• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1531-1538
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• 2014

The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demon-strated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.

• Korean Journal of Health Education and Promotion
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• v.24 no.5
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• pp.39-54
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• 2007

This study attempts to provide fundamental information for a health policy and health services by looking at the trends and types of the mortality rates in Korea and Japan. In this study, data of the death statistics of Korea and Japan over the 21-year period from 1983 to 2003 are analyzed. Mortality data are standardized ${\times}100,000$ to the 2003 Japan population, according to the direct method. In 2001/2003, the ranking of major causes of death in Korea and Japan has been greatly changed. In Korea, mortality rates from malignant neoplasms, diabetes mellitus, renal failure, falls and suicide have increased. In Japan, the mortality rates from pneumonia increase more than those from diabetes mellitus. In 2001/2003, the proportions of the mortality rates from chronic diseases are higher than those from acute diseases. In the Korean health promotion policy "Health Promotion 2020", a more intensive goal management is needed.

• Quality Improvement in Health Care
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• v.10 no.2
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• pp.216-231
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• 2003

Objectives: To develop a model that predicts a death probability of acute myocardial infarction(AMI) patient, and to evaluate a performance of hospital services using the developed model. Methods: Medical records of 861 AMI patients in 7 general hospitals during 1996 and 1997 were reviewed by two trained nurses. Variables studied were risk factors which were measured in terms of severity measures. A risk model was developed by using the logistic regression, and its performance was evaluated using cross-validation and bootstrap techniques. The statistical prediction capability of the model was assessed by using c-statistic, $R^2$ as well as Hosmer-Lemeshow statistic. The model performance was also evaluated using severity-adjusted mortalities of hospitals. Results: Variables included in the model building are age, sex, ejection fraction, systolic BP, congestive heart failure at admission, cardiac arrest, EKG ischemia, arrhythmia, left anterior descending artery occlusion, verbal response within 48 hours after admission, acute neurological change within 48 hours after admission, and 3 interaction terms. The c statistics and $R^2$ were 0.887 and 0.2676. The Hosmer-Lemeshow statistic was 6.3355 (p-value=0.6067). Among 7 hospitals evaluated by the model, two hospitals showed significantly higher mortality rates, while other two hospitals had significantly lower mortality rates, than the average mortality rate of all hospitals. The remaining hospitals did not show any significant difference. Conclusion: The comparison of the qualities of hospital service using risk-adjusted mortality rates indicated significant difference among them. We therefore conclude that risk-adjusted mortality rate of AMI patients can be used as an indicator for evaluating hospital performance in Korea.

• Korean Journal of Health Education and Promotion
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• v.20 no.4
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• pp.51-65
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• 2003

Objectives： To examine the regional mortality differences in The Republic of Korea according to geographic location. Methods： All 232 administrative districts of the Republic of Korea in 1998 were studied according to their geographic locations by dividing each district into three categories； "metropolis," "urban," and "rural". Crude mortality rates for doth sexes from total deaths as well as the three major causes of death in Korea (cardiovascular disease, cancer, and external causes) were calculated with raw data from the "1998 report on the causes of death statistics" and resident registration data. Standardized mortality ratios (SMR) were calculated using the indirect standardization method. Poisson regression analyses were performed to examine the effects of geographic locations on the risk of death. To correct for the socioeconomic differences of each region, the percentage of old ($\geq$ 65 years old) population, the number of privately owned cars per 100 population, and per capita manufacturing production industries were included in the model. Results： Most SMRs were the lowest in the metropolis and the highest in the rural areas. These differences were more prominent in men and in deaths from external causes. In deaths from cancer in women, the rural region showed the lowest SMR. In Poisson regression analysis after correcting for regional socioeconomic differences, the risk of death from all causes significantly increased in both urban (OR＝1.111) and rural (OR＝1.100) regions, except for rural women, compared to the metropolis region. In men, the rural region showed higher risk (OR＝1.180) than the urban region (OR＝1.l51). For cardiovascular disease and cancer, significant differences were not found between geographic locations, except in urban women for cardiovascular disease (OR＝1.151) and in rural women for cancer (OR＝0.887), compared to metropolis women. In deaths from external causes, the risk ratios significantly increased in both urban and rural regions and an increasing tendency from the metropolis to the rural region was clearly observed in both sexes. Conclusions： Regional mortality differences according to geographic location exist in The Republic of Korea and further research and policy approaches to reduce these differences are needed. to reduce these differences are needed.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.1-12
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• 2020

