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Ji Hyun Kim 2 Articles
Comparisons of Health Inequalities in Small Areas with Using the Standardized Mortality Ratios in Korea.
Ji Hyun Kim, Tae Ho Yoon
J Prev Med Public Health. 2008;41(5):300-306.
DOI: https://doi.org/10.3961/jpmph.2008.41.5.300
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  • 91 Download
  • 12 Crossref
AbstractAbstract PDF
OBJECTIVES
This study was performed to compare the standardized mortality ratios among different small areas and to explore the usefulness of standardized mortality ratios in South Korea. METHODS: To calculate the standardized mortality ratio (SMR), we obtained the national deaths certificate data (2004-2006) and national registration population data (2003-2006), and these were provided by the National Statistical Office. The small areas (Eup.Myoun.Dong) were based on the subdivisions of counties. Among the 3,580 small areas classified by the National Statistical Office, 3,571 areas were included in this study. The basic statistics and decile distributions of the SMRs for all the regional levels were calculated, and the small area maps were also produced for some selected regions. To evaluate the precision of SMR, we calculated the 95% confidence intervals of the SMR in selected small areas. RESULTS: The mean and the standard deviation of the SMRs among all small areas were 100.8 and 17.0, respectively. The range was 30.6-211.7 and the inter-quartile range was 20.7. Seoul metropolitan city displayed the lowest mean SMR among 16 regions in South Korea, and 34.6 percent of the small area SMRs belonged to the first decile(the lowest group). On the contrary, the mean SMR of Gyeongsangnam province was highest, and 26.1 percent of the small area SMRs belonged to the tenth decile(the highest group). In some areas, the precision of the SMR, which was calculated by the 95% confidence intervals, remained questionable, yet it was quite stable for almost areas. CONCLUSIONS: The standardized mortality ratios can be useful for allocating health resources at the small area level in Korea.
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  • Comparison of three small-area mortality metrics according to urbanity in Korea: the standardized mortality ratio, comparative mortality figure, and life expectancy
    Ikhan Kim, Hwa-Kyung Lim, Hee-Yeon Kang, Young-Ho Khang
    Population Health Metrics.2020;[Epub]     CrossRef
  • Life Expectancy in Areas around Subway Stations in the Seoul Metropolitan Area in Korea, 2008–2017
    Ikhan Kim, Hee-Yeon Kang, Young-Ho Khang
    Journal of Korean Medical Science.2020;[Epub]     CrossRef
  • Use of the National Health Information Database for Estimating Town-Level Mortality in Korea: Comparison with the National Administrative Data, 2014–2017
    Ikhan Kim, Youngs Chang, Hee-Yeon Kang, Yeon-Yong Kim, Jong Heon Park, Young-Ho Khang
    Journal of Korean Medical Science.2019;[Epub]     CrossRef
  • Trends in health-related behaviors of Korean adults: study based on data from the 2008 - 2014 Community Health Surveys
    Yang Wha Kang, Yun Sil Ko, Keon Yeop Kim, Changhyun Sung, Dong Han Lee, Eunkyeong Jeong
    Epidemiology and Health.2015; 37: e2015042.     CrossRef
  • Changes and determinants affecting on geographic variations in health behavior, prevalence of hypertension and diabetes in Korean
    Yoo-Mi Kim, Sung-Hong Kang
    Journal of Digital Convergence.2015; 13(11): 241.     CrossRef
  • Factors Affecting Diabetic Screening Behavior of Korean Adults: A Multilevel Analysis
    Hyeongsu Kim, Minjung Lee, Haejoon Kim, Kunsei Lee, Sounghoon Chang, Vitna Kim, Jun Pyo Myong, Soyoun Jeon
    Asian Nursing Research.2013; 7(2): 67.     CrossRef
  • Socioeconomic inequalities in health status in Korea
    Kyunghee Jung-Choi, Yu-Mi Kim
    Journal of the Korean Medical Association.2013; 56(3): 167.     CrossRef
  • A Comparison of Community Health Status by Region and an Investigation of related Factors using Community Health Indicators
    Eunok Park
    Journal of Korean Academy of Community Health Nursing.2012; 23(1): 31.     CrossRef
  • 〈 Field Action Report 〉 The Strategies to Address Regional Health Inequalities in Gyeongsangnam-Do: Health Plus Happiness Plus Projects
    Baek-Geun Jeong, Jang-Rak Kim, Yune-Sik Kang, Ki-Soo Park, Jin-Hyang Lee, Sun-Rae Jo, Gi-Deok Seo, Sang-Jun Joo, Eun-Suk Oh, Seung-Jin Kim, Seong-Jin Jo, Seung-Mi Kim, Dong-Mun Yeum, Mi-Young Sim
    Journal of agricultural medicine and community health.2012; 37(1): 36.     CrossRef
  • Adherence to Physical Activity Among Older Adults Using a Geographic Information System: Korean National Health and Nutrition Examinations Survey IV
    Hye-A Yeom, Dukyoo Jung, Mona Choi
    Asian Nursing Research.2011; 5(2): 118.     CrossRef
  • Assessment of Applicability of Standardized Rates for Health State Comparison Among Areas: 2008 Community Health Survey
    Geun-Yong Kwon, Do-Sang Lim, Eun-Ja Park, Ji-Sun Jung, Ki-Won Kang, Yun-A Kim, Ho Kim, Sung-Il Cho
    Journal of Preventive Medicine and Public Health.2010; 43(2): 174.     CrossRef
  • Development of Composite Deprivation Index for Korea: The Correlation with Standardized Mortality Ratio
    Hosung Shin, Suehyung Lee, Jang Min Chu
    Journal of Preventive Medicine and Public Health.2009; 42(6): 392.     CrossRef
Physician Factors Associated with the Blood Pressure Control among Hypertensive Patients.
