• Asian Pacific Journal of Cancer Prevention
• /
• 제13권9호
• /
• pp.4501-4504
• /
• 2012

In recent decades, decreasing trends in esophageal cancer mortality have been observed across China. We here describe esophageal cancer mortality trends in Linzhou city, a high-incidence region of esophageal cancer in China, during 1988-2010 and make a esophageal cancer mortality projection in the period 2011-2020 using a Bayesian approach. Age standardized mortality rates were estimated by direct standardization to the World population structure in 1985. A Bayesian age-period-cohort (BAPC) analysis was carried out in order to investigate the effect of the age, period and birth cohort on esophageal cancer mortality in Linzhou during 1988-2010 and to estimate future trends for the period 2011-2020. Age-adjusted rates for men and women decreased from 1988 to 2005 and changed little thereafter. Risk increased from 30 years of age until the very elderly. Period effects showed little variation in risk throughout 1988-2010. In contrast, a cohort effect showed risk decreased greatly in later cohorts. Forecasting, based on BAPC modeling, resulted in a increasing burden of mortality and a decreasing age standardized mortality rate of esophageal cancer in Linzhou city. The decrease of esophageal cancer mortality risk since the 1930 cohort could be attributable to the improvements of socialeconomic environment and lifestyle. The standardized mortality rates of esophageal cancer should decrease continually. The effect of aging on the population could explain the increase in esophageal mortality projected for 2020.

• Asian Pacific Journal of Cancer Prevention
• /
• 제16권18호
• /
• pp.8589-8594
• /
• 2016

Background: Liver cancer is one of the most common causes of death in the world. In Korea, hepatitis B virus (HBV) is a major risk factor for liver cancer but infection rates have been declining since the implementation of the national vaccination program. In this study, we examined the secular trends in liver cancer mortality to distinguish the effects of age, time period, and birth cohort. Materials and Methods: Data for the annual number of liver cancer deaths in Korean adults (30 years and older) were obtained from the Korean Statistical Information Service for the period from 1984-2013. Joinpoint regression analysis was used to study the shapes of and to detect the changes in mortality trends. Also, an age-period-cohort model was designed to study the effect of each age, period, and birth cohort on liver cancer mortality. Results: For both men and women, the age-standardized mortality rate for liver cancer increased from 1984 to 1993 and decreased thereafter. The highest liver cancer mortality rate has shifted to an older age group in recent years. Within the same birth cohort group, the mortality rate of older age groups has been higher than in the younger age groups. Age-period-cohort analysis showed an association with a high mortality rate in the older age group and in recent years, whereas a decreasing mortality rate were observed in the younger birth cohort. Conclusions: This study confirmed a decreasing trend in liver cancer mortality among Korean men and women after 1993. The trends in mortality rate may be mainly attributed to cohort effects.

• 품질경영학회지
• /
• 제44권3호
• /
• pp.677-688
• /
• 2016

Purpose: In this study, we examine the effects of circulatory diseases mortality in South Korea 2005-2013 using the air pollution index, Methods: We cluster the region of high risk mortality by SaTScan$^{TM}$9.3.1 and compare this result with the regional distribution of air pollution. We use the Geographically Weighted Regression (GWR) to consider the spatial heterogeneity of data collected by administrative district in order to estimate the model. As GWR is spatial analysis techniques utilizing the spatial information, regression model estimated for each region on the assumption that regression coefficients are different by region. Results: As a result of estimating model of the collected air pollution index, circulatory diseases mortality data combined with the spatial information, GWR was found to solve the problem of spatial autocorrelation and increase the fit of the model than OLS regression model. Conclusion: GWR is used to select the air pollution affecting the disease each year, the K-means cluster analysis discover the characteristics of the distribution of air pollution by region.