During the COVID-19 pandemic, most of the western countries with advanced medical technology failed to contain coronavirus. This fact triggered our research question of what factors influence the clinical outcomes like infection rates and case mortality rates. This study aims to identify the determinants of COVID-19 related infection rates and case mortality rates. We considered three sets of independent variables: 1) socio-demographic characteristics; 2) cultural characteristics; 3) healthcare system characteristics. For the analysis, we created an international dataset from diverse sources like World Bank, Worldometers, Hofstede Insight, GHS index etc. The COVID-19 related statistics were retrieved from Aug. 1. Total cases are from 95 countries. We used hierarchical regression method to examine the linear relationship among variables. We found that obesity, uncertainty avoidance, hospital beds per 1,000 made a significant influence on the standardized COVID-19 infection rates. The countries with higher BMI score or higher uncertainty avoidance showed higher infection rates. The standardized COVID-19 infection rates were inversely related to hospital beds per 1,000. In the analysis on the standardized COVID-19 case mortality rates, we found that two cultural characteristics(e.g., individualism, uncertainty avoidance) showed statistically significant influence on the case mortality rates. The healthcare system characteristics did not show any statistically significant relationship with the case mortality rates. The cultural characteristics turn out to be significant factors influencing the clinical outcomes during COVID-19 pandemic. The results imply that the persuasive communication is important to trigger the public commitment to follow preventive measures. The strategy to keep the hospital surge capacity needs to be developed.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6681-6686
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• 2013

Background: Fatal adverse events (FAEs) have been reported with sorafenib, a vascular endothelial growth factor receptor kinase inhibitor (VEGFR TKI). We here performed an up-to-date and detailed meta-analysis to determine the overall risk of FAEs associated with sorafenib. Methods: Databases, including PubMed, Embase and Web of Science, and abstracts presented at the American Society of Clinical Oncology annual meetings were searched to identify relevant studies. Eligible studies included randomized controlled trials evaluating sorafenib effects in patients with all malignancies. Summary incidence rates, relative risks (RRs), and 95% confidence intervals (CIs) were calculated for FAEs. In addition, subgroup analyses were performed according to tumor type and therapy regimen. Results: 13 trials recruiting 5,546 patients were included in our analysis. The overall incidence of FAEs with sorafenib was 1.99% (95%CI, 0.98-4.02%). Patients treated with sorafenib had a significantly increased risk of FAEs compared with patients treated with control medication, with an RR of 1.77 (95%CI 1.25-2.52, P=0.001). Risk varied with tumour type, but appeared independent of therapy regimen. A significantly increased risk of FAEs was observed in patients with lung cancer (RR 2.26; 95% CI 1.03-4.99; P= 0.043) and renal cancer (RR 1.84; 95% CI 1.15-2.94; P= 0.011). The most common causes of FAEs were hemorrhage (8.6%) and thrombus or embolism (4.9%). Conclusions: It is important for health care practitioners to be aware of the risks of FAEs associated with sorafenib, especially in patients with renal and lung cancer.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.55-62
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• 2021

