualitative and quantitative disadvantages in utilizing health care services for cancer in the last year of life.
Summary

Citations

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    Jung-won Lim
    Social Work in Health Care.2015; 54(1): 47.     CrossRef
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    Hong-Jun Cho
    Journal of the Korean Medical Association.2013; 56(3): 184.     CrossRef
  • Inequalities in Medical Care Utilization by South Korean Cancer Patients According to Income: A Retrospective Cohort Study
    Tae Ho Yoon, Sang-Yi Lee, Chul-Woung Kim, Su Young Kim, Baek-Geun Jeong, Hyeung-Keun Park
    International Journal of Health Services.2011; 41(1): 51.     CrossRef
  • Factors Influencing Utilization of Medical Care Among Osteoarthritis Patients in Korea: Using 2005 Korean National Health and Nutrition Survey Data
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    Journal of Preventive Medicine and Public Health.2010; 43(6): 513.     CrossRef
Developing the Predictive Model for the Group at High Risk for Colon Cancer.
Ae Kyoung Lee, Sang Yi Lee, Il Soo Park, Su Young Kim, Tae Ho Yoon, Baek Geun Jeong
J Prev Med Public Health. 2006;39(5):438-446.
  • 2,168 View
  • 49 Download
AbstractAbstract PDF
OBJECTIVES
We developed the predictive model for the incidence of colon cancer by utilizing the health screening data of the National Health Insurance in Korea. We also explored the characteristics of the high risk group for colon cancer. METHODS: The predictive model was used to determine those people who have a high risk for colon cancer within 2 years of their NHI health screening, and we excluded the people who had already been treated for cancer or who were cancer patient. The study population is the insured of the NHI, aged 40 or over and they had undergone health screening from the year 2000 to 2004, according to NHI health screening formula. We performed logistic regression analysis and used SAS Enterprise Miner 4.1. RESULTS: This study shows that there exists a higher rate of colon cancer in males than females. Also, for the population in their 60s, the incidence rate of colon cancer is much higher by 5.36 times than that for those people in their 40s. Amongst the behavioral factors, heavy drinking is the most important determinant of the colon cancer incidence (7.39 times in males and 21.51 times in females). CONCLUSIONS: Our study confirms that the major influencing factors for the incidence of colon cancer are drinking, lack of exercise, a medical history of colon polypus and a family history of colon cancer. As a result, we can choose the group that is at a high risk for colon cancer and provide customized medical information and selective management services according to their characteristics.
Summary

JPMPH : Journal of Preventive Medicine and Public Health