• 대한간호학회지
• /
• 제33권8호
• /
• pp.1153-1160
• /
• 2003

Purpose. 1) To identify the time taken from symptom onset to the arrival at the hospital (pre-hospital delay time) and time taken from the arrival at the hospital to the initiation of the major treatment (in-hospital delay time) 2) to examine whether rapid treatment results in lower mortality. 3) to examine whether the pre- and in-hospital delay time can independently predict in-hospital mortality. Methods. A retrospective study with 586 consecutive AMI patients was conducted. Results. Pre-hospital delay time was 5.25 (SD=10.36), and in-hospital delay time was 1.10 (SD=1.00) hours for the thrombolytic therapy and 50.24 (SD=121.18) hours for the percutaneous transluminal coronary angio-plasty (PTCA). In-hospital mortality was the highest when the patients were treated between 4 to 48 hours after symptom onset using PTCA (p=.02), and when treated between 30 minutes and one hour after hospital arrival using thrombolytics (p=.01). Using a hierarchical logistic regression model, the pre- and in-hospital delay times did not predict the in-hospital mortality. Conclusion. Pre- and in-hospital delay times need to be decreased to meet the desirable therapeutic time window. Thrombolytics should be given within 30 minutes after arrival at the hospital, and PTCA should be initiated within 4 hours after symptom onset to minimize in-hospital mortality of AMI patients.

• 보건행정학회지
• /
• 제24권3호
• /
• pp.271-282
• /
• 2014

Background: Although the mortality rate in cancers has been decreased recently, it is still one of the leading causes of death in most of the countries. This study analyzed the relationship between surgery volume and in hospital mortality of cancer patients. The purpose of this study is to investigate the relationship in Korean healthcare environment and to provide information for the policy development in reducing cancer mortality. Methods: The study sample was the 20,517 cancer patients who underwent surgery and discharged during a month period between 2008-2011. The data were collected in Patient Survey by Korean Institute of Social Affairs. Logistic regression was used to analyse a comprehensive analytic model that includes a binary dependent variable indicating death discharge and independent variables such as surgery volume, organizational characteristics of hospitals, socio-economical characteristics of the patients, and severity of disease indicators. Results: In chi-square test, as the surgery volume increases, the in-hospitals mortality showed a downward trends. In regression analysis, the relationship between surgery volume and mortality showed significant negative associations in all types of cancer except for pancreatic cancer. Conclusion: In the absence of other information patients undergoing cancer surgery can reduce their risk of operative death by selecting a high-volume hospital. Therefore, policies to enhance centralization of cancer surgery services should be considered.

• 보건행정학회지
• /
• 제17권3호
• /
• pp.87-105
• /
• 2007

The purpose of this study was to analyze whether nonemergency, isolated coronary artery bypass graft (CABG) surgery for high- or low-risk patients biases the assessment of the risk-adjusted mortality rates of hospitals. This study used 2002 National Health Insurance claims data for tertiary hospitals in Korea. The study sample consisted of 1,959 patients from 23 tertiary hospitals. The risk-adjustment model used the patients' biological, admission, and comorbidity data identified in the claims. The subjects were classified into high- and low-risk groups based on predicted surgical risk. The crude mortality rates and risk-adjusted mortality rates for low-risk, high-risk, and all patients in a hospital were compared based on the rank and the four intervals defined by quartile. Also, the crude mortality rates of the three groups were compared with their 95% confidence intervals of predicted mortality rates. The C-statistic (0.83) and Hosmer-Lemeshow test ($X^2$=11.47, p=0.18) indicated that the risk-adjustment model performed well. Presenting crude mortality rates with their 95% confidence intervals of predicted rates showed higher agreements among the three groups than using the rank or intervals of mortality rates defined by quartile in the hospital performance assessment. The crude mortality rates for the low-risk patients in 21 of the 23 hospitals were located on the same side of their 95% confidence intervals compared to that for all patients. High-risk patients and all patients differed at only one hospital. In conclusion, the impact of risk selection by hospital on the assessment results was the smallest when comparing the crude inpatient mortality rates of CABG patients with the 95% confidence intervals of predicted mortality rates. Given the increasing importance of quality improvements in Korean health policy, it will be necessary to use the appropriate method of releasing the hospital performance data to the public to minimize any unwanted impact such as risk-based hospital selection.