So Young Kim, In Sook Cho, Jae Ho Lee, Ji Hyun Kim, Eun Jung Lee, Jong Hyock Park, Jin Seok Lee, Yoon Kim
J Prev Med Public Health. 2007;40(6):487-494.
DOI: https://doi.org/10.3961/jpmph.2007.40.6.487
  • 4,755 View
  • 42 Download
  • 6 Crossref
AbstractAbstract PDF
OBJECTIVES
Little is known about the physician-related factors that are associated with the management of hypertension. The purpose of this study was to determine the physician-related factors associated with blood pressure control in hypertensive patients. METHODS: We surveyed 154 physicians at 117 public health (subhealth) centers in Gyeonggi-do. Forty-one physicians completed the survey (response rates: 26.6%) and 31 physicians were finally included as the study subjects. Using the information obtained from the selfreported survey, we measured the physician-related factors associated with hypertension control, including their perception of hypertension, prescription patterns (combination prescription rates, specific antihypertensives prescription rates among patients with diabetes mellitus), and sociodemographic factors. We then collected data on blood pressure and medication use in patients seen by these physicians from the health center's information system. We compared the physicians' perceived hypertension control rates with the actual rates, and then evaluated the rate of high overestimation (overestimation by more than 25% of the median degree of hypertension control rate overestimation) among the physicians. The physicians' antihypertensive prescription patterns were also evaluated. Multiple logistic regression analysis was used to evaluate the independent association between hypertension control and physicianrelated factors. RESULTS: The physicians tended to overestimate the proportion of their patients with controlled blood pressure (79.5% perceived vs. 57.8% actual). The percentage of physicians with high overestimation was 35.5% (11 physicians). The physicians with lower control rates were more likely to highly overestimate their patients' control rates. Physicians with below-median actual control rates tended to prescribe fewer combination treatments for patients with uncontrolled blood pressure and angiotensinconverting enzyme inhibitors or fewer angiotensin receptor blockers for patients with diabetes mellitus. The rate of high overestimation by physicians was 1.31 times higher in patients with uncontrolled blood pressure than in patients with other conditions (OR=1.31, 95% CI: 1.17-1.48). CONCLUSIONS: Physicians have a tendency to overestimate the rates of hypertension control in their patients. Because physicians have a direct role in treatment outcomes, physicians' overestimation about hypertension management contributes to inadequate blood pressure control. Thus, interventions for improving physician' awareness regarding the management of patients with hypertension are needed.
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Citations

Citations to this article as recorded by  
  • Clinical Pharmacist Team-Based Care in a Safety Net Medical Home: Facilitators and Barriers to Chronic Care Management
    Eboni G. Price-Haywood, Sarah Amering, Qingyang Luo, John J. Lefante
    Population Health Management.2017; 20(2): 123.     CrossRef
  • Psychometric Properties of a Short Self-Reported Measure of Medication Adherence Among Patients With Hypertension Treated in a Busy Clinical Setting in Korea
    Jeung-Hee Kim, Weon-Young Lee, Yeon-Pyo Hong, Wang-Seong Ryu, Kwang Je Lee, Wang-Soo Lee, Donald E. Morisky
    Journal of Epidemiology.2014; 24(2): 132.     CrossRef
  • Health Incentive Program and Hypertensive Patients' Blood Pressure Control
    Kyunghee Kang
    Journal of the Korea Academia-Industrial cooperation Society.2013; 14(9): 4388.     CrossRef
  • Comparison of agreement between different measures of blood pressure in normotensive females
    Ülkü Yapucu Güneş
    Applied Nursing Research.2010; 23(3): 159.     CrossRef
  • How to improve DAS28 use in daily clinical practice?--a pilot study of a nurse-led intervention
    L. T. C. van Hulst, M. C. W. Creemers, J. Fransen, L. C. Li, R. Grol, M. E. J. L. Hulscher, P. L. C. M. van Riel
    Rheumatology.2010; 49(4): 741.     CrossRef
  • The Effect of Re-building of Public Health Facilities on the Hypertension Control in the Rural Area
    Sung-A Chun, Baeg-Ju Na, Chul-Woung Kim, Moo-Sik Lee
    Journal of agricultural medicine and community health.2008; 33(1): 37.     CrossRef

JPMPH : Journal of Preventive Medicine and Public Health