Objectives: After heart disease, brain stroke (BS) is the second most common cause of death worldwide, underscoring the importance of understanding preventable and treatable risk factors for the outcomes of BS. This study aimed to model the survival of patients with BS in the presence of competing risks. Methods: This longitudinal study was conducted on 332 patients with a definitive diagnosis of BS. Demographic characteristics and risk factors were collected by a validated checklist. Patients' mortality status was investigated by telephone follow-up to identify deaths that may be have been caused by stroke or other factors (heart disease, diabetes, high cholesterol, etc.). Data were analyzed by the Lunn-McNeil approach at alpha=0.1. Results: Older age at diagnosis (59-68 years: adjusted hazard ratio [aHR], 2.19; 90% confidence interval [CI], 1.38 to 3.48; 69-75 years: aHR, 5.04; 90% CI, 3.25 to 7.80; ≥76 years: aHR, 5.30; 90% CI, 3.40 to 8.44), having heart disease (aHR, 1.65; 90% CI, 1.23 to 2.23), oral contraceptive pill use (women only) (aHR, 0.44; 90% CI, 0.24 to 0.78) and ischemic stroke (aHR, 0.52; 90% CI, 0.36 to 0.74) were directly related to death from BS. Older age at diagnosis (59-68 years: aHR, 21.42; 90% CI, 3.52 to 130.39; 75-69 years: aHR, 16.48; 90% CI, 2.75 to 98.69; ≥76 years: aHR, 26.03; 90% CI, 4.06 to 166.93) and rural residence (aHR, 2.30; 90% CI, 1.15 to 4.60) were directly related to death from other causes. Significant risk factors were found for both causes of death. Conclusions: BS-specific and non-BS-specific mortality had different risk factors. These findings could be utilized to prescribe optimal and specific treatment.

• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.703-719
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• 2015

We propose an extension of the Lee and Jho (2015) mean reverting the two factor mortality model by incorporating a period-specific cohort effect. We found that the consideration of cohort effect improves the mortality fit of Korea male data above age 65. Parameters are estimated by the weighted least squares method and Metropolis algorithm. We also emphasize that the cohort effect is necessary to choose the base survival index to calculate longevity bond issue price. A key contribution of the article is the proposal and development of a method to calculate the longevity bond price to hedge the longevity risk exposed to Korea National Pension Services.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.45 no.5
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• pp.499-506
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• 2012

We estimated the population size and fishing mortality of Pacific cod Gadus macrocephalus during the spawning season in waters off Woipo, Geoje Island, Korea, using a mark-recapture method. We marked and released 51 cod>50 cm in total length; six were recaptured by local fishermen during the period from December 15 to 31, 2009. The estimated population size was ca. 180,000 and the fishing mortality of the exploitable cod was 26%. Although we could assume a closed population due to the short survey period, we evaluated the uncertainty in the estimates by applying bootstrap resampling because the sample size was small. The estimated 95% confidence interval was 94,000-568,000 for the population size and 8-49% for fishing mortality. Our study demonstrated that the application of mark-recapture methods and bootstrap resampling can be useful in stock assessment for fisheries management in Korea, but requires a larger sample size, spatially extensive coverage, and sophisticated mark-recapture models based on a refined sampling design for reliable stock assessment and biological reference points in sustainable cod management.

• Journal of agricultural medicine and community health
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• v.34 no.1
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• pp.1-12
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• 2009

Objectives: The aim of this study was to characterize the community health indicators affecting standardized mortality rate of cerebrovascular diseases(CVD) and to identify the relationship between CVD mortality and community health indicators in Gangwon-do. Methods: The community health indicators included material deprivation index, medical resource, rates of road pavement and local tax. CVD mortality and the material deprivation index were calculated in the registered death data and the 2000 census which were obtained from the Korean National Statistics Office. The community health indicators were measured using 2001 statistical year book of Ganwon-do. Data were analyzed by using Excel 2003, SAS 9.1. CVD mortality and material deprivation index were visualized by Arcview 9.1. Results: CVD mortality varied by region and sex in Gangwon-do. The highest CVD mortality in male and female were noted at Goseong-gun, the lowest CVD mortality in male was at Yangyang-gun as it of female at Pyeongchang-gun. In Taebaek city where material deprivation index was also the highest; in Pyeongchang-gun was the lowest. Also the higher material deprivation index in some regions was the higher CVD mortality was. CVD mortality was not related with community health indicators. Conclusions: The results showed the regional difference of mortality of CVD among counties and cities in Gangwon-do. It is recommended that other community health indicators besides material deprivation index, road pavement rate, medical resources and local tax affecting CVD mortality need to be considered to improve the preventive strategies.