• 응용통계연구
• /
• 제33권4호
• /
• pp.421-437
• /
• 2020

본 논문은 최근에 널리 사용되고 있는 R 프로그램으로 출산율, 사망률, 국제이동률을 예측하고 이들 결과를 Leslie 행렬에 대입해 인구추계 산출하는 방법을 소개한다. 특히 Kaneko (2003)가 제안한 출산율의 일반화로그감마모형, Li 등 (2013)의 사망률 LC-ER 모형, Ramsay와 Silverman (2005)가 제안한 국제이동률의 함수적데이터모형을 시현할 수 있도록 하였다. 최근 R로 구현된 대표적인 인구추계 패키지로 demography, bayesPop가 소개되고 있으나, 이는 Human Mortality Database (HMD), Human Fertility Database (HFD)에 업로드된 자료에 한에서만 분석이 가능하고 기타 데이터를 적용하기 위해서는 자료 변경과 수정이 요구된다. 특히 우리나라의 경우 HMD에 단기 간의 자료로만 제공되어 있어 이 패키기를 적용하기에는 한계점이 있다. 이에 본 논문은 이런 실정과 한국의 저출산, 고령화, 내국인, 외국인 국제이동률 상이패턴을 반영할 수 있는 R 프로그램을 소개하고, 2117년까지의 인구추계를 도출하였다.

• Journal of Preventive Medicine and Public Health
• /
• 제43권2호
• /
• pp.151-158
• /
• 2010

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.

• 디지털융복합연구
• /
• 제13권12호
• /
• pp.245-257
• /
• 2015

본 연구는 복합만성질환 입원환자를 대상으로 중증도 보정 사망 예측모형을 개발하고, 중증도 보정 사망비의 변이 요인을 규명하여 변이를 줄일 수 있는 방안을 제시하고자 하였다. 이를 위해 퇴원손상심층조사 자료 2008년부터 2010년까지 자료를 수집하고 주진단이 만성질환이면서 주진단을 포함하여 2개 이상의 만성질환을 보유한 30세 이상의 복합만성질환 입원환자 110,700건을 최종 연구대상으로 선정하였다. 예측 모형 개발 시 데이터마이닝 기법(로지스틱회귀분석, 의사결정나무, 신경망 기법)을 적용하였다. 본 연구에서는 Elixhauser comorbidity index 동반상병 보정지수를 이용하여 의사결정나무분석으로 복합만성질환 입원환자의 중증도 보정 사망 예측모형을 개발하였다. 복합만성질환 입원환자의 의료기관 중증도 보정 사망비(HSMR)를 산출 한 결과 진료비 지불방법별, 병상규모별, 의료기관소재지별로 통계적으로 유의한 차이가 있는 것으로 나타났다. 상기 분석결과를 바탕으로 국가적 차원에서 복합만성질환 입원환자의 사망비를 효율적으로 관리하여 의료의 질 향상과 증가하는 의료비 부담 감소를 위해 지속적인 관심과 노력을 기울여야 할 것이다.

• Communications for Statistical Applications and Methods
• /
• 제19권5호
• /
• pp.705-720
• /
• 2012

In this paper, we introduce a hierarchical Bayesian model to simultaneously estimate the thresholds of each 6 cities. It was noted in the literature there was a dramatic increases in the number of deaths if the mean temperature passes a certain value (that we call a threshold). We estimate the difference of mortality before and after the threshold. For the hierarchical Bayesian analysis, some proper prior distribution of parameters and hyper-parameters are assumed. By combining the Gibbs and Metropolis-Hastings algorithm, we constructed a Markov chain Monte Carlo algorithm and the posterior inference was based on the posterior sample. The analysis shows that the estimates of the threshold are located at $25^{\circ}C{\sim}29^{\circ}C$ and the mortality around the threshold changes from -1% to 2~13%.